A prediction model for prognosis of gastric adenocarcinoma based on six metabolism-related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36852096", "kind": "science-record", "revision": 3, "content_hash": "sha256:40216409991804549d1bcc2b1c5350d5e2019f3028e0c01c746747e65a49b913", "created_at": "2026-11-01T19:01:29Z", "updated_at": "2026-11-01T22:08:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A prediction model for prognosis of gastric adenocarcinoma based on six metabolism-related genes.", "doi": "10.1016/j.bbrep.2023.101440", "pmid": "36852096", "authors": ["Jingyu Zhao", "Yu Liu", "Qianwen Cui", "Rongli He", "Jia-Rong Zhao", "Li Lu", "Hong-Qiang Wang", "Haiming Dai", "Hongzhi Wang", "Wulin Yang"], "journal": "Biochemistry and biophysics reports", "year": 2023, "abstract": "Background: The study of tumor metabolism is of great value to elucidate the mechanism of tumorigenesis and predict the prognosis of patients. However, the prognostic role of metabolism-related genes (MRGs) in gastric adenocarcinoma (GAD) remains poorly understood.\nMethods: We downloaded the gene chip dataset GSE79973 (n = 20) of GAD from the Gene Expression Omnibus (GEO) database to compare differentially expressed genes (DEGs) between normal and tumor tissues. We then extracted MRGs from these DEGs and systematically investigated the prognostic value of these differential MRGs for predicting patients' overall survival by univariable and multivariable Cox regression analysis. Six metabolic genes (ACOX3, APOE, DIO2, HSD17B4, NUAK1, and WHSC1L1) were identified as prognosis-associated hub genes, which were used to build a prognostic model in the training dataset GSE15459 (n = 200), and then validated in the dataset GSE62254 (n = 300).\nResults: Patients were divided into high-risk and low-risk subgroups based on the model's risk score, and it was found that patients in the high-risk subgroup had shorter overall survival than those in the low-risk subgroup, both in the training and testing datasets. In addition, for the training and testing cohorts, the area under the ROC curve of the prognostic model for one-year survival prediction was 0.723 and 0.667, respectively, indicating that the model has good predictive performance. Furthermore, we established a nomogram based on tumor stage and risk score to effectively predict the overall survival (OS) of GAD patients. The expression of 6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further confirmed that their expression influenced OS in GAD patients.\nConclusion: Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy.", "claims": [{"id": "claim-method", "statement": "Univariable Cox regression analysis was performed on the training cohort GSE15459 with 200 samples. According to a P-value less than 0.001, 16 metabolic genes associated with survival were identified (APOE, ATP5F1, CBX1, CYP4F12, DIO2, GAK, HSD17B4, LOX, MAP4K4, NUAK1, PDE3A, SCP2, SLC25A20, TGM2, WHSC1L1). Based on preliminarily selected prognostic genes, we established a multivariable Cox proportional risk regression model to predict the prognosis of patients with GAD and calculate the risk score.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36852096", "locator": "sections[6] \"Prognostic model construction\" paragraph 2", "quote": "Univariable Cox regression analysis was performed on the training cohort GSE15459 with 200 samples. According to a P-value less than 0.001, 16 metabolic genes associated with survival were identified (APOE, ATP5F1, CBX1, CYP4F12, DIO2, GAK, HSD17B4, LOX, MAP4K4, NUAK1, PDE3A, SCP2, SLC25A20, TGM2, WHSC1L1). Based on preliminarily selected prognostic genes, we established a multivariable Cox proportional risk regression model to predict the prognosis of patients with GAD and calculate the risk score."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36852096", "locator": "sections[33] \"Data Availability Statement\" paragraphs 1-3", "quote": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study established a six-metabolism-related-gene prognostic model for gastric adenocarcinoma that predicts overall survival and has potential clinical value.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36852096", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Collectively, the 6 MRGs signature might be a reliable tool for assessing OS in GAD patients, with potential application value in clinical decision-making and individualized therapy."