Gene profile of breast cancer tumors with low and high FAK expression
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Hu Qiang
PROVIDER: S-ECPF-GEOD-53618 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description:The gene expression profiles were identified in breast cancer tumors with different level of FAK
2014-02-01 | GSE53618 | GEO
Project description:The gene expression profiles were identified in breast cancer tumors with different level of FAK three tumors with low FAK expression identified by IHC and 3 tumors with high FAK expression. 2 triple-negative with low and one triple negative with high FAK expression was among these 6 samples
2014-02-01 | E-GEOD-53618 | biostudies-arrayexpress
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| S-ECPF-MTAB-1049 | biostudies-other
Project description:On the basis of prognostic information provided by the PAM50 predictor, we evaluated how samples grouped relative to the other breast tumor subtypes. mRNA samples from 24 patients were amplified, labeled, and hybridized to the Affymetrix GeneChip Human Exon 1.0 ST array. After normalization and analysis of the microarray data using Partek® software (http://www.partek.com), we clustered all samples using the PAM50 predictor. We analyzed tumors from 24 patients with breast cancer using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by AffymetrixExpression Console and analysed using Partek software
| S-ECPF-GEOD-58102 | biostudies-other
Project description:PURPOSE:Gene expression (GE) profiling for breast cancer classification and prognostication has become increasingly used in clinical diagnostics. GE profiling requires a reasonable tumor cell percentage and high-quality RNA. As a consequence, a certain amount of samples drop out. If tumor characteristics are different between samples included and excluded from GE profiling, this can lead to bias. Therefore, we assessed whether patient and tumor characteristics differ between tumors suitable or unsuitable for generating GE profiles in breast cancer. METHODS:In a consecutive cohort of 738 breast cancer patients who received neoadjuvant chemotherapy at the Netherlands Cancer Institute, GE profiling was performed. We compared tumor characteristics and treatment outcome between patients included and excluded from GE profiling. Results were validated in an independent cohort of 812 patients treated with primary surgery. RESULTS:GE analysis could be performed in 53% of the samples. Patients with tumor GE profiles more often had high-grade tumors [odds ratio 2.57 (95%CI 1.77-3.72), p < 0.001] and were more often lymph node positive [odds ratio 1.50 (95%CI 1.03-2.19), p = 0.035] compared to the group for which GE profiling was not possible. In the validation cohort, tumors suitable for gene expression analysis were more often high grade. CONCLUSIONS:In our gene expression studies, tumors suitable for GE profiling had more often an unfavorable prognostic profile. Due to selection of samples with a high tumor percentage, we automatically select for tumors with specific features, i.e., tumors with a higher grade and lymph node involvement. It is important to be aware of this phenomenon when performing gene expression analysis in a research or clinical context.
| S-EPMC5838139 | biostudies-literature
Project description:We compared the gene expression profile of 26 breast cancer cell lines to identify variations associated with different phenotypes and molecular subtype. The panel includes 13 estrogen receptor negative (ER-) and 13 ER+ cell lines. Four of the ER- cell lines and 5 of the ER+ cell lines are HER2 positive. We have used 2-color gene expression arrays for two separate studies. The one described here compares the intensities of one color channel across 26 cell lines, as normalized signal intensities. The second color channel is not analyzed here and will be used in a separate study.
