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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug
Onat Kadioglu1, Faranak Bahramimehr1, Mona Dawood2
1Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany.
Abstract:
RNA-sequencing has been proposed as a valuable technique to develop individualized therapy concepts for cancer patients based on their tumor-specific mutational profiles. Here, we aimed to identify drugs and inhibitors in an individualized therapy-based drug repurposing approach focusing on missense mutations for 35 biopsies of cancer patients. The missense mutations belonged to 9 categories (ABC transporter, apoptosis, angiogenesis, cell cycle, DNA damage, kinase, protease, transcription factor, tumor suppressor). The highest percentages of missense mutations were observed in transcription factor genes. The mutational profiles of all 35 tumors were subjected to hierarchical heatmap clustering. All 7 leukemia biopsies clustered together and were separated from solid tumors. Based on these individual mutation profiles, two strategies for the identification of possible drug candidates were applied: Firstly, virtual screening of FDA-approved drugs based on the protein structures carrying particular missense mutations. Secondly, we mined the Drug Gene Interaction (DGI) database (https://www.dgidb.org/) to identify approved or experimental inhibitors for missense mutated proteins in our dataset of 35 tumors. In conclusion, our approach based on virtual drug screening of FDA-approved drugs and DGI-based inhibitor selection may provide new, individual treatment options for patients with otherwise refractory tumors that do not respond anymore to standard chemotherapy.
Insights
This study used RNA-sequencing to identify potential cancer drugs by analyzing missense mutations in patient tumors. The approach identified personalized treatment options for refractory cancers using virtual screening and drug databases.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Individualized therapy concepts for cancer patients can be developed using RNA-sequencing and tumor-specific mutational profiles.
- Missense mutations in cancer genes are key targets for drug discovery and repurposing.
Purpose of the Study:
- To identify potential drugs and inhibitors for 35 cancer patient biopsies using an individualized therapy approach.
- To focus on missense mutations across nine functional categories, including transcription factors, kinases, and cell cycle regulators.
Main Methods:
- RNA-sequencing was performed on 35 tumor biopsies.
- Hierarchical heatmap clustering was used to analyze mutational profiles, separating leukemia from solid tumors.
- Two drug identification strategies were employed: virtual screening of FDA-approved drugs and mining the Drug Gene Interaction database.
Main Results:
- The highest percentage of missense mutations were found in transcription factor genes.
- Leukemia biopsies formed a distinct cluster separate from solid tumors.
- The study identified potential drug candidates based on individual tumor mutation profiles.
Conclusions:
- The combined approach of virtual drug screening and Drug Gene Interaction database mining offers a novel strategy for personalized cancer treatment.
- This method may provide new therapeutic options for patients with refractory tumors unresponsive to standard chemotherapy.
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