{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T11:32:20Z","timestamp":1777375940150,"version":"3.51.4"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100012547","name":"Guangxi Natural Science Foundation","doi-asserted-by":"publisher","award":["2022GXNSFAA035513"],"award-info":[{"award-number":["2022GXNSFAA035513"]}],"id":[{"id":"10.13039\/100012547","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Clinical Specialty Construction Project"},{"name":"Guangxi Key Clinical Specialty Construction Project"},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072124"],"award-info":[{"award-number":["62072124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Guangxi","award":["2023JJG170006"],"award-info":[{"award-number":["2023JJG170006"]}]},{"name":"CAAI-Huawei MindSpore Open Fund","award":["CAAIXSJLJJ-2022-022A"],"award-info":[{"award-number":["CAAIXSJLJJ-2022-022A"]}]},{"name":"Natural Science and Technology Innovation Development Foundation of Guangxi University","award":["2022BZRC009"],"award-info":[{"award-number":["2022BZRC009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30\u201350% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.<\/jats:p>","DOI":"10.1093\/bib\/bbae080","type":"journal-article","created":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T09:33:29Z","timestamp":1711964009000},"source":"Crossref","is-referenced-by-count":15,"title":["IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability"],"prefix":"10.1093","volume":"25","author":[{"given":"Zhanyu","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]},{"given":"Haibo","family":"Liao","sequence":"additional","affiliation":[{"name":"School of computer , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"},{"name":"Guangxi University , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]},{"given":"Liuliu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5506-8913","authenticated-orcid":false,"given":"Qingfeng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of computer , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"},{"name":"Guangxi University , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5839-7504","authenticated-orcid":false,"given":"Wei","family":"Lan","sequence":"additional","affiliation":[{"name":"School of computer , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"},{"name":"Guangxi University , Electronic and Information, , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8187-3676","authenticated-orcid":false,"given":"Shikang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University , Nanning, Guangxi Zhuang Autonomous Region 530021 , China"}]}],"member":"286","published-online":{"date-parts":[[2024,3,31]]},"reference":[{"key":"2024041917521237000_ref1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"2024041917521237000_ref2","doi-asserted-by":"crossref","first-page":"340","DOI":"10.6004\/jnccn.2023.0020","article-title":"NCCN guidelines\u00ae insights: non-small cell lung cancer, version 2.2023","volume":"21","author":"Ettinger","year":"2023","journal-title":"J Natl Compr Canc Netw"},{"key":"2024041917521237000_ref3","doi-asserted-by":"crossref","first-page":"7","DOI":"10.3322\/caac.21708","article-title":"Cancer statistics, 2022","volume":"72","author":"Siegel","year":"2022","journal-title":"CA Cancer J Clin"},{"key":"2024041917521237000_ref4","doi-asserted-by":"crossref","first-page":"1592","DOI":"10.1038\/s41467-022-29230-7","article-title":"Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression","volume":"13","author":"Yoo","year":"2022","journal-title":"Nat Commun"},{"key":"2024041917521237000_ref5","doi-asserted-by":"crossref","first-page":"e51","DOI":"10.1158\/0008-5472.CAN-17-0369","article-title":"Explore, visualize, and analyze functional cancer proteomic data using the cancer proteome atlas","volume":"77","author":"Li","year":"2017","journal-title":"Cancer Res"},{"key":"2024041917521237000_ref6","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.cell.2018.02.052","article-title":"An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics","volume":"173","author":"Liu","year":"2018","journal-title":"Cell"},{"key":"2024041917521237000_ref7","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/bs.adgen.2015.11.004","article-title":"Integrative analysis of multi-omics data for discovery and functional studies of complex human diseases","volume":"93","author":"Sun","year":"2016","journal-title":"Adv Genet"},{"key":"2024041917521237000_ref8","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1186\/s13059-017-1215-1","article-title":"Multi-omics approaches to disease","volume":"18","author":"Hasin","year":"2017","journal-title":"Genome Biol"},{"key":"2024041917521237000_ref9","doi-asserted-by":"crossref","first-page":"107739","DOI":"10.1016\/j.biotechadv.2021.107739","article-title":"Using machine learning approaches for multi-omics data analysis: a review","volume":"49","author":"Reel","year":"2021","journal-title":"Biotechnol