{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T21:58:02Z","timestamp":1780610282173,"version":"3.54.1"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,1,21]],"date-time":"2023-01-21T00:00:00Z","timestamp":1674259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"The Zhejiang Provincial Natural Science Foundation of China","award":["LY21C060003"],"award-info":[{"award-number":["LY21C060003"]}]},{"name":"Innovation Project for Institute of Computing Technology, CAS","award":["E161080"],"award-info":[{"award-number":["E161080"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32070670"],"award-info":[{"award-number":["32070670"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["XDA16021400"],"award-info":[{"award-number":["XDA16021400"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFC2500200"],"award-info":[{"award-number":["2021YFC2500200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFC2500203"],"award-info":[{"award-number":["2021YFC2500203"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,3,19]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The determination of transcriptome profiles that mediate immune therapy in cancer remains a major clinical and biological challenge. Despite responses induced by immune-check points inhibitors (ICIs) in diverse tumor types and all the big breakthroughs in cancer immunotherapy, most patients with solid tumors do not respond to ICI therapies. It still remains a big challenge to predict the ICI treatment response. Here, we propose a framework with multiple prior knowledge networks guided for immune checkpoints inhibitors prediction\u2014DeepOmix-ICI (or ICInet for short). ICInet can predict the immune therapy response by leveraging geometric deep learning and prior biological knowledge graphs of gene\u2013gene interactions. Here, we demonstrate more than 600 ICI-treated patients with ICI response data and gene expression profile to apply on ICInet. ICInet was used for ICI therapy responses prediciton across different cancer types\u2014melanoma, gastric cancer and bladder cancer, which includes 7 cohorts from different data sources. ICInet is able to robustly generalize into multiple cancer types. Moreover, the performance of ICInet in those cancer types can outperform other ICI biomarkers in the clinic. Our model [area under the curve (AUC\u2009=\u20090.85)] generally outperformed other measures, including tumor mutational burden (AUC\u2009=\u20090.62) and programmed cell death ligand-1 score (AUC\u2009=\u20090.74). Therefore, our study presents a prior-knowledge guided deep learning method to effectively select immunotherapy-response-associated biomarkers, thereby improving the prediction of immunotherapy response for precision oncology.<\/jats:p>","DOI":"10.1093\/bib\/bbad023","type":"journal-article","created":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T14:11:19Z","timestamp":1674396679000},"source":"Crossref","is-referenced-by-count":22,"title":["Biological knowledge graph-guided investigation of immune therapy response in cancer with graph neural network"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7736-2443","authenticated-orcid":false,"given":"Lianhe","family":"Zhao","sequence":"first","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3447-2842","authenticated-orcid":false,"given":"Xiaoning","family":"Qi","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Chen","sequence":"additional","affiliation":[{"name":"The First People's Hospital of Yunnan Province , Kunming, 650032, Yunnan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yixuan","family":"Qiao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dechao","family":"Bu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Wu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yufan","family":"Luo","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"},{"name":"University of Chinese Academy of Sciences , Beijing 100049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"BGI-Beijing , Beijing, 102601, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6046-8420","authenticated-orcid":false,"given":"Yi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences Research Center for Ubiquitous Computing Systems, Institute of Computing Technology, , Beijing 100190 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,1,21]]},"reference":[{"issue":"4","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1038\/s41571-022-00600-w","article-title":"Immune-checkpoint inhibitors: long-term implications of toxicity","volume":"19","author":"Johnson","year":"2022","journal-title":"Nat Rev Clin Oncol"},{"key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/bs.acr.2022.03.002","article-title":"Immunotherapies for hepatocellular carcinoma and intrahepatic cholangiocarcinoma: current and developing strategies","volume":"156","author":"Argemi","year":"2022","journal-title":"Adv Cancer Res"},{"issue":"9","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1038\/s41585-021-00483-z","article-title":"Using oncolytic viruses to ignite the tumour immune microenvironment in bladder cancer","volume":"18","author":"Li","year":"2021","journal-title":"Nat Rev Urol"},{"issue":"7","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1420","DOI":"10.21037\/tlcr-22-464","article-title":"Safety and efficacy of immune checkpoint inhibitors in non-small cell lung cancer patients with preexisting antinuclear antibodies: a retrospective cohort study","volume":"11","author":"Zhang","year":"2022","journal-title":"Transl Lung Cancer Res"},{"key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"e2100372","DOI":"10.1200\/PO.21.00372","article-title":"Changes in circulating tumor DNA reflect clinical benefit across multiple studies of patients with non-small-cell lung cancer treated with immune checkpoint inhibitors","volume":"6","author":"Vega","year":"2022","journal-title":"JCO Precis Oncol"},{"issue":"1","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"e000319","DOI":"10.1136\/jitc-2019-000319","article-title":"Characterization of tumor mutation burden, PD-L1 and DNA repair genes to assess relationship to immune checkpoint inhibitors response in metastatic renal cell carcinoma","volume":"8","author":"Labriola","year":"2020","journal-title":"J Immunother Cancer"},{"issue":"3","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1016\/j.cell.2021.01.002","article-title":"Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition","volume":"184","author":"Litchfield","year":"2021","journal-title":"Cell"},{"issue":"1","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s13073-019-0626-x","article-title":"Encircling the regions of the pharmacogenomic landscape that determine drug response","volume":"11","author":"Fernandez-Torras","year":"2019","journal-title":"Genome