E-GEOD-31138
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-31138 | ExpressionAtlas | 2019-06-14
REPOSITORIES: ExpressionAtlas
Similar Datasets
Project description:Identifying novel anti-angiogenic targets in human breast cancer
| PRJNA144953 | ENA
Project description:The genomic studies was designed to identify genes differentially expressed in tumor versus normal breast tissue. We aimed at identifying novel Antibody Drug Conjugate (ADC) targets that could be used to treat Triple Negative Breast Cancer (TNBC). Comparative genomic studies between normal breast and TNBC tissues, together with proteomic and bioinformatic analyses resulted in the elaboration of a catalog of potential ADC targets.
2021-10-12 | GSE185645 | GEO
Project description:Protein arginine methyltransferase-6 (PRMT6) regulates steroid-dependent transcription and alternative splicing, and is implicated in endocrine system development and function, cell death, cell cycle, gene expression and cancer. Despite its role in these processes, little is known about its function and cellular targets in breast cancer. To identify novel gene targets regulated by PRMT6 in breast cancer cells, we used a combination of small interfering RNA (siRNA) and exon-specific microarray profiling in vitro, coupled to in vivo validation in normal breast and primary human breast tumours. This approach, which allows the examination of genome-wide changes in individual exon usage and total transcript levels, demonstrated PRMT6 knockdown significantly affected: (i) the transcription of 159 genes, and (ii) alternate splicing of 449 genes. Importantly, the levels of PRMT6 itself were significantly decreased in breast cancer, relative to normal breast tissue. The PRMT6 dependent transcriptional and alternative splicing targets identified in vitro, were validated in human breast tumours. Notably, expression of PRMT6 and the corresponding gene signature, correlated with decreased probability of relapse-free or distant metastasis free survival in ER+ breast cancer. These results suggest that dysregulation of PRMT6 dependent transcription and alternative splicing may be involved in breast cancer pathophysiology and the molecular consequences identifying a unique and informative biomarker profile. Total RNA obtained from MCF7 breast cancer cells transfected with siRNA directed against PRMT6 or negative control siRNA (Ambion Silencer Select negative control).
2012-08-01 | E-GEOD-36542 | biostudies-arrayexpress
Project description:Protein arginine methyltransferase-6 (PRMT6) regulates steroid-dependent transcription and alternative splicing, and is implicated in endocrine system development and function, cell death, cell cycle, gene expression and cancer. Despite its role in these processes, little is known about its function and cellular targets in breast cancer. To identify novel gene targets regulated by PRMT6 in breast cancer cells, we used a combination of small interfering RNA (siRNA) and exon-specific microarray profiling in vitro, coupled to in vivo validation in normal breast and primary human breast tumours. This approach, which allows the examination of genome-wide changes in individual exon usage and total transcript levels, demonstrated PRMT6 knockdown significantly affected: (i) the transcription of 159 genes, and (ii) alternate splicing of 449 genes. Importantly, the levels of PRMT6 itself were significantly decreased in breast cancer, relative to normal breast tissue. The PRMT6 dependent transcriptional and alternative splicing targets identified in vitro, were validated in human breast tumours. Notably, expression of PRMT6 and the corresponding gene signature, correlated with decreased probability of relapse-free or distant metastasis free survival in ER+ breast cancer. These results suggest that dysregulation of PRMT6 dependent transcription and alternative splicing may be involved in breast cancer pathophysiology and the molecular consequences identifying a unique and informative biomarker profile.
2012-08-02 | GSE36542 | GEO
Project description:Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations, translocations, and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole genome shRNA “dropout screens” on 77 breast cancer cell lines. Using a new hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify novel vulnerabilities in breast cancer, including new candidate “drivers,” and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, novel effects of existing anti-cancer drugs, and new opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer, and PIK3CA mutations as a resistance determinant for BET-inhibitors. Additional formatted data can be found at http://neellab.github.io/bfg/. Code and tutorials for the siMEM algorithm can be found at http://neellab.github.io/simem/.
2016-01-14 | GSE73526 | GEO
Project description:Goal: To define the digital transcriptome of three breast cancer subtypes (TNBC, Non-TNBC, and HER2-positive) using RNA-sequencing technology. To elucidate differentially expressed known and novel transcripts, alternatively spliced genes and differential isoforms and lastly expressed variants in our dataset. Method: Dr. Suzanne Fuqua (Baylor College of Medicine) provided the human breast cancer tissue RNA samples. All of the human samples were used in accordance with the IRB procedures of Baylor College of Medicine. The breast tumour types, TNBC, Non-TNBC and HER2-positive, were classified on the basis of immunohistochemical and RT-qPCR classification. Results: Comparative transcriptomic analyses elucidated differentially expressed transcripts between the three breast cancer groups, identifying several new modulators of breast cancer. We discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome. Further, we showed that exon skip and intron retention are predominant splice events in breast cancer. In addition, we found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast. We also report novel expressed variants, allelic prevalence and abundance, and coexpression with other variation, and splicing signatures. Additionally we describe novel SNPs and INDELs in cancer relevant genes with no prior reported association of point mutations with cancer mRNA profiles of 17 breast tumor samples of three different subtypes (TNBC, non-TNBC and HER2-positive) and normal human breast organoids (epithelium) samples (NBS) were sequenced using Illumina HiSeq.
2013-11-08 | E-GEOD-52194 | biostudies-arrayexpress
Project description:CD8 T cells drive the anti-cancer immune response through the recognition of MHC I-associated peptides. In order to identify relevant targets for cancer immunotherapy in breast cancer, we characterized the immunopeptidome of 26 primary breast cancer samples from two different subtypes, hormone-receptor positive (n=14) and triple negative (n=12). We were able to identify tumor-specific and tumor associated antigens in both subtypes of breast cancer, which can be used for the development of anti-cancer vaccines or as targets for engineered T-cells.
2023-11-15 | PXD034818 | Pride
Project description:Methods for identifying protein-protein interactions have mostly been limited to tagged exogenous expression approaches. We now establish a rapid, robust and comprehensive method for finding interacting proteins using endogenous proteins from limited cell numbers. We apply this approach called ‘Rapid IP-Mass Spectrometry of Endogenous proteins (RIME)’ to identify ER, FoxA1 and E2F4 interacting proteins in breast cancer cells. From small numbers of starting cells, we find a comprehensive collection of known ER, FoxA1 and E2F4 targets, plus a number of novel unexpected interactors. One of the most ER (and FoxA1) associated interactors is GREB1, an estrogen induced gene with almost no known function. We apply RIME, in parallel with ER ChIP-seq, to identify ER protein interactors and ER binding events from solid tumor xenografts, resulting in the validation of the ER-GREB1 interactions. Furthermore, we establish a method for identifying endogenous interacting proteins from solid primary breast cancer samples, whih we apply to validate ER interactions with GREB1 and additional co-factors. Mechanistically, we show that GREB1 is recruited with ER to the chromatin where it functions as an essential estrogen-mediated regulatory factor required for effective ER transcriptional activity. Our novel approach enables, for the first time, the ability for discovery and validation of protein-protein interactions in whole tissue and solid tumors, revealing significant insight into ER regulatory factors. Examination of ERGREB1 and E2F4 genomic binding patterns in cell line and xenograft tumour models
2013-01-18 | E-GEOD-41561 | biostudies-arrayexpress
Project description:We report the application of FAIRE seq in Human Mammary Epithelial Cells for identifying the breast cancer risk functional SNPs in enhancer region. Examination of FAIRE assay in HMEC
2013-05-10 | E-GEOD-46074 | biostudies-arrayexpress