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PDF file - 556KB, Supplementary Figure 1a: Overview of pre-surgical studies: Fulvestrant (NEWEST), detailing study design (i) and samples (ii). S1b: Anastrozole (FAIMoS), detailing study design (i) and samples (ii). S1c: Summary of patient demographics and tumour characteristics for NEWEST and FAIMoS; Supplementary Figure 2ai: Spearman correlations between fulvestrant (F) and E-deprivation (ED) related and specific genes, selected proliferation-associated and E-regulated index genes in pre-treatment samples from NEWEST (n=22). Direct correlations are indicated in red and inverse correlations in green, with their strength reflected by colour intensity. S2aii: Spearman correlations between fulvestrant (F) and E-deprivation (ED) related and specific genes, selected proliferation-associated and E-regulated index genes in pre-treatment samples from FAIMoS (n=81). Direct correlations are indicated in red and inverse correlations in green, with their strength reflected by colour intensity. Supplementary Figure 2b: Summary of Spearman correlations between up-regulated (n=13) and down-regulated (n=28) genes which were fulvestrant-related (n=41), AURKA and ESR1, in pre-treatment in samples from (i) NEWEST and (ii) FAIMoS. Supplementary Figure 3a/b: mpact of ESR1 knockdown with an siRNA SMARTpool and four constituent oligonucleotides (a), on the mRNA expression of genes differentially down-regulated by fulvestrant (b). S3c: Impact of ESR1 knockdown with an siRNA SMARTpool and four constituent oligonucleotides (a), on the mRNA expression of genes differentially up-regulated by fulvestrant (c).

Purpose: To investigate potential associations between gene modules representing key biologic processes and response to aromatase inhibitors (AI) in estrogen receptor–positive (ER+) breast cancer.Patients and Methods: Paired gene expression and Ki67 protein expression were available from 69 postmenopausal women with ER+ early breast cancer, at baseline and 2 weeks post-anastrozole treatment, in the presurgical setting. Functional gene modules (n = 26) were retrieved from published studies and their module scores were computed before and after elimination of proliferation-associated genes (PAG). Ki67 and module scores were assessed at baseline and 2 weeks post-anastrozole. Unsupervised clustering was used to assess associations between modules and Ki67.Results: Proliferation-based modules were highly correlated with Ki67 expression both pretreatment and on-treatment. At baseline with and without PAGs, Ki67 expression was significantly inversely correlated with ERG, ESR1.2, SET, and PIK3CA modules. Modules measuring estrogen signaling strongly predicted antiproliferative response to therapy with and without PAGs. Baseline expression of insulin-like growth factor-1 (IGF-I) module predicted a poor change in Ki67-implicating genes within the module as involved in de novo resistance to AIs. High expression of Immune.2.STAT1 module pretreatment predicted poor antiproliferative response to therapy. A significant association between estrogen-regulated genes modules (ESR1, ESR1-2, SET, and ERG) was evident post AI.Conclusions: Multiple processes and pathways are affected by AI treatment in ER+ breast cancer. Modules closely associated with ESR1 expression were predictive of good antiproliferative response to AIs, but modules representing immune activity and IGF-I/MAPK were predictive of poor Ki67 response, supporting their therapeutic targeting in combination with AIs. Clin Cancer Res; 20(9); 2485–94. ©2014 AACR.

Spearman Rank Correlation Matrix (rho and p-value) of expression change in Gene Module Scores and Ki67, ∆log2Ki67 (log2(Ki67post) - log2(Ki67pre)). A: Including Proliferation-Associated Genes. B: Excluding Proliferation-Associated Genes.

PDF file - 29KB

Purpose: The majority of breast cancer patients who have estrogen receptor positive (ER+) tumors whose proliferation is reduced after estrogen deprivation by aromatase inhibitors (AI). This study investigates any link between proliferation and hypoxia, a major determinant of tumor biology, and defines the effect of estrogen deprivation on hypoxia-associated genes.Methods: Genome-wide expression profiles were obtained from tumor biopsies from 81 ER+ postmenopausal patients, before and after 2 weeks' anastrozole treatment. A hypoxia metagene was developed by identifying genes clustered with classical hypoxia-regulated genes, excluding those associated with proliferation. Proliferation was measured by Ki67 and a proliferation metagene derived from two published breast cancer data sets.Results: Hypoxia and proliferation metagenes were associated at baseline (Pearson correlation coefficient, r = 0.67, P < 10−4) and after 2 weeks (r = 0.71, P < 10−4). Hypoxia metagene at baseline was associated with 2-week Ki67 (r = 0.43, P = 0.0002) and more weakly with poor 2-week Ki67 change consistent with a weak association with AI resistance. Hypoxia metagene was significantly downregulated with AI. This downregulation was significantly associated with change in the proliferation metagene and with Ki67 but, importantly, not with the substantial change in expression of classical estrogen-dependent genes.Conclusions: Hypoxia metagene is closely associated with proliferation before and after AI treatment. The downregulation of hypoxia metagene after AI therapy is most likely the result of changes in proliferation. There may be a weak effect of hypoxia metagene on de novo resistance to AIs. These findings are important to consider in coapplication of antiproliferative agents with antiangiogenic or antihypoxia agents. Clin Cancer Res; 17(9); 3005–12. ©2011 AACR.

PDF file - 109K, Derivation of samples for microarray analysis.

PDF file - 33KB, Impact of fulvestrant and E-deprivation on selected index proliferation-associated or E-regulated genes.

