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Biomarker Characterization Centers

The Biomaker Characterization Centers (BCCs) identify, specify, and make distinctive new biomarkers or refine existing biomarkers. There are two kinds of BCCs:

Breast

Group

Site ID Investigator Site Name PI Type Member Type
812 Paulovich, Amanda, M.D., Ph.D. Fred Hutchinson Cancer Center Contact PI BCC, BDL
1048 Hoofnagle, Andrew, M.D., Ph.D. University of Washington MPI BCC, BRL
1051 Wang, Pei, Ph.D. Icahn School of Medicine at Mount Sinai MPI BCC

We propose to develop a blood-based test whose indicated use is to complement mammography in the early detection of breast cancers. Although mammography saves lives through early detection, it is imperfect. Approximately one in seven breast cancers goes undetected despite screening mammography, and interval cancers that manifest within a year of a normal mammogram remain a vexing problem, especially (although not exclusively) for the >27 million women in the United States with heterogeneously or extremely dense breasts at high risk for interval cancers. We propose to develop a blood test that could be used as an adjunct to mammography to improve early detection by improving sensitivity and/or specificity of mammography. Using a novel biomarker discovery approach leveraging human-in-mouse breast cancer patient-derived xenograft models and state-of-the-art mass spectrometry methods, we prioritized 162 candidate breast cancer protein biomarkers for validation studies. Our BCC will perform EDRN Phase 2 biomarker validation studies of our prioritized 162 candidate plasma protein biomarkers of breast cancer. We have an experienced multidisciplinary team (including two junior investigators) with a strong track record of productive collaboration and representing expertise in clinical oncology, cancer biomarkers, pathology, CLIA/CAP/GLP assays, epidemiology, radiology/breast imaging, cancer screening, ‘omics data generation, and biostatistics. Our team includes 2 industry partners, encompasses 3 CLIA laboratories, and can provide expertise and access to multiple quantitative platforms in a CLIA/CAP/GLP environment to support EDRN Network Collaborations for biomarker validation studies with other BCCs. The Biomarker Development Laboratory will contribute to the biomarker validation studies by: (i) developing qualified reagents & methods for quantifying 162 candidate protein biomarkers, (ii) procuring plasma biospecimens (compliant with EDRN PRoBE study design) for phase 2 biomarker validation studies, (iii) delivering plasma aliquots to our BRL CLIA labs in a blinded fashion, and (iv) analyzing EDRN phase 2 validation data generated by the BRL, providing statistical, epidemiological, and breast imaging expertise to set and evaluate performance metrics to ensure biomarkers are adequate to provide clinical utility for early detection. The Biomarker Reference Laboratory will contribute to the proposed validation studies by: (i) validating a CLIAcompliant standard operating procedure for an immuno-MRM assay to quantify up to 162 candidate protein biomarkers of early-stage breast cancer that will serve as the basis for our biomarker validation studies, (ii) performing phase 2 biomarker validation studies, and (iii) providing reference laboratory support for the EDRN network (e.g., mass spectrometric analyses, flow cytometry, NextGen sequencing and ELISA assays. The Administrative Core will support all aspects of the BCC, including managing all administrative and project management aspects of the BCC as well as managing all center logistics and communication. Contact PD/PI: Paulovich, Amanda G Project Summary/

Colon and Esophagus

Group

Site ID Investigator Site Name PI Type Member Type
160 Grady, William, M.D. Fred Hutchinson Cancer Center Contact PI BCC, BDL
1016 Yeung, Cecilia, M.D. Fred Hutch Cancer Center MPI BCC, BRL

Gastrointestinal (GI) cancers are a major cause of mortality and morbidity in the U.S. and their treatment
uses a substantial proportion of healthcare resources. Of the GI cancers, colorectal cancer (CRC) and
esophageal cancer (EAC) account for a majority of the cancer related deaths, and both are preventable by
screening and surveillance. The current screening tests are suboptimal and have variable success.
A major goal of CRC screening tests is to identify advanced tubular and serrated adenomas, which are
high-risk for becoming CRC, as well as early stage CRC. The risk for CRC is variable with some people being
at high risk because of family histories of CRC, hereditary cancer syndromes, or a personal history of adenomas.
High risk people are placed on aggressive colonoscopy based surveillance programs and low-risk people are
placed on minimal surveillance programs. Unfortunately, our current system for identifying high and low CRC
risk is suboptimal resulting in under and over surveillance and preventable interval CRCs. Better risk markers
for CRC to are needed to prevent interval CRCs and improve the overall effectiveness of CRC screening.
Analogous to CRC, EAC arises from a precancerous condition of the esophagus called Barretts
esophagus (BE), which is a specialized intestinal metaplasia of the esophagus and the highest risk factor for
EAC. It is present in 5% of the US population. BE progresses to EAC through successive histologic steps of
low grade dysplasia (LGD), high grade dysplasia (HGD) and then EAC. Screening and surveillance for BE is
recommended using serial upper endoscopy, which is controversial in its effectiveness for preventing deaths
from EAC. This is in part because, as with CRC, BE patients have variable risk of EAC and are placed on highrisk
and low-risk screening programs. However, the current system for assigning risk is not accurate and the
current screening test is expensive. More cost effective and accurate EAC and HGD screening/surveillance
assays and accurate BE risk biomarkers are needed.
We propose to develop an EDRN BCC that is integrated into the EDRN consortium and, through
collaborations within and outside the EDRN, will develop effective GI cancer screening biomarkers. We propose
to identify, validate, and develop accurate CLIA compliant risk biomarkers for CRC and for EAC in order to
prevent EAC and CRC missed under current screening protocols. Moreover, the accurate risk stratification of
patients for CRC and EAC will reduce the financial impact of current CRC and EAC prevention programs. We
also propose to identify and validate accurate CLIA compliant early detection markers for HGD and early stage
EAC that can be used in an inexpensive, non-endoscopic surveillance test.

Lung

Group

Site ID Investigator Site Name PI Type Member Type
813 Herman, James, M.D. University of Pittsburgh School of Medicine Contact PI BCC, BDL, BRL
201 Stass, Sanford, M.D. University of Maryland School of Medicine MPI BCC, BRL
818 Wang, Tza-Huei (Jeff), Ph.D. Johns Hopkins Whiting School of Engineering MPI BCC, BDL

This proposal for a Biomarker Characterization Center (BCC) for the Early Detection Research
Network (EDRN) seeks to improve the management of lung cancer through detection of cancerspecific
DNA methylation. This effort includes a Biomarker Development Laboratory (BDL) which
will optimize the methylation detection methods, implementation of these methods for clinical use
through a Biomarker Reference Laboratory (BRL) with a longstanding record of molecular testing
in a clinical setting, and an Administrative Core facilitating the interactions between the BDL and
BRL, and with other EDRN investigators and the NCI. Previous work by the applicants has
demonstrated the potential of DNA methylation detection for cancer diagnostics, and they have
developed extremely sensitive assays for the detection of hypermethylated DNA sequences and
optimized the isolation and processing of circulating cell-free DNA from tumors for these novel
assays. The approach has been used to detect circulating cancer-specific DNA methylation
changes for the early diagnosis of lung cancer in patients with screen-detected pulmonary
nodules. Although sensitivity and specificity of the assay are promising, additional improvements
in the performance are required for implementation of this approach in the setting of cancer
screening. In this BCC, detection of cancer-specific DNA methylation changes in the plasma will
be further improved, and new approaches developed and implemented to address the challenges
of ultrasensitive detection of DNA methylation in the blood. In addition, we will assess the potential
of these methods to detect other common and lethal malignancies. Our bioinformatic analysis of
DNA methylation from The Cancer Genome Atlas (TCGA) has identified novel highly frequent
cancer-specific methylation events common to all cancers, including lung cancer, that will be
developed into universal cancer detection assays. The use of TCGA data has also resulted in the
identification of other methylation alterations that allow determination of the origin (organ site) of
this cancer-specific signal. The combination of optimal sample processing, ultrasensitive
methylation detection, developed with universal cancer and histology specific loci detection, will
allow improved lung cancer early detection in the setting of CT screening and management of
detection of other cancer-specific DNA methylation from blood.

Group

Site ID Investigator Site Name PI Type Member Type
594 Lenburg, Marc, Ph.D. Boston University Contact PI BCC, BDL
1014 Beane-Ebel, Jennifer E., Ph.D. Boston University School of Medicine MPI BCC, BDL
1033 Bulman, William, Veracyte Inc Co-Investigator BCC, BRL
241 Dubinett, Steve, M.D. University of California Los Angeles MPI BCC, BDL
1015 Hsu, William, Ph.D. UCLA School of Engineering MPI BCC, BDL, BRL
1035 Pagano, Paul, Ph.D. LungLife AI, Inc Co-Investigator BCC, BRL
1034 Palazzolo, Michael, M.D., Ph.D. University of California, Los Angeles Co-Investigator BCC, BRL

Screen and incidentally detected intermediate risk indeterminant pulmonary nodules (IPN) represent a clinical
dilemma for which there is little consensus about appropriate follow up due to a lack of sensitive and specific
approaches for the detection of lung cancer absent invasive tissue sampling, and concerns about costs and
harms from invasive tissue sampling in this large clinical population. Minimally invasive approaches that could
accurately reclassify individuals from the intermediate risk group (5-65% risk of malignancy) to either low (< 5%)
or high (>65%) risk would reduce uncertainty and transform the diagnostic workup of intermediate risk IPN.
Developing, evaluating, standardizing, and validating such minimally invasive biomarkers so that they are ready
for clinical use is the goal of the proposed BU-UCLA Lung Cancer Biomarker Characterization Center (BCC). In
previous EDRN-funded work we established lung-cancer associated gene expression patterns in nasal
epithelium collected with a swab from the inferior turbinate as a lung cancer biomarker. A test based on this
innovative approach to lung cancer detection is being launched for clinical use as a CLIA LDT by our long-time
collaborator Veracyte, Inc., which is participating in this BCC. We will evaluate the nasal biomarker for lung
cancer in the setting of intermediate risk IPN. To further improve the ability to clinically discriminate benign from
malignant intermediate risk IPN, the BU-UCLA Lung Cancer Biomarker Discovery Lab embedded within the BCC
will develop and test lung cancer detection approaches that incorporate detection of circulating tumor cells (CTC)
using a CLIA LDT assay from our collaborator LungLife AI, Inc. as well as blood based immune biomarkers,
advanced imaging biomarkers, and refined nasal gene expression biomarkers. We will additionally determine if
longitudinal biomarker assessment improves lung cancer detection over cross-sectional measurements.
Promising assays will be refined, standardized, and validated by the BU-UCLA Lung Cancer Biomarker
Reference Lab embedded within the BCC to advance them toward clinical adoption. These studies are enabled
by biospecimens and imaging data that are being prospectively collected from diverse populations of patients
undergoing workup for intermediate risk IPN in several large-scale ongoing clinical studies including VA LPOP,
DECAMP 1-Plus, and UCLA IDx; lung cancer research programs at UCLA and Lahey; and our EDRN
collaborators at Nashville VA and Vanderbilt. The BU-UCLA Lung Cancer BCC Team has the required multidisciplinary
expertise in lung cancer, translational and clinical pulmonary medicine, biomarker discovery, clinical
assay development, biostatistics, clinical epidemiology, pathology, imaging, artificial intelligence, biological
sciences, bioinformatics, genomics, and complex scientific program management to accomplish these goals. An
Administrative Core embedded within the BCC will ensure that the BCC delivers on its aim to substantially
advance novel lung cancer biomarkers from discovery to clinical application and make significant contributions
to the Early Detection Research Network.

Group

Site ID Investigator Site Name PI Type Member Type
1049 Segal, Leopoldo, M.D. New York University Grossman School of Medicine Contact PI BCC, BDL, BRL
176 Pass, Harvey Ira, M.D. New York University School of Medicine MPI BCC, BDL, BRL

Lung cancer remains the leading cause of all cancer mortality. Improved imaging techniques enable the detection of lung cancer at earlier stages, yet a large number of patients with non-malignant lung nodules are frequently subjected to invasive diagnostic approaches. Even though surgical removal of early stage non-small cell lung cancer (NSCLC) is the most effective therapy, post-surgical recurrence of NSCLC remains a significant problem as survival. Currently there are no clinically useful biomarkers that can accurately diagnose the indeterminate nodule or identify those patients destined to have recurrence of cancer after successful surgical removal. Recently, the use of culture-independent techniques to characterize the microbiome by us and others has led to identification of microbial signatures associated with lung cancer diagnosis and prognosis among a cohort with a wide range of disease stages. Preliminary metagenomic data obtained in collaboration with Micronoma using blood samples of our NYU cohort have identified microbial signatures in systemic circulation associated with early-stage NSCLC diagnosis. Further, using a NanoString platform we have identified circulating RNA signatures predictive of early-stage NSCLC diagnosis. In addition, our preliminary data shows that lower airway signatures can be used to predict prognosis post-surgical removal of early stage cancer. These data suggest that microbial and host genomic signatures could be leveraged to develop useful biomarkers in early-stage NSCLC. The addition of metabolite measurements could further contribute to this predictive power since those are end products of microbial and host functions. Under this BCC application we will first identify top microbial/host biomarkers that predict early-stage NSCLC diagnosis and prognosis using blood and lower airway samples from a cohort of patients with lung nodules and a presumed surgical clinical Stage I (<3cm) but with a final histological diagnosis of early-stage NSCLC (TNM  IIIA) or non-NSCLC nodules. We will implement cutting edge bioinformatic approaches to identify the most promising targets from these unbiased omic approach (metagenome, metabolome and transcriptome) which will guide the development of targeted approaches that to be validated under the Biomarker Reference Laboratory. These targeted approaches will include the development of targeted microbial DNA next generation sequencing, targeted metabolite measurement and custom-made NanoString panels as CLIA level assays, internally and externally validated, that will identify patients at highest risk for NSCLC diagnosis and recurrence after complete surgical resection.

Lung and Ovary

Group

Site ID Investigator Site Name PI Type Member Type
523 LaBaer, Joshua, M.D., Ph.D. Arizona State University Contact PI BCC, BDL
230 Anderson, Karen, M.D., Ph.D. Arizona State University MPI BCC, BDL
1032 Stengelin, Martin, Ph.D. Meso Scale Diagnostics Co-Investigator BCC, BRL

The goal of the ASU Biomarker Characterization Center is to improve ovarian and lung cancer screening through
the development of biologically-relevant circulating immune biomarkers. The scientific approach of our Center is
based on several fundamental principles. First, that altered cancer protein expression, structure, and posttranslational
modifications induce host autoantibodies to create circulating biomarkers. Second, that alterations
in microbial antigen expression (such as respiratory pathogens) also induce immunity, often detected in benign
rather than malignant disease. Third, that the protein modifications, as well as the immune response to these
neoantigenic structures, are heterogeneous between people, and that serologic biomarkers may complement
circulating protein biomarkers. We will take a systems immunology approach to discover three types of
antibodies, anti-microbial antibodies, autoantibodies and anti-aberrant glycoprotein antibodies. Our proposal
builds on our extensive experiences with cancer biomarker discovery and immunoproteomics technology
development. Our previous results on autoantibody biomarkers have been confirmed in blinded phase 2
multicenter validation studies and led to a CLIA-certified commercial blood test. Our results have shown that
multiplexed panels of autoantibodies are required for adequate predictive value. With prior EDRN support, we
have developed a set of innovative immunoproteomics technologies, namely high-density nucleic acid
programmable protein array (HD-NAPPA), contra-capture protein array (CCPA) and multiplexed in solution
protein array (MISPA), that, together with the largest full-length human and microbial gene collection at our
DNASU plasmid repository, enable us to study antibodies against the full human proteome, microbial proteomes
and the human O-glycoproteome for antibody biomarker signatures in cancer. Our Meso Scale Diagnostics
(MSD) team has fielded over 3,000 instruments worldwide, and over 700 commercially available biomarker assay
kits. Our expertise at serologic assay development was selected by Operation Warp Speed to use the V-PLEX®
serology panels as the basis of its standard binding assays for immunogenicity assessments in all funded Phase
III clinical trials of COVID vaccines. We will use our MSD MultiArray platform to migrate the top serologic and
protein markers for their utility in our target clinical applications. We will collaborate with experts on lung and
ovarian cancer screening at Vanderbilt University Medical Center, Boston University, MD Anderson Cancer
Center, and German Cancer Research Center, who will also provide access to high-quality well-characterized
samples to develop circulating biomarkers to enhance ovarian cancer screening or to distinguish benign from
malignant pulmonary nodules. Adhering to the principles of PRoBE design, we will perform Phase I discovery by
screening protein arrays with cancer patient and control sera for cancer or control-specific antibodies. Candidate
biomarkers for both lung and ovarian cancers will undergo Phase 2 validation.

Ovary

Group

Site ID Investigator Site Name PI Type Member Type
800 Zhang, Zhen, Ph.D. Johns Hopkins University Contact PI BCC, BDL
200 Chan, Daniel, Ph.D. Johns Hopkins Medical Institutions Co-Investigator BCC, BRL
829 Shih, le-Ming, M.D., Ph.D. Johns Hopkins University School of Medicine MPI BCC, BDL

High-grade serous ovarian carcinoma (HGSOC) is the most common histological subtype of epithelial ovarian
cancer. The overarching goal of the proposed Biomarker Characterization Center (BCC) is to apply a bydesign
approach based on biology of HGSOC pathogenesis and unmet clinical needs to identify, verify and
prioritize, and validate biomarkers, and to develop them into an in vitro diagnostic multivariate index assay
(IVDMIA) with the intended use to capture HGSOC in high-risk women at the early stages including i)
precursors, ii) confinement to the ovary/fallopian tube or iii) low-volume diseases in high-risk women (BRCA1/2
carriers). The biomarkers that we propose to discover and validate in this proposal are intended for early
detection but not necessarily for screening in general population. The BCC’s capability in advanced data
generation technologies, multiplexed target assay development, and bioinformatics/data science will serve as
resources for the EDRN. Based on the success of our current EDRN projects, this BCC will continue our ongoing
biomarker development studies including the validation of candidate biomarkers that we have identified
through the current BDL. We propose the following specific aims:
1. To optimize and use novel specimen collection and processing technologies, and an iterative and
cumulative process that takes advantage of our newly gained knowledge of the biology in ovarian cancer
pathogenesis. BDL
2. To optimize and apply innovative bioinformatics, data sciences, and AI/ML tools that incorporate existing
knowledge and data to improve discovery of low frequency biomarkers that with their functionally shared
pathways/networks could collectively deliver an improved sensitivity while retaining a high specificity. BDL
3. To further develop and optimize the process for efficient multiplex targeted assay development with respect
to analytical performance, throughput, and specimen volume requirement for a broad spectrum of
candidate biomarkers using a “fit for purpose” approach. BRL
4. To optimize and apply a by-design approach to translating discoveries into clinical tests. Its application had
been critical in the development of two FDA cleared tests by JHU team members for the preoperative
assessment of ovarian malignancy risk. BDL/BRL
5. To provide expertise and analytical and data science capabilities to the entire EDRN community.
The multi-disciplinary team that we have assembled (molecular cancer biology, pathology, clinical chemistry,
mass spectrometry, biostatistics, data science, bioengineering), the unique, novel yet biologically and
statistically sound approaches, and our long-standing experience in biomarker research and translating
discoveries to FDA cleared clinical tests all together ensure the success of this proposed BCC.

