Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33778002", "kind": "science-record", "revision": 6, "content_hash": "sha256:cdf0c58e27670e2d8095f8166e2697fe936a87ec1887f524166febe0b7a4e47a", "created_at": "2026-11-01T15:41:30Z", "updated_at": "2026-11-01T21:25:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer.", "doi": "10.3389/fmolb.2021.608369", "pmid": "33778002", "authors": ["Gongwei Long", "Wei Ouyang", "Yucong Zhang", "Guoliang Sun", "Jiahua Gan", "Zhiquan Hu", "Heng Li"], "journal": "Frontiers in molecular biosciences", "year": 2021, "abstract": "Background: The incidence of prostate cancer (PCa) is high and increasing worldwide. The prognosis of PCa is relatively good, but it is important to identify the patients with a high risk of biochemical recurrence (BCR) so that additional treatment could be applied. Method: Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) to serve as training data. The GSE84042 dataset was used as a validation set. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a DNA repair gene (DRG) signature. The performance of the DRG signature was assessed based on Kaplan-Meier curve, receiver operating characteristic (ROC), and Harrell's concordance index (C-index). Furtherly, a prognostic nomogram was established and evaluated likewise. Results: A novel four DRG signature was established to predict BCR of PCa, which included POLM, NUDT15, AEN, and HELQ. The ROC and C index presented good performance in both training dataset and validation dataset. The patients were stratified by the signature into high- and low-risk groups with distinct BCR survival. Multivariate Cox analysis revealed that the DRG signature is an independent prognostic factor for PCa. Also, the DRG signature high-risk was related to a higher homologous recombination deficiency (HRD) score. The nomogram, incorporating the DRG signature and clinicopathological parameters, was able to predict the BCR with high efficiency and showed superior performance compared to models that consisted of only clinicopathological parameters. Conclusion: Our study identified a DRG signature and established a prognostic nomogram, which were reliable in predicting the BCR of PCa. This model could help with individualized treatment and medical decision making.", "claims": [{"id": "claim-method", "statement": "Next, we used the least absolute shrinkage and selection operator (LASSO) method for variable selection in a Cox regression model to determine significant prognostic genes, and one standard error (SE) above the minimum criteria was selected.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33778002", "locator": "sections[4] \"Signature Generation and Statistical Analysis\" paragraph 2", "quote": "Next, we used the least absolute shrinkage and selection operator (LASSO) method for variable selection in a Cox regression model to determine significant prognostic genes, and one standard error (SE) above the minimum criteria was selected."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) (GSE84042).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33778002", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) (GSE84042)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "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:33778002"], "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:GSE84042"], "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:GSE84042"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33778002", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fmolb.2021.608369", "sha256": "sha256:b1dc4c70c2e703f724879cad2133097d996c73301eb9a13262d8644cb09f8090", "bytes": 50484, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fmolb.2021.608369", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7991107", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE84042", "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=GSE84042", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE84042", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) (GSE84042).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) (GSE84042).