Purpose: Estrogen withdrawal by treatment with aromatase inhibitors is the most effective form of endocrine therapy for postmenopausal estrogen receptor–positive (ER+) breast cancer. However, response to therapy varies markedly and understanding of the precise molecular effects of aromatase inhibitors and causes of resistance is limited. We aimed to identify in clinical breast cancer those genes and pathways most associated with resistance to aromatase inhibitors by examining the global transcriptional effects of AI treatment.Experimental Design: Baseline and 2-week posttreatment biopsies were obtained from 112 postmenopausal women with ER+ breast cancer receiving neoadjuvant anastrozole. Gene expression data were obtained from 81 baseline and 2-week paired samples. Pathway analysis identified (i) the most prevalent changes in expression and (ii) the pretreatment genes/pathways most related to poor antiproliferative response.Results: A total of 1,327 genes were differentially expressed after 2-week treatment (false discovery rate < 0.01). Proliferation-associated genes and classical estrogen-dependent genes were strongly downregulated whereas collagens and chemokines were upregulated. Pretreatment expression of an inflammatory signature correlated with antiproliferative response to anastrozole and this observation was validated in an independent study. Higher expression of immune-related genes such as SLAMF8 and TNF as well as lymphocytic infiltration were associated with poorer response (P < 0.001) and validated in an independent cohort.Conclusions: The molecular response to aromatase inhibitor treatment varies greatly between patients consistent with the variable clinical benefit from aromatase inhibitor treatment. Higher baseline expression of an inflammatory signature is associated with poor antiproliferative response and should be assessed further as a novel biomarker and potential target for aromatase inhibitor-treated patients. Clin Cancer Res; 19(10); 2775–86. ©2013 AACR.

PDF file - 147KB, S7: Ingenuity based analysis of genes affected by E-deprivation: (a) In vitro and (b) FAIMoS (two weeks) detailing (i) canonical pathways (p

PDF file - 127KB, S9: Fold-changes and statistical significance of genes significantly and differentially affected by fulvestrant and E-deprivation in pre-surgical studies and in vitro models: (a) Up-regulated and (b) Down-regulated. Probes are annotated with gene symbols where available; S10: GO functional gene sets significantly and differentially affected by fulvestrant and E-deprivation in pre-surgical studies and in vitro models: (a) Up-regulated and (b) Down-regulated.

XLSX file - 250K, Excel file of differentially expressed and correlated genes.

PDF file - 87K, Lymphocytic infiltration in tumours.

PDF file - 58KB, S11: Summary of Spearman correlations between up-regulated (n=13) and down-regulated (n=28) genes which were fulvestrant-related (n=41), AURKA and ESR1, in pre-treatment in samples from (a) NEWEST and (b) FAIMoS; S12: Summary of treatment-related genes for which pre-treatment expression correlates significantly with treatment-induced changes in expression of the proliferation-associated gene AURKA: (a) High pre-treatment expression correlates with good response, (b) Low pre-treatment expression correlates with good response, and (c) high pre-treatment expression correlates with good response to low-dose fulvestrant. E-deprivation (ED), fulvestrant (F). Probes are annotated with gene symbols where available; S13: Impact of sixteen weeks of anastrozole on transcripts found to be specifically affected by fulvestrant: (a) Up-regulated and (b) Down-regulated.

Supplemental Figure Legend from Effect of Aromatase Inhibition on Functional Gene Modules in Estrogen Receptor–Positive Breast Cancer and Their Relationship with Antiproliferative Response

Supplemental Methods, Tables and Figures Tables Table S1. CES association with chemotherapy sensitivity (measured as pCR) in the MDACC-based dataset. Table S2. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model A. Table S3. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model B. Table S4. Univariate association of CES and various signatures with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S5. Association of CES and PAM50 Proliferation Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S6. Association of CES and CHEMOPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S7. Association of CES and the proliferation component of the Genomic Health Index (GHI; OncotypeDX Recurrence Score) with chemotherapy sensitivity in HR+/HER2- negative disease from the MDACC-based dataset. Table S8. Association of CES and Genomic Grade Index (GGI) Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S9. Association of CES and SET index Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S10. Association of CES and RCBPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S11. Association of CES and DLDA30 Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S12. Association of CES and ROR-P Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S13. Association of CES and Ki67 by IHC with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. 7 Table S14. Association of CES and PAM50 ROR with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. Table S15. CES association with endocrine sensitivity in the Marsden dataset (n=103). Table S16. CES association with endocrine sensitivity in the Marsden dataset within HER2-negative disease (n=89). Figures Fig. S1. Association of CES with Miller-Payne following chemotherapy in HR+/HER2- negative disease from the Malaga-based cohort. Fig. S2. CES association with endocrine sensitivity in the Edinburgh dataset (n=120). (A) Tumor volume changes of each patient and response classification. (B) Association of CES and other variables with response (defined as at least 70% reduction by 90 days) in the overall population. (C) Association of CES and other variables with response within HER2-negative disease. Fig. S3. Association of CES with pCR in the combined dataset from the MDACC- and Malaga-based cohorts.

PDF file - 826K, Clustering of the tumours based on immunohistochemical parameters.

Analysis results of assessing the effect of the impact of the gene expression of PAGs on FAIMoS dataset and their association with Ki67 protein expression.

PDF file - 46K, Prediction analysis of correlated genes.

PDF file - 68K, Multivariable analysis of inflammatory metagene, grade, ER H-score, baseline Ki67 and proportional change in Ki67.

PDF file - 44K, Patient demographics.

Supplementary Figure S1; Supplementary Tables S1-S6.

