Comprehensive analysis of tumor mutational load, genomic alterations, and PD-L1 status in gastrointestinal cancers using a multiplatform molecular profiling tool.

Abstract

93 Background: Tumor mutational load (TML) has been proposed as a biomarker of responsiveness to novel immune checkpoint inhibitors (ICIs) due its association with increased neoantigen formation and tumor immunogenicity. Gastrointestinal cancers (GICs) are generally insensitive to ICIs; therefore the aim of this study was to evaluate the TML, clinically relevant genomic alterations (CRGAs), and PDL-1 status of GIC patients (pts). Methods: We analyzed samples of pts with GICs using a multiplatform profiling tool (Caris Life Sciences, Phoenix, AZ). TML and CRGAs were calculated based on next generation sequencing and mutational load was stratified as high (≥17 mut/Mb), intermediate (8-16 mut/Mb), and low (≤ 7 mut/Mb). PD-L1 status was determined by IHC. Descriptive statistics and simple linear regression were used for analysis. Results: A total of 85 pts with GICs were analyzed. The median pt age was 65. 53% were males and 47% were females. Tumors were colorectal 51%, pancreatic 13%, esophageal 13%, gastric 9%, hepatobiliary 11%, anal canal 4%, and small intestine 1%. 80 cases (94%) had an adequate sample for profiling and TML was available in 59 cases (74%). Cases were 5% TML-high, 56% TML-intermediate, and 39% TML-low. The median TML was 9 mut/Mb and median CRGAs was 3. The most commonly detected CRGAs were TP53 (56%), APC (44%), KRAS (40%), ATM (18%) and PTEN (6%). A positive but very weak correlation was found between TML and number of CRGAs (R2 = 0.3). PD-L1 status was available in 74 cases (93%) with 86% being PD-L1 negative and 14% PD-L1 positive. PD-L1 expression was most commonly seen in esophageal (50%) and anal canal (30%) cancers. Among 57 tumors tested for both biomarkers, no correlation was found between a high TML and PD-L1 expression. Conclusions: TML varies among GICs, and higher TML scores were not associated with PD-L1 expression, but there was a weak correlation between TML and the number of CRGAs. Further analysis by stratification of GIC type and prognostic analysis to assess the correlation between TMB and response to ICIs is warranted.