Francesco Iorio

Publications

• Exploiting combinatorial patterns in cancer genomic data for personalized therapy and new target discovery
• Comprehensive pharmacogenomic profiling of malignant pleural mesothelioma identifies a subgroup sensitive to FGFR inhibition.
• Multilevel models improve precision and speed of IC50 estimates.
• Integrated transcriptomic and proteomic analysis identifies protein kinase CK2 as a key signaling node in an inflammatory cytokine network in ovarian cancer cells.
• Unravelling druggable signalling networks that control F508del-CFTR proteostasis.
• A Landscape of Pharmacogenomic Interactions in Cancer.
• E-MTAB-3610 - Transcriptional Profiling of 1,000 human cancer cell lines
• Prospective derivation of a living organoid biobank of colorectal cancer patients.
• Functional impact of genomic complexity on the transcriptome of Multiple Myeloma.
• A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia
• Integrative analysis of pharmacogenomics in major cancer cell line databases using CellMinerCDB
• Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.
• The germline genetic component of drug sensitivity in cancer cell lines
• Loss of functional BAP1 augments sensitivity to TRAIL in cancer cells.
• Transcription factor activities enhance markers of drug sensitivity in cancer.
• Pathway-based dissection of the genomic heterogeneity of cancer hallmarks’ acquisition with SLAPenrich
• GDSCTools for Mining Pharmacogenomic Interactions in Cancer.
• CELLector: Genomics-Guided Selection of Cancer In Vitro Models.
• Drug repurposing: progress, challenges and recommendations.
• Identification of Intrinsic Drug Resistance and Its Biomarkers in High-Throughput Pharmacogenomic and CRISPR Screens
• Analysis of CRISPR‐Cas9 screens identifies genetic dependencies in melanoma
• Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets
• Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens.
• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.
• Cancer research needs a better map.
• CellMinerCDB for Integrative Cross-Database Genomics and Pharmacogenomics Analyses of Cancer Cell Lines.
• CELLector: Genomics Guided Selection of Cancer in vitro Models
• Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy.
• Characterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis.
• JACKS: joint analysis of CRISPR/Cas9 knockout screens.
• Minimal genome-wide human CRISPR-Cas9 library.
• Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens.
• Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets.
• Computational estimation of quality and clinical relevance of cancer cell lines
• Reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 fitness screens
• Combinatorial CRISPR screen identifies fitness effects of gene paralogues
• Integrated cross-study datasets of genetic dependencies in cancer.
• CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
• Redefining false discoveries in cancer data analyses
• BRAF inhibitor resistance mediated by the AKT pathway in an oncogenic BRAF mouse melanoma model.
• Identification of drug-specific pathways based on gene expression data: application to drug induced lung injury.
• A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.
• Blood transcriptomics of drug-naive sporadic Parkinson's disease patients.
• Pharmacogenomic agreement between two cancer cell line data sets.
• Transcriptional response networks for elucidating mechanisms of action of multitargeted agents.
• Hemopoietic-specific Sf3b1-K700E knock-in mice display the splicing defect seen in human MDS but develop anemia without ring sideroblasts
• Efficient randomization of biological networks while preserving functional characterization of individual nodes
• Stem cell-like transcriptional reprogramming mediates metastatic resistance to mTOR inhibition.
• Genome-wide chemical mutagenesis screens allow unbiased saturation of the cancer genome and identification of drug resistance mutations.
• Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening.
• Systematic identification of genomic markers of drug sensitivity in cancer cells
• A screen for combination therapies in BRAF/NRAS wild type melanoma identifies nilotinib plus MEK inhibitor as a synergistic combination
• Artificial neural network analysis of circulating tumor cells in metastatic breast cancer patients
• A Yeast Synthetic Network for In Vivo Assessment of Reverse-Engineering and Modeling Approaches
• Interactive data analysis and clustering of genomic data
• Identifying network of drug mode of action by gene expression profiling
• Transcriptional gene network inference from a massive dataset elucidates transcriptome organization and gene function
• NIRest: A tool for gene network and mode of action inference
• Gene ontology fuzzy-enrichment analysis to investigate drug mode-of-action
• Transcriptional data: A new gateway to drug repositioning?
• DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data
• Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.
• Heterogeneity of genomic evolution and mutational profiles in multiple myeloma.
• Network based elucidation of drug response: from modulators to targets.
• Fast randomization of large genomic datasets while preserving alteration counts.
• Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties.
• Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors.
• Identification of small molecules enhancing autophagic function from drug network analysis.
• Discovery of drug mode of action and drug repositioning from transcriptional responses.
• An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens
• A heuristic algorithm solving the mutual-exclusivity-sorting problem
• Benchmark Software and Data for Evaluating CRISPR-Cas9 Experimental Pipelines Through the Assessment of a Calibration Screen
• RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity.
• Highlights from the 1st European cancer dependency map symposium and workshop.
• A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization
• Distinct genetic liability profiles define clinically relevant patient strata across common diseases.
• A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data
• An unbiased lncRNA dropout CRISPR-Cas9 screen reveals RP11-350G8.5 as a novel therapeutic target for multiple myeloma.
• Author Correction: A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data.