Med"},{"issue":"5560","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.1126\/science.1069492","article-title":"Systems biology: a brief overview","volume":"295","author":"Kitano","year":"2002","journal-title":"Science"},{"issue":"5","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1038\/s41573-020-0079-3","article-title":"Organs-on-chips: into the next decade","volume":"20","author":"Low","year":"2021","journal-title":"Nat Rev Drug Discov"},{"key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"2719","DOI":"10.1016\/j.csbj.2021.04.067","article-title":"DeepOmix: a scalable and interpretable multi-omics deep learning framework and application in cancer survival analysis","volume":"19","author":"Zhao","year":"2021","journal-title":"Comput Struct Biotechnol J"},{"key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"10331","DOI":"10.1038\/ncomms10331","article-title":"Network-based in silico drug efficacy screening","volume":"7","author":"Guney","year":"2016","journal-title":"Nat Commun"},{"key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1007\/978-94-017-7215-0_18","article-title":"Biomarker in cisplatin-based chemotherapy for urinary bladder cancer","volume":"867","author":"Ecke","year":"2015","journal-title":"Adv Exp Med Biol"},{"issue":"2","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1038\/s41592-019-0667-5","article-title":"NicheNet: modeling intercellular communication by linking ligands to target genes","volume":"17","author":"Browaeys","year":"2020","journal-title":"Nat Methods"},{"issue":"9","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1038\/s41591-018-0101-z","article-title":"Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer","volume":"24","author":"Kim","year":"2018","journal-title":"Nat Med"},{"issue":"2","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.ccell.2019.01.003","article-title":"Distinct immune cell populations define response to anti-PD-1 monotherapy and anti-PD-1\/anti-CTLA-4 combined therapy","volume":"35","author":"Gide","year":"2019","journal-title":"Cancer Cell"},{"issue":"12","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1916","DOI":"10.1038\/s41591-019-0654-5","article-title":"Integrative molecular and clinical modeling of clinical outcomes to PD1 blockade in patients with metastatic melanoma","volume":"25","author":"Liu","year":"2019","journal-title":"Nat Med"},{"issue":"887","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1259\/bjr.74.887.740983","article-title":"The RECIST (response evaluation criteria in solid Tumors) criteria: implications for diagnostic radiologists","volume":"74","author":"Padhani","year":"2001","journal-title":"Br J Radiol"},{"issue":"10","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1038\/s41591-018-0157-9","article-title":"Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma","volume":"24","author":"Auslander","year":"2018","journal-title":"Nat Med"},{"key":"2023032004363147800_","first-page":"185.1","article-title":"Hyperband: a novel bandit-based approach to Hyperparameter optimization","volume-title":"The Journal of Machine Learning Research","author":"Li","year":"2017"},{"issue":"1","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"3703","DOI":"10.1038\/s41467-022-31535-6","article-title":"Network-based machine learning approach to predict immunotherapy response in cancer patients","volume":"13","author":"Kong","year":"2022","journal-title":"Nat Commun"},{"key":"2023032004363147800_","first-page":"2825","article-title":"Scikit-learn: machine learning in python","volume-title":"The Journal of Machine Learning Research","author":"Pedregosa","year":"2011"},{"issue":"8","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"100293","DOI":"10.1016\/j.patter.2021.100293","article-title":"Interpretable systems biomarkers predict response to immune-checkpoint inhibitors","volume":"2","author":"Lapuente-Santana","year":"2021","journal-title":"Patterns (N Y)"},{"issue":"10","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1038\/s41591-018-0136-1","article-title":"Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response","volume":"24","author":"Jiang","year":"2018","journal-title":"Nat Med"},{"issue":"5","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1158\/2326-6066.CIR-18-0436","article-title":"Tumor microenvironment characterization in gastric cancer identifies prognostic and immunotherapeutically relevant gene signatures","volume":"7","author":"Zeng","year":"2019","journal-title":"Cancer Immunol Res"},{"issue":"28","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"16339","DOI":"10.1073\/pnas.2002179117","article-title":"Functional network analysis reveals an immune tolerance mechanism in cancer","volume":"117","author":"Mathews","year":"2020","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"1","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"3938","DOI":"10.1038\/s41467-022-31055-3","article-title":"Recurrent somatic mutations as predictors of immunotherapy response","volume":"13","author":"Gajic","year":"2022","journal-title":"Nat Commun"},{"issue":"6","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.ccell.2021.04.014","article-title":"Conserved pan-cancer microenvironment subtypes predict response to immunotherapy","volume":"39","author":"Bagaev","year":"2021","journal-title":"Cancer Cell"},{"issue":"9","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"2487","DOI":"10.1016\/j.cell.2021.03.030","article-title":"Synthetic lethality-mediated precision oncology via the tumor transcriptome","volume":"184","author":"Lee","year":"2021","journal-title":"Cell"},{"issue":"4","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"934","DOI":"10.1016\/j.cell.2017.09.028","article-title":"Tumor and microenvironment evolution during immunotherapy with Nivolumab","volume":"171","author":"Riaz","year":"2017","journal-title":"Cell"},{"issue":"13","key":"2023032004363147800_","doi-asserted-by":"crossref","first-page":"3540","DOI":"10.1158\/0008-5472.CAN-16-3556","article-title":"Immune-related gene expression profiling after PD-1 blockade in non-small cell lung carcinoma, head and neck squamous cell carcinoma, and melanoma","volume":"77","author":"Prat","year":"2017","journal-title":"Cancer Res"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/2\/bbad023\/49559900\/bbad023.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/24\/2\/bbad023\/49559900\/bbad023.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T07:23:04Z","timestamp":1679296984000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbad023\/6995380"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,21]]},"references-count":31,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,3,19]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbad023","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,3]]},"published":{"date-parts":[[2023,1,21]]},"article-number":"bbad023"}}