Breast Cell Lines: Experimental vs. Mixed Reference
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE18496 | GEO | 2009/10/10
SECONDARY ACCESSION(S): PRJNA120245
REPOSITORIES: GEO
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Project description:RNA expression patterns of breast cell lines were compared with a breast cell line mixed reference.
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Project description:Breast Cell Lines: Experimental vs. Mixed Reference
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Project description:Breast tumors are characterized into different subtypes based on their surface marker expression, which affects their prognosis and treatment. For example, triple negative breast cancer cells (ER-/PR-/Her2-) show reduced susceptibility towards radiotherapy and chemotherapeutic agents. Poly (ADP-ribose) polymerase (PARP) inhibitors have shown promising results in clinical trials, both as single agents and in combination with other chemotherapeutics, in several subtypes of breast cancer patients. PARP1 is involved in DNA repair, apoptosis, and transcriptional regulation and an understanding of the effects of PARP inhibitors, specifically on metabolism, is currently lacking. Here, we have used NMR-based metabolomics to probe the cell line-specific effects of PARP inhibitor and radiation on metabolism in three distinct breast cancer cell lines. Our data reveal several cell line independent metabolic changes upon PARP inhibition, including an increase in taurine. Pathway enrichment and topology analysis identified that nitrogen metabolism, glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and taurine and hypotaurine metabolism were enriched after PARP inhibition in the three breast cancer cell lines. We observed that the majority of metabolic changes due to radiation as well as PARP inhibition were cell line dependent, highlighting the need to understand how these treatments affect cancer cell response via changes in metabolism. Finally, we observed that both PARP inhibition and radiation induced a similar metabolic response in the HCC1937 (BRCA mutant cell line), but not in MCF-7 and MDAMB231 cells, suggesting that radiation and PARP inhibition share similar interactions with metabolic pathways in BRCA mutant cells. Our study emphasizes the importance of differences in metabolic responses to cancer treatments in different subtypes of cancers.
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Project description:These two transcriptome sequencing datasets were generated from two reference RNA samples established by the US FDA-led MicroArray Quality Control project with Illumina next-generation sequencing technology. The reference RNA sample A (UHRR, Catalog #740000) consists of total RNA extracted from 10 human cell lines of various origins: Blymphocyte, brain, breast, cervix, liposarcoma, liver, macrophage, skin, testis and Tlymphocyte. Equal quantities of DNAase-treated total RNA from each cell line were pooled to generate the UHRR. The reference RNA sample B (HBRR, Catalog #6050) consists of total RNA extracted from several regions of the brains from 23 adult donors.
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Project description:A variety of newly developed next-generation sequencing technologies are making their way rapidly into the research and clinical applications, for which accuracy and cross-lab reproducibility are critical, and reference standards are much needed. Our previous multicenter studies under the SEQC-2 umbrella using a breast cancer cell line with paired B-cell line have produced a large amount of different genomic data including whole genome sequencing (Illumina, PacBio, Nanopore), HiC, and scRNA-seq with detailed analyses on somatic mutations, single-nucleotide variations (SNVs), and structural variations (SVs). However, there is still a lack of well-characterized reference materials which include epigenomic and proteomic data. Here we further performed ATAC-seq, Methyl-seq, RNA-seq, and proteomic analyses and provided a comprehensive catalog of the epigenomic landscape, which overlapped with the transcriptomes and proteomes for the two cell lines. We identified >7,700 peptide isoforms, where the majority (95%) of the genes had a single peptide isoform. Protein expression of the transcripts overlapping CGIs were much higher than the protein expression of the non-CGI transcripts in both cell lines. We further demonstrated the evidence that certain SNVs were incorporated into mutated peptides. We observed that open chromatin regions had low methylation which were largely regulated by CG density, where CG-rich regions had more accessible chromatin, low methylation, and higher gene and protein expression. The CG-poor regions had higher repressive epigenetic regulations (higher DNA methylation) and less open chromatin, resulting in a cell line specific methylation and gene expression patterns. Our studies provide well-defined reference materials consisting of two cell lines with genomic, epigenomic, transcriptomic, scRNA-seq and proteomic characterizations which can serve as standards for validating and benchmarking not only on various omics assays, but also on bioinformatics methods. It will be a valuable resource for both research and clinical communities.
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