{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T09:58:24Z","timestamp":1787997504179,"version":"build-2784847793"},"reference-count":42,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T00:00:00Z","timestamp":1757030400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Haihe Laboratory of Cell Ecosystem Innovation Fund","award":["HH24KYZX0017"],"award-info":[{"award-number":["HH24KYZX0017"]}]},{"name":"Haihe Laboratory of Cell Ecosystem Innovation Fund","award":["23KPHDRC00360"],"award-info":[{"award-number":["23KPHDRC00360"]}]},{"name":"Haihe Laboratory of Cell Ecosystem Innovation Fund","award":["TJWJ2023QN064"],"award-info":[{"award-number":["TJWJ2023QN064"]}]},{"name":"Haihe Laboratory of Cell Ecosystem Innovation Fund","award":["TJWI2024QN063"],"award-info":[{"award-number":["TJWI2024QN063"]}]},{"name":"Tianjin Science and Technology Program","award":["HH24KYZX0017"],"award-info":[{"award-number":["HH24KYZX0017"]}]},{"name":"Tianjin Science and Technology Program","award":["23KPHDRC00360"],"award-info":[{"award-number":["23KPHDRC00360"]}]},{"name":"Tianjin Science and Technology Program","award":["TJWJ2023QN064"],"award-info":[{"award-number":["TJWJ2023QN064"]}]},{"name":"Tianjin Science and Technology Program","award":["TJWI2024QN063"],"award-info":[{"award-number":["TJWI2024QN063"]}]},{"name":"Tianjin Health and Medical Science and Technology Project","award":["HH24KYZX0017"],"award-info":[{"award-number":["HH24KYZX0017"]}]},{"name":"Tianjin Health and Medical Science and Technology Project","award":["23KPHDRC00360"],"award-info":[{"award-number":["23KPHDRC00360"]}]},{"name":"Tianjin Health and Medical Science and Technology Project","award":["TJWJ2023QN064"],"award-info":[{"award-number":["TJWJ2023QN064"]}]},{"name":"Tianjin Health and Medical Science and Technology Project","award":["TJWI2024QN063"],"award-info":[{"award-number":["TJWI2024QN063"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: The circadian rhythm regulates important functions in the body, such as metabolism, the cell cycle, DNA repair, and immune balance. Disruption of this rhythm can contribute to the development of cancer. Circadian rhythm genes (CRGs) are attracting attention for their connection to various cancers. However, their roles in LUAD are not yet well understood. Additionally, our knowledge of how they function at both the bulk tissue and single-cell levels is limited. This gap hinders a complete understanding of how CRGs impact the development and outcomes of LUAD. Methods: We selected 554 CRGs from public databases. We then obtained transcriptome data from TCGA and GEO. A total of 101 machine learning algorithm combinations were tested using 10 algorithms and 10-fold cross-validation. The best-performing model was based on Stepwise Cox regression and SuperPC. This model was validated with additional datasets. We also examined the relationships between CRGs, immune features, tumor mutation burden (TMB), and the response to immunotherapy. Drug sensitivity was also assessed. Single-cell data identified the cell types with active CRGs. Next, we performed qRT-PCR and other basic experiments to validate the expression of ARNTL2 in LUAD tissues and cell lines. The results indicated that ARNTL2 may play a key role in lung adenocarcinoma. Results: The CRG-based model clearly distinguished LUAD patients based on their risk. High-risk patients exhibited low immune activity, high TMB, and poor predicted responses to immunotherapy. Single-cell data revealed strong CRG signals in epithelial and fibroblast cells. These cell groups also displayed different communication patterns. Laboratory experiments showed that ARNTL2 was highly expressed in LUAD. It promoted cell growth, movement, and invasion. This suggests that ARNTL2 may play a role in promoting cancer. Conclusions: This study developed a machine learning model based on CRGs. It can predict survival and immune status in LUAD patients. The research also identified ARNTL2 as a key gene that may contribute to cancer progression. These findings highlight the significance of the circadian rhythm in LUAD and provide new perspectives for diagnosis and treatment.<\/jats:p>","DOI":"10.3390\/cancers17172911","type":"journal-article","created":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T07:46:17Z","timestamp":1757058377000},"page":"2911","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Application of Single-Cell Sequencing and Machine Learning in Prognosis and Immune Profiling of Lung Adenocarcinoma: Exploring Disease Mechanisms and Treatment Strategies Based on Circadian Rhythm Gene Signatures"],"prefix":"10.3390","volume":"17","author":[{"given":"Qiuqiao","family":"Mu","sequence":"first","affiliation":[{"name":"Clinical School of Thoracic, Tianjin Medical University, Tianjin 300070, China"},{"name":"Department of Thoracic Surgery, Tianjin Chest Hospital, Tianjin 300222, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Tianjin Chest Hospital, Tianjin 300222, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Tianjin