Prof. Serena Nik-Zainal

By Serena Nik-Zainal

Following a first-class degree in preclinical science, Serena obtained a medical degree from the University of Cambridge in December 2000, sponsored by Petroliam Nasional Berhad Malaysia (PETRONAS) and as a Fellow of the Cambridge Commonwealth Trust. She trained in general internal medicine before specializing in Clinical Genetics. She has been an Honorary Consultant in Clinical Genetics at Cambridge University Hospitals NHS Foundation Trust since February 2013.

Serena undertook a PhD at Wellcome Sanger Institute (WSI) exploring cancer using next-generation sequencing (NGS) technology in 2009. She was heavily involved in development of the whole genome sequencing (WGS) somatic variation pipeline and the development of an array of analytical principles that revealed the underlying abnormal biology of tumors – including generalized mutational signatures and imprints left by mutagenic processes that have occurred through cancer development, a novel phenomenon of localized hypermutation termed “kataegis”, as examples.

In a post-doctoral role and as an early investigator, she continued to explore large cancer datasets, leading production and analyses of the largest cohort of WGS cancers of a single tissue-type, of 560 breast cancers. She developed a team that began pursuing experimental validation of mutational signatures, dissecting mechanisms of mutagenesis using cellular models. Human induced pluripotent stem cells (hiPSC) were used to generate CRISPR-Cas9 knockouts of DNA repair genes and were systematically treated with a variety of environmental mutagens. She also recruited patients with DNA repair defects as part of the Insignia project until December 2018, in order to explore mutagenesis in normal cells prior to turning into cancer cells. The results from these endeavours serve as a reference resource of validated human mutational signatures.

As a Group Leader at Cambridge, Serena's team continues to advance the whole cancer genomics field through a combination of computational and experimental approaches, to ultimately create clinical applications.