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Wilson, C.

Publications and source records attributed to Wilson, C..

74 records · Page 5Linked 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↗

A Liquid Chromatography-Mass Spectrometry Method For Screening Disulfide Tethering Fragments

We report the refinement of a high-throughput, liquid-chromatography/mass spectrometry (LC/MS)-based screening method for the identification of covalent small-molecule binders to proteins. Using a custom library of 1600 disulfide-capped fragments targeting surface cysteine residues, we optimize sample preparation, chromatography, and ionization conditions to maximize the reliability and flexibility of the approach. Data collection at a rate of 90 seconds per sample balances speed and reliability for sustained screening over multiple, diverse projects run over a 24-month period. The method is applicable to protein targets of various classes and a range of molecular masses. Data are processed in a custom pipeline that calculates a % bound value for each compound and detects false-positives by calculating significance of detected masses ( signal significance). An example pipeline has been made available through Biovias ScienceCloud Protocol Exchange. Data collection and analysis methods for the screening of covalent adducts of intact proteins are now fast enough to screen the largest covalent compound libraries in 1-2 days.

biophysics↗