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2226207", "GSM2226208", "GSM2226209", "GSM2226210", "GSM2226211", "GSM2226212", "GSM2226213", "GSM2226214", "GSM2226215", "GSM2226216", "GSM2226217", "GSM2226218", "GSM2226219", "GSM2226220", "GSM2226221", "GSM2226222", "GSM2226223", "GSM2226224", "GSM2226225", "GSM2226226", "GSM2226227", "GSM2226228", "GSM2226229", "GSM2226230", "GSM2226231", "GSM2226232", "GSM2226233", "GSM2226234", "GSM2226235", "GSM2226236", "GSM2226237", "GSM2226238", "GSM2226239", "GSM2226240", "GSM2226241", "GSM2226242", "GSM2226243", "GSM2226244", "GSM2226245", "GSM2226246", "GSM2226247", "GSM2226248", "GSM2226249", "GSM2226250", "GSM2226251", "GSM2226252", "GSM2226253", "GSM2226254", "GSM2226255", "GSM2226256", "GSM2226257", "GSM2226258", "GSM2226259", "GSM2226260", "GSM2226261", "GSM2226262", "GSM2226263", "GSM2226264", "GSM2226265", "GSM2226266", "GSM2226267", "GSM2226268", "GSM2226269", "GSM2226270", "GSM2226271", "GSM2226272", "GSM2226273", "GSM2226274", "GSM2226275", "GSM2226276", "GSM2226277", "GSM2226278", "GSM2226279"], "sample_count": 73, "group_sizes": null, "group_sizes_basis": null, "platform": "16686;17586", "taxon": "Homo sapiens", "title": "Genomic hallmarks of localized, non-indolent prostate cancer", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33778002:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:5b5e2b72ac12292d20ed5f6557aa91f202b81872c26deef20f489261ca29e4ac", "bytes": 2461, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[9]/table-wrap[1]#T1", "version": null, "note": "Summary of performance of different models.", "structure": {"pmcid": "PMC7991107", "section_index": 9, "section_title": "Construction of the DRG Signature in TCGA Cohort", "row_count": 26, "column_count": 6}, "table": {"label": "TABLE 1", "caption": "Summary of performance of different models.", "rows": [["Parameters", "TCGA dataset", "GSE84042"], ["Value and 95% CI", "p value", "Value and 95% CI", "p value"], ["C Index of DRG signature", "0.777 (0.722–0.831)", "< 0.001", "0.634 (0.516–0.752)", "0.026"], ["C Index of Nomogram,", "0.780 (0.722–0.838)", "< 0.001", "0.750 (0.630–0.870)", "<0.001"], ["C Index of Clinical model", "0.711 (0.642–0.780)", "< 0.001", "0.680 (0.548–0.811)", "0.007"], ["C Index of Walz‘s model", "0.691 (0.620–0.762)", "< 0.001", "0.678 (0.535–0.822)", "0.014"], ["Nomogram vs clinical model", "IDI of 1 year", "0.040 (0.014–0.083)", "< 0.001", "0.066 (−0.028–0.230)", "0.170"], ["NRI of 1 year", "0.511 (0.159–0.662)", "0.016", "0.374 (−0.155–0.651)", "0.106"], ["IDI of 2 years", "0.046 (0.012–0.093)", "< 0.001", "0.068 (−0.017–0.218)", "0.128"], ["NRI of 2 years", "0.452 (0.031–0.610)", "0.042", "0.335 (−0.091–0.584)", "0.112"], ["IDI of 3 years", "0.076 (0.017–0.144)", "0.010", "0.105 (−0.039–0.279)", "0.138"], ["NRI of 3 years", "0.477 (0.055–0.616)", "0.028", "0.357 (−0.094–0.576)", "0.086"], ["IDI of 4 years", "0.072 (-0.001–0.150)", "0.056", "0.113 (−0.031–0.280)", "0.098"], ["NRI of 4 years", "0.376 (-0.030–0.551)", "0.068", "0.396 (−0.005–0.618)", "0.052"], ["IDI of 5 years", "0.049 (-0.037–0.131)", "0.276", "0.124 (−0.012–0.295)", "0.074"], ["NRI of 5 years", "0.302 (-0.118–0.496)", "0.128", "0.424 (0.017–0.638)", "0.040"], ["Nomogram vs Walz‘s model", "IDI of 1 year", "0.053 (0.021–0.098)", "< 0.001", "0.057 (−0.018–0.199)", "0.129"], ["NRI of 1 year", "0.052 (0.269–0.695)", "< 0.001", "0.388 (−0.299–0.636)", "0.378"], ["IDI of 2 years", "0.057 (0.019–0.108)", "0.006", "0.068 (−0.013–0.196)", "0.102"], ["NRI of 2 years", "0.428 (0.220–0.596)", "< 0.001", "0.350 (−0.134–0.587)", "0.194"], ["IDI of 3 years", "0.110 (0.039–0.195)", "< 0.001", "0.078 (−0.042–0.193)", "0.179"], ["NRI of 3 years", "0.435 (0.208–0.579)", "0.002", "0.373 (−0.301–0.575)", "0.289"], ["IDI of 4 years", "0.139 (0.049–0.242)", "< 0.001", "0.084 (−0.012–0.235)", "0.090"], ["NRI of 4 years", "0.380 (0.157–0.539)", "0.004", "0.413 (−0.205–0.608)", "0.169"], ["IDI of 5 years", "0.121 (0.009–0.231)", "0.038", "0.087 (−0.014–0.208)", "0.090"], ["NRI of 5 years", "0.309 (0.055–0.498)", "0.024", "0.424 (−0.202–0.637)", "0.209"]], "row_count": 26, "column_count": 6, "numeric_cells": 119, "header_rows": 