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study established a six-metabolism-related-gene prognostic model for gastric adenocarcinoma that predicts overall survival and has potential clinical value.", "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:36852096"], "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:GSE15459"], "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:GSE15459"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36852096", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.bbrep.2023.101440", "sha256": "sha256:210246c40e58f2d307d23e0d94c6a5d9b96d39b71fcc0f2004485d8e7184807e", "bytes": 37647, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.bbrep.2023.101440", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9957706", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE15459", "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=GSE15459", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE15459", "version": null, "note": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM387788", "GSM387789", "GSM387790", "GSM387791", "GSM387792", "GSM387793", "GSM387794", "GSM387795", "GSM387796", "GSM387797", "GSM387798", "GSM387799", "GSM387800", "GSM387801", "GSM387802", "GSM387803", "GSM387804", "GSM387805", "GSM387806", "GSM387807", "GSM387808", "GSM387809", "GSM387810", "GSM387811", "GSM387812", "GSM387813", "GSM387814", "GSM387815", "GSM387816", "GSM387817", "GSM387818", "GSM387819", "GSM387820", "GSM387821", "GSM387822", "GSM387823", "GSM387824", "GSM387825", "GSM387826", "GSM387827", "GSM387828", "GSM387829", "GSM387830", "GSM387831", "GSM387832", "GSM387833", "GSM387834", "GSM387835", "GSM387836", "GSM387837", "GSM387838", "GSM387839", "GSM387840", "GSM387841", "GSM387842", "GSM387843", "GSM387844", "GSM387845", "GSM387846", "GSM387847", "GSM387848", "GSM387849", "GSM387850", "GSM387851", "GSM387852", "GSM387853", "GSM387854", "GSM387855", "GSM387856", "GSM387857", "GSM387858", "GSM387859", "GSM387860", "GSM387861", "GSM387862", "GSM387863", "GSM387864", "GSM387865", "GSM387866", "GSM387867", "GSM387868", "GSM387869", "GSM387870", "GSM387871", "GSM387872", "GSM387873", "GSM387874", "GSM387875", "GSM387876", "GSM387877", "GSM387878", "GSM387879", "GSM387880", "GSM387881", "GSM387882", "GSM387883", "GSM387884", "GSM387885", "GSM387886", "GSM387887", "GSM387888", "GSM387889", "GSM387890", "GSM387891", "GSM387892", "GSM387893", "GSM387894", "GSM387895", "GSM387896", "GSM387897", "GSM387898", "GSM387899", "GSM387900", "GSM387901", "GSM387902", "GSM387903", "GSM387904", "GSM387905", "GSM387906", "GSM387907", "GSM387908", "GSM387909", "GSM387910", "GSM387911", "GSM387912", "GSM387913", "GSM387914", "GSM387915", "GSM387916", "GSM387917", "GSM387918", "GSM387919", "GSM387920", "GSM387921", "GSM387922", "GSM387923", "GSM387924", "GSM387925", "GSM387926", "GSM387927", "GSM387928", "GSM387929", "GSM387930", "GSM387931", "GSM387932", "GSM387933", "GSM387934", "GSM387935", "GSM387936", "GSM387937", "GSM387938", "GSM387939", "GSM387940", "GSM387941", "GSM387942", "GSM387943", "GSM387944", "GSM387945", "GSM387946", "GSM387947", "GSM387948", "GSM387949", "GSM387950", "GSM387951", "GSM387952", "GSM387953", "GSM387954", "GSM387955", "GSM387956", "GSM387957", "GSM387958", "GSM387959", "GSM387960", "GSM387961", "GSM387962", "GSM387963", "GSM387964", "GSM387965", "GSM387966", "GSM387967", "GSM387968", "GSM387969", "GSM387970", "GSM387971", "GSM387972", "GSM387973", "GSM387974", "GSM387975", "GSM387976", "GSM387977", "GSM387978", "GSM387979", "GSM387980", "GSM387981", "GSM387982", "GSM387983", "GSM387984", "GSM387985", "GSM387986", "GSM387987"], "sample_count": 200, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gastric Cancer Project '08 (Singapore Patient Cohort)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE62254", "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=GSE62254", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE62254", "version": null, "note": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1523727", "GSM1523728", "GSM1523729", "GSM1523744", "GSM1523745", "GSM1523746", "GSM1523747", "GSM1523748", "GSM1523765", "GSM1523768", "GSM1523769", "GSM1523770", "GSM1523771", "GSM1523772", "GSM1523773", "GSM1523774", "GSM1523775", "GSM1523776", "GSM1523777", "GSM1523778", "GSM1523779", "GSM1523780", "GSM1523781", "GSM1523782", "GSM1523783", "GSM1523784", "GSM1523785", "GSM1523786", "GSM1523787", "GSM1523788", "GSM1523