| S-ECPF-GEOD-44836 | biostudies-other
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
| S-ECPF-GEOD-44838 | biostudies-other
Project description:Focal adhesion kinase (FAK) is a non-receptor tyrosine kinase that plays an important role in survival signaling. FAK has been shown to be overexpressed in breast cancer tumors at early stages of tumorigenesis.To study the direct effect of FAK on breast tumorigenesis, we developed Tet-ON (tetracycline-inducible) system of MCF-7 breast cancer cells stably transfected with FAK or dominant-negative, C-terminal domain of FAK (FAK-CD), and also FAKsiRNA with silenced FAK MCF-7 stable cell line. Increased expression of FAK in isogenic Tet-inducible MCF-7 cells caused increased cell growth, adhesion and soft agar colony formation in vitro, while expression of dominant-negative FAK inhibitor caused inhibition of these cellular processes. To study the role of induced FAK and FAK-CD in vivo, we inoculated these Tet-inducible cells in nude mice to generate tumors in the presence or absence of doxycycline in the drinking water. FAKsiRNA-MCF-7 cells were also injected into nude mice to generate xenograft tumors.Induction of FAK resulted in significant increased tumorigenesis, while induced FAK-CD resulted in decreased tumorigenesis. Taq Man Low Density Array assay demonstrated specific induction of FAKmRNA in MCF-7-Tet-ON-FAK cells. DMP1, encoding cyclin D binding myb-like protein 1 was one of the genes specifically affected by Tet-inducible FAK or FAK-CD in breast xenograft tumors. In addition, silencing of FAK in MCF-7 cells with FAK siRNA caused increased cell rounding, decreased cell viability in vitro and inhibited tumorigenesis in vivo. Importantly, Affymetrix microarray gene profiling analysis using Human Genome U133A GeneChips revealed >4300 genes, known to be involved in apoptosis, cell cycle, and adhesion that were significantly down- or up-regulated (p < 0.05) by FAKsiRNA.Thus, these data for the first time demonstrate the direct effect of FAK expression and function on MCF-7 breast cancer tumorigenesis in vivo and reveal specific expression of genes affected by silencing of FAK.
| S-EPMC3087335 | biostudies-literature
Project description:BackgroundThere is extensive scientific evidence that radiation therapy (RT) is a crucial treatment, either alone or in combination with other treatment modalities, for many types of cancer, including breast cancer (BC). BC is a heterogeneous disease at both clinical and molecular levels, presenting distinct subtypes linked to the hormone receptor (HR) status and associated with different clinical outcomes. The aim of this study was to assess the molecular changes induced by high doses of ionizing radiation (IR) on immortalized and primary BC cell lines grouped according to Human epidermal growth factor receptor (HER2), estrogen, and progesterone receptors, to study how HR status influences the radiation response. Our genomic approach using in vitro and ex-vivo models (e.g., primary cells) is a necessary first step for a translational study to describe the common driven radio-resistance features associated with HR status. This information will eventually allow clinicians to prescribe more personalized total doses or associated targeted therapies for specific tumor subtypes, thus enhancing cancer radio-sensitivity.MethodsNontumorigenic (MCF10A) and BC (MCF7 and MDA-MB-231) immortalized cell lines, as well as healthy (HMEC) and BC (BCpc7 and BCpcEMT) primary cultures, were divided into low grade, high grade, and healthy groups according to their HR status. At 24 h post-treatment, the gene expression profiles induced by two doses of IR treatment with 9 and 23 Gy were analyzed by cDNA microarray technology to select and compare the differential gene and pathway expressions among the experimental groups.ResultsWe present a descriptive report of the substantial alterations in gene expression levels and pathways after IR treatment in both immortalized and primary cell cultures. Overall, the IR-induced gene expression profiles and pathways appear to be cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to HR status.ConclusionsGenomic biomarkers and gene-signatures of specific tumor subtypes, selected according to their HR status and molecular features, could facilitate personalized biological-driven RT treatment planning alone and in combination with targeted therapies.
| S-EPMC5979377 | biostudies-literature
Project description:Most of the breast cancer samples used in clinical research contain multiple cell types other than epithelial cells alone. The non-epithelial cell types have have a substantial effect on the gene expression-profile, which is used to define molecular subtypes of the tumours. The purpose of this data set is to retrieve gene-expression profile within tumour epithelial cells. We collected 9 breast cancer epithelial cell lines and 5 tumour sampes from which epithelial cells were sorted and enriched using BerEp4 antibody coated beads. We profiled the mRNA expression level of these samples and classified probe sets into epithelial genes which were those genes with present calls in at least 50% of the samples. Then we derived an 23-gene signature based on only the epithelial genes to stratify breast cancer. Gene-expression profile analysis of 9 breast cancer epithelial cell lines and 5 tumour epithelium samples purified using BerEp4 antibody coated beads.
| S-ECPF-GEOD-23640 | biostudies-other