Globally there is a growing use of high-throughput sequencing approaches in cancer research, which is mainly due to the decrease in the cost of sequencing.
Generating genomic data is no longer the limiting factor – increasingly, the challenge sits with the analytical approach. It is therefore vital to understand the limitations of sequencing and bioinformatic methods to improve the use of DNA and RNA sequence data for cancer research and clinical care of cancer patients.
Peter Tsai, who works on the Genomics Aotearoa Genomics Translational Oncology project, is passionate about applying and developing different genomic and bioinformatic methods to better understand the cancer genome to improve patient treatment.
Currently 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, including pancreatic neuroendocrine tumours, small intestine neuroendocrine tumours and melanoma.
It is hoped that this can identify biomarkers that can be used in clinical diagnosis or treatment to improve patient care.
About Peter
Peter completed his BSc (bioinformatics specialisation), MSc in Bioinformatics at the University of Auckland. Later, he joined Bioinformatics Institute at the University of Auckland as a research programmer before starting his PhD with Professor Cris Print.
During his PhD, Peter investigated the genomic landscape of pancreatic neuroendocrine tumours using multi-omic data and identified distinct genomic features associated with patient outcomes. He also investigated different bioinformatics approaches' limitations in quantitating TP53 transcript isoforms using both simulated and cell line RNA-seq data.
He also worked as a support scientist for Biomatters during his PhD, providing scientific and analytical support for analysing sequencing datasets.
Peter's area of expertise:
• Cancer genomics
• Bioinformatics
• Evolutionary biology
Read more about Genomic Translational Oncology here