A new exploration: characterization of the differentiation trajectory of prostate cancer cells

A new exploration: characterization of the differentiation trajectory of prostate cancer cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A new exploration: characterization of the differentiation trajectory of prostate cancer cells Jiyu Yang, Changyou Wang, Xiao Ma, Jie Li, Haoran Yuan, Renzhen Tan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4499641/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Prostate cancer is one of the most common malignancies in men, and in-depth study of its gene expression patterns is essential to understand the formation and progression of prostate cancer. Although the heterogeneity of prostate cancer cells has been explored by single-cell transcriptomics, the different differentiation states from normal epithelial cells might lead to confusion about heterogeneous tumor characteristics. In this study, we analyzed the heterogeneity of prostate cancer tumor subsets in detail using single-cell data from the GEO database by means of cell annotation and enrichment analysis, with a special focus on matching the differentiation status of normal epithelial cells. We found that there are unique or shared tumor signatures among these subpopulations, providing important clues for insight into the development of prostate cancer. Patients and methods: We searched the GEO public database (GSE193337) for prostate cancer single-cell data and conducted rigorous data quality control. The cells were annotated using Single R and Azimuth tools, and malignant epithelial cells were screened for subsequent heterogeneous clustering. Using an anchor-site integration approach, we identified normal epithelial cells that matched each tumor subset at the same TSNE neighbor plot location as a control group for subsequent studies. Pseudo-temporal trajectory analysis, functional enrichment analysis, cell communication analysis, and transcription factor regulatory network analysis were performed on the obtained tumor heterogeneous subsets. We further conducted immune infiltration analysis and pan-cancer analysis of transcription factors with aberrant transcriptional activity. Results: We found that prostate cancer cells exhibited enrichment of the androgen receptor pathway in the early stages of differentiation (malignant2, 3 subsets). All three subpopulations showed down-regulation of the enrichment of P53 and the apoptotic pathway, which might be associated with apoptotic evasion. Cell communication analysis showed that malignant2 and 3 subsets showed more active extracellular matrix signaling communication and higher levels of MHC-related molecular expression compared to normal epithelial cells matched to their respective subpopulations. All three tumor subsets expressed higher levels of EGFR, ERBB2, interferon receptor, MIF, and cell adhesion-related signals. Through transcription factor regulatory network analysis, we observed that the transcriptional activity of YY1, NKX3-1 and EHF in these subpopulations was higher than that of normal epithelial cells at the same differentiation stage, especially YY1 might act as an upstream regulator of MIF signaling pathway. ATF3 is a key upstream transcriptional regulator of differentially expressed genes in the P53 and apoptotic pathways. Immune infiltration analysis showed that the expression of YY1, EHF, NKX3-1 and ATF3 was significantly associated with the infiltration of immune cells in prostate cancer. Pan-cancer analysis showed that YY1 and NKX3-1 were significantly overexpressed in prostate cancer, while ATF3 was significantly underexpressed. Among them, the hazard ratio of YY1 in overall survival of prostate cancer was 11.9 ( P< 0.05), and the risk of disease-free survival and progression-free survival of ATF3 in prostate cancer was 0.791 and 0.88 ( P< 0.05), respectively. Conclusion: Through a detailed analysis of prostate cancer tumor subsets, particularly those matching the differentiation status of normal epithelial cells, we have identified unique or shared tumor characteristics among them. Enrichment analysis has unveiled key pathways associated with the three tumor subsets, offering valuable insights into the development of prostate cancer. The results of immune infiltration and pan-cancer analysis underscore the significance of YY1 and ATF3 in prostate cancer, correlating their abnormal expression with patient survival. This opens up new avenues for future research, holding the promise of providing more precise strategies for the personalized treatment of prostate cancer. prostate cancer single-cell transcriptomics heterogeneity transcription factors cell communication Full Text Additional Declarations No competing interests reported. Supplementary Files supplementary.zip Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 22 Jul, 2024 Reviews received at journal 21 Jul, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviews received at journal 10 Jul, 2024 Reviewers agreed at journal 05 Jul, 2024 Reviewers invited by journal 23 Jun, 2024 Editor assigned by journal 30 May, 2024 Submission checks completed at journal 30 May, 2024 First submitted to journal 29 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4499641","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313033130,"identity":"339eb402-2e25-419a-96b7-4671100f5eaa","order_by":0,"name":"Jiyu Yang","email":"","orcid":"","institution":"Yanbian University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jiyu","middleName":"","lastName":"Yang","suffix":""},{"id":313033132,"identity":"c53b4722-b5d8-44c0-9033-bc802f1d576e","order_by":1,"name":"Changyou