July 18, 2022
Common Chromosome Errors in Cancer
During the rapid and uncontrolled growth that is a hallmark of cancerous cells, the tight checkpoints on cell division often fail, resulting in abnormal numbers of chromosomes in daughter cells.
This phenomenon, called aneuploidy, surprisingly appears to be non-random, particularly in cancer. Cancers exhibit distinct patterns of chromosomal rearrangements depending on the organ of origin, metastasis and relapse occurrences. So is there a predictor or driver of these chromosomal abnormalities other than the natural selection that occurs after aberrant mitosis?
Single Cell Karyotype Sequencing Uncovers Nuclear Location as a Key Driver of Aneuploidy
In an elegant set of experiments published last week in Nature, Klaasen et. al. designed a protocol to examine the propensity of different chromosomes for missegregation. The authors were able to synchronize the cell cycle phase of their cells to G2, which were then stimulated to proceed into mitosis in the presence or absence of a small molecule inhibitor of a key mitotic enzyme.
This particular inhibitor caused a very similar pattern of mitotic errors as that found in cancer cells. The cells were then subjected to single-cell karyotype sequencing (scKaryo-seq), a type of single-cell DNA sequencing that identifies the copy number of each chromosome in a single cell.
The authors found that chromosomes 1-5, 8, 11, and X had a much higher probability of missegregation than would occur randomly, while chromosomes 14, 15, and 19-22 had a much lower propensity. These findings, combined with other visualizations of the mitotic process, indicate that it is a chromosome’s distance from the nuclear center during interphase that determines its propensity for missegregation, with those that are further away having a higher probability of mis-segregating.
This helps explain the evolution of certain cancer lineages and the chromosomal errors found within them and can help narrow the research field to those chromosomes most commonly affected by missegregation.
Outsourcing Bioinformatics Analysis
This study uses a unique application of single-cell sequencing to gain a high-resolution, high-throughput understanding of the chromosomal copy numbers in individual cells. Storing and analyzing genomic data of any kind, however, is a challenging computational task.
Our experts at Bridge Informatics can help design custom cloud infrastructure for your data storage needs, as well as high-quality, reproducible data analysis pipelines. Book a free discovery call today to discuss your project needs.
Jane Cook, Journalist & Content Writer, Bridge Informatics
Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in the management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email [email protected] or [email protected].