Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36443508", "kind": "science-record", "revision": 4, "content_hash": "sha256:0b9df80b5961658ae6ddc266d040330935fb6f0408f02cdb0e768cbf82d1e51f", "created_at": "2026-11-01T19:00:55Z", "updated_at": "2026-11-01T22:50:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive evaluation of breast cancer immunotherapy and tumor microenvironment characterization based on interleukin genes-related risk model.", "doi": "10.1038/s41598-022-25059-8", "pmid": "36443508", "authors": ["Yalei Lv", "Zihe Bai", "Xiaoyan Wang", "Jiayin Liu", "Yuntao Li", "Xiaolin Zhang", "Yujie Shan"], "journal": "Scientific reports", "year": 2022, "abstract": "Breast cancer (BRCA) is the most prevalent malignancy and the leading cause of death in women. Interleukin (IL) genes are critical in tumor initiation and control. Nevertheless, the prognosis value of the IL in BRCA remains unclear. We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard. Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature. GSE22219, GSE25065, and GSE21653 were derived as validation sets. The expression differences in the tumor microenvironment (TME), immunotherapy, and chemosensitivity of BRCA between the high- and low-risk groups were evaluated. Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA. IL score could distinguish BRCA patients with inferior outcomes, and AUC of it was 0.70, 0.76, and 0.72 for 1-,3- and 5- years, respectively, which was also verified in GSE22219, GSE25065, and GSE21653 cohorts. Meanwhile, compared to luminal A and luminal B, HER2-positive and TNBC had significantly higher IL score. Besides, the high-risk group had a significantly higher prevalence of TP53 and TTN but a lower prevalence of PIK3CA, as well as higher tumor mutation burden (TMB) and neoantigen level. High- and low-risk groups exhibited notable differences in immunomodulators and tumor infiltrates immune cells (TIICs), and the high-risk group had significantly lower Tumor Immune Dysfunction and Exclusion (TIDE) score. Additionally, the high-risk group has more responders to immune or anti-HER2 combination therapy, whereas the low-risk group has higher sensitivity to docetaxel and paclitaxel. Consequently, we constructed a reliable risk model based on the IL genes, which can provide more information on both the risk stratification and personalizing management strategies for BRCA.", "claims": [{"id": "claim-method", "statement": "Firstly, we performed random forest (RF) with R package “randomSurvivalForest” (version 3.6.4)27 to obtain hub IL genes (with variable relative importance ≥ 0.4). Secondly, the least absolute shrinkage and selection operator (LASSO) regression analysis28 was applied to screen out the optimal genes through the \"glmnet\" R package29, and the best λ value was obtained by tenfold cross-validation used for gene screening. We took the intersection genes of hub genes and optimal genes from RF and LASSO, respectively, and applied multivariate Cox regression analysis to construct a risk model based on them.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36443508", "locator": "sections[4] \"Construction and validation of the IL score\" paragraph 2", "quote": "Firstly, we performed random forest (RF) with R package “randomSurvivalForest” (version 3.6.4)27 to obtain hub IL genes (with variable relative importance ≥ 0.4). Secondly, the least absolute shrinkage and selection operator (LASSO) regression analysis28 was applied to screen out the optimal genes through the \"glmnet\" R package29, and the best λ value was obtained by tenfold cross-validation used for gene screening. We took the intersection genes of hub genes and optimal genes from RF and LASSO, respectively, and applied multivariate Cox regression analysis to construct a risk model based on them."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36443508", "locator": "sections[32] \"notes\" paragraph 1", "quote": "The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36443508", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA."