A comprehensive analysis of TRP-related gene signature, and immune infiltration in patients with colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39154317", "kind": "science-record", "revision": 2, "content_hash": "sha256:667d810c1d308d2dad6c2587f5c6478b896a5c5490de56bad66fc5672d083c14", "created_at": "2026-11-01T20:29:16Z", "updated_at": "2026-11-01T21:33:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A comprehensive analysis of TRP-related gene signature, and immune infiltration in patients with colorectal cancer.", "doi": "10.1007/s12672-024-01227-2", "pmid": "39154317", "authors": ["Yicheng Liu", "Xiaobing Yao", "Wenjun Zhao", "Jin Xu", "Haiyan Zhang", "Ting Huang", "Chuang Wu", "Jiajia Yang", "Cheng Tang", "Qianqian Ye", "Weiye Hu", "Qingming Wang"], "journal": "Discover oncology", "year": 2024, "abstract": "BACKGROUND: Transient receptor potential (TRP) channels are involved in the development and progression of tumors. However, their role in colorectal cancer (CRC) remains unclear, and this study aims to investigate the role of TRP-related genes in CRC.\nMETHODS: Data was obtained from The Cancer Genome Atlas (TCGA) database, and analyses were conducted on the GSE14333 and GSE38832 datasets to assess the prognosis and mark TRP-related genes (TRGs). Subsequently, clustering analysis and immune infiltration analysis were performed to explore the relevant TRGs. In vitro validation of key TRGs' gene and protein expression was conducted using human colon cancer cells.\nRESULTS: Compared to normal tissues, 8 TRGs were significantly upregulated in CRC, while 11 were downregulated. TRPA1 was identified as a protective prognostic factor, whereas TRPM5 (HR = 1.349), TRPV4 (HR = 1.289), and TRPV3 (HR = 1.442) were identified as prognostic risk factors. Receiver operating characteristic (ROC) curves and Kaplan-Meier (KM) analyses yielded similar results. Additionally, lower expression of TRPA1 and higher expression of TRPV4 and TRPM5 were negatively correlated with patient prognosis, and experimental validation confirmed the underexpression of TRPA1 and overexpression of TRPV4 and TRPM5 in CRC cell lines.\nCONCLUSION: This study identifies a TRP channel-related prognosis in CRC, providing a novel approach to stratifying CRC prognosis.", "claims": [{"id": "claim-method", "statement": "We conducted Cox regression analyses, including univariate and multivariate analyses, to identify the risk variables in clinical data and TRGs of CRC patients for building a nomogram.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39154317", "locator": "sections[6] \"A predictive nomogram of TRG construction\" paragraph 2", "quote": "We conducted Cox regression analyses, including univariate and multivariate analyses, to identify the risk variables in clinical data and TRGs of CRC patients for building a nomogram."}], "state": "complete"}, {"id": "claim-data-access", "statement": "RNA-sequencing data and clinical data were downloaded from The Cancer Genome Atlas (TCGA, https://cancergenome.nih.gov/) and The Genotype-Tissue Expression (GTEx, https://gtexportal.org/home/datasets) database. All data supporting the findings of this study were available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39154317", "locator": "sections[28] \"notes\" paragraph 1", "quote": "RNA-sequencing data and clinical data were downloaded from The Cancer Genome Atlas (TCGA, https://cancergenome.nih.gov/) and The Genotype-Tissue Expression (GTEx, https://gtexportal.org/home/datasets) database. All data supporting the findings of this study were available from the corresponding author upon reasonable request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:39154317"], "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": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39154317", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-024-01227-2", "sha256": "sha256:87e0232ece31c134c68a12db7edf56164041760adf59099a993f38287beffb64", "bytes": 27953, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1007/s12672-024-01227-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11330954", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "We conducted Cox regression analyses, including univariate and multivariate analyses, to identify the risk variables in clinical data and TRGs of CRC patients for building a nomogram."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {"p_value": "A p-value was calculated for KM c"}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-4", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "PCA"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": ["GSE14333 and GSE38832"], "resolved_accessions": [], "statements": ["RNA-sequencing data and clinical data were downloaded from The Cancer Genome Atlas (TCGA, https://cancergenome.nih.gov/) and The Genotype-Tissue Expression (GTEx, https://gtexportal.org/home/datasets) database. All data supporting the findings of this study were available from the corresponding author upon reasonable request."], "basis": "The paper names GSE14333 and GSE38832, but the accession does not resolve in the repository (no reason recorded), so the data cannot be reached from here. 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