Wang","email":"","orcid":"","institution":"Yanbian 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Although the heterogeneity of prostate cancer cells has been explored by single-cell transcriptomics, the different differentiation states from normal epithelial cells might lead to confusion about heterogeneous tumor characteristics. In this study, we analyzed the heterogeneity of prostate cancer tumor subsets in detail using single-cell data from the GEO database by means of cell annotation and enrichment analysis, with a special focus on matching the differentiation status of normal epithelial cells. We found that there are unique or shared tumor signatures among these subpopulations, providing important clues for insight into the development of prostate cancer.\u003c/p\u003e\n\u003cp\u003ePatients and methods: We searched the GEO public database (GSE193337) for prostate cancer single-cell data and conducted rigorous data quality control. The cells were annotated using Single R and Azimuth tools, and malignant epithelial cells were screened for subsequent heterogeneous clustering. Using an anchor-site integration approach, we identified normal epithelial cells that matched each tumor subset at the same TSNE neighbor plot location as a control group for subsequent studies. Pseudo-temporal trajectory analysis, functional enrichment analysis, cell communication analysis, and transcription factor regulatory network analysis were performed on the obtained tumor heterogeneous subsets. We further conducted immune infiltration analysis and pan-cancer analysis of transcription factors with aberrant transcriptional activity.\u003c/p\u003e\n\u003cp\u003eResults: We found that prostate cancer cells exhibited enrichment of the androgen receptor pathway in the early stages of differentiation (malignant2, 3 subsets). All three subpopulations showed down-regulation of the enrichment of P53 and the apoptotic pathway, which might be associated with apoptotic evasion. Cell communication analysis showed that malignant2 and 3 subsets showed more active extracellular matrix signaling communication and higher levels of MHC-related molecular expression compared to normal epithelial cells matched to their respective subpopulations. All three tumor subsets expressed higher levels of EGFR, ERBB2, interferon receptor, MIF, and cell adhesion-related signals. Through transcription factor regulatory network analysis, we observed that the transcriptional activity of YY1, NKX3-1 and EHF in these subpopulations was higher than that of normal epithelial cells at the same differentiation stage, especially YY1 might act as an upstream regulator of MIF signaling pathway. ATF3 is a key upstream transcriptional regulator of differentially expressed genes in the P53 and apoptotic pathways. Immune infiltration analysis showed that the expression of YY1, EHF, NKX3-1 and ATF3 was significantly associated with the infiltration of immune cells in prostate cancer. Pan-cancer analysis showed that YY1 and NKX3-1 were significantly overexpressed in prostate cancer, while ATF3 was significantly underexpressed. Among them, the hazard ratio of YY1 in overall survival of prostate cancer was 11.9 (\u003cem\u003eP\u0026lt;\u003c/em\u003e0.05), and the risk of disease-free survival and progression-free survival of ATF3 in prostate cancer was 0.791 and 0.88 (\u003cem\u003eP\u0026lt;\u003c/em\u003e0.05), respectively.\u003c/p\u003e\n\u003cp\u003eConclusion: Through a detailed analysis of prostate cancer tumor subsets, particularly those matching the differentiation status of normal epithelial cells, we have identified unique or shared tumor characteristics among them. Enrichment analysis has unveiled key pathways associated with the three tumor subsets, offering valuable insights into the development of prostate cancer. The results of immune infiltration and pan-cancer analysis underscore the significance of YY1 and ATF3 in prostate cancer, correlating their abnormal expression with patient survival. This opens up new avenues for future research, holding the promise of providing more precise strategies for the personalized treatment of prostate cancer.\u003c/p\u003e","manuscriptTitle":"A new exploration: characterization of the differentiation trajectory of prostate cancer cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-12 13:52:55","doi":"10.21203/rs.3.rs-4499641/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-22T16:50:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-21T19:29:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36925323135725923878794415255898820094","date":"2024-07-15T16:51:43+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-10T05:58:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260277133129383352621460628169358647781","date":"2024-07-05T17:50:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-23T18:01:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-30T08:10:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-30T08:09:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2024-05-30T01:28:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bb597d30-3fcb-42ad-a3ef-16eb99a2f7ab","owner":[],"postedDate":"June 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-09-02T13:19:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-12 13:52:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4499641","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4499641","identity":"rs-4499641","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}