789", "GSM1523790", "GSM1523791", "GSM1523792", "GSM1523793", "GSM1523794", "GSM1523795", "GSM1523796", "GSM1523797", "GSM1523798", "GSM1523799", "GSM1523800", "GSM1523801", "GSM1523802", "GSM1523803", "GSM1523804", "GSM1523805", "GSM1523806", "GSM1523807", "GSM1523808", "GSM1523809", "GSM1523810", "GSM1523811", "GSM1523812", "GSM1523813", "GSM1523814", "GSM1523815", "GSM1523816", "GSM1523817", "GSM1523818", "GSM1523819", "GSM1523820", "GSM1523821", "GSM1523822", "GSM1523823", "GSM1523824", "GSM1523825", "GSM1523826", "GSM1523827", "GSM1523828", "GSM1523829", "GSM1523830", "GSM1523831", "GSM1523832", "GSM1523833", "GSM1523834", "GSM1523835", "GSM1523836", "GSM1523837", "GSM1523838", "GSM1523839", "GSM1523840", "GSM1523841", "GSM1523842", "GSM1523843", "GSM1523844", "GSM1523845", "GSM1523846", "GSM1523847", "GSM1523848", "GSM1523849", "GSM1523850", "GSM1523851", "GSM1523852", "GSM1523853", "GSM1523854", "GSM1523855", "GSM1523856", "GSM1523857", "GSM1523858", "GSM1523859", "GSM1523860", "GSM1523861", "GSM1523862", "GSM1523863", "GSM1523864", "GSM1523865", "GSM1523866", "GSM1523867", "GSM1523868", "GSM1523869", "GSM1523870", "GSM1523871", "GSM1523872", "GSM1523873", "GSM1523874", "GSM1523875", "GSM1523876", "GSM1523877", "GSM1523878", "GSM1523879", "GSM1523880", "GSM1523881", "GSM1523882", "GSM1523883", "GSM1523884", "GSM1523885", "GSM1523886", "GSM1523887", "GSM1523888", "GSM1523889", "GSM1523890", "GSM1523891", "GSM1523892", "GSM1523893", "GSM1523894", "GSM1523895", "GSM1523896", "GSM1523897", "GSM1523898", "GSM1523899", "GSM1523901", "GSM1523903", "GSM1523904", "GSM1523905", "GSM1523906", "GSM1523908", "GSM1523909", "GSM1523910", "GSM1523911", "GSM1523918", "GSM1523919", "GSM1523920", "GSM1523921", "GSM1523922", "GSM1523923", "GSM1523924", "GSM1523925", "GSM1523926", "GSM1523927", "GSM1523928", "GSM1523929", "GSM1523930", "GSM1523931", "GSM1523932", "GSM1523933", "GSM1523934", "GSM1523935", "GSM1523936", "GSM1523937", "GSM1523938", "GSM1523939", "GSM1523940", "GSM1523941", "GSM1523942", "GSM1523943", "GSM1523944", "GSM1523945", "GSM1523946", "GSM1523947", "GSM1523948", "GSM1523949", "GSM1523950", "GSM1523951", "GSM1523952", "GSM1523953", "GSM1523954", "GSM1523955", "GSM1523956", "GSM1523957", "GSM1523958", "GSM1523959", "GSM1523960", "GSM1523961", "GSM1523962", "GSM1523963", "GSM1523964", "GSM1523965", "GSM1523966", "GSM1523967", "GSM1523968", "GSM1523969", "GSM1523970", "GSM1523971", "GSM1523972", "GSM1523973", "GSM1523974", "GSM1523975", "GSM1523976", "GSM1523977", "GSM1523978", "GSM1523979", "GSM1523980", "GSM1523981", "GSM1523982", "GSM1523983", "GSM1523984", "GSM1523985", "GSM1523986", "GSM1523987", "GSM1523988", "GSM1523989", "GSM1523990", "GSM1523991", "GSM1523992", "GSM1523993", "GSM1523994", "GSM1523995", "GSM1523996", "GSM1523997", "GSM1523998", "GSM1523999", "GSM1524000", "GSM1524001", "GSM1524002", "GSM1524003", "GSM1524004", "GSM1524005", "GSM1524006", "GSM1524007", "GSM1524008", "GSM1524009", "GSM1524010", "GSM1524011", "GSM1524012", "GSM1524013", "GSM1524014", "GSM1524015", "GSM1524016", "GSM1524017", "GSM1524018", "GSM1524019", "GSM1524020", "GSM1524021", "GSM1524022", "GSM1524023", "GSM1524024", "GSM1524025", "GSM1524026", "GSM1524027", "GSM1524028", "GSM1524029", "GSM1524030", "GSM1524031", "GSM1524032", "GSM1524033", "GSM1524034", "GSM1524035", "GSM1524036", "GSM1524037", "GSM1524038", "GSM1524039", "GSM1524040", "GSM1524041", "GSM1524042", "GSM1524043", "GSM1524044", "GSM1524045", "GSM1524046", "GSM1524047", "GSM1524048", "GSM1524049", "GSM1524050", "GSM1524051", "GSM1524052", "GSM1524053", "GSM1524054", "GSM1524055", "GSM1524056", "GSM1524057", "GSM1524058", "GSM1524059", "GSM1524060", "GSM1524061", "GSM1524062", "GSM1524068", "GSM1524069", "GSM1524070", "GSM1524071", "GSM1524072"], "sample_count": 300, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Molecular analysis of gastric cancer identifies discrete subtypes associated with distinct clinical characteristics and survival outcomes: the ACRG (Asian Cancer Research Group) study [gastric tumors]", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE79973", "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=GSE79973", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE79973", "version": null, "note": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2109532", "GSM2109533", "GSM2109534", "GSM2109535", "GSM2109536", "GSM2109537", "GSM2109538", "GSM2109539", "GSM2109540", "GSM2109541", "GSM2109542", "GSM2109543", "GSM2109544", "GSM2109545", "GSM2109546", "GSM2109547", "GSM2109548", "GSM2109549", "GSM2109550", "GSM2109551"], "sample_count": 20, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Expression data from gastric cancer and paried normal tissues", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE62254 not downloaded", "asset:data:geo:GSE62254 licence not read", "asset:data:geo:GSE79973 not downloaded", "asset:data:geo:GSE79973 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": "Univariable Cox regression analysis was performed on the training cohort GSE15459 with 200 samples. According to a P-value less than 0.001, 16 metabolic genes associated with survival were identified (APOE, ATP5F1, CBX1, CYP4F12, DIO2, GAK, HSD17B4, LOX, MAP4K4, NUAK1, PDE3A, SCP2, SLC25A20, TGM2, WHSC1L1). Based on preliminarily selected prognostic genes, we established a multivariable Cox proportional risk regression model to predict the prognosis of patients with GAD and calculate the risk score."}}, {"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"}}, {"id": "method-3", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"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": 0.7, "band": "medium", "quote": "ROC curve"}}], "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": ["GSE79973", "GSE15459", "GSE62254"], "resolved_accessions": ["GSE79973", "GSE15459", "GSE62254"], "statements": ["The datasets presented in this study can be found in online repositories, as mentioned in the “Materials and Methods” section. All data related to this study are available from the corresponding author upon reasonable request.\nThe data that has been used is confidential."], "basis": "The paper names GSE79973, GSE15459, GSE62254 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:36852096", "data:geo:GSE15459"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE15459"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:32:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 11546, "completion_tokens": 1611, "cached_tokens": 128}}, "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:36852096", "type": "paper", "label": "pmid:36852096"}, {"id": "source:pmid:36852096", "type": "manuscript", "label": "PMID 36852096 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36852096", "type": "paper", "label": "pmid:36852096"}, {"id": "source:pmid:36852096", "type": "manuscript", "label": "PMID 36852096 full text"}, {"id": "data:geo:GSE15459", "type": "dataset", "label": "GEO GSE15459"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36852096", "type": "extraction", "used": ["source:pmid:36852096"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE15459", "type": "accession_resolution", "used": ["data:geo:GSE15459"], "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:36852096", "parent_hash": "sha256:1e663e4aa25ea55e6877d1006b317495a44db821ecd2d28ecc5c78cd31077526", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE15459 licence not read", "asset:data:geo:GSE15459 not downloaded", "asset:data:geo:GSE62254 licence not read", "asset:data:geo:GSE62254 not downloaded", "asset:data:geo:GSE79973 licence not read", "asset:data:geo:GSE79973 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["6 MRGs at the protein level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis furthe", "level was confirmed by immunohistochemistry (IHC). Kaplan-Meier survival analysis further con", "GAD patients, totally 8 pairs of samples for immunohistochemistry. All of these patients were diagnosed by pat"], "order_basis": "paper_text_order:1704", "id": "assay:1"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["ssed using the same on-chip platform GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array, Santa Clar"], "order_basis": "paper_text_order:2906", "id": "assay:2"}, {"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": ["Univariable Cox regression analysis was performed on the training cohort GSE15459 with 200 samples. According to a P-value less than 0.001, 16 metabolic genes associated with survival were identified (APOE, ATP5F1, CBX1, CYP4F12, DIO2, GAK, HSD17B4, LOX, MAP4K4, NUAK1, PDE3A, SCP2, SLC25A20, TGM2, WHSC1L1). Based on preliminarily selected prognostic genes, we established a multivariable Cox proportional risk regression model to predict the prognosis of patients with GAD and calculate the risk score."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}