Genetic Diversity Predicts Outcomes in Head and Neck Cancer
A new measure of the heterogeneity of cells within a tumor appears to predict treatment outcomes of patients with the most common type of head and neck cancer. In the May 20 issue of the journal Cancer, investigators at Massachusetts General Hospital (MGH) and Massachusetts Eye and Ear Infirmary describe how their measure was a better predictor of survival than most traditional risk factors in a small group of patients with squamous cell carcinoma of the head and neck.
"Our findings will eventually allow better matching of treatments to individual patients, based on this characteristic of their tumors," said lead author Edmund Mroz, PhD, of the MGH Center for Cancer Research. "This method of measuring heterogeneity can be applied to most types of cancer, so our work should help researchers determine whether a similar relationship between heterogeneity and outcome occurs in other tumors."
Measuring Tumor Heterogeneity
For decades investigators have hypothesized that tumors with a high degree of genetic heterogeneity would be more difficult to treat because particular subgroups might be more likely to survive a particular drug or radiation or to have spread before diagnosis. While recent studies have identified specific genes and proteins that can confer treatment resistance in tumors, there previously has been no way of conveniently measuring tumor heterogeneity.
Working in the laboratory of senior author James Rocco, MD, PhD, Director of the Massachusetts Eye and Ear Infirmary/MGH Head and Neck Molecular Oncology Research Laboratory, Dr. Mroz and his colleagues developed their new measure by analyzing advanced gene sequencing data to produce a value reflecting the genetic diversity within a tumor—not only the number of genetic mutations but how broadly particular mutations are shared within different subgroups of tumor cells. They first described this measure, called mutant-allele tumor heterogeneity (MATH), in the March 2013 issue of Oral Oncology.
Study Details
In the current study, the investigators used MATH to analyze genetic data from the tumors of 74 patients with squamous cell head and neck carcinoma for whom they had complete treatment and outcome information. Not only did they find that higher MATH values were strongly associated with shorter overall survival—with each unit of increase reflecting a 5% increase in the risk of death—but that relationship was also seen within groups of patients already at risk for poor outcome. For example, among patients with human papillomavirus–negative tumors, those with higher MATH values were less likely to survive than those with lower MATH values.
Overall, MATH values were more strongly related to outcomes than most previously identified risk factors and improved outcome predictions based on all other risk factors the researchers examined.
The impact of MATH value on outcome appeared strongest among patients treated with chemotherapy, which may reflect a greater likelihood that highly heterogeneous tumors contain treatment-resistant cells, Dr. Mroz said. He also noted that what reduces the chance of survival appears to be the subgroups of cells with different mutations within a tumor, not the process of mutation itself. "If all the tumor cells have gone through the same series of mutations, a single treatment might still be able to kill all of them. But if there are subgroups with different sets of mutations, one subgroup might be resistant to one type of treatment, while another subgroup might resist a different therapy," he said
Future Implications
In addition to combining MATH values with clinical characteristics to better predict a patient's chance of successful treatment, Dr. Mroz noted that MATH could someday help determine treatment choice—directing the use of more aggressive therapies against tumors with higher values, while allowing patients with lower values to receive less intense standard treatment. While MATH will probably be just as useful at predicting outcomes for other solid tumors, the investigators note, that will need to be shown in future studies.
"Our results have important implications for the future of oncology care," said Dr. Rocco, the Daniel Miller Associate Professor of Otology and Laryngology at Harvard Medical School. "MATH offers a simple, quantitative way to test hypotheses about intratumor genetic heterogeneity, including the likelihood that targeted therapy will succeed. They also raise important questions about how genetic heterogeneity develops within a tumor and whether heterogeneity can be exploited therapeutically."
The study was supported by National Institute of Dental and Craniofacial Research grants R01DE022087 and RC2DE020958, National Cancer Institute grant R21CA119591, Cancer Prevention Research Institute of Texas grant RP100233, and the Bacardi MEEI Biobank Fund. The MGH has filed a patent application for the MATH measure.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
