A TFAP2C Gene Signature is Predictive of Outcome in HER2 Breast Cancer (ChIP-Seq)
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ABSTRACT:
PROVIDER: PRJNA523615 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8606170.fastq.gz | Fastqsanger.gz | |||
| SRR8606171.fastq.gz | Fastqsanger.gz |
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Project description:A subset of HER2 breast cancers with amplification of the TFAP2C gene locus becomes addicted to AP-2g. We sought to define AP-2g-regulated genes that control growth and invasiveness by comparing HER2 cell lines with differential response to TFAP2C knockdown. A set of 68 differentially expressed genes was identified, which included CDH5 and CDKN1A. Pathway analysis implicated the MAPK13/p38δ and retinoic acid regulatory nodes, which were confirmed to display divergent responses. The AP-2g gene signature was highly predictive of outcome in HER2-positive breast cancer patients. We conclude that AP-2g regulates a set of genes in HER2 breast cancer that drive cancer growth and invasiveness and that the AP-2g gene signature can predict outcome of patients with HER2 breast cancer.
2020-04-13 | GSE126897 | GEO
Project description:A TFAP2C Gene Signature is Predictive of Outcome in HER2 Breast Cancer
| PRJNA523611 | ENA
Project description:Abstract: A subset of HER2 breast cancers with amplification of the TFAP2C gene locus becomes addicted to AP-2g. We sought to define AP-2g-regulated genes that control growth and invasiveness by comparing HER2 cell lines with differential response to TFAP2C knockdown. A set of 68 differentially expressed genes was identified, which included CDH5 and CDKN1A. Pathway analysis implicated the MAPK13/p38δ and retinoic acid regulatory nodes, which were confirmed to display divergent responses. The AP-2g gene signature was highly predictive of outcome in HER2-positive breast cancer patients. We conclude that AP-2g regulates a set of genes in HER2 breast cancer that drive cancer growth and invasiveness and that the AP-2g gene signature can predict outcome of patients with HER2 breast cancer. Results: Using an optimized data analysis workflow, we mapped about 50-75 million sequence reads per sample to the human genome Human Feb.2009 (GRCh37/hg19) (hg19). By RNA-seq analysis, knockdown of TFAP2C in HCC1954 with siRNA (compared to NT siRNA) identified 364 genes with significantly altered expression. To further create specificity for AP-2gamma-regulated genes, RNA-seq analysis was performed comparing expression in shHCC1954 with shTFAP2C cells vs. shNT; this analysis identified 8,986 genes with significantly altered expression. The two data sets were subsequently compared to identify a set of genes that were consistently altered with knockdown of TFAP2C by siRNA and shRNA. This comparison confirmed the identification of 152 AP-2gamma target genes in HCC1954 cells. Because HCC1954 demonstrated opposite growth regulation and invasiveness with knockdown of TFAP2C compared to SKBR3, we hypothesized that the AP-2gamma target genes responsible for growth and invasion would be differentially regulated with knockdown of TFAP2C in HCC1954 versus SKBR3. Hence, RNA-seq analysis was performed in SKBR3 after knockdown of TFAP2C with siRNA; in this analysis, a total of 3814 genes were significantly altered. The pattern of expression for the 152 AP-2gamma target genes identified in HCC1954 was subsequently compared to expression changes in SKBR3. Of note, only 79 of the 152 TFAP2C target genes in HCC1954 were found to change expression significantly in the RNA-seq data set from SKBR-3. Conclusions: Knockdown of TFAP2C with co-knockdown of CDH5 in SKBR-3 confirmed no significant effect on invasion, though there was a slight reduction in invasiveness with knockdown of CDH5 that failed to reach statistical significance (p=0.12). These findings support the conclusion that regulation of CDH5 and CDKN1A contribute to alterations of proliferation and invasiveness induced by knockdown of TFAP2C.
2020-04-13 | GSE126894 | GEO
Project description:A TFAP2C Gene Signature is Predictive of Outcome in HER2 Breast Cancer (RNA-Seq)
| PRJNA523613 | ENA
Project description:The AP-2γ transcription factor, encoded by the TFAP2C gene, regulates the expression of estrogen receptor-alpha (ERα) and other genes associated with hormone response in luminal breast cancer. Little is known about the role of AP-2γ in other breast cancer subtypes. A subset of HER2+ breast cancers with amplification of the TFAP2C gene locus becomes addicted to AP-2γ. Herein, we sought to define AP-2γ gene targets in HER2+ breast cancer and identify genes accounting for physiologic effects of growth and invasiveness regulated by AP-2γ. Comparing HER2+ cell lines that demonstrated differential response to growth and invasiveness with knockdown of TFAP2C, we identified a set of 68 differentially expressed target genes. CDH5 and CDKN1A were among the genes differentially regulated by AP-2γ and that contributed to growth and invasiveness. Pathway analysis implicated the MAPK13/p38δ and retinoic acid regulatory nodes, which were confirmed to display divergent responses in different HER2+ cancer lines. To confirm the clinical relevance of the genes identified, the AP-2γ gene signature was found to be highly predictive of outcome in patients with HER2+ breast cancer. We conclude that AP-2γ regulates a set of genes in HER2+ breast cancer that drive cancer growth and invasiveness. The AP-2γ gene signature predicts outcome of patients with HER2+ breast cancer and pathway analysis predicts that subsets of patients will respond to drugs that target the MAPK or retinoic acid pathways. IMPLICATIONS: A set of genes regulated by AP-2γ in HER2+ breast cancer that drive proliferation and invasion were identified and provided a gene signature that is predictive of outcome in HER2+ breast cancer.
