MD Anderson Research Indicates Molecular Subtype Classification Improves Chemotherapy Decision For Patients With Colorectal Cancer

Posted Friday , June 07,2013

At this year’s annual conference of the American Society of Clinical Oncology (ASCO), the topic of molecular subtyping, which can help physicians predict adjuvant (post-surgical) chemotherapy benefits in patients with colorectal cancer, was selected as a primary focus of discussion, due to the findings of a recent MD Anderson study, as well as its significance in effectively treating colorectal cancer patients.
In the study, the tumor tissue of 543 patients in Stage II and III of colorectal cancer and in Stage I to IV in TCGA (The Cancer Genome Atlas project) dataset was examined, and the researchers identified three major molecular subtypes of colorectal cancer, all of which have a significant association with prognosis and response.
“Different patients have different responses to treatment for colorectal cancer because of the underlying biology of the tumor. Having this new information about molecular subtypes provides valuable information regarding prognosis and treatment,” said poster co-author Scott Kopetz, M.D., Ph.D., FACP, a medical oncologist at The University of Texas MD Anderson Cancer Center. “We now know that, along with clinical-pathological risk factors, the subtype is clinically relevant in the treatment decision process.”
Related to this topic of molecular subtyping, there was another poster at the ASCO meeting, which reports the validity of the genomic classifier ColoPrint®, which is a technology provided by Agendia, for the accurate prediction of outcomes and benefits of chemotherapy in Stage II and III colon cancer patients. The poster reporting this study showed that there was a significant improvement at accuracy of prognostic prediction, which indicates that it supports physicians in deciding which patients would benefit most from chemotherapy and which patients would not.
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Related links to this article:
American Society of Clinical Oncology < http://www.asco.org/ >
Agendia – decoding cancer – < http://www.agendia.com/ >
The Cancer Genome Atlas project < http://cancergenome.nih.gov/ >