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pmid:40133591
Prognostic impact of a senescence gene signature in multiple myeloma.
GeroScience · 2025 doi:10.1007/s11357-025-01622-9
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Experiment
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Data
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Complete file
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All percentages were calculated as the portion of the total number of patients (n = 1416). Not all data were available for all patients. Molecular subtypes: CD1 — cases with IgH translocations activating CCND1 or CCND3; CD2 — IgH translocations activating CCND1 or CCND3, and the expression of the early B-cell markers CD20 and PAX5; HY, hyperdiploid subgroup; LB, low bone disease subgroup; MF — increased expression of c-MAF or MAFB; MS — upregulation of FGFR3 and/or MMSET; MY, myeloid-like subgroup; PR, proliferation subgroup [32]. Abbreviations: Isotypes: FLC, Free Light Chain; IGA, Immunoglobulin A; IGG, Immunoglobulin G; Light Chain, monoclonal light chains without accompanying heavy chains", "structure": {"pmcid": "PMC12181611", "section_index": 9, "section_title": "Database setup", "row_count": 36, "column_count": 3}, "table": {"label": "Table 1", "caption": "Demographic and clinical characteristics of multiple myeloma patients in the integrated database. All percentages were calculated as the portion of the total number of patients (n = 1416). Not all data were available for all patients. Molecular subtypes: CD1 — cases with IgH translocations activating CCND1 or CCND3; CD2 — IgH translocations activating CCND1 or CCND3, and the expression of the early B-cell markers CD20 and PAX5; HY, hyperdiploid subgroup; LB, low bone disease subgroup; MF — increased expression of c-MAF or MAFB; MS — upregulation of FGFR3 and/or MMSET; MY, myeloid-like subgroup; PR, proliferation subgroup [32]. 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Need identify single numerical result headline for main finding. Likely HR = 0.6. Unit? Paper prints HR dimensionless perhaps unit \"hazard ratio (HR)\"? Required parent_value number, unit string, evidence exact contiguous quote containing number, whole clause sufficient attribution. Need headline number only in target_result perhaps \"HR = 0.6\" or \"0.6\". Registered target \"headline numerical result paper states for main finding\". Abstract explicit: \"The weighted SenMayo gene signature strongly correlated with overall survival in MM patients (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05).\" Need quote whole clause attribution. parent_value 0.6. unit likely \"hazard ratio\" or \"HR\" as printed. User says unit must be unit paper prints. HR is a metric, perhaps unit \"HR\" or \"hazard ratio\". Evidence exact contiguous quote. Could quote full sentence. target_result perhaps \"HR = 0.6\". number_stated true.\n\nQuestion asks \"Report headline number only\" but schema has target_result. Maybe target_result string \"0.6\" only, while unit \"hazard ratio\". Evidence quote full clause. Need not calculate. Let's formulate valid JSON. Exact quote including en dashes etc. \"The weighted SenMayo gene signature strongly correlated with overall survival in MM patients (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05).\" Contiguous exact. Unit paper prints? It prints HR, not \"hazard ratio\" in result, though elsewhere \"univariate hazard ratios\". 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the source evidence must resolve the difference.", "evidence": {"provider_errors": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "reason": "a quoted statement is absent from the supplied text", "raw_response": "{\n \"target_result\": \"The weighted SenMayo gene signature was associated with overall survival in multiple myeloma patients (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05), with the 75th percentile of survival reached at 36.1 months in the low-expression group and 57 months in the high-expression group.\",\n \"work_type\": \"analysis_only_for_target\",\n \"physical_methods\": [],\n \"analysis_methods\": [\n \"Univariate Cox regression\",\n \"Kaplan–Meier survival analysis\",\n \"Multivariate Cox regression\",\n \"Benjamini–Hochberg false discovery rate correction\"\n ],\n \"statistical_method\": \"Univariate Cox regression\",\n \"method_evidence\": \"Univariate Cox regression analysis was conducted to assess the prognostic significance of the SenMayo gene signature on overall survival (OS).\",\n \"repositories\": [\n {\n \"repository\": \"Gene Expression Omnibus (GEO)\",\n \"accession\": \"GSE24080\",\n \"data_description\": \"Gene expression and clinical data from 1416 multiple myeloma patients obtained from four GEO datasets and integrated into a unified database.\",\n \"evidence\": \"Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database.\",\n \"publicly_downloadable\": false\n },\n {\n \"repository\": \"Gene Expression Omnibus (GEO)\",\n \"accession\": \"GSE4204\",\n \"data_description\": \"Gene expression and clinical data from 1416 multiple myeloma patients obtained from four GEO datasets and integrated into a unified database.\",\n \"evidence\": \"Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database.