Mouse xenograft models for elucidating drug resistance mechanisms

Divergence of treatment responses to chemotherapy exists across patients (often with unknown underlying mechanisms), with some patients exhibiting worsened outcome upon treatment. Genomic approaches (such as microarray profiling and whole genome sequencing) hold promise for transforming cancer treatment, particularly, in tailoring drug regimen to specific patients. Nevertheless, formulating effective personalized treatment via surveying the mutational landscape remains difficult, due to current deficiencies in predicting drug sensitivity from genotype. Xenografts, both indirect (via cell line) and direct (from primary tumours), are good physiologic models of cancers. Their utility in informing cancer treatment, however, is constrained by high cost of generating and maintaining genetically modified animals, and the paucity of tissue samples from biopsies. Advent of high throughput biomolecular profiling tools finally enable reading out the expansive molecular fingerprints that encode observed phenotypes in xenografts. Using pheochromocytoma (an adrenal medulla cancer) as example, this short essay provides a broad overview of the scientific and clinical possibilities offered by xenograft models for understanding resistance mechanisms to particular chemotherapeutic regimens, and upon identification of the putative mutations, confirms their functional roles as either oncogenes or tumour suppressors. Additionally, workflow involved in generating a predictive platform, based on non-invasive blood biomarkers, for informing drug treatment options is discussed. Known as an integrated genomic classifier, combination of physiological response of direct xenografts to drug treatment and bioinformatics enabled correlation of blood biomarkers to observed phenotype at cellular and animal levels, and provides the biological basis for predicting patients’ prognosis without invasive biopsy of solid tumours. Elucidation of drug resistance mechanisms entails: (i) recapitulating in vivo tumour behaviour using cell lines derived from primary tumour; (ii) identification of aetiological