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

TITLE=Integrated genomic analysis to identify druggable targets for pancreatic cancer

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.989077

DOI=10.3389/fonc.2022.989077

ISSN=2234-943X

ABSTRACT=According to National Comprehensive Cancer Network, the standard treatment for pancreatic cancer (PC) are gemcitabine and fluorouracil. It is usually combined with other chemotherapeutic agents. However, the drug resistance remains a huge challenge, leading to the ineffective of curing the PC. Therefore, we are eager to discover new treatments for PC by utilizing the 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 gene of PC. Five functional annotations were applied to prioritized the PC risk genes: Kyoto encyclopedia of genes and genomes; Biological process; Knock out mouse; Gene list automatically derived for you); and Gene omnibus dataset series. Each functional annotation was given a score, and genes with a score of ≥2 were labeled as biological PC risk genes. Further, DrugBank database was utilized to extract PC drug targets. To narrow down the most promising drugs for PC, we used CMap Touchstone analysis. Finally, ClinicalTrial.gov and literature review were used to screen the drug under clinical and preclinical investigation for PC. We extracted 895 PC-associated genes according to the cbBioPortal database and prioritized it using five functional annotations; 318 genes were found and assigned as biological-PC risk genes. Further, 216 genes were druggable according to the DrugBank database. To identify the promising drugs, CMap Touchstone analysis was applied which contain the profiles of gemcitabine in the MCF7 cell line as the standard PC treatment. Eventually, 13 drugs were selected as the promising PC candidate drugs prioritized. Among those 13 drugs, interestingly we found 8 drugs undergoing clinical trial; 2 drugs pre-clinical study; and 3 drugs with no evidence status. Importantly, we found midostaurin targeted PRKA and fulvestrant targeted ESR1 as promising candidate drugs for PC treatment based on pipeline genomic driven drug repurposing. In summary, our integrated analysis using a genomic information database demonstrated the viability data as a potential drug discovery resource. Furthermore, we propose two drugs (midostaurin and fulvestrant) as promising drug repurposing for PC treatment.