Group

Site ID Investigator Site Name PI Type Member Type
610 Skates, Steven, Ph.D. Massachusetts General Hospital Contact PI BCC, BDL
1031 Kulasingam, Vathany, Ph.D. University Health Network Co-Investigator BCC, BRL
1002 Patel, Abhijit, M.D. Yale University MPI BCC, BDL

A three-decade research program developing, optimizing, and testing an annual blood-based test for the early
detection of ovarian cancer in normal risk postmenopausal women failed to show a cancer-specific mortality
reduction. The likely fundamental reason for the failure is the short window of opportunity provided by a
blood-based signal. The proposed BCC will seek to identify an alternative biospecimen for the source of signal
which has a much greater window of time for detection in early-stage disease so that an annual testing
frequency will have a high likelihood of detecting ovarian cancer during its curable stages. Due to the direct
connection of the uterus to the fallopian tube, where the cell of origin resides, a uterine lavage will likely
contain the earliest biological signals of the presence of ovarian cancer. Identifying a minimal ovarian cancer
signal amongst a much greater background of uterine epithelium cells and cellular material requires a very
sensitive test. Our BCC will build on a recently developed innovative genome-wide methylation test and
combine it with a sensitive antibody based proteomic test. Having optimized the combined test to detect a
signal in uterine lavage, the BCC will determine its sensitivity in Pap smears. The BCC will optimize the
combined test on training uterine lavage samples, validate the test on independent validation cohort of
uterine lavage samples, and assess its performance in Pap smear samples. If the optimized test is sensitive in
Pap smears, then the overall goal of a clinically acceptable and readily performed test (Pap smear) conducted
at a feasible frequency of every 12 months will be a crucial step towards an annual test for the early detection
of ovarian cancer in normal risk postmenopausal women, the population in which 80% of ovarian cancers
occur. The long-term goal is an early detection program resulting in a significant reduction in ovarian cancer
mortality. The intended use of the test developed by the BCC will be as a clinical decision-support tool for
screening normal risk postmenopausal women for early detection of ovarian cancer. Such a test will fill an
unmet health gap since there is currently no early detection test for ovarian cancer.

Prostate

Group

Site ID Investigator Site Name PI Type Member Type
188 Chinnaiyan, Arul M., M.D., Ph.D. University of Michigan Contact PI BCC, BDL
1030 Kitchen, John, Ph.D. LynxDx Co-Investigator BCC, BRL
1011 Tosoian, Jeffrey, M.D. Vanderbilt University Medical Center MPI BCC, BRL
1029 Xiao, Lanbo, Ph.D. University of Michigan Co-Investigator BCC, BRL

This application proposes the formation of the Michigan-Vanderbilt University Medical Center (VUMC) EDRN
Biomarker Characterization Center (BCC). This BCC represents a collaborative, multi-disciplinary team of
academic (University of Michigan (U-M) and VUMC) and industry (LynxDx) partners focused on discovering,
developing, and scaling clinical-grade assays for the early detection of aggressive prostate cancer. Through
previous EDRN efforts, our team characterized multiple important prostate cancer biomarkers, most notably the
TMPRSS2-ETS gene fusions. Through collaboration with an EDRN Clinical Validation Center (CVC; Dr. Sanda
PI), we developed, validated, and clinically implemented MyProstateScore (MPS), an early detection test
incorporating urine quantification of two prostate cancer-specific transcripts—the TMPRSS2:ERG gene fusion
and the long non-coding RNA (lncRNA) PCA3. Introduced in our CLIA laboratory, MPS informs shared decision
making after PSA testing based on individualized risk predictions of aggressive prostate cancer on biopsy. Here,
pairing the cancer-specific components of the MPS test with recent discovery of high-grade cancer-specific
biomarkers, we outline the development, optimization, and clinical validation of the next generation of diagnostic
tests – capable of reliably, selectively detecting potentially lethal cancers that stand to benefit from early curative
treatment. Our Biomarker Developmental Laboratory (BDL) will employ the experimental platform, MPS-SEQ,
for capture RNA-seq analysis of urine samples to detect aggressive prostate cancer transcripts, lncRNAs,
circular RNAs, fusion transcripts, mutations, indels, and splice variants. Our Biomarker Reference Laboratory
(BRL) will in parallel develop a clinical grade urine assay, MPS-50, for the multiplex QPCR analysis of up to 50
amplicons. While the first 50 amplicons of MPS-50 have already been nominated, future improvements of the
assay content and platform will be informed by work carried out in our BDL. To fuel these studies, our BCC has
identified urine biospecimen cohorts collected under rigorous standard operating procedures in compliance with
PRoBE criteria including the Michigan Prostate SPORE, Emory University, the Center for Prostate Disease
Research, University of Texas San Antonio Health, Eastern Virginia Medical School, and VUMC/Meharry
Medical College. The overall Aims of this BCC serve to develop, assess, and optimize MPS-SEQ and MPS-50
for identifying high-grade prostate cancer in diverse at-risk populations. Our BRL will also focus on standardizing
clinically-validated biomarker assays for consistent and reliable use in accordance with CLIA/CAP guidelines at
the U-M Center for Translational Pathology in order to facilitate network consortium studies and at LynxDx in
order to scale, commercialize, and obtain FDA approvals. As recognized by the EDRN, novel biomarkers specific
for aggressive prostate cancer are urgently needed. Importantly, our mission and efforts extend beyond our BCC
and prostate cancer, as we actively participate in the EDRN biomarker community and support continued
collaborative efforts with other BCCs and CVCs to advance the overall EDRN mission.

Group

Site ID Investigator Site Name PI Type Member Type
92 Semmes, John, Ph.D. Eastern Virginia Medical School Contact PI BCC, BRL
823 Boutros, Paul, Ph.D. The University of California, Los Angeles MPI BCC, BRL
822 Kislinger, Thomas, Ph.D. Princess Margaret Cancer Centre, University Health Network, University of Toronto MPI BCC, BDL

The critical challenge in the clinical management of newly-diagnosed localized prostate cancer remains
distinguishing indolent from aggressive and life-threatening cancers. Biomarkers are urgently needed to
identify those patients who harbor aggressive disease and will derive benefit from definitive treatment. We
therefore, propose to apply complimentary proteogenomic-based discovery approaches to identify and then
validate molecular features in prostate proximal fluids and tumor tissues that will be utilized in accurate early
detection of aggressive forms of prostate cancer and improve disease risk stratification. The intended use of
these biomarkers will be the early identification of men at risk for grade progression and improved riskstratification
for them.
We have three biomarker development laboratory aims: 1) Validate our existing urine-based biomarkers for
grade progression in a ProBE-compliant study selected from our own cohorts and the EDRN GU upgrading
study. 2) Develop and validate urine and tissue-based biomarkers for the risk-stratification of MRI “invisible”
high-grade lesions. 3) Develop and validate biomarkers to sub-stratify risk associated with deleterious
germline BRCA2 variants.
Our biomarker reference laboratory will develop and validate targeted clinically robust assays for multi-protein
biomarkers panels. We will also develop decision algorithms that are cross-referenced for statistical rigor and
benchmarked for optimal clinical performance. In addition to these BCC activities, we will develop robust
PRM-MS assays and statistically rigorous decision tools for other EDRN BCCs and CVCs.
Taken together, our EDRN biomarker characterization center will be a core part of the the EDRN ecosystem.
We will continue to actively participate in trans-Network activities, and to share patient cohorts, protocols,
datasets and analysis approaches and expertise. We will supplement these activities by focusing on
promoting the growth of new and diverse talent in biomarker development through fostering junior investigator
involvement across the full spectrum of biomarker development.

Group

Site ID Investigator Site Name PI Type Member Type
1047 Chan, Daniel, Ph.D. The Johns Hopkins University Contact PI BCC, BRL
448 Zhang, Hui L., Ph.D. Johns Hopkins University School of Medicine MPI BCC, BDL

Active surveillance (AS) is the preferred management option for low risk prostate cancer (PCa) patients who would benefit from conservative treatment. However, due to the lack of reliable methods in the initial clinical evaluation to identify true low-risk PCa patients for AS enrollment and during AS monitoring to detect a rising risk of progression, patients who could benefit from conservative management through AS are often over-treated, yet at the same time patients initially chosen for AS with a missed high-risk disease are under-treated. The goal of the proposed EDRN Biomarker Characterization Center (BCC) is to develop and validate in vitro diagnostic multivariate index assays (IVDMIA) that combine a panel of biomarkers into a single-valued numerical index with the intended use for the clinical unmet needs for 1) assisting in the preoperative assessment of PCa aggressiveness and decision for enrollment into AS; and 2) detecting a rising risk of progression during AS to triage patients for additional and possibly more invasive procedures for needed disease reclassification. The objective for the IVDMIA development is to improve specificity while maintaining a high negative predictive value in order to safely enroll more patients with true low-risk PCa into AS and reduce the number of unnecessary biopsies and or costly workup procedures for patients in AS. To achieve this goal, we propose an integrated BCC at the JHU consisting of a multi-disciplinary team including PIs from current EDRN BDL (Dr. Hui Zhang) and BRL (Dr. Daniel W. Chan), and a previous CVC (Dr. Alan Partin). The targeted population is JHU AS patients with >20 years of enrollment and clinical follow-up. Our team has many years of experience in biomarker discovery, verification, validation, and translation into clinical diagnostics and the development of IVDMIA, e.g. OVA1, the 1st proteomics IVDMIA cleared by the FDA (2009). We plan to take advantage of the serum biomarkers already discovered for aggressive PCa from our current BDL and BRL and begin the verification and validation in the targeted AS population by our BRL. In parallel, our BDL will focus on the discovery of new candidate serum, urine and tissue biomarkers by applying cutting edge technologies to the AS population, such as mass spectrometry based high throughput proteomics, protein modifications, and single cell analysis of lasercapture- microdissected tissues. We plan to combine these biomarkers into IVDMIAs. Finally, we will work with our industry partners to translate these IVDMIAs into CLIA certified and/or FDA cleared/approved clinical diagnostics. We believe with these innovative, yet, practical approaches, our BCC offers the best opportunity to make significant contributions to the EDRN network and address the critical clinical unmet needs for PCa patients. If the over-treatment, under-treatment, decrease in unnecessary biopsies, and increase in biopsy accuracy can be successfully addressed, the morbidities associated with PCa diagnosis and treatment can be significantly decreased, while enhancing the detection and treatment of clinically significant PCa. In addition, our BRL, a CLIA and CAP certified clinical laboratory at JHU, will serve as a resource center for the EDRN network.

Biomarker Developmental Laboratories

Biomarker Developmental Laboratories (BDLs) discover and develop new biomarkers or refine existing biomarkers. They are the primary source of new biomarkers or panels of biomarkers on which the EDRN conducts validation trials. They also develop assays to detect candidate biomarkers and conduct pre-validation studies.

Breast

Group

Site ID Investigator Site Name PI Type Member Type
812 Paulovich, Amanda, M.D., Ph.D. Fred Hutchinson Cancer Center Contact PI BCC, BDL

We propose to develop a blood-based test whose indicated use is to complement mammography in the early detection of breast cancers. Although mammography saves lives through early detection, it is imperfect. Approximately one in seven breast cancers goes undetected despite screening mammography, and interval cancers that manifest within a year of a normal mammogram remain a vexing problem, especially (although not exclusively) for the >27 million women in the United States with heterogeneously or extremely dense breasts at high risk for interval cancers. We propose to develop a blood test that could be used as an adjunct to mammography to improve early detection by improving sensitivity and/or specificity of mammography. Using a novel biomarker discovery approach leveraging human-in-mouse breast cancer patient-derived xenograft models and state-of-the-art mass spectrometry methods, we prioritized 162 candidate breast cancer protein biomarkers for validation studies. Our BCC will perform EDRN Phase 2 biomarker validation studies of our prioritized 162 candidate plasma protein biomarkers of breast cancer. We have an experienced multidisciplinary team (including two junior investigators) with a strong track record of productive collaboration and representing expertise in clinical oncology, cancer biomarkers, pathology, CLIA/CAP/GLP assays, epidemiology, radiology/breast imaging, cancer screening, ‘omics data generation, and biostatistics. Our team includes 2 industry partners, encompasses 3 CLIA laboratories, and can provide expertise and access to multiple quantitative platforms in a CLIA/CAP/GLP environment to support EDRN Network Collaborations for biomarker validation studies with other BCCs. The Biomarker Development Laboratory will contribute to the biomarker validation studies by: (i) developing qualified reagents & methods for quantifying 162 candidate protein biomarkers, (ii) procuring plasma biospecimens (compliant with EDRN PRoBE study design) for phase 2 biomarker validation studies, (iii) delivering plasma aliquots to our BRL CLIA labs in a blinded fashion, and (iv) analyzing EDRN phase 2 validation data generated by the BRL, providing statistical, epidemiological, and breast imaging expertise to set and evaluate performance metrics to ensure biomarkers are adequate to provide clinical utility for early detection. The Biomarker Reference Laboratory will contribute to the proposed validation studies by: (i) validating a CLIAcompliant standard operating procedure for an immuno-MRM assay to quantify up to 162 candidate protein biomarkers of early-stage breast cancer that will serve as the basis for our biomarker validation studies, (ii) performing phase 2 biomarker validation studies, and (iii) providing reference laboratory support for the EDRN network (e.g., mass spectrometric analyses, flow cytometry, NextGen sequencing and ELISA assays. The Administrative Core will support all aspects of the BCC, including managing all administrative and project management aspects of the BCC as well as managing all center logistics and communication.

Colon and Esophagus

Group

Site ID Investigator Site Name PI Type Member Type
160 Grady, William, M.D. Fred Hutchinson Cancer Center Contact PI BCC, BDL

Gastrointestinal (GI) cancers are a major cause of mortality and morbidity in the U.S. and their treatment
uses a substantial proportion of healthcare resources. Of the GI cancers, colorectal cancer (CRC) and
esophageal cancer (EAC) account for a majority of the cancer related deaths, and both are preventable by
screening and surveillance. The current screening tests are suboptimal and have variable success.
A major goal of CRC screening tests is to identify advanced tubular and serrated adenomas, which are
high-risk for becoming CRC, as well as early stage CRC. The risk for CRC is variable with some people being
at high risk because of family histories of CRC, hereditary cancer syndromes, or a personal history of adenomas.
High risk people are placed on aggressive colonoscopy based surveillance programs and low-risk people are
placed on minimal surveillance programs. Unfortunately, our current system for identifying high and low CRC
risk is suboptimal resulting in under and over surveillance and preventable interval CRCs. Better risk markers
for CRC to are needed to prevent interval CRCs and improve the overall effectiveness of CRC screening.
Analogous to CRC, EAC arises from a precancerous condition of the esophagus called Barretts
esophagus (BE), which is a specialized intestinal metaplasia of the esophagus and the highest risk factor for
EAC. It is present in 5% of the US population. BE progresses to EAC through successive histologic steps of
low grade dysplasia (LGD), high grade dysplasia (HGD) and then EAC. Screening and surveillance for BE is
recommended using serial upper endoscopy, which is controversial in its effectiveness for preventing deaths
from EAC. This is in part because, as with CRC, BE patients have variable risk of EAC and are placed on highrisk
and low-risk screening programs. However, the current system for assigning risk is not accurate and the
current screening test is expensive. More cost effective and accurate EAC and HGD screening/surveillance
assays and accurate BE risk biomarkers are needed.
We propose to develop an EDRN BCC that is integrated into the EDRN consortium and, through
collaborations within and outside the EDRN, will develop effective GI cancer screening biomarkers. We propose
to identify, validate, and develop accurate CLIA compliant risk biomarkers for CRC and for EAC in order to
prevent EAC and CRC missed under current screening protocols. Moreover, the accurate risk stratification of
patients for CRC and EAC will reduce the financial impact of current CRC and EAC prevention programs. We
also propose to identify and validate accurate CLIA compliant early detection markers for HGD and early stage
EAC that can be used in an inexpensive, non-endoscopic surveillance test.

Lung

Group

Site ID Investigator Site Name PI Type Member Type
813 Herman, James, M.D. University of Pittsburgh School of Medicine Contact PI BCC, BDL, BRL
818 Wang, Tza-Huei (Jeff), Ph.D. Johns Hopkins Whiting School of Engineering MPI BCC, BDL

This proposal for a Biomarker Characterization Center (BCC) for the Early Detection Research
Network (EDRN) seeks to improve the management of lung cancer through detection of cancerspecific
DNA methylation. This effort includes a Biomarker Development Laboratory (BDL) which
will optimize the methylation detection methods, implementation of these methods for clinical use
through a Biomarker Reference Laboratory (BRL) with a longstanding record of molecular testing
in a clinical setting, and an Administrative Core facilitating the interactions between the BDL and
BRL, and with other EDRN investigators and the NCI. Previous work by the applicants has
demonstrated the potential of DNA methylation detection for cancer diagnostics, and they have
developed extremely sensitive assays for the detection of hypermethylated DNA sequences and
optimized the isolation and processing of circulating cell-free DNA from tumors for these novel
assays. The approach has been used to detect circulating cancer-specific DNA methylation
changes for the early diagnosis of lung cancer in patients with screen-detected pulmonary
nodules. Although sensitivity and specificity of the assay are promising, additional improvements
in the performance are required for implementation of this approach in the setting of cancer
screening. In this BCC, detection of cancer-specific DNA methylation changes in the plasma will
be further improved, and new approaches developed and implemented to address the challenges
of ultrasensitive detection of DNA methylation in the blood. In addition, we will assess the potential
of these methods to detect other common and lethal malignancies. Our bioinformatic analysis of
DNA methylation from The Cancer Genome Atlas (TCGA) has identified novel highly frequent
cancer-specific methylation events common to all cancers, including lung cancer, that will be
developed into universal cancer detection assays. The use of TCGA data has also resulted in the
identification of other methylation alterations that allow determination of the origin (organ site) of
this cancer-specific signal. The combination of optimal sample processing, ultrasensitive
methylation detection, developed with universal cancer and histology specific loci detection, will
allow improved lung cancer early detection in the setting of CT screening and management of
detection of other cancer-specific DNA methylation from blood.

