Dataset Information

Pathway-based analysis of breast cancer.

ABSTRACT:

Introduction

Although HER2 and ER pathways are predominant pathways altered in breast cancer, it is now well accepted that many other signaling pathways are also involved in the pathogenesis of breast cancer. The understanding of these additional pathways may assist in identifying new therapeutic approaches for breast cancer.

Methods

13 invasive ductal carcinoma tissues and 5 benign breast tissues were analyzed for the mRNA expression level of 1243 cancer pathway-related genes using SmartChip (WaferGen, CA), a real-time PCR-base method. In addition, the levels of 131 cancer pathway-related proteins and phosphoproteins in 33 paired breast cancers were measured using our innovative Protein Pathway Array.

Results

Out of 1,243 mRNAs, 68.7% (854) were detected in breast cancer and 395 mRNAs were statistically significant (fold change >2) between benign and cancer tissues. Of these mRNAs, 105 only expressed in breast cancer tissues and 33 mRNAs only expressed in normal breast tissues. Out of 131 proteins and phosphoproteins, 68% (89) were detected in cancer tissues and 57 proteins were significantly differentiated between tumor and normal tissues. Interestingly, only 3 genes (CDK6, Vimentin and SLUG) showed decreases in both protein and mRNA. Six proteins (BCL6, CCNE1, PCNA, PDK1, SRC and XIAP) were differentially expressed between tumor and normal tissues but no differences were observed at mRNA levels. Analyses of mRNA and protein data using Ingenuity Pathway Analysis showed more than 15 pathways were altered in breast cancer and 6 of which were shared between mRNAs and proteins, including p53, IL17, HGF, NGF, PTEN and PI3K/AKT pathways.

Conclusions

There is a broad dysregulation of various pathways in breast cancer both at protein levels and mRNA levels. It is important to note that mRNA expression does not correlate with protein level, suggesting different regulation mechanisms between proteins and mRNAs.

SUBMITTER: Song D

PROVIDER: S-EPMC4058311 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Pathway-based analysis of breast cancer.

Song Dong D Cui Miao M Zhao Gang G Fan Zhimin Z Nolan Katherine K Yang Ying Y Lee Peng P Ye Fei F Zhang David Y DY

American journal of translational research 20140515 3

<h4>Introduction</h4>Although HER2 and ER pathways are predominant pathways altered in breast cancer, it is now well accepted that many other signaling pathways are also involved in the pathogenesis of breast cancer. The understanding of these additional pathways may assist in identifying new therapeutic approaches for breast cancer.<h4>Methods</h4>13 invasive ductal carcinoma tissues and 5 benign breast tissues were analyzed for the mRNA expression level of 1243 cancer pathway-related genes usi ...[more]

PMID: 24936222

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Project description:Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions.

Dataset Information

Pathway-based analysis of breast cancer.

Introduction

Methods

Results

Conclusions

Publications

Pathway-based analysis of breast cancer.

Similar Datasets

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