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SIDRA

GXB

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Description

Node Negative, ER-

Purpose

The association between large tumor size and metastatic risk in a majority of clinical cancers has led to questions as to whether these observations are causally related or whether one is simply a marker for the other. The aim of this study was to investigate this question through the analysis of a previously defined “lung metastasis gene-expression signature” (LMS) that mediates experimental breast cancer metastasis selectively to the lung and is expressed by primary human breast cancer with a high risk for developing lung metastasis.

Hypothesis

The hypothesis of this study was that the LMS could provide a mechanistic link between metastasis gene expression, accelerated tumor growth, and likelihood of metastatic recurrence.

Experimental Design

This dataset contains 58 estrogen receptor-negative samples from a cohort of early stage node negative breast cancer patients. Tumour samples were selected from the tumour bank at the Erasmus Medical Center (Rotterdam, Netherlands).

The complete EMC-344 cohort (as referred to by Minn et al) consists of an additional 286 samples as previously described by Wang et al (GEO accession number GSE2034).

Methods

Microarray analysis was performed with Affymetrix U133A.

Additional Information

Minn, Andy J., Gaorav P. Gupta, David Padua, Paula Bos, Don X. Nguyen, Dimitry Nuyten, Bas Kreike, et al. “Lung Metastasis Genes Couple Breast Tumor Size and Metastatic Spread.” Proceedings of the National Academy of Sciences of the United States of America 104, no. 16 (April 17, 2007): 6740–45. doi:10.1073/pnas.0701138104.

Wang, Yixin, Jan G. M. Klijn, Yi Zhang, Anieta M. Sieuwerts, Maxime P. Look, Fei Yang, Dmitri Talantov, et al. “Gene-Expression Profiles to Predict Distant Metastasis of Lymph-Node-Negative Primary Breast Cancer.” Lancet (London, England) 365, no. 9460 (February 19, 2005): 671–79. doi:10.1016/S0140-6736(05)17947-1.

Platform Affymetrix HG-U133A
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GSE5327_appended.meta.data_v1.csv

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