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Ennis, D.

Publications and source records attributed to Ennis, D..

2 recordsLinked to original sources

Copy-number signatures and mutational processes in ovarian carcinoma

Tumours with profound copy-number aberration elude molecular stratification due to their genomic complexity. By representing this complexity as a mixture of copy-number signatures, we provide molecular explanations for differing clinical outcomes. Here we present a method for copy-number signature identification, deriving eight signatures in 117 shallow whole-genome sequenced high-grade serous ovarian cancers (HGSOC), which validated on independent cohorts of 95 deep whole-genome sequenced, and 402 SNP array-profiled cases. Three copy-number signatures predicted longer overall survival, while the others predicted poorer outcome. We found evidence for the mutational processes giving rise to copy-number change for six of the eight signatures via correlations with other genomic features. Our results provide insights into the pathogenesis of HGSOC by uncovering multiple mutational processes that shape genomes following TP53 mutation. Importantly, our work shows that most HGSOC have a mixture of mutational processes suggesting that targeting a single mutator phenotype may be therapeutically suboptimal.

cancer biology

Single Molecule Fluorescence In Situ Hybridisation For Quantitating Post-Transcriptional Regulation In Drosophila Brains

RNA in situ hybridization can be a powerful method to investigate post-transcriptional regulation, but analysis of intracellular mRNA distributions in thick, complex tissues like the brain poses significant challenges. Here, we describe the application of single-molecule fluorescent in situ hybridization (smFISH) to quantitate primary transcription and post-transcriptional regulation in whole-mount Drosophila larval and adult brains. Combining immunofluorescence and smFISH probes for different regions of a single gene, i.e., exons, 3UTR, and introns, we show examples of a gene that is regulated post-transcriptionally and one that is regulated at the level of transcription. We also show that the method can be used to co-visualise a variety of different transcripts and proteins in neuronal stems cells as well as deep brain structures such as mushroom body neuropils. Finally, we introduce the use of smFISH as asensitivealternative to conventional antibody labelling to mark specific neural stem cell populations in the brain.

neuroscience