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pmid:38254953
A Comprehensive Metabolism-Related Gene Signature Predicts the Survival of Patients with Acute Myeloid Leukemia.
Yujia Zhai · Heng Shen · Hui Wei
Genes · 2023 doi:10.3390/genes15010063
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Experiment
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Analysis
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Complete file
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A comprehensive prognostic model based on metabolism signatures has not yet been developed. (2) Methods: We applied Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) normalization to establish a metabolism-related prognostic gene signature based on glycolysis, fatty acid metabolism, and the tricarboxylic acid cycle gene signatures. The Cancer Genome Atlas-Acute Myeloid Leukemia-like (TCGA-LAML) cohort was set as the training dataset for model construction. Three independent AML cohorts (GSE37642, GSE10358, and GSE12417) combined from Gene Expression Omnibus (GEO) datasets and the Beat-AML dataset were retrieved as two validation sets to test the robustness of the model. The transcriptome data and clinic information of the cohorts were enrolled for the analysis. (3) Results: Divided by the median value of the metabolism risk score, the five-year overall survival (OS) of the high-risk and low-risk groups in the training set were 8.2% and 41.3% (p < 0.001), respectively. The five-year OS of the high-risk and low-risk groups in the combined GEO cohort were 25.5% and 37.3% (p = 0.002), respectively. In the Beat-AML cohort, the three-year OS of the high-risk and low-risk groups were 16.2% and 40.2% (p = 0.0035), respectively. The metabolism risk score showed a significantly negative association with the long-term survival of AML. Furthermore, this metabolism risk score was an independent unfavorable factor for OS by univariate analysis and multivariate analysis. (4) Conclusions: Our study constructed a comprehensive metabolism-related signature with twelve metabolism-related genes for the risk stratification and outcome prediction of AML. This novel signature might contribute to a better use of metabolism reprogramming factors as prognostic markers and provide novel insights into potential metabolism targets for AML treatment.", "claims": [{"id": "claim-data-access", "statement": "The data presented in this study are openly available in the TCGA-LAML database at https://gdc.cancer.gov/about-data/publications/laml_2012 [10], GSE37642 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642 [11], GSE10358 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358 [12], GSE12417 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417 [13], and the Beat-AML database at https://www.cancer.gov/ccg/blog/2019/beataml [14].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38254953", "locator": "sections[20] \"Data Availability Statement\" paragraph 2", "quote": "The data presented in this study are openly available in the TCGA-LAML database at https://gdc.cancer.gov/about-data/publications/laml_2012 [10], GSE37642 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642 [11], GSE10358 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358 [12], GSE12417 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417 [13], and the Beat-AML database at https://www.cancer.gov/ccg/blog/2019/beataml [14]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study established a 12-gene metabolism-related prognostic signature for AML using Cox regression analysis and LASSO, with the TCGA-LAML cohort used for model construction and the combined GEO and Beat-AML cohorts used for validation.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38254953", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We applied Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) normalization to establish a metabolism-related prognostic gene signature based on glycolysis, fatty acid metabolism, and the tricarboxylic acid cycle gene signatures."}, {"asset": "source:pmid:38254953", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The Cancer Genome Atlas-Acute Myeloid Leukemia-like (TCGA-LAML) cohort was set as the training dataset for model construction."}, {"asset": "source:pmid:38254953", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Three independent AML cohorts (GSE37642, GSE10358, and GSE12417) combined from Gene Expression Omnibus (GEO) datasets and the Beat-AML dataset were retrieved as two validation sets to test the robustness of the model."