Scientists at the Ohio State University Comprehensive Cancer Center have developed a new method for measuring genetic variability within a tumor that might one day help doctors identify patients with aggressive cancers that are more likely to resist therapy.
Researchers used a new scoring technique they developed called MATH (mutant-allele tumor heterogeneity) to measure the genetic variability among cancer cells within tumors from 305 patients with head and neck cancer. High MATH scores corresponded to tumors with many differences among the gene mutations present in different cancer cells.
Cancers that showed high genetic variability, i.e., "intra-tumor heterogeneity," correlated with lower patient survival. If prospective studies verify the findings, MATH scores could help identify the most effective treatment for patients and predict a patient's prognosis.
It’s long been hypothesized that multiple sub-populations of mutated cells within a single cancer lead to worse clinical outcomes; however, oncologists do not use tumor heterogeneity to guide clinical care decisions or assess disease prognosis because there is no single, easy-to-implement method of doing so in clinical practice.
To address this need, James Rocco, M.D., Ph.D., and his colleagues developed MATH to make it easier for doctors to measure genetic variability in patients' tumors and to help guide treatment decisions. Their study (“Intra-tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas”), reported in PLOS Medicine, confirms that high genetic variability with a patient's tumor is related to increased mortality in head and neck squamous cell carcinoma.
"Genetic variability within tumors is likely why people fail treatment," says Dr. Rocco, professor and John and Mary Alford Chair of Head and Neck Surgery. "In patients who have high heterogeneity tumors it is likely that there are several clusters of underlying mutations, in the same tumor, driving the cancer. So their tumors are likely to have some cells that are already resistant to any particular therapy."
For the current study, Dr. Rocco and his team used the MATH tool to analyze retrospective data from 305 head and neck squamous cell carcinoma patients from The Cancer Genome Atlas (TCGA). This NIH repository of publicly available data was launched in 2006 as a pilot project and now includes samples from more than 11,000 patients across 33 tumor types. The MATH score was calculated from data obtained by TCGA via whole-exome sequencing.
Researchers confirmed that high intra-tumor heterogeneity was related to increased mortality in this sub segment of patients. Each 10% increase in MATH score corresponded to an 8.8% increased likelihood of death.
“To our knowledge this study is the first to combine data from hundreds of patients, treated at multiple institutions, to document a relation between intra-tumor heterogeneity and overall survival in any type of cancer,” wrote the investigators. “We suggest applying the simply calculated MATH metric of heterogeneity to prospective studies of HNSCC and other tumor types.”