Landscape of Tumor Mutation Load, Mismatch Repair Deficiency, and PD-L1 Expression in a Large Patient Cohort of Gastrointestinal Cancers

Authors:

Mohamed E. Salem, Alberto Puccini, Axel Grothey, Derek Raghavan, Richard M. Goldberg, Joanne Xiu, W. Michael Korn, Benjamin A. Weinberg, Jimmy J. Hwang, Anthony F. Shields, John L. Marshall, Philip A. Philip, and Heinz-Josef Lenz

Abstract:

The efficacy of immunotherapy varies widely among different gastrointestinal cancers. Response to immune checkpoint inhibitors is shown to correlate with tumor mutation load (TML), mismatch repair deficiency (dMMR) status, and programmed cell death-ligand 1 (PD-L1) expression. Herein, we quantify TML, dMMR, and PD-L1 expression and determine their interrelationship in gastrointestinal cancers. Here, a total of 4,125 tumors from 14 different gastrointestinal cancer sites were studied using validated assays. Next-generation sequencing was performed on genomic DNA isolated from formalinfixed paraffin-embedded tumor specimens using the NextSeq platform. TML was calculated using only somatic nonsynonymous missense mutations sequenced with a 592-gene panel. Microsatellite instability (MSI) was assessed using direct analysis of altered known MSI loci in the target regions of the sequenced genes. PD-L1 expression was analyzed by IHC.

Interestingly, right-sided colon and small-bowel adenocarcinomas had the highest prevalence of TML-high tumors (14.6% and 10.2%, respectively). Pancreatic neuroendocrine tumors and gastrointestinal stromal tumors had the lowest rates of TML-high (1.3% and 0%, respectively). TML-high was strongly associated with MSI-H (P < 0.0001). However, all TML-high anal cancers (8.3%) were microsatellite stable (MSS). Higher PD-L1 expression was more likely to be seen in MSI compared with MSS tumors (20.6% vs. 7.8%, P < 0.0001).

Implications:

TML-high rate varied widely among gastrointestinal cancers. Although MSI is conceivably the main driver for TMLhigh, other factors may be involved. Future clinical trials are needed to evaluate whether the integration of TML, MSI, and PD-L1 could better identify potential responders to immunotherapy.

Download Publication