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Proteomic Approach for Diagnostic Applications in Head and Neck Cancer

243
Tainsky, Michael A.Karmanos Cancer Institute
Autoantibodies
Case/control
Other, Specify
Lung and Upper Aerodigestive Cancers Research Group

To evaluate the test characteristics of a panel of biomarkers for identifying patients with early stage head and neck squamous cell carcinoma (HNSCC). The primary endpoints are sensitivity, specificity and accuracy of the marker panel. This study of the test characteristics of a modeling strategy for diagnosing HNSCC uses a case-control design, with several types of cases and several types of controls.

AIM 1: Eliminate nonspecific antigen biomarkers that cross-react with sera from patients with nonmalignant head and neck diseases, autoimmune diseases and other types of cancers. AIM 2: Validate this diagnostic strategy for early HNSCC detection based on pattern of serum immunoreactivity against the biomarker panel. AIM 3: Assess the use of this diagnostic strategy for early detection of HNSCC in collaboration with other EDRN and non-EDRN sites.
We are using IgG molecules specific to cancer patients as a bait to clone antigens derived from phage T7 display cDNA libraries of mRNA from tumor tissue that we use as biomarkers for the early detection of cancer. In a sense we are using the immune system as a biosensor. The immune system elaborates antibodies which we detect as they react with the antigens we clone. The antigens are expressed and then robotically spotted on microarrays. The microarrays are treated with sera from other patients and the binding of IgGs in those sera is used to find the most commonly reactive antigens. We print replicates of thousands of antigens on the microarrays and analyze them with a two-color detection system. The patients' IgGs bound to the spotted antigens are detected using a secondary antibody against human IgG labeled with Alexa-647, a red dye. The second color provides a control for each spot. We use a monoclonal antibody to the N-terminal 11 amino acids of phage backbone protein onto which each antigen is cloned as a fusion protein. That monoclonal antibody is detected with an Alexa-532 (green dye) labeled antibody against murine IgG. The dye ratios provide a control for variations in spotting so as to quantitate the IgG binding to each clone using sera of each patient. We also have a negative control clone that contains no additional amino acids in the cloning vector. The dye ratios on the chips are normalized and those data used in a t-test using sera from patients and healthy controls. Those clones significant in a t-test are used on a validation set of patients and controls not including the previous training samples. The antibody binding data of those subjects in the validation set are tested using machine learning techniques such as neural networks and n-fold cross validation to determine the accuracy of the classifiers.

There are currently no biomarkers annotated for this protocol.

No datasets are currently associated with this protocol.


2015 Steering Committee Meeting

The next EDRN Steering Committee Meeting will take place March 31st through April 2nd, 2015, in Atlanta, Georgia.

Announcement 12/02/2014

New Round of EDRN FOAs

The RFAs for EDRN have been released:
- Biomarker Developmental Laboratories (U01),
- Clinical Validation Centers (U01),
- Biomarker Reference Laboratories (U24),
- Data Management and Coordinating Center (U24).

EDRN Renewal flyer NOTE-New receipt deadline for applications submitted for all EDRN FOAs is January 20, 2015, by 5:00 PM local time of applicant organization.

There will be a Pre-Application webinar to discuss each of the four individual EDRN FOAs on Tuesday, December 2nd, 2014, from 1pm-5pm (Eastern). Potential applicants interested in participating in the webinar should send a message to Dr. Sharmistha Ghosh (ghoshjanjigias@mail.nih.gov) no later than 5:00 p.m. (EST) November 21, 2014. Please mention the FOA of interest in the subject line.

Announcement 10/07/2014

EDRN Patient Advocates will host an EDRN Advocacy Educational Webinar, Biomarkers for Prostate Cancer Detection and Monitoring, on Monday, January 12th, 2015, at 1 p.m. EDT / 10 a.m. PDT. Registration is not required for this. Please click for more information.