Ingle, James N.

2 Background: The MA.17 trial demonstrated that extended adjuvant endocrine therapy with letrozole after 5-y of tamoxifen markedly reduced the risk of recurrence in women with ER+ early stage breast cancer. This trial provides an opportunity to assess the ability of biomarkers to predict late recurrences in ER+ breast cancer. The Breast Cancer Index (BCI), a continuous risk index based on the combination of HOXB13:IL17BR (H:I) and the molecular grade index (MGI), estimates the individual risk of recurrence in ER+ breast cancer patients. In this study, the prognostic utility of BCI to predict late recurrences was examined. Methods: FFPE tumor blocks were collected from patients who experienced a breast cancer recurrence up to unblinding of MA.17. Controls were matched 2:1 for age, tumor size, nodal status and prior chemotherapy, and were disease free for longer than cases. All cases were reviewed for standard histopathology and evaluated using the real-time RT-PCR BCI assay. Results: Patient characteristics for the case-control study were similar to that from the overall study. Characteristics for cases (N=83) and controls (N=166) were not significantly different except for treatment. A higher percentage of controls compared to cases tended to be categorized as low risk by BCI (58% vs 43%), while a lower percentage of controls than cases tended to be categorized as high risk by BCI (34% vs 24%). In univariate analysis, treatment, BCI, H:I and HOXB13, but not tumor grade or MGI, were significant predictors of late recurrence. After adjusting for standard variables (age, tumor grade and treatment), BCI (OR 2.37; P=0.03), H:I (OR 2.55; P=0.04) and HOXB13 (OR 1.35; P=0.02) remained significant predictors of recurrence. HOXB13 expression at diagnosis predicted patient benefit from extended endocrine therapy with letrozole. Conclusions: In this case-controlled study, the data demonstrate that BCI is a significant predictor of late recurrences in ER+ patients following 5-y of tamoxifen. The prognostic performance of BCI to predict late recurrences was largely dependent on HOXB13 expression. The integration of H:I and MGI within BCI provides prognostic utility for both early and late recurrences.

Abstract Genetic risks in breast cancer remain only partly understood. Here, we report the results of a genome-wide association study of germline DNA from 4,658 women, including 252 women experiencing a breast cancer recurrence, who were entered on the MA.27 adjuvant trial comparing the aromatase inhibitors (AI) anastrozole and exemestane. Single-nucleotide polymorphisms (SNP) of top significance were identified in the gene encoding MIR2052HG, a long noncoding RNA of unknown function. Heterozygous or homozygous individuals for variant alleles exhibited a ∼40% or ∼63% decrease, respectively, in the hazard of breast cancer recurrence relative to homozygous wild-type individuals. Functional genomic studies in lymphoblastoid cell lines and ERα-positive breast cancer cell lines showed that expression from MIR2052HG and the ESR1 gene encoding estrogen receptor-α (ERα) was induced by estrogen and AI in a SNP-dependent manner. Variant SNP genotypes exhibited increased ERα binding to estrogen response elements, relative to wild-type genotypes, a pattern that was reversed by AI treatment. Further, variant SNPs were associated with lower expression of MIR2052HG and ERα. RNAi-mediated silencing of MIR2052HG in breast cancer cell lines decreased ERα expression, cell proliferation, and anchorage-independent colony formation. Mechanistic investigations revealed that MIR2052HG sustained ERα levels both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated, proteasome-dependent degradation of ERα. Taken together, our results define MIR2052HS as a functionally polymorphic gene that affects risks of breast cancer recurrence in women treated with AI. More broadly, our results offer a pharmacogenomic basis to understand differences in the response of breast cancer patients to AI therapy. Cancer Res; 76(23); 7012–23. ©2016 AACR.

