Reduced Expression of Genes Regulating Cohesion Induces Chromosome Instability that May Promote Cancer and Impact Patient Outcomes

Sci Rep. 2020 Jan 17;10(1):592. doi: 10.1038/s41598-020-57530-9.

Abstract

Chromosome instability (CIN), or continual changes in chromosome complements, is an enabling feature of cancer; however, the molecular determinants of CIN remain largely unknown. Emerging data now suggest that aberrant sister chromatid cohesion may induce CIN and contribute to cancer. To explore this possibility, we employed clinical and fundamental approaches to systematically assess the impact reduced cohesion gene expression has on CIN and cancer. Ten genes encoding critical functions in cohesion were evaluated and remarkably, each exhibits copy number losses in 12 common cancer types, and reduced expression is associated with worse patient survival. To gain mechanistic insight, we combined siRNA-based silencing with single cell quantitative imaging microscopy to comprehensively assess the impact reduced expression has on CIN in two karyotypically stable cell lines. We show that reduced expression induces CIN phenotypes, namely increases in micronucleus formation and nuclear areas. Subsequent direct tests involving a subset of prioritized genes also revealed significant changes in chromosome numbers with corresponding increases in moderate and severe cohesion defects within mitotic chromosome spreads. Collectively, our clinical and fundamental findings implicate reduced sister chromatid cohesion, resulting from gene copy number losses, as a key pathogenic event in the development and progression of many cancer types.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Line
  • Chromatids / genetics*
  • Chromosomal Instability*
  • Chromosome Segregation
  • Down-Regulation
  • Female
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks*
  • HCT116 Cells
  • Humans
  • Male
  • Neoplasms / genetics*
  • Patient Outcome Assessment
  • Single-Cell Analysis
  • Survival Analysis

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