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pmid:34717544
Cancer-associated fibroblasts impact the clinical outcome and treatment response in colorectal cancer via immune system modulation: a comprehensive genome-wide analysis.
Yu-Feng Chen · Zhao-Liang Yu · Min-Yi Lv · Ze-Rong Cai · Yi-Feng Zou · Ping Lan · Xiao-Jian Wu · Feng Gao
Molecular medicine (Cambridge, Mass.) · 2021 doi:10.1186/s10020-021-00402-3
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Complete file
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However, there is a lack of universal measures of CAFs in colorectal cancer (CRC). The aim of this study was to assess the utility of a fibroblast-related gene signature (FRGS) for predicting patient outcomes and reveal its relevant mechanism.\nMETHODS: The GSE39582 dataset, which includes 316 CRC patients who did not receive adjuvant chemotherapy was used as a discovery cohort to identify the prognostic fibroblast-related genes (FRGs). A total of 1352 CRC patients were divided into one training cohort (GSE39582, n = 461) and two validation cohorts (TCGA, n = 338; meta-validation, n = 553) for the construction of the FRGS and the verification of its prognostic value in stage II/III CRC patients. Functional annotation and analysis were performed to explore the underlying mechanism. The ability of the FRGS to predict immunotherapy response was further tested in a clear cell renal cell carcinoma (ccRCC) cohort.\nRESULTS: An 11-gene signature that had prognostic value for stage II/III CRC patients in both validation cohorts was developed (TCGA cohort: HR = 1.90, 95% CI 1.16-3.12, P < 0.01; meta-validation cohort: HR = 1.95, 95% CI 1.39-2.73, P < 0.001). A high level of CAFs was correlated with worse prognosis in CRC patients who did not receive adjuvant chemotherapy (HR = 3.63, 95% CI 2.24-5.88, P < 0.001). Importantly, patients in the low-risk group were found to be benefit from chemotherapy (P < 0.01), but not in the high CAF group (P > 0.05). Similar results were found in the TCGA cohort. Integrated with clinical characteristics, the FRGS was confirmed to be an independent prognostic factor in the multivariate analysis after adjustment for tumour TNM stage (GSE39582 cohort: HR = 3.19, 95% CI 1.88-5.41, P < 0.001; TCGA cohort: HR = 5.00, 95% CI 1.58-15.85, P = 0.007; meta-validation cohort: HR = 2.99, 95% CI 1.44-6.21, P = 0.003). Furthermore, the enrichment analysis found that the antitumour immune response was suppressed and the infiltration of CD4 T cells and M1 macrophages was depressed in the high CAF group. The FRGS was also found to have value in predicting for immunotherapy response in the ccRCC cohort.\nCONCLUSIONS: The 11-gene FRGS had independent prognostic value for CRC patients, as well as utility in the prediction of benefit from chemotherapy. CAFs in the tumour microenvironment might have an impact on the prognosis of CRC patients via inhibiting immune response.", "claims": [{"id": "claim-method", "statement": "Univariate analysis of the association of the FRGS and other clinicopathological factors with survival was performed using the log-rank test. Factors that were significantly associated with DFS and OS in univariate analyses were included in the Cox proportional hazards regression multivariate analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34717544", "locator": "sections[7] \"Statistical analysis\" paragraph 2", "quote": "Univariate analysis of the association of the FRGS and other clinicopathological factors with survival was performed using the log-rank test. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE14333"], "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": ["data:geo:GSE14333"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34717544", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s10020-021-00402-3", "sha256": 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"taxon": "Homo sapiens", "title": "Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE14333 not downloaded", "asset:data:geo:GSE14333 licence not read", "asset:data:geo:GSE17536 not downloaded", "asset:data:geo:GSE17536 licence not read", "asset:data:geo:GSE33113 not downloaded", "asset:data:geo:GSE33113 licence not read", "asset:data:geo:GSE37892 not downloaded", "asset:data:geo:GSE37892 licence not read", "asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": 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Factors that were significantly associated with DFS and OS in univariate analyses were included in the Cox proportional hazards regression multivariate analysis."}}, {"id": "method-2", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}], "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "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": "R1", "reachable": true, "accessions": ["GSE39582", "GSE14333", "GSE17536", "GSE37892", "GSE33113"], "resolved_accessions": ["GSE39582", "GSE14333", "GSE17536", "GSE37892", "GSE33113"], "statements": ["The datasets generated and analyzed during the current study are available in the GSE39582 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39582), TCGA (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga), GSE14333 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE14333), GSE17536 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536), GSE37892 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37892) and GSE33113 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33113)."], "basis": "The paper names GSE39582, GSE14333, GSE17536, GSE37892, GSE33113 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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