Unveiling Prognostic RNA Biomarkers through a Multi-Cohort Study in Colorectal Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38542291", "kind": "science-record", "revision": 3, "content_hash": "sha256:faef9a8e601b981dcf7731bddce2b3bf166bc4689a51417e1056ec14ed33ee73", "created_at": "2026-11-01T19:20:29Z", "updated_at": "2026-11-01T22:11:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Unveiling Prognostic RNA Biomarkers through a Multi-Cohort Study in Colorectal Cancer.", "doi": "10.3390/ijms25063317", "pmid": "38542291", "authors": ["Zehwan Kim", "Jaebon Lee", "Ye Eun Yoon", "Jae Won Yun"], "journal": "International journal of molecular sciences", "year": 2024, "abstract": "Because cancer is a leading cause of death and is thought to be caused by genetic errors or genomic instability in many circumstances, there have been studies exploring cancer's genetic basis using microarray and RNA-seq methods, linking gene expression data to patient survival. This research introduces a methodological framework, combining heterogeneous gene expression data, random forest selection, and pathway analysis, alongside clinical information and Cox regression analysis, to discover prognostic biomarkers. Heterogeneous gene expression data for colorectal cancer were collected from TCGA-COAD (RNA-seq), and GSE17536 and GSE39582 (microarray), and were integrated with Entrez Gene IDs. Using Cox regression analysis and random forest, genes with consistent hazard ratios and significantly affecting patient survivability were chosen. Predictive accuracy was evaluated using ROC curves. Pathway analysis identified potential RNA biomarkers. The authors identified 28 RNA biomarkers. Pathway analysis revealed enrichment in cancer-related pathways, notably EGFR downstream signaling and IGF1R signaling. Three RNA biomarkers (ZEB1-AS1, PI4K2A, and ITGB8-AS1) and two clinical biomarkers (stage and age) were chosen for a prognostic model, improving predictive performance compared to using clinical biomarkers alone. Despite biomarker identification challenges, this study underscores integration of heterogenous gene expression data for discovery.", "claims": [{"id": "claim-method", "statement": "Utilizing a multiple Cox regression model that accounted for factors such as age, sex, and tumor stage, 28 RNA biomarkers were identified by filtering for those with significant p-values and consistent hazard ratio direction (HR > 1 in all cohorts or HR < 1 in all cohorts) across the three cohorts (Table 2).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38542291", "locator": "sections[4] \"2.2. Cox Regression Analysis Test Result\" paragraph 2", "quote": "Utilizing a multiple Cox regression model that accounted for factors such as age, sex, and tumor stage, 28 RNA biomarkers were identified by filtering for those with significant p-values and consistent hazard ratio direction (HR > 1 in all cohorts or HR < 1 in all cohorts) across the three cohorts (Table 2)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38542291", "locator": "sections[23] \"notes\" paragraph 1", "quote": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The authors identified 28 RNA biomarkers.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38542291", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The authors identified 28 RNA biomarkers."