Intra-tumor heterogeneity in head and neck cancer and its clinical implications

Abstract

The presence of heritable differences among cancer cells within a tumor, called intra-tumor genetic heterogeneity, has long been suspected of playing a role in poor responses to therapy. Research over the past decade has documented the existence of such heterogeneity within tumors of individual patients and documented its potential clinical significance. The research methods for identifying this heterogeneity were not, however, readily adaptable to widespread clinical application. After a brief review of this background, we describe the development of a measure of intra-tumor genetic heterogeneity, based on whole-exome sequencing of individual tumor samples, that could be applied to biopsy specimens in a clinical setting. This measure has now been used in head and neck squamous cell carcinoma (HNSCC) to document, for the first time, a relation of high intra-tumor genetic heterogeneity to shorter overall survival in a large, multi-institutional study. The implications of heterogeneity for research and clinical care thus now need to be addressed.

Keywords: Head and neck squamous cell carcinoma; Intra-tumor genetic heterogeneity; Next-generation sequencing; Targeted therapy.

Fig. 1

The idea behind mutant-allele tumor heterogeneity (MATH) measurement. Heterozygous mutations in a tumor in which all cells share the same mutations (top) will show a narrow distribution of mutant-allele fractions (MAF) after DNA is extracted and subjected to next-generation sequencing (left to right). The width of the distribution of MAF will represent random sampling of mutant and normal alleles, as illustrated hypothetically for 100 total reads at each locus (right). Cells whose combination of shared and unique mutations defines a genetically heterogeneous tumor (bottom) will show a wider distribution of MAF values and a lower median MAF value among mutated loci. MATH is the percentage ratio of the distribution width (the median absolute deviation, MAD) to the median MAF value. Adapted from Mroz and Rocco, with permission.

Fig. 2

Relation of MATH values to HPV status and TP53 mutation status in HNSCC. Box-and-whisker plots with individual tumor MATH values shown for HNSCC sequenced by Stransky et al. Adapted from Mroz and Rocco, with permission.

Fig. 3

MATH values of HNSCC are not closely related to the number of mutations, a standard measure of mutation rate. Shown for HNSCC sequenced by Stransky et al. From Mroz and Rocco, used with permission.

Fig. 4

Relation of MATH to overall survival in the 74 patients whose HNSCC had been sequenced by Stransky et al. Kaplan–Meier curves from Mroz et al, used with permission.

Fig. 5

Relation of MATH to overall survival in patients whose HNSCC had been sequenced by Stransky et al and who had received systemic chemotherapy as part of treatment. Kaplan–Meier curves from Mroz et al, used with permission.

Fig. 6

MATH values (low, blue; high, red) distinguish outcomes in patients with oral-cavity (left) or laryngeal (right) tumors (top), even when TNM stage is taken into account (bottom). Kaplan–Meier of cases analyzed by The Cancer Genome Atlas. From Mroz et al, figure freely available under the Creative Commons Attribution license.