Identification of functional networks of estrogen- and c-Myc-responsive genes and their relationship to response to tamoxifen therapy in breast cancer.
BACKGROUND
Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance.


RESULTS
With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures.


CONCLUSIONS
These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance.
Musgrove
Elizabeth A
EA
Cancer Research Program, Garvan Institute of Medical Research, Sydney, Australia. e.musgrove@garvan.org.au
Sergio
C Marcelo
CM
Loi
Sherene
S
Inman
Claire K
CK
Anderson
Luke R
LR
Alles
M Chehani
MC
Pinese
Mark
M
Caldon
C Elizabeth
CE
Schütte
Judith
J
Gardiner-Garden
Margaret
M
Ormandy
Christopher J
CJ
McArthur
Grant
G
Butt
Alison J
AJ
Sutherland
Robert L
RL
D018931:Antineoplastic Agents, Hormonal / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000188:drug therapy* / Q000235:genetics* / Q000473:pathology; D002453:Cell Cycle; D016923:Cell Death; D045744:Cell Line, Tumor; D004273:DNA, Neoplasm / Q000235:genetics; D004967:Estrogens / Q000502:physiology*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D016259:Genes, myc; D006801:Humans; D016271:Proto-Oncogene Proteins c-myc / Q000502:physiology*; D012044:Regression Analysis; D013629:Tamoxifen / Q000627:therapeutic use*; D014158:Transcription, Genetic / Q000187:drug effects; D016896:Treatment Outcome
D018931:Antineoplastic Agents, Hormonal; D004273:DNA, Neoplasm; D004967:Estrogens; D016271:Proto-Oncogene Proteins c-myc; D013629:Tamoxifen