Dataset Information

Development and validation of a novel platform-independent metastasis signature in human breast cancer.

ABSTRACT:

Purpose

The molecular drivers of metastasis in breast cancer are not well understood. Therefore, we sought to identify the biological processes underlying distant progression and define a prognostic signature for metastatic potential in breast cancer.

Experimental design

In vivo screening for metastases was performed using Chick Chorioallantoic Membrane assays in 21 preclinical breast cancer models. Expressed genes associated with metastatic potential were identified using high-throughput analysis. Correlations with biological function were determined using the Database for Annotation, Visualization and Integrated Discovery.

Results

We identified a broad range of metastatic potential that was independent of intrinsic breast cancer subtypes. 146 genes were significantly associated with metastasis progression and were linked to cancer-related biological functions, including cell migration/adhesion, Jak-STAT, TGF-beta, and Wnt signaling. These genes were used to develop a platform-independent gene expression signature (M-Sig), which was trained and subsequently validated on 5 independent cohorts totaling nearly 1800 breast cancer patients with all p-values < 0.005 and hazard ratios ranging from approximately 2.5 to 3. On multivariate analysis accounting for standard clinicopathologic prognostic variables, M-Sig remained the strongest prognostic factor for metastatic progression, with p-values < 0.001 and hazard ratios > 2 in three different cohorts.

Conclusion

M-Sig is strongly prognostic for metastatic progression, and may provide clinical utility in combination with treatment prediction tools to better guide patient care. In addition, the platform-independent nature of the signature makes it an excellent research tool as it can be directly applied onto existing, and future, datasets.

SUBMITTER: Zhao SG

PROVIDER: S-EPMC4431866 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and validation of a novel platform-independent metastasis signature in human breast cancer.

Zhao Shuang G SG Shilkrut Mark M Speers Corey C Liu Meilan M Wilder-Romans Kari K Lawrence Theodore S TS Pierce Lori J LJ Feng Felix Y FY

PloS one 20150514 5

<h4>Purpose</h4>The molecular drivers of metastasis in breast cancer are not well understood. Therefore, we sought to identify the biological processes underlying distant progression and define a prognostic signature for metastatic potential in breast cancer.<h4>Experimental design</h4>In vivo screening for metastases was performed using Chick Chorioallantoic Membrane assays in 21 preclinical breast cancer models. Expressed genes associated with metastatic potential were identified using high-th ...[more]

PMID: 25974184

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Dataset Information

Development and validation of a novel platform-independent metastasis signature in human breast cancer.

Purpose

Experimental design

Results

Conclusion

Publications

Development and validation of a novel platform-independent metastasis signature in human breast cancer.

Similar Datasets

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