Analysis of the role of CHPF in colorectal cancer tumorigenesis and immunotherapy based on bioinformatics and experiments.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39292317", "kind": "science-record", "revision": 2, "content_hash": "sha256:3ae66aa572efe4ffd0aaf60b04f49707565341439aba75570577f2b357cd2406", "created_at": "2026-11-01T20:29:27Z", "updated_at": "2026-11-01T21:33:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Analysis of the role of CHPF in colorectal cancer tumorigenesis and immunotherapy based on bioinformatics and experiments.", "doi": "10.1007/s12672-024-01340-2", "pmid": "39292317", "authors": ["Qingyu Song", "Pengchao Wang", "Jingyu Wu", "Ming Lu", "Qingcheng Xia", "Yexin Shi", "Zijun Wang", "Xiang Ma", "Qinghong Zhao"], "journal": "Discover oncology", "year": 2024, "abstract": "BACKGROUND: Chondroitin polymerizing factor (CHPF) has been found to be involved in the development of numerous cancers and correlated with poor prognosis. However, its role in the tumorigenesis and development of colorectal cancer (CRC) remains unknown.\nMETHODS: In our research, we explored CHPF expression and clinicopathological characteristics using The Cancer Genome Atlas Program (TCGA), UALCAN, GSE9348, TIMER2.0 and The Human Protein Atlas (HPA) database, in addition, we validated CHPF expression in CRC cell lines by Real-Time Quantitative PCR (qRT-PCR) and Western blot (WB). KM-Plotter, PrognoScan and TCGA were also utilized to verify its prognosis value in CRC. Small-interfer RNA (Si-RNA) was used to perform Cell Counting Kit-8 (CCK8), colony formation, 5-ethynyl-2'-deoxyuridine (EDU), transwell and wound healing assays to testify its function on the tumor progression. Based on TCGA database, we probed potential biological mechanism by which CHPF play its role via clusterProfiler package and GEPIA database and we validated their correlation by WB assay. Moreover, we explored its potential association with the tumor microenvironment (TME), immune infiltrated cells, immune checkpoints, tumor mutation burden (TMB) as well as microsatellite instability (MSI), and investigated immunotherapy sensitivity via Tumor Immune Dysfunction and Exclusion (TIDE) algorithm as well as potentially effective therapeutic drugs via pRRophetic algorithm.\nRESULTS: CHPF was identified upregulated in CRC tissues and cells, correlated with poor prognosis, and nodal metastasis status, stage and histological subtype. Down-regulation of CHPF inhibited CRC cell proliferation, migration and its expression correlated with wnt pathway key molecules. In addition, high expression of CHPF was positively correlated with TME scores, Regulatory T cells (Tregs) cell infiltration degree, Programmed death-1 (PD-1), MSI-high (MSI-H), and TIDE scores, however, not with TMB. Targeted drug analysis showed that patients with high CHPF expression were more sensitive to telatinib, recaparib, serdemetan, and trametinib.\nCONCLUSION: CHPF could promote the proliferation and migration of CRC cells and lead to poor prognosis, possibly through wnt pathways as well as changes in TME. Patients with high expression of CHPF had poor efficacy in immunotherapy, which might be related to Tregs cell infiltration. Above all, it might offer more reliable guidance for future immunotherapy.", "claims": [{"id": "claim-method", "statement": "Moreover, the survival value of CHPF expression in CRC patients were analyzed by PrognoScan (GSE17536) (http://dna00.bio.kyutech.ac.jp/PrognoScan/) [26], Kaplan–Meier Plotter (http://kmplot.com/analysis/) [27], as well as TCGA CRC cohort.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39292317", "locator": "sections[5] \"Clinicopathological correlation and survival analysis\" paragraph 2", "quote": "Moreover, the survival value of CHPF expression in CRC patients were analyzed by PrognoScan (GSE17536) (http://dna00.bio.kyutech.ac.jp/PrognoScan/) [26], Kaplan–Meier Plotter (http://kmplot.com/analysis/) [27], as well as TCGA CRC cohort."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data in our study could be obtained from TCGA, and GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39292317", "locator": "sections[30] \"notes\" paragraph 1", "quote": "All data in our study could be obtained from TCGA, and GEO database."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39292317"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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