Pancreas Cancer Precision Treatment Using Avatar Mice from a Bioinformatics Perspective

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related death among solid malignancies. Unfortunately, PDAC lethality has not substantially decreased over the past 20 years. This aggressiveness is related to the genomic complexity and heterogeneity of PDAC, but also to the absence of an effective screening for the detection of early-stage tumors and a lack of efficient therapeutic options. Therefore, there is an urgent need to improve the arsenal of anti-PDAC drugs for an effective treatment of these patients. Patient-derived xenograft (PDX) mouse models represent a promising strategy to personalize PDAC treatment, offering a bench testing of candidate treatments and helping to select empirical treatments in PDAC patients with no therapeutic targets. Moreover, bioinformatics-based approaches have the potential to offer systematic insights into PDAC etiology predicting putatively actionable tumor-specific genomic alterations, identifying novel biomarkers and generating disease-associated gene expression signatures. This review focuses on recent efforts to individualize PDAC treatments using PDX models. Additionally, we discuss the current understanding of the PDAC genomic landscape and the putative druggable targets derived from mutational studies. PDAC molecular subclassifications and gene expression profiling studies are reviewed as well. Finally, latest bioinformatics methodologies based on somatic variant detection and prioritization, in silico drug response prediction, and drug repositioning to improve the treatment of advanced PDAC tumors are also covered.

Personalized RNA Medicine for Pancreatic Cancer

“…In this study, through the utilization of PDO as a rapid screen for TPN-21, we show for the first time the potential of personalized models for RNA-based precision medicine therapy in PDAC. By working with patient avatars, we have shown the potential to harness the ability of PDO and PDX models to predict clinical outcomes of patients and thus align preclinical work to patient response to TPN-21 therapy, a key goal in personalized medicine (41). Our work reveals that for PDAC, miR-21 is both a companion diagnostic and the therapeutic target, a theranostic.…”

Graph analytics for phenome-genome associations inference

“…Several databases covering different types of supporting evidence of our predictions were employed. PanDrugs (Perales-Patón et al Public Health Genomics. 2017) (build of April 2017) is a computational method to prioritize therapies by considering the biological relevance of altered genes in cancer, their therapeutic vulnerability and drugs clinical application.…”

New era for pancreatic endoscopic ultrasound: From imaging to molecular pathology of pancreatic cancer

“…PDAC aggressiveness is related to its genomic instability and heterogeneity. Patient-derived xenograft (PDX) mouse models, also known as “avatar models”, may represent a promising tool to personalize pancreatic cancer treatments[55]. The construction of PDX models from surgical specimens is extremely limited for PDAC patients, as only 10%-15% of them present with localized resectable tumors[56].…”