Predicting which cancer patients will best respond to therapy is an enormous health care issue. It has been recently suggested, based on early reads of whole exome sequencing data, that there may only be ~12 molecular pathways that drive the development and progression of cancer. Many experimental therapies are now targeting these pathways. We believe that gene expression signatures may be one of the best ways to judge the activation of a particular molecular pathway, by providing a """"""""molecular summary"""""""" of the activity of many genes. Moreover, we believe that the selective addition of mutational assessment may improve the resolving power of a hybrid, multi-analyte (DNA + RNA) test that may be used to guide patients to the most effective drugs. We have recently developed gene expression signatures to measure the activation of two of the most important pathways in colon cancer, RAS and PI3K, for which there is an increasing availability of pathway targeted therapeutics. Due to the complex nature of these pathways, simple analysis of canonical single gene mutations only identifies the response characteristics of a proportion (<30%) of the population. Here, we propose to technically validate the existing RAS and PI3K signatures and to refine their activity through novel mutational assessment. Multi-analyte signatures/ algorithms will be clinically validated in a CLIA environment with a cohort of colorectal cancer patients treated with cetuximab therapy. This approach will prepare signatures for clinical application in the near future.

Public Health Relevance

This proposal seeks to identify a reliable means to identify the right drugs for the right cancer patients. Current approaches over treat many patients to help an unknown few, with substantial costs and toxicities. The application of molecular signatures to individualize therapy holds significant promise to personalize cancer care, improve response rates, reduces toxicity and associated costs. Here we will combine RNA gene expression signatures with gene mutation assessments to identify responders and non-responders to cetuximab therapy.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Thurin, Magdalena
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Spartanburg Regional Medical Center
United States
Zip Code
Davis, Thomas B; Yang, Mingli; Schell, Michael J et al. (2018) PTPRS Regulates Colorectal Cancer RAS Pathway Activity by Inactivating Erk and Preventing Its Nuclear Translocation. Sci Rep 8:9296
Omolo, Bernard; Yang, Mingli; Lo, Fang Yin et al. (2016) Adaptation of a RAS pathway activation signature from FF to FFPE tissues in colorectal cancer. BMC Med Genomics 9:65
Schell, Michael J; Yang, Mingli; Missiaglia, Edoardo et al. (2016) A Composite Gene Expression Signature Optimizes Prediction of Colorectal Cancer Metastasis and Outcome. Clin Cancer Res 22:734-45
Schell, Michael J; Yang, Mingli; Teer, Jamie K et al. (2016) A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC. Nat Commun 7:11743
Kim, Richard; Schell, Michael J; Teer, Jamie K et al. (2015) Co-evolution of somatic variation in primary and metastatic colorectal cancer may expand biopsy indications in the molecular era. PLoS One 10:e0126670
Lee, Chang Gong; McCarthy, Susan; Gruidl, Mike et al. (2014) MicroRNA-147 induces a mesenchymal-to-epithelial transition (MET) and reverses EGFR inhibitor resistance. PLoS One 9:e84597