Researchers have found that breast and ovarian cancer-causing genes can now be detected with a combination of PCR tests and machine learning. In a recent study funded by top US-based research organizations, scientists discovered a new way to detect functional changes in cancer-causing genes, rather than detecting mutations in these genes. By looking for specific signals in the blood that activate genes toward cancer-causing mutations, researchers were able to detect microRNA constellations in blood samples and ultimately resulted in 94% accuracy in detecting mutations.
This groundbreaking discovery means that cancer risks can be detected in people in a more cost-effective and affordable manner. Complications in screening for cancer-causing mutations have been widespread, including the fact that almost a million people carry BRCA1/2 gene mutations without being aware of them. Additionally, many countries, like India, lack gene testing systems for mutations. With this new method, screening for such diseases becomes easier, and for people with a family history of cancers, it is recommended that they undergo genetic testing and further screening tests for those who test positive for mutations of these two genes.
This research has multiple implications for cancer treatment and detection. This method offers a more comprehensive view of cancer risk compared to gene sequencing since it detects the signal changes in the pathway, rather than any particular gene or component causing the pathway’s mutation. Thus, any molecule causing these signaling changes can be detected, which is essential since many cancer-causing genes remain unknown to this day. Moreover, this discovery makes screening for inherited cancer risks more accessible, especially for those with a family history of specific types of cancers like breast and ovarian cancers. Further clinical studies are ongoing, but this new screening method shows promise.
