Phosphogluconate dehydrogenase is a predictive biomarker for immunotherapy in hepatocellular carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36338768", "kind": "science-record", "revision": 5, "content_hash": "sha256:da6d8133d723f8a613f48c72abc9b0c344a9986c7df557eabb0ab09e9b93e78e", "created_at": "2026-11-01T18:15:46Z", "updated_at": "2026-11-01T22:50:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Phosphogluconate dehydrogenase is a predictive biomarker for immunotherapy in hepatocellular carcinoma.", "doi": "10.3389/fonc.2022.993503", "pmid": "36338768", "authors": ["Tiantian Liu", "Jianni Qi", "Hao Wu", "Le Wang", "Lihui Zhu", "Chengyong Qin", "Jiao Zhang", "Qiang Zhu"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Background: Phosphogluconate dehydrogenase (PGD) is involved in the regulation of various tumors. However, its role in hepatocellular carcinoma (HCC) is poorly understood. This study tried to determine the prognostic efficacy of PGD and its value for immunotherapy in HCC.\nMethods: The data from the TCGA database was used to explore the predictive power of PGD expression and methylation on the overall survival (OS) of HCC through Cox regression and the Kaplan-Meier analysis. Then, we used the GEO and ICGC database to further verify the predictive power. Finally, the relationship between PGD and immune cells and the relationship between PGD and the efficacy of immunotherapy were explored through bioinformatics analysis in HCC.\nResults: PGD is highly expressed in HCC tissues, which is negatively regulated by PGD methylation. Low PGD expression and PGD hypermethylation predict better OS in HCC patients. Besides, a meta-analysis based on the TCGA, GSE14520, and ICGC databases further confirms that low PGD expression is closely related to favorable OS. Then, we find significant differences of immune cell infiltrations between high and low PGD expression groups. Expressions of immune checkpoints, most HLA members and tumor mutation burden (TMB) are higher in the high PGD expression group, which indicates beneficial efficacy of immunotherapy in this group. And the potential mechanisms of PGD are exhibited.\nConclusion: PGD is an independent prognostic factor of HCC patients and plays an important role in immune cell infiltration and immunotherapy, which indicates that PGD can be used as a predictive biomarker for HCC immunotherapy.", "claims": [{"id": "claim-method", "statement": "We evaluated the impact of PGD expression and PGD DNA methylation on overall survival (OS) in HCC patients from the TCGA database, using Kaplan-Meier survival analysis via the R package “survival.” A ROC curve was also performed with the R package of “survival ROC”. The prognostic significance of PGD for HCC patients was validated in the ICGC database. Moreover, a meta-analysis with all HCC patients based on the three databases was used to further verify and summarize the prognostic utility of PGD for HCC. We showed the result of a meta-analysis by forest plot, and pooled HR (hazard ratio) was calculated based on the fixed-effect model because there is no obvious heterogeneity (I2<50%).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36338768", "locator": "sections[4] \"Evaluation of PGD on the prognosis of HCC patients\" paragraph 2", "quote": "We evaluated the impact of PGD expression and PGD DNA methylation on overall survival (OS) in HCC patients from the TCGA database, using Kaplan-Meier survival analysis via the R package “survival.” A ROC curve was also performed with the R package of “survival ROC”. The prognostic significance of PGD for HCC patients was validated in the ICGC database. Moreover, a meta-analysis with all HCC patients based on the three databases was used to further verify and summarize the prognostic utility of PGD for HCC. We showed the result of a meta-analysis by forest plot, and pooled HR (hazard ratio) was calculated based on the fixed-effect model because there is no obvious heterogeneity (I2<50%)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that support the findings of this study are available in The Cancer Genome Atlas database at https://cancergenome.nih.gov, TIMER database at https://cistrome.shinyapps.io/timer, Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo under the accession number GSE14520, and International Cancer Genome Consortium database at https://dcc.icgc.org.