Giorgio E. M. Melloni

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UNLABELLED The identification of genes maintaining cancer growth is critical to our understanding of tumorigenesis. We report the first in vivo genetic screen of patient-derived tumors, using metastatic melanomas and targeting 236 chromatin genes by expression of specific shRNA libraries. Our screens revealed unprecedented numerosity of genes indispensable(More)
MOTIVATION Cellular mRNA levels originate from the combined action of multiple regulatory processes, which can be recapitulated by the rates of pre-mRNA synthesis, pre-mRNA processing and mRNA degradation. Recent experimental and computational advances set the basis to study these intertwined levels of regulation. Nevertheless, software for the(More)
A key challenge in the analysis of cancer genomes is the identification of driver genes from the vast number of mutations present in a cohort of patients. DOTS-Finder is a new tool that allows the detection of driver genes through the sequential application of functional and frequentist approaches, and is specifically tailored to the analysis of few tumor(More)
Since the publication of this article, the authors have identified an error within Table 2, namely that the AML subgroups listed at the bottom of the table were incorrect. The correct table is shown here. The article has also been rectified, and now carries the correct information. The Publishers apologize for any inconvenience this has caused. a TCGA b(More)
It has been shown that individual acute myeloid leukemia (AML) patients are characterized by one of few initiating DNA mutations and 5-10 cooperating mutations not yet defined among hundreds identified by massive sequencing of AML genomes. We report an in vivo insertional-mutagenesis screen for genes cooperating with one AML initiating mutations (PML-RARA,(More)
The analyses carried out using 2 different bioinformatics pipelines (SomaticSniper and MuTect) on the same set of genomic data from 133 acute myeloid leukemia (AML) patients, sequenced inside the Cancer Genome Atlas project, gave discrepant results. We subsequently tested these 2 variant-calling pipelines on 20 leukemia samples from our series (19 primary(More)
BACKGROUND The landscape of cancer-predisposing genes has been extensively investigated in the last 30 years with various methodologies ranging from candidate gene to genome-wide association studies. However, sequencing data are still poorly exploited in cancer predisposition studies due to the lack of statistical power when comparing millions of variants(More)
The increasing availability of resequencing data has led to a better understanding of the most important genes in cancer development. Nevertheless, the mutational landscape of many tumor types is heterogeneous and encompasses a long tail of potential driver genes that are systematically excluded by currently available methods due to the low frequency of(More)
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