Gene expression, molecular class changes, and pathway analysis after neoadjuvant systemic therapy for breast cancer

AM Gonzalez-Angulo, T Iwamoto, S Liu, H Chen… - Clinical Cancer …, 2012 - AACR
AM Gonzalez-Angulo, T Iwamoto, S Liu, H Chen, KA Do, GN Hortobagyi, GB Mills
Clinical Cancer Research, 2012AACR
Purpose: To examine gene expression differences between pre-and post-neoadjuvant
systemic therapy (NST) specimens of breast cancers and identify biologic changers that may
lead to new therapeutic insights. Methods: Gene expression data from prechemotherapy fine
needle aspiration specimens were compared with resected residual cancers in 21 patients
after 4 to 6 months of NST. We removed stroma-associated genes to minimize confounding
effects. PAM50 was used to assign molecular class. Paired t test and gene set analysis were …
Abstract
Purpose: To examine gene expression differences between pre- and post-neoadjuvant systemic therapy (NST) specimens of breast cancers and identify biologic changers that may lead to new therapeutic insights.
Methods: Gene expression data from prechemotherapy fine needle aspiration specimens were compared with resected residual cancers in 21 patients after 4 to 6 months of NST. We removed stroma-associated genes to minimize confounding effects. PAM50 was used to assign molecular class. Paired t test and gene set analysis were used to identify differentially expressed genes and pathways.
Results: The ER and HER2 status based on mRNA expression remained stable in all but two cases, and there were no changes in proliferation metrics (Ki67 and proliferating cell nuclear antigen expression). Molecular class changed in 8 cases (33.3%), usually to normal-like class, which was associated with low residual cancer cell cellularity. The expression of 200 to 600 probe sets changed between baseline and post-NST samples. In basal-like cancers, pathways driven by increased expression of phosphoinositide 3-kinase, small G proteins, and calmodulin-dependent protein kinase II and energy metabolism were enriched, whereas immune cell–derived and the sonic hedgehog pathways were depleted in residual cancer. In non–basal-like breast cancers, notch signaling and energy metabolism (e.g., fatty acid synthesis) were enriched and sonic hedgehog signaling and immune-related pathways were depleted in residual cancer. There was no increase in epithelial–mesenchymal transition or cancer stem cell signatures.
Conclusions: Our data indicate that energy metabolism related processes are upregulated and immune-related signals are depleted in residual cancers. Targeting these biologic processes may represent promising adjuvant treatment strategies for patients with residual cancer. Clin Cancer Res; 18(4); 1109–19. ©2012 AACR.
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