Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35280985", "kind": "science-record", "revision": 4, "content_hash": "sha256:6b4016b75913e5e366337ea9ef864dc826d83cd3d742b37b8a9d5727b11b403d", "created_at": "2026-11-01T18:14:03Z", "updated_at": "2026-11-01T22:06:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy.", "doi": "10.3389/fimmu.2022.839362", "pmid": "35280985", "authors": ["Dechao Feng", "Xu Shi", "Facai Zhang", "Qiao Xiong", "Qiang Wei", "Lu Yang"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Background: We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy.\nMethods: We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages.\nResults: SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP.\nConclusions: The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.", "claims": [{"id": "claim-method", "statement": "We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35280985", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35280985", "locator": "sections[12] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing RP.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35280985", "locator": "sections[11] \"Conclusions\" paragraph 2", "quote": "The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing RP."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing RP.", "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:35280985"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE46602"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE46602"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35280985", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.839362", "sha256": "sha256:4a5a46ffc98ce210cb554d67d9c0e2b7b013013e16fae0efae6419b4c0fe7e90", "bytes": 50847, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.839362", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8908254", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE46602", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE46602", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE46602", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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