P16.01 Clonal Landscape Predicts Outcome in Lung Squamous Cell Carcinoma Patients with a Low Tumor Mutational Burden

Abstract

Tumor heterogeneity metrics have become widely used in research, however none have been clinically approved. Two such methods of interest are PyClone and Mutant Allele Tumor Heterogeneity (MATH). Although PyClone has shown predictive power in manycancers, no statistically significant relationship has been found in lung squamous cell carcinoma (LUSC) . While MATH has shown clinical implications in head and neck squamous cell carcinoma. To investigate this relationship we integrated tumor mutational burden (TMB), a clinically approved biomarker for immunotherapy, MATH, and PyClone. Patients were classified as high/low if their TMB, MATH, and PyClone values were above or below their respective medians. Together these metrics may yield stronger predictive value than each metric on it’s own. Data for 178 patients was obtained from the GDC data portal (SNV and CNV) and the cBioPortal (Clinical). Dividing the total number of somatic mutations by exom size (38Mb) yielded TMB. For PyClone, a minimum cluster size of 2 was used. MATH calculations were performed via maftools, a publicly available python library. TMB, MATH, and PyClone values were able to be calculated for 100 patients who had survival outcome data available. This cohort was composed of 57% Stage I, 24% Stage II, 16% Stage III, and 2% Stage IV patients at an average age of 69. All statistical analysis was performed in python via publicly available libraries. Individually, TMB, MATH, and PyClone did not have a statistically significant association with outcome. MATH score did not significantly contribute to statistical power and was not used after initial assessment. Low TMB/High PyClone patients had superior PFS (51 vs. 18 months, p = 0.002, HR 0.39 CI 0.21-0.72) and OS (51 vs. 22 months, p=0.0437, HR 0.56 CI 0.32 - 0.99) than their Low TMB/Low PyClone counterparts. Low TMB/Low PyClone group was 70% Stage I, 22% Stage II, and 8% Stage III with an average age of 73. Low TMB/High PyClone group was 52% Stage I, 30% Stage II, and 18% Stage III with an average age of 68. TMB, MATH, and PyClone are all derived in different ways and may capture different aspects of tumor heterogeneity. When patients were classified based on median TMB and PyClone, clonal distribution measured by PyClone predicted survival in lung squamous cell carcinoma patients with a low TMB. Our study suggests interaction between TMB and clonality in predicting survival, awaiting validation with further studies.