E-GEOD-50939 - Tumor Intrinsic Subtype is Reflected in Cancer-Adjacent Benign Tissue

Released on 30 April 2014, last updated on 3 June 2014
Homo sapiens
Samples (142)
Arrays (2)
Protocols (147)
Introduction: Overall survival of early-stage breast cancer (BC) patients is similar for those who undergo breast conserving therapy (BCT) and mastectomy, however, 10-15% of women undergoing BCT suffer ipsilateral breast tumor recurrence. The risk of recurrence may vary with age or breast cancer subtype. Understanding the gene expression of the cancer-adjacent tissue and/or stromal response to specific tumor subtypes is important for developing clinical strategies to reduce recurrence risk. Methods: We studied gene expression data in cancer-adjacent tissue from 158 BC patients. Complementary in vitro cocultures were used to study cell-cell communication between fibroblasts and specific breast cancer subtypes. Results: Our results suggest that intrinsic tumor subtypes are reflected in histologically normal cancer-adjacent tissue. Gene expression of cancer-adjacent tissues shows that triple negative (Claudin-low or Basal-like tumors) exhibit increased expression of genes involved in inflammation and immune response. While such changes could reflect distinct immune populations present in the microenvironment of different breast cancer subtypes, altered immune response gene expression was also observed in cocultures in the absence of immune cell infiltrates, emphasizing that these inflammatory mediators are secreted by breast-specific cells. In addition, while triple negative BCs are associated with upregulated immune response genes, Luminal breast cancers are more commonly associated with estrogen-response in adjacent tissues. Conclusions: Specific characteristics of BCs are reflected in the surrounding benign tissue. This commonality between tumor and surrounding tissue may underlie second primaries and local recurrences. Biomarkers derived from cancer-adjacent tissue may be helpful in defining personalized surgical strategies or in predicting recurrence risk. reference x sample
Experiment type
transcription profiling by array 
Melissa Troester <troester@unc.edu>, Melissa A Troester, Patricia Casbas-Hernandez
Investigation descriptionE-GEOD-50939.idf.txt
Sample and data relationshipE-GEOD-50939.sdrf.txt
Processed data (1)E-GEOD-50939.processed.1.zip
Array designsA-AGIL-28.adf.txt, A-GEOD-16272.adf.txt