Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34221079", "kind": "science-record", "revision": 7, "content_hash": "sha256:78ef0f8f820819afee2e568bf314509674f0069bcd93171542f837d252ab3b0a", "created_at": "2026-11-01T15:41:41Z", "updated_at": "2026-11-01T22:04:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis.", "doi": "10.1155/2021/5970085", "pmid": "34221079", "authors": ["Honglan Guo", "Qinqiao Fan"], "journal": "Evidence-based complementary and alternative medicine : eCAM", "year": 2021, "abstract": "BACKGROUND: We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR.\nMETHOD: With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC).\nRESULTS: HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948-0.983) in the TCGA cohort and 0.956 (95% CI: 0.932-0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway.\nCONCLUSION: HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.", "claims": [{"id": "claim-method", "statement": "Area under the curve (AUC) values obtained from the receiver operating characteristic (ROC) curve analysis was utilized to assess the diagnostic effectiveness of HMMR in both cohorts. In this study, a TCGA-LIHC cohort consisting of samples of 374 human HCC tissues and 50 nonneoplastic tissues, as well as clinicopathological characteristics of patients, was downloaded from the TCGA (https://portal.gdc.cancer.gov/) database. Furthermore, 240 HCC mRNA expression and 260 cases of patients with clinical data from the International Cancer Genome Consortium (ICGC) database were further downloaded (https://dcc.icgc.org/, LIRI-JP), among which 202 normal samples were from solid tissues and 240 primary HCC patients were included in this study to further validate the results yielded in the TCGA cohort.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34221079", "locator": "sections[5] \"2.3. Statistical Analysis\" paragraph 2", "quote": "Area under the curve (AUC) values obtained from the receiver operating characteristic (ROC) curve analysis was utilized to assess the diagnostic effectiveness of HMMR in both cohorts."}, {"asset": "source:pmid:34221079", "locator": "sections[3] \"2.1. Patients' Data\" paragraph 2", "quote": "In this study, a TCGA-LIHC cohort consisting of samples of 374 human HCC tissues and 50 nonneoplastic tissues, as well as clinicopathological characteristics of patients, was downloaded from the TCGA (https://portal.gdc.cancer.gov/) database."}, {"asset": "source:pmid:34221079", "locator": "sections[6] \"2.4. Validation in an External Cohort\" paragraph 2", "quote": "Furthermore, 240 HCC mRNA expression and 260 cases of patients with clinical data from the International Cancer Genome Consortium (ICGC) database were further downloaded (https://dcc.icgc.org/, LIRI-JP), among which 202 normal samples were from solid tissues and 240 primary HCC patients were included in this study to further validate the results yielded in the TCGA cohort."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in the present study are available from the TCGA (https://portal.gdc.cancer.gov/repository) database and the International Cancer Genome Consortium (https://dcc.icgc.org/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34221079", "locator": "sections[15] \"Data Availability\" paragraph 2", "quote": "The datasets used in the present study are available from the TCGA (https://portal.gdc.cancer.gov/repository) database and the International Cancer Genome Consortium (https://dcc.icgc.org/) database."}], "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:34221079"], "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. 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