Gene expression signature involved in estrogen receptor status and prognosis of breast cancers.
Ontology highlight
ABSTRACT: Fine needle aspiration biopsies (FNABs) of breast cancers were taken before and after surgeries from 16 patients. The cDNA microarray data were used to determine the gene expression profile responding to patient's clinical finding and tumor's pathological changes. A gene profile was generated as Estrogen Receptor Gene Signature (ERGS). The ERGS was verified in a reference dataset and correlated with patient's prognosis significantly. Keywords: Breast cancer, fine needle biopsy, estrogen receptor, prognostic gene signature
Project description:Fine needle aspiration biopsies (FNABs) of breast cancers were taken before and after surgeries from 16 patients. The cDNA microarray data were used to determine the gene expression profile responding to patient's clinical finding and tumor's pathological changes. A gene profile was generated as Estrogen Receptor Gene Signature (ERGS). The ERGS was verified in a reference dataset and correlated with patient's prognosis significantly. Keywords: Breast cancer, fine needle biopsy, estrogen receptor, prognostic gene signature Dye-swap technical replicates were included both FNABs taken before and after surgeries for every patient, then the four replicated array data per patient were combined for analysis.
Project description:Paired fine needle aspiration biopsies (FNABs) of breast cancers were taken before (PRE) and after (POST) surgeries from 16 patients and compared the cDNA microarray data to determine the genes that were differentially expressed between the FNABs taken at the two time points. The timing of fine needle aspiration biopsies can be a confounding factor in microarray data analyses in breast cancer. FOS-related genes, which have been implicated in early hypoxia as well as the development of breast cancers, were differentially expressed before and after surgery. Therefore, it is important that future studies take timing of tissue acquisition into account. Keywords: Breast cancer, fine needle, biopsy timing, microarray standardization, early hypoxic genes
Project description:Paired fine needle aspiration biopsies (FNABs) of breast cancers were taken before (PRE) and after (POST) surgeries from 16 patients and compared the cDNA microarray data to determine the genes that were differentially expressed between the FNABs taken at the two time points. The timing of fine needle aspiration biopsies can be a confounding factor in microarray data analyses in breast cancer. FOS-related genes, which have been implicated in early hypoxia as well as the development of breast cancers, were differentially expressed before and after surgery. Therefore, it is important that future studies take timing of tissue acquisition into account. Keywords: Breast cancer, fine needle, biopsy timing, microarray standardization, early hypoxic genes Dye-swap technical replicates were included both in PRE and POST FNABs for every patient, then the two replicated array data were combined for analysis.
Project description:This SuperSeries is composed of the following subset Series: GSE23384: Gene profiling using archival formalin-fixed paraffin-embedded breast cancer specimens can generate informative microarray data: A comparison with matched fresh fine needle aspiration biopsy samples (FFPE samples) GSE23385: Gene profiling using archival formalin-fixed paraffin-embedded breast cancer specimens can generate informative microarray data: A comparison with matched fresh fine needle aspiration biopsy samples (FNA samples) Refer to individual Series
Project description:We used ultrasound-guided fine needle aspiration of the draining axillary lymph nodes to interrogate influenza vaccine-induced GC responses in humans.
Project description:We used ultrasound-guided fine needle aspiration of the draining ipsilateral axillary lymph nodes to interrogate SARS-CoV-2 mRNA vaccine-induced GC responses in humans.
Project description:The contralateral unaffected breast of women with unilateral breast cancer (cases) is a good model for defining subtype-specific risk since women with ER-negative index primaries are at high risk for subsequent ER-negative primary cancers. We performed random fine needle aspiration (rFNA) of the unaffected breasts of cases; samples from 30 subjects (15 ER-positive and 15 ER-negative cases matched for age, race and menopausal status), were used for Illumina expression array analysis.
Project description:The contralateral unaffected breast of women with unilateral breast cancer (cases) is a good model for defining subtype-specific risk since women with ER-negative index primaries are at high risk for subsequent ER-negative primary cancers. We performed random fine needle aspiration (rFNA) of the unaffected breasts of cases; samples from 30 subjects (15 ER-positive and 15 ER-negative cases matched for age, race and menopausal status), were used for Illumina expression array analysis. In this study, we have examined gene expression profiles in random fine needle aspirate (rFNA) samples from the contralateral breasts of women with new unilateral breast cancer (cases) to seek candidate panels of ER-specific risk biomarkers. On a discovery set of 30 women, we have identified gene expression differences in the contralateral breast that associate with ER+ or ER- index primary tumors.
Project description:Estrogen action is mediated by various genes including estrogen-responsive genes (ERGs). ERGs have been used as markers for gene expression and as reporter-genes, while gene expression profiling using a set of ERGs has been used as statistically reliable transcriptomic assays, such as DNA microarray assays and RNA-seq. However, the quality of ERGs has not been extensively examined. Here, we found a set of 300 ERGs newly identified by six sets of RNA-seq data obtained from estrogen-treated and control human breast cancer MCF-7 cells. The ERGs exhibited statistical stability as judged by the coefficient of variation (CV) analysis, and their usefulness as markers for estrogenic activity by examining the stability of data in the study of correlation analysis, and functional association with estrogen action through database searches. A set of the top 30 genes based on CV ranking were further evaluated quantitatively by RT-PCR and qualitatively by a functional analysis using GO and KEGG databases and by a mechanistic analysis to classify ERα/β-dependent or ER-independent types of transcriptional regulation. The 30 ERGs were characterized by (1) the enzymes, such as metabolic enzymes, proteases and protein kinases, (2) the genes with specific cell functions, such as cell-signaling mediators, tumor-suppressors and the roles in breast cancer, (3) the association with transcriptional regulation, and/or (4) estrogen-responsiveness. Therefore, the ERGs identified here could represent various cell functions and cell signaling pathways including estrogen signaling, and thus, would be useful to evaluate estrogenic activity.