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pmid:38961904
Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia.
Yiyun Pan · Wen Zeng · Xiaoming Nie · Hailong Chen · Chuanhua Xie · Shouju Guo · Dechang Xu · Yijian Chen
Heliyon · 2024 doi:10.1016/j.heliyon.2024.e32154
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
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38961904", "kind": "science-record", "revision": 2, "content_hash": "sha256:2083295a2f7076a961fdbfbcd6fb65682b4fff4bc6cba3cb52e695256af2fbae", "created_at": "2026-11-01T20:29:02Z", "updated_at": "2026-11-01T21:33:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia.", "doi": "10.1016/j.heliyon.2024.e32154", "pmid": "38961904", "authors": ["Yiyun Pan", "Wen Zeng", "Xiaoming Nie", "Hailong Chen", "Chuanhua Xie", "Shouju Guo", "Dechang Xu", "Yijian Chen"], "journal": "Heliyon", "year": 2024, "abstract": "Background: Acute Myeloid Leukemia (AML) exhibits a wide array of phenotypic manifestations, progression patterns, and heterogeneous responses to immunotherapies, suggesting involvement of complex immunobiological mechanisms. This investigation aimed to develop an integrated prognostic model for AML by incorporating cancer driver genes, along with clinical and phenotypic characteristics of the disease, and to assess its implications for immunotherapy responsiveness.\nMethods: Critical oncogenic driver genes linked to survival were identified by screening primary effector and corresponding gene pairs using data from The Cancer Genome Atlas (TCGA), through univariate Cox proportional hazard regression analysis. This was independently verified using dataset GSE37642. Primary effector genes were further refined using LASSO regression. Transcriptomic profiling was quantified using multivariate Cox regression, and the derived prognostic score was subsequently validated. Finally, a multivariate Cox regression model was developed, incorporating the transcriptomic score along with clinical parameters such as age, gender, and French-American-British (FAB) classification subtype. The 'Accurate Prediction Model of AML Overall Survival Score' (APMAO) was developed and subsequently validated. Investigations were conducted into functional pathway enrichment, alterations in the gene mutational landscape, and the extent of immune cell infiltration associated with varying APMAO scores. To further investigate the potential of APMAO scores as a predictive biomarker for responsiveness to cancer immunotherapy, we conducted a series of analyses. These included examining the expression profiles of genes related to immune checkpoints, the interferon-gamma signaling pathway, and m6A regulation. Additionally, we explored the relationship between these gene expression patterns and the Tumor Immune Dysfunction and Exclusion (TIDE) dysfunction scores.\nResults: Through the screening of 95 cancer genes associated with survival and 313 interacting gene pairs, seven genes (ACSL6, MAP3K1, CHIC2, HIP1, PTPN6, TFEB, and DAXX) were identified, leading to the derivation of a transcriptional score. Age and the transcriptional score were significant predictors in Cox regression analysis and were integral to the development of the final APMAO model, which exhibited an AUC greater than 0.75 and was successfully validated. Notable differences were observed in the distribution of the transcriptional score, age, cytogenetic risk categories, and French-American-British (FAB) classification between high and low APMAO groups. Samples with high APMAO scores demonstrated significantly higher mutation rates and pathway enrichments in NFKB, TNF, JAK-STAT, and NOTCH signaling. Additionally, variations in immune cell infiltration and immune checkpoint expression, activation of the interferon-γ pathway, and expression of m6A regulators were noted, including a negative correlation between CD160, m6A expression, and APMAO scores.\nConclusion: The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes. It was linked to unique phenotypic characteristics, distinctive immune and mutational profiles, and patterns of expression for markers related to immunotherapy sensitivity. These observations suggest the potential for facilitating precision immunotherapy and advocate for its exploration in upcoming clinical trials.", "claims": [{"id": "claim-method", "statement": "To identify potential cancer driver genes associated with overall survival (OS), we performed univariate Cox proportional hazard regression analysis using the R packages survivor (version 3.2–7) and survminer (version 0.4.8).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38961904", "locator": "sections[4] \"Identification of cancer driver genes\" paragraph 2", "quote": "To identify potential cancer driver genes associated with overall survival (OS), we performed univariate Cox proportional hazard regression analysis using the R packages survivor (version 3.2–7) and survminer (version 0.4.8)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). All the data generated or analyzed during the course of this study have been included in this published article and its accompanying supplementary information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38961904", "locator": "sections[15] \"Availability of data and materials\" paragraph 2", "quote": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). All the data generated or analyzed during the course of this study have been included in this published article and its accompanying supplementary information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38961904", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The combined APMAO score integrating transcriptional and clinical parameters demonstrated robust prognostic performance in predicting AML survival outcomes.", "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:38961904"], "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:GSE10358"], "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:GSE10358"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38961904", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e32154", "sha256": "sha256:fad73c96bc3ac43e1e733992312dacf34e68fad692216c49d4c90963057c5627", "bytes": 89317, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.heliyon.2024.e32154", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11219318", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10358", "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=GSE10358", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10358", "version": null, "note": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). 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Leukemia", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE12417", "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=GSE12417", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE12417", "version": null, "note": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). 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"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE146173", "version": null, "note": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). 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"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": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). All the data generated or analyzed during the course of this study have been included in this published article and its accompanying supplementary information files.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). All the data generated or analyzed during the course of this study have been included in this published article and its accompanying supplementary information files.", "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", 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"GSM924578", "GSM924579"], "sample_count": 984, "group_sizes": null, "group_sizes_basis": 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:GSE106291 not downloaded", "asset:data:geo:GSE106291 licence not read", "asset:data:geo:GSE12417 not downloaded", "asset:data:geo:GSE12417 licence not read", "asset:data:geo:GSE146173 not downloaded", "asset:data:geo:GSE146173 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": 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE37642", "GSE12417", "GSE10358", "GSE146173", "GSE106291"], "resolved_accessions": ["GSE37642", "GSE12417", "GSE10358", "GSE146173", "GSE106291"], "statements": ["GSE37642 (weblink [39]), GSE12417 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12417), GSE10358 (weblink: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE10358), GSE146173 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE146173), and GSE106291 (URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE106291) dataset were obtained from the Gene Expression Omnibus (GEO) database (URL: https://www.ncbi.nlm.nih.gov/geo/), while the TCGA-LAML data was acquired from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/). 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