Mutation characteristics of the MYC proximal network and its implications for immunotherapy in human cancer

Abstract

Abstract Background The proximal MYC network (PMN), formed by MYC, related transcription factors, and coregulatory proteins, has been implicated in cancer. However, it is lacking systematic assessment of the effect of the mutation of PMN-related genes on immune checkpoint inhibitor (ICI) response. Methods To explore this, a discovery cohort that patients with whole-exome sequencing (WES) and ICI-treated clinical information were integrated. Another independent pan-cancer cohort that patients with next-generation sequencing (NGS) data were collected for further verification. The Cancer Genome Atlas (TCGA) cohort was used to analyze mutation frequency and genomic mutation characteristics. The anti-tumor immunity and molecular mechanism analysis was performed using the public available single-cell RNA-seq, tissue RNA-seq, and ChIP-seq data. Results Among the 13 PMN-related genes, MGA has the highest mutation frequency (8%). A higher objective response rate (ORR, 56.7% vs 29.3%) and durable clinical benefit (DCB, 67.9% vs 43.6%) were found in MGA-mutated (MGA-MUT) patients. Compared with MGA-wildtype (MGA-WT) patients, MGA-MUT patients obtained a longer overall survival time. Multivariate regression analysis showed that MGA mutation was an independent prognostic factor in ICI-treated patients. Furthermore, MGA-MUT patients have more mutation events in the genome with a higher mutation frequency of several genes (such as TTN, MUC16, and LRP1B, etc). A higher tumor mutation burden (TMB) and neoantigens were detected in MGA-MUT patients. MGA-MUT patients have more abundance in immune cells (including CD8 + T cells and macrophages). Most of the cytotoxic activity, immune checkpoint, and chemokine genes were upregulated in the MGA-MUT tumors. At the single-cell level, MGA was mainly expressed on most immune cells, including CD8 Tex, NK cell, monocyte/macrophage, etc. Mechanistically, several anti-tumor immunity pathways were enhanced in MGA-MUT tumors. Conclusions MGA-MUT is favorable to immunotherapy across multiple cancer types, which might be a predictive biomarker for patients’ clinical outcomes.