Supervisor View Full Details 2nd

• genetics, genomics and molecular biology
• cancer/oncology

• Pathology

• Oncology

I am a histopathologist and a molecular diagnostician. Over the last 15 years, the focus of my translational research and my diagnostic work has been to marry phenotype and genotype. Using molecular pathology approaches, I have described the clinical significance of stem cell markers such as CD133 [Mod Pathol. 2010 Mar;23(3):450-7] and SALL4 [N Engl J Med. 2013 Jun 13;368(24):2266 -76] in hepatocellular carcinoma (HCC). My laboratory generated the first evidence that the SALL4 protein, usually involved in cancer stem cell biology, was upregulated in HCC and had a strong negative prognostic value. This work went on to characterize a peptide that would inhibit the growth of HCC in a mouse model, validating SALL4 as a therapeutic target.
In general, my laboratories has contributed to understanding the clinical relevance of approximately 20 candidate biomarkers and disease mediators such as EphA2 (Clin Can Res 2015), TBX2 (Oncotarget 2014), CD44-v8 10 (Can Res 2014), Hydrogen Sulphide [FASEB J. 2005 Jul;19(9):1196-8.], FGFR4 (Cell Death Dis 2014), cell adhesion and chromatin remodeling genes [Nat Genet. 2012 May;44(5):570-4] and AXL (Clin Can Res 2014), representing one of the main efforts by a molecular pathologist, world-wide, in defining the clinical relevance of cancer biomarkers.

Conceptual Hypothesis – The link between the knowledge of the nature and function of cells, and their two- and three-dimensional spatial arrangement in cancer tissue samples, is vastly underutilized, under-resources and under-discovered because of the perception that it is a human, subjective, pattern-recognition exercise. We believe that through artificial Intelligence (AI) we will be able to read the complex rules of arrangements of cellular elements in vastly heterogeneous micro-environmental frameworks, and will be able to predict transcriptomic pathways, genomic profiles, diagnostic classifications and therapeutic outcomes. My group aims to create a comprehensive morpho-molecular description of tumour heterogeneity, using laser capture to map the tumour microenvironment onto tumour clonal evolution and using DNA sequencing, transcriptomics, immunochemistry/histology to describe the spatial relationships between cells. This will identify unequivocal in-silico correlates of molecular features related to tumour immunology, examining stromal & immune cell, heterogeneity of tumours and how this relates to tumour cell/clonal evolution.

Specifics – Our laboratory has developed QuPath, a new, flexible, extensible, open source software application for digital pathology. Designed to provide the tools needed by researchers and pathologists, QuPath has been downloaded > 3000 times and has a growing community of active users in academia and industry. QuPath was written to overcome the limitations of existing bioimage analysis applications, both open source and commercial, with regard to digital pathology.

Strategic interest - The proposed research will focus digital pathology approaches, in the context of an integromics framework, to understand the tumour ecology of a specific cancer. The cancer focus will be decided upon based on the candidate’s clinical interest.

This is an ideal project for a pathologist or an oncologist to enter cancer research through a broad range of techniques and technologies, and should equip the successful candidate for a long-term career in academic oncology and pathology.