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Biology subjects

Berard, C.

Publications and source records attributed to Berard, C..

3 recordsLinked to original sources

Molecular determinants of cardiac lymphatic dysfunction in a chronic pressure-overload model

Cardiac lymphatics have emerged as potential targets in cardiovascular diseases (CVDs). However, we recently reported that despite extensive lymphatic expansion during experimental cardiac pressure-overload, lymphatic drainage remained insufficient. To unravel the cellular and molecular mechanisms underlying lymphatic dysfunction in CVDs, we applied cardiac single-cell (sc) analyses in a murine heart failure model. Transaortic constriction (TAC), in C57BL/6J and BALB/c mice, was used to model chronic pressure-overload-induced cardiac hypertrophy and heart failure, respectively. Cardiac lymphatic (LEC) and blood vascular (BECs) endothelial cells were analyzed by scRNAseq (10XGenomics). Lymphatic targets were validated by immunohistochemistry and wholemount-imaging, and in vitro using human LEC cultures. We identified three distinct cardiac lymphatic subpopulations, capillary (LEC1), precollector (LEC2), and valvular (LEC3) clusters, and several BECs clusters, including venous BEC (vBEC). Chronic pressure-overload led to expansion of lymphatic capillaries and loss of valves in BALB/c, but not C75BL6/J. Analysis of differentially expressed genes (DEG) post-TAC revealed reduction only in BALB/c of lymphatic cell-junction components. In contrast, LEC expression of anchoring filaments, immune cell-adhesion molecules, and chemokines was preserved, or increased, indicating functional lymphatic-mediated immune cell uptake post-TAC. Interestingly, around 35% of DEGs identified in cardiac LECs post-TAC were similarly altered in interleukin (IL)-1{beta}-stimulated human LECs. In conclusion, loss of lymphatic valves and dysregulated lymphatic barrier properties may underly poor drainage capacity during pressure-overload, despite potent lymphangiogenesis and preserved LEC immune attraction. Further studies are needed to address how to restore lymphatic health to accelerate resolution of both inflammation and edema in CVDs.

cell biology↗

Prolonging lung cancer response to EGFR inhibition by targeting the selective advantage of resistant cells

Non-small cell lung cancers (NSCLCs) treated with tyrosine kinase inhibitors (TKIs) of the epidermal growth factor receptor (EGFR) almost invariably relapse in the long term, due to the emergence of subpopulations of resistant cells. Here we show that the lack of sensitivity of these cells to EGFR-TKIs constitutes a vulnerability that can be potentially targeted. Through a DNA barcoding approach, we demonstrate that the clinically approved drug sorafenib specifically abolishes the selective advantage of EGFR-TKI-resistant cells, while preserving the response of EGFR-TKI-sensitive cells, thus resulting in overall inhibition of clonal evolution within the tumor cell mass population. Sorafenib is active against multiple mechanisms of resistance/tolerance to EGFR-TKIs and its effects depend on early inhibition of MAPK interacting kinase (MNK) activity and signal transducer and activator of transcription 3 (STAT3) phosphorylation, and later down-regulation of MCL1 and EGFR. Using several xenograft and allograft models to recapitulate different mechanisms and kinetics of acquired resistance, we show that the sorafenib-EGFR-TKI combination can substantially delay tumor growth and promote the recruitment of inflammatory cells. Together, our findings indicate that sorafenib can substantially prolong the response to EGFR-TKIs by targeting NSCLC capacity to adapt to treatment through the emergence of resistant cells.

cancer biology↗

UMI-Gen: a UMI-based reads simulator for variant calling evaluation in paired-end sequencing NGS libraries

MotivationWith Next Generation Sequencing becoming more affordable every year, NGS technologies asserted themselves as the fastest and most reliable way to detect Single Nucleotide Variants (SNV) and Copy Number Variations (CNV) in cancer patients. These technologies can be used to sequence DNA at very high depths thus allowing to detect abnormalities in tumor cells with very low frequencies. A lot of different variant callers are publicly available and usually do a good job at calling out variants. However, when frequencies begin to drop under 1%, the specificity of these tools suffers greatly as true variants at very low frequencies can be easily confused with sequencing or PCR artifacts. The recent use of Unique Molecular Identifiers (UMI) in NGS experiments offered a way to accurately separate true variants from artifacts. UMI-based variant callers are slowly replacing raw-reads based variant callers as the standard method for an accurate detection of variants at very low frequencies. However, benchmarking done in the tools publication are usually realized on real biological data in which real variants are not known, making it difficult to assess their accuracy. ResultsWe present UMI-Gen, a UMI-based reads simulator for targeted sequencing paired-end data. UMI-Gen generates reference reads covering the targeted regions at a user customizable depth. After that, using a number of control files, it estimates the background error rate at each position and then modifies the generated reads to mimic real biological data. Finally, it will insert real variants in the reads from a list provided by the user. AvailabilityThe entire pipeline is available at https://gitlab.com/vincent-sater/umigen-master under MIT license. Contactvincent.sater@gmail.com

bioinformatics↗