NET-related gene signature for predicting AML prognosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38643300", "kind": "science-record", "revision": 2, "content_hash": "sha256:6d4688a9badc946972b3ba59e81de3cf4961b8d95c2770a349454fded5f7e9ed", "created_at": "2026-11-01T19:20:36Z", "updated_at": "2026-11-01T21:32:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "NET-related gene signature for predicting AML prognosis.", "doi": "10.1038/s41598-024-59464-y", "pmid": "38643300", "authors": ["Jiajia Wang", "Huiping Wang", "Yangyang Ding", "Xunyi Jiao", "Jinli Zhu", "Zhimin Zhai"], "journal": "Scientific reports", "year": 2024, "abstract": "Acute Myeloid Leukemia (AML) is a malignant blood cancer with a high mortality rate. Neutrophil extracellular traps (NETs) influence various tumor outcomes. However, NET-related genes (NRGs) in AML had not yet received much attention. This study focuses on the role of NRGs in AML and their interaction with the immunological microenvironment. The gene expression and clinical data of patients with AML were downloaded from the TCGA-LAML and GEO cohorts. We identified 148 NRGs through the published article. Univariate Cox regression was used to analyze the association of NRGs with overall survival (OS). The least absolute shrinkage and selection operator were utilized to assess the predictive efficacy of NRGs. Kaplan-Meier plots visualized survival estimates. ROC curves assessed the prognostic value of NRG-based features. A nomogram, integrating clinical information and prognostic scores of patients, was constructed using multivariate logistic regression and Cox proportional hazards regression models. Twenty-seven NRGs were found to significantly impact patient OS. Six NRGs-CFTR, ENO1, PARVB, DDIT4, MPO, LDLR-were notable for their strong predictive ability regarding patient survival. The ROC values for 1-, 3-, and 5-year survival rates were 0.794, 0.781, and 0.911, respectively. In the training set (TCGA-LAML), patients in the high NRG risk group showed a poorer prognosis (p < 0.001), which was validated in two external datasets (GSE71014 and GSE106291). The 6-NRG signature and corresponding nomograms exhibit superior predictive accuracy, offering insights for pre-immune response evaluation and guiding future immuno-oncology treatments and drug selection for AML patients.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression was employed to identify NETs associated with overall survival (OS) in the TCGA-LAML cohort (n = 136; p < 0.1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38643300", "locator": "sections[5] \"Identification of NRGs associated with overall survival (OS)\" paragraph 2", "quote": "Univariate Cox regression was employed to identify NETs associated with overall survival (OS) in the TCGA-LAML cohort (n = 136; p < 0.1)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38643300", "locator": "sections[25] \"Data availability\" paragraph 2", "quote": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six-NRG signature comprising CFTR, ENO1, PARVB, DDIT4, MPO, and LDLR was developed and validated as an AML prognostic model.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38643300", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Six NRGs—CFTR, ENO1, PARVB, DDIT4, MPO, LDLR—were notable for their strong predictive ability regarding patient survival."}, {"asset": "source:pmid:38643300", "locator": "sections[15] \"NET-related genes with significant prognostic value in AML\" paragraph 2", "quote": "Those genes are CFTR, ENO1, PARVB, DDIT4, MPO, and LDLR."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six-NRG signature comprising CFTR, ENO1, PARVB, DDIT4, MPO, and LDLR was developed and validated as an AML prognostic model.", "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:38643300"], "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:GSE106291"], "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:GSE106291"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38643300", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-024-59464-y", "sha256": "sha256:7b9847687c6c9796a467131d30e110678ee15ec2d9e8e9dbe4d7e2245437cd2b", "bytes": 44272, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-024-59464-y", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11032381", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE106291", "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=GSE106291", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE106291", "version": null, "note": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2835244", "GSM2835245", "GSM2835246", "GSM2835247", "GSM2835248", "GSM2835249", "GSM2835250", "GSM2835251", "GSM2835252", "GSM2835253", "GSM2835254", "GSM2835255", "GSM2835256", "GSM2835257", "GSM2835258", "GSM2835259", "GSM2835260", "GSM2835261", "GSM2835262", "GSM2835263", "GSM2835264", "GSM2835265", "GSM2835266", "GSM2835267", "GSM2835268", "GSM2835269", "GSM2835270", "GSM2835271", "GSM2835272", "GSM2835273", "GSM2835274", "GSM2835275", "GSM2835276", "GSM2835277", "GSM2835278", "GSM2835279", "GSM2835280", "GSM2835281", "GSM2835282", "GSM2835283", "GSM2835284", "GSM2835285", "GSM2835286", "GSM2835287", "GSM2835288", "GSM2835289", "GSM2835290", "GSM2835291", "GSM2835292", "GSM2835293", "GSM2835294", "GSM2835295", "GSM2835296", "GSM2835297", "GSM2835298", "GSM2835299", "GSM2835300", "GSM2835301", "GSM2835302", "GSM2835303", "GSM2835304", "GSM2835305", "GSM2835306", "GSM2835307", "GSM2835308", "GSM2835309", "GSM2835310", "GSM2835311", "GSM2835312", "GSM2835313", "GSM2835314", "GSM2835315", "GSM2835316", "GSM2835317", "GSM2835318", "GSM2835319", "GSM2835320", "GSM2835321", "GSM2835322", "GSM2835323", "GSM2835324", "GSM2835325", "GSM2835326", "GSM2835327", "GSM2835328", "GSM2835329", "GSM2835330", "GSM2835331", "GSM2835332", "GSM2835333", "GSM2835334", "GSM2835335", "GSM2835336", "GSM2835337", "GSM2835338", "GSM2835339", "GSM2835340", "GSM2835341", "GSM2835342", "GSM2835343", "GSM2835344", "GSM2835345", "GSM2835346", "GSM2835347", "GSM2835348", "GSM2835349", "GSM2835350", "GSM2835351", "GSM2835352", "GSM2835353", "GSM2835354", "GSM2835355", "GSM2835356", "GSM2835357", "GSM2835358", "GSM2835359", "GSM2835360", "GSM2835361", "GSM2835362", "GSM2835363", "GSM2835364", "GSM2835365", "GSM2835366", "GSM2835367", "GSM2835368", "GSM2835369", "GSM2835370", "GSM2835371", "GSM2835372", "GSM2835373", "GSM2835374", "GSM2835375", "GSM2835376", "GSM2835377", "GSM2835378", "GSM2835379", "GSM2835380", "GSM2835381", "GSM2835382", "GSM2835383", "GSM2835384", "GSM2835385", "GSM2835386", "GSM2835387", "GSM2835388", "GSM2835389", "GSM2835390", "GSM2835391", "GSM2835392", "GSM2835393", "GSM2835394", "GSM2835395", "GSM2835396", "GSM2835397", "GSM2835398", "GSM2835399", "GSM2835400", "GSM2835401", "GSM2835402", "GSM2835403", "GSM2835404", "GSM2835405", "GSM2835406", "GSM2835407", "GSM2835408", "GSM2835409", "GSM2835410", "GSM2835411", "GSM2835412", "GSM2835413", "GSM2835414", "GSM2835415", "GSM2835416", "GSM2835417", "GSM2835418", "GSM2835419", "GSM2835420", "GSM2835421", "GSM2835422", "GSM2835423", "GSM2835424", "GSM2835425", "GSM2835426", "GSM2835427", "GSM2835428", "GSM2835429", "GSM2835430", "GSM2835431", "GSM2835432", "GSM2835433", "GSM2835434", "GSM2835435", "GSM2835436", "GSM2835437", "GSM2835438", "GSM2835439", "GSM2835440", "GSM2835441", "GSM2835442", "GSM2835443", "GSM2835444", "GSM2835445", "GSM2835446", "GSM2835447", "GSM2835448", "GSM2835449", "GSM2835450", "GSM2835451", "GSM2835452", "GSM2835453", "GSM2835454", "GSM2835455", "GSM2835456", "GSM2835457", "GSM2835458", "GSM2835459", "GSM2835460", "GSM2835461", "GSM2835462", "GSM2835463", "GSM2835464", "GSM2835465", "GSM2835466", "GSM2835467", "GSM2835468", "GSM2835469", "GSM2835470", "GSM2835471", "GSM2835472", "GSM2835473", "GSM2835474", "GSM2835475", "GSM2835476", "GSM2835477", "GSM2835478", "GSM2835479", "GSM2835480", "GSM2835481", "GSM2835482", "GSM2835483", "GSM2835484", "GSM2835485", "GSM2835486", "GSM2835487", "GSM2835488", "GSM2835489", "GSM2835490", "GSM2835491", "GSM2835492", "GSM2835493"], "sample_count": 250, "group_sizes": null, "group_sizes_basis": null, "platform": "18460", "taxon": "Homo sapiens", "title": "A 29-Gene and Cytogenetic Score for the Prediction of Resistance to Induction Treatment in Acute Myeloid 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: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": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291.", "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:GSE106291 not downloaded", "asset:data:geo:GSE106291 licence not read", "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": "Univariate Cox regression was employed to identify NETs associated with overall survival (OS) in the TCGA-LAML cohort (n = 136; p < 0.1)."}}, {"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": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.7, "band": "medium", "quote": "logistic regression"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}], "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", "GSE106291"], "resolved_accessions": ["GSE71014", "GSE106291"], "statements": ["All data are available from the TCGA database (https://xenabrowser.net/datapages/) and GEO (https://ncbi.nlm.nih.gov/geo/) database within the article. GEO database under accession number GSE71014 and GSE106291."], "basis": "The paper names GSE71014, GSE106291 in GEO database 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:38643300", "data:geo:GSE106291"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE106291"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:16:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 13212, "completion_tokens": 1504, "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:38643300", "type": "paper", "label": "pmid:38643300"}, {"id": "source:pmid:38643300", "type": "manuscript", "label": "PMID 38643300 full text"}, {"id": "data:geo:GSE106291", "type": "dataset", "label": "GEO GSE106291"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38643300", "type": "paper", "label": "pmid:38643300"}, {"id": "source:pmid:38643300", "type": "manuscript", "label": "PMID 38643300 full text"}, {"id": "data:geo:GSE106291", "type": "dataset", "label": "GEO GSE106291"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38643300", "type": "extraction", "used": ["source:pmid:38643300"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE106291", "type": "accession_resolution", "used": ["data:geo:GSE106291"], "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:38643300", "parent_hash": "sha256:1840c7bd472d8e0ec200e346bb8459164b4c0ccb23d69528401ed3a5f8a50aa3", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:GSE106291 licence not read", "asset:data:geo:GSE106291 not downloaded", "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": "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": ["Univariate Cox regression was employed to identify NETs associated with overall survival (OS) in the TCGA-LAML cohort (n = 136; p < 0.1)."], "order_basis": "analysis_only", "id": "assay:1"}]}