Purpose: Hormone receptor–positive (HR+) breast cancer is clinically and biologically heterogeneous, and subgroups with different prognostic and treatment sensitivities need to be identified.Experimental Design: Research-based PAM50 subtyping and expression of additional genes was performed on 63 patients with HR+/HER2− disease randomly assigned to neoadjuvant multiagent chemotherapy versus endocrine therapy in a phase II trial. The biology associated with treatment response was used to derive a PAM50-based chemoendocrine score (CES). CES's predictive ability was evaluated in 4 independent neoadjuvant data sets (n = 675) and 4 adjuvant data sets (n = 1,505). The association of CES, intrinsic biology, and PAM50 risk of relapse (ROR) was explored across 6,007 tumors.Results: Most genes associated with endocrine sensitivity were also found associated with chemotherapy resistance. In the chemotherapy test/validation data sets, CES was independently associated with pathologic complete response (pCR), even after adjusting for intrinsic subtype. pCR rates of the CES endocrine–sensitive (CES-E), uncertain (CES-U), and chemotherapy-sensitive (CES-C) groups in both data sets combined were 25%, 11%, and 2%, respectively. In the endocrine test/validation data sets, CES was independently associated with response. Compared with ROR, >90% of ROR-low and ROR-high tumors were identified as CES-E and CES-C, respectively; however, each CES group represented >25% of ROR-intermediate disease. In terms of survival outcome, CES-C was associated with poor relapse-free survival in patients with ROR-intermediate disease treated with either adjuvant endocrine therapy only or no adjuvant systemic therapy, but not in patients treated with (neo)adjuvant chemotherapy.Conclusions: CES is a genomic signature capable of estimating chemoendocrine sensitivity in HR+ breast cancer beyond intrinsic subtype and risk of relapse. Clin Cancer Res; 23(12); 3035–44. ©2016 AACR.

PDF file - 81K, IPA analysis and genes in the inflammatory immune response signature.

XLSX file - 1531KB, Details of transcripts and Gene Ontology (GO) functional sets resulting from comparative analyses. Probes are annotated with gene symbols where available.

PDF file - 134KB, S3: Top 30 genes significantly affected by E-deprivation: (a) In vitro and (b) FAIMoS (two weeks), (i) Up-regulated and (ii) Down-regulated. Probes are annotated with gene symbols where available; S4: Top 30 genes significantly affected by fulvestrant: (a) In vitro and (b) NEWEST (high-dose), (i) Up-regulated and (ii) Down-regulated. Probes are annotated with gene symbols where available; S5: Top 30 GO functional gene sets significantly affected by E-deprivation: (a) In vitro and (b) FAIMoS (two weeks), (i) Up-regulated and (ii) Down-regulated; S6: Top 30 GO functional gene sets significantly affected by fulvestrant: (a) In vitro and (b) NEWEST (high-dose), (i) Up-regulated and (ii) Down-regulated.

Purpose: Endocrine therapies include aromatase inhibitors and the selective estrogen receptor (ER) downregulator fulvestrant. This study aimed to determine whether the reported efficacy of fulvestrant over anastrozole, and high- over low-dose fulvestrant, reflect distinct transcriptional responses.Experimental Design: Global gene expression profiles from ERα-positive breast carcinomas before and during presurgical treatment with fulvestrant (n = 22) or anastrozole (n = 81), and corresponding in vitro models, were compared. Transcripts responding differently to fulvestrant and estrogen deprivation were identified and integrated using Gene Ontology, pathway and network analyses to evaluate their potential significance.Results: The overall transcriptional response to fulvestrant and estrogen deprivation was correlated (r = 0.61 in presurgical studies, r = 0.87 in vitro), involving downregulation of estrogen-regulated and proliferation-associated genes. The transcriptional response to fulvestrant was of greater magnitude than estrogen deprivation (slope = 0.62 in presurgical studies, slope = 0.63 in vitro). Comparative analyses identified 28 genes and 40 Gene Ontology categories affected differentially by fulvestrant. Seventeen fulvestrant-specific genes, including CAV1/2, SNAI2, and NRP1, associated with ERα, androgen receptor (AR), and TP53, in a network regulating cell cycle, death, survival, and tumor morphology. Eighteen genes responding differently to fulvestrant specifically predicted antiproliferative response to fulvestrant, but not anastrozole. Transcriptional effects of low-dose fulvestrant correlated with high-dose treatment, but were of lower magnitude (ratio = 0.29).Conclusions: The transcriptional response to fulvestrant has much in common with estrogen deprivation, but is stronger with distinctions potentially attributable to arrest of estrogen-independent ERα activity and involvement of AR signaling. Genes responding differently to fulvestrant may have predictive utility. These data are consistent with the clinical efficacy of fulvestrant versus anastrozole and higher dosing regimens. Clin Cancer Res; 20(15); 3962–73. ©2014 AACR.

Background Oestrogen receptor-positive (ER+) breast cancer is commonly treated using endocrine therapies such as aromatase inhibitors which block synthesis of oestradiol, but the influence of this therapy on the immune composition of breast tumours has not been fully explored. Previous findings suggest that tumour infiltrating lymphocytes and immune-related gene expression may be altered by treatment with aromatase inhibitors. However, whether these changes are a direct result of impacts on the host immune system or mediated through tumour cells is not known. We aimed to investigate the effect of oestrogen deprivation on the expression of chemokines and immune infiltration in vitro and in an ER+ immunocompetent mouse model. Methods RT-qPCR and a bead-based Bioplex system were used to investigate the expression of chemokines in MCF-7 breast cancer cells deprived of oestrogen. A migration assay and flow cytometry were used to measure the migration of human peripheral blood mononuclear cells (PBMCs) to MCF-7 cells grown without the main biologically active oestrogen, oestradiol. Using flow cytometry and immunohistochemistry, we examined the immune cell infiltrate into tumours created by injecting SSM3 ER+ breast cancer cells into wild-type, immunocompetent 129/SvEv mice. Results This study demonstrates that oestrogen deprivation increases breast cancer secretion of TNF, CCL5, IL-6, IL-8, and CCL22 and alters total human peripheral blood mononuclear cell migration in an in vitro assay. Oestrogen deprivation of breast cancer cells increases migration of CD4+ T cells and decreases migration of CD11c+ and CD14+ PBMC towards cancer cells. PBMC migration towards breast cancer cells can be reduced by treatment with the non-steroidal anti-inflammatory drugs, aspirin and celecoxib. Treatment with endocrine therapy using the aromatase inhibitor letrozole increases CD4+ T cell infiltration into ER+ breast cancer tumours in immune competent mice. Conclusions These results suggest that anti-oestrogen treatment of ER+ breast cancer cells can alter cytokine production and immune cells in the area surrounding the cancer cells. These findings may have implications for the combination and timing of anti-oestrogen therapies with other therapies.