Adv"},{"key":"2024041917521237000_ref10","doi-asserted-by":"crossref","first-page":"107277","DOI":"10.1016\/j.compbiolchem.2020.107277","article-title":"Incorporating deep learning and multi-omics autoencoding for analysis of lung adenocarcinoma prognostication","volume":"87","author":"Lee","year":"2020","journal-title":"Comput Biol Chem"},{"key":"2024041917521237000_ref11","article-title":"Predicting deep learning based multi-omics parallel integration survival subtypes in lung cancer using reverse phase protein array data","volume":"10","author":"Takahashi","journal-title":"Biomolecules"},{"key":"2024041917521237000_ref12","article-title":"Interpretation of deep learning in genomics and epigenomics","volume":"22","author":"Talukder","journal-title":"Brief Bioinform"},{"key":"2024041917521237000_ref13","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1038\/s41576-022-00532-2","article-title":"Obtaining genetics insights from deep learning via explainable artificial intelligence","volume":"24","author":"Novakovsky","year":"2023","journal-title":"Nat Rev Genet"},{"key":"2024041917521237000_ref14","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics13111932","article-title":"Explainable AI for Retinoblastoma Diagnosis: Interpreting Deep Learning Models with LIME and SHAP","volume-title":"Diagnostics (Basel)","author":"Aldughayfiq"},{"key":"2024041917521237000_ref15","article-title":"A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs","volume":"2020","author":"Mitra","journal-title":"Annu Int Conf IEEE Eng Med Biol Soc"},{"key":"2024041917521237000_ref16","article-title":"Grad-CAM helps interpret the deep learning models trained to classify multiple sclerosis types using clinical brain magnetic resonance imaging","volume":"353","author":"Zhang","journal-title":"J Neurosci Methods"},{"key":"2024041917521237000_ref17","article-title":"Interpretable meta-learning of multi-omics data for survival analysis and pathway enrichment","volume":"39","author":"Cho","journal-title":"Bioinformatics"},{"key":"2024041917521237000_ref18","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/nmeth.4627","article-title":"Using deep learning to model the hierarchical structure and function of a cell","volume":"15","author":"Ma","year":"2018","journal-title":"Nat Methods"},{"key":"2024041917521237000_ref19","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1038\/s41586-021-03922-4","article-title":"Biologically informed deep neural network for prostate cancer discovery","volume":"598","author":"Elmarakeby","year":"2021","journal-title":"Nature"},{"key":"2024041917521237000_ref20","doi-asserted-by":"crossref","first-page":"i443","DOI":"10.1093\/bioinformatics\/btab285","article-title":"PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma","volume":"37","author":"Oh","year":"2021","journal-title":"Bioinformatics"},{"key":"2024041917521237000_ref21","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":"2024041917521237000_ref22","doi-asserted-by":"crossref","first-page":"D687","DOI":"10.1093\/nar\/gkab1028","article-title":"The Reactome pathway knowledgebase 2022","volume":"50","author":"Gillespie","year":"2022","journal-title":"Nucleic Acids Res"},{"key":"2024041917521237000_ref23","article-title":"UCSCXenaShiny: an R\/CRAN package for interactive analysis of UCSC Xena data","volume":"38","author":"Wang","journal-title":"Bioinformatics"},{"key":"2024041917521237000_ref24","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1038\/ng.2764","article-title":"The cancer genome atlas pan-cancer analysis project","volume":"45","author":"Weinstein","year":"2013","journal-title":"Nat Genet"},{"key":"2024041917521237000_ref25","doi-asserted-by":"crossref","first-page":"143","DOI":"10.11613\/BM.2013.018","article-title":"The chi-square test of independence","volume":"23","author":"McHugh","year":"2013","journal-title":"Biochem Med (Zagreb)"},{"key":"2024041917521237000_ref26","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1186\/s12943-022-01651-4","article-title":"The reversion of DNA methylation-induced miRNA silence via biomimetic nanoparticles-mediated gene delivery for efficient lung adenocarcinoma therapy","volume":"21","author":"Liang","year":"2022","journal-title":"Mol Cancer"},{"key":"2024041917521237000_ref27","doi-asserted-by":"crossref","first-page":"e12813","DOI":"10.1111\/jpi.12813","article-title":"Melatonin may suppress lung adenocarcinoma progression via regulation of the circular noncoding RNA hsa_circ_0017109\/miR-135b-3p\/TOX3 axis","volume":"73","author":"Wang","year":"2022","journal-title":"J Pineal Res"},{"key":"2024041917521237000_ref28","doi-asserted-by":"crossref","first-page":"4340","DOI":"10.1158\/0008-5472.CAN-22-1289","article-title":"MNX1-AS1 promotes phase separation of IGF2BP1 to drive c-Myc-mediated cell-cycle progression and proliferation in lung cancer","volume":"82","author":"Zhu","year":"2022","journal-title":"Cancer Res"},{"key":"2024041917521237000_ref29","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1186\/s13046-023-02638-9","article-title":"METTL3 