Prevalidation of salivary biomarkers for oral cancer detection.

Abstact

Oral cancer is the sixth most common cancer with a 5-year survival rate of approximately 60%. Presently, there are no scientifically credible early detection techniques beyond conventional clinical oral examination. The goal of this study is to validate whether the seven mRNAs and three proteins previously reported as biomarkers are capable of discriminating patients with oral squamous cell carcinomas (OSCC) from healthy subjects in independent cohorts and by a National Cancer Institute (NCI)-Early Detection Research Network (EDRN)-Biomarker Reference Laboratory (BRL).

Three hundred and ninety-five subjects from five independent cohorts based on case controlled design were investigated by two independent laboratories, University of California, Los Angeles (Los Angeles, CA) discovery laboratory and NCI-EDRN-BRL.

Expression of all seven mRNA and three protein markers was increased in OSCC versus controls in all five cohorts. With respect to individual marker performance across the five cohorts, the increase in interleukin (IL)-8 and subcutaneous adipose tissue (SAT) was statistically significant and they remained top performers across different cohorts in terms of sensitivity and specificity. A previously identified multiple marker model showed an area under the receiver operating characteristic (ROC) curve for prediction of OSCC status ranging from 0.74 to 0.86 across the cohorts.

The validation of these biomarkers showed their feasibility in the discrimination of OSCCs from healthy controls. Established assay technologies are robust enough to perform independently. Individual cutoff values for each of these markers and for the combined predictive model need to be further defined in large clinical studies.

Salivary proteomic and transcriptomic biomarkers can discriminate oral cancer from control subjects.

Authors
  • Abemayor E
  • Akin D
  • Arellano M
  • Chia D
  • Elashoff D
  • Feng Z
  • Henson B
  • Hu S
  • Kastratovic DA
  • Le A
  • Lingen M
  • Messadi D
  • Morris D
  • Nabili V
  • Randolph T
  • Reiss J
  • Sinha U
  • Wang J
  • Wang M
  • Wong DT
  • Xiao H
  • Zhou H
PubMed ID
Appears In
Cancer Epidemiol Biomarkers Prev, 2012, 21 (4)