\",\n \"publicly_downloadable\": false\n },\n {\n \"repository\": \"Gene Expression Omnibus (GEO)\",\n \"accession\": \"GSE57317\",\n \"data_description\": \"Gene expression and clinical data from 1416 multiple myeloma patients obtained from four GEO datasets and integrated into a unified database.\",\n \"evidence\": \"Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database.\",\n \"publicly_downloadable\": false\n },\n {\n \"repository\": \"Gene Expression Omnibus (GEO)\",\n \"accession\": \"GSE9782\",\n \"data_description\": \"Gene expression and clinical data from 1416 multiple myeloma patients obtained from four GEO datasets and integrated into a unified database.\",\n \"evidence\": \"Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database.\",\n \"publicly_downloadable\": false\n }\n ],\n \"availability_statement\": \"The paper states that the gene expression and clinical data were obtained from four GEO datasets, but it does not explicitly state that these data can be downloaded without an application, embargo, or request and does not state that they are available on request.\",\n \"data_on_request\": false,\n \"source_claims\": [\n \"The weighted SenMayo gene signature was associated with overall survival in MM patients (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05).\",\n \"The 75th percentile probability of survival was 36.1 months in the low-expression group and 57 months in the high-expression group.\",\n \"Independent validation was reported for GSE4204, GSE24080, and GSE57317.\",\n \"The senescence signature retained prognostic value in multivariate analyses paired with isotype and sex.\",\n \"Neither molecular subtype nor the senescence signature achieved statistical significance in the multivariate model pairing them.\"\n ],\n \"missing_information\": [\n \"The source does not explicitly describe the download or access conditions for the four GEO datasets.\",\n \"The source does not state that the underlying data are available on request.\",\n \"The source does not provide a separate repository or accession for the integrated unified database.\"\n ],\n \"evidence_spans\": [\n \"The weighted SenMayo gene signature strongly correlated with overall survival in MM patients (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05).\",\n \"The 75th percent probability of survival was reached at 36.1 months in the low-expression patient group, compared to 57 months in the high-expression group.\",\n \"Independent validation in datasets with sufficient patient numbers confirmed the prognostic value of the SenMayo signature (GSE4204: HR = 0.58, 95% CI = 0.39–0.88, p = 0.0089; GSE24080: HR = 0.61, 95% CI = 0.45–0.83, p = 0.0012; GSE57317: HR = 0.25, 95% CI = 0.08–0.77, p = 0.0095).\",\n \"Gene expression and clinical data from 1416 MM patients were obtained from four GEO datasets (GSE24080, GSE4204, GSE57317, and GSE9782) and integrated into a unified database.\",\n \"The raw data were processed using MAS5 normalization, scaling adjustments, and JetSet probe selection to ensure cross-platform comparability.\",\n \"The final gene signature was computed as a weighted mean expression of 122 senescence-associated genes, with weights derived from univariate hazard ratios.\",\n \"Univariate Cox regression analysis was conducted to assess the prognostic significance of the SenMayo gene signature on overall survival (OS).\",\n \"The Kaplan–Meier plotter was utilized to analyze the association between gene expression and survival [28, 29].\",\n \"Then, false discovery rate (FDR) was controlled using the Benjamini–Hochberg method to account for multiple hypothesis testing [30, 31].\",\n \"A multivariate Cox regression analysis was conducted to evaluate the combined effect of the senescence signature and key clinical parameters, including gender, isotypes, and molecular subgroups.\",\n \"We identified a strong association with overall survival (HR = 0.6, 95% CI = 0.47–0.76, p = 1.7e-05; depicted in Fig. 1A), with a false discovery rate under 1%.\",\n \"In the low-expression patient group, the 75th percent probability of survival was 36.1 months. In contrast, it was 57 months in the high-expression group, demonstrating a significantly prolonged survival.\",\n \"The senescence signature demonstrated significant prognostic value when paired with isotype (p = 5.3e-13), which was also independently significant (p for isotype = 2.1e-04).\",\n \"Of note, neither the molecular subtype nor the senescence signature achieves statistical significance when paired in a multivariate analysis.\"\n ]\n}"}]}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:f4b83b8aa95c77cbd4e3ed0811b8dc1489b87036726aabe79b8cb0e276da195b", "type": "sep_package", "label": "SEP v1 package for pmid:40133591"}], "activities": [{"id": "activity:conversion:pmid:40133591", "type": "conversion", "used": ["package:f4b83b8aa95c77cbd4e3ed0811b8dc1489b87036726aabe79b8cb0e276da195b"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:40133591", "parent_hash": "sha256:a0b4ed452fb686c4241efe1518600401f59a35e8b9c00c6d5a8a3c9f596a2bc9", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:40133591 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40133591' does not resolve to a declared asset", "targets"]}