The Mechanism and Prognostic Value of DNA Polymerase δ Subunits in Hepatocellular Carcinoma: Implications for Precision Therapy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35173474", "kind": "science-record", "revision": 3, "content_hash": "sha256:0d67cf2c89c685ae1eb9d06e138f4ae4ba7793d7b7c6ee60214b050679e0b8c4", "created_at": "2026-11-01T17:36:55Z", "updated_at": "2026-11-01T21:27:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Mechanism and Prognostic Value of DNA Polymerase δ Subunits in Hepatocellular Carcinoma: Implications for Precision Therapy.", "doi": "10.2147/IJGM.S347162", "pmid": "35173474", "authors": ["Qing Wang", "Song Zhang", "Qiaodong Xu", "Jiahong Liang", "Peidong Zhang", "Wenlong Huang", "Zhihuan Lin", "Shaodong Zheng", "Songgang Gu", "Jiang Yan"], "journal": "International journal of general medicine", "year": 2022, "abstract": "PURPOSE: Polymerase δ (POLD) proteins is a pivotal B-family DNA polymerase in the process of genome replication and repair and are comprised of POLD1-4. The predictive value of POLDs in hepatocellular carcinoma (HCC) has not been evaluated until now.\nPATIENTS AND METHODS: A total of 369 hepatocellular carcinoma samples and 50 adjacent normal samples were enrolled from the TCGA-LIHC database, and the GSE10186 database was also used. Transcription, methylation and genetic alteration status of HCC patients were evaluated by GEPIA, Kaplan-Meier plotter, cBioPortal, MethHC, MethSurv. SurvExpress was employed to generate the overall prognosis prediction signature of POLDs. POLDs coexpressed genes were explored and enriched in potential pathways. K-M curves were generated to compare the different survival results in different groups, while ROC curves were used to validate the efficiency of the POLD signature.\nRESULTS: All four POLD subunits were highly expressed in HCC tumor tissues. POLD1-3 and increased mRNA levels were also positively associated with advanced tumor stage and OS prognosis. Methylation in the promoter of POLDs affects mRNA expression and OS, especially for some specific CpG sites. Meanwhile, POLDs could preferably predict the prognosis for patients who suffered from a high gene mutation burden. We evaluated the combined prognostic predictive value of four POLD subunits in both the TCGA-LIHC and GSE10186 databases and recognized the statistically significant HR of the high-risk group, along with the reliable predictive value. The coexpressed gene sets and annotation results showed that the POLD coexpressed genes were mostly associated with DNA repair and cell cycle regulation pathways.\nCONCLUSION: POLD is an essential predictive factor for the prognosis of HCC. The united signature could precisely identify unfavorable clinical outcome of HCC.", "claims": [{"id": "claim-method", "statement": "Multivariate Cox regression analysis of POLDs was performed in OS to generate the coef and risk score formula.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35173474", "locator": "sections[10] \"Statistical Analysis\" paragraph 2", "quote": "Multivariate Cox regression analysis of POLDs was performed in OS to generate the coef and risk score formula."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are included within the article. The gene expression data can be accessed on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35173474", "locator": "sections[22] \"Data Sharing Statement\" paragraph 2", "quote": "The data used to support the findings of this study are included within the article. The gene expression data can be accessed on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined four-POLD prognostic signature identified unfavorable overall survival in both TCGA-LIHC and GSE10186 HCC cohorts.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "We also observed that a high risk indicated an unfavorable OS (HR=2.56, 95% CI: 1.71–3.84, P<0.001) (Figure 5C), and the AUC value was 0.655 (Figure 5D)."}, "evidence": [{"asset": "source:pmid:35173474", "locator": "sections[16] \"United Prognosis Predicting Value of Four POLDs\" paragraph 2", "quote": "We also observed that a high risk indicated an unfavorable OS (HR=2.56, 95% CI: 1.71–3.84, P<0.001) (Figure 5C), and the AUC value was 0.655 (Figure 5D)."}, {"asset": "source:pmid:35173474", "locator": "sections[16] \"United Prognosis Predicting Value of Four POLDs\" paragraph 2", "quote": "The high risk was also associated with poor prognosis in GSE10186 patients (HR=2.17, 95% CI: 1.05–4.47, P=0.03576), while the AUC value was 0.709 (Figure 5G and H)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The combined four-POLD prognostic signature identified unfavorable overall survival in both TCGA-LIHC and GSE10186 HCC cohorts.", "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:35173474"], "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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