Biology subjects

Turatsinze, J.-V.

Publications and source records attributed to Turatsinze, J.-V..

4 recordsLinked to original sources

bioRxiv2024

Long-read sequencing reveals aberrant fragmentation patterns and origins of circulating DNA in cancer

Circulating cell-free DNA (cfDNA) carries fragmentation patterns that serve as biomarkers of cancer, but standard sequencing approaches miss large portions of the fragment length spectrum. In addition to altered fragmentation patterns, cancer patients often have elevated levels of cfDNA, but the underlying mechanisms are not well understood. To address both questions, we analyzed cancer cases with elevated cfDNA levels using Oxford Nanopore (ONT) sequencing. Long-read ONT sequencing captures the full spectrum of cfDNA fragment lengths and enables cell type inference based on DNA methylation markers. One cohort included cases from several cancer types with elevated cfDNA levels, and a second consisted of patients from a single neuroendocrine cancer study. In each cohort, cases with the highest cfDNA levels showed either hypofragmentation (excess fragments of 1-4 kb) or hyperfragmentation (excess fragments <145 bp). Hypofragmentation reflected blood cell DNA released during delayed sample processing, bearing DNASE1L3-associated hallmarks, while in one cohort we also observed ultra-long fragments (>7.5 kb) lacking these hallmarks and consistent with plasma lysis. By contrast, hyperfragmented samples often had elevated levels of both cancer- and blood-derived DNA, indicating an inflammatory or other system process rather than cancer-specific origin. These findings clarify the distinction between biological and artifactual fragmentation, expand our understanding of cfDNA biology, and highlight long-read sequencing as a powerful tool for biomarker discovery.

cancer biology↗

bioRxiv2023

Monitoring plasma nucleosome concentrations to measure of disease response and progression in dogs with hematopoietic malignancies.

BackgroundHematopoietic malignancies are extremely common in pet dogs and represent nearly 30% of the malignancies diagnosed in this population each year. Clinicians commonly use existing tools such as physical exam findings, radiographs, ultrasound and baseline blood work to monitor these patients for treatment response and remission. Circulating biomarkers, such as prostate specific antigen or carcinoembryonic antigen, can be useful tools for monitoring treatment response and remission status in human cancer patients. To date, there has a been a lack of useful circulating biomarkers available to veterinary oncology patients. MethodsCirculating plasma nucleosome concentrations were evaluated at diagnosis, throughout treatment and during remission monitoring for 40 dogs with lymphoma, acute myelogenous leukemia and multiple myeloma. Additionally, C-reactive protein and thymidine kinase-1 levels were recorded. ResultsPlasma nucleosome concentrations were significantly higher at diagnosis and progressive disease than they were when dogs were in remission. All but two dogs had plasma nucleosome concentrations that returned to the low range during treatment. These two dogs had the shortest progression free and overall survival times. Dogs with the highest plasma nucleosome concentrations had a significantly shorter first progression free survival than dogs with lower plasma nucleosome concentrations at diagnosis. Plasma nucleosome concentrations correlated better with disease response and progression than either thymidine kinase or C reactive protein. ConclusionsPlasma nucleosome concentrations can be a useful tool for treatment monitoring and disease progression in dogs with hematopoietic malignancies.

cancer biology↗

bioRxiv2021

TIGER: The gene expression regulatory variation landscape of human pancreatic islets

GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

bioinformatics↗

bioRxiv2019

The impact of pro-inflammatory cytokines on the β-cell regulatory landscape provides new insights into the genetics of type 1 diabetes

Early stages of type 1 diabetes (T1D) are characterized by local autoimmune inflammation and progressive loss of insulin-producing pancreatic {beta} cells. We show here that exposure to pro-inflammatory cytokines unmasks a marked plasticity of the {beta}-cell regulatory landscape. We expand the repertoire of human islet regulatory elements by mapping stimulus-responsive enhancers linked to changes in the {beta}-cell transcriptome, proteome and 3D chromatin structure. Our data indicates that the {beta} cell response to cytokines is mediated by the induction of novel regulatory regions as well as the activation of primed regulatory elements pre-bound by islet-specific transcription factors. We found that T1D-associated loci are enriched of the newly mapped cis-regulatory regions and identify T1D-associated variants disrupting cytokine-responsive enhancer activity in human {beta} cells. Our study illustrates how {beta} cells respond to a pro-inflammatory environment and implicate a role for stimulus-response islet enhancers in T1D.

genomics↗