June 29, 2022
What is Metastasis?
Cancer metastasis is a profound clinical challenge, but the underlying cellular mechanisms are still poorly characterized. Metastasis occurs when cancerous cells detach from a tumor and enter the bloodstream, where they can circulate to other parts of the body and colonize a new tissue.
The origin of these circulating tumor cells (CTCs) was long thought to be from a constant “shedding” of cells by a tumor (also the principle behind blood-based cancer biomarker assays) or a physical insult to the tumor causing cells to detach. However, a recent and striking paper in Nature last week uncovered that cancer cells seem to metastasize most aggressively during sleep.
Metastasis Increases During Sleep
The authors found a pattern that most of the spontaneous events of cancerous cells being shed into the bloodstream in both human and mouse models of breast cancer were occurring during sleep. What drives this unusual phenomenon? The answer, according to the authors, is two-fold.
Using single-cell RNA sequencing (scRNA-seq), the authors analyzed the transcriptomes of the CTCs and found that in the rest-phase CTCs that were highly prone to metastasis, there was a dramatic increase in expression of key mitotic genes. This upregulation of mitosis seems to allow for metastatic proficiency.
A Future for Time-Based Cancer Treatments
Secondly, systemic circadian rhythm hormones like melatonin and glucocorticoids regulate CTC dynamics, helping upregulate metastasis during sleep as well. This paper provides convincing evidence for time-based monitoring and treatment of metastasis-prone cancers, as well as a much-improved understanding of the molecular mechanisms underlying metastasis.
Outsourcing Bioinformatics Analysis
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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].