Group

Site ID Investigator Site Name PI Type Member Type
594 Lenburg, Marc, Ph.D. Boston University Contact PI BCC, BDL
1014 Beane-Ebel, Jennifer E., Ph.D. Boston University School of Medicine MPI BCC, BDL
241 Dubinett, Steve, M.D. University of California Los Angeles MPI BCC, BDL
1015 Hsu, William, Ph.D. UCLA School of Engineering MPI BCC, BDL, BRL

Screen and incidentally detected intermediate risk indeterminant pulmonary nodules (IPN) represent a clinical
dilemma for which there is little consensus about appropriate follow up due to a lack of sensitive and specific
approaches for the detection of lung cancer absent invasive tissue sampling, and concerns about costs and
harms from invasive tissue sampling in this large clinical population. Minimally invasive approaches that could
accurately reclassify individuals from the intermediate risk group (5-65% risk of malignancy) to either low (< 5%)
or high (>65%) risk would reduce uncertainty and transform the diagnostic workup of intermediate risk IPN.
Developing, evaluating, standardizing, and validating such minimally invasive biomarkers so that they are ready
for clinical use is the goal of the proposed BU-UCLA Lung Cancer Biomarker Characterization Center (BCC). In
previous EDRN-funded work we established lung-cancer associated gene expression patterns in nasal
epithelium collected with a swab from the inferior turbinate as a lung cancer biomarker. A test based on this
innovative approach to lung cancer detection is being launched for clinical use as a CLIA LDT by our long-time
collaborator Veracyte, Inc., which is participating in this BCC. We will evaluate the nasal biomarker for lung
cancer in the setting of intermediate risk IPN. To further improve the ability to clinically discriminate benign from
malignant intermediate risk IPN, the BU-UCLA Lung Cancer Biomarker Discovery Lab embedded within the BCC
will develop and test lung cancer detection approaches that incorporate detection of circulating tumor cells (CTC)
using a CLIA LDT assay from our collaborator LungLife AI, Inc. as well as blood based immune biomarkers,
advanced imaging biomarkers, and refined nasal gene expression biomarkers. We will additionally determine if
longitudinal biomarker assessment improves lung cancer detection over cross-sectional measurements.
Promising assays will be refined, standardized, and validated by the BU-UCLA Lung Cancer Biomarker
Reference Lab embedded within the BCC to advance them toward clinical adoption. These studies are enabled
by biospecimens and imaging data that are being prospectively collected from diverse populations of patients
undergoing workup for intermediate risk IPN in several large-scale ongoing clinical studies including VA LPOP,
DECAMP 1-Plus, and UCLA IDx; lung cancer research programs at UCLA and Lahey; and our EDRN
collaborators at Nashville VA and Vanderbilt. The BU-UCLA Lung Cancer BCC Team has the required multidisciplinary
expertise in lung cancer, translational and clinical pulmonary medicine, biomarker discovery, clinical
assay development, biostatistics, clinical epidemiology, pathology, imaging, artificial intelligence, biological
sciences, bioinformatics, genomics, and complex scientific program management to accomplish these goals. An
Administrative Core embedded within the BCC will ensure that the BCC delivers on its aim to substantially
advance novel lung cancer biomarkers from discovery to clinical application and make significant contributions
to the Early Detection Research Network.

Group

Site ID Investigator Site Name PI Type Member Type
1049 Segal, Leopoldo, M.D. New York University Grossman School of Medicine Contact PI BCC, BDL, BRL
176 Pass, Harvey Ira, M.D. New York University School of Medicine MPI BCC, BDL

Lung cancer remains the leading cause of all cancer mortality. Improved imaging techniques enable the detection of lung cancer at earlier stages, yet a large number of patients with non-malignant lung nodules are frequently subjected to invasive diagnostic approaches. Even though surgical removal of early stage non-small cell lung cancer (NSCLC) is the most effective therapy, post-surgical recurrence of NSCLC remains a significant problem as survival. Currently there are no clinically useful biomarkers that can accurately diagnose the indeterminate nodule or identify those patients destined to have recurrence of cancer after successful surgical removal. Recently, the use of culture-independent techniques to characterize the microbiome by us and others has led to identification of microbial signatures associated with lung cancer diagnosis and prognosis among a cohort with a wide range of disease stages. Preliminary metagenomic data obtained in collaboration with Micronoma using blood samples of our NYU cohort have identified microbial signatures in systemic circulation associated with early-stage NSCLC diagnosis. Further, using a NanoString platform we have identified circulating RNA signatures predictive of early-stage NSCLC diagnosis. In addition, our preliminary data shows that lower airway signatures can be used to predict prognosis post-surgical removal of early stage cancer. These data suggest that microbial and host genomic signatures could be leveraged to develop useful biomarkers in early-stage NSCLC. The addition of metabolite measurements could further contribute to this predictive power since those are end products of microbial and host functions. Under this BCC application we will first identify top microbial/host biomarkers that predict early-stage NSCLC diagnosis and prognosis using blood and lower airway samples from a cohort of patients with lung nodules and a presumed surgical clinical Stage I (<3cm) but with a final histological diagnosis of early-stage NSCLC (TNM  IIIA) or non-NSCLC nodules. We will implement cutting edge bioinformatic approaches to identify the most promising targets from these unbiased omic approach (metagenome, metabolome and transcriptome) which will guide the development of targeted approaches that to be validated under the Biomarker Reference Laboratory. These targeted approaches will include the development of targeted microbial DNA next generation sequencing, targeted metabolite measurement and custom-made NanoString panels as CLIA level assays, internally and externally validated, that will identify patients at highest risk for NSCLC diagnosis and recurrence after complete surgical resection.

Lung and Ovary

Group

Site ID Investigator Site Name PI Type Member Type
523 LaBaer, Joshua, M.D., Ph.D. Arizona State University Contact PI BCC, BDL
230 Anderson, Karen, M.D., Ph.D. Arizona State University MPI BCC, BDL

The goal of the ASU Biomarker Characterization Center is to improve ovarian and lung cancer screening through
the development of biologically-relevant circulating immune biomarkers. The scientific approach of our Center is
based on several fundamental principles. First, that altered cancer protein expression, structure, and posttranslational
modifications induce host autoantibodies to create circulating biomarkers. Second, that alterations
in microbial antigen expression (such as respiratory pathogens) also induce immunity, often detected in benign
rather than malignant disease. Third, that the protein modifications, as well as the immune response to these
neoantigenic structures, are heterogeneous between people, and that serologic biomarkers may complement
circulating protein biomarkers. We will take a systems immunology approach to discover three types of
antibodies, anti-microbial antibodies, autoantibodies and anti-aberrant glycoprotein antibodies. Our proposal
builds on our extensive experiences with cancer biomarker discovery and immunoproteomics technology
development. Our previous results on autoantibody biomarkers have been confirmed in blinded phase 2
multicenter validation studies and led to a CLIA-certified commercial blood test. Our results have shown that
multiplexed panels of autoantibodies are required for adequate predictive value. With prior EDRN support, we
have developed a set of innovative immunoproteomics technologies, namely high-density nucleic acid
programmable protein array (HD-NAPPA), contra-capture protein array (CCPA) and multiplexed in solution
protein array (MISPA), that, together with the largest full-length human and microbial gene collection at our
DNASU plasmid repository, enable us to study antibodies against the full human proteome, microbial proteomes
and the human O-glycoproteome for antibody biomarker signatures in cancer. Our Meso Scale Diagnostics
(MSD) team has fielded over 3,000 instruments worldwide, and over 700 commercially available biomarker assay
kits. Our expertise at serologic assay development was selected by Operation Warp Speed to use the V-PLEX®
serology panels as the basis of its standard binding assays for immunogenicity assessments in all funded Phase
III clinical trials of COVID vaccines. We will use our MSD MultiArray platform to migrate the top serologic and
protein markers for their utility in our target clinical applications. We will collaborate with experts on lung and
ovarian cancer screening at Vanderbilt University Medical Center, Boston University, MD Anderson Cancer
Center, and German Cancer Research Center, who will also provide access to high-quality well-characterized
samples to develop circulating biomarkers to enhance ovarian cancer screening or to distinguish benign from
malignant pulmonary nodules. Adhering to the principles of PRoBE design, we will perform Phase I discovery by
screening protein arrays with cancer patient and control sera for cancer or control-specific antibodies. Candidate
biomarkers for both lung and ovarian cancers will undergo Phase 2 validation.

Ovary

Group

Site ID Investigator Site Name PI Type Member Type
800 Zhang, Zhen, Ph.D. Johns Hopkins University Contact PI BCC, BDL
829 Shih, le-Ming, M.D., Ph.D. Johns Hopkins University School of Medicine MPI BCC, BDL

High-grade serous ovarian carcinoma (HGSOC) is the most common histological subtype of epithelial ovarian
cancer. The overarching goal of the proposed Biomarker Characterization Center (BCC) is to apply a bydesign
approach based on biology of HGSOC pathogenesis and unmet clinical needs to identify, verify and
prioritize, and validate biomarkers, and to develop them into an in vitro diagnostic multivariate index assay
(IVDMIA) with the intended use to capture HGSOC in high-risk women at the early stages including i)
precursors, ii) confinement to the ovary/fallopian tube or iii) low-volume diseases in high-risk women (BRCA1/2
carriers). The biomarkers that we propose to discover and validate in this proposal are intended for early
detection but not necessarily for screening in general population. The BCC’s capability in advanced data
generation technologies, multiplexed target assay development, and bioinformatics/data science will serve as
resources for the EDRN. Based on the success of our current EDRN projects, this BCC will continue our ongoing
biomarker development studies including the validation of candidate biomarkers that we have identified
through the current BDL. We propose the following specific aims:
1. To optimize and use novel specimen collection and processing technologies, and an iterative and
cumulative process that takes advantage of our newly gained knowledge of the biology in ovarian cancer
pathogenesis. BDL
2. To optimize and apply innovative bioinformatics, data sciences, and AI/ML tools that incorporate existing
knowledge and data to improve discovery of low frequency biomarkers that with their functionally shared
pathways/networks could collectively deliver an improved sensitivity while retaining a high specificity. BDL
3. To further develop and optimize the process for efficient multiplex targeted assay development with respect
to analytical performance, throughput, and specimen volume requirement for a broad spectrum of
candidate biomarkers using a “fit for purpose” approach. BRL
4. To optimize and apply a by-design approach to translating discoveries into clinical tests. Its application had
been critical in the development of two FDA cleared tests by JHU team members for the preoperative
assessment of ovarian malignancy risk. BDL/BRL
5. To provide expertise and analytical and data science capabilities to the entire EDRN community.
The multi-disciplinary team that we have assembled (molecular cancer biology, pathology, clinical chemistry,
mass spectrometry, biostatistics, data science, bioengineering), the unique, novel yet biologically and
statistically sound approaches, and our long-standing experience in biomarker research and translating
discoveries to FDA cleared clinical tests all together ensure the success of this proposed BCC.

Group

Site ID Investigator Site Name PI Type Member Type
610 Skates, Steven, Ph.D. Massachusetts General Hospital Contact PI BCC, BDL
1002 Patel, Abhijit, M.D. Yale University MPI BCC, BDL

A three-decade research program developing, optimizing, and testing an annual blood-based test for the early
detection of ovarian cancer in normal risk postmenopausal women failed to show a cancer-specific mortality
reduction. The likely fundamental reason for the failure is the short window of opportunity provided by a
blood-based signal. The proposed BCC will seek to identify an alternative biospecimen for the source of signal
which has a much greater window of time for detection in early-stage disease so that an annual testing
frequency will have a high likelihood of detecting ovarian cancer during its curable stages. Due to the direct
connection of the uterus to the fallopian tube, where the cell of origin resides, a uterine lavage will likely
contain the earliest biological signals of the presence of ovarian cancer. Identifying a minimal ovarian cancer
signal amongst a much greater background of uterine epithelium cells and cellular material requires a very
sensitive test. Our BCC will build on a recently developed innovative genome-wide methylation test and
combine it with a sensitive antibody based proteomic test. Having optimized the combined test to detect a
signal in uterine lavage, the BCC will determine its sensitivity in Pap smears. The BCC will optimize the
combined test on training uterine lavage samples, validate the test on independent validation cohort of
uterine lavage samples, and assess its performance in Pap smear samples. If the optimized test is sensitive in
Pap smears, then the overall goal of a clinically acceptable and readily performed test (Pap smear) conducted
at a feasible frequency of every 12 months will be a crucial step towards an annual test for the early detection
of ovarian cancer in normal risk postmenopausal women, the population in which 80% of ovarian cancers
occur. The long-term goal is an early detection program resulting in a significant reduction in ovarian cancer
mortality. The intended use of the test developed by the BCC will be as a clinical decision-support tool for
screening normal risk postmenopausal women for early detection of ovarian cancer. Such a test will fill an
unmet health gap since there is currently no early detection test for ovarian cancer.

Prostate

Group

Site ID Investigator Site Name PI Type Member Type
188 Chinnaiyan, Arul M., M.D., Ph.D. University of Michigan Contact PI BCC, BDL

This application proposes the formation of the Michigan-Vanderbilt University Medical Center (VUMC) EDRN
Biomarker Characterization Center (BCC). This BCC represents a collaborative, multi-disciplinary team of
academic (University of Michigan (U-M) and VUMC) and industry (LynxDx) partners focused on discovering,
developing, and scaling clinical-grade assays for the early detection of aggressive prostate cancer. Through
previous EDRN efforts, our team characterized multiple important prostate cancer biomarkers, most notably the
TMPRSS2-ETS gene fusions. Through collaboration with an EDRN Clinical Validation Center (CVC; Dr. Sanda
PI), we developed, validated, and clinically implemented MyProstateScore (MPS), an early detection test
incorporating urine quantification of two prostate cancer-specific transcripts—the TMPRSS2:ERG gene fusion
and the long non-coding RNA (lncRNA) PCA3. Introduced in our CLIA laboratory, MPS informs shared decision
making after PSA testing based on individualized risk predictions of aggressive prostate cancer on biopsy. Here,
pairing the cancer-specific components of the MPS test with recent discovery of high-grade cancer-specific
biomarkers, we outline the development, optimization, and clinical validation of the next generation of diagnostic
tests – capable of reliably, selectively detecting potentially lethal cancers that stand to benefit from early curative
treatment. Our Biomarker Developmental Laboratory (BDL) will employ the experimental platform, MPS-SEQ,
for capture RNA-seq analysis of urine samples to detect aggressive prostate cancer transcripts, lncRNAs,
circular RNAs, fusion transcripts, mutations, indels, and splice variants. Our Biomarker Reference Laboratory
(BRL) will in parallel develop a clinical grade urine assay, MPS-50, for the multiplex QPCR analysis of up to 50
amplicons. While the first 50 amplicons of MPS-50 have already been nominated, future improvements of the
assay content and platform will be informed by work carried out in our BDL. To fuel these studies, our BCC has
identified urine biospecimen cohorts collected under rigorous standard operating procedures in compliance with
PRoBE criteria including the Michigan Prostate SPORE, Emory University, the Center for Prostate Disease
Research, University of Texas San Antonio Health, Eastern Virginia Medical School, and VUMC/Meharry
Medical College. The overall Aims of this BCC serve to develop, assess, and optimize MPS-SEQ and MPS-50
for identifying high-grade prostate cancer in diverse at-risk populations. Our BRL will also focus on standardizing
clinically-validated biomarker assays for consistent and reliable use in accordance with CLIA/CAP guidelines at
the U-M Center for Translational Pathology in order to facilitate network consortium studies and at LynxDx in
order to scale, commercialize, and obtain FDA approvals. As recognized by the EDRN, novel biomarkers specific
for aggressive prostate cancer are urgently needed. Importantly, our mission and efforts extend beyond our BCC
and prostate cancer, as we actively participate in the EDRN biomarker community and support continued
collaborative efforts with other BCCs and CVCs to advance the overall EDRN mission.

Group

Site ID Investigator Site Name PI Type Member Type
92 Semmes, John, Ph.D. Eastern Virginia Medical School Contact PI BCC
822 Kislinger, Thomas, Ph.D. Princess Margaret Cancer Centre, University Health Network, University of Toronto MPI BCC, BDL

The critical challenge in the clinical management of newly-diagnosed localized prostate cancer remains
distinguishing indolent from aggressive and life-threatening cancers. Biomarkers are urgently needed to
identify those patients who harbor aggressive disease and will derive benefit from definitive treatment. We
therefore, propose to apply complimentary proteogenomic-based discovery approaches to identify and then
validate molecular features in prostate proximal fluids and tumor tissues that will be utilized in accurate early
detection of aggressive forms of prostate cancer and improve disease risk stratification. The intended use of
these biomarkers will be the early identification of men at risk for grade progression and improved riskstratification
for them.
We have three biomarker development laboratory aims: 1) Validate our existing urine-based biomarkers for
grade progression in a ProBE-compliant study selected from our own cohorts and the EDRN GU upgrading
study. 2) Develop and validate urine and tissue-based biomarkers for the risk-stratification of MRI “invisible”
high-grade lesions. 3) Develop and validate biomarkers to sub-stratify risk associated with deleterious
germline BRCA2 variants.
Our biomarker reference laboratory will develop and validate targeted clinically robust assays for multi-protein
biomarkers panels. We will also develop decision algorithms that are cross-referenced for statistical rigor and
benchmarked for optimal clinical performance. In addition to these BCC activities, we will develop robust
PRM-MS assays and statistically rigorous decision tools for other EDRN BCCs and CVCs.
Taken together, our EDRN biomarker characterization center will be a core part of the the EDRN ecosystem.
We will continue to actively participate in trans-Network activities, and to share patient cohorts, protocols,
datasets and analysis approaches and expertise. We will supplement these activities by focusing on
promoting the growth of new and diverse talent in biomarker development through fostering junior investigator
involvement across the full spectrum of biomarker development.