Purpose Inherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function. Methods We measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours. Results BRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3–23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10−04) increase in expression variability in BRCA1-associated breast tumours. Conclusion Our novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p –8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

Simple Summary Tribbles proteins possess the structure of protein kinases but function by forming protein complexes rather than phosphorylating substrates. Here we review the structure–function relationship of TRIB1 in cancers. Of the Tribbles proteins, TRIB1 is currently the most well characterised structurally. TRIB1 has different states that could potentially be targeted by small-molecule inhibitors and well-established relevance in acute myeloid leukaemia through degradation of transcription factors. Less is understood about the role of TRIB1 in solid tumours. Further research is required to fully realise the potential of TRIB1 as either a direct target of small-molecule drugs or a biomarker of treatment response across diverse cancer types. Abstract The Tribbles family of proteins—comprising TRIB1, TRIB2, TRIB3 and more distantly related STK40—play important, but distinct, roles in differentiation, development and oncogenesis. Of the four Tribbles proteins, TRIB1 has been most well characterised structurally and plays roles in diverse cancer types. The most well-understood role of TRIB1 is in acute myeloid leukaemia, where it can regulate C/EBP transcription factors and kinase pathways. Structure–function studies have uncovered conformational switching of TRIB1 from an inactive to an active state when it binds to C/EBPα. This conformational switching is centred on the active site of TRIB1, which appears to be accessible to small-molecule inhibitors in spite of its inability to bind ATP. Beyond myeloid neoplasms, TRIB1 plays diverse roles in signalling pathways with well-established roles in tumour progression. Thus, TRIB1 can affect both development and chemoresistance in leukaemia; glioma; and breast, lung and prostate cancers. The pervasive roles of TRIB1 and other Tribbles proteins across breast, prostate, lung and other cancer types, combined with small-molecule susceptibility shown by mechanistic studies, suggests an exciting potential for Tribbles as direct targets of small molecules or biomarkers to predict treatment response.

This abstract was withdrawn by the authors. Citation Format: Dunbier AK, Hazlett J, Niemi G, Kemp R. Withdrawn [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-06-18.

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Recently we have developed and validated a microarray-derived 4-gene test (Edinburgh EndoResponse4) to predict response to AIs in the neoadjuvant setting. We have also demonstrated the translational potential of this test in predicting accurately clinical response when mRNA is measured for these genes by polymerase chain reaction (PCR) or the gene protein is measured by immunohistochemistry (IHC). There is a major clinical need for biomarkers to predict which patients are likely to recur on adjuvant endocrine therapy so alternative or additional treatments can be provided to reduce recurrence and improve outcome. The aim of this study was to determine if Endoresponse4 and IHC of these gene proteins could do this. Methods: The original microarray assay used pre- and on-treatment (14-days) biopsies from 73 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole prior to surgery with 10 years follow-up after adjuvant letrozole. Matched formalin-fixed paraffin embedded (FFPE) tissue sections from 42 of these patients were used for IHC and antibodies were optimised against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. The ability of our test to estimate recurrence-free (RFS) and breast cancer specific overall survival (OS) using both PCR and IHC was then tested in a unique validation cohort of 140 post-menopausal women with ER-rich breast cancer treated with 2 weeks of neoadjuvant letrozole or anastrozole prior to surgery followed by adjuvant endocrine therapy and 10 years of follow up.. Results: Within our training cohort (n=73) using Kaplan-Meier analysis our 4-gene test predicted neoadjuvant clinical response and demonstrated a significant association with both RFS (P=0.029) and OS (P=0.009). This approach predicts outcomes within 2-weeks rather than 4-months of treatment required in other studies such as P024. Using IHC in the training cohort (n=42), two gene markers in combination (IL6ST at diagnosis and MCM4 after 2-weeks treatment) predicted both RFS (P=0.017) and OS (P=0.009) with great accuracy. The 140 patient group is being analysed and the findings are so far are consistent with the initial training cohort and indicate a significant association with outcomes. Conclusion: • A 4 gene model with clinical potential has been developed and validated to predict response to neoadjuvant aromatase inhibitors. • This 4 gene model predicts for response and also predicts relapse free and overall survival. • Proteins encoded by 2 of these 4 genes measured by IHC in an initial test set of 42 patients predict accurately both EFS and OS • A validation cohort (n=140) with over 10-years of follow-up will be available at SABCS 2015 to determine if this 2 biomarker test can predict outcome on adjuvant endocrine therapy. Citation Format: Turnbull AK, Arthur LM, Webber V, Thomas J, Uddin S, Webb H, Dunbier A, Dowsett M, Renshaw L, Sims AH, Dixon JM. A validated test for neoadjuvant clinical response to endocrine therapy in breast cancer that estimates accurately recurrence-free and overall survival. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-20.

