{"doi":"10.3390/ijms231810605","title":"High-Content Drug Discovery Targeting Molecular Bladder Cancer Subtypes","abstract":"Molecular subtypes of muscle-invasive bladder cancer (MIBC) display differential survival and drug sensitivities in clinical trials. To date, they have not been used as a paradigm for phenotypic drug discovery. This study aimed to discover novel subtype-stratified therapy approaches based on high-content screening (HCS) drug discovery. Transcriptome expression data of CCLE and BLA-40 cell lines were used for molecular subtype assignment in basal, luminal, and mesenchymal-like cell lines. Two independent HCSs, using focused compound libraries, were conducted to identify subtype-specific drug leads. We correlated lead drug sensitivity data with functional genomics, regulon analysis, and in-vitro drug response-based enrichment analysis. The basal MIBC subtype displayed sensitivity to HDAC and CHK inhibitors, while the luminal subtype was sensitive to MDM2 inhibitors. The mesenchymal-like cell lines were exclusively sensitive to the ITGAV inhibitor SB273005. The role of integrins within this mesenchymal-like MIBC subtype was confirmed via its regulon activity and gene essentiality based on CRISPR-Cas9 knock-out data. Patients with high ITGAV expression showed a significant decrease in the median overall survival. Phenotypic high-content drug screens based on bladder cancer cell lines provide rationales for novel stratified therapeutic approaches as a framework for further prospective validation in clinical trials.","journal":"International Journal of Molecular Sciences","year":2022,"id":278829,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8949,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":469869,"name":"Qiong Zhou","orcid":"0000-0002-8240-0440","position":1,"is_corresponding":false},{"id":292059,"name":"Joshua M. Abbott","orcid":"0000-0002-1897-3228","position":2,"is_corresponding":false},{"id":951400,"name":"Florus C. de Jong","orcid":"0000-0001-6853-5982","position":3,"is_corresponding":false},{"id":491596,"name":"Hector Esquer","orcid":"0000-0002-1911-1523","position":4,"is_corresponding":false},{"id":3027,"name":"James C. Costello","orcid":"0000-0003-3158-9682","position":5,"is_corresponding":false},{"id":71231,"name":"Dan Theodorescu","orcid":"0000-0002-8708-8206","position":6,"is_corresponding":false},{"id":469872,"name":"Daniel V. LaBarbera","orcid":"0000-0001-9460-3862","position":7,"is_corresponding":false},{"id":491599,"name":"Sébastien Rinaldetti","orcid":"0000-0003-1053-3831","position":0,"is_corresponding":true}],"reference_count":60,"raw_metadata":null,"created_at":"2026-07-19T00:28:47.357993Z","pmid":"36142576","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}