Group

Site ID Investigator Site Name PI Type Member Type
1047 Chan, Daniel, Ph.D. The Johns Hopkins University Contact PI BCC
448 Zhang, Hui L., Ph.D. Johns Hopkins University School of Medicine MPI BCC, BDL

Active surveillance (AS) is the preferred management option for low risk prostate cancer (PCa) patients who would benefit from conservative treatment. However, due to the lack of reliable methods in the initial clinical evaluation to identify true low-risk PCa patients for AS enrollment and during AS monitoring to detect a rising risk of progression, patients who could benefit from conservative management through AS are often over-treated, yet at the same time patients initially chosen for AS with a missed high-risk disease are under-treated. The goal of the proposed EDRN Biomarker Characterization Center (BCC) is to develop and validate in vitro diagnostic multivariate index assays (IVDMIA) that combine a panel of biomarkers into a single-valued numerical index with the intended use for the clinical unmet needs for 1) assisting in the preoperative assessment of PCa aggressiveness and decision for enrollment into AS; and 2) detecting a rising risk of progression during AS to triage patients for additional and possibly more invasive procedures for needed disease reclassification. The objective for the IVDMIA development is to improve specificity while maintaining a high negative predictive value in order to safely enroll more patients with true low-risk PCa into AS and reduce the number of unnecessary biopsies and or costly workup procedures for patients in AS. To achieve this goal, we propose an integrated BCC at the JHU consisting of a multi-disciplinary team including PIs from current EDRN BDL (Dr. Hui Zhang) and BRL (Dr. Daniel W. Chan), and a previous CVC (Dr. Alan Partin). The targeted population is JHU AS patients with >20 years of enrollment and clinical follow-up. Our team has many years of experience in biomarker discovery, verification, validation, and translation into clinical diagnostics and the development of IVDMIA, e.g. OVA1, the 1st proteomics IVDMIA cleared by the FDA (2009). We plan to take advantage of the serum biomarkers already discovered for aggressive PCa from our current BDL and BRL and begin the verification and validation in the targeted AS population by our BRL. In parallel, our BDL will focus on the discovery of new candidate serum, urine and tissue biomarkers by applying cutting edge technologies to the AS population, such as mass spectrometry based high throughput proteomics, protein modifications, and single cell analysis of lasercapture- microdissected tissues. We plan to combine these biomarkers into IVDMIAs. Finally, we will work with our industry partners to translate these IVDMIAs into CLIA certified and/or FDA cleared/approved clinical diagnostics. We believe with these innovative, yet, practical approaches, our BCC offers the best opportunity to make significant contributions to the EDRN network and address the critical clinical unmet needs for PCa patients. If the over-treatment, under-treatment, decrease in unnecessary biopsies, and increase in biopsy accuracy can be successfully addressed, the morbidities associated with PCa diagnosis and treatment can be significantly decreased, while enhancing the detection and treatment of clinically significant PCa. In addition, our BRL, a CLIA and CAP certified clinical laboratory at JHU, will serve as a resource center for the EDRN network.

Biomarker Reference Laboratories

Biomarker Reference Laboratories (BRLs) conduct assays for EDRN validation trials. The assays are performed on blinded biospecimens to minimize bias in the analysis and independently verify the assay performance. BRLs also serve as the primary resource for analytical validation of biomarkers, technological development, standardization, assay refinement and quality control.

All Organs

Group

Site ID Investigator Site Name PI Type Member Type
611 He, Hua-Jun, Ph.D. National Institute of Standards & Technology Contact PI BRL

No summary available for the above ↑ site at this time.

Group

Site ID Investigator Site Name PI Type Member Type
234 Liu, Tao, Ph.D. Pacific Northwest National Laboratory Contact PI BRL

No summary available for the above ↑ site at this time.

Breast

Group

Site ID Investigator Site Name PI Type Member Type
812 Paulovich, Amanda, M.D., Ph.D. Fred Hutchinson Cancer Center Contact PI BCC
1048 Hoofnagle, Andrew, M.D., Ph.D. University of Washington MPI BCC, BRL

We propose to develop a blood-based test whose indicated use is to complement mammography in the early detection of breast cancers. Although mammography saves lives through early detection, it is imperfect. Approximately one in seven breast cancers goes undetected despite screening mammography, and interval cancers that manifest within a year of a normal mammogram remain a vexing problem, especially (although not exclusively) for the >27 million women in the United States with heterogeneously or extremely dense breasts at high risk for interval cancers. We propose to develop a blood test that could be used as an adjunct to mammography to improve early detection by improving sensitivity and/or specificity of mammography. Using a novel biomarker discovery approach leveraging human-in-mouse breast cancer patient-derived xenograft models and state-of-the-art mass spectrometry methods, we prioritized 162 candidate breast cancer protein biomarkers for validation studies. Our BCC will perform EDRN Phase 2 biomarker validation studies of our prioritized 162 candidate plasma protein biomarkers of breast cancer. We have an experienced multidisciplinary team (including two junior investigators) with a strong track record of productive collaboration and representing expertise in clinical oncology, cancer biomarkers, pathology, CLIA/CAP/GLP assays, epidemiology, radiology/breast imaging, cancer screening, ‘omics data generation, and biostatistics. Our team includes 2 industry partners, encompasses 3 CLIA laboratories, and can provide expertise and access to multiple quantitative platforms in a CLIA/CAP/GLP environment to support EDRN Network Collaborations for biomarker validation studies with other BCCs. The Biomarker Development Laboratory will contribute to the biomarker validation studies by: (i) developing qualified reagents & methods for quantifying 162 candidate protein biomarkers, (ii) procuring plasma biospecimens (compliant with EDRN PRoBE study design) for phase 2 biomarker validation studies, (iii) delivering plasma aliquots to our BRL CLIA labs in a blinded fashion, and (iv) analyzing EDRN phase 2 validation data generated by the BRL, providing statistical, epidemiological, and breast imaging expertise to set and evaluate performance metrics to ensure biomarkers are adequate to provide clinical utility for early detection. The Biomarker Reference Laboratory will contribute to the proposed validation studies by: (i) validating a CLIAcompliant standard operating procedure for an immuno-MRM assay to quantify up to 162 candidate protein biomarkers of early-stage breast cancer that will serve as the basis for our biomarker validation studies, (ii) performing phase 2 biomarker validation studies, and (iii) providing reference laboratory support for the EDRN network (e.g., mass spectrometric analyses, flow cytometry, NextGen sequencing and ELISA assays. The Administrative Core will support all aspects of the BCC, including managing all administrative and project management aspects of the BCC as well as managing all center logistics and communication. Contact PD/PI: Paulovich, Amanda G Project Summary/

Colon and Esophagus

Group

Site ID Investigator Site Name PI Type Member Type
160 Grady, William, M.D. Fred Hutchinson Cancer Center Contact PI BCC
1016 Yeung, Cecilia, M.D. Fred Hutch Cancer Center MPI BCC, BRL

Gastrointestinal (GI) cancers are a major cause of mortality and morbidity in the U.S. and their treatment
uses a substantial proportion of healthcare resources. Of the GI cancers, colorectal cancer (CRC) and
esophageal cancer (EAC) account for a majority of the cancer related deaths, and both are preventable by
screening and surveillance. The current screening tests are suboptimal and have variable success.
A major goal of CRC screening tests is to identify advanced tubular and serrated adenomas, which are
high-risk for becoming CRC, as well as early stage CRC. The risk for CRC is variable with some people being
at high risk because of family histories of CRC, hereditary cancer syndromes, or a personal history of adenomas.
High risk people are placed on aggressive colonoscopy based surveillance programs and low-risk people are
placed on minimal surveillance programs. Unfortunately, our current system for identifying high and low CRC
risk is suboptimal resulting in under and over surveillance and preventable interval CRCs. Better risk markers
for CRC to are needed to prevent interval CRCs and improve the overall effectiveness of CRC screening.
Analogous to CRC, EAC arises from a precancerous condition of the esophagus called Barretts
esophagus (BE), which is a specialized intestinal metaplasia of the esophagus and the highest risk factor for
EAC. It is present in 5% of the US population. BE progresses to EAC through successive histologic steps of
low grade dysplasia (LGD), high grade dysplasia (HGD) and then EAC. Screening and surveillance for BE is
recommended using serial upper endoscopy, which is controversial in its effectiveness for preventing deaths
from EAC. This is in part because, as with CRC, BE patients have variable risk of EAC and are placed on highrisk
and low-risk screening programs. However, the current system for assigning risk is not accurate and the
current screening test is expensive. More cost effective and accurate EAC and HGD screening/surveillance
assays and accurate BE risk biomarkers are needed.
We propose to develop an EDRN BCC that is integrated into the EDRN consortium and, through
collaborations within and outside the EDRN, will develop effective GI cancer screening biomarkers. We propose
to identify, validate, and develop accurate CLIA compliant risk biomarkers for CRC and for EAC in order to
prevent EAC and CRC missed under current screening protocols. Moreover, the accurate risk stratification of
patients for CRC and EAC will reduce the financial impact of current CRC and EAC prevention programs. We
also propose to identify and validate accurate CLIA compliant early detection markers for HGD and early stage
EAC that can be used in an inexpensive, non-endoscopic surveillance test.

Lung

Group

Site ID Investigator Site Name PI Type Member Type
813 Herman, James, M.D. University of Pittsburgh School of Medicine Contact PI BCC, BDL, BRL
201 Stass, Sanford, M.D. University of Maryland School of Medicine MPI BCC, BRL

This proposal for a Biomarker Characterization Center (BCC) for the Early Detection Research
Network (EDRN) seeks to improve the management of lung cancer through detection of cancerspecific
DNA methylation. This effort includes a Biomarker Development Laboratory (BDL) which
will optimize the methylation detection methods, implementation of these methods for clinical use
through a Biomarker Reference Laboratory (BRL) with a longstanding record of molecular testing
in a clinical setting, and an Administrative Core facilitating the interactions between the BDL and
BRL, and with other EDRN investigators and the NCI. Previous work by the applicants has
demonstrated the potential of DNA methylation detection for cancer diagnostics, and they have
developed extremely sensitive assays for the detection of hypermethylated DNA sequences and
optimized the isolation and processing of circulating cell-free DNA from tumors for these novel
assays. The approach has been used to detect circulating cancer-specific DNA methylation
changes for the early diagnosis of lung cancer in patients with screen-detected pulmonary
nodules. Although sensitivity and specificity of the assay are promising, additional improvements
in the performance are required for implementation of this approach in the setting of cancer
screening. In this BCC, detection of cancer-specific DNA methylation changes in the plasma will
be further improved, and new approaches developed and implemented to address the challenges
of ultrasensitive detection of DNA methylation in the blood. In addition, we will assess the potential
of these methods to detect other common and lethal malignancies. Our bioinformatic analysis of
DNA methylation from The Cancer Genome Atlas (TCGA) has identified novel highly frequent
cancer-specific methylation events common to all cancers, including lung cancer, that will be
developed into universal cancer detection assays. The use of TCGA data has also resulted in the
identification of other methylation alterations that allow determination of the origin (organ site) of
this cancer-specific signal. The combination of optimal sample processing, ultrasensitive
methylation detection, developed with universal cancer and histology specific loci detection, will
allow improved lung cancer early detection in the setting of CT screening and management of
detection of other cancer-specific DNA methylation from blood.

Group

Site ID Investigator Site Name PI Type Member Type
594 Lenburg, Marc, Ph.D. Boston University Contact PI BCC
1033 Bulman, William, Veracyte Inc Co-Investigator BCC, BRL
1015 Hsu, William, Ph.D. UCLA School of Engineering MPI BCC, BDL, BRL
1035 Pagano, Paul, Ph.D. LungLife AI, Inc Co-Investigator BCC, BRL
1034 Palazzolo, Michael, M.D., Ph.D. University of California, Los Angeles Co-Investigator BCC, BRL

Screen and incidentally detected intermediate risk indeterminant pulmonary nodules (IPN) represent a clinical
dilemma for which there is little consensus about appropriate follow up due to a lack of sensitive and specific
approaches for the detection of lung cancer absent invasive tissue sampling, and concerns about costs and
harms from invasive tissue sampling in this large clinical population. Minimally invasive approaches that could
accurately reclassify individuals from the intermediate risk group (5-65% risk of malignancy) to either low (< 5%)
or high (>65%) risk would reduce uncertainty and transform the diagnostic workup of intermediate risk IPN.
Developing, evaluating, standardizing, and validating such minimally invasive biomarkers so that they are ready
for clinical use is the goal of the proposed BU-UCLA Lung Cancer Biomarker Characterization Center (BCC). In
previous EDRN-funded work we established lung-cancer associated gene expression patterns in nasal
epithelium collected with a swab from the inferior turbinate as a lung cancer biomarker. A test based on this
innovative approach to lung cancer detection is being launched for clinical use as a CLIA LDT by our long-time
collaborator Veracyte, Inc., which is participating in this BCC. We will evaluate the nasal biomarker for lung
cancer in the setting of intermediate risk IPN. To further improve the ability to clinically discriminate benign from
malignant intermediate risk IPN, the BU-UCLA Lung Cancer Biomarker Discovery Lab embedded within the BCC
will develop and test lung cancer detection approaches that incorporate detection of circulating tumor cells (CTC)
using a CLIA LDT assay from our collaborator LungLife AI, Inc. as well as blood based immune biomarkers,
advanced imaging biomarkers, and refined nasal gene expression biomarkers. We will additionally determine if
longitudinal biomarker assessment improves lung cancer detection over cross-sectional measurements.
Promising assays will be refined, standardized, and validated by the BU-UCLA Lung Cancer Biomarker
Reference Lab embedded within the BCC to advance them toward clinical adoption. These studies are enabled
by biospecimens and imaging data that are being prospectively collected from diverse populations of patients
undergoing workup for intermediate risk IPN in several large-scale ongoing clinical studies including VA LPOP,
DECAMP 1-Plus, and UCLA IDx; lung cancer research programs at UCLA and Lahey; and our EDRN
collaborators at Nashville VA and Vanderbilt. The BU-UCLA Lung Cancer BCC Team has the required multidisciplinary
expertise in lung cancer, translational and clinical pulmonary medicine, biomarker discovery, clinical
assay development, biostatistics, clinical epidemiology, pathology, imaging, artificial intelligence, biological
sciences, bioinformatics, genomics, and complex scientific program management to accomplish these goals. An
Administrative Core embedded within the BCC will ensure that the BCC delivers on its aim to substantially
advance novel lung cancer biomarkers from discovery to clinical application and make significant contributions
to the Early Detection Research Network.

Group

Site ID Investigator Site Name PI Type Member Type
1049 Segal, Leopoldo, M.D. New York University Grossman School of Medicine Contact PI BCC, BDL, BRL
176 Pass, Harvey Ira, M.D. New York University School of Medicine MPI BCC, BRL

Lung cancer remains the leading cause of all cancer mortality. Improved imaging techniques enable the detection of lung cancer at earlier stages, yet a large number of patients with non-malignant lung nodules are frequently subjected to invasive diagnostic approaches. Even though surgical removal of early stage non-small cell lung cancer (NSCLC) is the most effective therapy, post-surgical recurrence of NSCLC remains a significant problem as survival. Currently there are no clinically useful biomarkers that can accurately diagnose the indeterminate nodule or identify those patients destined to have recurrence of cancer after successful surgical removal. Recently, the use of culture-independent techniques to characterize the microbiome by us and others has led to identification of microbial signatures associated with lung cancer diagnosis and prognosis among a cohort with a wide range of disease stages. Preliminary metagenomic data obtained in collaboration with Micronoma using blood samples of our NYU cohort have identified microbial signatures in systemic circulation associated with early-stage NSCLC diagnosis. Further, using a NanoString platform we have identified circulating RNA signatures predictive of early-stage NSCLC diagnosis. In addition, our preliminary data shows that lower airway signatures can be used to predict prognosis post-surgical removal of early stage cancer. These data suggest that microbial and host genomic signatures could be leveraged to develop useful biomarkers in early-stage NSCLC. The addition of metabolite measurements could further contribute to this predictive power since those are end products of microbial and host functions. Under this BCC application we will first identify top microbial/host biomarkers that predict early-stage NSCLC diagnosis and prognosis using blood and lower airway samples from a cohort of patients with lung nodules and a presumed surgical clinical Stage I (<3cm) but with a final histological diagnosis of early-stage NSCLC (TNM  IIIA) or non-NSCLC nodules. We will implement cutting edge bioinformatic approaches to identify the most promising targets from these unbiased omic approach (metagenome, metabolome and transcriptome) which will guide the development of targeted approaches that to be validated under the Biomarker Reference Laboratory. These targeted approaches will include the development of targeted microbial DNA next generation sequencing, targeted metabolite measurement and custom-made NanoString panels as CLIA level assays, internally and externally validated, that will identify patients at highest risk for NSCLC diagnosis and recurrence after complete surgical resection.

