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On page 1 showing 1 ~ 2 papers out of 2 papers

Defining Optimal Conditions for Tumor Extracellular Vesicle DNA Extraction for Mutation Profiling.

  • Julia Elzanowska‎ et al.
  • Cancers‎
  • 2022‎

(1) Background: Extracellular vesicles (EVs) have emerged as crucial players in the communication between cells in both physiological and pathological scenarios. The functions of EVs are strongly determined by their molecular content, which includes all bioactive molecules, such as proteins, lipids, RNA, and, as more recently described, double-stranded DNA. It has been shown that in oncological settings DNA associated with EVs (EV-DNA) is representative of the genome of parental cells and that it reflects the mutational status of the tumor, gaining much attention as a promising source of biomarker mutant DNA. However, one of the challenges in studies of EV-DNA is the lack of standardization of protocols for the DNA extraction from EVs, as well as ways to assess quality control, which hinders its future implementation in clinics. (2) Methods: We performed a comprehensive comparison of commonly used approaches for EV-DNA extraction by assessing DNA quantity, quality, and suitability for downstream analyses. (3) Results: We here established strategic points to consider for EV-DNA preparation for mutational analyses, including qPCR and NGS. (4) Conclusions: We put in place a workflow that can be applied for the detection of clinically relevant mutations in the EV-DNA of cancer patients.


The Impact of ETV6-NTRK3 Oncogenic Gene Fusions on Molecular and Signaling Pathway Alterations.

  • Matias Kinnunen‎ et al.
  • Cancers‎
  • 2023‎

Chromosomal translocations creating fusion genes are common cancer drivers. The oncogenic ETV6-NTRK3 (EN) gene fusion joins the sterile alpha domain of the ETV6 transcription factor with the tyrosine kinase domain of the neurotrophin-3 receptor NTRK3. Four EN variants with alternating break points have since been detected in a wide range of human cancers. To provide molecular level insight into EN oncogenesis, we employed a proximity labeling mass spectrometry approach to define the molecular context of the fusions. We identify in total 237 high-confidence interactors, which link EN fusions to several key signaling pathways, including ERBB, insulin and JAK/STAT. We then assessed the effects of EN variants on these pathways, and showed that the pan NTRK inhibitor Selitrectinib (LOXO-195) inhibits the oncogenic activity of EN2, the most common variant. This systems-level analysis defines the molecular framework in which EN oncofusions operate to promote cancer and provides some mechanisms for therapeutics.


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