Identification of genes and cellular response factors related to immunotherapy response in mismatch repair-proficient colorectal cancer: a bioinformatics analysis

Abstract

Background: Mismatch repair-proficient (pMMR) colorectal cancers (CRCs) are thought to be primarily resistant to immune checkpoint inhibitor (ICI) monotherapy. However, recent clinical trials have reported that early-to-mid stage (non-metastatic) CRC responds well to ICI monotherapy. We hypothesized that the efficacy of immunotherapy is linked to a series of gene expression profiles that can characterize the pMMR CRC disease stage.Methods: Using the Cancer Genome Atlas (TCGA) CRC data sets, we first investigated transcriptomic features that continuously changed (were continuously upregulated or downregulated) with pMMR CRC disease-stage progression. We defined these gene sets as stage-associated genes. The deconvolution algorithm then enriched these genes with the dynamic changes in the cell type populations of the CRC tumor microenvironment (TME). Finally, the stage-associated genes were cross-referenced to the current transcriptome profile data on ICI treatment of pMMR CRC, which revealed the gene set specifying an effective pMMR tumor response.Results: In total, 774 genes were found to increase in expression and 845 genes to decrease in expression as the stage increased. Using deconvolution methods, we discovered 2 major disease stage-associated alterations in the cellular composition of pMMR CRCs, including changes in cell types involved in host immune responses and tumor cell metastasis. The central memory CD8+ T cell population decreased as the pMMR CRC disease stage increased, but the endothelial cell populations associated with proliferation and metastasis increased. Using a different cell type annotation set (LM22), we discovered that as the disease progressed, M1 macrophages and CD8+ T cells decreased in the TME. In mismatch repair-deficient patients with CRC, however, such a decrease was not observed. Finally, we identified 27 signature genes that can be used to assess ICI efficacy in treatment-naïve patients with pMMR CRC. Conclusions:The current study sought to identify the underlying molecular mechanisms, pathways, and cell landscapes that explain why early-to-mid stage pMMR CRC responds well to ICI treatment. This analysis might be valuable for the selection of patients who might benefit from immunotherapeutic strategies.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

“…59 Nevertheless, our fine-grained populations do extend the set of cell types previously evaluated. Further, that set includes cell types of clinical significance and that earlier deconvolution studies have already linked to survival, 17,60,61 progression, 62 and response to immune checkpoint inhibitors. [19][20][21] Finally, the top performers could be retrained to predict exhausted CD8+ T cells or other immune subpopulations characterized by single-cell studies by applying the code we make available here or the resources on the CIBERSORTx website.…”