Dive Brief:
- A group of Japanese scientists have found six distinct types of liver cancer through a whole-genome analysis of 300 Japanese patients. Published in Nature Genetics, the study identified mutations which lead to liver cancer in nearly 40 genes, including 10 which had not previously been linked to the cancer, the Japan Times reports.
- The analysis could help identify genetic markers for the disease, possible bolstering the efficacy of targeted therapies in cancer patients.
- Five-year survival rates across the six types differed substantially, ranging from 0% to 80%, reinforcing the need for better diagnostic capabilities.
Dive Insight:
The research team, from Japan's National Cancer Center, the Riken Research Institute and the University of Tokyo, took DNA and RNA blood samples of 300 Japanese patients with liver cancer and fed the information through genome sequencers to identify mutations.
This yielded an enormous 300 terabytes of genomic data, necessitating the use of a supercomputer at the University of Tokyo to process, according to the Japan Times. Comparing the genomes of cancer patients with those of health individuals helped characterize six different types of liver cancer, based on the location of mutations.
"These results emphasize the value of whole-genome sequencing analysis in discovering cancer driver mutations and understanding comprehensive molecular profiles of liver cancer, especially with regard to STVs and noncoding mutations," the researchers said in the study abstract.
Beyond deepening scientist's understanding of the genomic characteristics of liver cancer, the study could aid the development of targeted, personalized therapies for the cancer.
Many pharma companies are working on treatments which target specific proteins in order to boost the body's immune response to cancers. Think PD1/PDL1 checkpoint inhibitors. Other biotechs are working on CRISPR and CAR-T technologies to selectively edit or enhance cell genes. Most of these treatments are not aimed at liver cancers, however.
Genome analyses like this one could help complement these therapies, hopefully increasing specificity and efficacy as disease-causing genes are singled out.