m6A genotypes and prognostic signature for assessing the prognosis of patients with acute myeloid leukemia.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37596597", "kind": "science-record", "revision": 3, "content_hash": "sha256:e09bbe124e0c6c24e95600824a1fbf489ab6b440fbc22e9576764c1a7b11459d", "created_at": "2026-11-01T19:02:24Z", "updated_at": "2026-11-01T22:10:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "m6A genotypes and prognostic signature for assessing the prognosis of patients with acute myeloid leukemia.", "doi": "10.1186/s12920-023-01629-1", "pmid": "37596597", "authors": ["Caizhu Fu", "Ruirui Kou", "Jie Meng", "Duanfeng Jiang", "Ruilan Zhong", "Min Dong"], "journal": "BMC medical genomics", "year": 2023, "abstract": "BACKGROUND: N6-methyladenosine (m6A) has been confirmed to function critically in acute myeloid leukemia (AML) progression. Hitherto, the subtyping and prognostic predictive significance of m6A-correlated genes in AML is unclear.\nMETHOD: From The Cancer Genome Atlas (TCGA-LAML), Therapeutically Applicable Research to Generate Effective Treatments (TARGET-AML) and Gene Expression Omnibus (GEO, GSE71014) databases, we collected the sequencing data of AML patients. The batch effect was removed via limma package for TCGA-LAML and TARGET-AML, and the aggregated samples were AML cohorts. Samples in the AML cohort identified m6A models in AML by consensus clustering based on 23-m6A-related modulators. M6A-related differentially expressed genes (m6ARDEGs) influencing the overall survival (OS) of AML were determined by performing differential expression analysis and univariate COX analysis, and consensus-based clustering was utilized to access AML molecular subtypes. LASSO and multivariate COX analyses were performed to obtain the optimized m6ARDEGs to construct the m6A Prognostic Risk Score (m6APR_Score). Whether the model was robust was evaluated according to Kaplan-Meier (K-M) and receiver operator characteristic (ROC) curves. Further, the abundance of immune cell infiltration was explored in different m6A modification patterns and molecular subtypes and m6APR_Score groupings. Finally, nomogram was constructed to predict OS in AML. Quantitative real-time polymerase chain reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were used to validate the genes in m6APR_Score in AML cells.\nRESULTS: The m6A models (m6AM1, m6AM2, m6AM3) and molecular subtypes (C1, C2, C3) were identified in the AML cohort, exhibiting different prognosis and immunoreactivity. We recognized novel prognostic biomarkers of AML such as CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48. AML patients were grouped into high-m6APR_Score and low-m6APR_Score groups, with the later group showing a better prognosis than former one. Both the AML cohort and the validation cohort GSE71014 demonstrated excellent prediction. Finally, the nomogram accurately predicted the survival of patients suffering from AML. Further, the decision curves showed that both nomogram and m6APR_Score showed excellent prediction. It was confirmed in vitro experiments that mRNA expressions of NRIP1, ACSL1, METTL7B and OGT were elevated, while CD83 and C4orf48 mRNA expressions downregulated in AML cells. A significant increase in the viability of U937 and THP-1 cell lines after inhibition of CD83, while siMETTL7B had contrast results.\nCONCLUSION: Our study demonstrated that m6APR_Score and CD83, NRIP1, ACSL1, METTL7B, OGT, and C4orf48 potentially provided novel and promising prognostic support for AML patients.", "claims": [{"id": "claim-method", "statement": "LASSO and multivariate COX regression analyses were conducted on m6ARDEGs capable of influencing AML prognosis to construct an AML prognostic model [19], and the AML prognostic risk score (m6APR_Score) was calculated by the following equation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37596597", "locator": "sections[6] \"Prognostic assessment model construction and validation\" paragraph 2", "quote": "LASSO and multivariate COX regression analyses were conducted on m6ARDEGs capable of influencing AML prognosis to construct an AML prognostic model [19], and the AML prognostic risk score (m6APR_Score) was calculated by the following equation."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37596597", "locator": "sections[31] \"Availability of data and materials\" paragraph 2", "quote": "The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our study constructed a 6-gene prognostic predictive model for predicting prognosis in AML, which constructed an m6A signature that could also serve as an independent prognostic factor for AML compared to traditional clinicopathological prognostic factors.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37596597", "locator": "sections[24] \"Conclusion\" paragraph 2", "quote": "Our study constructed a 6-gene prognostic predictive model for predicting prognosis in AML, which constructed an m6A signature that could also serve as an independent prognostic factor for AML compared to traditional clinicopathological prognostic factors."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our study constructed a 6-gene prognostic predictive model for predicting prognosis in AML, which constructed an m6A signature that could also serve as an independent prognostic factor for AML compared to traditional clinicopathological prognostic factors.", "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:37596597"], "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:GSE71014"], "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:GSE71014"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37596597", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-023-01629-1", "sha256": "sha256:31bf3d4e8af6025e70f226fb261e0162379b58837b4522d911836ef4cdde3dea", "bytes": 