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pmid:37367950
Identification and validation of a 7-genes prognostic signature for adult acute myeloid leukemia based on aging-related genes.
Peng Ke · Qian Zhu · Ting Xu · Xiaofei Yang · Ying Wang · Huiying Qiu · Depei Wu · Xiebing Bao · Suning Chen
Aging · 2023 doi:10.18632/aging.204843
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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The numbers of seven-ARG sequences were selected to construct the survival prognostic signature in TCGA-LAML cohort, and two GEO datasets were used independently to verify the prognostic values of signature. According to seven-ARGs signature, patients were categorized into two subgroups. Patients with high-risk prognostic score were defined as HRPS-group/high-risk group, while others were set as LRPS-group/low-risk group. HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001). In validation, the results emphasized a satisfactory discrimination in different time points, and confirmed the poor OS of HRPS-group both in GSE37642 (HR=1.96, P=0.001) and GSE106291 (HR=1.88, P<0.001). Many signal pathways, including immune- and tumor-related processes, especially NF-κB signaling, were highly enriched in HRPS-group. Coupled with high immune-inflamed infiltration, the HRPS-group was highly associated with the driver gene and oncogenic signaling pathway of TP53. Prediction of blockade therapy targeting immune checkpoint indicated varied benefits base on the different ARGs signature score, and the results of predicted drug response suggested that Pevonedistat, an inhibitor of NEDD8-activating enzyme, targeting NF-κB signaling, may have potential therapeutic value for HRPS-group. Compared with clinical factors alone, the signature had an independent value and more predictive power of AML prognosis. The 7-ARGs signature may help to guide clinical-decision making to predict drug response, and survival in AML patients.", "claims": [{"id": "claim-method", "statement": "Via random survival forest algorithm (Figure 1A, 1B), we identified a 7-ARGs signature with a lowest OOB error rate for predicting AML survival (Figure 1C), Subsequently, seven ARGs with a relative importance greater than 0.52 were transferred to establish a prognostic signature for AML (Figure 1D).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37367950", "locator": "sections[3] \"Construction of ARGs-related prognostic signature\" paragraph 4", "quote": "Via random survival forest algorithm (Figure 1A, 1B), we identified a 7-ARGs signature with a lowest OOB error rate for predicting AML survival (Figure 1C), Subsequently, seven ARGs with a relative importance greater than 0.52 were transferred to establish a prognostic signature for AML (Figure 1D)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "TCGA-LAML cohort was downloaded as the training set for constructing prognostic signature base on ARGs, including publicly available gene expression and clinical data.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37367950", "locator": "sections[14] \"Source of data\" paragraph 2", "quote": "TCGA-LAML cohort was downloaded as the training set for constructing prognostic signature base on ARGs, including publicly available gene expression and clinical data."}], "state": "complete"}, {"id": "claim-target-result", "statement": "HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001).", "kind": "quantitative", "target": {"value": 3.39, "unit": "hazard ratio", "tolerance": null, "source": "HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001)."}, "evidence": [{"asset": "source:pmid:37367950", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "HRPS-group presented adverse overall survival (OS) than LRPS-group in TCGA-AML cohort (HR=3.39, P<0.001).", "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:37367950"], "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. 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"GSM361381", "GSM361382", "GSM361383", "GSM361384", "GSM361385"], "sample_count": 526, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression profiling of CEBPA double and single mutant and CEBPA wild type AML.", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE37642", "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=GSE37642", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE37642", "version": null, "note": "TCGA-LAML cohort was downloaded as the training set for constructing prognostic signature base on ARGs, including publicly available gene expression and clinical data.", "structure": 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No tolerance is published because the paper states none."}, {"id": "target-published-estimate-p-value", "claim_id": "claim-target-result", "operation": "pearson_r", "expected_value": 0.001, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. 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