The genetic landscape of tumors is always evolving. Cancer cells have unstable genomes, with new mutations cropping up as cancer cells divide. Equipped with these new mutations, tumors may metastasize or become resistant to chemotherapy, so figuring out which variants the cells in a tumor are carrying is important.
Next-generation sequencing (NGS) can reveal the mutations present before, during, and after chemotherapy, helping scientists understand the tumor’s response to a drug. For example, in metastatic breast cancer cells that had developed resistance to a PI(3)Kalpha inhibitor, scientists found that the cells developed multiple mutations in the tumor suppressor PTEN, causing loss of expression. This change was responsible for the cells’ resistance to the drug. (link) Being able to identify how tumor cells are able to resist treatment is a key element of overcoming that resistance.
NGS will no doubt continue to reveal these kinds of crucial findings in cancer and other areas of research. But while NGS is cheaper and faster than ever before, the massive amount of data that comes from sequencing the whole genome can be overwhelming, and is not sensitive enough to detect low-frequency variants.
An emerging strategy to overcome these challenges is to make use of a traditional technique, PCR, to focus on amplifying only the most relevant regions of the genome. The amount of sequencing data from these focused regions is more manageable, so mutations can be analyzed more quickly, and can be detected at low frequencies. Click here to watch our 3-minute video about this technology!
Which approach do you use to get the most relevant and accurate sequencing data for your project, and why?