Protein expression profile analysis of breast cancer patients with different menopausal status by iTRAQ
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
liying guo
PROVIDER: PXD021412 | iProX | Fri Sep 11 00:00:00 BST 2020
REPOSITORIES: iProX
Similar Datasets
Project description:The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 480,000 CpGs in a total of 407 samples, including 50 normal samples from healthy women, 42 matched normal-adjacent breast cancer pairs (84 samples), 263 unmatched breast cancers, 7 normal samples from BRCA1 carriers and 4 BRCA1 breast cancers. ***WARNING: incomplete metadata supplied for this study***
2015-06-18 | GSE69914 | GEO
Project description:Purpose Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with no targeted treatment available. Our previous study identified 38 TNBC-specific genes with altered expression in tumour samples compared to normal samples. This study aimed to identify whether DNA methylation contributed to these gene expression changes in the same breast cancer cohort. Additionally, we aimed to identify a whole genome methylation profile that contributes to the progression from primary breast tumour to lymph node metastasis. Methods We used the DNA of 23 primary TNBC samples, 12 matched lymph node metastases, and 11 matched normal adjacent tissues to perform 450K Illumina methylation arrays. The results were validated in an independent cohort of 70 primary TNBC samples. Results The gene expression of 16/38 TNBC-specific genes was associated with significantly altered methylation. Furthermore, altered methylation of 18 genes associated with lymph node metastasis was identified and validated in an independent cohort. Additionally, novel methylation changes between primary tumours and lymph node metastases, as well as those associated with survival were identified. Conclusion This study has shown that DNA methylation plays an important role in altered gene expression patterns of TNBC-specific genes and is the first study to perform whole genome DNA methylation analysis that includes matched lymph node metastases in this breast cancer subtype. This novel insight into the progression of TNBC to secondary cancers may provide potential prognostic indicators for this hard-to-treat breast cancer subtype. study cohort
2017-02-10 | GSE78751 | GEO
Project description:Development of a primary tumor gene expression profile that can predict the presence of circulating tumor cells in the blood of breast cancer patients. The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Seventy-two primary breast cancer tumor have been analyzed against a breast cancer reference pool.
2012-04-11 | E-GEOD-31364 | biostudies-arrayexpress
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Keywords: Tumor sample comparison
2006-08-23 | GSE5546 | GEO
Project description:<p><strong>BACKGROUND:</strong> Metabolomic characterization of tumours can potentially improve prediction of cancer prognosis and treatment response. Here, we describe efforts to validate previous metabolomic findings using a historical cohort of breast cancer patients and discuss challenges with using older biobanks collected with non-standardized sampling procedures.</p><p><strong>METHODS:</strong> In total, 100 primary breast cancer samples were analysed by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS) and subsequently examined by histology. Metabolomic profiles were related to the presence of cancer tissue, hormone receptor status, T-stage, N-stage and survival. RNA integrity number (RIN), and metabolomic profiles were compared with an ongoing breast cancer biobank.</p><p><strong>RESULTS:</strong> The 100 samples had a median RIN of 4.3, while the ongoing biobank had a significantly higher median RIN of 6.3 (<em>p</em> = 5.86 x 10^-7). A low RIN was associated with changes in choline-containing metabolites and creatine, and the samples in the older biobank showed metabolic differences previously associated with tissue degradation. The association between metabolomic profile and oestrogen receptor status was in accordance with previous findings, however, with a lower classification accuracy.</p><p><strong>CONCLUSIONS:</strong> Our findings highlight the importance of standardized biobanking procedures in breast cancer metabolomics studies.</p>
2022-01-24 | MTBLS1355 | MetaboLights
Project description:Purpose Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with no targeted treatment available. Our previous study identified 38 TNBC-specific genes with altered expression in tumour samples compared to normal samples. This study aimed to identify whether DNA methylation contributed to these gene expression changes in the same breast cancer cohort. Additionally, we aimed to identify a whole genome methylation profile that contributes to the progression from primary breast tumour to lymph node metastasis. Methods We used the DNA of 23 primary TNBC samples, 12 matched lymph node metastases, and 11 matched normal adjacent tissues to perform 450K Illumina methylation arrays. The results were validated in an independent cohort of 70 primary TNBC samples. Results The gene expression of 16/38 TNBC-specific genes was associated with significantly altered methylation. Furthermore, altered methylation of 18 genes associated with lymph node metastasis was identified and validated in an independent cohort. Additionally, novel methylation changes between primary tumours and lymph node metastases, as well as those associated with survival were identified. Conclusion This study has shown that DNA methylation plays an important role in altered gene expression patterns of TNBC-specific genes and is the first study to perform whole genome DNA methylation analysis that includes matched lymph node metastases in this breast cancer subtype. This novel insight into the progression of TNBC to secondary cancers may provide potential prognostic indicators for this hard-to-treat breast cancer subtype. Validation cohort (70 IDC TNBC samples)
2017-02-10 | GSE78754 | GEO
Project description:As we clarified before, the FOXP3 gene is an X-linked tumor suppressor gene in mammary carcinoma in both human and mouse. We also clarified that the ERBB2 and SKP2 oncogenes were transcriptionally under control of the FOXP3 gene product in mammary epithelial cells. In order to further clarify the FOXP3 down stream target genes in human breast cancer cells, we planed to conduct a microarray analysis of FOXP3-induced gene expression profiling. MCF7, a human breast cancer cell line, with FOXP3-tet-off system was cultured with and without Doxycyclin for 2 days. In the MCF7 cell cultured without Dox, the FOXP3 transcript was significantly induced as compared to the MCF7 cultured with Dox. Total RNA from MCF7 with and wihtout Dox were extracted by Qiagen's RNeasy column and they were applied to Affymetrix Human U133 2.0 array according to the manufacture's protocol. We clarified as yet unknown FOXP3 target genes in human epithelial cells, e.g., the p21 gene, by this analysis.
2009-08-12 | E-MTAB-73 | biostudies-arrayexpress
Project description:NUP93 expression inversely correlates with the survival of triple negative breast cancer patients. However, the role of NUP93 in tumor propagation has not yet been fully clarified. In this project we combined high-resolution imaging, migration assays and genetic analyses to demonstrate that NUP93 modulates actin cytoskeleton remodeling, epithelial-to-mesenchymal transition and invasion of triple negative breast cancer cells through direct interaction with the genome.
2020-01-18 | GSE137691 | GEO
Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.
2008-06-13 | E-GEOD-5546 | biostudies-arrayexpress
Project description:Development of a primary tumor gene expression profile that can predict the presence of circulating tumor cells in the blood of breast cancer patients. The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome.
2012-04-12 | GSE31364 | GEO