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Nucleic Acids Research Papers on Targeting DNA Damage Response, TSMiner, VarSAn

Researchers at the University of Texas MD Anderson Cancer Center present findings from a CRISPR-based gene editing screen aimed at finding genetic alterations that influence response to inhibitors targeting parts of the DNA damage response (DDR) pathway. Results from their screen in human cell lines and follow-up experiments suggest that cells may become more sensitive to CHK1 inhibitor treatment when the YWHAE gene is missing or more vulnerable to DNAPK inhibitor treatment in the absence of a gene called APEX1, for example, but appear better equipped to withstand ATM inhibitor treatments when the KLHL15 gene is knocked out. The team also explored the consequences of combining distinct DDR inhibitors, including enhanced apoptosis events found in cells exposed to both ATM and PARP inhibitors. "Our results enhance the understanding of DDR pathways," the authors write, "and will facilitate the use of DDR-targeting agents in cancer therapy."

A team from China outlines an analytical method for untangling regulatory network data from RNA sequencing data generated during time course experiments. The "time-series miner" (TSMiner) brings together transcription factor-target gene interaction data, pathway clues, and transcriptomic profiles generated over time, the investigators say. When they applied TSMiner to expression data generated for mouse liver samples collected at a dozen time points during the process of regeneration after a partial hepatectomy surgery, the authors tracked down dozens of transcriptional repressors with altered activity across the time series, along with almost 400 transcriptional activators and more than 150 genes that appeared to contribute to the process. "The application of TSMiner to the [liver regeneration] RNA-seq data revealed both known mechanisms of [liver regeneration] and mechanisms that have not been previously reported," they write, noting that "we discovered an immune response cascade that included cell apoptosis, apoptotic cell clearance, and T-cell differentiation."

University of Illinois at Urbana-Champaign researchers report on a computational tool known as the "variant set annotator," or VarSAn, designed to detect pathways of interest from a genetic variant set with the help of network analyses. The tool "treats non-coding and coding variants differently, properly accounts for the number of pathways impacted by each variant, and identifies relevant pathways even if many variants do not directly impact genes of the pathway," they note. After evaluating the approach, the team turned to VarSAn to assess more than 650 de novo variants detected in two dozen parent-child trios affected by hypoplastic left heart syndrome, uncovering ties between the rare congenital heart condition and dozens of pathways, including a VEGFA-VEGFR2 pathway implicated in hypoplastic left heart syndrome and other heart conditions in the past.

 

The Scan

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