Detecting missing structural variants in an individual’s tumour of uncertain origin

Abstract

Structural Variants (SV) are frequent in cancer and are increasing recognised as potent drivers of tumour development, progression and resistance to therapy. In this talk I will discuss our work in progress using Oxford Nanopore adaptive sampling technologies to identify SV in the massively aneuploid tumours of a single patient. Adaptive sampling was able to both confirm SV previously found using short read and 10x linked read technologies and identify new SVs that other technologies were unable to detect. Based on our experience, we expect Oxford Nanopore adaptive sampling technologies to grow in importance for SV analysis in cancer.

Biography

Peter has a PhD in cancer bioinformatics and is passionate about applying and developing different genomic and bioinformatic methods to better understand the cancer genome to improve patient treatment. Currently, working as a Research Fellow in the Faculty of Medical and Health Science at the University of Auckland, he works in collaboration with several different researchers, clinicians and oncologists to study the genomic landscape of different cancer types, this includes pancreatic neuroendocrine tumours, small intestine neuroendocrine tumours and melanoma. It is hoped that this work can identify biomarkers for use in clinical diagnosis to improve patient care.