41756, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-023-01629-1", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10436408", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE71014", "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=GSE71014", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE71014", "version": null, "note": "The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1825455", "GSM1825456", "GSM1825457", "GSM1825458", "GSM1825459", "GSM1825460", "GSM1825461", "GSM1825462", "GSM1825463", "GSM1825464", "GSM1825465", "GSM1825466", "GSM1825467", "GSM1825468", "GSM1825469", "GSM1825470", "GSM1825471", "GSM1825472", "GSM1825473", "GSM1825474", "GSM1825475", "GSM1825476", "GSM1825477", "GSM1825478", "GSM1825479", "GSM1825480", "GSM1825481", "GSM1825482", "GSM1825483", "GSM1825484", "GSM1825485", "GSM1825486", "GSM1825487", "GSM1825488", "GSM1825489", "GSM1825490", "GSM1825491", "GSM1825492", "GSM1825493", "GSM1825494", "GSM1825495", "GSM1825496", "GSM1825497", "GSM1825498", "GSM1825499", "GSM1825500", "GSM1825501", "GSM1825502", "GSM1825503", "GSM1825504", "GSM1825505", "GSM1825506", "GSM1825507", "GSM1825508", "GSM1825509", "GSM1825510", "GSM1825511", "GSM1825512", "GSM1825513", "GSM1825514", "GSM1825515", "GSM1825516", "GSM1825517", "GSM1825518", "GSM1825519", "GSM1825520", "GSM1825521", "GSM1825522", "GSM1825523", "GSM1825524", "GSM1825525", "GSM1825526", "GSM1825527", "GSM1825528", "GSM1825529", "GSM1825530", "GSM1825531", "GSM1825532", "GSM1825533", "GSM1825534", "GSM1825535", "GSM1825536", "GSM1825537", "GSM1825538", "GSM1825539", "GSM1825540", "GSM1825541", "GSM1825542", "GSM1825543", "GSM1825544", "GSM1825545", "GSM1825546", "GSM1825547", "GSM1825548", "GSM1825549", "GSM1825550", "GSM1825551", "GSM1825552", "GSM1825553", "GSM1825554", "GSM1825555", "GSM1825556", "GSM1825557", "GSM1825558"], "sample_count": 104, "group_sizes": null, "group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "An mRNA Expression Signature for Prognostication in De Novo Acute Myeloid Leukemia Patients with Normal Karyotype", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE71014 not downloaded", "asset:data:geo:GSE71014 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": "LASSO and multivariate COX regression analyses were conducted on m6ARDEGs capable of influencing AML prognosis to construct an AML prognostic model [19], and the AML prognostic risk score (m6APR_Score) was calculated by the following equation."}}, {"id": "method-2", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.7, "band": "medium", "quote": "Kaplan-Meier"}}, {"id": "method-3", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 0.7, "band": "medium", "quote": "limma"}}], "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": ["GSE71014"], "resolved_accessions": ["GSE71014"], "statements": ["The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request."], "basis": "The paper names GSE71014 in Gene Expression Omnibus (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:37596597", "data:geo:GSE71014"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE71014"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:51:05Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 13437, "completion_tokens": 1405, "cached_tokens": 264}}, "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:37596597", "type": "paper", "label": "pmid:37596597"}, {"id": "source:pmid:37596597", "type": "manuscript", "label": "PMID 37596597 full text"}, {"id": "data:geo:GSE71014", "type": "dataset", "label": "GEO GSE71014"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:37596597", "type": "paper", "label": "pmid:37596597"}, {"id": "source:pmid:37596597", "type": "manuscript", "label": "PMID 37596597 full text"}, {"id": "data:geo:GSE71014", "type": "dataset", "label": "GEO GSE71014"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-37596597", "type": "extraction", "used": ["source:pmid:37596597"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE71014", "type": "accession_resolution", "used": ["data:geo:GSE71014"], "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:37596597", "parent_hash": "sha256:9cad7838fc64617a17145e8ea7513aaca1e8d02b11b6e43c63ef5644e9dcbe57", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE71014 licence not read", "asset:data:geo:GSE71014 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["itative real-time polymerase chain reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were", "tive real-time polymerase chain reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were", "CD83, NRIP1, ACSL1, METTL7B, OGT, C4orf48 by RT-qPCR in GM12878, THP1 and U937 cell lines. The ex", "n of m6APR_Score model genes. A-F Results of RT-qPCR assays for NRIP1, ACSL1, METTL7B, OGT, CD83"], "order_basis": "paper_text_order:1563", "id": "assay:1"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["reaction (RT-qPCR) and cell counting kit-8 (CCK-8) assay were used to validate the genes in m6", "2878, THP-1 and U937 cell lines (n = 3). G-H CCK8 assay results of THP-1 and U937 cell lines a", "ell lines after CD83 inhibition (n = 3). I-J CCK8 assay results of THP-1 and U937 cell lines a"], "order_basis": "paper_text_order:1598", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.85, "evidence": ["L cohort, exhibiting different prognosis and immunoreactivity. We recognized novel prognostic biomarkers o"], "order_basis": "paper_text_order:1823", "id": "assay:3"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["rials and methods Cell culture and transient transfection GM12878 (BNCC360167), THP-1 (BNCC358410) and", "a). Cells were cultured in DEME F-12 medium. Transfection of the negative control (NC), CD83 siRNA and", "nsfection of the negative control (NC), CD83 siRNA and METTL7B siRNA (Sagon, China) was conduct", "egative control (NC), CD83 siRNA and METTL7B siRNA (Sagon, China) was conducted by applying Lip"], "order_basis": "paper_text_order:2902", "id": "assay:4"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["otechnology Co. (Beijing, China). Cells were cultured in DEME F-12 medium. Transfection of the negati"], "order_basis": "paper_text_order:3064", "id": "assay:5"}, {"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": ["LASSO and multivariate COX regression analyses were conducted on m6ARDEGs capable of influencing AML prognosis to construct an AML prognostic model [19], and the AML prognostic risk score (m6APR_Score) was calculated by the following equation."], "order_basis": "consumes_earlier_output", "id": "assay:6"}]}