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The authors identified 28 RNA biomarkers.", "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:38542291"], "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:GSE17536"], "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:GSE17536"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38542291", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/ijms25063317", "sha256": "sha256:9cbadf255c21b29cd379f3472cd50daac81945b3965eb7eace6dde8c288328d5", "bytes": 27023, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/ijms25063317", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10969897", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17536", "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=GSE17536", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17536", "version": null, "note": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM437093", "GSM437094", "GSM437095", "GSM437096", "GSM437097", "GSM437098", "GSM437099", "GSM437100", "GSM437101", "GSM437102", "GSM437103", "GSM437104", "GSM437105", "GSM437106", "GSM437107", "GSM437108", "GSM437109", "GSM437110", "GSM437111", "GSM437112", "GSM437113", "GSM437114", "GSM437115", "GSM437116", "GSM437117", "GSM437118", "GSM437119", "GSM437120", "GSM437121", "GSM437122", "GSM437123", "GSM437124", "GSM437125", "GSM437126", "GSM437127", "GSM437128", "GSM437129", "GSM437130", "GSM437131", "GSM437132", "GSM437133", "GSM437134", "GSM437135", "GSM437136", "GSM437137", "GSM437138", "GSM437139", "GSM437140", "GSM437141", "GSM437142", "GSM437143", "GSM437144", "GSM437145", "GSM437146", "GSM437147", "GSM437148", "GSM437149", "GSM437150", "GSM437151", "GSM437152", "GSM437153", "GSM437154", "GSM437155", "GSM437156", "GSM437157", "GSM437158", "GSM437159", "GSM437160", "GSM437161", "GSM437162", "GSM437163", "GSM437164", "GSM437165", "GSM437166", "GSM437167", "GSM437168", "GSM437169", "GSM437170", "GSM437171", "GSM437172", "GSM437173", "GSM437174", "GSM437175", "GSM437176", "GSM437177", "GSM437178", "GSM437179", "GSM437180", "GSM437181", "GSM437182", "GSM437183", "GSM437184", "GSM437185", "GSM437186", "GSM437187", "GSM437188", "GSM437189", "GSM437190", "GSM437191", "GSM437192", "GSM437193", "GSM437194", "GSM437195", "GSM437196", "GSM437197", "GSM437198", "GSM437199", "GSM437200", "GSM437201", "GSM437202", "GSM437203", "GSM437204", "GSM437205", "GSM437206", "GSM437207", "GSM437208", "GSM437209", "GSM437210", "GSM437211", "GSM437212", "GSM437213", "GSM437214", "GSM437215", "GSM437216", "GSM437217", "GSM437218", "GSM437219", "GSM437220", "GSM437221", "GSM437222", "GSM437223", "GSM437224", "GSM437225", "GSM437226", "GSM437227", "GSM437228", "GSM437229", "GSM437230", "GSM437231", "GSM437232", "GSM437233", "GSM437234", "GSM437235", "GSM437236", "GSM437237", "GSM437238", "GSM437239", "GSM437240", "GSM437241", "GSM437242", "GSM437243", "GSM437244", "GSM437245", "GSM437246", "GSM437247", "GSM437248", "GSM437249", "GSM437250", "GSM437251", "GSM437252", "GSM437253", "GSM437254", "GSM437255", "GSM437256", "GSM437257", "GSM437258", "GSM437259", "GSM437260", "GSM437261", "GSM437262", "GSM437263", "GSM437264", "GSM437265", "GSM437266", "GSM437267", "GSM437268", "GSM437269"], "sample_count": 177, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (Moffitt