Skip to main content

Article Category

News

Article available in the folowing languages:

Identifying the key to better cancer therapies

How can scientists accurately predict how different cancer cells will respond to various drugs? According to a new study, the answer lies not in the mutations of individual genes that drive the cancer, but in the “mutational signature” left on the entire cancer genome.

Health

In cancer precision medicine today, doctors use genetic information from their patients’ tumours to plan and monitor treatment strategies. By studying a tumour’s DNA, they can identify the mutations and other genetic changes that drive the patients’ cancer and therefore predict how the tumour will respond to a specific drug. However, such predictive markers are currently quite rare. In fact, specific drugs have yet to be developed for a large number of mutated driver genes (genes whose mutations cause cancer progression). Moreover, tumour response to a drug varies widely from one patient to another, and – as reported in a ‘EurekAlert!’ news release – “such variability is often not linked to driver gene mutations.” With this in mind, researchers supported by the EU-funded HYPER-INSIGHT, DECIDER and PROBIST projects sought to find out if so-called mutational signatures would be useful markers of cancer cell response to various drugs. A mutational signature is the imprint left on the cancer genome of any DNA damage and repair that has occurred during a tumour’s formation. Mutational signatures do not originate from driver genes, but instead reflect the mutations that have occurred across the whole genome.

More powerful predictors than traditional genetic markers

The research team found that mutational signatures can in fact accurately predict how various drugs will act on the cancer cells of different types of tumours. “We have performed statistical analysis using machine-learning methods, considering jointly cancer cell genomes, their response to various drugs, and their response to gene editing experiments. Surprisingly, our analysis revealed that the ‘classical’ genetic markers such as driver gene mutations or copy-number changes are often less powerful than the mutational signature genetic markers in predicting drug response,” states Dr Fran Supek of HYPER-INSIGHT project host and DECIDER and PROBIST projects’ partner Institute for Research in Biomedicine, Spain, in the same news release. According to the scientists, signatures of deficiencies in DNA repair tend to indicate cancer cell sensitivity to certain drugs. “Given that tumours have impaired DNA repair mechanisms, these predicted therapies would have a greater capacity to kill cancer cells and spare healthy ones,” explains the news release. In contrast, signatures of prior exposures to DNA-damaging agents such as chemotherapy tend to associate with drug resistance. Replication analyses conducted across independent drug and CRISPR genetic screening data sets revealed hundreds of robust associations between mutational signatures and drug responses. “The algorithms used to identify the mutational signatures and link them to drug vulnerabilities are open access,” the news release reports. The study supported by HYPER-INSIGHT (Hypermutated tumors: insight into genome maintenance and cancer vulnerabilities provided by an extreme burden of somatic mutations), DECIDER (Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer), and PROBIST (COFUND BIST POSTDOCTORAL FELLOWSHIP PROGRAMME) was published in the journal ‘Nature Communications’. For more information, please see: HYPER-INSIGHT project DECIDER project PROBIST project web page

Keywords

HYPER-INSIGHT, DECIDER, PROBIST, cancer, tumour, gene, DNA, drug, mutation, mutational signature, genetic markers, drug response

Related articles