The Tribbles family of pseudokinases recruits substrates to the ubiquitin ligase COP1 to facilitate ubiquitylation. CCAAT/enhancer-binding protein (C/EBP) family transcription factors are crucial Tribbles substrates in adipocyte and myeloid cell development. We found that the TRIB1 pseudokinase was able to recruit various C/EBP family members and that the binding of C/EBPβ was attenuated by phosphorylation. To explain the mechanism of C/EBP recruitment, we solved the crystal structure of TRIB1 in complex with C/EBPα, which revealed that TRIB1 underwent a substantial conformational change relative to its substrate-free structure and bound C/EBPα in a pseudosubstrate-like manner. Crystallographic analysis and molecular dynamics and subsequent biochemical assays showed that C/EBP binding triggered allosteric changes that link substrate recruitment to COP1 binding. These findings offer a view of pseudokinase regulation with striking parallels to bona fide kinase regulation—by means of the activation loop and αC helix—and raise the possibility of small molecules targeting either the activation “loop-in” or “loop-out” conformations of Tribbles pseudokinases.

One Sentence SummarySubstrate binding to Tribbles-homolog 1 (TRIB1) pseudokinase induces allosteric changes that allow formation of a complex with the COP1 ubiquitin ligase.AbstractThe Tribbles family of pseudokinases recruit substrates to the COP1 ubiquitin ligase for ubiquitination. CCAAT-enhancer binding protein (C/EBP) family transcription factors are crucial Tribbles substrates in adipocyte and myeloid development. Here we show that the TRIB1 pseudokinase can recruit various C/EBP family members, with binding of C/EBPβ attenuated by phosphorylation. To explain the mechanism of substrate recruitment, we solved the crystal structure of TRIB1 in complex with C/EBPα. TRIB1 undergoes a significant conformational change relative to its substrate-free structure, to bind C/EBPα in a pseudo-substrate-like manner. Crucially, substrate binding triggers allosteric changes that link substrate recruitment to COP1 binding, which is consistent with molecular dynamics and biochemical studies. These findings offer a view of pseudokinase regulation with striking parallels to bona fide kinase regulation— via the activation loop and αC-helix—and raise the possibility of small molecules targeting either the activation loop-in, or loop-out, conformations of Tribbles pseudokinases.

Purpose Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy. Patients and Methods Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor–alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements. Results The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer –specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry. Conclusion A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

Purpose: Hormone receptor–positive (HR+) breast cancer is clinically and biologically heterogeneous, and subgroups with different prognostic and treatment sensitivities need to be identified. Experimental Design: Research-based PAM50 subtyping and expression of additional genes was performed on 63 patients with HR+/HER2− disease randomly assigned to neoadjuvant multiagent chemotherapy versus endocrine therapy in a phase II trial. The biology associated with treatment response was used to derive a PAM50-based chemoendocrine score (CES). CES's predictive ability was evaluated in 4 independent neoadjuvant data sets (n = 675) and 4 adjuvant data sets (n = 1,505). The association of CES, intrinsic biology, and PAM50 risk of relapse (ROR) was explored across 6,007 tumors. Results: Most genes associated with endocrine sensitivity were also found associated with chemotherapy resistance. In the chemotherapy test/validation data sets, CES was independently associated with pathologic complete response (pCR), even after adjusting for intrinsic subtype. pCR rates of the CES endocrine–sensitive (CES-E), uncertain (CES-U), and chemotherapy-sensitive (CES-C) groups in both data sets combined were 25%, 11%, and 2%, respectively. In the endocrine test/validation data sets, CES was independently associated with response. Compared with ROR, >90% of ROR-low and ROR-high tumors were identified as CES-E and CES-C, respectively; however, each CES group represented >25% of ROR-intermediate disease. In terms of survival outcome, CES-C was associated with poor relapse-free survival in patients with ROR-intermediate disease treated with either adjuvant endocrine therapy only or no adjuvant systemic therapy, but not in patients treated with (neo)adjuvant chemotherapy. Conclusions: CES is a genomic signature capable of estimating chemoendocrine sensitivity in HR+ breast cancer beyond intrinsic subtype and risk of relapse. Clin Cancer Res; 23(12); 3035–44. ©2016 AACR.

Purpose: To investigate potential associations between gene modules representing key biologic processes and response to aromatase inhibitors (AI) in estrogen receptor–positive (ER+) breast cancer. Patients and Methods: Paired gene expression and Ki67 protein expression were available from 69 postmenopausal women with ER+ early breast cancer, at baseline and 2 weeks post-anastrozole treatment, in the presurgical setting. Functional gene modules (n = 26) were retrieved from published studies and their module scores were computed before and after elimination of proliferation-associated genes (PAG). Ki67 and module scores were assessed at baseline and 2 weeks post-anastrozole. Unsupervised clustering was used to assess associations between modules and Ki67. Results: Proliferation-based modules were highly correlated with Ki67 expression both pretreatment and on-treatment. At baseline with and without PAGs, Ki67 expression was significantly inversely correlated with ERG, ESR1.2, SET, and PIK3CA modules. Modules measuring estrogen signaling strongly predicted antiproliferative response to therapy with and without PAGs. Baseline expression of insulin-like growth factor-1 (IGF-I) module predicted a poor change in Ki67-implicating genes within the module as involved in de novo resistance to AIs. High expression of Immune.2.STAT1 module pretreatment predicted poor antiproliferative response to therapy. A significant association between estrogen-regulated genes modules (ESR1, ESR1-2, SET, and ERG) was evident post AI. Conclusions: Multiple processes and pathways are affected by AI treatment in ER+ breast cancer. Modules closely associated with ESR1 expression were predictive of good antiproliferative response to AIs, but modules representing immune activity and IGF-I/MAPK were predictive of poor Ki67 response, supporting their therapeutic targeting in combination with AIs. Clin Cancer Res; 20(9); 2485–94. ©2014 AACR.

