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Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [methylation]

ABSTRACT: Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [methylation]

PROVIDER: PRJNA721453 | ENA |

REPOSITORIES: ENA

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Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer

Project description:Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer

| PRJNA721449 | ENA

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [methylation]

Project description:Triple negative breast cancer is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with normal epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFbeta signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. EPIC Bead Chip

2021-07-01 | GSE171956 | GEO

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer

2021-06-24 | PXD025238 | Pride

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [RNA-seq]

2021-07-01 | GSE171957 | GEO

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [RNA-seq]

Project description:Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer [RNA-seq]

| PRJNA721450 | ENA

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer.

Project description:Triple negative breast cancer (TNBC) is an aggressive type of breast cancer with very little treatment options. TNBC is very heterogeneous with large alterations in the genomic, transcriptomic, and proteomic landscapes leading to various subtypes with differing responses to therapeutic treatments. We applied a multi-omics data integration method to evaluate the correlation of important regulatory features in TNBC BRCA1 wild-type MDA-MB-231 and TNBC BRCA1 5382insC mutated HCC1937 cells compared with non-tumorigenic epithelial breast MCF10A cells. The data includes DNA methylation, RNAseq, protein, phosphoproteomics, and histone post-translational modification. Data integration methods identified regulatory features from each omics method that had greater than 80% positive correlation within each TNBC subtype. Key regulatory features at each omics level were identified distinguishing the three cell lines and were involved in important cancer related pathways such as TGFβ signaling, PI3K/AKT/mTOR, and Wnt/beta-catenin signaling. We observed overexpression of PTEN, which antagonizes the PI3K/AKT/mTOR pathway, and MYC, which downregulates the same pathway in the HCC1937 cells relative to the MDA-MB-231 cells. The PI3K/AKT/mTOR and Wnt/beta-catenin pathways are both downregulated in HCC1937 cells relative to MDA-MB-231 cells, which likely explains the divergent sensitivities of these cell lines to inhibitors of downstream signaling pathways. The DNA methylation and RNAseq data is freely available via GEO GSE171958 and the proteomics data is available via the ProteomeXchange PXD025238.

| S-EPMC8504614 | biostudies-literature

Multi-omics data integration reveals correlated regulatory features of triple negative breast cancer

Project description:This SuperSeries is composed of the SubSeries listed below.

2021-07-01 | GSE171958 | GEO

Single Cell triple omics sequencing reveals genetic and epigenetic heterogeneity in hepatocellular carcinoma

Project description:Single cell genome, DNA methylome, and transcriptome sequencing has been achieved separately. However, to analyze the regulation of RNA expression by genetic and epigenetic factors within an individual cell, it is necessary to analyze these omics simultaneously from the same single cell. Here we developed a single cell triple omics sequencing technique- scTrio-seq, to analyze the genome, DNA methylome, and transcriptome concurrently of a mammalian cell. 6 single human HepG2 cell line cells were sequenced using the newly developed scTrio-seq, other 2 HepG2 cells were sequenced using scRNA-seq and other 2 HepG2 cells were sequenced using scRRBS as technique control. 6 single mouse embryonic stem cells (mESCs) were sequenced using the newly developted scTrio-seq. Meanwhile, two scRNA-seq and two scRRBS were also completed using two mESCs separately. 26 single cells from hepatocellular carcinoma were sequenced using scTrio-seq to analyze the regulation relations between three omics of cancer cells.

2016-03-01 | E-GEOD-65364 | biostudies-arrayexpress

Genetic factors underlying immune response to tick infestation of resistant and susceptible cattle unrevealed by omics data integration

Project description:Genetic factors underlying immune response to tick infestation of resistant and susceptible cattle unrevealed by omics data integration

2023-12-01 | GSE224634 | GEO

Single Cell triple omics sequencing reveals genetic and epigenetic heterogeneity in hepatocellular carcinoma

2016-03-01 | GSE65364 | GEO