Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37013470", "kind": "science-record", "revision": 3, "content_hash": "sha256:48fcdc20de9e44ae6edbe5c1250d5172d48dd619cf097d7a48458c4a462279a2", "created_at": "2026-11-01T19:01:40Z", "updated_at": "2026-11-01T22:09:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer.", "doi": "10.1186/s12885-023-10779-5", "pmid": "37013470", "authors": ["Kunqiao Hong", "Qian Yang", "Haisen Yin", "Na Wei", "Wei Wang", "Baoping Yu"], "journal": "BMC cancer", "year": 2023, "abstract": "BACKGROUND: As a common malignant tumor, esophageal carcinoma (ESCA) has a low early diagnosis rate and poor prognosis. This study aimed to construct the prognostic features composed of ZNF family genes to effectively predict the prognosis of ESCA patients.\nMETHODS: The mRNA expression matrix and clinical data were downloaded from TCGA and GEO database. Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, and nomogram to evaluate the prognostic value within and across sets, separately and combined. We also validated the prognostic value of the six-gene signature using GSE53624 dataset. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). Finally, real-time quantitative PCR was used to detect the expression of six prognostic ZNF genes in twelve pairs of ESCA and adjacent normal tissues.\nRESULTS: A six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified. Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore, age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed that the six genes model was closely related to immune cells infiltration and could be used as a potential predictor of chemotherapy sensitivity.\nCONCLUSION: We identified six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized prevention and treatment.", "claims": [{"id": "claim-method", "statement": "Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37013470", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The Supplementary Material for this article can be found online at this study, further inquiries can be directed to the corresponding authors. 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The datasets analyzed during the current study are available online from the GSE53624 dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53624) and The Cancer Genome Atlas Program ()."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper identified a six-gene ZNF-family prognostic model that independently predicted overall survival in ESCA patients in both TCGA and GSE53624.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37013470", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified."}, {"asset": "source:pmid:37013470", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The paper identified a six-gene ZNF-family prognostic model that independently predicted overall survival in ESCA patients in both TCGA and GSE53624.", "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:37013470"], "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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