promotes chemoresistance in small cell lung cancer by inducing mitophagy","volume":"42","author":"Sun","year":"2023","journal-title":"J Exp Clin Cancer Res"},{"key":"2024041917521237000_ref30","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1038\/s41586-023-05880-5","article-title":"STING inhibits the reactivation of dormant metastasis in lung adenocarcinoma","volume":"616","author":"Hu","year":"2023","journal-title":"Nature"},{"key":"2024041917521237000_ref31","doi-asserted-by":"crossref","first-page":"3944","DOI":"10.7150\/ijbs.70889","article-title":"CircFAT1 promotes lung adenocarcinoma progression by sequestering miR-7 from repressing IRS2-ERK-mediated CCND1 expression","volume":"18","author":"Peng","year":"2022","journal-title":"Int J Biol Sci"},{"key":"2024041917521237000_ref32","doi-asserted-by":"crossref","first-page":"3917","DOI":"10.1158\/0008-5472.CAN-22-0432","article-title":"High-resolution profiling of lung adenocarcinoma identifies expression subtypes with specific biomarkers and clinically relevant vulnerabilities","volume":"82","author":"Roh","year":"2022","journal-title":"Cancer Res"},{"key":"2024041917521237000_ref33","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.canlet.2021.10.001","article-title":"SERPINE2\/PN-1 regulates the DNA damage response and radioresistance by activating ATM in lung cancer","volume":"524","author":"Zhang","year":"2022","journal-title":"Cancer Lett"},{"key":"2024041917521237000_ref34","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1038\/s41420-022-01152-9","article-title":"KCNK3 inhibits proliferation and glucose metabolism of lung adenocarcinoma via activation of AMPK-TXNIP pathway","volume":"8","author":"Lin","year":"2022","journal-title":"Cell Death Discov"},{"key":"2024041917521237000_ref35","doi-asserted-by":"crossref","first-page":"e266","DOI":"10.1016\/j.jtho.2019.07.021","article-title":"Coexistence of a novel PRKCB-ALK, EML4-ALK double-fusion in a lung adenocarcinoma patient and response to Crizotinib","volume":"14","author":"Luo","year":"2019","journal-title":"J Thorac Oncol"},{"key":"2024041917521237000_ref36","doi-asserted-by":"crossref","first-page":"109462","DOI":"10.1016\/j.cellsig.2019.109462","article-title":"A novel long non-coding RNA LINC00355 promotes proliferation of lung adenocarcinoma cells by down-regulating miR-195 and up-regulating the expression of CCNE1","volume":"66","author":"Liang","year":"2020","journal-title":"Cell Signal"},{"key":"2024041917521237000_ref37","doi-asserted-by":"crossref","first-page":"2791","DOI":"10.1200\/JCO.20.03307","article-title":"Clinicopathologic features and response to therapy of NRG1 fusion-driven lung cancers: the eNRGy1 global Multicenter registry","volume":"39","author":"Drilon","year":"2021","journal-title":"J Clin Oncol"},{"key":"2024041917521237000_ref38","doi-asserted-by":"crossref","first-page":"1693","DOI":"10.1016\/j.annonc.2020.08.2335","article-title":"NRG1 fusion-driven tumors: biology, detection, and the therapeutic role of afatinib and other ErbB-targeting agents","volume":"31","author":"Laskin","year":"2020","journal-title":"Ann Oncol"},{"key":"2024041917521237000_ref39","doi-asserted-by":"crossref","first-page":"1800986","DOI":"10.1183\/13993003.00986-2018","article-title":"Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning","volume":"53","author":"Wang","year":"2019","journal-title":"Eur Respir J"},{"key":"2024041917521237000_ref40","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1016\/j.jtho.2020.04.014","article-title":"Effective treatment of lung adenocarcinoma Harboring EGFR-activating mutation, T790M, and cis-C797S triple mutations by Brigatinib and Cetuximab combination therapy","volume":"15","author":"Wang","year":"2020","journal-title":"J Thorac Oncol"},{"key":"2024041917521237000_ref41","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1038\/s41591-021-01450-2","article-title":"Toward personalized treatment approaches for non-small-cell lung cancer","volume":"27","author":"Wang","year":"2021","journal-title":"Nat Med"},{"key":"2024041917521237000_ref42","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41576-020-0265-5","article-title":"Integrating genetic and non-genetic determinants of cancer evolution by single-cell multi-omics","volume":"22","author":"Nam","year":"2021","journal-title":"Nat Rev Genet"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/3\/bbae080\/57255600\/bbae080.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/3\/bbae080\/57255600\/bbae080.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,19]],"date-time":"2024-04-19T17:52:41Z","timestamp":1713549161000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae080\/7638265"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,27]]},"references-count":42,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,3,27]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae080","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,5]]},"published":{"date-parts":[[2024,3,27]]},"article-number":"bbae080"}}