Background: Aromatase inhibitors (AIs) have an established role in the treatment of estrogen receptor alpha positive post-menopausal breast cancer. Response rates are only 50-70% even in patients with ER-rich cancers in the neoadjuvant setting and are lower in advanced disease. Recently we developed and validated a microarray-derived 4-gene test to predict response to AIs in the neoadjuvant setting. Whole-genome expression analysis is impractical for clinical utility. There is a need to translate and validate any test utilising clinically accessible and reproducible material and technologies such as polymerase chain reaction (PCR) and immunohistochemistry (IHC). Methods: The original microarray experiment used pre- and on-treatment (at 14 days and 3-months) biopsies from 89 post-menopausal women with ER-rich breast cancer receiving 3 months of neoadjuvant letrozole. Dynamic response was based on periodic 3D ultrasound measurements performed during treatment. The derived 4-gene model was independently validated in a cohort of 44 post-menopausal women with ER-rich breast cancer treated with neoadjuvant anastrozole [table 1]. RNA was extracted from the original biopsies for RT-qPCR analysis using validated primers for the 4 genes with SYBR-green technology normalised to the geometric mean of 3 housekeeping genes. Matched formalin-fixed paraffin embedded (FFPE) tissue sections were used for IHC with optimised antibodies against 3 of the 4 proteins (where validated antibodies were available) using Envision technology. Results: PCR: Microarray and PCR expression levels for each of the four genes were well correlated (Pearson r=0.87-0.65, p Conclusion: Table 1NAccuracySensitivitySpecificityPPVNPVMicroarray (Training)890.960.890.980.980.96Microarray (Validation)440.910.800.970.920.90PCR260.960.951.001.000.86IHC280.890.861.001.000.89Sensitivity and specificity of model in training (microarray, PCR, IHC) and validation datasets (microarray). PPV/NPV = postivie/negative predictive value. •A 4 gene model has been developed and validated to predict response to neoadjuvant aromatase inhibitors. •This model has been shown to work with a high degree of accuracy using both PCR and IHC technologies. Further independent validation is currently underway. •This new test has the potential to predict accurately the benefit of endocrine therapy and has huge potential clinical value. Citation Format: Arran K Turnbull, Laura Arthur, Victoria Webber, Jeremy Thomas, Charlotte Heerlyn, Phoebe Thornton, Anita Dunbier, Mitch Dowsett, Lorna Renshaw, Andrew H Sims, J Michael Dixon. Development for clinical utility of a validated predictive test of clinical response to aromatase inhibitors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-05-01.

Purpose Risk of distant recurrence (DR) among women with estrogen receptor (ER) –positive early breast cancer is the major determinant of recommendations for or against chemotherapy. It is frequently estimated using the Oncotype DX recurrence score (RS). The PAM50 risk of recurrence (ROR) score provides an alternative approach, which also identifies intrinsic subtypes. Patients and Methods mRNA from 1,017 patients with ER-positive primary breast cancer treated with anastrozole or tamoxifen in the ATAC trial was assessed for ROR using the NanoString nCounter. Likelihood ratio (LR) tests and concordance indices (c indices) were used to assess the prognostic information provided beyond that of a clinical treatment score (CTS) by RS, ROR, or IHC4, an index of DR risk derived from immunohistochemical assessment of ER, progesterone receptor, human epidermal growth factor receptor 2 (HER2), and Ki67. Results ROR added significant prognostic information beyond CTS in all patients (Δ LR-χ2 = 33.9; P < .001) and in all four subgroups: node negative, node positive, HER2 negative, and HER2 negative/node negative; more information was added by ROR than by RS. C indices in the HER2-negative/node-negative subgroup were 0.73, 0.76, and 0.78 for CTS, CTS plus RS, and CTS plus ROR, respectively. More patients were scored as high risk and fewer as intermediate risk by ROR than by RS. Relatively similar prognostic information was added by ROR and IHC4 in all patients but more by ROR in the HER2-negative/node-negative group. Conclusion ROR provides more prognostic information in endocrine-treated patients with ER-positive, node-negative disease than RS, with better differentiation of intermediate- and higher-risk groups.

Purpose: Estrogen withdrawal by treatment with aromatase inhibitors is the most effective form of endocrine therapy for postmenopausal estrogen receptor–positive (ER+) breast cancer. However, response to therapy varies markedly and understanding of the precise molecular effects of aromatase inhibitors and causes of resistance is limited. We aimed to identify in clinical breast cancer those genes and pathways most associated with resistance to aromatase inhibitors by examining the global transcriptional effects of AI treatment. Experimental Design: Baseline and 2-week posttreatment biopsies were obtained from 112 postmenopausal women with ER+ breast cancer receiving neoadjuvant anastrozole. Gene expression data were obtained from 81 baseline and 2-week paired samples. Pathway analysis identified (i) the most prevalent changes in expression and (ii) the pretreatment genes/pathways most related to poor antiproliferative response. Results: A total of 1,327 genes were differentially expressed after 2-week treatment (false discovery rate < 0.01). Proliferation-associated genes and classical estrogen-dependent genes were strongly downregulated whereas collagens and chemokines were upregulated. Pretreatment expression of an inflammatory signature correlated with antiproliferative response to anastrozole and this observation was validated in an independent study. Higher expression of immune-related genes such as SLAMF8 and TNF as well as lymphocytic infiltration were associated with poorer response (P < 0.001) and validated in an independent cohort. Conclusions: The molecular response to aromatase inhibitor treatment varies greatly between patients consistent with the variable clinical benefit from aromatase inhibitor treatment. Higher baseline expression of an inflammatory signature is associated with poor antiproliferative response and should be assessed further as a novel biomarker and potential target for aromatase inhibitor-treated patients. Clin Cancer Res; 19(10); 2775–86. ©2013 AACR.

