Statistics with a kick: Data analysis reveals cancer genes
Researchers at the University of Basel have developed an analytical method to detect genes involved in the development of cancer. Using this approach, they were able to identify a number of new cancer genes, including one that plays a role in breast cancer.
09 September 2021
Tracking down as yet unknown cancer genes is the basis for discovering new targets for cancer drugs. The search for cancer genes has never been more efficient, thanks to new techniques. Whereas researchers used to knock out one gene at a time in cells and then study the effect and thus the role of the gene, this can now be done in thousands of cells in parallel. With the help of special biomolecules, known as short hairpin RNAs, different genes can be switched off in a targeted manner. Such screening experiments generate huge data sets.
Researchers led by Dr. Salvatore Piscuoglio of the University of Basel and Dr. Ng of the University of Bern have developed a statistical analysis platform to systematically comb through the data sets from such screening experiments for genes involved in the development of cancer. They report on this important new tool for research in the journal Nucleic Acid Research.
The analysis also focuses on detecting genes that are specific to certain types of cancer by comparing such experiments in different cancer cell lines.
Breast cancer gene identified
The researchers were able to demonstrate the effectiveness of their analysis platform, which is called APSiC (Analysis of Perturbation Screens for identifying novel Cancer genes), by identifying a number of genes from existing data sets that have been shown to play a role in cancer development. In addition to known cancer genes, however, they also tracked down some as yet unknown ones.
For example, they were able to prove that one of the identified genes, called LRRC4B, is involved in the development of breast cancer. They are currently working to decipher the exact role of the gene and other candidate genes.
“The advantage of our analysis platform is that candidate genes can be identified even when comparing only a few cancer cell lines,” Piscuoglio explains. “Previous analyses could only provide reliable results based on the comparison of hundreds of cell lines.” With APSiC, Piscuoglio and his team hope to accelerate research on cancer genes, laying the groundwork for new therapeutic approaches.
Original publication
Hesam Montazeri et al.
Systematic identification of novel cancer genes through analysis of deep shRNA perturbation screens
Nucleic Acid Research (2021), doi: 10.1093/nar/gkab627