Lung and Ovary

Group

Site ID Investigator Site Name PI Type Member Type
523 LaBaer, Joshua, M.D., Ph.D. Arizona State University Contact PI BCC
1032 Stengelin, Martin, Ph.D. Meso Scale Diagnostics Co-Investigator BCC, BRL

The goal of the ASU Biomarker Characterization Center is to improve ovarian and lung cancer screening through
the development of biologically-relevant circulating immune biomarkers. The scientific approach of our Center is
based on several fundamental principles. First, that altered cancer protein expression, structure, and posttranslational
modifications induce host autoantibodies to create circulating biomarkers. Second, that alterations
in microbial antigen expression (such as respiratory pathogens) also induce immunity, often detected in benign
rather than malignant disease. Third, that the protein modifications, as well as the immune response to these
neoantigenic structures, are heterogeneous between people, and that serologic biomarkers may complement
circulating protein biomarkers. We will take a systems immunology approach to discover three types of
antibodies, anti-microbial antibodies, autoantibodies and anti-aberrant glycoprotein antibodies. Our proposal
builds on our extensive experiences with cancer biomarker discovery and immunoproteomics technology
development. Our previous results on autoantibody biomarkers have been confirmed in blinded phase 2
multicenter validation studies and led to a CLIA-certified commercial blood test. Our results have shown that
multiplexed panels of autoantibodies are required for adequate predictive value. With prior EDRN support, we
have developed a set of innovative immunoproteomics technologies, namely high-density nucleic acid
programmable protein array (HD-NAPPA), contra-capture protein array (CCPA) and multiplexed in solution
protein array (MISPA), that, together with the largest full-length human and microbial gene collection at our
DNASU plasmid repository, enable us to study antibodies against the full human proteome, microbial proteomes
and the human O-glycoproteome for antibody biomarker signatures in cancer. Our Meso Scale Diagnostics
(MSD) team has fielded over 3,000 instruments worldwide, and over 700 commercially available biomarker assay
kits. Our expertise at serologic assay development was selected by Operation Warp Speed to use the V-PLEX®
serology panels as the basis of its standard binding assays for immunogenicity assessments in all funded Phase
III clinical trials of COVID vaccines. We will use our MSD MultiArray platform to migrate the top serologic and
protein markers for their utility in our target clinical applications. We will collaborate with experts on lung and
ovarian cancer screening at Vanderbilt University Medical Center, Boston University, MD Anderson Cancer
Center, and German Cancer Research Center, who will also provide access to high-quality well-characterized
samples to develop circulating biomarkers to enhance ovarian cancer screening or to distinguish benign from
malignant pulmonary nodules. Adhering to the principles of PRoBE design, we will perform Phase I discovery by
screening protein arrays with cancer patient and control sera for cancer or control-specific antibodies. Candidate
biomarkers for both lung and ovarian cancers will undergo Phase 2 validation.

Ovary

Group

Site ID Investigator Site Name PI Type Member Type
800 Zhang, Zhen, Ph.D. Johns Hopkins University Contact PI BCC
200 Chan, Daniel, Ph.D. Johns Hopkins Medical Institutions Co-Investigator BCC, BRL

High-grade serous ovarian carcinoma (HGSOC) is the most common histological subtype of epithelial ovarian
cancer. The overarching goal of the proposed Biomarker Characterization Center (BCC) is to apply a bydesign
approach based on biology of HGSOC pathogenesis and unmet clinical needs to identify, verify and
prioritize, and validate biomarkers, and to develop them into an in vitro diagnostic multivariate index assay
(IVDMIA) with the intended use to capture HGSOC in high-risk women at the early stages including i)
precursors, ii) confinement to the ovary/fallopian tube or iii) low-volume diseases in high-risk women (BRCA1/2
carriers). The biomarkers that we propose to discover and validate in this proposal are intended for early
detection but not necessarily for screening in general population. The BCC’s capability in advanced data
generation technologies, multiplexed target assay development, and bioinformatics/data science will serve as
resources for the EDRN. Based on the success of our current EDRN projects, this BCC will continue our ongoing
biomarker development studies including the validation of candidate biomarkers that we have identified
through the current BDL. We propose the following specific aims:
1. To optimize and use novel specimen collection and processing technologies, and an iterative and
cumulative process that takes advantage of our newly gained knowledge of the biology in ovarian cancer
pathogenesis. BDL
2. To optimize and apply innovative bioinformatics, data sciences, and AI/ML tools that incorporate existing
knowledge and data to improve discovery of low frequency biomarkers that with their functionally shared
pathways/networks could collectively deliver an improved sensitivity while retaining a high specificity. BDL
3. To further develop and optimize the process for efficient multiplex targeted assay development with respect
to analytical performance, throughput, and specimen volume requirement for a broad spectrum of
candidate biomarkers using a “fit for purpose” approach. BRL
4. To optimize and apply a by-design approach to translating discoveries into clinical tests. Its application had
been critical in the development of two FDA cleared tests by JHU team members for the preoperative
assessment of ovarian malignancy risk. BDL/BRL
5. To provide expertise and analytical and data science capabilities to the entire EDRN community.
The multi-disciplinary team that we have assembled (molecular cancer biology, pathology, clinical chemistry,
mass spectrometry, biostatistics, data science, bioengineering), the unique, novel yet biologically and
statistically sound approaches, and our long-standing experience in biomarker research and translating
discoveries to FDA cleared clinical tests all together ensure the success of this proposed BCC.

Group

Site ID Investigator Site Name PI Type Member Type
610 Skates, Steven, Ph.D. Massachusetts General Hospital Contact PI BCC
1031 Kulasingam, Vathany, Ph.D. University Health Network Co-Investigator BCC, BRL

A three-decade research program developing, optimizing, and testing an annual blood-based test for the early
detection of ovarian cancer in normal risk postmenopausal women failed to show a cancer-specific mortality
reduction. The likely fundamental reason for the failure is the short window of opportunity provided by a
blood-based signal. The proposed BCC will seek to identify an alternative biospecimen for the source of signal
which has a much greater window of time for detection in early-stage disease so that an annual testing
frequency will have a high likelihood of detecting ovarian cancer during its curable stages. Due to the direct
connection of the uterus to the fallopian tube, where the cell of origin resides, a uterine lavage will likely
contain the earliest biological signals of the presence of ovarian cancer. Identifying a minimal ovarian cancer
signal amongst a much greater background of uterine epithelium cells and cellular material requires a very
sensitive test. Our BCC will build on a recently developed innovative genome-wide methylation test and
combine it with a sensitive antibody based proteomic test. Having optimized the combined test to detect a
signal in uterine lavage, the BCC will determine its sensitivity in Pap smears. The BCC will optimize the
combined test on training uterine lavage samples, validate the test on independent validation cohort of
uterine lavage samples, and assess its performance in Pap smear samples. If the optimized test is sensitive in
Pap smears, then the overall goal of a clinically acceptable and readily performed test (Pap smear) conducted
at a feasible frequency of every 12 months will be a crucial step towards an annual test for the early detection
of ovarian cancer in normal risk postmenopausal women, the population in which 80% of ovarian cancers
occur. The long-term goal is an early detection program resulting in a significant reduction in ovarian cancer
mortality. The intended use of the test developed by the BCC will be as a clinical decision-support tool for
screening normal risk postmenopausal women for early detection of ovarian cancer. Such a test will fill an
unmet health gap since there is currently no early detection test for ovarian cancer.

Prostate

Group

Site ID Investigator Site Name PI Type Member Type
188 Chinnaiyan, Arul M., M.D., Ph.D. University of Michigan Contact PI BCC
1030 Kitchen, John, Ph.D. LynxDx Co-Investigator BCC, BRL
1011 Tosoian, Jeffrey, M.D. Vanderbilt University Medical Center MPI BCC, BRL
1029 Xiao, Lanbo, Ph.D. University of Michigan Co-Investigator BCC, BRL

This application proposes the formation of the Michigan-Vanderbilt University Medical Center (VUMC) EDRN
Biomarker Characterization Center (BCC). This BCC represents a collaborative, multi-disciplinary team of
academic (University of Michigan (U-M) and VUMC) and industry (LynxDx) partners focused on discovering,
developing, and scaling clinical-grade assays for the early detection of aggressive prostate cancer. Through
previous EDRN efforts, our team characterized multiple important prostate cancer biomarkers, most notably the
TMPRSS2-ETS gene fusions. Through collaboration with an EDRN Clinical Validation Center (CVC; Dr. Sanda
PI), we developed, validated, and clinically implemented MyProstateScore (MPS), an early detection test
incorporating urine quantification of two prostate cancer-specific transcripts—the TMPRSS2:ERG gene fusion
and the long non-coding RNA (lncRNA) PCA3. Introduced in our CLIA laboratory, MPS informs shared decision
making after PSA testing based on individualized risk predictions of aggressive prostate cancer on biopsy. Here,
pairing the cancer-specific components of the MPS test with recent discovery of high-grade cancer-specific
biomarkers, we outline the development, optimization, and clinical validation of the next generation of diagnostic
tests – capable of reliably, selectively detecting potentially lethal cancers that stand to benefit from early curative
treatment. Our Biomarker Developmental Laboratory (BDL) will employ the experimental platform, MPS-SEQ,
for capture RNA-seq analysis of urine samples to detect aggressive prostate cancer transcripts, lncRNAs,
circular RNAs, fusion transcripts, mutations, indels, and splice variants. Our Biomarker Reference Laboratory
(BRL) will in parallel develop a clinical grade urine assay, MPS-50, for the multiplex QPCR analysis of up to 50
amplicons. While the first 50 amplicons of MPS-50 have already been nominated, future improvements of the
assay content and platform will be informed by work carried out in our BDL. To fuel these studies, our BCC has
identified urine biospecimen cohorts collected under rigorous standard operating procedures in compliance with
PRoBE criteria including the Michigan Prostate SPORE, Emory University, the Center for Prostate Disease
Research, University of Texas San Antonio Health, Eastern Virginia Medical School, and VUMC/Meharry
Medical College. The overall Aims of this BCC serve to develop, assess, and optimize MPS-SEQ and MPS-50
for identifying high-grade prostate cancer in diverse at-risk populations. Our BRL will also focus on standardizing
clinically-validated biomarker assays for consistent and reliable use in accordance with CLIA/CAP guidelines at
the U-M Center for Translational Pathology in order to facilitate network consortium studies and at LynxDx in
order to scale, commercialize, and obtain FDA approvals. As recognized by the EDRN, novel biomarkers specific
for aggressive prostate cancer are urgently needed. Importantly, our mission and efforts extend beyond our BCC
and prostate cancer, as we actively participate in the EDRN biomarker community and support continued
collaborative efforts with other BCCs and CVCs to advance the overall EDRN mission.

Group

Site ID Investigator Site Name PI Type Member Type
92 Semmes, John, Ph.D. Eastern Virginia Medical School Contact PI BCC
823 Boutros, Paul, Ph.D. The University of California, Los Angeles MPI BCC, BRL

The critical challenge in the clinical management of newly-diagnosed localized prostate cancer remains
distinguishing indolent from aggressive and life-threatening cancers. Biomarkers are urgently needed to
identify those patients who harbor aggressive disease and will derive benefit from definitive treatment. We
therefore, propose to apply complimentary proteogenomic-based discovery approaches to identify and then
validate molecular features in prostate proximal fluids and tumor tissues that will be utilized in accurate early
detection of aggressive forms of prostate cancer and improve disease risk stratification. The intended use of
these biomarkers will be the early identification of men at risk for grade progression and improved riskstratification
for them.
We have three biomarker development laboratory aims: 1) Validate our existing urine-based biomarkers for
grade progression in a ProBE-compliant study selected from our own cohorts and the EDRN GU upgrading
study. 2) Develop and validate urine and tissue-based biomarkers for the risk-stratification of MRI “invisible”
high-grade lesions. 3) Develop and validate biomarkers to sub-stratify risk associated with deleterious
germline BRCA2 variants.
Our biomarker reference laboratory will develop and validate targeted clinically robust assays for multi-protein
biomarkers panels. We will also develop decision algorithms that are cross-referenced for statistical rigor and
benchmarked for optimal clinical performance. In addition to these BCC activities, we will develop robust
PRM-MS assays and statistically rigorous decision tools for other EDRN BCCs and CVCs.
Taken together, our EDRN biomarker characterization center will be a core part of the the EDRN ecosystem.
We will continue to actively participate in trans-Network activities, and to share patient cohorts, protocols,
datasets and analysis approaches and expertise. We will supplement these activities by focusing on
promoting the growth of new and diverse talent in biomarker development through fostering junior investigator
involvement across the full spectrum of biomarker development.

Group

Site ID Investigator Site Name PI Type Member Type
1047 Chan, Daniel, Ph.D. The Johns Hopkins University Contact PI BCC, BRL
108 Chesnut, Gregory, M.D. Center for Prostate Disease Research Uniformed Services University of the Health Sciences and the Walter Reed National Military Medical Center Contact PI BRL

Active surveillance (AS) is the preferred management option for low risk prostate cancer (PCa) patients who would benefit from conservative treatment. However, due to the lack of reliable methods in the initial clinical evaluation to identify true low-risk PCa patients for AS enrollment and during AS monitoring to detect a rising risk of progression, patients who could benefit from conservative management through AS are often over-treated, yet at the same time patients initially chosen for AS with a missed high-risk disease are under-treated. The goal of the proposed EDRN Biomarker Characterization Center (BCC) is to develop and validate in vitro diagnostic multivariate index assays (IVDMIA) that combine a panel of biomarkers into a single-valued numerical index with the intended use for the clinical unmet needs for 1) assisting in the preoperative assessment of PCa aggressiveness and decision for enrollment into AS; and 2) detecting a rising risk of progression during AS to triage patients for additional and possibly more invasive procedures for needed disease reclassification. The objective for the IVDMIA development is to improve specificity while maintaining a high negative predictive value in order to safely enroll more patients with true low-risk PCa into AS and reduce the number of unnecessary biopsies and or costly workup procedures for patients in AS. To achieve this goal, we propose an integrated BCC at the JHU consisting of a multi-disciplinary team including PIs from current EDRN BDL (Dr. Hui Zhang) and BRL (Dr. Daniel W. Chan), and a previous CVC (Dr. Alan Partin). The targeted population is JHU AS patients with >20 years of enrollment and clinical follow-up. Our team has many years of experience in biomarker discovery, verification, validation, and translation into clinical diagnostics and the development of IVDMIA, e.g. OVA1, the 1st proteomics IVDMIA cleared by the FDA (2009). We plan to take advantage of the serum biomarkers already discovered for aggressive PCa from our current BDL and BRL and begin the verification and validation in the targeted AS population by our BRL. In parallel, our BDL will focus on the discovery of new candidate serum, urine and tissue biomarkers by applying cutting edge technologies to the AS population, such as mass spectrometry based high throughput proteomics, protein modifications, and single cell analysis of lasercapture- microdissected tissues. We plan to combine these biomarkers into IVDMIAs. Finally, we will work with our industry partners to translate these IVDMIAs into CLIA certified and/or FDA cleared/approved clinical diagnostics. We believe with these innovative, yet, practical approaches, our BCC offers the best opportunity to make significant contributions to the EDRN network and address the critical clinical unmet needs for PCa patients. If the over-treatment, under-treatment, decrease in unnecessary biopsies, and increase in biopsy accuracy can be successfully addressed, the morbidities associated with PCa diagnosis and treatment can be significantly decreased, while enhancing the detection and treatment of clinically significant PCa. In addition, our BRL, a CLIA and CAP certified clinical laboratory at JHU, will serve as a resource center for the EDRN network.

Clinical Validation Centers

Clinical Validation Centers (CVCs) conduct validation trials on biomarkers discovered/developed by both EDRN and non-EDRN investigators. CVCs also provide high-quality, well-annotated biospecimens to the BDLs for biomarker discovery, development and pre-validation studies. The use of biospecimens collected using rigorous standard operating procedures helps minimize false discoveries.

Breast

Group

Site ID Investigator Site Name PI Type Member Type
593 Li, Christopher, M.D., Ph.D. Fred Hutchinson Cancer Center Contact PI CVC
1021 Partridge, Savannah, Ph.D. University of Washington SOM MPI CVC

There remain clear clinical and public health needs to improve the early detection of breast cancer. While
mammography is an effective tool, there are issues with respect to optimizing its use and performance, and
despite widespread screening breast cancer remains the 2nd most common cause of cancer related death
among U.S. women. Through the current EDRN Clinical Validation Center (CVC) led by Dr. Li we have
validated 15 candidate biomarkers through a series of Phase 2 and Phase 3 validation studies that involved
successive series of three independent sets of preclinical samples. Outside of EDRN funding, Dr. Partridge
has led the development of novel strategies to improve breast cancer detection based on quantitative markers
derived from screening MRIs in high-risk women and application of artificial intelligence (AI) approaches in
collaboration with Microsoft. Our overarching goal is to conduct Phase 2 and 3 validation studies of bloodbased
biomarkers and imaging strategies that will be integrated and jointly assessed in a Phase 4 validation
study. Supporting this goal we propose the following 4 projects: Project 1: Phase 3 validation of early detection
biomarkers for ER+ breast cancer; Project 2: Phase 2 and 3 validation of protein biomarkers for the early
detection of breast cancer discovered using a mass spectrometry-based platform; Project 3: Phase 3 validation
of quantitative markers and AI algorithms applied to MRI screening exams for the early detection of breast
cancer in women at high risk; and Project 4: Phase 4 validation of blood-based biomarkers and imaging
algorithms for the early detection of breast cancer. Additionally, we will provide biospecimens and expertise to
support high quality PRoBE compliant EDRN discovery and validation studies across several cancer types.
With the combined expertise of our multidisciplinary team of investigators and our engagement with key
commercial partners, this CVC will both lead well-justified, rigorously designed validation studies and provide
abundant resources to EDRN. Given the strength of our biomarker candidates, the sets of biospecimens that
will be used, the study designs employed, and the clearly delineated clinical applications proposed, we
anticipate that this work will yield near-term clinical impact.

Colon

Group

Site ID Investigator Site Name PI Type Member Type
664 Bresalier, Bob, M.D. The University of Texas MD Anderson Cancer Center Contact PI CVC
662 Syngal, Sapna, M.D. Dana Farber Cancer Institute-BWH MPI CVC

The Great Lakes New England Clinical Validation Center (GLNE CVC), a Clinical Validation Consortium
component of the Early Detection Research Network (EDRN) is a highly collaborative group of investigators
whose aims to validate biomarkers for the early detection and risk assessment of cancers of the gastrointestinal
tract. In this fifth competitive application, the GLNE continues to test the overall hypothesis that a panel of
circulating and stool based biomarkers will increase the adherence to colorectal screening and in doing so reduce
mortality caused by colorectal cancers. Based on the rising incidence of colorectal cancer (CRC) among adults
age <50 in the US, and the low compliance and high mortality in underserved populations, increased emphasis
is placed on these populations. The GLNE also proposes to continue its ongoing support of EDRN discovery
priorities. We propose to address the following aims: (1) Primary Aim To expand and renew the archive of
appropriately preserved stool, serum, plasma, urine, tissue and DNA biospecimens to be used by EDRN
investigators for current and future validation and biomarker discovery research with expanded inclusion of
subjects with early-onset CRC and underserved populations. This will allow assessment of the utility of individual
stool-based, and serum-based biomarkers and biomarker panels for discriminating between individuals without
neoplasia (subjects both at average and higher risk for developing colon cancer), and those with colon cancer
or screen-relevant neoplasia (cancer plus advanced adenoma), and construction of panels of markers to
discriminate between these groups. (2) To perform validation trials of promising biomarkers discovered by EDRN
investigators, external collaborating institutions and collaborating EDRN industrial partners for the early detection
of colorectal neoplasia. In this context we propose to (a) to clinically validate (via a methods comparison study)
the performance of a point-of-care blood- based biomarker panel with the testing of serum/plasma samples
obtained in clinics serving low-income and underserved communities and (b) to clinically validate an established
4-plex stool protein panel for early diagnosis of CRC. (3) To follow prospectively subjects enrolled in an
established prospective Phase 2 validation trial to identify pre-diagnostic specimens which may be used to
develop predictive markers.

