Biology subjects

Cappannini, A.

Publications and source records attributed to Cappannini, A..

3 recordsLinked to original sources

bioRxiv2024

The three YTHDF paralogs and VIRMA are the major tumor drivers among the m6A core genes in a pan-cancer analysis

N6-methyladenosine (m6A) is the most abundant internal modification in mRNAs. Despite accumulating evidence for the profound impact of m6A on cancer biology, there are conflicting reports that alterations in genes encoding the m6A machinery proteins can either promote or suppress cancer, even in the same tumor type. Using data from The Cancer Genome Atlas, we performed a pan-cancer investigation of 15 m6A core factors in nearly 10,000 samples from 31 tumor types to reveal underlying cross-tumor patterns. Altered expression, largely driven by copy number variations at the chromosome arm level, results in the most common mode of dysregulation of these factors. YTHDF1, YTHDF2, YTHDF3, and VIRMA are the most frequently altered factors and the only ones to be uniquely altered when tumors are grouped according to the expression pattern of the m6A factors. These genes are also the only ones with coherent, pan-cancer predictive power for progression-free survival. On the contrary, METTL3, the most intensively studied m6A factor as a cancer target, shows much lower levels of alteration and no predictive power for patient survival. Therefore, we propose the non-enzymatic YTHDF and VIRMA genes as preferred subjects to dissect the role of m6A in cancer and as priority cancer targets. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/598899v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1e39eeborg.highwire.dtl.DTLVardef@d6628dorg.highwire.dtl.DTLVardef@e048a6org.highwire.dtl.DTLVardef@c19812_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

DEGRONOPEDIA - a web server for proteome-wide inspection of degrons

The ubiquitin-proteasome system is a proteolytic pathway that removes damaged and unwanted proteins. Their selective turnover is initiated by ubiquitin (Ub) attachment, mainly by Ub ligases that recognize substrates through their short linear motifs termed degrons. A degradation-targeting degron comprises a nearby Ub-modified residue and an intrinsically disordered region (IDR) involved in interaction with the proteasome. Degron-signaling has been studied over the last decades, yet there are no resources for systematic screening of degron sites to facilitate studies on their biological significance, such as targeted protein degradation approaches. To bridge this gap, we developed DEGRONOPEDIA, a web server that allows exploration of degron motifs in the proteomes of seven model organisms and maps these data to Lys, Cys, Thr, and Ser residues that can undergo ubiquitination and to IDRs proximal to them, both in sequence and structure. The server also reports the post-translational modifications and pathogenic mutations within the degron and its flanking regions, as these can modulate the degrons accessibility. Degrons often occur at the amino or carboxyl end of a protein substrate, acting as initiators of the N-/C-degron pathway, respectively. Therefore, since they may appear following the protease cleavage, DEGRONOPEDIA simulate sequence nicking based on experimental data and theoretical predictions and screen for emerging degron motifs. Moreover, we implemented machine learning to predict the stability of the N-/C-termini, facilitating the identification of substrates of the N-/C-degron pathways. We are confident that our tool will stimulate research on degron-signaling providing output information in a ready-to-validate context. DEGRONOPEDIA can be freely accessed at degronopedia.com.

bioinformatics↗

bioRxiv2020

New Evolutionary and Structural Insights In Plasmodium Proteins

One of the most debated topics in Evolutionary Biology concerns Low Complexity Regions of P. falciparum, the causative agent of the most virulent and deadly form of human malaria. In this work, we analysed the proteome of 22 plasmodium species including P. falciparum. SEG predicts that proteins containing Low Complexity Regions turn out to be longer than those which are predicted to be completely complex (without Low Complexity Regions). Moreover, using some well-known bioinformatics tools such as the Effective Number of Codons, the Pr2 and a new index that we have called SPI, we have noticed how proteins that embed Low Complexity Regions are under lower selective pressure than those that do not present this type of locus. By applying the Relative Synonymous Codon Usage and other tools developed ad hoc for this study, we note, instead, how the Low Complexity Regions appear to have a non-neutral codon bias with respect to the host proteins.

bioinformatics↗