CDC7 inhibition drives an inflammatory response and a p53-dependent senescent-like state in breast epithelial cells.

Drugs that block DNA replication prevent cell proliferation, which may result in anticancer activity. The latter is dependent on the drug's mode of action as well as on cell type-dependent responses to treatment. The inhibition of Cell division cycle 7-related protein kinase (CDC7), a key regulator of DNA replication, decreases the efficiency of origin firing and hampers the restarting of paused replication forks. Here, we show that upon prolonged CDC7 inhibition, breast-derived MCF10A cells progressively withdraw from the cell cycle and enter a reversible senescent-like state. This is characterised by the rewiring of the transcriptional programme with the induction of cytokine and chemokine expression and correlates with the accumulation of Cyclic GMP-AMP synthase (cGAS)-positive micronuclei. Importantly, cell fate depends on Cellular tumour antigen p53 (p53) function as cells no longer enter senescence but are funnelled into apoptosis upon p53 knockout. This work uncovers key features of the secondary response to CDC7 inhibitors, which could aid the development of these compounds as anticancer drugs.

GNOSIS: an R Shiny app supporting cancer genomics survival analysis with cBioPortal.

Exploratory analysis of cancer consortia data curated by the cBioPortal repository typically requires advanced programming skills and expertise to identify novel genomic prognostic markers that have the potential for both diagnostic and therapeutic exploitation. We developed GNOSIS (GeNomics explOrer using StatistIcal and Survival analysis in R), an R Shiny App incorporating a range of R packages enabling users to efficiently explore and visualise such clinical and genomic data. GNOSIS provides an intuitive graphical user interface and multiple tab panels supporting a range of functionalities, including data upload and initial exploration, data recoding and subsetting, data visualisations, statistical analysis, mutation analysis and, in particular, survival analysis to identify prognostic markers. GNOSIS also facilitates reproducible research by providing downloadable input logs and R scripts from each session, and so offers an excellent means of supporting clinician-researchers in developing their statistical computing skills.