Group

Site ID Investigator Site Name PI Type Member Type
609 Schoen, Robert E., M.D., M.P.H University of Pittsburgh Cancer Institute Contact PI CVC
1020 Tomasetti, Cristian, Ph.D. City of Hope/Tgen MPI CVC

The goal of our Clinical Validation Center (CVC) is to advance and validate blood-based detection of colorectal
advanced adenoma. Whereas blood-based testing for invasive colorectal cancer is progressing, with multiple
companies pursuing products, the ability of blood-based testing to detect advanced adenomas, the premalignant
lesions closest to invasive cancer, is uncertain. To optimally impact colorectal cancer incidence,
blood-based biomarkers cannot just detect cancer, they should also have sufficient sensitivity to identify
subjects with advanced adenomas. For our CVC, we organized and assembled a network of highly skilled
clinical centers including a focus on minority populations, to prospectively collect well-characterized, highquality
blood specimens from a large number of subjects with advanced adenoma prior to undergoing
polypectomy and serially post-polypectomy. From the same clinical centers, we will collect blood specimens
from control subjects. Specimens will be collected and processed using standard protocols, and relevant
demographic and clinical variables will be captured to facilitate biomarker validation studies. Specifically, we
will use these well-characterized specimens to validate our data on the utility of original, innovative techniques
for molecular detection of advanced adenomas including RealSeqS in combination with custom machine
learning algorithms such as SignaL. We propose two Specific Aims. In Specific Aim 1, we will conduct a phase
2 case-control study to validate our novel methods for advanced adenoma detection. We will prospectively
recruit patients with advanced adenoma (N=400) and site-specific control subjects (N=400) for comparison to
the case subjects. In Specific Aim 2, we will utilize serial blood specimens systematically collected postpolypectomy
from our case subjects to determine whether our novel molecular detection techniques can be
used to predict likelihood of recurrence and potentially guide surveillance colonoscopy exams. Advanced
adenomas are the important, next frontier in non-invasive colorectal cancer screening, and our CVC is
equipped to profoundly advance blood-based detection of advanced adenoma.
Contact PD/PI: Schoen, Robert E
Project Summary/

Esophagus

Group

Site ID Investigator Site Name PI Type Member Type
169 Markowitz, Sanford, M.D., Ph.D. Case Western Reserve University Contact PI CVC
1027 Bettegowda, Chetan, B.S., M.D., Ph.D. Johns Hopkins University MPI CVC
1018 Chak, Amitabh, M.D. UH Cleveland Medical Center MPI CVC
347 Shaheen, Nicholas, B.A., M.D., M.P.H. University of North Carolina MPI CVC
1028 Wani, Sachin, M.D. University of Colorado Anschutz Medical Campus MPI CVC
1017 Willis, Joseph, M.D. Case Western Reserve University MPI CVC

This EDRN-CVC proposal is aimed at the validation of molecular biomarkers for distinguishing high versus low
risk esophageal neoplasias (Barrett’s esophagus) for the purpose of guiding selection and management of
patients for endoscopic eradication therapy (EET). Two validation studies are proposed: the first, a phase 4
prospective study to identify a patient group at low progression risk who can be spared EET; the second, a phase
3 retrospective study to distinguish individuals who following EET are at low versus high risk of disease
recurrence. Barrett’s esophagus (BE) is the precursor lesion of esophageal adenocarcinoma (EAC), a cancer
with 80% lethality whose incidence has increased more than 7-fold in the past three decades. BE progresses to
EAC in a step-wise fashion from non-dysplastic BE, to low grade dysplasia (LGD), to high grade dysplasia (HGD),
and finally cancer. EAC prevention is based on using EET to ablate HGD BE before it can progress to EAC.
However, increasingly, EET is also becoming the default therapy for LGD, a highly imprecise diagnosis about
which expert pathologists frequently disagree, and which is applied to as many as 40% of BE patients at some
point during their course. As EET has a 9% complication rate, the result is an emerging epidemic of overtreatment
of BE with LGD. In a prior EDRN-BDL award, our team developed the “BAD” technology for early detection of
BE progression. In BAD, we used a brushing device to sample a patient’s full BE esophageal segment. We then
analyzed the DNA from this sample using next-generation sequencing technology (developed for liquid biopsy
assays) to instead detect presence of BE clones that had acquired gains or losses on specific driver
chromosomes associated with EAC. Detection of driver chromosome changes (dubbed Very-BAD), typified EAC
and HGD. In contrast, 28% of LGD showed complete absence of any chromosomally aberrant clones (dubbed
Not-BAD). We will now validate Not-BAD as a biomarker that identifies LGD at such low progression risk as to
not require EET. We will do this by partnering with the SURVENT trial, that will be the first U.S. prospective study
to follow LGD patients managed by surveillance, not ablation. A second major challenge with EET is that over
25% of patients recur following ablation (with either high risk BE, HGD, or EAC). These patients face a substantial
burden of post-EET surveillance endoscopies, initially at every 3-month intervals. In our prior EDRN-BDL, our
team identified a panel of methylated DNA biomarkers for sensitive molecular early detection of BE (currently
awarded FDA breakthrough device designation). We have further identified that these markers remain retained
in a subset of patients post-EET. We accordingly now propose a retrospective Phase 3 study to further validate
these DNA markers for molecular assessment of minimal residual disease, whose post-EET elimination identifies
individuals achieving complete molecular eradication of BE, and hence at low risk of disease recurrence and not
in need of intense post-EET surveillance. We do this by partnering with the unique UNC-BEECAB biorepository
of post-EET esophageal biopsies from patients whose disease did or did not recur following ablation.

Head and Neck

Group

Site ID Investigator Site Name PI Type Member Type
1045 Anderson, Karen, M.D., Ph.D. Arizona State University MPI CVC
1046 Sturgis, Erich, M.D., M.P.H Baylor College of Medicine MPI CVC

The goal of the EDRN Southwest Clinical Validation Center for Head and Neck Cancer is to improve oropharyngeal cancer screening through the rigorous validation of salivary biomarkers. The scientific approach of our Center is based on several fundamental principles. First, that human papillomaviral (HPV) infection and persistence induces carcinogenesis in the oropharynx over decades, generating well-documented circulating and salivary viral nucleic acid and serologic biomarkers. These biomarkers have not yet been tested in rigorous, prospective studies with centralized CLIA/CAP biomarker validation. Second, the low incidence requires that effective screening paradigms for oropharyngeal cancers (OPC) use novel systems for large-scale prospective studies using self-collection sampling, digital enrollment, and distributive systems to enable enrollment in underserved communities. Third, that the clinical management of positive biomarkers be rigorously addressed. Our proposal builds on our extensive experiences with cancer biomarker development, verification, validation, innovative clinical study management, and expertise in HPV oropharyngeal cancer screening. Our previous results on HPV serologic biomarkers have been confirmed in blinded phase 2 multicenter validation studies. Our results have shown that multiplexed panels of IgG antibodies for HPV16 are required for adequate predictive value. Our Meso Scale Diagnostics, LLC. (MSD®) team has fielded over 3,000 instruments worldwide, and over 700 commercially available biomarker assay kits. Their expertise at serologic assay development led to one of their V-PLEX® serology panels being selected by Operation Warp Speed as the basis of its standard binding assays for immunogenicity assessments in all funded Phase III clinical trials of COVID vaccines. We will use the MSD MULTI-ARRAY® platform to migrate the HPV serologic markers for target clinical applications in saliva. This represents an ongoing collaboration with experts in large-scale self-collection salivary biomarker screening at Arizona State University, experts on head and neck cancer screening at Baylor University Medical Center, and AT Still University (ATSU) School of Dentistry and Oral Health. We will generate high-quality well-characterized samples to validate circulating and salivary biomarkers to enhance oropharyngeal cancer screening. Adhering to the principles of PRoBE design, we will perform Phase 2 validation of HPV serology and nucleic acid testing with cancer patient and control sera and saliva, followed by developing and testing the methodology needed to conduct a prospective Phase 4 salivary screening study. We will provide a resource for expertise and clinical repository for the rigorous validation of salivary and circulating biomarkers for cancer screening.

Liver

Group

Site ID Investigator Site Name PI Type Member Type
726 Singal, Amit, M.D. UT Southwestern Medical Center Contact PI CVC
1019 Kanwal, Fasiha, M.D. Baylor College of Medicine MPI CVC
992 Marrero, Jorge, M.D., M.S. University of Pennsylvania MPI CVC
143 Parikh, Neehar, M.D. University of Michigan MPI CVC

Hepatocellular carcinoma (HCC) is one of the fastest-growing cause of cancer death in the U.S. and it is
projected to be the 3rd leading cause of cancer death in the U.S. by 2040 given the poor effectiveness of current
HCC risk stratification and early detection strategies. Specifically, HCC screening is recommended in all patients
with cirrhosis, despite annual HCC risk varying between 1-4%/year, highlighting a need for risk stratification
biomarkers. HCC screening is performed using abdominal ultrasound and the serum biomarker alpha fetoprotein
(AFP); however, this strategy misses over one-third of HCCs at an early stage and results in screening harms in
many patients. The goal of our Clinical Validation Center for HCC (CVC-HCC) is to validate novel blood and
imaging biomarkers in phase I-III studies to improve HCC risk stratification and early detection.
Translation of HCC biomarkers to practice has been hampered by a dearth of high-quality sample sets including
both stored blood and imaging. Existing sample sets also primarily include patients with cirrhosis from active
viral hepatitis, with limited applicability to contemporary populations who primarily have cured viral hepatitis or
non-viral causes of liver disease. Our CVC will create a contemporary resource with blood and imaging data to
allow for rapid validation of promising biomarkers for HCC risk-stratification and early detection in phase I-III
studies. A specific population in need of better biomarkers is patients with indeterminate liver nodules (ILNs) on
diagnostic CT or MRI, which are observed in over one-fourth of patients undergoing HCC screening and have a
high, yet variable, risk for developing into HCC (annual risk ~6-10%/year). Our group has validated a novel bloodbased
biomarker, PLSec, for risk stratification and a biomarker panel, GALAD, for early HCC detection in patients
with cirrhosis and herein propose to perform a phase II-III biomarker study to evaluate them in patients with ILNs.
Our team includes national leaders in HCC screening, imaging, and biomarker validation. We are leading efforts
to evaluate HCC biomarkers including the EDRN-funded Hepatocellular Early Detection Strategy (HEDS) Study,
NCI-funded Translational Liver Cancer (TLC) Consortium, and CPRIT-funded Texas HCC Consortium. We will
leverage existing infrastructure across five health systems to create two novel resources not offered by the
current sample sets including (1) a biorepository with both blood and imaging data from patients, with and without
HCC, representing contemporary etiologies of liver disease for Phase II studies and (2) a prospective cohort of
patients with ILNs to evaluate HCC risk stratification and early detection biomarkers in Phase III studies using a
prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) design. We will work with the BCCs
and DMCC to evaluate novel biomarkers, facilitating contributions to trans-network projects. Overall, our CVCHCC
will lead to significant advances in phase I-III validation of novel biomarkers for HCC risk stratification and
early detection, areas of need that will facilitate development of well-designed phase IV clinical utility trials.

Lung

Group

Site ID Investigator Site Name PI Type Member Type
240 Grogan, Eric, M.D. Vanderbilt -Ingram Cancer Center Contact PI CVC
863 Deppen, Stephen, Ph.D. Vanderbilt University Medical Center MPI CVC

Lung cancer remains the number one cancer killer in the United States and clinically useful biomarkers are
needed to improve early detection and diagnosis. The objectives of this proposal for our continuing Clinical
Validation Center are to push early lung cancer detection biomarkers into clinical practice while continuing to
serve as a core resource to the EDRN, as well as to our academic and industry partners. Our overall objective
is to demonstrate that biospecimen and imaging biomarkers will provide clinical utility to diagnose lung cancer
by reducing the number of invasive procedures performed for benign disease and the time to diagnosis for
cancer. Aim 1 will seek to demonstrate clinical utility of a combined biomarker and radiomic approach for
providing Indeterminate Pulmonary Nodule (IPN) diagnoses. We will expand the existing lung specimen and
imaging biorepository available to the scientific community, demonstrate the clinical utility of combination
biospecimen and radiomic biomarkers, and validate additional candidate lung cancer risk biomarkers. We will
diversify the population and enhance statistical power by recruiting from existing partnerships funded by prior
EDRN funding: Meharry Medical College and Washington University in St. Louis. We seek to accomplish three
objectives in this aim: 1) to validate the combined approach of hsCYFRA 21-1 cancer biomarker, radiomic
(HealthMyne) biomarker and a Histoplasmosis benign biomarker (MiraVista) in the EDRN Lung Team Project 2
and National Lung Screening Trial reference cohorts, 2) to determine the clinical utility of the Histoplasmosis test
followed by a Combined Biomarker Model (hsCYFRA21-1, radiomics, and Mayo Model) in a Phase 4 randomized
clinical trial and 3) to validate new candidate blood and epithelial biomarkers in Phase 2 and 3 prospectivespecimen-
collection and retrospective-blinded-evaluation (PRoBE) design studies for the early diagnosis of lung
cancer. In Aim 2 we will validate radiomic risk assessment platforms in IPNs and conduct a pilot clinical
implementation trial in screening discovered IPNs. We will leverage the robust bioinformatics infrastructure at
Vanderbilt University Medical Center to capture and deidentify 800 thoracic CT scans in patients with IPNs. A
Lung Cancer Prediction Convolutional Neural Network (LCP-CNN) and the HealthMyne radiomic model will be
compared to each other and against the Lung-RADS categories. We will perform a prospective pilot evaluation
of the best performing model in Lung-RADS category 3 and 4 IPNs. To accomplish Aim 2 we will: 1) compare
the accuracy of LCP-CNN and HealthMyne radiomics 2) determine the LCP-CCN’s ability to reclassify nodules
in screening patients in a prospective clinical implementation pilot study. At the completion of this proposal, we
will have 1) evaluated clinical utility of combining lung cancer biospecimen and imaging biomarkers, 2) developed
a platform within current practice to present an imaging biomarker approach to improve IPN risk assessment,
and 3) enhanced the biorepository resource for the EDRN and collaborative use.

Group

Site ID Investigator Site Name PI Type Member Type
151 Hanash, Samir, M.D., Ph.D. The University of Texas MD Anderson Cancer Center Contact PI CVC

The lung cancer early detection CVC has two main goals: Specific Aim 1 is to develop a bloodbased
biomarker panel for personalized risk assessment, modeled for its cost effectiveness. To
this effect, substantial validation work in phase 3 studies has been done using retrospective
longitudinal cohorts to test the performance of a four-marker protein panel (4MP) as a means to
determine lung cancer risk and need for CT screening. The goal moving forward is to test the
4MP alone and in combinations with other types of markers in the screening setting, using lung
cancer screening cohorts available to the CVC. The resulting marker panel, in combination with
subject characteristics, would identify subjects who are currently not eligible based on USPSTF
criteria that would benefit from CT screening based on their risk, ultimately leading to a utility trial
for which a concept has been presented at a recent EDRN scientific meeting. The utility trial
concept also includes as an objective to test the value of biomarkers in informing subjects who
are currently eligible but not decided to undergo CT screening, about their risk through a decision
sharing process. Specific Aim 2 will test the use of biomarkers and AI for interpretation of CT
images and to personalize the screening frequency and duration. Sub Aim 1 is intended to validate
the macrovasculature surrounding a nodule (vessel number) previously developed as a
biomarker, in an independent screening cohort. Sub Aim 2 is intended to develop a validated
integrative computational model for improved early lung cancer detection that includes bloodbased
biomarkers, CT features such as emphysema, presence or absence of a nodule, small
airways and subject characteristics for interpretation of CT images and to determine screening
frequency. The model will be subjected to a cost effectiveness analysis compared to current lung
cancer screening guidelines.
The CVC represents a multi-institution, multi-investigator effort with expertise in cancer
biomarkers and statistics; pulmonology and lung cancer; epidemiology; radiomics, bioinformatics
and artificial intelligence; and clinical trial design, simulation modeling and cost-effectiveness
analysis. The CVC brings in substantial accomplishments in biomarker discovery and validation
related to lung cancer screening and in CT image analysis. In pursuit of its aims, the CVC has
access to samples from a multitude of cohorts for validation studies.

