2319P - CADSP: A web tool for comprehensive drug sensitivity analysis in pan-cancer

Background

Drug therapy is an essential component of cancer treatment. Accurate drug sensitivity analysis can help healthcare professionals determine the right drugs to use, leading to improved patient outcomes and quality of life. However, a lack of web-based tools with robust visualization and analysis capabilities for pan-cancer drug sensitivity remains a challenge.

Methods

To address this gap, we developed the Comprehensive Analysis of Drug Sensitivity in Pan-cancer (CADSP), a Shiny-based web tool. We collected oncology drug sensitivity-related data from large publicly available databases, including Gene Expression Omnibus (GEO), The Cancer Genome Atlas Program (TCGA), and Drug Sensitivity in Cancer (GDSC).

Results

The current version of CADSP includes transcriptomic data for over 29,000 samples, covering 44 cancer types, 288 drugs, and more than 9,000 gene perturbation data. Users can easily perform various tumor drug sensitivity analyses using CADSP. The tool provides numerous analysis and visualization methods, such as differential gene analysis, gene correlation analysis, pathway analysis, drug analysis, and gene perturbation analysis. Table: 2319P

Comparison of CADSP with other anti-tumor drug sensitivity analysis web server

Conclusions

CADSP greatly simplifies the exploration of primary and secondary drug resistance at the single-gene and pathway levels for physicians and researchers. By combining drug resistance data and gene perturbation data, CADSP also offers new avenues for discovering key genes that drive drug resistance. CADSP is available at https://smuonco.shinyapps.io/CADSP/.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

The Natural Science Foundation of Guangdong Province [2018A030313846, 2021A1515012593]; the Science and Technology Planning Project of Guangdong Province [2019A030317020]; the National Natural Science Foundation of China [81802257, 81871859, 81772457, 82172750 and 82172811]; and the Guangdong Basic and Applied Basic Research Foundation (Guangdong - Guangzhou Joint Funds) [2022A1515111212].

Disclosure

All authors have declared no conflicts of interest.