The preoperative setting is increasingly popular for the clinical investigation of hormonal agents and new biological drugs. The effectiveness of endocrine agents is well established for estrogen receptor–positive disease, and the emphasis in preoperative studies is on their combination with agents targeted at resistance mechanisms over 3 or more months. New agents are also being assessed for early evidence of clinical efficacy in shorter-term window-of-opportunity studies. The establishment of Ki67 as an intermediate marker of treatment benefit and of long-term outcome, with endocrine drugs, provides the opportunity for new trial designs with Ki67 as the primary endpoint. The PeriOperative Endocrine Therapy for Individualizing Care (POETIC) trial is randomizing (2:1) 4000 estrogen receptor–positive patients to 2 weeks presurgical treatment with a nonsteroidal aromatase inhibitor or no presurgical treatment. It provides a unique opportunity for detailed study of the determinants of response and resistance to estrogen deprivation as well as testing the role of presurgical therapy for improved biomarker-based estimates of prognosis. J Natl Cancer Inst Monogr 2011;43:120–123

Most estrogen receptor α (ER)-positive breast cancers initially respond to antiestrogens, but many eventually become estrogen-independent and recur. We identified an estrogen-independent role for ER and the CDK4/Rb/E2F transcriptional axis in the hormone-independent growth of breast cancer cells. ER downregulation with fulvestrant or small interfering RNA (siRNA) inhibited estrogen-independent growth. Chromatin immunoprecipitation identified ER genomic binding activity in estrogen-deprived cells and primary breast tumors treated with aromatase inhibitors. Gene expression profiling revealed an estrogen-independent, ER/E2F-directed transcriptional program. An E2F activation gene signature correlated with a lesser response to aromatase inhibitors in patients' tumors. siRNA screening showed that CDK4, an activator of E2F, is required for estrogen-independent cell growth. Long-term estrogen-deprived cells hyperactivate phosphatidylinositol 3-kinase (PI3K) independently of ER/E2F. Fulvestrant combined with the pan-PI3K inhibitor BKM120 induced regression of ER+ xenografts. These data support further development of ER downregulators and CDK4 inhibitors, and their combination with PI3K inhibitors for treatment of antiestrogen-resistant breast cancers. Significance: ERα retains genomic activity and drives a CDK4/E2F-dependent transcriptional program despite estrogen deprivation therapy. Combined inhibition of ER and PI3K induced regression of ER+ xenografts, supporting further development of strong ER downregulators and CDK4 inhibitors, and their combination with PI3K inhibitors for the treatment of antiestrogen-resistant breast cancers. Cancer Discovery; 1(4); 338–51. ©2011 AACR. Read the Commentary on this article by Van Tine et al., p. 287 This article is highlighted in the In This Issue feature, p. 275

Aromatase inhibitors (AI) have improved the treatment of oestrogen receptor positive (ER+) breast cancer. Despite the efficacy of these agents over 40% of patients relapse with endocrine resistant disease. Here we describe an in vitro model of acquired resistance to long-term oestrogen deprivation (LTED). The LTED cells retain expression of the ER and appear hypersensitive to oestrogen as a result of altered kinase activity. Furthermore analysis of temporal changes in gene expression during the acquisition of resistance highlight growth factor receptor pathways as key mediators of this adaptive process.

Purpose: Although most patients with estrogen receptor α (ER)-positive breast cancer initially respond to endocrine therapy, many ultimately develop resistance to antiestrogens. However, mechanisms of antiestrogen resistance and biomarkers predictive of such resistance are underdeveloped. Experimental Design: We adapted four ER+ human breast cancer cell lines to grow in an estrogen-depleted medium. A gene signature of estrogen independence was developed by comparing expression profiles of long-term estrogen-deprived (LTED) cells to their parental counterparts. We evaluated the ability of the LTED signature to predict tumor response to neoadjuvant therapy with an aromatase inhibitor and disease outcome following adjuvant tamoxifen. We utilized Gene Set Analysis (GSA) of LTED cell gene expression profiles and a loss-of-function approach to identify pathways causally associated with resistance to endocrine therapy. Results: The LTED gene expression signature was predictive of high tumor cell proliferation following neoadjuvant therapy with anastrozole and letrozole, each in different patient cohorts. This signature was also predictive of poor recurrence-free survival in two studies of patients treated with adjuvant tamoxifen. Bioinformatic interrogation of expression profiles in LTED cells revealed a signature of MYC activation. The MYC activation signature and high MYC protein levels were both predictive of poor outcome following tamoxifen therapy. Finally, knockdown of MYC inhibited LTED cell growth. Conclusions: A gene expression signature derived from ER+ breast cancer cells with acquired hormone independence predicted tumor response to aromatase inhibitors and associated with clinical markers of resistance to tamoxifen. Activation of the MYC pathway was associated with this resistance. Clin Cancer Res; 17(7); 2024–34. ©2011 AACR.

