{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T11:08:52Z","timestamp":1778411332831,"version":"3.51.4"},"reference-count":65,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Technol Cancer Res Treat"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Urological cancers, including prostate, renal, and bladder cancers, present significant challenges to human health, particularly for patients in advanced stages due to limited targeted therapy options, high drug resistance, and poor prognosis. This study seeks to systematically identify new therapeutic targets by integrating multi-omics data and elucidating their molecular mechanisms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Our methodology involved a multi-phase integrative approach to identify therapeutic targets in urological cancers. We conducted a transcriptome-wide Mendelian randomization (TWMR) analysis using the druggable genome. We used cis-expression quantitative trait loci (cis-eQTL) data from the eQTLGen consortium (N = 31,684) as exposures and GWAS summary statistics from FinnGen R11 and Open GWAS as outcomes. Significant genes were identified through Bonferroni correction, followed by colocalization analysis to assess shared genetic effects between risk SNPs and gene expression. Summary-data-based MR (SMR) analysis was carried out using eQTLGen data. Validation of potential targets included drug prediction using DSigDB and molecular docking with AutoDock Vina. Furthermore, we integrated DNA methylation quantitative trait loci (mQTL) data from GoDMC to explore methylation-mediated regulatory mechanisms through mediation MR analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Our transcriptome-wide MR analysis identified 11 high-confidence therapeutic targets in urological cancers: 4 in prostate cancer (BNIP2, KAT5, MMP24, SIK2), 2 in renal cancer (GRB10, GPR17), and 5 in bladder cancer (CELSR1, GPS1, PROC, GSTM1, KLC3). Molecular docking confirmed favorable interactions between these targets and existing drugs. Epigenetic analyses showed DNA methylation-mediated regulation of key targets: PROC (cg09747827) and CELSR1 (cg00784671) in bladder cancer, and SIK2 (cg11344533) in prostate cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study integrates multi-omics data to identify 11 high-confidence therapeutic targets in urological cancers and is the first to elucidate DNA methylation-mediated regulatory mechanisms for targets like PROC and SIK2. The findings introduce a \u201cDNA methylation-gene expression\u201d axis-based strategy for combined targeted-epigenetic therapy, providing crucial evidence for optimizing precision treatment in urological oncology.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/15330338261449014","type":"journal-article","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T02:25:37Z","timestamp":1778207137000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Druggable Genome-Wide Mendelian Randomization Identifies Therapeutic Targets and DNA Methylation-Mediated Regulation in Urological Malignancies"],"prefix":"10.1177","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-4631-9302","authenticated-orcid":false,"given":"Taoen","family":"Li","sequence":"first","affiliation":[{"name":"Southern Medical University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Wei","sequence":"additional","affiliation":[{"name":"Southern Medical University"},{"name":"Guangdong Provincial People\u2019s Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,5,7]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.15585\/mmwr.mm6941a1"},{"key":"e_1_3_6_3_2","first-page":"9","article-title":"Overcoming drug resistance in castrate-resistant prostate cancer: current mechanisms and emerging therapeutic approaches","volume":"8","author":"Khorasanchi A","year":"2025","unstructured":"Khorasanchi A, Hong F, Yang Y, et al. 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