MATH, a novel measure of intratumor genetic heterogeneity, is high in poor-outcome classes of head and neck squamous cell carcinoma

Abstract

Differences among cancer cells within a tumor are important in tumorigenesis and treatment resistance, yet no measure of intratumor heterogeneity is suitable for routine application. We developed a quantitative measure of intratumor genetic heterogeneity, based on differences among mutated loci in the mutant-allele fractions determined by next-generation sequencing (NGS) of tumor DNA. We then evaluated the application of this measure to head and neck squamous cell carcinoma (HNSCC). We analyzed published electronically available NGS results for 74 HNSCC. For each tumor we calculated mutant-allele tumor heterogeneity (MATH) as the ratio of the width to the center of its distribution of mutant-allele fractions among tumor-specific mutated loci. Intratumor heterogeneity assessed by MATH was higher in three poor-outcome classes of HNSCC: tumors with disruptive mutations in the TP53 gene (versus wild-type TP53 or non-disruptive mutations), tumors negative versus positive for human papillomavirus (even when restricted to tumors having wild-type TP53), and HPV-negative tumors from smokers with more pack-years of cigarette exposure (with TP53 status taken into account). The relation of this type of intratumor heterogeneity to HNSCC outcome classes supports its further evaluation as a prognostic biomarker. As NGS of tumor DNA becomes widespread in clinical research and practice, MATH should provide a simple, quantitative, and clinically practical biomarker to help evaluate relations of intratumor genetic heterogeneity to outcome in any type of cancer.