Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Identifying breast cancer biomarkers

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Francisco Lopez

PROVIDER: E-GEOD-29431 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Current clinical guidelines suggest that breast cancers with low hormone receptor expression (LowHR) in 1% to 10% of tumor cells should be regarded as hormone receptor positive tumors. However, clinical data shows that patients with such tumors have a worse outcome compared to patients with hormone receptor expression above 10 %. Further, gene expression studies suggest that these tumors have a TNBC-like signature similar to triple negative breast cancers (TNBC). The goal of this study was to use DNA methylation-based classification to clarify the status for this infrequent but important patient subgroup. We performed whole genome DNA methylation profiling on 23 LowHR breast cancer specimens, including 13 samples with HER2 amplification and compared our results with a reference breast cancer cohort from The Cancer Genome Atlas. Unsupervised clustering and dimensionality reduction revealed that breast cancers with low hormone receptor expression that lacked HER2 amplification usually clustered with TNBC reference samples (8/10; “LowHR TNBC-like”). In contrast, most specimens with low hormone receptor expression and HER2 amplification grouped with hormone receptor positive cancers (11/13; “LowHR HRpos-like”). We observed highly similar DNA methylation patterns of LowHR TNBC-like samples and true TNBCs with almost no differential methylation. Furthermore, the Ki67 proliferation index of LowHR TNBC-like samples as well as clinical outcome parameters were more similar to TNBCs and differed from LowHR_HRpos-like cases. We here demonstrate that LowHR breast cancer comprises two molecularly distinct groups that can be separated by DNA methylation profiling. More clinical data is required for a definite classification of these tumors, but our data strongly suggests that LowHR TNBC-like samples are molecularly, histologically and clinically closely related to TNBC, while LowHR HRpos-like specimens are closely related to hormone receptor positive tumors.

Dataset Information

Identifying breast cancer biomarkers

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets