Our research

While collaborating on genome-scale characterization of different tumor entities, the lab is focused on following topics:

Comprehensive molecular understanding of renal cell carcinoma

Renal cell carcinoma (RCC) is the most common form of kidney tumor. RCC has different subtypes with clear cell (ccRCC; conventional) subtype being the most frequently diagnosed one affecting 75-80% of RCCs. The incidence of RCC is increasing worldwide, and clinical management is challenged by significant heterogeneity in patient outcome due to the lack of robust biological markers for routine clinical use. Furthermore, it is essential to identify novel therapies as RCCs are resistant to conventional therapies, such as chemotherapy.

We use cutting-edge genomic technologies, including single-cell and spatial omics to identify biomarkers and therapeutic targets for RCCs. While, our initial focus in ccRCC is on establishing biomarkers for prognosis and identifying therapeutic targets, our research in other and rare RCCs is concentrated on precise diagnosis and defining genomic drivers of those tumors. Our research in the field of RCC is supported by access to unique cohorts and datasets including the McGill/MUHC RCC biobank, and our extensive collaboration network across the globe.

Systems level understanding of complex disorders through integrating single-cell and spatial omics

Single-cell transcriptomic analysis has opened new avenues to investigate molecular underpinnings of human disorders at a ‘systems level’ by capturing functional status of single cells, from different lineages, that cohabit in the same environment, and how they interact to drive disease. Nevertheless, the currently available technologies provide only a partial view of disease mechanisms due to the challenges related to tissue preparation to obtain high quality samples, the lack of the unbiased single cell proteomics approaches. This is especially challenging for immune-driven diseases and cancer, where the tissue composition is dramatically altered by immune cell infiltration and changes in the micro-environment. We adapt and apply state state-of-the-art spatial profiling technology and methods, together with innovative data analysis tools, to map cell-cell communications that are active in diseased tissues. We seek to deliver functional maps of cell-cell circuits in diseases by integrating the single-cell profiles with spatially-resolved landscapes of transcriptome and proteome to understand complex disorders at a systems level.

Investigating intra-tumoral heterogeneity and its contribution to tumor progression

Approaches to stratifying risk or tailoring therapy for individual cancer patients based on the molecular profile of their tumor biopsy are complicated by the existence of genetic heterogeneity (representing distinct populations of cancer cells with different sets of mutations; subclones) both within and across tumors. Furthermore, across tumor sites, genomes of disseminated cancer cells may have similarities at the onset of metastatic disease, but substantial changes in the genetic composition occur spatially and over time, supporting the suggestion that the expansion of aggressive driver clone(s) and the emergence of relevant subclones correlate with development of incurable disease and potential therapeutic resistance. Our lab has optimized protocols of NGS on minutes amount of fragmented DNA (e.g. cell-free DNA) as well as on DNA isolated from Formalin-fixed, paraffin-embedded (FFPE) samples providing an opportunity to analyze archived primary tumors of patients affected with metastatic or recurrent disease. We investigate the heterogeneous clonal composition of primary and metastatic tumors in order to study clonal evolution in cancer metastasis. Furthermore, we expand our analyses to include dynamics of cell-free tumor DNA (ctDNA) to facilitate clinical applications of our findings through non-invasive liquid biopsy approaches.