DNA Test Accurately Predicts Resistance to Common Chemotherapy Treatments

Chemotherapy remains a cornerstone of cancer treatment, but its toxicity to healthy cells can result in severe short- and long-term side effects. Despite its widespread use, not all patients respond to chemotherapy, leading to unnecessary exposure to its harsh effects. Addressing this challenge, researchers have developed a new test that can accurately predict whether a tumor will be resistant to common chemotherapy treatments, offering a path toward more personalized and effective cancer care.

The predictive test, created by scientists at the Cancer Research UK Cambridge Institute (Cambridge, UK), in collaboration with other researchers, aims to improve treatment decision-making by identifying, in advance, which patients are unlikely to benefit from certain chemotherapy regimens. The test works by analyzing chromosomal instability (CIN) signatures—specific changes in the order, structure, and number of copies of DNA in cancer cells. By sequencing the full genome of a tumor and comparing it to that of healthy cells, the researchers can detect patterns of chromosomal disruption that are indicative of chemotherapy resistance. These patterns help predict resistance to three major classes of chemotherapy: platinum-based, anthracycline, and taxane.

To validate the test, researchers applied it to data from 840 patients with various types of cancer. Patients were classified as either “chemotherapy resistant” or “chemotherapy sensitive,” and were then virtually assigned to an alternative chemotherapy type to assess how long treatment remained effective. This simulation, which emulated a randomized controlled trial, showed that predicted resistance was strongly associated with treatment failure. For example, resistance to taxane chemotherapy corresponded with higher failure rates in ovarian, metastatic breast, and metastatic prostate cancers. Similarly, the study published in Nature Genetics, shows that resistance to anthracycline chemotherapy predicted worse outcomes in ovarian and metastatic breast cancer, while resistance to platinum-based chemotherapy was linked to higher failure rates in ovarian cancer.

The test is still undergoing further analysis and holds significant clinical promise. By identifying the likelihood of treatment resistance at the time of diagnosis, physicians could spare patients from ineffective chemotherapy and its associated side effects. The team behind the test is now preparing regulatory submissions for clinical use and is working on expanding the technology to include predictions for other targeted cancer drugs across a broader range of cancer types.

“It was important to us to create a test that could be easily adopted in clinic, using material we already collect during diagnosis and well-established genomic sequencing methods,” said Dr. Ania Piskorz, co-lead author and Head of Genomics at Cancer Research UK Cambridge Institute. “The test is based on the full DNA sequence that we get from these methods, and we can adapt it to work alongside other genomic sequencing methods that are commonly used to personalize treatment for cancer.”

Related Links:
Cancer Research UK Cambridge Institute