{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T09:07:24Z","timestamp":1776157644756,"version":"3.50.1"},"reference-count":44,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Yunnan Talent Support Plan","award":["XDYC-QNRC-2022-0286"],"award-info":[{"award-number":["XDYC-QNRC-2022-0286"]}]},{"name":"The Local United Fund of Yunnan Province","award":["202301BA070001-031"],"award-info":[{"award-number":["202301BA070001-031"]}]},{"name":"The Scientific Research Foundation of Yunnan Education Department","award":["2025J0768"],"award-info":[{"award-number":["2025J0768"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. The identification of effective molecular targets is crucial for advancing precision medicine and prognostic strategies. This study aims to uncover key CRC biomarkers through integrative bioinformatics analyses, providing mechanistic insights for therapeutic development.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed three CRC datasets from the Gene Expression Omnibus (GEO) database. Expression quantitative trait loci (eQTL) analysis was performed to identify instrumental variables (IVs), which were subsequently used in Mendelian Randomization (MR) analysis with CRC Genome-Wide Association Study (GWAS) data. MR-associated genes were intersected with differentially expressed genes (DEGs) to screen disease-related key genes. Functional enrichment analyses were conducted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Additionally, immune cell infiltration and gene-immune correlation analyses were performed. Finally, validation was performed using independent GEO, The Cancer Genome Atlas (TCGA) datasets, summary data-based Mendelian randomization (SMR) and quantitative reverse transcription polymerase chain reaction (qRT-PCR) in CRC cell lines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 776 upregulated and 981 downregulated DEGs were identified. Nine key genes were prioritized:\n                      <jats:italic>ATP13A4, CD1C, METTL7A, SLC18A1, CREB5, CXCR1, GZMB, HECW2,<\/jats:italic>\n                      and\n                      <jats:italic>TEAD2<\/jats:italic>\n                      , predominantly involved in cytokine receptor interaction pathways. CIBERSORT analysis revealed increased activated CD4+ memory T cells and M0 macrophages, alongside decreased plasma cells and natural killer (NK) cells in CRC. Key genes demonstrated significant correlation with immune cell subsets (\n                      <jats:italic>e.g.<\/jats:italic>\n                      , neutrophils, mast cells), highlighting their role in CRC immunobiology. Validation\n                      <jats:italic>via<\/jats:italic>\n                      SMR and qRT-PCR assays demonstrated significant dysregulation of four target genes (\n                      <jats:italic>CXCR1<\/jats:italic>\n                      ,\n                      <jats:italic>HECW2<\/jats:italic>\n                      ,\n                      <jats:italic>ATP13A4<\/jats:italic>\n                      ) (\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&lt;\u00a00.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>\n                      This study suggests that\n                      <jats:italic>CXCR1<\/jats:italic>\n                      ,\n                      <jats:italic>HECW2<\/jats:italic>\n                      , and\n                      <jats:italic>ATP13A4<\/jats:italic>\n                      may be involved in CRC development, providing a reference for targeted and immunotherapy research.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.7717\/peerj.21070","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T08:15:23Z","timestamp":1776154523000},"page":"e21070","source":"Crossref","is-referenced-by-count":0,"title":["Identification of colorectal cancer immune biomarkers\n                    <i>via<\/i>\n                    eQTL mapping: a Mendelian randomization and transcriptomic analysis study"],"prefix":"10.7717","volume":"14","author":[{"given":"Genyuan","family":"Pu","sequence":"first","affiliation":[{"name":"School of Basic Medicine, Dali University, Dali, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zi","family":"Yin","sequence":"additional","affiliation":[{"name":"School of Basic Medicine, Dali University, Dali, 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