Microarray gene expression profile of primary breast tumour tissue
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ABSTRACT:
PROVIDER: PRJNA844059 | ENA |
REPOSITORIES: ENA
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Project description:Data were used for study of changes in gene expressions in breast primary tumour of patients with circulating tumour cells positive on mesenchymal marker (CTC EMT). Study aimed to identify signaling pathways associated with the presence of CTC_EMT in PBC patients. This translational study included 17 patients with PBC and 5 donors of normal breast tissue. CTC_EMT were detected before surgery by quantitative RT-PCR assay for expression of epithelial-to-mesenchymal transition (EMT) genes (TWIST1, SNAIL1, SLUG, ZEB1). Total RNA was extracted, in parallel, from the fresh frozen primary tumor and whole-transcriptome profiles were obtained using RNA sequencing and by microarray. RNA-seqquencing version of same samples has been submitted to SRA (BioSaples accessions are provided here). Also data under BioProject PRJNA751534 originate from the same samples.
2022-06-01 | GSE205185 | GEO
Project description:BackgroundMicroarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.MethodsIn this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.ResultsSupervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47-0.73).ConclusionThe developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.
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Project description:MicroRNAs (miRNAs), a class of short non-coding RNAs, often act post-transcriptionally to inhibit gene expression. We used a bead-based flow cytometric profiling method to obtain miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples. Of 309 human miRNAs assayed we identify 133 miRNAs expressed in human breast and breast tumours. We used mRNA expression profiling to classify the breast tumours into Luminal A, Luminal B, Basal-like, HER2+/ER- and Normal-like. A number of miRNAs are differentially expressed between these molecular tumour subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumour subtypes in an independent data set. Keywords = miRNA Keywords = microRNA Keywords = normal Keywords = tumour Keywords = cell line Keywords = breast Keywords = cancer Keywords: Bead-based flow cytometric profiling miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples
2007-10-09 | E-GEOD-7842 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs), a class of short non-coding RNAs, often act post-transcriptionally to inhibit gene expression. We used a bead-based flow cytometric profiling method to obtain miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples. Of 309 human miRNAs assayed we identify 133 miRNAs expressed in human breast and breast tumours. We used mRNA expression profiling to classify the breast tumours into Luminal A, Luminal B, Basal-like, HER2+/ER- and Normal-like. A number of miRNAs are differentially expressed between these molecular tumour subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumour subtypes in an independent data set. Keywords = miRNA Keywords = microRNA Keywords = normal Keywords = tumour Keywords = cell line Keywords = breast Keywords = cancer Keywords: Bead-based flow cytometric profiling
2007-10-09 | GSE7842 | GEO
Project description:Frozen tissue specimens from primary breast tumors were collected under approved protocols and profiled using Affymetrix U133 series expression microarrays. This cohort was assembled at the National University Hospital (NUH), Singapore in 2003, and profiled at the Genome Institute of Singapore, Microarray and Expression Genomics Lab. Dr. Lance D. Miller (Wake Forest University School of medicine) directed the profiling work. A publication describing the generation of these data is not yet available. However, these data can be used alongside other Affymetrix breast tumour data sets to form large meta-cohorts for breast cancer research, as was done in Lasham et. al. J Natl Cancer Inst. 2012 Jan 18;104(2):133-146.
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Project description:Transcriptomic changes of tumor endothelial cells in spontaneous breast tumour model and implanted breast tumour model
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2022-12-23 | PXD027341 | Pride
Project description:The main objective of the study was to identify potential diagnostic and follow up markers along with therapeutic targets for breast cancer. We performed gene expression studies using the microarray technology on 65 samples including 41 breast tumours [24 early stage, 17 locally advanced, 18 adjacent normal tissue [paired normal] and 6 apparently normal from breasts which had been operated for non-malignant conditions. All the samples had frozen section done – tumours needed to have 70% or more tumour cells; paired normal and apparently normal had to be morphologically normal with no tumour cells.
2019-10-18 | GSE139038 | GEO
Project description:Frozen tissue specimens from primary breast tumors were collected under IRB-approved protocols from 2 medical centers and profiled using Affymetrix U133 series expression microarrays. This cohort comprises of two subcohorts derived from the Institute Jules Bordet (IJB), Brussels (n=41) (2002) and Guys Hospital, London (n=7) (2003). Dr. Christos Sotiriou (Institute Jules Bordet) directed the microarray work in Brussels. A publication describing the generation of these data is not yet available. However, these data can be used alongside other Affymetrix breast tumour data sets to form large meta-cohorts for breast cancer research, as was done in Lasham et. al. J Natl Cancer Inst. 2012 Jan 18;104(2):133-146.
2012-03-31 | GSE36773 | GEO