CRISPR-Cas9-guided oncogenic chromosomal translocations with conditional fusion protein expression in human

Fabio Vanoli1, Mark Tomishima1, Weiran Feng1,2

  • 1Developmental Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065.

Insights

Scientists developed a new gene editing strategy to model cancer-causing genomic rearrangements. This method efficiently selects cells with specific oncogenic translocations, like EWSR1-WT1, for cancer research.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Gene editing is used to model tumor cell genomic rearrangements.
  • Nonhomologous end joining (NHEJ) is a common but inefficient repair pathway for these rearrangements.
  • Cloning cells with desired rearrangements before oncogenic transformation is challenging due to low event frequency.

Purpose of the Study:

  • To develop a novel gene editing strategy for efficient modeling of cancer-relevant genomic rearrangements.
  • To select human mesenchymal stem cells harboring the EWSR1-WT1 oncogenic translocation.
  • To create a conditionally expressible fusion transcript under endogenous promoter control.

Main Methods:

  • Combined CRISPR-Cas9 technology with homology-directed repair (HDR).
  • Targeted induction of double-strand breaks at specific endogenous loci.
  • Selection of human mesenchymal stem cells with the EWSR1-WT1 translocation.
  • Utilized Cre recombinase for conditional expression of the fusion transcript.

Main Results:

  • Successfully generated human mesenchymal stem cells with the EWSR1-WT1 oncogenic translocation.
  • The EWSR1-WT1 fusion transcript is expressed under the endogenous EWSR1 promoter.
  • Conditional expression of the fusion transcript was achieved using Cre recombinase.
  • The developed method is adaptable for generating other cancer-relevant rearrangements.

Conclusions:

  • The novel strategy efficiently selects cells with specific oncogenic translocations.
  • This approach facilitates the study of cancer development and progression.
  • The method is versatile and can be applied to model various cancer-associated genomic rearrangements.