}, {"asset": "source:pmid:36443508", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We collected data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and 94 IL genes were identified from GeneCard."}, {"asset": "source:pmid:36443508", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Based on the random forest (RF), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox regression analysis, we constructed an IL signature."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Overall, 21 IL genes were selected to construct an IL risk model, of which IL18BP, IL17D, and IL23A were the first time identified as prognostic genes in BRCA.", "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:36443508"], "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:GSE21653"], "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:GSE21653"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36443508", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-022-25059-8", "sha256": "sha256:19d4943fcaf288e83fe1c512ea9ad08a9ff4cebc7fcee129db225424530e6361", "bytes": 40868, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-022-25059-8", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9705306", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE21653", "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=GSE21653", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE21653", "version": null, "note": "The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets 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 and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM540108", "GSM540109", "GSM540110", "GSM540111", "GSM540112", "GSM540113", "GSM540114", "GSM540115", "GSM540116", "GSM540117", "GSM540118", "GSM540119", "GSM540120", "GSM540121", "GSM540122", "GSM540123", "GSM540124", "GSM540125", "GSM540126", "GSM540127", "GSM540128", "GSM540129", "GSM540130", "GSM540131", "GSM540132", "GSM540133", "GSM540134", "GSM540135", "GSM540136", "GSM540137", "GSM540138", "GSM540139", "GSM540140", "GSM540141", "GSM540142", "GSM540143", "GSM540144", "GSM540145", "GSM540146", "GSM540147", "GSM540148", "GSM540149", "GSM540150", "GSM540151", "GSM540152", "GSM540153", "GSM540154", "GSM540155", "GSM540156", "GSM540157", "GSM540158", "GSM540159", "GSM540160", "GSM540161", "GSM540162", "GSM540163", "GSM540164", "GSM540165", "GSM540166", "GSM540167", "GSM540168", "GSM540169", "GSM540170", "GSM540171", "GSM540172", "GSM540173", "GSM540174", "GSM540175", "GSM540176", "GSM540177", "GSM540178", "GSM540179", "GSM540180", "GSM540181", "GSM540182", "GSM540183", "GSM540184", "GSM540185", "GSM540186", "GSM540187", "GSM540188", "GSM540189", "GSM540190", "GSM540191", "GSM540192", "GSM540193", "GSM540194", "GSM540195", "GSM540196", "GSM540197", "GSM540198", "GSM540199", "GSM540200", "GSM540201", "GSM540202", "GSM540203", "GSM540204", "GSM540205", "GSM540206", "GSM540207", "GSM540208", "GSM540209", "GSM540210", "GSM540211", "GSM540212", "GSM540213", "GSM540214", "GSM540215", "GSM540216", "GSM540217", "GSM540218", "GSM540219", "GSM540220", "GSM540221", "GSM540222", "GSM540223", "GSM540224", "GSM540225", "GSM540226", "GSM540227", "GSM540228", "GSM540229", "GSM540230", "GSM540231", "GSM540232", "GSM540233", "GSM540234", "GSM540235", "GSM540236", "GSM540237", "GSM540238", "GSM540239", "GSM540240", "GSM540241", "GSM540242", "GSM540243", "GSM540244", "GSM540245", "GSM540246", "GSM540247", "GSM540248", "GSM540249", "GSM540250", "GSM540251", "GSM540252", "GSM540253", "GSM540254", "GSM540255", "GSM540256", "GSM540257", "GSM540258", "GSM540259", "GSM540260", "GSM540261", "GSM540262", "GSM540263", "GSM540264", "GSM540265", "GSM540266", "GSM540267", "GSM540268", "GSM540269", "GSM540270", "GSM540271", "GSM540272", "GSM540273", "GSM540274", "GSM540275", "GSM540276", "GSM540277", "GSM540278", "GSM540279", "GSM540280", "GSM540281", "GSM540282", "GSM540283", "GSM540284", "GSM540285", "GSM540286", "GSM540287", "GSM540288", "GSM540289", "GSM540290", "GSM540291", "GSM540292", "GSM540293", "GSM540294", "GSM540295", "GSM540296", "GSM540297", "GSM540298", "GSM540299", "GSM540300", "GSM540301", "GSM540302", "GSM540303", "GSM540304", "GSM540305", "GSM540306", "GSM540307", "GSM540308", "GSM540309", "GSM540310", "GSM540311", "GSM540312", "GSM540313", "GSM540314", "GSM540315", "GSM540316", "GSM540317", "GSM540318", "GSM540319", "GSM540320", "GSM540321", "GSM540322", "GSM540323", "GSM540324", "GSM540325", "GSM540326", "GSM540327", "GSM540328", "GSM540329", "GSM540330", "GSM540331", "GSM540332", "GSM540333", "GSM540334", "GSM540335", "GSM540336", "GSM540337", "GSM540338", "GSM540339", "GSM540340", "GSM540341", "GSM540342", "GSM540343", "GSM540344", "GSM540345", "GSM540346", "GSM540347", "GSM540348", "GSM540349", "GSM540350", "GSM540351", "GSM540352", "GSM540353", "GSM540354", "GSM540355", "GSM540356", "GSM540357", "GSM540358", "GSM540359", "GSM540360", "GSM540361", "GSM540362", "GSM540363", "GSM540364", "GSM540365", "GSM540366", "GSM540367", "GSM540368", "GSM540369", "GSM540370", "GSM540371", "GSM540372", "GSM540373"], "sample_count": 266, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "A gene expression signature identifies two prognostic subgroups of basal breast cancer", "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:GSE22219", "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=GSE22219", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE22219", "version": null, "note": "The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets 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 and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM553184", "GSM553185", "GSM553186", "GSM553187", "GSM553188", "GSM553189", "GSM553190", "GSM553191", "GSM553192", "GSM553193", "GSM553194", "GSM553195", "GSM553196", "GSM553197", "GSM553198", "GSM553199", "GSM553200", "GSM553201", "GSM553202", "GSM553203", "GSM553204", "GSM553205", "GSM553206", "GSM553207", "GSM553208", "GSM553209", "GSM553210", "GSM553211", "GSM553212", "GSM553213", "GSM553214", "GSM553215", "GSM553216", "GSM553217", "GSM553218", "GSM553219", "GSM553220", "GSM553221", "GSM553222", "GSM553223", "GSM553224", "GSM553225", "GSM553226", "GSM553227", "GSM553228", "GSM553229", "GSM553230", "GSM553231", "GSM553232", "GSM553233", "GSM553234", "GSM553235", "GSM553236", "GSM553237", "GSM553238", "GSM553239", "GSM553240", "GSM553241", "GSM553242", "GSM553243", "GSM553244", "GSM553245", "GSM553246", "GSM553247", "GSM553248", "GSM553249", "GSM553250", "GSM553251", "GSM553252", "GSM553253", "GSM553254", "GSM553255", "GSM553256", "GSM553257", "GSM553258", "GSM553259", "GSM553260", "GSM553261", "GSM553262", "GSM553263", "GSM553264", "GSM553265", "GSM553266", "GSM553267", "GSM553268", "GSM553269", "GSM553270", "GSM553271", "GSM553272", "GSM553273", "GSM553274", "GSM553275", "GSM553276", "GSM553277", "GSM553278", "GSM553279", "GSM553280", "GSM553281", "GSM553282", "GSM553283", "GSM553284", "GSM553285", "GSM553286", "GSM553287", "GSM553288", "GSM553289", "GSM553290", "GSM553291", "GSM553292", "GSM553293", "GSM553294", "GSM553295", "GSM553296", "GSM553297", "GSM553298", "GSM553299", "GSM553300", "GSM553301", "GSM553302", "GSM553303", "GSM553304", "GSM553305", "GSM553306", "GSM553307", "GSM553308", "GSM553309", "GSM553310", "GSM553311", "GSM553312", "GSM553313", "GSM553314", "GSM553315", "GSM553316", "GSM553317", "GSM553318", "GSM553319", "GSM553320", "GSM553321", "GSM553322", "GSM553323", "GSM553324", "GSM553325", "GSM553326", "GSM553327", "GSM553328", "GSM553329", "GSM553330", "GSM553331", "GSM553332", "GSM553333", "GSM553334", "GSM553335", "GSM553336", "GSM553337", "GSM553338", "GSM553339", "GSM553340", "GSM553341", "GSM553342", "GSM553343", "GSM553344", "GSM553345", "GSM553346", "GSM553347", "GSM553348", "GSM553349", "GSM553350", "GSM553351", "GSM553352", "GSM553353", "GSM553354", "GSM553355", "GSM553356", "GSM553357", "GSM553358", "GSM553359", "GSM553360", "GSM553361", "GSM553362", "GSM553363", "GSM553364", "GSM553365", "GSM553366", "GSM553367", "GSM553368", "GSM553369", "GSM553370", "GSM553371", "GSM553372", "GSM553373", "GSM553374", "GSM553375", "GSM553376", "GSM553377", "GSM553378", "GSM553379", "GSM553380", "GSM553381", "GSM553382", "GSM553383", "GSM553384", "GSM553385", "GSM553386", "GSM553387", "GSM553388", "GSM553389", "GSM553390", "GSM553391", "GSM553392", "GSM553393", "GSM553394", "GSM553395", "GSM553396", "GSM553397", "GSM553398", "GSM553399"], "sample_count": 