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Scaffidi, P.

Publications and source records attributed to Scaffidi, P..

2 recordsLinked to original sources

Target-specific precision of CRISPR-mediated genome editing

The CRISPR-Cas9 system has successfully been adapted to edit the genome of various organisms. However, our ability to predict editing accuracy, efficacy and outcome at specific sites is limited by an incomplete understanding of how the bacterial system interacts with eukaryotic genomes and DNA repair machineries. Here, we performed the largest comparison of indel profiles to date, examining over one thousand sites in the genome of human cells, and uncovered general principles guiding CRISPR-mediated DNA editing. We find that precision of DNA editing varies considerably among sites, with some targets showing one highly-preferred indel and others displaying a wide range of infrequent indels. Editing precision correlates with editing efficiency, homology-associated end-joining for both insertions and deletions, and a preference for single-nucleotide insertions. Precise targets and the identity of their preferred indel can be predicted based on simple rules that mainly depend on the fourth nucleotide upstream of the PAM sequence. Regardless of precision, site-specific indel profiles are highly robust and depend on both DNA sequence and chromatin features. Our findings have important implications for clinical applications of CRISPR technology and reveal general patterns of broken end-joining that can inform us on DNA repair mechanisms in human cells.

molecular biology

Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma

The identification of somatic alterations with a cancer promoting role is challenging in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we developed a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously (mutations, copy number alterations and structural rearrangements). Analysing 261 EACs from the OCCAMS Consortium, we discovered a large number of novel cancer genes that, together with well-known drivers, help promote cancer. Validation using 107 additional EACs confirmed the robustness of the approach. Unlike known drivers whose alterations recur across patients, the large majority of the newly discovered cancer genes are rare or patient-specific. Despite this, they converge towards perturbing cancer-related processes, including intracellular signalling, cell cycle regulation, proteasome activity and Toll-like receptor signalling. Recurrence of process perturbation, rather than individual genes, divides EACs into six clusters that differ in their molecular and clinical features and suggest patient stratifications for personalised treatments. By experimentally mimicking or reverting alterations of predicted cancer genes, we validated their contribution to cancer progression and revealed EAC acquired dependencies, thus demonstrating their potential as therapeutic targets.

cancer biology