Identification and validation of endoplasmic reticulum stress-related genes that enhance immunotherapy in colon cancer.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39145077", "kind": "science-record", "revision": 2, "content_hash": "sha256:5f85729736a7a7d7cd93155e7b9c22cf2538b82a040000cb551ccbbffcf4ee8a", "created_at": "2026-11-01T20:29:16Z", "updated_at": "2026-11-01T21:33:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of endoplasmic reticulum stress-related genes that enhance immunotherapy in colon cancer.", "doi": "10.21037/tcr-23-2227", "pmid": "39145077", "authors": ["Baolin Wang", "Jun Yang", "Jiexin Wu", "Xiaoming Hu", "Jun Zhu", "Jiang Fang", "Bo Han", "Bo Zhou"], "journal": "Translational cancer research", "year": 2024, "abstract": "Background: Endoplasmic reticulum stress (ERS)-related genes are related to tumor growth, metastasis, and immunotherapy response. In this paper, we tried to identify ERS-related genes related to immunotherapy in colon cancer.\nMethods: ERS-related genes were downloaded from the Molecular Signatures Database (MSigDB) and GeneCards websites. Normal and tumor samples of the colon were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), and Gene Expression Omnibus (GEO) databases. A risk model based on gene coefficients was constructed by using the least absolute shrinkage and selection operator (LASSO) regression. The inherent biological process differences between risk groups were explored by Gene Ontology (GO) and gene set enrichment analysis (GSEA). ESTIMATE and single-sample GSEA (ssGSEA) algorithms were used to analyze the correlation between tumor microenvironment (TME) and immune checkpoint and risk score. The semi-inhibitory concentration (IC50) values of chemotherapeutic drugs between risk groups were calculated to evaluate the sensitivity of immunotherapy.\nResults: The pathway analysis showed that the ERS risk model was relevant to biosynthesis and metabolism. Consistent clustering based on the ERS-related differentially expressed genes (DEGs) demonstrated that the samples divided into three clusters had significant clinicopathological differences. A risk model consisting of six ERS-related genes was established. The model was verified on GSE39582 and GSE17536 testing datasets. The results showed that ERS risk model was significantly related to TME and immune checkpoint, and these genes enhanced the immunotherapy ability of colon cancer.\nConclusions: We established a risk model with ERS-related genes (PMM2, STC2, EIF2AK1, HSPA1A, SLC8A1, KCNQ1), which enhance the sensitivity of immunotherapy for colon cancer. 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