Canadian researchers have developed a new computational method of discovering cancer-related gene fusions from DNA sequencing data. Along with developing the software, the group has used it to discover gene fusions in ovarian cancer for the first time.
The group's research, published in PLoS Computational Biology, shows that its so-called deFuse software could become a key tool in better characterizing malignancies. They say the software, while not able to find all gene fusions, is more effective at combing DNA sequencing data for fused genes than previous methods. Their technology uncovered gene fusions from ovarian cancer and sarcoma samples.
A major part of developing better drugs for cancer is to better understand all the various molecular drivers of tumor growth. Gene fusions, often caused by DNA repair errors, are known culprits in certain blood cancers and sarcomas. For example, the BCR-AbL1 gene fusion is a key target for treating chronic myelogenous leukemia. And gene fusions are more recently understood to be present in solid tumors such as prostate and breast cancers.
Drugs that can home in on the proteins resulting from gene fusions in cancer could improve treatment of certain types of cancer. While not perfect, the deFuse technology appears to be a step in the right direction for improving our ability to hunt down gene fusions in cancer. That could lead to new and targeted drugs that help prolong the lives of cancer patients.
- read the PLoS Computational Biology article