BACKGROUND: Although the presence of genetic heterogeneity within the tumors of individual patients is established, it is unclear whether greater heterogeneity predicts a worse outcome. A quantitative measure of genetic heterogeneity based on next-generation sequencing (NGS) data, mutant-allele tumor heterogeneity (MATH), was previously developed and applied to a data set on head and neck squamous cell carcinoma (HNSCC). Whether this measure correlates with clinical outcome was not previously assessed. METHODS: The authors examined the association between MATH and clinical, pathologic, and overall survival data for 74 patients with HNSCC for whom exome sequencing was completed. RESULTS: High MATH (a MATH value above the median) was found to be significantly associated with shorter overall survival (hazards ratio, 2.5; 95% confidence interval, 1.3-4.8). MATH was similarly found to be associated with adverse outcomes in clinically high-risk patients with an advanced stage of disease, and in those with tumors classified as high risk on the basis of validated biomarkers including those that were negative for human papillomavirus or having disruptive tumor protein p53 mutations. In patients who received chemotherapy, the hazards ratio for high MATH was 4.1 (95% confidence interval, 1.6-10.2). CONCLUSIONS: This novel measure of tumor genetic heterogeneity is significantly associated with tumor progression and adverse treatment outcomes, thereby supporting the hypothesis that higher genetic heterogeneity portends a worse clinical outcome in patients with HNSCC. The prognostic value of some known biomarkers may be the result of their association with high genetic heterogeneity. MATH provides a useful measure of that heterogeneity to be prospectively validated as NGS data from homogeneously treated patient cohorts become available.
BACKGROUND: Although the presence of genetic heterogeneity within the tumors of individual patients is established, it is unclear whether greater heterogeneity predicts a worse outcome. A quantitative measure of genetic heterogeneity based on next-generation sequencing (NGS) data, mutant-allele tumor heterogeneity (MATH), was previously developed and applied to a data set on head and neck squamous cell carcinoma (HNSCC). Whether this measure correlates with clinical outcome was not previously assessed. METHODS: The authors examined the association between MATH and clinical, pathologic, and overall survival data for 74 patients with HNSCC for whom exome sequencing was completed. RESULTS: High MATH (a MATH value above the median) was found to be significantly associated with shorter overall survival (hazards ratio, 2.5; 95% confidence interval, 1.3-4.8). MATH was similarly found to be associated with adverse outcomes in clinically high-risk patients with an advanced stage of disease, and in those with tumors classified as high risk on the basis of validated biomarkers including those that were negative for human papillomavirus or having disruptive tumor protein p53 mutations. In patients who received chemotherapy, the hazards ratio for high MATH was 4.1 (95% confidence interval, 1.6-10.2). CONCLUSIONS: This novel measure of tumor genetic heterogeneity is significantly associated with tumor progression and adverse treatment outcomes, thereby supporting the hypothesis that higher genetic heterogeneity portends a worse clinical outcome in patients with HNSCC. The prognostic value of some known biomarkers may be the result of their association with high genetic heterogeneity. MATH provides a useful measure of that heterogeneity to be prospectively validated as NGS data from homogeneously treated patient cohorts become available.
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