Associate member - Dangoor center for Personalized Medicine

Recent successes of targeted drugs on end stage cancer patients highlight the value of mutation-based biomarkers with high positive predictive value for drug response predictions. Since these mutations are observed in a wide panel of cancers, effort is being made to implement broad mutation screening to instruct the right drugs for each patient. Concurrent explosion of both sequencing depth and novel drug development (currently 500-800 novel targeted drugs) further motivate an increase in the throughput of such prospective diagnostic tool. However, many drugs that target a key etiological pathway in cancer, lack obvious markers of response to assist it’s appropriate administration. Such markers are not only in the interest of health funds, but also minimize patient morbidity. Although effective against melanoma patients, in breast and colon cancers PLX4032 is evaded, often through feedback mechanisms that increase expression of EGFR. This highlights the necessity of direct laboratory tests for patient-specific drug responses, and mechanisms of drug resistance.


To achieve this, this lab measures:


1. For each cancer sample (micro dissected cancer cells from FFPE archival material of cancer samples) and control tissue we measure:


a.     Key gene expression,


b.     Genome-wide Copy Number variation,


c.     Ultra-high-representation target sequencing of exons of cancer causing genes.


d.     Cancer driving translocations.


2. Empirical testing of candidate drug response in patient-specific living cancer tissue, growing in Xenografts.


3. Drug response is assessed both biochemically (PamGene phosphor-peptide profiling), as well as physiologically (FDG-PET-CT imaging).


4. Drug resistant cases are subjected to lentiviral high throughput shRNA screens for functional genomic drug-gene interactions. The screen identifies genes, which if inhibited, would sensitize the patient sample to existing regimens or modalities.


Using these novel approaches we hope to (1) improve the performance and validity of predictive disease markers; (2) Understand the mechanistic basis of disease markers; (3) Generate novel imaging/molecular imaging approaches for screening and 
management; (4) Identify and validate molecular targets for combination therapy, which would avoid drug resistance.


These approaches are explored in clinical context as well as preclinical service core, which would provide biomarkers to be described in the IND to the FDA as inclusion criteria before phase one begins, as well as explore combination therapies to improve efficacy, all in advance of the first human treatment, or with drugs that failed FDA NDA in the past, when they were not indicated via biomarkers of response. These technologies will be explored in advanced lethal cancer cases, where current treatment prognosis is poor, such as GBM, stage III serous papillary ovarian cancer, metastatic and drug resistant breast and colon cancers, lung cancer, or HCC.