2, "locator": "section[9]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:33778002:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:d1301d3eabb5b41d15e01546a5b602c52b3c0d7e5f96288e0a9a1e95de4d0807", "bytes": 1125, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[1]#T2", "version": null, "note": "Outcomes of univariate and multivariate cox regression analysis.", "structure": {"pmcid": "PMC7991107", "section_index": 12, "section_title": "Identification of Independent Prognostic Parameters", "row_count": 8, "column_count": 9}, "table": {"label": "TABLE 2", "caption": "Outcomes of univariate and multivariate cox regression analysis.", "rows": [["Variable", "TCGA dataset", "GSE84042"], ["Univariate analysis", "Multivariate analysis", "Univariate analysis", "Multivariate analysis"], ["HR and 95% CI", "p value", "HR and 95% CI", "p value", "HR and 95% CI", "p value", "HR and 95% CI", "p value"], ["Age", "0.995 (0.957–1.036)", "0.819", "NA", "NA", "0.980 (0.908–1.058)", "0.612", "NA", "NA"], ["Pathologic T (ref: T2)T3-T4", "4.942 (2.233–10.940)", "< 0.001", "2.280 (0.951–5.464)", "0.065", "3.251 (1.124–9.408)", "0.0296", "4.467 (1.520–13.130)", "0.007"], ["Gleason score", "2.113 (1.613–2.768)", "< 0.001", "1.541 (1.145–2.074)", "0.004", "2.208 (0.499–9.770)", "0.296", "NA", "NA"], ["PSA", "1.021 (1.005–1.037)", "0.009", "1.008 (0.987–1.029)", "0.465", "1.030 (0.955–1.111)", "0.442", "NA", "NA"], ["DRG signature (ref: low risk) High risk", "5.296 (3.013–9.310)", "< 0.001", "3.462 (1.927–6.221)", "< 0.001", "0.293 (0.101–0.850)", "0.024", "4.672 (1.580–13.810)", "0.005"]], "row_count": 8, "column_count": 9, "numeric_cells": 37, "header_rows": 3, "locator": "section[12]/table-wrap[1]#T2"}}], "gaps": ["asset:data:geo:GSE84042 not downloaded", "asset:data:geo:GSE84042 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "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": 1.0, "band": "verbatim", "quote": "Next, we used the least absolute shrinkage and selection operator (LASSO) method for variable selection in a Cox regression model to determine significant prognostic genes, and one standard error (SE) above the minimum criteria was selected."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE84042"], "resolved_accessions": ["GSE84042"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) (GSE84042)."], "basis": "The paper names GSE84042 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:33778002", "data:geo:GSE84042", "asset:table:pmid:33778002:1", "asset:table:pmid:33778002:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE84042"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:28:38Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 41271, "completion_tokens": 1333, "cached_tokens": 785}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:33778002", "type": "paper", "label": "pmid:33778002"}, {"id": "source:pmid:33778002", "type": "manuscript", "label": "PMID 33778002 full text"}, {"id": "data:geo:GSE84042", "type": "dataset", "label": "GEO GSE84042"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33778002", "type": "paper", "label": "pmid:33778002"}, {"id": "source:pmid:33778002", "type": "manuscript", "label": "PMID 33778002 full text"}, {"id": "data:geo:GSE84042", "type": "dataset", "label": "GEO GSE84042"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33778002", "type": "extraction", "used": ["source:pmid:33778002"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE84042", "type": "accession_resolution", "used": ["data:geo:GSE84042"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:33778002", "parent_hash": "sha256:bc6e73cbc760310226a30f3c088847122060f68674cd33d5573f53d536dd9f10", "fork_of": null, "generation": 5}, "gaps": ["asset:data:geo:GSE84042 licence not read", "asset:data:geo:GSE84042 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Next, we used the least absolute shrinkage and selection operator (LASSO) method for variable selection in a Cox regression model to determine significant prognostic genes, and one standard error (SE) above the minimum criteria was selected."], "order_basis": "analysis_only", "id": "assay:1"}]}