Researchers analyzed 10,478 cancer genomes from 35 cancer types, identifying 330 potential cancer-driving genes, 74 of which were newly associated with cancer. Scientists from The Institute of Cancer Research, London, showed that more than 55% of the tumors of the participants could potentially have clinically relevant mutations.
The advantage of this is that it could then predict the patient’s sensitivity or resistance to specific treatments and their eligibility for clinical trials, as reported in Nature Genetics.
This research was driven by genetic data taken from the UK 100,000 Genomes Project to identify DNA changes that convert cells to cancerous cells, known as driver mutations. This includes a range of cancer types such as colorectal, breast, lung, and uterine cancer. Then they examined the entire genome sequences of individuals whose DNA was mapped as part of the project.
The researchers were able to detect driver mutations that have not been previously reported using the largest whole genome sequencing dataset of human tumors (10,478). The data uncovered that 74 driver genes among the 330 genes associated with cancer had never been studied about any type of cancer and thus provide new treatment targets for multiple cancers. Overall, the largest number of new driver genes were identified for ovarian, bladder, and bowel cancer. Furthermore, genes including MAP3K21, USP17L22, and TPTE emerged as key genes in bowel, breast, and lung cancer development, respectively.
Researchers evaluated how newly identified driver genes might aid in making future treatment decisions. They found that of all the samples they studied, 55% had one or more actionable or biologically relevant alterations that could inform the use of currently approved therapy.
Certain patients whose tumors had mutational profiles, such as those indicating homologous recombination deficiency, suggest DNA repair issues and could benefit from a type of cancer drug targeting PARP, some of which are already used for specific types of breast and ovarian cancer.
For the U.K. population, the samples came from the main cancer types. Additionally, the patients were younger than the typical U.K. cancer patient and had earlier-stage tumors. Thus, much more exploration of the data is necessary, the study authors concluded. Sequencing panels with an increasing number of genes might help move new treatments toward a more limited treatment group of patients with molecularly defined tumors.
The genetic foundations of cancer are open to potential avenues for treatment, following this comprehensive analysis of cancer genomes, said Dr. Amit Sud, now Wellcome Trust Early Career Fellow at the Dana-Farber Cancer Institute, Boston, U.S., and Academic Clinical Lecturer in Genetics and Epidemiology at the ICR at the time of the study. With these findings, we hope other studies will arise that help us better understand cancer and develop and test new targeted approaches.
“We aimed to extend the reach of precision therapies to a population of patients that would otherwise be unable to tolerate local or systemic therapy,” said Hertell.
The study adds to mounting evidence suggesting that as the cost of whole genome sequencing declines, straightforward all-inclusive tests should be incorporated into routine cancer care to identify cancer drivers and other genomic features missed by traditional testing. “But the research suggests that the benefit of precision oncology could extend to many more patients,” says Professor Richard Houlston, Professor of Molecular and Population Genetics at ICR and senior author of the study. “Precision Oncology first came into our domain 25 years ago and is now well established in cancer treatment.”
“We hope that this study will spur more research to find out what those mutations mean in terms of basic biology and perhaps even how to test the genes we found in treatment of the cancer.” Data sharing is critical for speeding discovery and further educating precision oncology.
Reference: Kinnersley B, Sud A, Everall A, et al. Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology. Nat Genet. 2024;56(9):1868-1877. doi:10.1038/s41588-024-01785-9
