Identification of a hypoxia-related gene prognostic signature in colorectal cancer based on bulk and single-cell RNA-seq.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36781976", "kind": "science-record", "revision": 2, "content_hash": "sha256:4d7d6097c7e007cd491065c673599dece7853f723eafa23886741515aa3f69ad", "created_at": "2026-11-01T19:01:22Z", "updated_at": "2026-11-01T21:30:08Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a hypoxia-related gene prognostic signature in colorectal cancer based on bulk and single-cell RNA-seq.", "doi": "10.1038/s41598-023-29718-2", "pmid": "36781976", "authors": ["Yihuan Qiao", "Xunliang Jiang", "Yaoting Li", "Ke Wang", "Rujie Chen", "Jun Liu", "Yongtao Du", "Li Sun", "Jipeng Li"], "journal": "Scientific reports", "year": 2023, "abstract": "Colorectal cancer (CRC) is the most common and fatal tumor in the gastrointestinal system. Its incidence and mortality rate have increased in recent years. Hypoxia, a persistent physiological tumor feature, plays a vital role in CRC tumorigenesis, metastasis, and tumor microenvironment (TME). Therefore, we constructed a hypoxia-related gene (HRG) nomogram to predict overall survival (OS) and explored the role of HRGs in the CRC TME. The Cancer Genome Atlas (TCGA) dataset was used as the training set, and two Gene Expression Omnibus datasets (GSE39582 and GSE103479) were used as the testing sets. HRGs were identified using the Gene Set Enrichment Analysis (GSEA) database. An HRG prognostic model was constructed in the training set using the least absolute shrinkage and selection operator regression algorithm and validated in the testing sets. Then, we analyzed tumor-infiltrating cells (TICs) using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. Furthermore, single-cell next-generation RNA sequencing (RNA-seq) was used to investigate HRG expression in different TICs in the GSE139555 dataset. Finally, reverse transcription polymerase chain reactions (RT-PCR) were used to validate HRG mRNA expression in ten pairs of CRC normal and cancer tissue samples. A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780). GSEA enrichment analysis identified six pathways enriched in the high-risk group. The TIC analysis indicated that the high-risk group had lower T-cell expression and higher neutrophil expression than the low-risk group. Furthermore, immune-related genes had an inseparable relationship with the HRG prognostic signature. Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) and glucose-6-phosphate isomerase (GPI) gene expression in natural killer (NK) and CD8+ T cells. RT-PCR in ten CRC normal-tumor tissue pairs showed that expression of the signature's six HRGs varied differently in cancerous and paracancerous tissues. The constructed HRG signature successfully predicted the OS of whole-stage CRC patients. In addition, we showed that the signature's six HRGs were closely associated with the TME in CRC, where hypoxia inhibits the antitumor function of T cells.", "claims": [{"id": "claim-method", "statement": "The most predictive signature was constructed using multivariate Cox regression analyses with the survival R package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36781976", "locator": "sections[5] \"HRG prognostic signature construction\" paragraph 2", "quote": "The most predictive signature was constructed using multivariate Cox regression analyses with the survival R package."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.The datasets generated and/or analysed during the current study are available in the TCGA and GEO repository, https://portal.gdc.cancer.gov/, https://www.ncbi.nlm.nih.gov/geo/.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36781976", "locator": "sections[22] \"Data availability\" paragraph 2", "quote": "The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.The datasets generated and/or analysed during the current study are available in the TCGA and GEO repository, https://portal.gdc.cancer.gov/, https://www.ncbi.nlm.nih.gov/geo/."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36781976", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six HRG prognostic signature was constructed, with a superior OS prediction ability in CRC patients (area under the receiver operating characteristic curve (AUC) at one year: 0.693, AUC at three years: 0.712, and AUC at five years: 0.780).", "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:36781976"], "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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"sample_count": 585, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "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:GSE103479 not downloaded", "asset:data:geo:GSE103479 licence not read", "asset:data:geo:GSE139555 not downloaded", "asset:data:geo:GSE139555 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": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, 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Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) a", "Materials and methods Single-cell RNA-seq analysis of HRGs The different TICs were gro", "owever, ALDOB was not expressed in any TICs. Single-cell RNA-seq analysis of HRGs. (A) The distribution of TI"], "order_basis": "paper_text_order:56", "id": "assay:1"}, {"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["orectal cancer based on bulk and single-cell RNA-seq.", "single-cell next-generation RNA sequencing (RNA-seq) was used to investigate HRG expression in d", "G prognostic signature. Based on single-cell RNA-seq data, we found elevated hexokinase 1 (HK1) a", "hm. 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