ShinyTHOR app: Shiny-built tumor high-throughput omics-based roadmap

Navarrete-Bencomo E.; Segura A.V.C.; Sevillano O.R.; Mayanga A.; Sono J.L.B.; Rojas C.A.O.; Carrasco A.G.M. · Bioinformatics Advances (2025) · DOI: 10.1093/bioadv/vbaf061

Resumen

Motivation: The Cancer Cell Line Encyclopedia (CCLE), launched in 2008, systematically organizes multi-omic and pharmacological data from over 1000 cancer cell lines with molecular dependency maps accessible through the DepMap tool. However, DepMap lacks tools for systematic comparison of mRNAs, miRNAs, proteins, and metabolites, as well as their links to drug responses and gene signatures. Extracting this data externally requires bioinformatics expertise, limiting access for wet-lab researchers. Results: We developed ShinyTHOR, a web app for intuitive access to multi-omic (transcriptomic, metabolomic, methylomic, proteomic, and miRNomic) and drug-related data. It integrates datasets from CCLE, miRTarBase, circInteractome, and the Genomics of Drug Sensitivity in Cancer. ShinyTHOR includes six modules: (1) identifying top/bottom ten cell lines by marker expression or drug IC50, (2) single-sample Gene Set Enrichment Analysis (ssGSEA), (3) multi-analyte expression evaluation, (4) miRNA-target interactions across cancer types, (5) miRNA impact on mRNA translation via protein levels, and (6) circRNA/miRNA modulation. To validate its utility, we applied ShinyTHOR to a gastric cancer prognosis study (GES7). Availability and implementation: ShinyTHOR is freely accessible for non-commercial use at https://alexismurillo.shinyapps.io/ShinyThor, with source code available at https://github.com/Murillo22/ShinyThor. © The Author(s) 2025. Published by Oxford University Press.

Instituciones: Universidad Científica del Sur; Universidad de San Martín de Porres