Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing.

TitleChemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing.
Publication TypeJournal Article
Year of Publication2022
AuthorsPham T-H, Qiu Y, Liu J, Zimmer S, O'Neill E, Xie L, Zhang P
JournalPatterns (N Y)
Date Published2022 Apr 08

Chemical-induced gene expression profiles provide critical information of chemicals in a biological system, thus offering new opportunities for drug discovery. Despite their success, large-scale analysis leveraging gene expressions is limited by time and cost. Although several methods for predicting gene expressions were proposed, they only focused on imputation and classification settings, which have limited applications to real-world scenarios of drug discovery. Therefore, a chemical-induced gene expression ranking (CIGER) framework is proposed to target a more realistic but more challenging setting in which overall rankings in gene expression profiles induced by de novo chemicals are predicted. The experimental results show that CIGER significantly outperforms existing methods in both ranking and classification metrics. Furthermore, a drug screening pipeline based on CIGER is proposed to identify potential treatments of drug-resistant pancreatic cancer. Our predictions have been validated by experiments, thereby showing the effectiveness of CIGER for phenotypic compound screening of precision medicine.

Alternate JournalPatterns (N Y)
PubMed ID35465231
PubMed Central IDPMC9023899
Grant ListR01 GM122845 / GM / NIGMS NIH HHS / United States
R01 GM141279 / GM / NIGMS NIH HHS / United States
R01 LM013771 / LM / NLM NIH HHS / United States