| S-EPMC6942205 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-04-13 | GSE126898 | GEO
Project description:Purpose HER2 gene amplification or protein overexpression (HER2+) defines a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biological appearance and clinical behavior of HER2+ tumors using molecular profiling. Materials and Methods Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histological grade and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent breast cancer data sets. Results Unsupervised analysis identified three subtypes of HER2+ tumors with mixed stage, histological grade and ER-status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2+ breast cancer across multiple independent breast cancer data sets and identify a sizable HER2+ group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER−, lymph node positive or high-grade tumors, irrespective of HER2-status. The predictor included genes associated to immune response, tumor invasion and metastasis. Conclusion The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2+ tumors and may become useful for improved selection of patients that need additional treatment with new drugs targeting the HER2 pathway. Array comparative genomic hybridization (aCGH) identified 58 breast tumors with amplification of HER2 from a larger cohort of approx 500 tumors breast. Global gene expression profiles were obtained using 70-mer oligonucleotide microarrays. Unsupervised hierarchical clustering of the 58 tumors, using Pearson correlation and complete linkage, identified three main clusters. One cluster showed significantly poorer clinical outcome. Significance of microarray (SAM) analysis was performed to identify 158 genes separating the poor outcome cluster compared to the other two clusters. Gene expression centroids, based on the 158 genes, were created for each cluster for validation in independent breast cancer data sets.
2010-03-16 | E-GEOD-18328 | biostudies-arrayexpress
Project description:Purpose HER2 gene amplification or protein overexpression (HER2+) defines a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. We aimed to investigate the heterogeneous biological appearance and clinical behavior of HER2+ tumors using molecular profiling. Materials and Methods Hierarchical clustering of gene expression data from 58 HER2-amplified tumors of various stage, histological grade and estrogen receptor (ER) status was used to construct a HER2-derived prognostic predictor that was further evaluated in several large independent breast cancer data sets. Results Unsupervised analysis identified three subtypes of HER2+ tumors with mixed stage, histological grade and ER-status. One subtype had a significantly worse clinical outcome. A prognostic predictor was created based on differentially expressed genes between the subtype with worse outcome and the other subtypes. The predictor was able to define patient groups with better and worse outcome in HER2+ breast cancer across multiple independent breast cancer data sets and identify a sizable HER2+ group with long disease-free survival and low mortality. Significant correlation to prognosis was also observed in basal-like, ER−, lymph node positive or high-grade tumors, irrespective of HER2-status. The predictor included genes associated to immune response, tumor invasion and metastasis. Conclusion The HER2-derived prognostic predictor provides further insight into the heterogeneous biology of HER2+ tumors and may become useful for improved selection of patients that need additional treatment with new drugs targeting the HER2 pathway.
2010-03-16 | GSE18328 | GEO
Project description:Assessment of tumor pathological and transcriptional biomarkers in pre- and on-treatment core biopsies predictive of response and outcome after neoadjuvant chemotherapy plus Bevacizumab in patients with HER2-negative breast cancer: Results from a multi-center, single-arm, phase 2 study (the PROMIX trial) Global gene expression profiling was performed on samples from 3 time points (baseline, after 2 cycles and surgery) from women with breast cancer receivcing neoadjuvant chemotherapy with bevacizumab in a phase 2 trial
2017-09-01 | GSE87455 | GEO
Project description:The complexity of gene regulation has created obstacles to defining mechanisms that establish the patterns of gene expression characteristic of the different clinical phenotypes of breast cancer. Transcription factor TFAP2C plays a critical role in the regulation of both estrogen receptor-alpha (ERM-NM-1) and c-ErbB2/HER2 (Her2). Herein, we performed chromatin immunoprecipitation and direct sequencing (ChIP-seq) for TFAP2C in four breast cancer cell lines representing different clinical phenotypes. Comparing the genomic binding sites for TFAP2C in the various cell lines, we identified that glutathione peroxidase (GPX1) is regulated by TFAP2C through an AP-2 regulatory region in the promoter of the GPX1 gene. Knock-down of TFAP2C, but not the related factor TFAP2A, resulted in an abrogation of GPX1 expression. Selenium-dependent GPX activity correlated with endogenous GPX1 expression, and overexpression of exogenous GPX1 induced GPX activity and significantly increased resistance to tert-butyl hydroperoxide. Methylation of the CpG island encompassing the AP-2 regulatory region was identified in cell lines where TFAP2C failed to bind the GPX1 promoter and GPX1 expression was unresponsive to TFAP2C. Furthermore, in cell lines where GPX1 promoter methylation was associated with gene silencing, treatment with 5-aza-dC (an inhibitor of DNA methylation) resulted in activation of GPX1 RNA and protein expression. Methylation of the GPX1 promoter was identified in approximately 20% of primary breast cancers and a highly significant correlation between TFAP2C and GPX1 expression was confirmed when considering only those tumors with an unmethylated promoter, whereas the related factor, TFAP2A, failed to demonstrate a correlation. The results demonstrate that TFAP2C regulates the expression of GPX1, which influences the redox state and sensitivity to oxidative stress induced by peroxides. Given the established role of GPX1 in breast cancer, the results provide an important mechanism for TFAP2C to further influence oncogenesis and progression of breast carcinoma cells. 4 ChIP-Seq data for TFAP2C in human breast carcinoma cell lines MCF-7, BT-474, MDA-MB-453 and SKBR-3.
2012-09-12 | E-GEOD-36351 | biostudies-arrayexpress