Samples)", "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:GSE39582", "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=GSE39582", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE39582", "version": null, "note": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1681353", "GSM1681354", "GSM1681355", "GSM1681356", "GSM1681357", "GSM1681358", "GSM1681359", "GSM1681360", "GSM1681361", "GSM1681362", "GSM1681363", "GSM1681364", "GSM1681365", "GSM1681366", "GSM1681367", "GSM1681368", "GSM1681369", "GSM1681370", "GSM1681371", "GSM971957", "GSM971958", "GSM971959", "GSM971960", "GSM971961", "GSM971962", "GSM971963", "GSM971964", "GSM971965", "GSM971966", "GSM971967", "GSM971968", "GSM971969", "GSM971970", "GSM971971", "GSM971972", "GSM971973", "GSM971974", "GSM971975", "GSM971976", "GSM971977", "GSM971978", "GSM971979", "GSM971980", "GSM971981", "GSM971982", "GSM971983", "GSM971984", "GSM971985", "GSM971986", "GSM971987", "GSM971988", "GSM971989", "GSM971990", "GSM971991", "GSM971992", "GSM971993", "GSM971994", "GSM971995", "GSM971996", "GSM971997", "GSM971998", "GSM971999", "GSM972000", "GSM972001", "GSM972002", "GSM972003", "GSM972004", "GSM972005", "GSM972006", "GSM972007", "GSM972008", "GSM972009", "GSM972010", "GSM972011", "GSM972012", "GSM972013", "GSM972014", "GSM972015", "GSM972016", "GSM972017", "GSM972018", "GSM972019", "GSM972020", "GSM972021", "GSM972022", "GSM972023", "GSM972024", "GSM972025", "GSM972026", "GSM972027", "GSM972028", "GSM972029", "GSM972030", "GSM972031", "GSM972032", "GSM972033", "GSM972034", "GSM972035", "GSM972036", "GSM972037", "GSM972038", "GSM972039", "GSM972040", "GSM972041", "GSM972042", "GSM972043", "GSM972044", "GSM972045", "GSM972046", "GSM972047", "GSM972048", "GSM972049", "GSM972050", "GSM972051", "GSM972052", "GSM972053", "GSM972054", "GSM972055", "GSM972056", "GSM972057", "GSM972058", "GSM972059", "GSM972060", "GSM972061", "GSM972062", "GSM972063", "GSM972064", "GSM972065", "GSM972066", "GSM972067", "GSM972068", "GSM972069", "GSM972070", "GSM972071", "GSM972072", "GSM972073", "GSM972074", "GSM972075", "GSM972076", "GSM972077", "GSM972078", "GSM972079", "GSM972080", "GSM972081", "GSM972082", "GSM972083", "GSM972084", "GSM972085", "GSM972086", "GSM972087", "GSM972088", "GSM972089", "GSM972090", "GSM972091", "GSM972092", "GSM972093", "GSM972094", "GSM972095", "GSM972096", "GSM972097", "GSM972098", "GSM972099", "GSM972100", "GSM972101", "GSM972102", "GSM972103", "GSM972104", "GSM972105", "GSM972106", "GSM972107", "GSM972108", "GSM972109", "GSM972110", "GSM972111", "GSM972112", "GSM972113", "GSM972114", "GSM972115", "GSM972116", "GSM972117", "GSM972118", "GSM972119", "GSM972120", "GSM972121", "GSM972122", "GSM972123", "GSM972124", "GSM972125", "GSM972126", "GSM972127", "GSM972128", "GSM972129", "GSM972130", "GSM972131", "GSM972132", "GSM972133", "GSM972134", "GSM972135", "GSM972136", "GSM972137", "GSM972138", "GSM972139", "GSM972140", "GSM972141", "GSM972142", "GSM972143", "GSM972144", "GSM972145", "GSM972146", "GSM972147", "GSM972148", "GSM972149", "GSM972150", "GSM972151", "GSM972152", "GSM972153", "GSM972154", "GSM972155", "GSM972156", "GSM972157", "GSM972158", "GSM972159", "GSM972160", "GSM972161", "GSM972162", "GSM972163", "GSM972164", "GSM972165", "GSM972166", "GSM972167", "GSM972168", "GSM972169", "GSM972170", "GSM972171", "GSM972172", "GSM972173", "GSM972174", "GSM972175", "GSM972176", "GSM972177", "GSM972178", "GSM972179", "GSM972180", "GSM972181", "GSM972182", "GSM972183", "GSM972184", "GSM972185", "GSM972186", "GSM972187", "GSM972188", "GSM972189", "GSM972190", "GSM972191", "GSM972192", "GSM972193", "GSM972194", "GSM972195", "GSM972196", "GSM972197", "GSM972198", "GSM972199", "GSM972200", "GSM972201", "GSM972202", "GSM972203", "GSM972204", "GSM972205", "GSM972206", "GSM972207", "GSM972208", "GSM972209", "GSM972210", "GSM972211", "GSM972212", "GSM972213", "GSM972214", "GSM972215", "GSM972216", "GSM972217", "GSM972218", "GSM972219", "GSM972220", "GSM972221", "GSM972222", "GSM972223", "GSM972224", "GSM972225", "GSM972226", "GSM972227", "GSM972228", "GSM972229", "GSM972230", "GSM972231", "GSM972232", "GSM972233", "GSM972234", "GSM972235", "GSM972236", "GSM972237", "GSM972238", "GSM972239", "GSM972240", "GSM972241", "GSM972242", "GSM972243", "GSM972244", "GSM972245", "GSM972246", "GSM972247", "GSM972248", "GSM972249", "GSM972250", "GSM972251", "GSM972252", "GSM972253", "GSM972254", "GSM972255", "GSM972256", "GSM972257", "GSM972258", "GSM972259", "GSM972260", "GSM972261", "GSM972262", "GSM972263", "GSM972264", "GSM972265", "GSM972266", "GSM972267", "GSM972268", "GSM972269", "GSM972270", "GSM972271", "GSM972272", "GSM972273", "GSM972274", "GSM972275", "GSM972276", "GSM972277", "GSM972278", "GSM972279", "GSM972280", "GSM972281", "GSM972282", "GSM972283", "GSM972284", "GSM972285", "GSM972286", "GSM972287", "GSM972288", "GSM972289", "GSM972290", "GSM972291", "GSM972292", "GSM972293", "GSM972294", "GSM972295", "GSM972296", "GSM972297", "GSM972298", "GSM972299", "GSM972300", "GSM972301", "GSM972302", "GSM972303", "GSM972304", "GSM972305", "GSM972306", "GSM972307", "GSM972308", "GSM972309", "GSM972310", "GSM972311", "GSM972312", "GSM972313", "GSM972314", "GSM972315", "GSM972316", "GSM972317", "GSM972318", "GSM972319", "GSM972320", "GSM972321", "GSM972322", "GSM972323", "GSM972324", "GSM972325", "GSM972326", "GSM972327", "GSM972328", "GSM972329", "GSM972330", "GSM972331", "GSM972332", "GSM972333", "GSM972334", "GSM972335", "GSM972336", "GSM972337", "GSM972338", "GSM972339", "GSM972340", "GSM972341", "GSM972342", "GSM972343", "GSM972344", "GSM972345", "GSM972346", "GSM972347", "GSM972348", "GSM972349", "GSM972350", "GSM972351", "GSM972352", "GSM972353", "GSM972354", "GSM972355", "GSM972356", "GSM972357", "GSM972358", "GSM972359", "GSM972360", "GSM972361", "GSM972362", "GSM972363", "GSM972364", "GSM972365", "GSM972366", "GSM972367", "GSM972368", "GSM972369", "GSM972370", "GSM972371", "GSM972372", "GSM972373", "GSM972374", "GSM972375", "GSM972376", "GSM972377", "GSM972378", "GSM972379", "GSM972380", "GSM972381", "GSM972382", "GSM972383", "GSM972384", "GSM972385", "GSM972386", "GSM972387", "GSM972388", "GSM972389", "GSM972390", "GSM972391", "GSM972392", "GSM972393", "GSM972394", "GSM972395", "GSM972396", "GSM972397", "GSM972398", "GSM972399", "GSM972400", "GSM972401", "GSM972402", "GSM972403", "GSM972404", "GSM972405", "GSM972406", "GSM972407", "GSM972408", "GSM972409", "GSM972410", "GSM972411", "GSM972412", "GSM972413", "GSM972414", "GSM972415", "GSM972416", "GSM972417", "GSM972418", "GSM972419", "GSM972420", "GSM972421", "GSM972422", "GSM972423", "GSM972424", "GSM972425", "GSM972426", "GSM972427", "GSM972428", "GSM972429", "GSM972430", "GSM972431", "GSM972432", "GSM972433", "GSM972434", "GSM972435", "GSM972436", "GSM972437", "GSM972438", "GSM972439", "GSM972440", "GSM972441", "GSM972442", "GSM972443", "GSM972444", "GSM972445", "GSM972446", "GSM972447", "GSM972448", "GSM972449", "GSM972450", "GSM972451", "GSM972452", "GSM972453", "GSM972454", "GSM972455", "GSM972456", "GSM972457", "GSM972458", "GSM972459", "GSM972460", "GSM972461", "GSM972462", "GSM972463", "GSM972464", "GSM972465", "GSM972466", "GSM972467", "GSM972468", "GSM972469", "GSM972470", "GSM972471", "GSM972472", "GSM972473", "GSM972474", "GSM972475", "GSM972476", "GSM972477", "GSM972478", "GSM972479", "GSM972480", "GSM972481", "GSM972482", "GSM972483", "GSM972484", "GSM972485", "GSM972486", "GSM972487", "GSM972488", "GSM972489", "GSM972490", "GSM972491", "GSM972492", "GSM972493", "GSM972494", "GSM972495", "GSM972496", "GSM972497", "GSM972498", "GSM972499", "GSM972500", "GSM972501", "GSM972502", "GSM972503", "GSM972504", "GSM972505", "GSM972506", "GSM972507", "GSM972508", "GSM972509", "GSM972510", "GSM972511", "GSM972512", "GSM972513", "GSM972514", "GSM972515", "GSM972516", "GSM972517", "GSM972518", "GSM972519", "GSM972520", "GSM972521", "GSM972522"], "sample_count": 585, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression Classification of Colon Cancer defines six molecular subtypes with distinct clinical, molecular and survival characteristics [Expression]", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE17536 not downloaded", "asset:data:geo:GSE17536 licence not read", "asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 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": "Utilizing a multiple Cox regression model that accounted for factors such as age, sex, and tumor stage, 28 RNA biomarkers were identified by filtering for those with significant p-values and consistent hazard ratio direction (HR > 1 in all cohorts or HR < 1 in all cohorts) across the three cohorts (Table 2)."}}, {"id": "method-2", "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-3", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-4", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.8, "band": "high", "quote": "logistic regression"}}, {"id": "method-5", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-6", "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": [], "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": ["GSE17536", "GSE39582"], "resolved_accessions": ["GSE17536", "GSE39582"], "statements": ["The RNA expression data and clinical data are available in the GEO under the accession number GSE17536 and GSE39582 and in the UCSC XENA website (https://xena.ucsc.edu/, accessed on 6 January 2024)."], "basis": "The paper names GSE17536, GSE39582 in NCBI 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:38542291", "data:geo:GSE17536"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE17536"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:13:36Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 8436, "completion_tokens": 2217, "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:38542291", "type": "paper", "label": "pmid:38542291"}, {"id": "source:pmid:38542291", "type": "manuscript", "label": "PMID 38542291 full text"}, {"id": "data:geo:GSE17536", "type": "dataset", "label": "GEO GSE17536"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38542291", "type": "paper", "label": "pmid:38542291"}, {"id": "source:pmid:38542291", "type": "manuscript", "label": "PMID 38542291 full text"}, {"id": "data:geo:GSE17536", "type": "dataset", "label": "GEO GSE17536"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38542291", "type": "extraction", "used": ["source:pmid:38542291"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE17536", "type": "accession_resolution", "used": ["data:geo:GSE17536"], "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:38542291", "parent_hash": "sha256:dd7e5b74d82f7763262f115f43258a682e09c244a62ab476dd3f9c9422c7443e", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE17536 licence not read", "asset:data:geo:GSE17536 not downloaded", "asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 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": ["Utilizing a multiple Cox regression model that accounted for factors such as age, sex, and tumor stage, 28 RNA biomarkers were identified by filtering for those with significant p-values and consistent hazard ratio direction (HR > 1 in all cohorts or HR < 1 in all cohorts) across the three cohorts (Table 2)."], "order_basis": "analysis_only", "id": "assay:1"}]}