Chest Hospital, Tianjin 300222, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Tan","sequence":"additional","affiliation":[{"name":"Qingdao Hospital, University of Health and Rehabilitation Sciences, Qingdao 266113, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9139-195X","authenticated-orcid":false,"given":"Xin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Tianjin Chest Hospital, Tianjin 300222, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6602-357X","authenticated-orcid":false,"given":"Daqiang","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, Tianjin Chest Hospital, Tianjin 300222, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,5]]},"reference":[{"key":"ref_1","first-page":"10","article-title":"Cancer statistics, 2025","volume":"75","author":"Siegel","year":"2025","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","first-page":"209","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":"ref_3","doi-asserted-by":"crossref","unstructured":"(2014). Comprehensive molecular profiling of lung adenocarcinoma. Nature, 511, 543\u2013550.","DOI":"10.1038\/nature13385"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"220","DOI":"10.21037\/tlcr.2018.05.06","article-title":"The epidemiology of lung cancer","volume":"7","author":"Wu","year":"2018","journal-title":"Transl. Lung Cancer Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1038\/s41586-024-07113-9","article-title":"An atlas of epithelial cell states and plasticity in lung adenocarcinoma","volume":"627","author":"Han","year":"2024","journal-title":"Nature"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7928","DOI":"10.1038\/s41467-024-52139-2","article-title":"Genomic and immune heterogeneity of multiple synchronous lung adenocarcinoma at different developmental stages","volume":"15","author":"Zhao","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/s41698-024-00548-3","article-title":"Immune microenvironment heterogeneity of concurrent adenocarcinoma and squamous cell carcinoma in multiple primary lung cancers","volume":"8","author":"Zhang","year":"2024","journal-title":"NPJ Precis. Oncol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.1038\/s12276-021-00681-0","article-title":"Roles of circadian clocks in cancer pathogenesis and treatment","volume":"53","author":"Lee","year":"2021","journal-title":"Exp. Mol. Med."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Qu, M. (2023). Molecular crosstalk between circadian clock and cancer and therapeutic implications. Front. Nutr., 10.","DOI":"10.3389\/fnut.2023.1143001"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Vainshelbaum, N.M., Salmina, K., Gerashchenko, B.I., Lazovska, M., Zayakin, P., Cragg, M.S., Pjanova, D., and Erenpreisa, J. (2022). Role of the Circadian Clock \u201cDeath-Loop\u201d in the DNA Damage Response Underpinning Cancer Treatment Resistance. Cells, 11.","DOI":"10.1101\/2022.01.14.476363"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"324","DOI":"10.1016\/j.cmet.2016.07.001","article-title":"Circadian Rhythm Disruption Promotes Lung Tumorigenesis","volume":"24","author":"Papagiannakopoulos","year":"2016","journal-title":"Cell Metab."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3748","DOI":"10.21037\/jtd-22-570","article-title":"High-risk early-stage lung adenocarcinoma patients are identified by an immune-related circadian clock gene signature","volume":"14","author":"Wang","year":"2022","journal-title":"J. Thorac. Dis."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1038\/s41573-020-00109-w","article-title":"Circadian rhythm as a therapeutic target","volume":"20","author":"Ruan","year":"2021","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2540","DOI":"10.1038\/s41467-021-22801-0","article-title":"Single-cell profiling of tumor heterogeneity and the microenvironment in advanced non-small cell lung cancer","volume":"12","author":"Wu","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1038\/s41588-024-01997-z","article-title":"Dissecting tumor transcriptional heterogeneity from single-cell RNA-seq data by generalized binary covariance decomposition","volume":"57","author":"Liu","year":"2025","journal-title":"Nat. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3684","DOI":"10.1038\/s41467-021-24010-1","article-title":"Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma","volume":"12","author":"Ho","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1038\/s41392-022-01150-4","article-title":"Single-cell transcriptomic profiling reveals the tumor heterogeneity of small-cell lung cancer","volume":"7","author":"Tian","year":"2022","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6748","DOI":"10.1038\/s41388-021-02054-3","article-title":"Single-cell RNA sequencing reveals distinct tumor microenvironmental patterns in lung adenocarcinoma","volume":"40","author":"Bischoff","year":"2021","journal-title":"Oncogene"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e71","DOI":"10.1093\/nar\/gkv1507","article-title":"TCGAbiolinks: An R\/Bioconductor package for integrative analysis of TCGA data","volume":"44","author":"Colaprico","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Parmigiani, G., and Johnson, W.E. (2020). ComBat-seq: Batch effect adjustment for RNA-seq count data. NAR Genom. Bioinform., 2.","DOI":"10.1093\/nargab\/lqaa078"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Love, M.I., Huber, W., and Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol., 15.","DOI":"10.1186\/s13059-014-0550-8"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.cels.2015.12.004","article-title":"The Molecular Signatures Database (MSigDB) hallmark gene set collection","volume":"1","author":"Liberzon","year":"2015","journal-title":"Cell Syst."