Patterns and changes in gene expression following neo-adjuvant anti-estrogen treatment in estrogen receptor-positive breast cancer

2008 ◽  
Vol 15 (2) ◽  
pp. 439-449 ◽  
Author(s):  
V. Cappelletti ◽  
M. Gariboldi ◽  
L. De Cecco ◽  
S. Toffanin ◽  
J. F Reid ◽  
...  
2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Qiong Gao ◽  
Elena López-Knowles ◽  
Maggie Chon U Cheang ◽  
James Morden ◽  
Ricardo Ribas ◽  
...  

Abstract To investigate the impact of sampling methodology on gene expression data from primary estrogen receptor–positive (ER+) breast cancer biopsies, global gene expression was measured in core-cut biopsies at baseline and surgery from patients randomly assigned to receive either two weeks of presurgical aromatase inhibitor (AI; n = 157) or no presurgical treatment (n = 56). Those genes most markedly altered in the AI group (eg, FOS, DUSP1, RGS1, FOSB) were similarly altered in the no treatment group; some widely investigated genes that were apparently unaffected in the AI group (eg, MYC) were counter-altered in the control group, masking actual AI-dependent changes. In the absence of a control group, these artefactual changes would likely lead to the most affected genes being the erroneous focus of research. The findings are likely relevant to all archival collections of ER+ breast cancer.


2017 ◽  
Vol 06 (03) ◽  
Author(s):  
Gayatri Devi V ◽  
Anil Kuman Badana ◽  
Madhuri Ch ◽  
Murali Mohan P ◽  
Shailandra Naik ◽  
...  

Author(s):  
Xianxiong Ma ◽  
Hengyu Chen ◽  
Ming Yang ◽  
Zunxiang Ke ◽  
Mengyi Wang ◽  
...  

Background: The aim of this paper was to identify an immunotherapy-sensitive subtype for estrogen receptor-positive breast cancer (ER+ BC) patients by exploring the relationship between cancer genetic programs and antitumor immunity via multidimensional genome-scale analyses.Methods: Multidimensional ER+ BC high-throughput data (raw count data) including gene expression profiles, copy number variation (CNV) data, single-nucleotide polymorphism mutation data, and relevant clinical information were downloaded from The Cancer Genome Atlas to explore an immune subtype sensitive to immunotherapy using the Consensus Cluster Plus algorithm based on multidimensional genome-scale analyses. One ArrayExpress dataset and eight Gene Expression Omnibus (GEO) datasets (GEO-meta dataset) as well as the Molecular Taxonomy of Breast Cancer International Consortium dataset were used as validation sets to confirm the findings regarding the immune profiles, mutational features, and survival outcomes of the three identified immune subtypes. Moreover, the development trajectory of ER+ BC patients from the single-cell resolution level was also explored.Results: Through comprehensive bioinformatics analysis, three immune subtypes of ER+ BC (C1, C2, and C3, designated the immune suppressive, activation, and neutral subtypes, respectively) were identified. C2 was associated with up-regulated immune cell signatures and immune checkpoint genes. Additionally, five tumor-related pathways (transforming growth factor, epithelial–mesenchymal transition, extracellular matrix, interferon-γ, and WNT signaling) tended to be more activated in C2 than in C1 and C3. Moreover, C2 was associated with a lower tumor mutation burden, a decreased neoantigen load, and fewer CNVs. Drug sensitivity analysis further showed that C2 may be more sensitive to immunosuppressive agents.Conclusion: C2 (the immune activation subtype) may be sensitive to immunotherapy, which provides new insights into effective treatment approaches for ER+ BC.


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