216, "group_sizes": null, "group_sizes_basis": null, "platform": "6098", "taxon": "Homo sapiens", "title": "Gene expression profiling of early primary breast cancer to identify prognostic markers and associated pathways", "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:GSE25065", "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=GSE25065", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE25065", "version": null, "note": "The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets 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 and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM615631", "GSM615632", "GSM615633", "GSM615634", "GSM615635", "GSM615636", "GSM615637", "GSM615638", "GSM615639", "GSM615640", "GSM615641", "GSM615642", "GSM615643", "GSM615644", "GSM615645", "GSM615646", "GSM615647", "GSM615648", "GSM615649", "GSM615650", "GSM615651", "GSM615652", "GSM615653", "GSM615654", "GSM615655", "GSM615656", "GSM615657", "GSM615658", "GSM615659", "GSM615660", "GSM615661", "GSM615662", "GSM615663", "GSM615664", "GSM615665", "GSM615666", "GSM615667", "GSM615668", "GSM615669", "GSM615670", "GSM615671", "GSM615672", "GSM615673", "GSM615674", "GSM615675", "GSM615676", "GSM615677", "GSM615678", "GSM615679", "GSM615680", "GSM615681", "GSM615682", "GSM615683", "GSM615684", "GSM615685", "GSM615686", "GSM615687", "GSM615688", "GSM615689", "GSM615690", "GSM615691", "GSM615692", "GSM615693", "GSM615694", "GSM615695", "GSM615696", "GSM615697", "GSM615698", "GSM615699", "GSM615700", "GSM615701", "GSM615702", "GSM615703", "GSM615704", "GSM615705", "GSM615706", "GSM615707", "GSM615708", "GSM615709", "GSM615710", "GSM615711", "GSM615712", "GSM615713", "GSM615714", "GSM615715", "GSM615716", "GSM615717", "GSM615718", "GSM615719", "GSM615720", "GSM615721", "GSM615722", "GSM615723", "GSM615724", "GSM615725", "GSM615726", "GSM615727", "GSM615728", "GSM615729", "GSM615730", "GSM615731", "GSM615732", "GSM615733", "GSM615734", "GSM615735", "GSM615736", "GSM615737", "GSM615738", "GSM615739", "GSM615740", "GSM615741", "GSM615742", "GSM615743", "GSM615744", "GSM615745", "GSM615746", "GSM615747", "GSM615748", "GSM615749", "GSM615750", "GSM615751", "GSM615752", "GSM615753", "GSM615754", "GSM615755", "GSM615756", "GSM615757", "GSM615758", "GSM615759", "GSM615760", "GSM615761", "GSM615762", "GSM615763", "GSM615764", "GSM615765", "GSM615766", "GSM615767", "GSM615768", "GSM615769", "GSM615770", "GSM615771", "GSM615772", "GSM615773", "GSM615774", "GSM615775", "GSM615776", "GSM615777", "GSM615778", "GSM615779", "GSM615780", "GSM615781", "GSM615782", "GSM615783", "GSM615784", "GSM615785", "GSM615786", "GSM615787", "GSM615788", "GSM615789", "GSM615790", "GSM615791", "GSM615792", "GSM615793", "GSM615794", "GSM615795", "GSM615796", "GSM615797", "GSM615798", "GSM615799", "GSM615800", "GSM615801", "GSM615802", "GSM615803", "GSM615804", "GSM615805", "GSM615806", "GSM615807", "GSM615808", "GSM615809", "GSM615810", "GSM615811", "GSM615812", "GSM615813", "GSM615814", "GSM615815", "GSM615816", "GSM615817", "GSM615818", "GSM615819", "GSM615820", "GSM615821", "GSM615822", "GSM615823", "GSM615824", "GSM615825", "GSM615826", "GSM615827", "GSM615828"], "sample_count": 198, "group_sizes": null, "group_sizes_basis": null, "platform": "96", "taxon": "Homo sapiens", "title": "Validation cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE21653 not downloaded", "asset:data:geo:GSE21653 licence not read", "asset:data:geo:GSE22219 not downloaded", "asset:data:geo:GSE22219 licence not read", "asset:data:geo:GSE25065 not downloaded", "asset:data:geo:GSE25065 licence not read"]}, "analysis": {"state": "partial", "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": "Firstly, we performed random forest (RF) with R package “randomSurvivalForest” (version 3.6.4)27 to obtain hub IL genes (with variable relative importance ≥ 0.4). Secondly, the least absolute shrinkage and selection operator (LASSO) regression analysis28 was applied to screen out the optimal genes through the \"glmnet\" R package29, and the best λ value was obtained by tenfold cross-validation used for gene screening. We took the intersection genes of hub genes and optimal genes from RF and LASSO, respectively, and applied multivariate Cox regression analysis to construct a risk model based on them."