Biology subjects

Darbo, E.

Publications and source records attributed to Darbo, E..

4 recordsLinked to original sources

bioRxiv2020

SRF-MYOCD axis is the targetable driver of a well differentiated aggressive subtype of leiomyosarcomas

In leiomyosarcoma (LMS), a very aggressive disease, a relatively transcriptionally uniform subgroup of well differentiated tumors has been described and is associated with poor survival. The question raised how differentiation and tumor progression, two apparently antagonist processes, coexist and allow tumor malignancy. We first identified the most transcriptionally homogeneous LMS subgroup in three independent cohorts, which we named hLMS. The integration of multi-omics data and functional analysis suggests that hLMS originate from vascular smooth muscle cells and show that hLMS transcriptional program reflects both modulation of smooth muscle contraction activity controlled by MYOCD/SRF regulatory network and activation of the cell cycle activity controlled by E2F/RB1 pathway. We propose that the phenotypic plasticity of vascular smooth muscle cells coupled with MYOCD/SRF pathway amplification, essential for hLMS survival, concomitant with PTEN absence and RB1 alteration, could explain how hLMS balance this uncommon interplay between differentiation and aggressiveness.

cancer biology↗

bioRxiv2020

ATRX alteration contributes to tumor growth and immune escape in pleomorphic sarcomas

Whole genome and transcriptome sequencing of a cohort of 67 leiomyosarcomas revealed ATRX to be one of the most frequently mutated genes in leiomyosarcomas after TP53 and RB1. While its function is well described in the alternative lengthening of telomeres mechanism, we wondered whether its alteration could have complementary effects on sarcoma oncogenesis. ATRX alteration is associated with the down-expression of genes linked to differentiation in leiomyosarcomas, and to immunity in an additional cohort of 60 poorly differentiated sarcomas. In vitro and in vivo models showed that ATRX loss increases tumor growth rate and immune escape by decreasing the immunity load of active mast cells in sarcoma tumors. These data indicate that an alternative to unsuccessful targeting of the adaptive immune system in sarcoma could be to target the innate system. This might lead to a better outcome for sarcoma patients in terms of ATRX status.

cancer biology↗

bioRxiv2020

Consensus clustering applied to multi-omic disease subtyping

BackgroundFacing the diversity of omic data and the difficulty of selecting one result over all those produced by several methods, consensus strategies have the potential to reconcile multiple inputs and to produce robust results. ResultsHere, we introduce ClustOmics, a generic consensus clustering tool that we use in the context of cancer subtyping. ClustOmics relies on a non-relational graph database, which allows for the simultaneous integration of both multiple omic data and results from various clustering methods. This new tool conciliates input clusterings, regardless of their origin, their number, their size or their shape. ClustOmics implements an intuitive and flexible strategy, based upon the idea of evidence accumulation clustering. It computes co-occurrences of pairs of samples in input clusters and uses this score as a similarity measure to reorganise data into consensus clusters. ConclusionWe applied ClustOmics to multi-omic disease subtyping on real TCGA cancer data from ten different cancer types. We showed that ClustOmics is robust to heterogeneous qualities of input partitions, smoothing and reconciling preliminary predictions into high quality consensus clusters, both from a computational and a biological point of view. The comparison to a state-of-the-art consensus based integration tool, COCA, further corroborated this statement. However, the main interest of ClustOmics is not to compete with other tools, but rather to make profit from their various predictions when no gold-standard metric is available to assess their significance. AvailabilityClustOmics source code, released under MIT licence, as well as the results obtained on TCGA cancer data are available on Github: https://github.com/galadrielbriere/ClustOmics.

bioinformatics↗

bioRxiv2018

Genome-Wide Reconstitution of Chromatin Transactions: RSC Preferentially disrupts H2A.Z-Containing Nucleosomes

Chromatin transactions are typically studied in vivo, or in vitro using artificial chromatin lacking the epigenetic complexity of the natural material. Attempting to bridge the gap between these approaches, we established a system for isolating the yeast genome as a library of mono-nucleosomes harboring the natural epigenetic signature, suitable for biochemical manipulation. Combined with deep sequencing, this library was used to investigate the intrinsic stability of individual nucleosomes, and - as proof of principle - the nucleosome preference of the chromatin remodeling complex, RSC. Our data indicate that the natural stability of nucleosomes differs greatly, with nucleosomes on tRNA genes and on promoters of protein-coding genes standing out as intrinsically unstable. Interestingly, RSC shows a distinct preference for nucleosomes derived from regions with a high density of histone variant H2A.Z, and this preference is indeed markedly diminished using nucleosomes from cells lacking H2A.Z. Importantly, the preference for H2A.Z remodeling/nucleosome ejection can also be reconstituted with recombinant nucleosome arrays. Together, our data indicate that, despite being separated from their genomic context, individual nucleosomes can retain their original identity as promoter- or TSS-nucleosomes. Besides shedding new light on nucleosome stability and the chromatin remodeler RSC, the simple experimental system outlined here should be generally applicable to the study of chromatin transactions.

biochemistry↗