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36338768", "locator": "sections[17] \"Data availability statement\" paragraph 2", "quote": "The data that support the findings of this study are available in The Cancer Genome Atlas database at https://cancergenome.nih.gov, TIMER database at https://cistrome.shinyapps.io/timer, Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo under the accession number GSE14520, and International Cancer Genome Consortium database at https://dcc.icgc.org."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Across TCGA, ICGC, and GSE14520, meta-analysis of 848 HCC patients showed that low PGD expression predicted better overall survival, with a pooled HR of 0.49 (95% CI 0.24–0.73).", "kind": "quantitative", "target": {"value": 0.282, "unit": "p-value", "tolerance": null, "source": "According to the results of the meta-analysis based on 848 HCC patients from the above three databases, the pooled HR and 95% CI of the relationship between PGD expression and OS were 0.49(0.24–0.73), and there was no significant heterogeneity between the three databases (I2 = 20.9%, P = 0.282, Figure 3E )."}, "evidence": [{"asset": "source:pmid:36338768", "locator": "sections[11] \"Verification of the prognostic value of PGD expression in ICGC and GEO database\" paragraph 4", "quote": "According to the results of the meta-analysis based on 848 HCC patients from the above three databases, the pooled HR and 95% CI of the relationship between PGD expression and OS were 0.49(0.24–0.73), and there was no significant heterogeneity between the three databases (I2 = 20.9%, P = 0.282, Figure 3E )."}, {"asset": "source:pmid:36338768", "locator": "sections[11] \"Verification of the prognostic value of PGD expression in ICGC and GEO database\" paragraph 4", "quote": "Therefore, we can conclude that low PGD expression is a good predictor of OS in HCC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Across TCGA, ICGC, and GSE14520, meta-analysis of 848 HCC patients showed that low PGD expression predicted better overall survival, with a pooled HR of 0.49 (95% CI 0.24–0.73).", "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:36338768"], "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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evaluated the impact of PGD expression and PGD DNA methylation on overall survival (OS) in HCC patients from the TCGA database, using Kaplan-Meier survival analysis via the R package “survival.” A ROC curve was also performed with the R package of “survival ROC”. The prognostic significance of PGD for HCC patients was validated in the ICGC database. Moreover, a meta-analysis with all HCC patients based on the three databases was used to further verify and summarize the prognostic utility of PGD for HCC. We showed the result of a meta-analysis by forest plot, and pooled HR (hazard ratio) was calculated based on the fixed-effect model because there is no obvious heterogeneity (I2<50%)."}}, {"id": "method-2", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-3", "family": "meta_analysis", "specific": "fixed_effects", "label": "Meta-analysis / evidence synthesis", "dsl_operations": [], "missing_operations": ["fixed_effects_pool"], "expressible": false, "parameters": {"i_squared": "use there is no obvious heterogeneity (I2<50%)"}, "data_shapes": ["study_level_effect_estimates"], "evidence": {"score": 0.8, "band": "high", "quote": "fixed-effect"}}, {"id": "method-4", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.8, "band": "high", "quote": "ROC curve"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "classification_metrics", "expected_value": 0.282, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE14520"], "resolved_accessions": ["GSE14520"], "statements": ["The data that support the findings of this study are available in The Cancer Genome Atlas database at https://cancergenome.nih.gov, TIMER database at https://cistrome.shinyapps.io/timer, Gene Expression Omnibus database at https://www.ncbi.nlm.nih.gov/geo under the accession number GSE14520, and International Cancer Genome Consortium database at https://dcc.icgc.org."], "basis": "The paper names GSE14520 in Gene Expression Omnibus database and the accession resolves in the repository. 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The prognostic significance of PGD for HCC patients was validated in the ICGC database. Moreover, a meta-analysis with all HCC patients based on the three databases was used to further verify and summarize the prognostic utility of PGD for HCC. We showed the result of a meta-analysis by forest plot, and pooled HR (hazard ratio) was calculated based on the fixed-effect model because there is no obvious heterogeneity (I2<50%)."], "order_basis": "analysis_only", "id": "assay:1"}]}