Gene expression profiles of breast cancer metastasis according to organ site
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE175692 | GEO | 2021/05/28
REPOSITORIES: GEO
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Project description:The ability to predict metastatic potential is of clinical and biological importance. Numerous metastasis/relapse predictors exist for breast cancer patients; however, what is less well established is whether predicting metastasis to specific organs sites is feasible. In this study we sought to determine: 1) the degree to which gene signatures vary across tumors and their metastases, 2) if genomic intrinsic subtypes associate with particular organs of relapse, and 3) if other genomic signatures can predict spread to specific organs. Using a gene expression microarray data set of >1000 breast tumors and metastases, we observed that >90% of 298 gene signatures were similarly expressed between matched pairs of breast tumors and metastases; those most altered were reflective of cell types including fibroblasts and immune cells. Significant associations were identified between tumor subtypes and organ of first relapse. Among these, HER2-enriched tumors were significantly associated with liver, and Basal-like and Claudin-low tumors with brain and lung. Correspondingly, previously published brain and lung metastasis signatures, along with embryonic stem cell and tumor initiating cell signatures, were also associated with Basal-like and Claudin-low subtypes. These signatures strongly correlated with low Differentiation Scores (DS) and, to a lesser extent, high proliferation. Interestingly, within Basal-like and Claudin-low tumors, low DS further predicted for brain and lung metastases. In total, intrinsic subtype and DS provide clinically useful information that identifies the distant organ sites that should be most closely monitored for signs of disease recurrence. 414 samples profiled on Agilent microarrays.
2011-06-20 | E-GEOD-26338 | biostudies-arrayexpress
Project description:The ability to predict metastatic potential is of clinical and biological importance. Numerous metastasis/relapse predictors exist for breast cancer patients; however, what is less well established is whether predicting metastasis to specific organs sites is feasible. In this study we sought to determine: 1) the degree to which gene signatures vary across tumors and their metastases, 2) if genomic intrinsic subtypes associate with particular organs of relapse, and 3) if other genomic signatures can predict spread to specific organs. Using a gene expression microarray data set of >1000 breast tumors and metastases, we observed that >90% of 298 gene signatures were similarly expressed between matched pairs of breast tumors and metastases; those most altered were reflective of cell types including fibroblasts and immune cells. Significant associations were identified between tumor subtypes and organ of first relapse. Among these, HER2-enriched tumors were significantly associated with liver, and Basal-like and Claudin-low tumors with brain and lung. Correspondingly, previously published brain and lung metastasis signatures, along with embryonic stem cell and tumor initiating cell signatures, were also associated with Basal-like and Claudin-low subtypes. These signatures strongly correlated with low Differentiation Scores (DS) and, to a lesser extent, high proliferation. Interestingly, within Basal-like and Claudin-low tumors, low DS further predicted for brain and lung metastases. In total, intrinsic subtype and DS provide clinically useful information that identifies the distant organ sites that should be most closely monitored for signs of disease recurrence.
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Project description:Breast cancer is a profoundly heterogeneous disease with respect to biological and clinical behavior. Gene expression profiling has been used to dissect this complexity and stratify tumors into intrinsic gene expression subtypes associated with distinct biology, patient outcome and different genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. We applied global DNA copy number and gene expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy number aberrations and genomic subgroups of breast cancer. We identified 31 genomic regions that were highly amplified in >1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions (66 and 67 with DNA copy number gain and loss, respectively) revealed six genomic subtypes, termed: 17q12, basal-complex, luminal-simple, luminal-complex, amplifier and mixed subtype. Four of them had striking similarity to intrinsic gene expression subtypes and showed association to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having better prognosis while the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene expression subtypes, the former being enriched for 8p12-amplified cases while the mixed subtype included many tumors with predominantly DNA copy number losses and poor prognosis.
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