}}, {"id": "method-2", "family": "group_comparison", "specific": "student_t_test", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["student_t"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Student's t-test"}}, {"id": "method-3", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-4", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-5", "family": "machine_learning", "specific": "random_forest", "label": "Machine learning", "dsl_operations": [], "missing_operations": ["machine_learning_random_forest"], "expressible": false, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 0.7, "band": "medium", "quote": "random forest"}}, {"id": "method-6", "family": "contingency_analysis", "specific": "fisher_exact", "label": "Categorical (contingency table) analysis", "dsl_operations": ["contingency_table", "chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "Fisher's exact"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["GSE22219", "GSE25065", "GSE21653"], "resolved_accessions": ["GSE22219", "GSE25065", "GSE21653"], "statements": ["The datasets generated and analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository (http://xena.ucsc.edu/), and GSE22219, GSE25065, and GSE21653 from Gene Expression Omnibus (GEO) repository (https://www.ncbi.nlm.nih.gov/geo/). Access to both repositories is not required accession number. The datasets analyzed during the current study are available from the corresponding author on reasonable request."], "basis": "The paper names GSE22219, GSE25065, GSE21653 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:36443508", "data:geo:GSE21653"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE21653"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:17:38Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 11194, "completion_tokens": 2582, "cached_tokens": 256}}, "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:36443508", "type": "paper", "label": "pmid:36443508"}, {"id": "source:pmid:36443508", "type": "manuscript", "label": "PMID 36443508 full text"}, {"id": "data:geo:GSE21653", "type": "dataset", "label": "GEO GSE21653"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36443508", "type": "paper", "label": "pmid:36443508"}, {"id": "source:pmid:36443508", "type": "manuscript", "label": "PMID 36443508 full text"}, {"id": "data:geo:GSE21653", "type": "dataset", "label": "GEO GSE21653"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36443508", "type": "extraction", "used": ["source:pmid:36443508"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE21653", "type": "accession_resolution", "used": ["data:geo:GSE21653"], "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:36443508", "parent_hash": "sha256:d5b128af4986bc5b600c4b1dae3ce9a74772e2076f5e063c7c2afcb50112a1f6", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE21653 licence not read", "asset:data:geo:GSE21653 not downloaded", "asset:data:geo:GSE22219 licence not read", "asset:data:geo:GSE22219 not downloaded", "asset:data:geo:GSE25065 licence not read", "asset:data:geo:GSE25065 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "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": ["Firstly, we performed random forest (RF) with R package “randomSurvivalForest” (version 3.6.4)27 to obtain hub IL genes (with variable relative importance ≥ 0.4). Secondly, the least absolute shrinkage and selection operator (LASSO) regression analysis28 was applied to screen out the optimal genes through the \"glmnet\" R package29, and the best λ value was obtained by tenfold cross-validation used for gene screening. We took the intersection genes of hub genes and optimal genes from RF and LASSO, respectively, and applied multivariate Cox regression analysis to construct a risk model based on them."], "order_basis": "analysis_only", "id": "assay:1"}]}