Browsing by Author "Fantini, Damiano"

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    APE1/Ref-1 Interacts with NPM1 within Nucleoli and Plays a Role in the rRNA Quality Control Process
    (2009-04) Vascotto, Carlo; Fantini, Damiano; Romanello, Milena; Cesaratto, Laura; Deganuto, Marta; Leonardi, Antonio; Radicella, J Pablo; Kelley, Mark R.; D'Ambrosio, Chiara; Scaloni, Andrea; Quadrifoglio, Franco; Tell, Gianluca
    APE1/Ref-1 (hereafter, APE1), a DNA repair enzyme and a transcriptional coactivator, is a vital protein in mammals. Its role in controlling cell growth and the molecular mechanisms that fine-tune its different cellular functions are still not known. By an unbiased proteomic approach, we have identified and characterized several novel APE1 partners which, unexpectedly, include a number of proteins involved in ribosome biogenesis and RNA processing. In particular, a novel interaction between nucleophosmin (NPM1) and APE1 was characterized. We observed that the 33 N-terminal residues of APE1 are required for stable interaction with the NPM1 oligomerization domain. As a consequence of the interaction with NPM1 and RNA, APE1 is localized within the nucleolus and this localization depends on cell cycle and active rRNA transcription. NPM1 stimulates APE1 endonuclease activity on abasic double-stranded DNA (dsDNA) but decreases APE1 endonuclease activity on abasic single-stranded RNA (ssRNA) by masking the N-terminal region of APE1 required for stable RNA binding. In APE1-knocked-down cells, pre-rRNA synthesis and rRNA processing were not affected but inability to remove 8-hydroxyguanine-containing rRNA upon oxidative stress, impaired translation, lower intracellular protein content, and decreased cell growth rate were found. Our data demonstrate that APE1 affects cell growth by directly acting on RNA quality control mechanisms, thus affecting gene expression through posttranscriptional mechanisms.
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    MutSignatures: an R package for extraction and analysis of cancer mutational signatures
    (Nature Publishing Group, 2020-10-26) Fantini, Damiano; Vidimar, Vania; Yu, Yanni; Condello, Salvatore; Meeks, Joshua J.; Obstetrics and Gynecology, School of Medicine
    Cancer cells accumulate somatic mutations as result of DNA damage, inaccurate repair and other mechanisms. Different genetic instability processes result in characteristic non-random patterns of DNA mutations, also known as mutational signatures. We developed mutSignatures, an integrated R-based computational framework aimed at deciphering DNA mutational signatures. Our software provides advanced functions for importing DNA variants, computing mutation types, and extracting mutational signatures via non-negative matrix factorization. Specifically, mutSignatures accepts multiple types of input data, is compatible with non-human genomes, and supports the analysis of non-standard mutation types, such as tetra-nucleotide mutation types. We applied mutSignatures to analyze somatic mutations found in smoking-related cancer datasets. We characterized mutational signatures that were consistent with those reported before in independent investigations. Our work demonstrates that selected mutational signatures correlated with specific clinical and molecular features across different cancer types, and revealed complementarity of specific mutational patterns that has not previously been identified. In conclusion, we propose mutSignatures as a powerful open-source tool for detecting the molecular determinants of cancer and gathering insights into cancer biology and treatment.