This has underpinned the development of precision oncology, used as molecular profiling of tumors to identify changes that may be targeted for therapy.
Progress in sequencing technology has increased the number of structural variants identified in each genome from 2 500 in the 1000 Genomes Project to more than 27 000 in recent multi-platform sequencing studies.
Identification of variants acquired in cancer cells requires distinguishing tumor-specific somatic structural variants (TSSVs) from variants present in the germline and mosaic variants present in non-tumor cells. This is often done by differential analysis between paired cancer and normal samples, but despite technological innovations, this is hampered by problems common to cancer samples such as polyploidy, heterogeneity, and contamination.
The detection of structural variants is also affected by technical limitations of the sequencing platform, primarily genome coverage error and alignment uncertainty.
It is believed that for complete characterization of cancer genomes, integration of long-read and short-read data is required, which can potentially be overcome using WGS and a multi-platform approach, thereby improving TSSV identification.
In recognition of these benefits, in MNM Bioscience we rely on the data and capabilities derived from whole-genome sequencing. Designing complex solutions for this potential is to build a platform that enables their processing and identification of biological insights. The next level is to train models and tools based on artificial intelligence to match the right therapy for every cancer patient and to uncover the "black matter" in cancer genomes to discover new therapeutic targets.
This is a milestone towards precision oncology, which is evolving before our eyes.