Purpose: The majority of breast cancer patients who have estrogen receptor positive (ER+) tumors whose proliferation is reduced after estrogen deprivation by aromatase inhibitors (AI). This study investigates any link between proliferation and hypoxia, a major determinant of tumor biology, and defines the effect of estrogen deprivation on hypoxia-associated genes. Methods: Genome-wide expression profiles were obtained from tumor biopsies from 81 ER+ postmenopausal patients, before and after 2 weeks' anastrozole treatment. A hypoxia metagene was developed by identifying genes clustered with classical hypoxia-regulated genes, excluding those associated with proliferation. Proliferation was measured by Ki67 and a proliferation metagene derived from two published breast cancer data sets. Results: Hypoxia and proliferation metagenes were associated at baseline (Pearson correlation coefficient, r = 0.67, P < 10−4) and after 2 weeks (r = 0.71, P < 10−4). Hypoxia metagene at baseline was associated with 2-week Ki67 (r = 0.43, P = 0.0002) and more weakly with poor 2-week Ki67 change consistent with a weak association with AI resistance. Hypoxia metagene was significantly downregulated with AI. This downregulation was significantly associated with change in the proliferation metagene and with Ki67 but, importantly, not with the substantial change in expression of classical estrogen-dependent genes. Conclusions: Hypoxia metagene is closely associated with proliferation before and after AI treatment. The downregulation of hypoxia metagene after AI therapy is most likely the result of changes in proliferation. There may be a weak effect of hypoxia metagene on de novo resistance to AIs. These findings are important to consider in coapplication of antiproliferative agents with antiangiogenic or antihypoxia agents. Clin Cancer Res; 17(9); 3005–12. ©2011 AACR.

Aim: To identify molecular mechanisms and predictors of response to aromatase inhibitors (AIs) in primary ER+ breast cancer. Background: Although AIs are highly effective suppressants of estrogen synthesis in postmenopausal women, up to 50% of patients derive little or no clinical benefit from AI treatment. The proliferation marker Ki67 provides a valuable pharmacodynamic marker for response in the presurgical setting and 2 week measurements of this marker have been shown to predict recurrence-free survival1. However, understanding of the precise molecular effects of AIs and causes of resistance is limited. We present, to our knowledge, the largest study of the transcriptional effects of AI treatment in the neoadjuvant setting. Methods: Baseline and 2wk post-treatment core-cut tumor biopsies were obtained from 112 postmenopausal women with stage I to IIIB ER+ early breast cancer who received single agent neoadjuvant anastrozole2. RNA extracted from biopsies was analysed on Illumina 48K microarrays. Genes which changed expression upon anastrozole treatment were identified using paired class comparison of the 81 matched baseline and 2wk pairs from which gene expression data was available. Correlates of response were determined using multiple testing corrected Spearman correlation analysis. Pathway analysis was performed on the ranked list of correlated genes. IHC for Ki67, ER and PgR was performed centrally on FFPE sections from duplicate core biopsies. Results: At a false discovery rate (FDR) of 0.01, 1154 genes were differentially expressed (792 down-regulated and 362 up-regulated). Proliferation-associated genes and classical estrogen-dependent genes such as TOP2A, CCNB2, TFF1, and PDZK1 were strongly downregulated (FDR 1. Dowsett et al., JNCI, 2007, 99, 167-70. 2. Smith et al., JCO, 2007, 3816-22. Supported by the Mary-Jean Mitchell Green Foundation and Breakthrough Breast Cancer. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr S2-5.

Aim: To compare changes in whole genome transcription elicited by anastrozole (ANA) and fulvestrant (FUL) in estrogen receptor positive (ER+) breast cancer. Background: Aromatase inhibitors (AIs), such as ANA, and the selective estrogen receptor down-regulator, FUL, are both effective in the treatment of ER+ breast cancer. AIs reduce stimulation of ER by suppressing estrogen synthesis while FUL acts as an antagonist and receptor down-regulator. Better understanding of their mechanism of action may lead to a more rational clinical application of these two drugs. Methods: Pre-and post-treatment core-cut tumor biopsies were obtained from 105 postmenopausal women with ER+ early breast cancer who received neoadjuvant FUL[1]. Genome-wide expression data were available from 22 matched baseline and post-treatment pairs from the patients who received 500mg of FUL every 28 days and 500mg on day 14 of the first month (FUL500), also, from 16 patients who received 250mg of FUL every 28 days (FUL250). In addition, microarray data were obtained from 81 matched pre-and post-treatment pairs of tumor biopsies from postmenopausal women with ER+ breast cancer who received single agent neoadjuvant ANA[2]. Results: At a false discovery rate (FDR) of 5%, expression of 1875 genes changed with FUL500 but no genes changed with FUL250. Each of 4 index proliferation genes (TOP2A,AURKA, CCNB2, CDC20) and 4 index estrogen responsive genes (ERGs) (TFF1, PGR, PDZK1, GREB1) showed greater suppression with FUL500 than FUL250. Further study of FUL was conducted only in the FUL500 group. At 5% FDR, 1457 genes decreased in expression and 1064 increased with ANA while 1083 decreased and 792 increased with FUL500. Most genes that showed significant changes with ANA also showed changes of a similar magnitude with FUL500 but there were some individual striking differences. There was more commonality in the genes that decreased in expression than those that increased. The reduction in a proliferation metagene was similar with ANA and FUL500 (geometric mean suppression, 23.1% and 23.2% respectively). Each of the 4 proliferation index genes showed a very similar degree of change using the 2 drugs as did the 4 ERGs. However, while IQ motif containing GTPase activating protein 3 was among the 5 most significantly changed genes with ANA (mean 52% suppression, FDR Conclusions: Gene expression changes with FUL250 were modest but with FUL500 were similar in extent to those observed with ANA. Evaluation of the substantial differences in individual gene responses between the two drugs may allow their more rational clinical use. Kuter I, et al; Breast Cancer Res Treat 2008; 109: 589 Smith I.E, et al ; J Clin Oncol 2007; 25:3816 Supported by AstraZeneca, the Mary-Jean Mitchell Green Foundation and Breakthrough Breast Cancer. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P1-12-02.