Principal Investigator, Dr Serena Nik-Zainal’s Josef Steiner Award is for her successful application to accelerate holistic cancer genome interpretation towards the clinic with collaborators Dr Paul Calleja and Dr Ignacio Medina. The Dr. Josef Steiner Cancer Research Prize 2019, originally also known as the “Nobel Prize for Cancer Research”, goes to Prof. Dr. Serena Nik-Zainal from the Department of Medical Genetics, University of Cambridge . Thanks to her research, mutations in cancer tumours can be analysed using new bioinformatic methods, which enables new approaches to targeted therapies. The prize was awarded on Friday, 18 October, at the University of Bern. Dr Nik-Zainal presented her work under the title “Accelerating holistic cancer genome interpretation towards the clinic”.
The Dr. Josef Steiner Cancer Research Award
In its efforts to promote cancer research efficiently and sustainably in the spirit of the founder, each Dr. Josef Steiner Cancer Research Award is given to an excellent research project of a young investigator in this field. The Swiss Dr. Peter Cerrutti was honored as the first prize winner in 1986. Since then, numerous excellent researchers from Europe, the US and Australia have been awarded the Dr. Josef Steiner Cancer Research Award. It has been issued every other year since 1998. The winning project is supported for a period of four years with a sum of 1,000,000 Swiss francs. It is the award of a private foundation with the biggest cash prize of its kind in the world and was originally referred to as the “Nobel Prize for Cancer Research”. The winning project is selected following a multi-stage process in which the scientific quality, the originality, the qualification of the project authors and the feasibility of the proposed studies are all taken into consideration.
Today, the Dr. Josef Steiner Cancer Foundation, which is comprised of physiologists from the Universities of Bern, Geneva and Zürich and chaired by the member from Bern, is awarding the Dr. Josef Steiner Cancer Research Award 2019 to Prof. Serena Nik-Zainal. The bioinformatician from the Department of Medical Genetics and the MRC Cancer Unit at the University of Cambridge is receiving the award in recognition of her groundbreaking research in developing new methods in the field of bioinformatics for the clinically-relevant classification of tumors. It is the first time that the Dr. Josef Steiner Cancer Research Award goes in full to a women scientist.
Stephan Rohr, Co-Director of the Institute for Physiology and president of the foundation’s board, is handed over the Dr. Josef Steiner Cancer Research Award on Friday, October 18, on the occasion of a ceremony at the University of Bern. He had this to say about the winner: “New genetic analysis methods produce a huge flood of data. Interpreting that data without the aid of a suitable algorithms is inconceivable. Serena Nik-Zainal has made groundbreaking progress in the field of cancerous genetic mutations in recent years by developing such algorithms. The award enables her to expand the database and to make the analyses accessible for non-specialists in the future. We’re convinced that her approach will advance cancer research significantly.”
Making big data accessible for cancer research
Every cancerous tumor has many thousands of mutations in its genome. New technologies in reading the human genome, called sequencing, allows scientists today to study all these mutations in a single experiment. Serena Nik-Zainal first developed her expertise in analysis and interpretation of whole cancer genome sequencing, investigating the frequency, distribution and patterns of all the mutations that arise in cancers, called mutational signatures, in a large number of tumors using computational approaches. Her team has pioneered ways of reading and interpreting whole human cancer genomes, and they have developed algorithms to report abnormalities first, in breast cancer tumors, but now across all tumour-types. It turns out than nearly one in five breast cancer patients has particular gene defects that could make them respond to more specific therapies. With her project, Nik-Zainal plans to introduce these algorithms to clinical practice by establishing user-friendly interfaces for clinicians and scientists, with the ultimate goal of making cancer diagnosis and prognosis easier. Nik-Zainal will use the Dr. Josef Steiner Cancer Research Award to build comprehensive computational infrastructure that will allow more cancer patients to be efficiently examined, using her bioinformatic analysis methods, making it possible to better understand the development of mutations in individual cancer patients and thus facilitate new therapeutic options for the successful treatment of patients.
Dr Nik-Zainal said, ‘The rate-limiting step in cancer genomics today is not the ability to perform sequencing. It is the expertise in performing downstream analysis and making a clinically-useful interpretation, that remains the hurdle between genomic technology and the clinical context.
Our research efforts began with showing that the totality of mutagenesis from large cohorts of whole genome sequenced tumours could reveal mutational signatures, imprints left by mutagenic DNA damage and repair processes that have occurred through cancer development. Subsequently, our team focused on experimentally validating these analytical concepts in cellular model systems. We examined mechanisms of mutagenesis related to DNA repair defects and of environmental mutagens. The powerful combination of computational analytics and experimental insights helped to drive the development of clinical computational tools to interpret whole cancer genomes more effectively.
At the Clinical School, University of Cambridge, the Josef Steiner Award will help us enhance translation of our expertise and develop novel, clinically meaningful algorithmic tools. We seek to consolidate our current knowledge into infrastructure that is appropriate for the future. We are building a more automated foundation, that can be referred back to at any point, and that will scale with more data coming. It needs to be more user-friendly for the next generation of clinicians and scientists to explore and be suitable for advanced data analytics. We will be able to focus on asking novel biological and clinical questions of these large datasets and ultimately, accelerate making clinically-relevant progress.’