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Integrative Multi-Omic characterization of LYN deficient HS-5 stroma cells

ABSTRACT: LYN kinase is a tyrosine kinase, that regulates cellular homeostasis in a context specific manner. Our group could show, that its expression in the leukemic microenvironment of chronic lymphocytic leukemia contributes to disease progression (Nguyen PH et al.; Cancer Cell; 2016). To analyze the effect of LYN kinase on the leukemia supportive phenotype of the bone marrow stromal cell line HS-5, we generated single cell clones of LYN deficient cells. These cells were analyzed in a Multi-Omic approach, comprising four "Omic" layers [microarray-based transcriptome, label-free quantitative proteome and secretome, and SILAC-labelled phosphoproteome (phospho-tyrosine (pYome))] and analyzed integratively. Raw data of the single "Omic" layers are deposited in different repositories and linked below. The results of the data analysis for every "Omic" layer can be found in the spreadsheets below.

ORGANISM(S): Homo sapiens (human)

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PROVIDER: S-BSST703 | biostudies-other |

REPOSITORIES: biostudies-other

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Secretome of LYN deficient HS-5 stroma cells

Project description:LYN kinase is a tyrosine kinase, that regulates cellular homeostasis in a context specific manner. Our group could show, that its expression in the leukemic microenvironment of chronic lymphocytic leukemia contributes to disease progression (Nguyen PH et al.; Cancer Cell; 2016). To analyze the effect of LYN kinase on the leukemia supportive phenotype of the bone marrow stromal cell line HS-5, we generated single cell clones of LYN deficient cells. These cells were analyzed in a Multi-Omic approach, including quantitative, label-free proteomic analysis of the Secretome.

2023-05-10 | PXD028855 | Pride

Transcriptome of LYN deficient HS-5 stroma cells

Project description:LYN kinase is a tyrosine kinase, that regulates cellular homeostasis in a context-specific manner. Our group could show, that its expression in the leukemic microenvironment of chronic lymphocytic leukemia contributes to disease progression (Nguyen PH et al.; Cancer Cell; 2016). To analyze the effect of LYN kinase on the leukemia supportive phenotype of the bone marrow stromal cell line HS-5, we generated single cell clones of LYN deficient stroma cells. These cells were analyzed in a Multi-Omic approach, including microarray based analysis of the transcriptome.

2023-01-01 | E-MTAB-10980 | biostudies-arrayexpress

Proteome / pYome of LYN deficient HS-5 stroma cells

2023-05-10 | PXD030582 | Pride

ATAC-Seq analysis of LYN deficient HS-5 stroma cells

2023-02-01 | E-MTAB-12531 | biostudies-arrayexpress

RNA-Seq analysis of LYN deficient HS-5 stroma cells cocultured with primary human CLL cells

2023-02-10 | E-MTAB-12629 | biostudies-arrayexpress

MOTA: Multi-omic integrative analysis for biomarker discovery.

Project description:Recent advancement of omic technologies provides researchers with opportunities to search for disease biomarkers at the systems level. However, selection of biomarker candidates from a large number of molecules involved at various layers of the biological system is challenging. In this paper, we propose multi-omic integrative analysis (MOTA), a network-based method that uses information from multi-omic data to identify candidate disease biomarkers. We evaluated the performance of MOTA in selecting disease-associated molecules from four sets of multi-omic data representing three cohorts of hepatocellular carcinoma (HCC) cases and patients with liver cirrhosis. The results demonstrate that MOTA leads to selection of more biomarker candidates that shared by two different cohorts compared to traditional statistical methods. Also, the networks constructed by MOTA allow users to investigate biological significance of the selected biomarker candidates.

| S-EPMC6986235 | biostudies-literature

Integrative multi-omic analysis reveals neurodevelopmental gene dysregulation in CIC-knockout and IDH1-mutant cells.

Project description:Capicua (CIC)'s transcriptional repressor function is implicated in neurodevelopment and in oligodendroglioma (ODG) aetiology. However, CIC's role in these contexts remains obscure, primarily from our currently limited knowledge regarding its biological functions. Moreover, CIC mutations in ODG invariably co-occur with a neomorphic IDH1/2 mutation, yet the functional relationship between these two genetic events is unknown. Here, we analysed models derived from an E6/E7/hTERT-immortalized (i.e. p53- and RB-deficient) normal human astrocyte cell line. To examine the consequences of CIC loss, we compared transcriptomic and epigenomic profiles between CIC wild-type and knockout cell lines, with and without mutant IDH1 expression. Our analyses revealed dysregulation of neurodevelopmental genes in association with CIC loss. CIC ChIP-seq was also performed to expand upon the currently limited ensemble of known CIC target genes. Among the newly identified direct CIC target genes were EPHA2 and ID1, whose functions are linked to neurodevelopment and the tumourigenicity of in vivo glioma tumour models. NFIA, a known mediator of gliogenesis, was discovered to be uniquely overexpressed in CIC-knockout cells expressing mutant IDH1-R132H protein. These results identify neurodevelopment and specific genes within this context as candidate targets through which CIC alterations may contribute to the progression of IDH-mutant gliomas. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd on behalf of The Pathological Society of Great Britain and Ireland.

| S-EPMC9305137 | biostudies-literature

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis.

Project description:Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression.

| S-EPMC4595013 | biostudies-literature

An integrative analysis of the age-associated multi-omic landscape across cancers.

Project description:Age is the most important risk factor for cancer, as cancer incidence and mortality increase with age. However, how molecular alterations in tumours differ among patients of different age remains largely unexplored. Here, using data from The Cancer Genome Atlas, we comprehensively characterise genomic, transcriptomic and epigenetic alterations in relation to patients' age across cancer types. We show that tumours from older patients present an overall increase in genomic instability, somatic copy-number alterations (SCNAs) and somatic mutations. Age-associated SCNAs and mutations are identified in several cancer-driver genes across different cancer types. The largest age-related genomic differences are found in gliomas and endometrial cancer. We identify age-related global transcriptomic changes and demonstrate that these genes are in part regulated by age-associated DNA methylation changes. This study provides a comprehensive, multi-omics view of age-associated alterations in cancer and underscores age as an important factor to consider in cancer research and clinical practice.

| S-EPMC8058097 | biostudies-literature

An integrative U method for joint analysis of multi-level omic data.

Project description:BackgroundThe advance of high-throughput technologies has made it cost-effective to collect diverse types of omic data in large-scale clinical and biological studies. While the collection of the vast amounts of multi-level omic data from these studies provides a great opportunity for genetic research, the high dimensionality of omic data and complex relationships among multi-level omic data bring tremendous analytic challenges.ResultsTo address these challenges, we develop an integrative U (IU) method for the design and analysis of multi-level omic data. While non-parametric methods make less model assumptions and are flexible for analyzing different types of phenotypes and omic data, they have been less developed for association analysis of omic data. The IU method is a nonparametric method that can accommodate various types of omic and phenotype data, and consider interactive relationship among different levels of omic data. Through simulations and a real data application, we compare the IU test with commonly used variance component tests.ConclusionsResults show that the proposed test attains more robust type I error performance and higher empirical power than variance component tests under various types of phenotypes and different underlying interaction effects.

| S-EPMC6457037 | biostudies-literature

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