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

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...

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Detalles Bibliográficos
Autores principales: Xue, Wenxiu, Shi, Jinglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830321/
https://www.ncbi.nlm.nih.gov/pubmed/36636048
http://dx.doi.org/10.21037/jgo-22-1070
Descripción
Sumario: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.