Francesco Iorio

Francesco Iorio is a computer scientist, currently Group Leader at HT’s Computational Biology Research Centre and team leader at the Wellcome Sanger Institute in Hixton (UK). He works on analytical methods for pharmacogenomics, therapeutic target discovery, drug repositioning and biomedical big-data mining, with a specific focus on cancer, rare diseases and neurodegenerative disorders such as Alzheimer’s and Parkinson’s disease. Francesco is building up his group and research activity, dividing his time between Milan and Cambdrige.

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Publications

  • 07/2022 - Cell Reports

    Reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 fitness screens

    Pooled genome-wide CRISPR-Cas9 screens are furthering our mechanistic understanding of human biology and have allowed us to identify new oncology therapeutic targets. Scale-limited CRISPR-Cas9 screens—typically employing guide RNA libraries targeting subsets of functionally related genes, biological pathways, or portions of the druggable genome—constitute an optimal setting for investigating narrow hypotheses and are easier to execute […]

  • 07/2022 - Molecular Systems Biology

    Computational estimation of quality and clinical relevance of cancer cell lines

    Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome-wide editing screenings have facilitated the discovery of clinically relevant gene–drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision […]

  • 11/2021 - BMC Genomics

    CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens

    Background CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from […]

  • 09/2021 - Clinical Cancer Research

    Functional impact of genomic complexity on the transcriptome of Multiple Myeloma

    Purpose: Multiple Myeloma (MM) is a biologically heterogenous plasma-cell disorder. In this study we aimed at dissecting the functional impact on transcriptome of gene mutations, copy-number abnormalities (CNAs), and chromosomal rearrangements (CRs). Moreover, we applied a geno-transcriptomic approach to identify specific biomarkers for personalized treatments. Methods: We analyzed 514 newly-diagnosed patients from the IA12 release […]

  • 03/2021 - Nature Communications

    Integrated cross-study datasets of genetic dependencies in cancer

    CRISPR-Cas9 viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy. Integrating the datasets resulting from these studies is necessary to adequately represent the heterogeneity of human cancers and to assemble a comprehensive map of cancer genetic vulnerabilities. Here, we integrated […]