Integrated genomic analysis to identify druggable targets for pancreatic cancer

Eko Mugiyanto; Wirawan Adikusuma; Lalu Muhammad Irham; Wan-Chen Huang; Wei-Chiao Chang; Chun-Nan Kuo

doi:10.3389/fonc.2022.989077

Integrated genomic analysis to identify druggable targets for pancreatic cancer

Front Oncol. 2022 Dec 1:12:989077. doi: 10.3389/fonc.2022.989077. eCollection 2022.

Authors

Eko Mugiyanto^{1

2}, Wirawan Adikusuma^{3

4}, Lalu Muhammad Irham⁵, Wan-Chen Huang⁶, Wei-Chiao Chang^{1

3

7

8}, Chun-Nan Kuo^{3

7}

Affiliations

¹ PhD Program in Clinical Drug Development of Herbal Medicine, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
² Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Pekajangan Pekalongan, Pekalongan, Indonesia.
³ Department of Clinical Pharmacy, School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
⁴ Department of Pharmacy, Faculty of Health Science, University of Muhammadiyah Mataram, Mataram, Indonesia.
⁵ Faculty of Pharmacy, University of Ahmad Dahlan, Yogyakarta, Indonesia.
⁶ Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan.
⁷ Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
⁸ Integrative Research Center for Critical Care, Department of Pharmacy, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.

Abstract

According to the National Comprehensive Cancer Network and the American Society of Clinical Oncology, the standard treatment for pancreatic cancer (PC) is gemcitabine and fluorouracil. Other chemotherapeutic agents have been widely combined. However, drug resistance remains a huge challenge, leading to the ineffectiveness of cancer therapy. Therefore, we are trying to discover new treatments for PC by utilizing genomic information to identify PC-associated genes as well as drug target genes for drug repurposing. Genomic information from a public database, the cBio Cancer Genomics Portal, was employed to retrieve the somatic mutation genes of PC. Five functional annotations were applied to prioritize the PC risk genes: Kyoto Encyclopedia of Genes and Genomes; biological process; knockout mouse; Gene List Automatically Derived For You; and Gene Expression Omnibus Dataset. DrugBank database was utilized to extract PC drug targets. To narrow down the most promising drugs for PC, CMap Touchstone analysis was applied. Finally, ClinicalTrials.gov and a literature review were used to screen the potential drugs under clinical and preclinical investigation. Here, we extracted 895 PC-associated genes according to the cBioPortal database and prioritized them by using five functional annotations; 318 genes were assigned as biological PC risk genes. Further, 216 genes were druggable according to the DrugBank database. CMap Touchstone analysis indicated 13 candidate drugs for PC. Among those 13 drugs, 8 drugs are in the clinical trials, 2 drugs were supported by the preclinical studies, and 3 drugs are with no evidence status for PC. Importantly, we found that midostaurin (targeted PRKA) and fulvestrant (targeted ESR1) are promising candidate drugs for PC treatment based on the genomic-driven drug repurposing pipelines. In short, integrated analysis using a genomic information database demonstrated the viability for drug repurposing. We proposed two drugs (midostaurin and fulvestrant) as promising drugs for PC.

Keywords: drug repurposing; fulvestrant; genomic; midostaurin; pancreatic cancer.