International research consortium to tackle tumour drug resistance using single-cell sequencing – Innovita Research

International research consortium to tackle tumour drug resistance using single-cell sequencing

An international consortium of academic and industrial leaders in the field of cancer research, including researchers at the Wellcome Sanger Institute, has announced the launch of a new research program called “PERSIST-SEQ”.

PERSIST-SEQ intends to provide the cancer research community with a new gold standard workflow for single-cell sequencing by developing and validating best practices, as well as generating and analysing high-quality data.

DNA processing in a genomics research lab. Photo credit: National Cancer Institute

The project aims to empower the scientific community to unravel drug resistance and develop smarter therapeutic strategies to better treat cancer and prevent resistance. PERSIST-SEQ is a five-year public-private partnership, which is funded by the Innovative Medicines Initiative (IMI), and led by the Oncode Institute and AstraZeneca, with the Wellcome Sanger Institute as one of the collaborators.

Cancer takes nearly 10 million lives each year worldwide*, 90 per cent of which result from untreatable cancer relapse occurring after initially effective treatment**. Therapeutic resistance is one of the primary causes of cancer death and is clinically difficult to predict, prevent or treat. Although resistance has been studied extensively in the last decades, there is no comprehensive understanding of its underlying mechanisms, nor how they differ between cancer types or therapies.

A better understanding of these mechanisms can contribute to better patient stratification, the development of effective drug strategies targeting the resistance mechanisms as well as improved cancer treatment strategies. Moreover, resistance is a major industrial challenge since it causes failure in the drug discovery and development process. Therapeutic resistance is largely unpredictable and difficult to model. Therefore, better tools are needed to identify or predict resistance mechanisms. These tools would, in turn, decrease the costs and risks associated with cancer drug development significantly.

Source: Sanger Institute