}, {"asset": "source:pmid:38254953", "locator": "sections[12] \"3.3. Establishment of Metabolism-Related Gene Prognostic Signature from Metabolism-Related Genes Associated with OS in the TCGA-LAML Dataset\" paragraph 3", "quote": "Ultimately, we determined the best lambda value (0.0625) and used the β coefficients of 12 genes (SESN2, ABCB11, SORT1, SLC27A4, INSR, PC, SDHB, ALDH2, ENO1, SDHA, NUP210, and HK2) selected by the LASSO model."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study established a 12-gene metabolism-related prognostic signature for AML using Cox regression analysis and LASSO, with the TCGA-LAML cohort used for model construction and the combined GEO and Beat-AML cohorts used for validation.", "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:38254953"], "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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"GSM311828", "GSM311829", "GSM311830", "GSM311831", "GSM311832", "GSM311833", "GSM311834", "GSM311835", "GSM311836", "GSM311837", "GSM311838", "GSM311839", "GSM311840", "GSM311841", "GSM311842", "GSM311843", "GSM311844", "GSM311845", "GSM311846", "GSM311847", "GSM311848", "GSM311849", "GSM311850", "GSM311851", "GSM311852", "GSM311853", "GSM311854", "GSM311855", "GSM311856", "GSM311857", "GSM311858", "GSM311859", "GSM311860", "GSM311861", "GSM311862", "GSM311863", "GSM311864", "GSM311865", "GSM311866", "GSM311867", "GSM311868", "GSM311869", "GSM311870", "GSM311871", "GSM311872", "GSM311873", "GSM311874", "GSM311875", "GSM311876", "GSM311877", "GSM311878", "GSM311879", "GSM311880", "GSM311881", "GSM311882", "GSM311883", "GSM311884", "GSM311885", "GSM311886", "GSM311887", "GSM311888", "GSM311889", "GSM311890", "GSM311891", "GSM311892", "GSM311893", "GSM311894", "GSM311895", "GSM311896", "GSM311897", "GSM311898", "GSM311899", "GSM311900", "GSM311901", "GSM311902", "GSM311903", "GSM311904", "GSM311905", "GSM311906", "GSM311907", "GSM311908", "GSM311909", "GSM311910", "GSM311911", "GSM311912", "GSM311913", "GSM311914", "GSM311915", "GSM311916", "GSM311917", "GSM311918", "GSM311919", "GSM311920", "GSM311921", "GSM311922", "GSM311923", "GSM316652", "GSM316653", "GSM316654", "GSM316655", "GSM316656", "GSM316657", "GSM316658", "GSM316659", "GSM316660", "GSM316661", "GSM316662", "GSM316663", "GSM316664", "GSM316665", "GSM316666", "GSM316667", "GSM316668", "GSM316669", "GSM316670", "GSM316671", "GSM316672", "GSM316673", "GSM316674", "GSM316675", "GSM316676", "GSM316677", "GSM316678", "GSM316679", "GSM316680", "GSM316681", "GSM316682", "GSM316683", "GSM316684", "GSM316685", "GSM316686", "GSM316687", "GSM316688", "GSM316689", "GSM316690", "GSM316691", "GSM316692", "GSM316693", "GSM316694", "GSM316695", "GSM316696", "GSM316697", "GSM316698", "GSM316699", "GSM316700", "GSM316701", "GSM316702", "GSM316703", "GSM316704", "GSM316705", "GSM316706", "GSM316707", "GSM316708", "GSM316709", "GSM316710", "GSM316711", "GSM316712", "GSM316713", "GSM316714", "GSM316715", "GSM316716", "GSM316717", "GSM316718", "GSM316719", "GSM316720", "GSM316721", "GSM316722", "GSM316723", "GSM316724", "GSM316725", "GSM316726", "GSM316727", "GSM316728", "GSM316729", "GSM316730"], "sample_count": 405, "group_sizes": null, "group_sizes_basis": null, "platform": "570;96;97", "taxon": "Homo sapiens", "title": "Prognostic gene signature for normal karyotype AML", "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: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": "The data presented in this study are openly available in the TCGA-LAML database at https://gdc.cancer.gov/about-data/publications/laml_2012 [10], GSE37642 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642 [11], GSE10358 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358 [12], GSE12417 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417 [13], and the Beat-AML database at https://www.cancer.gov/ccg/blog/2019/beataml [14].", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data presented in this study are openly available in the TCGA-LAML database at https://gdc.cancer.gov/about-data/publications/laml_2012 [10], GSE37642 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642 [11], GSE10358 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358 [12], GSE12417 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417 [13], and the Beat-AML database at https://www.cancer.gov/ccg/blog/2019/beataml [14].", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM923596", "GSM923597", "GSM923598", "GSM923599", "GSM923600", "GSM923601", "GSM923602", "GSM923603", "GSM923604", "GSM923605", "GSM923606", "GSM923607", "GSM923608", "GSM923609", "GSM923610", "GSM923611", "GSM923612", "GSM923613", "GSM923614", "GSM923615", "GSM923616", "GSM923617", "GSM923618", "GSM923619", "GSM923620", "GSM923621", "GSM923622", "GSM923623", "GSM923624", "GSM923625", "GSM923626", "GSM923627", "GSM923628", "GSM923629", "GSM923630", "GSM923631", "GSM923632", "GSM923633", "GSM923634", "GSM923635", "GSM923636", "GSM923637", "GSM923638", "GSM923639", "GSM923640", "GSM923641", "GSM923642", "GSM923643", "GSM923644", "GSM923645", "GSM923646", "GSM923647", "GSM923648", "GSM923649", "GSM923650", "GSM923651", "GSM923652", "GSM923653", "GSM923654", "GSM923655", "GSM923656", "GSM923657", "GSM923658", "GSM923659", "GSM923660", 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null, "platform": "570;96;97", "taxon": "Homo sapiens", "title": "Prognostic gene signature for AML", "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:GSE10358 not downloaded", "asset:data:geo:GSE10358 licence not read", "asset:data:geo:GSE12417 not downloaded", "asset:data:geo:GSE12417 licence not read", "asset:data:geo:GSE37642 not downloaded", "asset:data:geo:GSE37642 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": 0.7, "band": "medium", "quote": "Cox regression"}}, {"id": "method-2", "family": "sequence_alignment", "specific": "blast", "label": "Sequence alignment / homology", "dsl_operations": ["sequence_align", "alignment_identity"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["sequence_records"], "evidence": {"score": 0.8, "band": "high", "quote": "blast"}}], "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": ["GSE37642", "GSE10358", "GSE12417"], "resolved_accessions": ["GSE37642", "GSE10358", "GSE12417"], "statements": ["The data presented in this study are openly available in the TCGA-LAML database at https://gdc.cancer.gov/about-data/publications/laml_2012 [10], GSE37642 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE37642 [11], GSE10358 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358 [12], GSE12417 database at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417 [13], and the Beat-AML database at https://www.cancer.gov/ccg/blog/2019/beataml [14]."], "basis": "The paper names GSE37642, GSE10358, GSE12417 in Gene Expression Omnibus (GEO) dataset GSE37642 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:38254953", "data:geo:GSE10358"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE10358"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:06:00Z", "independence": "single_reader"}, "evidence_check": {"method": null, "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15181, "completion_tokens": 2800, "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:38254953", "type": "paper", "label": "pmid:38254953"}, {"id": "source:pmid:38254953", "type": "manuscript", "label": "PMID 38254953 full text"}, {"id": "data:geo:GSE10358", "type": "dataset", "label": "GEO GSE10358"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38254953", "type": "paper", "label": "pmid:38254953"}, {"id": "source:pmid:38254953", "type": "manuscript", "label": "PMID 38254953 full text"}, {"id": "data:geo:GSE10358", "type": "dataset", "label": "GEO GSE10358"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38254953", "type": "extraction", "used": ["source:pmid:38254953"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE10358", "type": "accession_resolution", "used": ["data:geo:GSE10358"], "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:38254953", "parent_hash": "sha256:b68f3d019f7aad4c61aa1680c7a9e8a5bd63cb6f209b86f451eec68c6da29fa5", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE10358 licence not read", "asset:data:geo:GSE10358 not downloaded", "asset:data:geo:GSE12417 licence not read", "asset:data:geo:GSE12417 not downloaded", "asset:data:geo:GSE37642 licence not read", "asset:data:geo:GSE37642 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ets to test the robustness of the model. The transcriptome data and clinic information of the cohorts w", "Data Sources and Patient Characteristics The RNA-seq data of bone marrow (BM) samples and clinica", "ober 2022). After excluding patients without RNA-seq data or without survival information and rem"], "order_basis": "paper_text_order:1038", "id": "assay:1"}, {"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": 0.7, "evidence": ["Cox regression"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}