{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T23:29:43Z","timestamp":1793230183352,"version":"4.5.0"},"reference-count":36,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T00:00:00Z","timestamp":1776211200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T00:00:00Z","timestamp":1776211200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100007316","name":"Division of Cancer Prevention, National Cancer Institute","doi-asserted-by":"publisher","award":["P30CA240139"],"award-info":[{"award-number":["P30CA240139"]}],"id":[{"id":"10.13039\/100007316","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Quant. Biol."],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Cancer is a highly heterogeneous disease, characterized by significant variability across multiple dimensions. This diversity has been extensively studied from various perspectives. In this study, we aim to examine cancer heterogeneity through the lens of immune cell composition within the tumor microenvironment. Transcriptome profiles of 11,274 subjects from 33 cancer types were deconvoluted to infer the composition of 22 immune cell types. A deep learning\u2010based model was adapted to model a binary outcome for cancer type, tumor versus normal. The Shannon index was used to represent immune cell diversity. Cox proportional hazards regression was used to evaluate the prognostic values of immune cells. Tumor and normal tissues showed significantly different immune cell compositions in 183 of 352 comparisons, with macrophage M0 levels consistently elevated in most tumors except lung adenocarcinoma. ResNet models using immune cell data achieved strong performance in distinguishing tumor versus normal samples (average F1 score\u00a0=\u00a00.64 when combined with clinical features). Four immune features were significantly associated with disease\u2010specific survival across three cancer types: macrophage M0 and macrophage M2 in bladder urothelial carcinoma, macrophage M0 in kidney renal clear cell carcinoma, and the Treg\/CD8\n                    <jats:sup>+<\/jats:sup>\n                    T cell ratio in skin cutaneous melanoma. Although immune cell diversity varied across cancers, it was not broadly predictive of prognosis, highlighting the cancer type\u2010specific nature of immune remodeling. Our results demonstrated cancer heterogeneity through the analysis of immune cell composition and diversity using deep learning models and prognostic analysis. The significant findings revealed varying patterns across different cancer types, indicating that no unifying standard can be established across all cancers.\n                  <\/jats:p>","DOI":"10.1002\/qub2.70037","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T03:47:07Z","timestamp":1776311227000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cancer heterogeneity explored through immune cell deconvolution of the tumor microenvironment"],"prefix":"10.1002","volume":"14","author":[{"given":"Limin","family":"Jiang","sequence":"first","affiliation":[{"name":"Department of Public Health Sciences University of Miami  Miami Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chung\u2010I","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Statistics Cheng Kung University  Tainan China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Xin","sequence":"additional","affiliation":[{"name":"Department of Computer Science University of South Carolina  Columbia South Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jijun","family":"Tang","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Public Health Sciences University of Miami  Miami Florida USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12943-020-01238-x"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nri819"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.smim.2020.101435"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/ni.2703"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrclinonc.2016.144"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/JLB.1MR0120-196R"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/ni1102-991"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/nm.3909"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13073-019-0638-6"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccell.2021.04.014"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.immuni.2019.08.004"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.crmeth.2021.100084"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aat7807"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1093\/annonc\/mdu191"},{"key":"e_1_2_12_16_1","doi-asserted-by":"publisher","DOI":"10.1080\/2162402X.2015.1134412"},{"key":"e_1_2_12_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3337"},{"issue":"2017","key":"e_1_2_12_18_1","first-page":"30","article-title":"The reversible residual network: backpropagation without storing activations","volume":"30","author":"Gomez AN","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"e_1_2_12_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1995.tb02031.x"},{"key":"e_1_2_12_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12024-023-00674-7"},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13184712"},{"key":"e_1_2_12_22_1","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1268939"},{"key":"e_1_2_12_23_1","doi-asserted-by":"publisher","DOI":"10.1186\/s41232-024-00335-4"},{"key":"e_1_2_12_24_1","doi-asserted-by":"publisher","DOI":"10.3390\/biom14020190"},{"key":"e_1_2_12_25_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13046-023-02832-9"},{"key":"e_1_2_12_26_1","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.1013686"},{"key":"e_1_2_12_27_1","doi-asserted-by":"publisher","DOI":"10.1038\/icb.2014.67"},{"key":"e_1_2_12_28_1","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-15-1439"},{"key":"e_1_2_12_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11864-021-00891-8"},{"key":"e_1_2_12_30_1","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2023.1209947"},{"key":"e_1_2_12_31_1","doi-asserted-by":"publisher","DOI":"10.1158\/2159-8290.CD-23-0434"},{"key":"e_1_2_12_32_1","article-title":"At the crossroads of TNF alpha signaling and cancer","volume":"17","author":"Manohar SM","year":"2024","journal-title":"Curr Mol Pharmacol"},{"key":"e_1_2_12_33_1","doi-asserted-by":"publisher","DOI":"10.2174\/0118761429249717230920113227"},{"key":"e_1_2_12_34_1","doi-asserted-by":"publisher","DOI":"10.2174\/1874467215666220324114624"},{"key":"e_1_2_12_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpan.2024.12.001"},{"issue":"1","key":"e_1_2_12_36_1","first-page":"62","article-title":"Breaking boundaries: chronic diseases and the frontiers of immune microenvironments","volume":"1","author":"Li G","year":"2025","journal-title":"Med Res"},{"key":"e_1_2_12_37_1","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"}],"container-title":["Quantitative Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/qub2.70037","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/qub2.70037","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/qub2.70037","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T17:38:18Z","timestamp":1790962698000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/qub2.70037"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,15]]},"references-count":36,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["10.1002\/qub2.70037"],"URL":"https:\/\/doi.org\/10.1002\/qub2.70037","archive":["Portico"],"relation":{},"ISSN":["2095-4689","2095-4697"],"issn-type":[{"value":"2095-4689","type":"print"},{"value":"2095-4697","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,15]]},"assertion":[{"value":"2024-11-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-22","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70037"}}