Abstract 2319P
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
CADSP | canSAR | CellMiner | GSCALite | PharmacoDB | DRESIS | |
Dataset | TCGA, GDSC, GEO(including NCI-60), GPSAdb | TCGA, ICGC | GDSC, CCLE, CTRP, NCI-60 | GDSC, TCGA, GTEx | NCI-60, GDSC, PRISM, CCLE, gCSI | DrugBank, CCNSC, TTD |
Sample | ∼29,000 | ∼25,000 | 1,400 | 23,594 | 1,757 | - |
Cancer types | 44 | 26 | 60 | 33 | 30 | 125 |
Analysis module | ①Differential expression gene analysis ②Correlation analysis ③Pathway analysis(GSEA, ssGSEA, Pathview) ④Drug analysis ⑤Genetic perturbations | Genomic data analysis | Correlation analysis | ①Genomic data analysis ②Pathway activity ③miRNA network ④Drug sensitivity | ①Genomic data analysis ②Correlation analysis ③Drug sensitivity | Resistance mechanisms analysis |
Parameters customization | ✓ | ✕ | ✕ | ✕ | ✕ | ✕ |
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.
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