Group

Site ID Investigator Site Name PI Type Member Type
1044 Velculescu, Victor, M.D., Ph.D. Johns Hopkins University Contact PI CVC
86 Sidransky, David, M.D. Johns Hopkins University MPI CVC

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer. Our groups have pioneered liquid biopsy approaches for detection and characterization of cancer. Recently we have developed a genome-wide approach for analysis of cfDNA fragmentation profiles called DELFI, DNA evaluation of fragments for early interception. We demonstrated that fragmentation profiles of healthy individuals from low coverage whole genome sequencing reflect nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. Through the analysis of cell-free DNA fragmentation patterns, we identified patients with localized cancer and this tool of early detection could result in better patient outcomes. Lung cancer is the most lethal cancer in the world, and its incidence continues to increase worldwide. There is an urgent, unmet clinical need for development of noninvasive approaches to improve cancer screening for high-risk individuals and ultimately the general population. A clear understanding of molecular changes along the pathway of lung tumorigenesis is critical for identifying biomarkers related to carcinogenesis and tumor progression. Biomarker development for early detection of lung cancer has broad clinical applications in screening as well as for distinguishing malignant from benign pulmonary nodules. Tools to better predict the fate of early lesions non-invasively would be invaluable for early detection of lung cancer, when curative approaches are more likely to succeed. Unlike targeted deep sequencing approaches that would be cost prohibitive for broad use in a screening population, our approach is affordable, highly scalable, and may lead to more effective strategies for clinical intervention. The recent intersection of cancer genomics with novel noninvasive blood tests could revolutionize cancer screening. The purpose of our proposed research is to study the origins and molecular characteristics of cell-free DNA fragments along the progression of Lung Cancer, profiling these alterations in preneoplastic lung lesions likely to progress to invasive cancer, and in treatable lung tumors, as well as in normal controls and in benign lesions. We aim to implement new features to further optimize our DELFI molecular test in plasma. The proposed plan is to test and validate our approach in both accrued samples and a prospective lung cancer screening population. Ultimately, this approach already shows great promise as a pan-cancer early detection strategy and we intend to expand our research in this direction in collaboration with other EDRN centers. We envision that these analyses will be rapidly translated into the clinical setting, providing new noninvasive approaches for early cancer detection.

Multiple

Group

Site ID Investigator Site Name PI Type Member Type
816 Heine, John, Ph.D. H. Lee Moffitt Cancer Center & Research Institute, Inc. Contact PI CVC
815 Schabath, Matthew, Ph.D. H. Lee Moffitt Cancer Center & Research Institute, Inc. MPI CVC

An overarching goal of cancer screening is to detect cancer at an early stage while it is localized, treatable, and curable. However, cancer screening is associated with false positives, high rates of indeterminate findings, overdiagnosis, and overtreatment, which are serious limitations that need to be addressed to improve early detection efforts. Because medical imaging is a key component of early detection for many cancers, quantitative imaging/radiomics can provide biomarkers to address many of these limitations with early detection. Our group, Quantitative Imaging Clinical Validation Center at Moffitt Cancer Center (QICVC-MCC), helped pioneer image biomarker approaches leveraged in the prior funding cycle to create the first and only EDRN Clinical Validation Center (CVC) dedicated to the validation of image biomarkers. For breast cancer, we validated several breast density-type risk markers and diagnostic models in women classified as BI-RADS 4, noting the three subcategories within this classification were strong diagnostic markers, and constructed a bio-image repository for this subgroup. For lung cancer, we conducted extensive studies applying conventional radiomics for risk prediction, discrimination between malignant and benign nodules, distinguishing between indolent and aggressive lung cancers, predicting tumor mutations, and predicting treatment response. In this renewal, we will expand our CVC from validated conventional feature-based radiomics as a benchmark to compare end-to-end deep learning (DL) methods, expand to other populations, and implement AI platforms for analyzing breast, lung, and other organ site images. In breast imaging (Aim 1), we will expand our efforts from parametric modeling to machine learning/DL for improved risk, early detection, and diagnostic predictions and continue our data repository developments. In lung imaging (Aim 2), we will expand our efforts from lung cancer screening to incidentally detected nodules and surgically resected early-stage lung cancer. Additionally, in Aim 3 we will seek out additional opportunities within the EDRN to conduct studies of image biomarkers in other organ sites beyond breast and lung (e.g., prostate, pancreas, and cutaneous) to address emerging Network objectives. The EDRN has proven that it is greater than the sum of the individual projects. As such, in Aim 4 we propose to build a repository for the housing and sharing of images, algorithms, radiomics, clinical data, and information on biospecimens. In this CVC renewal, we will systematically validate radiomic features and novel image metrics in the early detection of cancer. This research is significant because such information may be able to complement existing clinical guidelines and lead to new strategies to apply noninvasive image biomarkers. The research of the QICVC-MCC is performed at an NCI-Designated Comprehensive Cancer Center, which is an outstanding environment to conduct such studies given the access to large patient populations and outstanding resources, and the clinical setting to deploy such biomarkers for improved personalized cancer care.

Ovary

Group

Site ID Investigator Site Name PI Type Member Type
236 Bast, Robert C, M.D. The University of Texas MD Anderson Cancer Center Contact PI CVC

Advances in cytoreductive surgery and combination chemotherapy have improved 5-year survival in patients with epithelial ovarian cancer, but the rate of cure remains essentially unchanged over the last two decades. Computer models suggest that detection of ovarian cancer in early stage (I-II) could improve rates of cure by 10-30%. In two major trials, a two-stage strategy where rising values of CA125 analyzed with a Bayesian Risk of Ovarian Cancer Algorithm (ROCA) prompted transvaginal sonography and abnormal imaging prompted surgery proved sufficiently specific to exceed a positive predictive value (PPV) of 10%. With support of the EDRN, 7,869 apparently healthy women have participated in the Normal Risk Ovarian Cancer Screening Study (NROSS) at 11 different sites in the United States with 46,008 CA125 determinations over the last 21 years. Twenty-nine patients have been referred for operations detecting 17 ovarian cancers with 12 (71%) in early stage I or II. In addition, 4 cases of early stage endometrial cancer were detected, yielding a PPV for detecting cancer of 72%. No more than 2-3 operations will be required to detect each case of ovarian cancer. As CA125 is expressed by only 80% of epithelial ovarian cancers, better sensitivity is likely to be achieved with multiple biomarkers. During this grant cycle we have reported that HE4, HE4 antigen-autoantibody complexes, and osteopontin significantly enhance the sensitivity of CA125 for detecting early stage (I-II) disease and have developed a ROCA2 that includes all 4 biomarkers and detects advanced disease 1.4 to 4.8 years earlier than ROCA. We have found elevated levels of anti-TP53 autoantibodies (AA) in 20-25% of patients with ovarian cancer. Titers of anti-TP53 rise 12 months prior to CA125 and 22 months prior to diagnosis in patients where CA125 does not increase. In an EDRN consortium with investigators from Fred Hutchinson Cancer Center, Arizona State University and the Massachusetts General Hospital, we have compared 5 anti-TP53 autoantibody assays and found the RAPID assay most sensitive. Some 28 different AA have been assayed in a standard panel of 952 sera to identify three - TP53, CTAG1, and IL-8 – that can be detected in early stage disease and complement CA125. Over the last two decades, we have collected and preserved 922 blood and 774 tissue samples at the time of initial surgery in patients with ovarian cancers. During the last 6.5 years we have banked 18,754 new serum and plasma samples from the NROSS and provided serum/plasma samples for 11 investigators to test biomarkers for early stage ovarian cancer. We have published 23 peer reviewed articles, reviews and commentaries. A team of 36 investigators and staff will pursue 3 Specific Aims: 1) to conduct the NROSS2 trial to determine the specificity and PPV of a two-stage ovarian cancer screening strategy using a 4 biomarker ROCA2 and a panel of 3 autoantibodies; 2) to evaluate multiple biomarkers for early detection of recurrence or persistence of disease at positive second look operations; and 3) to maintain and share a serum and plasma bank to facilitate evaluation of novel biomarkers for early detection of ovarian cancer.

Pancreas

Group

Site ID Investigator Site Name PI Type Member Type
797 Maitra, Anirban, M.B.B.S. The University of Texas M D Anderson Cancer Center Contact PI CVC

Early detection of pancreatic ductal adenocarcinoma (PDAC) is an area of highest priority and an unmet need
for advancing public health in the United States. Certain sub-groups of patients, such as those with germline
mutations, mucinous pancreatic cysts and new-onset diabetes (NOD) are at higher than average risk for PDAC.
In the immediate prior cycle, our EDRN Clinical Validation Center (CVC) at MD Anderson Cancer Center
(MDACC): (a) facilitated the conduct of the first ever, multi-institutional, blinded “biomarker bakeoff” in PDAC by
providing annotated biospecimens, (b) completed one of the first EDRN-defined Phase 3 biomarker studies in
PDAC using pre-diagnostic samples (Fahrmann et al, Gastroenterology 2021), and (c) served as a conduit for
the implementation of additional EDRN collaborative research initiatives, including a pre-diagnostic PDAC
imaging consortium. Our renewal application represents a Gulf Coast-Great Lakes EDRN Clinical Validation
Center (GCGLEC) in Pancreatic Cancer is comprised of UTMDACC/Lyndon B Johnson Hospital (Harris Health,
TX), Henry Ford Health System (HFHS, Detroit, MI) and Ochsner Health System (OHS, New Orleans, LA) and
has three major objectives: First, to implement a multi-institutional framework for collecting the highest quality
biospecimens from patients with a variety of well-defined pancreatic pathologies (including early stage PDAC,
pancreatic cystic lesions, and other benign pancreatic diseases, such as chronic pancreatitis, benign cysts, and
endocrine tumors of low malignant potential), in order to conduct biomarker validation studies for early detection
of PDAC that conform to EDRN-defined Phase 2 and Phase 3 study design. Current PDAC biomarker studies
typically have sparse representation from racial and ethnic minorities, and therefore a major impetus of the
GCGLEC will be to address the “disparity gap” in biomarker research by obtaining biospecimens from
underrepresented minorities. Second, the GCGLEC will build upon our published Phase 3 study utilizing the
“anchor panel” of CA19-9, LRG1 and TIMP-1, by conducting four additional PRoBE-compliant studies that
incorporate autoantibodies, metabolites and additional protein biomarkers for improving the sensitivity of
diagnosing asymptomatic PDAC without compromising the 99% or greater specificity threshold. These EDRNdefined
Phase 3 studies will be conducted in pre-diagnostic cases and controls obtained from existing cohorts,
including the PLCO, WHI, and the so-called “Harvard cohorts” (NHS, PHS, WHS and HPFS), as well as ongoing
prospective cohorts undergoing accrual, such as the NCI-funded New Onset Hyperglcyemia and Diabetes (NOD)
cohort, and the Early detection Initiation (EDI) in PDAC, a collaboration between PanCAN and the NCI. Third,
the GCGLEC will serve as a “hub” for collaborative activities within and outside the EDRN, including
collaborations with investigators funded by the Pancreatic Cancer Detection Consortium (PCDC), and laying the
foundations for conducting an EDRN-approved multi-institutional “clinical utility” (Phase 4 study) for PDAC early
detection, within a CAP/CLIA environment.
Contact PD/PI: Maitra, Anirban
Project Summary/

Group

Site ID Investigator Site Name PI Type Member Type
156 Brand, Randall E., M.D. University of Pittsburgh Contact PI CVC
607 Batra, Surinder, Ph.D. University of Nebraska Medical Center MPI CVC

Pancreatic adenocarcinoma (PDAC), with an overall 5-year survival of 11%, is the 3rd most common cause of cancer deaths in the United States, despite accounting for only 2% of all malignancies. Only a minority of patients (~11%) are diagnosed with “localized” disease (I or IIA), which has a 5-year survival rate of about 40% in setting of a node-negative, margin negative pancreatic resection. An obvious strategy for improving the dismal survival would be to detect PDAC when localized and thus at a more curable stage. Since screening the general population for PDAC is not feasible, current efforts have focused on identifying a subset of the people at an increased risk for PDAC development. Currently, only up to 25% of individuals who develop PDAC are candidates for pancreatic cancer surveillance. About 10% are individuals with a strong family history or a combination of family history and germline mutations associated with the risk of PDAC development. The other ~15% are individuals with cystic neoplasms of the pancreas, including IPMNs and MCNs. The inability to predict the malignant transformation of mucinous cysts and thus identify the cysts that should be surgically removed requires appropriate surveillance. Despite developing multiple consensus guidelines on managing cystic lesions, it is still challenging to determine which mucinous cysts will undergo malignant transformation. During the previous funding cycle, we identified and evaluated novel serum biomarker panels comprising mucins (MUC4, MUC5AC), mucin-associated glycoepitopes (STRA), TGM2, THSP2, TIMP2, and autoantibodies that were validated in a blinded case-control cohort aimed at detecting resectable PDAC. Preliminary mutational profiling of pancreatic cyst fluid (phase I and II) identified a unique panel (PancreaSeq) that helped define the malignant risk of pancreatic cysts. The goal of the current Clinical Validation Center (CVC) is to validate further these panel(s) in a prospective-specimen-collection, retrospective-blinded-evaluation (PRoBE) compliant manner in cohorts of high-risk individuals who are current or potential candidates for early detection or diagnosis of PDAC. Aim 1 will validate cyst fluid and blood-based biomarkers in patients with cystic lesions to identify advanced precursor lesions and differentiate low-grade dysplasia and no lethal potential. In this aim, we will validate candidate biomarkers, including PancreaSeq mutational panel (Phase 3), inflammatory markers (Phase 2), and mucins (MUC4, MUC5AC, STRA) (Phase 3) in the cyst fluid (high specificity) and serum samples (high sensitivity) to identify interval malignancy during surveillance imaging. Aim 2 will evaluate the performance of optimized biomarker panel(s) for early detection of malignant disease in patients with a hereditary predisposition undergoing surveillance for PDAC development and in patients with new-onset diabetes and chronic pancreatitis, defined as within two years of initial diagnosis, who are at a significantly increased risk compared to the general population for having an undiagnosed PDAC. Impact: The proposed studies will validate the clinical utility of promising biomarker panels for early detection of PDAC and risk stratification of pancreatic cystic lesions, which can be used in phase IV clinical utility studies.

Prostate

Group

Site ID Investigator Site Name PI Type Member Type
742 Sanda, Martin, M.D. Emory University CVC

We hypothesize that new biomarkers to refine selecting men for prostate biopsy, together with imaging innovations to refine biopsy targeting, will enhance prostate cancer early detection by reducing unnecessary biopsy and over-detection of indolent disease. With this goal, we assembled biospecimen and imaging data via rigorous SOP’s in pre-biopsy cohorts designed to avoid bias. We provided specimens and guidance on PRoBE adherence to EDRN Labs, NIH Consortia (eg SPOREs) and industry and co-led, in prior cycles, EDRN studies that facilitated FDA approval of the Prostate Health Index (phi) and urinary PCA3. In the current cycle, we enrolled 3,263 subjects and distributed 27,072 biospecimens to 25 PI’s leading to 56 publications. Our multicenter phase III validation of an algorithm combining urinary PCA3 and TMPRSS2:Erg (T2:Erg) measurement validated the cost-effectiveness of this biomarker combination. We then showed significant benefit of sequentially testing blood phi followed by conditional urine PCA3 and T2:Erg testing. Further, we partnered with a commercial collaborator having expertise in bringing tissue RNA assays to regulatory approval and clinical use, to complete whole transcriptome urinary RNA expression analysis in a multi-center case-control cohort of 587 men, resolving a 33-gene predictive model that significantly improved prediction of aggressive prostate cancer compared to PSA, clinical factors, or urinary PCA3 and T2:Erg. To advance prostate cancer imaging, we completed a phase II validation study using the radiotracer fluciclovine (FACBC) in PET-CT to characterize aggressiveness of prostate cancer at initial diagnosis (to our knowledge, this was first completed American validation study of FACBC PET-CT for primary, untreated, early stage prostate cancer). For this renewal, we expand our inclusiveness by adding UAB and UTSW (which, with Emory, enrolled the majority of African-Americans in EDRN’s Prostate MRI trial). For this resubmission, two biomedical engineering investigators expert in Artificial Intelligence (AI) have joined our CVC, who bring preliminary data supporting a rigorously developed, retrospectively validated deep-learning MRI AI nomogram to predict PCa on biopsy that is poised for prospective validation. Based on the combined preliminary data in urinary RNA biomarkers, MRI AI, and PET imaging from our expanded CVC team, we now propose the following Aims: 1) To validate, by nested case-control study using PROBE design, the performance of a 33-gene urinary RNA panel in predicting aggressive prostate cancer on biopsy; 2) To validate a deep learning-based nomogram using MRI AI to predict aggressive prostate cancer on biopsy 3) To evaluate the performance of PET-MRI in the detection of clinically significant prostate cancer; 4) To conduct, with CISNET, cost-effectiveness evaluation of the impact of these new biomarker, imaging and detection techniques. Finally, we commit to continuing to serve as a Collaborative Resource for the EDRN, through leadership and participation in Set-Aside and Core Collaborative Studies and provision of biospecimens and blinded clinical data to EDRN BCC’s and other collaborating biomarker labs.

Data Management and Coordinating Center

The Data Management and Coordinating Center (DMCC) works with the CVCs to conduct biomarker validation trials. The DMCC assists with protocol design, monitors the trial, and maintains the data and biospecimen tracking system. The DMCC is responsible for analyzing the results of the trials, thereby reducing bias as they are independent from the laboratories that discovered the biomarkers. The DMCC provides statistical advice to the BDLs, develops theoretical and applied approaches for simultaneous analysis of multiple markers, and collaborates with the EDRN Informatics Center.

DMCC

Site ID Investigator Site Name PI Type Member Type
5 Feng, Ziding, Ph.D. Fred Hutchinson Cancer Center Contact PI DMCC
782 Etzioni, Ruth, Ph.D. Fred Hutchinson Cancer Center MPI DMCC
1012 Zheng, Yingye, Ph.D. Fred Hutchinson Cancer Center MPI DMCC

The key for the Early Detection Research Network (EDRN)'s success lies in good communication among scientists in multiple disciplines; efficient evaluation and prioritization of promising biomarkers; and rigorous validation studies to demonstrate their clinical utility. The overall aims of the proposed renewal of the Data Management and Coordinating Center (DMCC) are to (i) provide coordination of EDRN in order to enhance communication and collaboration among EDRN investigators and with general scientific communities; (ii) coordinate EDRN validation studies and provide leadership in data science; (iii) disseminate cancer biomarker information to broader scientific communities and the public; and (iv) manage the EDRN Core funds. Under the direction of the EDRN Steering Committee, the DMCC will 1) perform network coordination and outreach and promote collaborations among scientific investigators by providing support for EDRN meetings and workshops, developing and maintaining EDRN secure websites and listservs, producing and maintaining all EDRN documents, and maintaining the online review system for applications submitted to the EDRN; 2) support EDRN validation studies by developing and maintaining validation study data management systems; working with EDRN investigators on study design, protocol development, data forms, and study manuals; coordinating and monitoring studies; tracking specimens; and performing QA/QC and study evaluation; and provide and promote best statistical and computational practices to EDRN studies; 3) work with the NCI and JPL to provide informatics resources for the EDRN Secure Web site for data security, data warehousing, and data sharing, and a Public Web site for dissemination; and 4) work closely with the EDRN SC and the NCI Project Coordinator and Fred Hutch OSR to timely activate the core funds after the EDRN SC approval and ensure the compliance of all regulatory requirements for sub-award management.

