Bioinformatics and computational approaches for analyzing patient-derived disease models in cancer research
Research output: Contribution to journal › Review article › peer-review
Colleges, School and Institutes
Patient-derived organoids (PDO) and patient-derived xenografts (PDX) continue to emerge as important preclinical platforms for investigations into the molecular landscape of cancer. While the advantages and disadvantage of these models have been described in detail, this review focuses in particular on the bioinformatics and state-of-the art techniques that accompany preclinical model development. We discuss the strength and limitations of currently used technologies, particularly 'omics profiling and bioinformatics analyses, in addressing the 'efficacy' of preclinical models, both for tumour characterization as well as their use in identifying potential therapeutics. We select pancreatic ductal adenocarcinoma (PDAC) as a case study to highlight the state of the art of the field, and address new avenues for improved bioinformatics characterization of preclinical models.
|Number of pages||6|
|Journal||Computational and Structural Biotechnology Journal|
|Publication status||Published - 5 Feb 2020|
- xenograft, organoid, disease model, bioinformatics, computational biology