Precision medicine based on drug repositioning capable of gene expression profile reversal of individual malignant cells in pancreatic adenocarcinoma

• Grant number: 24/06595-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2024
• End date: May 31, 2025
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Luiz Antonio Lupi Júnior
• Grantee: Felipe Rosa
• Host Institution: Pró-Reitoria de Pesquisa e Pós-Graduação. Universidade do Oeste Paulista (UNOESTE). Presidente Prudente , SP, Brazil

Abstract

Pancreatic cancer is characterized as a fatal condition and one of the most aggressive and lethal malignancies, with 495,773 new cases anticipated worldwide and 466,003 resultant deaths, establishing a death-to-new-case ratio of 94%. Pancreatic ductal adenocarcinoma (PDAC) accounts for over 90% of these cases, exhibiting a five-year survival rate ranging from 2% to 9% across various regions and nations. The carcinogenesis of PDAC is marked by the accumulation of genetic alterations, leading to the activation of oncogenes or loss of function in tumor suppressor genes, including KRAS, CDKN2A, TP53, and SMAD4, which are critical for its initiation and persistence. The molecular mechanisms in PDAC are exceedingly complex at the cellular, genomic, epigenomic, and metabolic levels, making its diagnosis and treatment exceptionally challenging. The lack of substantial progress in clinical treatment can be attributed to the current inability to develop effective therapies, with standard treatments still consisting of surgical resection and cytotoxic therapies. In this context, single-cell RNA sequencing (scRNA-seq) data analysis and drug repositioning appear as promising tools, as they facilitate an understanding of the molecular complexity of pancreatic cancer to seek more effective therapies. scRNA-seq analysis allows for an intricate view of both intra- and intertumoral cellular heterogeneity, as well as stromal and immunological interactions, which contribute to tumoral malignancy and treatment response. Meanwhile, the drug repositioning strategy enables the exploration of new therapeutic indications for existing drugs. Leveraged on scRNA-seq data, this strategy affords the prediction of drugs that specifically target neoplastic cells and further promotes the development of precision medicine by enabling the identification of patient-specific tumoral profiles. This work aims to identify potential therapeutic targets for drug repositioning in PDAC based on the reversal of gene expression in individual malignant cells. For this purpose, publicly available scRNA-seq data from untreated human PDAC tumor tissue samples will be reanalyzed using the Seurat and CopyCat packages (R v.4.2.1). Cell types will be classified through their marker genes, followed by the acquisition of the gene expression signature and the list of differentially expressed genes (DEGs) in neoplastic cells compared to normal pancreatic ductal cells. Utilizing these data, the OCTAD (Open Cancer Therapeutic Discovery) platform will be employed to identify approved drugs with high potential to reverse the gene expression signature of PDAC. The findings will be validated in silico using the latest version of DepMap (Cancer Dependency Map). The application of scRNA-seq analysis in PDAC to drug repositioning holds the potential to identify more effective therapeutic strategies in the short term, including the development of personalized protocols, contributing to the reduction of the high mortality rates associated with the disease.