Informatics Center

The Informatics Center, provided by the Jet Propulsion Laboratory, pioneers data science software, systems, tools, and data-driven methodologies, serving the data capture, management, sharing, and analysis needs to enable a national biomarker data ecosystem.

Site ID Investigator Site
128 Crichton, Dan NASA Jet Propulsion Laboratory

National Cancer Institute

The National Cancer Institute is the hub of the Early Detection Research Network.

Site ID Investigator Site
87 Srivastava, Sudhir National Cancer Institute

Associate Members

This section lists associate EDRN members.

Associate Member A — EDRN Funded

Site ID Investigator Site
262 Beer, David University of Michigan Medical School
153 Beretta, Laura Fred Hutchinson Cancer Center
520 Bianchi, Laura K. NorthShore University HealthSystem
702 Blasutig, Ivan University of Toronto
158 Diamandis, Eleftherios P. Mount Sinai Hospital
1121 Douville, Christopher Johns Hopkins University
159 Elsaleh, Hany University of California Los Angeles
840 Fan, Jia Tulane School of Medicine
199 Fedarko, Neal S. Johns Hopkins School of Medicine
261 Gite, Sadanand Ambergen Inc.
225 Goldman, Radoslav Lombardi Comprehensive Cancer Center
685 Guerrero-Preston, Rafael Johns Hopkins University School of Medicine
413 Hazelton, William Donald Fred Hutchinson Cancer Center
849 Hoque, Mohammad Johns Hopkins University School of Medicine
414 Jiang, Feng University of Maryland Baltimore
164 King, Bonnie L. Stanford University
165 Livneh, Zvi Weizmann Institute of Science
168 Luduena, Richard F UT Health Science Center San Antonio
578 Macoska, Jill University of Massachusetts Boston
266 Mor, Gil Yale University
508 Mori, Yuriko Johns Hopkins University School of Medicine
173 Mutter, George L. Brigham and Womens Hospital
177 Patz, Edward Duke University Medical Center
948 Pisanic, Thomas Johns Hopkins University
850 Rao, Jianyu University of California at Los Angeles
340 Ressom, Habtom W. Lombardi Comprehensive Cancer Center
474 Schmittgen, Thomas The Ohio State University College of Pharmacy
590 Selaru, Florin Johns Hopkins University School of Medicine
181 Simeone, Diane M. University of Michigan
186 Veltri, Robert W. Johns Hopkins University
312 Weiss, Robert University of California Davis
331 Zeng, Gang University of California Los Angeles

Associate Member B

Site ID Investigator Site
127 Adam, Bao-Ling Medical College of Georgia
884 Al baghdadi, Tareq Trinity Health Ann Arbor Hospital
416 Allen, Peter J. Duke University
453 Aparicio, Belen Instituto Valenciano de Infertilidad
889 Barocas, Dan Vanderbilt University
146 Befeler, Alex Saint Louis University
531 Berg, Christine National Cancer Institute-PLCO
1054 Bhan, Irun Massachusetts General
939 Bregar, Amy Massachusetts General Hospital
846 Brenner, Hermann DKFZ-German Cancer Research Center
424 Brooks, James D. Stanford University Medical Center
538 Buechler, Joe Biosite Incorporated
529 Busby, Erik Greenville Health System
987 Buxbaum, James University of Southern California
248 Califano, Joseph Johns Hopkins Medical Institute
426 Carroll, Peter R. University of California San Francisco
671 Carroll, Robert University of Illinois at Chicago
979 Casu, Anna AdventHealth Translational Research Institute
1053 Chalasani, Naga Indiana University
68 Chia (Retired), David University of California Los Angeles
962 Cole, John T Ochsner Medical Center
997 Cooperberg, Matthew SF VA
680 Coverley, Dawn University of York
858 Craik, Charles University of California San Francisco
1024 Crockett, Seth Oregon Health Science University
978 Curtis , Amarinthia (Amy) Spartanburg Regional Health Services
859 Das, Koushik Washington University
131 Diaz-Mayoral, Norma Frederick National Laboratory for Cancer Research
442 Digel, Jon Fred Hutchinson Cancer Center
682 DiMaio, Christopher Mount Sinai Medical Center
814 Drescher, Charles Fred Hutchinson Cancer Center
670 Eisenberg, Marcia LabCorp Molecular Biology & Pathology
443 El-Zein, Randa The University of Texas MD Anderson Cancer Center
998 Fabrizio, Michael Eastern Virginia Medical School
864 Farrell, James J Yale
877 Fisher, William Baylor College of Medicine
854 Garcia, Christine Kaiser Permanente San Francisco Medical Center
311 Gaston, Sandra M. University of Miami Miller School of Medicine
851 Gilbert, Lucy McGill University
428 Gleave, Martin University of British Columbia
238 Godwin, Andrew K University of Kansas Medical Center
1118 Goel, Ajay City of Hope
857 Goggins, Michael Johns Hopkins
676 Grady UW, William University of Washington
491 Groskopf, Jack Hologic Gen-Probe Incorporated
879 Hart, Philip The Ohio State University Wexner Medical Center
546 Hoerres, Mike Source MDx
867 Hu, Jim Weill Cornell Medicine-Urology
878 Hughes, Steven University of Florida
589 Isaacs, William Johns Hopkins University
870 Jones, Monica Luminis Health Anne Arundel Medical Center
449 Kalloger, Steve E. Kalloger Consulting
417 Kaul, Karen NorthShore University HealthSystem
125 Kibel, Adam Brigham and Womens Hospital
977 Kwon, David S Henry Ford Health System
516 Laird-Offringa, Ite University of Southern California/Norris Cancer Center
519 Lam, Stephen British Columbia Cancer Agency
518 Lam, Wan British Columbia Cancer Research Centre/Cancer Genetics and Development Biology
785 Lamb, Carla Lahey Hospital and Medical Center
88 Leach, Robin J University of Texas Health Science Center at San Antonio
1116 Li, Debiao Cedars Sinai
142 Lin UW, Daniel W. University of Washington
441 Lin VA, Daniel W. VA Medical Center Seattle
949 Liss, Michael The University of Texas Heath Science Center, San Antonio
197 Lok, Anna University of Michigan
525 Lotan, Yair UT Southwestern Medical Center at Dallas
1120 Majumder, Shounak Mayo Clinic
545 Martin, Frances Eastern Virginia Medical School
332 Mathew, Anu Meso Scale Diagnostics
779 Mazumder, Raja George Washington University
899 McClure, Tim Cornell University
198 McConnell, Daniel S. University of Michigan
677 McGills, Sarah University of North Carolina
1056 Mehta, Neil University of California San Francisco
605 Mercola, Dan University of California Irvine
222 Monnig, William B. The Urology Group
110 Moon, Chulso Cangen Biotechnologies Inc.
596 Mosquera, Juan Miguel Weill Cornell Medical College-Central Review
429 Nelson, Peter S Fred Hutchinson Cancer Center
147 Nguyen, Mindie Stanford University
713 Norman, Gary L. INOVA Diagnostics Inc.
890 Olumi, Aria Beth Israel Deaconess Medical Center
975 Onitilo, Adedayo A Marshfield Clinic Health System
876 Pandol, Stephen Cedars Sinai Medical Center
775 Parekh, Dipen J University of Miami Miller School of Medicine
684 Park, Walter Stanford University
1113 Pavlovich, Christian Johns Hopkins University
976 Pisegna, Joseph R VA Greater Los Angeles Healthcare System
943 Pow-Sang, Julio H. Lee Moffitt Cancer Center and Research Institute, inc.
709 Prichard, Jeffrey Geisinger Health System
866 Punnen, Sanoj University of Miami
777 Punnen, Sanoj Miami Veterans Affairs Hospital
887 Rais-Bahrami, Soroush University of Alabama at Birmingham
148 Reddy, Rajender University of Pennsylvania
852 Risques, Rosana University of Washington
145 Roberts, Lewis Mayo Clinic
498 Robinson, Bruce University of Western Australia
84 Rom, William New York University School of Medicine
1119 Rosenthal, Michael Dana Farber Cancer Institute
710 Rowland Jr., Kendrith Carle Cancer Center
845 Ruffin, IV, Mack T. Hershey-Penn State Medical Center
880 Saeed, Zeb Indiana University
1057 Salgia, Reena Henry Ford Helath System
938 Salk, Jessie TwinStrand
833 Sanda, Martin Emory University School of Medicine
1055 Satapathy, Sanjaya Northwell
121 Schoenberg, Mark P. Johns Hopkins University
144 Schwartz, Myron Mount Sinai Hospital
672 Shaukat , Aasma University of Minnesota
1040 Shaukat, Aasma NYU Langone
856 Singhi, Aatur University of Pittsburgh
944 Sonn, Geoffrey Stanford University Medical Center
743 Stark, Azadeh Henry Ford Health Systems
450 Steffensen, Karina Dahl Vejle Hospital
661 Stoffel, Elena University of Michigan
940 Stone, Rebecca Johns Hopkins University
946 Symonds, Erin Flinders Centre for Innovation in Cancer
614 Takacs, Laszlo Biosystems International SAS
927 Teshima, Christopher St Michael's Hospital
868 Tewari, Ashutosh Icahn School of Medicine at Mt. Sinai
517 Tewari, Muneesh Fred Hutchinson Cancer Center
194 Thorlacius, Steinunn Iceland Genomics Corporation
446 Troyer, Dean Eastern Virginia Medical School
881 Van Den Eeden, Stephen Kaiser Permanente Northern California
875 Vege, Santhi S. Mayo Clinic
1117 Von Hoff, Daniel Translational Genomics Research Institute
776 Vuskovic, Marko San Diego State University
203 Wagner, Andrew Beth Israel Deaconess Medical Center
886 Watts, Kara Montefiore Medical Center
918 Wei, John University of Michigan Pathology
510 Wei, John University of Michigan Recruiting
765 Weight, Christopher Cleveland Clinic
865 Willey, James University of Toledo College of Medicine
974 Williams, Heather University of Arkansas for Medical Sciences
961 Winick, Jeffrey Wako Diagnostics/Fujifilm
882 Wu, Bechien Kaiser Permanente Southern California
969 Young, Graeme Lab – Flinders Centre for Innovation in Cancer
994 Zaghiyan, Karen Cedars Sinai Medical Center
1058 Zhou, Kali University of Southern California
83 Johns Hopkins University Department of Urology

Associate Member C

Site ID Investigator Site
599 Backman, Vadim Northwestern University
63 Barker, Peter E. National Institute of Standards and Technology
922 Barton, Jennifer The University of Arizona
65 Bigbee, William L. University of Pittsburgh Cancer Institute
452 Birrer, Michael University of Arkansas for Medical Sciences
66 Block, Timothy Drexel University College of Medicine
187 Cairns, Paul Fox Chase Cancer Center
945 Chari, Suresh The University of Texas MD Anderson Cancer Center
69 Costa, Jose Yale University School of Medicine
70 Cramer, Daniel Brigham and Womens Hospital
985 Cuzick, Jack Queen Mary University of London/Wolfson Institute of Preventative Medicine
71 Czerniak, Bogdan The University of Texas MD Anderson Cancer Center
202 Engstrom, Paul Fox Chase Cancer Center
189 Esserman, Laura J. University of California at San Francisco
1022 Fernandez, Facundo M. Georgia Institute of Technology
150 Fishman, David Mount Sinai Medical Center
73 Franklin, Wilbur Alan University of Colorado Health Science Center
341 Franklin2, Wilbur The University of Texas MD Anderson Cancer Center
74 Gazdar, Adi UT Southwestern Medical Center
455 Getzenberg, Robert Johns Hopkins University
579 Golubnitschaja, Prof. Dr. Olga Rheinische Friedrich-Wilhelms-Universitat
75 Grizzle, William E. University of Alabama at Birmingham
161 Haab, Brian Van Andel Research Institute
77 Helzlsouer, Kathy Johns Hopkins University
190 Hollingsworth, Michael University of Nebraska Medical Center
409 Huflejt, Margaret E. New York University School of Medicine
162 Jendoubi, Moncef Milagen Inc.
163 Khan, Seema A. Northwestern University Feinberg School of Medicine
191 Killary, Ann M. The University of Texas MD Anderson Cancer Center
283 Kim, Nam diaDexus
592 Lampe, Paul Fred Hutchinson Cancer Center
821 Lewis, Michael Baylor College of Medicine
192 Liu, Alvin Y. University of Washington
1023 Livi, Carolina Akadeum Life Sciences, Inc.
167 Lokshin, Anna University of Pittsburgh Cancer Institute
260 Lubman, David University of Michigan Medical School
80 Lynch, Henry Creighton University
989 Madabhushi, Anant Case Western Reserve University
81 Marks, Jeffrey Duke University Medical Center
231 McIntosh, Martin Fred Hutchinson Cancer Center
82 Meltzer, Stephen Johns Hopkins University
309 Morre, D. James NOX Technologies
580 Ostroff, Rachel SomaLogic
993 Putcha, Girish Independent Consultant
180 Rittmaster, Roger S. GlaxoSmithKline
781 Rosser, Charles J University of Hawaii Cancer Center
193 Roy, Hemant K. Boston University
608 Sen, Subrata The University of Texas MD Anderson Cancer Center
798 Showe, Louise C. Wistar
601 Spira, Avrum Boston University
85 Spitz, Margaret R. The University of Texas MD Anderson Cancer Center
820 Tang, Cha-Mei Creatv MicroTech Inc.
89 Tockman, Melvyn S. H. Lee Moffitt Cancer Center
817 Tomlins, Scott University of Michigan
90 Trock, Bruce Johns Hopkins Medical Institutions
91 Unger, Elizabeth R. Centers for Disease Control
284 Wolfert, Robert Metabolon
233 Zangar, Richard (Rick) C. Pacific Northwest National Laboratory
93 Zhao, Yingming UT Southwestern Medical Center
67 University of Michigan

SPOREs

Site ID Investigator Site
343 Canto, Marcia Johns Hopkins University
348 Ding, Ivan National Cancer Institute
247 Jett, James R Mayo Clinic
237 Partridge, Edward E University of Alabama
346 Sampliner, Richard University of Arizona
239 Ujhazy, Peter National Cancer Institute
235 Urban, Nicole Fred Hutchinson Cancer Center
345 Wang, Kenneth K Mayo Rochester
344 Wolfsen, Herbert Mayo Jacksonville

Non-EDRN Sites

Site ID Investigator Site
751 Abbott, Karen Florida International University
999 Adams, Eddie Micronoma, Inc.
708 Berenberg, Jeffrey Tripler Army Medical Center
1038 Burns, Kathleen Dana-Farber Cancer Institute
926 Chilkoti, Ashutosh Duke University
1092 Despa, Florin University of Kentucky
454 Disis, Mary L University of Washington
793 Dolan, Nancy Northwestern University Feinberg School of Medicine
1090 Fahrmann, Johannes The University of Texas MD Anderson Cancer Center
602 Gambhir, Sam Stanford University
509 Giannelli, Gianluigi University of Bari
788 Hemken, Philip M Abbott Diagnostics R&D
515 Hirschowitz, Edward University of Kentucky
780 Honda, Kazufumi Nippon Medical School
929 Johnson, Bruce Dana Farber Cancer Institute
1043 Jung, Giman Toray International
1111 Khammanivong, Ali Oncodea
794 Konda, Vani University of Chicago
1041 Levy, Samuel Bluestar Genomics
931 Lidgard, Graham Exact Sciences
420 Listwin, Don Canary Foundation
803 Maragh, Samantha National Institute of Standards and Technology
891 Matrisian, Lynn Pancreatic Cancer Action Network
786 McKenney, Jesse Cleveland Clinic
1000 Mehta, Anand Medical University of South Carolina
772 Mukherjee, Pinku CanDiag Inc
885 Nilsson, Anki Glycobond
643 Nissenberg, Merel Grey NASPCC/Mountain Foundation For Lung Cancer
615 Norton, Larry Memorial Sloan Kettering Cancer Center
920 Ohtsuki, Sumio Kumamoto University
930 Olopade, Funmi University of Chicago
996 Pettersson, Kim University of Turku
932 Philip, Reena Food and Drug Administration
928 Polyak, Kornelia (Nelly) Dana Farber Cancer Institute
1025 Pozo Mendoza, Oscar J Institut Hospital de Mar d' Investigacion Mediques
646 Qu, Kevin Quest Diagnostics
1004 Schenk, Jeannette Fred Hutchinson Cancer Center
711 Tuszynski, George Temple University
457 Valcour, Andre Lab Corps
947 Villanueva, Augusto Icahn School of Medicine at Mt. Sinai
1039 Walt, David Brigham and Women's Hospital
522 Wilson, Michael S. EIC Laboratories Inc.
647 Yamada, Hiro Wako Diagnostics
718 Yost, Kathleen Grand Rapids Clinical Oncology Program
1112 Zhou, Xianghong (Jasmine) University of California, Los Angeles
728 Research Advocacy Network

Advancement of Head and Neck Cancer Early Detection Research (AHEAD)

Site ID Investigator Site
1095 Alexandrov, Ludmil B. University of California, San Diego
1104 Amelio, Antonio Luigi H. Lee Moffitt Cancer Center
1099 Chinn, Steven Bennett University of Michigan
1109 Cortes, Michelle National Institutes of Health
1103 Giuliano, Anna R. H. Lee Moffitt Cancer Center
1096 Gutkind, Silvio University of California, San Diego
1098 Lei, Yu Leo University of Texas M.D. Anderson Cancer Center
1105 Li, Hua Washington University
1097 Lippman, Scott M. University of California, San Diego
1108 Melillo, Amanda National Institute of Dental and Craniofacial Research
1101 Momen Herav, Fatemeh Columbia University
1093 Pai, Sara Isabel Yale University
1102 Rozek, Laura Georgetown University
1100 Wang, Thomas D. University of Michigan
1106 Wang, Xiaowei University of Illinois Chicago
1094 Weissleder, Ralph Massachusetts General Hospital
1107 Zhong, Chen National Institute of Dental and Craniofacial Research