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1093\/bioinformatics\/btr260","article-title":"Molecular signatures database (MSigDB) 3.0","volume":"27","author":"Liberzon","year":"2011","journal-title":"Bioinformatics"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1038\/s41467-022-28421-6","article-title":"Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer","volume":"13","author":"Liu","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"W509","DOI":"10.1093\/nar\/gkaa407","article-title":"TIMER2.0 for analysis of tumor-infiltrating immune cells","volume":"48","author":"Li","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1038\/nmeth.3337","article-title":"Robust enumeration of cell subsets from tissue expression profiles","volume":"12","author":"Newman","year":"2015","journal-title":"Nat. Methods"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1186\/s13073-019-0638-6","article-title":"Molecular and pharmacological modulators of the tumor immune contexture revealed by deconvolution of RNA-seq data","volume":"11","author":"Finotello","year":"2019","journal-title":"Genome Med."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1186\/s13073-020-00783-w","article-title":"The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression","volume":"12","author":"Petitprez","year":"2020","journal-title":"Genome Med."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Aran, D., Hu, Z., and Butte, A.J. (2017). xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol., 18.","DOI":"10.1186\/s13059-017-1349-1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e26476","DOI":"10.7554\/eLife.26476","article-title":"Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data","volume":"6","author":"Racle","year":"2017","journal-title":"eLife"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2847","DOI":"10.1093\/bioinformatics\/btw313","article-title":"Complex heatmaps reveal patterns and correlations in multidimensional genomic data","volume":"32","author":"Gu","year":"2016","journal-title":"Bioinformatics"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1038\/nature08460","article-title":"Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1","volume":"462","author":"Barbie","year":"2009","journal-title":"Nature"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1038\/ncomms3612","article-title":"Inferring tumour purity and stromal and immune cell admixture from expression data","volume":"4","author":"Yoshihara","year":"2013","journal-title":"Nat. Commun."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive Integration of Single-Cell Data","volume":"177","author":"Stuart","year":"2019","journal-title":"Cell"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","article-title":"Inference and analysis of cell-cell communication using CellChat","volume":"12","author":"Jin","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Shao, X., Liao, J., Li, C., Lu, X., Cheng, J., and Fan, X. (2021). CellTalkDB: A manually curated database of ligand-receptor interactions in humans and mice. Brief. Bioinform., 22.","DOI":"10.1093\/bib\/bbaa269"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1038\/nature12213","article-title":"Mutational heterogeneity in cancer and the search for new cancer-associated genes","volume":"499","author":"Lawrence","year":"2013","journal-title":"Nature"},{"key":"ref_41","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."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Munteanu, C., Turti, S., Achim, L., Muresan, R., Souca, M., Prifti, E., M\u00e2rza, S.M., and Papuc, I. (2024). The Relationship between Circadian Rhythm and Cancer Disease. Int. J. Mol. Sci., 25.","DOI":"10.3390\/ijms25115846"}],"container-title":["Cancers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6694\/17\/17\/2911\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:39:51Z","timestamp":1760035191000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6694\/17\/17\/2911"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,5]]},"references-count":42,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["cancers17172911"],"URL":"https:\/\/doi.org\/10.3390\/cancers17172911","relation":{},"ISSN":["2072-6694"],"issn-type":[{"value":"2072-6694","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,5]]}}}