A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening

Publication type:
Journal article
Metadata:
Autoren
  • Onat Kadioglu
  • Faranak Bahramimehr
  • Mona Dawood
  • Nuha Mahmoud
  • Mohamed Elbadawi
  • Xiaohua Lu
  • Yagmur Buelbuel
  • Jana Agnieszka Schulz
  • Lisa Kraemer
  • Marie-Kathrin Urschel
  • Zoe Kuenzli
  • Leila Abdulrahman
  • Fadwa Aboumaachar
  • Lajien Kadalo
  • Le Van Nguyen
  • Sara Shaidaei
  • Nawal Thaher
  • Kathrin Walter
  • Karolin Christiane Besler
  • Andreas Spuller
  • Markus Munder
  • Henry Johannes Greten
  • Thomas Efferth
Autoren-URL
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000955573500001&DestLinkType=FullRecord&DestApp=WOS_CPL
DOI
10.1016/j.compbiomed.2023.106781
eISSN
1879-0534
Externe Identifier
  • Clarivate Analytics Document Solution ID: A5MZ0
  • PubMed Identifier: 36931205
ISSN
0010-4825
Zeitschrift
COMPUTERS IN BIOLOGY AND MEDICINE
Schlüsselwörter
  • Cancer
  • Drug discovery
  • Drug repurposing
  • Mutation analysis
  • Personalized medicine
  • Precision medicine
  • Targeted chemotherapy
Artikelnummer
ARTN 106781
Datum der Veröffentlichung
2023
Status
Published
Titel
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening
Sub types
  • Article
Ausgabe der Zeitschrift
157

Data source: Web of Science (Lite)

Other metadata sources:
Autoren
  • Onat Kadioglu
  • Faranak Bahramimehr
  • Mona Dawood
  • Nuha Mahmoud
  • Mohamed Elbadawi
  • Xiaohua Lu
  • Yagmur Bülbül
  • Jana Agnieszka Schulz
  • Lisa Krämer
  • Marie-Kathrin Urschel
  • Zoe Künzli
  • Leila Abdulrahman
  • Fadwa Aboumaachar
  • Lajien Kadalo
  • Le Van Nguyen
  • Sara Shaidaei
  • Nawal Thaher
  • Kathrin Walter
  • Karolin Christiane Besler
  • Andreas Spuller
  • Markus Munder
  • Henry Johannes Greten
  • Thomas Efferth
DOI
10.1016/j.compbiomed.2023.106781
ISSN
0010-4825
Zeitschrift
Computers in Biology and Medicine
Sprache
en
Artikelnummer
106781
Paginierung
106781 - 106781
Datum der Veröffentlichung
2023
Status
Published
Herausgeber
Elsevier BV
Herausgeber URL
http://dx.doi.org/10.1016/j.compbiomed.2023.106781
Datum der Datenerfassung
2023
Titel
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening
Ausgabe der Zeitschrift
157

Data source: Crossref

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.
Addresses
  • Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Mainz, Germany.
Autoren
  • Onat Kadioglu
  • Faranak Bahramimehr
  • Mona Dawood
  • Nuha Mahmoud
  • Mohamed Elbadawi
  • Xiaohua Lu
  • Yagmur Bülbül
  • Jana Agnieszka Schulz
  • Lisa Krämer
  • Marie-Kathrin Urschel
  • Zoe Künzli
  • Leila Abdulrahman
  • Fadwa Aboumaachar
  • Lajien Kadalo
  • Le Van Nguyen
  • Sara Shaidaei
  • Nawal Thaher
  • Kathrin Walter
  • Karolin Christiane Besler
  • Andreas Spuller
  • Markus Munder
  • Henry Johannes Greten
  • Thomas Efferth
DOI
10.1016/j.compbiomed.2023.106781
eISSN
1879-0534
Externe Identifier
  • PubMed Identifier: 36931205
Funding acknowledgements
  • Johannes Gutenberg-Universität Mainz:
Open access
false
ISSN
0010-4825
Zeitschrift
Computers in biology and medicine
Schlüsselwörter
  • Humans
  • Neoplasms
  • Transcription Factors
  • Drug Evaluation, Preclinical
  • Early Detection of Cancer
  • Drug Repositioning
  • Transcriptome
Sprache
eng
Medium
Print-Electronic
Online publication date
2023
Paginierung
106781
Datum der Veröffentlichung
2023
Status
Published
Datum der Datenerfassung
2023
Titel
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
157

Data source: Europe PubMed Central

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.
Date of acceptance
2023
Autoren
  • Onat Kadioglu
  • Faranak Bahramimehr
  • Mona Dawood
  • Nuha Mahmoud
  • Mohamed Elbadawi
  • Xiaohua Lu
  • Yagmur Bülbül
  • Jana Agnieszka Schulz
  • Lisa Krämer
  • Marie-Kathrin Urschel
  • Zoe Künzli
  • Leila Abdulrahman
  • Fadwa Aboumaachar
  • Lajien Kadalo
  • Le Van Nguyen
  • Sara Shaidaei
  • Nawal Thaher
  • Kathrin Walter
  • Karolin Christiane Besler
  • Andreas Spuller
  • Markus Munder
  • Henry Johannes Greten
  • Thomas Efferth
Autoren-URL
https://www.ncbi.nlm.nih.gov/pubmed/36931205
DOI
10.1016/j.compbiomed.2023.106781
eISSN
1879-0534
Zeitschrift
Comput Biol Med
Schlüsselwörter
  • Cancer
  • Drug discovery
  • Drug repurposing
  • Mutation analysis
  • Personalized medicine
  • Precision medicine
  • Targeted chemotherapy
  • Humans
  • Drug Evaluation, Preclinical
  • Transcriptome
  • Drug Repositioning
  • Early Detection of Cancer
  • Neoplasms
  • Transcription Factors
Sprache
eng
Country
United States
Paginierung
106781
PII
S0010-4825(23)00246-9
Datum der Veröffentlichung
2023
Status
Published
Datum, an dem der Datensatz öffentlich gemacht wurde
2023
Titel
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.
Sub types
  • Journal Article
Ausgabe der Zeitschrift
157

Data source: PubMed

Autoren
  • Onat Kadioglu
  • Faranak Bahramimehr
  • Mona Dawood
  • Nuha Mahmoud
  • Mohamed Elbadawi
  • Xiaohua Lu
  • Yagmur Bülbül
  • Jana Agnieszka Schulz
  • Lisa Krämer
  • Marie-Kathrin Urschel
  • Zoe Künzli
  • Leila Abdulrahman
  • Fadwa Aboumaachar
  • Lajien Kadalo
  • Le Van Nguyen
  • Sara Shaidaei
  • Nawal Thaher
  • Kathrin Walter
  • Karolin Christiane Besler
  • Andreas Spuller
  • Markus Munder
  • Henry Johannes Greten
  • Thomas Efferth
Zeitschrift
Comput. Biol. Medicine
Paginierung
106781 - 106781
Datum der Veröffentlichung
2023
Titel
A drug repurposing approach for individualized cancer therapy based on transcriptome sequencing and virtual drug screening.
Ausgabe der Zeitschrift
157

Data source: DBLP

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