WEHI PhD Completion Seminar hosted by Professor Tony Papenfuss

Samuel Lee

PhD Student – Papenfuss Laboratory, Bioinformatics division – Computational Biology Theme, WEHI

Computational approaches for modelling heterogeneity across complex biological phenotypes

 

Davis Auditorium

Join via SLIDO enter code #WEHIphdcompletion

Including Q&A session

Followed by refreshments in Tapestry Lounge

Variation within, and between, distinct types of cancer has come to be appreciated as a key factor that impacts both the differing responses of patients to treatment and to metastatic progression. This heterogeneity can best be appreciated via the outputs of large scale consortia efforts like The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopaedia (CCLE), which show remarkable diversity in the transcriptomic profiles of patient samples and in vitro cell lines respectively. Of course, this heterogeneity does not only affect translation in the cancer context—it can almost be considered a hallmark of complex cellular diseases. Recognition and clearance of targeted drug delivery strategies via the immune system is but one way this can occur.

During my PhD I focused on two main aims of research: the joint analysis of preclinical models and patient samples of solid cancers, and also computational approaches for understanding interactions between immune cells and nanoparticles. I’ll present work on three main projects, (1) a novel framework for predicting immune cell association with nanoparticles using protein interactions (2) benchmarking of computational methods for aligning patient tumour samples where I’ve been able to identify methods that are robust to technical factors that commonly plague cross dataset analyses, and (3) analysis of organotropism in the context of metastatic breast cancer where I’ve identified how organ-specific adaptation effects intratumoural heterogeneity.

Sam is a fourth year PhD student in the Bioinformatics division under the supervision of Professor Tony Papenfuss and Professor Melissa Davis. He’s also worked closely with Dr. Matthew Faria in the Quantitative Biology Group (UoM) and A/Prof Delphine Merino in the Tumour Progression and Heterogeneity Laboratory (ONJCRI) throughout his PhD. With a background in biomedical science and human genetics Sam’s research has focused on applying computational methods to large biological datasets, with an eye to how biological knowledge can be integrated in a principled manner to improve analyses.

All welcome!