Homo sapiens
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PROVIDER: PRJNA263956 | ENA |
REPOSITORIES: ENA
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Project description:Intra-tumor genetic heterogeneity in breast cancers with heterogeneous HER2 gene amplification
| PRJNA281183 | ENA
Project description:We separately analyzed the HER2-negative and HER2-positive components of 12 HER2 heterogeneous breast cancers using gene copy number profiling and massively parallel sequencing, and identified potential driver genetic alterations restricted to the HER2-negative cells in each case. Our results indicate that even driver genetic alterations, such as HER2, can be heterogeneously distributed in a cancer, and that the HER2-negative components are likely driven by genetic alterations not present in the HER2-positive components, including BRF2 and DSN1 amplification.
2015-04-16 | GSE67908 | GEO
Project description:HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group. Genome-wide DNA copy number profiling, using BAC array comparative genomic hybridization (aCGH) were performed on 200 tumors with mixed clinical characteristics and amplification of HER2. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number aberrations (CNAs) in HER2+ tumors. This analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer.
2010-04-14 | GSE21259 | GEO
Project description:<p>HER2 (ERBB2) gene amplification and overexpression are present in 15-30% of invasive breast cancers. While HER2-targeted agents such as trastuzumab are effective treatments, therapeutic resistance remains a concern in HER2-positive breast cancer with 40-50% of patients having residual disease after neoadjuvant treatment with chemotherapy and trastuzumab.</p> <p>To investigate features that may make it possible to predict at diagnosis which cancers will be responsive to trastuzumab and chemotherapy, 48 tumor/normal DNA pairs extracted from pretreatment tumor biopsies and blood of HER2-positive breast cancer cases treated with neoadjuvant chemotherapy and trastuzumab were sequenced. Whole genome and exome sequence from tumor (average depth 49x and 71x) and normal (average depth 33x and 69x) DNA are included here as well as RNAseq data for 42 of the tumors. The study cohort was equally divided between patients who experienced pathological complete response and those with residual disease.</p> <p>Samples were obtained from the American College of Surgeons Oncology Group Z1041 trial (NCT00513292) and a local single-institution study (NCT00353483).</p>
| phs001291 | dbGaP
Project description:HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group. Genome-wide DNA copy number profiling, using BAC array comparative genomic hybridization (aCGH) were performed on 200 tumors with mixed clinical characteristics and amplification of HER2. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number aberrations (CNAs) in HER2+ tumors. This analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer. Genomic profiling of 200 breast tumors using tiling BAC aCGH (32K, 33K and 38K). A number of cases were hybridized as replicates or dye-swaps.
2010-04-14 | E-GEOD-21259 | biostudies-arrayexpress
Project description:Background: Breast cancer is a heterogeneous neoplasm. Distinct subtypes of breast cancer have been defined, suggesting the existence of molecular differences contributing to their clinical outcomes. However, the molecular differences between HER2 positive and negative breast cancer tumors remain unclear. Objective: The aim of this study was to identify a gene expression profile for breast tumors based on HER2 status. Material and methods: The HER2 status was determined by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) in 54 breast tumor samples. Using Affymetrix microarray data from these breast tumors, we established the expression profiling of breast cancer based on HER2 IHC and FISH results. To validate microarray experiment data, real-time quantitative reverse transcription-PCR was performed. Results: We found significant differences between the HER2-positive and HER2-negative breast tumor samples, which included overexpression of HER2, as well as other genes located on 17q12, and genes functionally related to migration. Conclusion: Our study shows the potential of integrated genomics profiling to shed light on the molecular knowledge of HER2-positive breast tumors. The tumor samples under study correspond to 54 primary breast carcinomas. They included 15 cases with a HER2 IHC3+ score with HER2 gene amplification, 13 cases with IHC2+ score with amplification and 13 without HER2 gene amplification, and 13 cases IHC0/1+ score without HER2 gene amplification. 12 samples of breast normal tissues from breast cancer patients were also included as a reference. Neither overexpression nor amplification of HER2 was observed.
2011-12-22 | E-GEOD-29431 | biostudies-arrayexpress
Project description:Lymph node status is a crucial predictor for the overall survival of invasive breast cancer. However, lymph node involvement is only detected in about half of HER2 positive patients. Currently, there are no biomarkers available for distinguishing small size HER2-positive breast cancers with different lymph node statuses. Thus, in the present study, we applied label-free quantitative proteomic strategy to construct plasma proteomic profiles of ten patients with small size HER2-positive breast cancers (5 patients with lymph node metastasis versus 5 patients with lymph node metastasis).
2018-02-08 | PXD007217 | Pride
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:Hormones and growth factors accelerate cell proliferation of breast cancer cells, and these molecules are well investigated targets for drug development and application. The mechanisms of cell proliferation of breast cancers lacking estrogen receptor (ER) and HER2 have not been fully understood. The purpose of the present study is to find genes that are differentially expressed in breast cancers and that might significantly contribute to cell proliferation in these cancers. Forty tumor samples, consisting of ten each of immunohistochemically ER(+)/HER2(-), ER(+)/HER2(+), ER(-)/HER2(+), and ER(-)/HER2(-) cancer were analyzed using oligonucleotide microarrays. Both genes and tumor samples were subjected to hierarchical clustering. ER(+)/HER2(-) breast cancers and ER(-)/HER2(-) cancers tended to form a tumor cluster, but HER2 positive breast cancers were split into different tumor clusters. Significant differential expression between IHC-ER(-)/HER2(-) and other tumors was defined as having an expression level at least 2-fold higher or 2-fold lower, and analyzed by multi-step two-way ANOVA. Genes overexpressed differently in IHC-ER(-)/HER2(-) breast cancers compared to other all three types were 8 genes (FABP7, GABRP, GAL, CXCL13, CDC42EP4, C2F, FOXM1, CSDA), and underexpressed genes were nine including ITGB5, KIAA0310, MAGED2, PRSS11, SORL1, TGFB3, KRT18, CPE, BCAS1. No gene was directly related to cell proliferation such as cyclins, cyclin-dependent kinase, p53, p16, and the pRb and p21 families. We had a particular focus on a transcriptional factor E2F-5 from a list of genes overexpressed in ER negative breast cancers compared to ER positive breast cancers, and further examined. Gene amplification of E2F-5 was detected in 5/57 (8.8%) in breast cancers by FISH. No point mutation was found at the binding domain with DNA or dimerization partner of E2F-5. Immunohistochemically E2F-5 positive cancers were more frequent in ER(-)/HER2(-) cancer (14/27, 51.9%) than in other types of cancer (5/30, 16.7%) (p=0.05). E2F-5 positive cancers had higher Ki-67 labeling index (59.5%) than E2F-5 negative cancers (36.3%). E2F-5 positive cancers showed higher histological grade including metaplastic carcinoma, and worse clinical outcome with shorter disease free survival in node negative patients. In conclusion, we demonstrated that there is a population of breast cancer with overexpression of a cell cycle related transcriptional factor E2F-5. E2F-5 positive breast cancers were frequent in ER(-)/HER2(-) group with high Ki-67 labeling index, high histological grade and worse clinical outcome. Keywords: immunohistochemical phenotype
2009-03-14 | GSE6367 | GEO
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