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Integrated single cell genetic and transcriptional analysis suggests novel private drivers of chronic lymphocytic leukemia.

ABSTRACT: Integrated single cell genetic and transcriptional analysis suggests novel private drivers of chronic lymphocytic leukemia.

PROVIDER: PRJNA387321 | ENA |

REPOSITORIES: ENA

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Project description:Integrated single cell genetic and transcriptional analysis suggests novel private drivers of chronic lymphocytic leukemia.

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Integrated Genomic Analysis of Chronic Lymphocytic Leukaemia

Project description:Chronic lymphocytic leukaemia (CLL) is a frequent and heterogeneous disease whose genetic alterations determining the clinicobiological behaviour are not fully understood. Here, we describe a comprehensive evaluation of the genomic landscape of 452 CLLs and 54 monoclonal B-lymphocytosis (MBL), a precursor disorder. This study provides an integrated portrait of the genomic landscape of CLL, identifies new recurrent mutations acting as drivers of the disease, and suggests clinical interventions which may improve the management of patients with this neoplasia.

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Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia.

Project description:Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

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An Integrated Approach to Uncover Drivers of Cancer

Project description:We developed a computational framework that integrates chromosomal copy number and gene expression data for detecting aberrations that promote cancer progression. We demonstrate the utility of this framework using a melanoma dataset. Our analysis correctly identified known drivers of melanoma and predicted multiple novel tumor dependencies. Two dependencies, TBC1D16 and RAB27A, confirmed empirically, suggest that abnormal regulation of protein trafficking contributes to proliferation in melanoma. Together, these results demonstrate the ability of integrative Bayesian approaches to identify novel candidate drivers with biological, and possibly therapeutic, importance in cancer. Effects of knockdown of two genes -TBC1D16 and RAB27A - were tested on four cell lines each, each of them with two different hairpins. As a control, we used a hairping targeting GFP. shGFP experiments were done in biological duplicates or more. The second WM1976-shGFP sample was identified as an outlier by a PCA analysis and was excluded from our analysis.

2010-12-01 | E-GEOD-23884 | biostudies-arrayexpress

Transcriptome splicing analysis in K562 cells expressing rare and private spliceosomal mutations

Project description:Genes encoding RNA splicing factors are frequently mutated in clonal hematopoesis and diverse cancers. Most spliceosomal mutations affect specific hotspot residues, causing changes in exon and splice site recognition that promote disease. However, a subset of patients carry splicesomal mutations in non-hotspot residues, and their contribution to disease are unknown. Here we systematically characterized the function of several rare and private spliceosomal mutations in order to determine their potential disease relevance. We discovered that several rare and private spliceosomal mutations phenocopy the mechanistic splicing alterations induced by their "hotspot" counterparts. Our data suggest that many rare and private spliceosomal mutations contribute to disease pathogenesis.

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Metabolic drivers of human keratinocyte differentiation revealed by integrated metabolome and transcriptome analysis

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Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers (microRNA)

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Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers (mRNA)

Project description:Oral cavity squamous cell carcinoma (OSCC) is a disease with extensive morbidity and mortality and few useful molecular targets. Multiplatform integrated genomic analysis was performed in order to identify genomic drivers and molecularly discernible tumor subtypes. mRNA, miRNA and methylation data are all submitted to GEO We measured gene expression of 43 OSCC cases with the Affymetrix Human Exon 1.0 ST Array

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Integrative genomic characterization of oral squamous cell carcinoma identifies frequent somatic drivers (methylation)

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