The variety of genetic mutations (heterogeneity) of cells within a tumor appears to signal worse clinical outcomes in persons with head and neck squamous cell carcinoma (HNSCC), a recent study demonstrated.
As summarized in a statement from Massachusetts General Hospital (MGH) in Boston, Massachusetts, tumors that are genetically heterogeneous have different subgroups of tumor cells undergoing different mutations at different DNA sites. Researchers have long theorized that treatment would be less successful in tumors with a high degree of genetic heterogeneity because particular cell subgroups might be more likely than one or more other subgroups to survive a particular drug or radiation.
Edmund A. Mroz, PhD, of the MGH Center for Cancer Research, and colleagues previously had developed and tested a quantitative measure of tumor genetic heterogeneity. To create the measure, known as MATH (mutant-allele tumor heterogeneity), they analyzed advanced gene-sequencing data to produce a value that reflects the genetic diversity within a tumor, including the number of genetic mutations as well as how broadly particular mutations are shared within different subgroups of tumor cells.
After developing MATH, the investigators sought to apply the measure to assess whether greater heterogeneity does in fact predict a worse outcome. In this effort, described in the journal Cancer, Mroz’s team examined the association between MATH and clinical, pathologic, and overall survival data in 74 persons with HNSCC for whom complete treatment and outcome information was available.
The evaluation revealed a significant association between high MATH (a MATH value above the median) and shorter overall survival: Each unit of increase reflected a 5% increase in the risk of death. Furthermore, that association was also seen in clinically high-risk patients with advanced disease, and in patients whose tumors were classified as high risk due to displaying such validated biomarkers as being negative for human papillomavirus (HPV) or having disruptive tumor protein p53 mutations.
The impact of MATH value on outcome was particularly strong among patients who received chemotherapy. Mroz noted in the MGH statement that this finding may reflect a greater likelihood that highly heterogeneous tumors contain treatment-resistant cells.
Overall, MATH values were more strongly related to outcomes than were most previously identified risk factors, and MATH values improved outcome predictions based on all other risk factors analyzed.