Abstract Background: Intrinsic resistance has been linked to ER down-regulation and poor clinical outcome in breast tumors. Aurora-A kinase (AURKA) promotes distant metastases through activation of epithelial to mesenchymal transition (EMT) programming and expansion of breast tumor initiating cells (BTICs) harboring a CD44high/CD24low phenotype. Moreover, AURKA induces down-regulation of ERα expression and resistance to endocrine therapy that is mediated by SMAD5 transcription factor (D’Assoro et al., Oncogene 2014: 33:599-610). The aim of this study was to evaluate the role of AURKA in endocrine resistance induced by breast cancer stemness and ER down-regulation. Materials and Methods: We employed parental MCF-7 and variant MCF-7 cells ex-vivo (vMCF- 7/LCC9, vMCF-7/FR) that have high endogenous levels of AURKA, are ERlow, and exhibit in vivo resistance to fulvestrant. Real-Time Cell Proliferation and Apoptosis assays were performed to assess response to endocrine and/or AURKA-targeted therapy using the innovative IncuCyte ZOOM System. Stemness activity was assessed by culturing breast cancer cells under non-adherent conditions to generate mammospheres. Expression of ER, CD44 and CD24 markers was characterized by FACS analysis and immunofluorescence. Results: Pharmacologic inhibition of AURKA activity with the small molecule, alisertib, significantly restored sensitivity to fulvestrant in vMCF-7/LCC9 and vMCF-7/FR cells. To establish whether fulvestrant resistance was linked to enrichment of BTICs, breast cancer cells were cultured under non-adherent conditions to generate mammospheres. vMCF-7/FR cells generated mammospheres at higher efficiency compared to parental cells suggesting that vMCF-7/FR cells exhibited high self-renewal activity. vMCF-7/FR-derived mammospheres displayed a stem cell-like CD44high/CD24low phenotype that was further characterized by low levels of ER expression and resistance to fulvestrant. When vMCF-7 FR-derived mammospheres were treated with alisertib alone or combined with fulvestrant, the combination was more effective in mediating restoration of endocrine sensitivity. The phenotype of the alisertib-treated mammospheres was functionally linked to loss of CD44 expression, restoration of CD24 and ER expression, and sensitivity to fulvestrant. Conclusions: These findings provide further evidence that AURKA activity plays a central role in breast cancer progression through the genesis and clonal expansion of BTICs that are characterized by ER down-regulation and resistance to endocrine therapy. These results are important for the treatment of endocrine resistant breast tumors because they provide the rationale for the development of an innovative therapeutic approach to combine endocrine therapy with a targeted inhibitor of AURKA activity. Citation Format: Antonino B. D’Assoro, Tufia Haddad, Matthew Goetz, Mary Kuffel, John Hawse, Vera Suman, Jeffrey Salisbury, James Ingle, Evanthia Galanis. Pharmacologic targeting of Aurora-A kinase restores ERα expression and endocrine sensitivity through impairment of breast cancer stemness. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3313.

Abstract INTRODUCTION: The tumor microenvironment consists of a complicated interplay between a heterogeneous mixture of tumor cells and the surrounding tissue and there is a burgeoning interest in the role of the tissue microbiota within this microenvironment. Our group has investigated the breast tumor microbiome using the unaligned (non-human) reads from 796 RNASequencing data obtained from The Cancer Genome Atlas (TCGA) repository of Breast Cancer. METHODS: Unmapped sequences for 720 TCGA tumor samples and 76 paired normal samples were analyzed with Kraken v0.10.5 using the RefSeq 16S and standard genomes. To minimize false discoveries Kraken results were filtered to species that have bacterial genomic and 16S read support. Cluster analysis of the T-distributed Stochastic Neighbor Embedding (tsne) was performed and consensus voting of 26 maximum scoring metrics identified 3 distinct clusters. Differential abundance analysis was performed with the edgeR package. Covariate association analysis was performed for tumor clinical characteristics, as well as sample heterogeneity characteristics. RESULTS: There were three microbiome clusters we identified using TCGA breast samples. The average silhouette width of the third cluster was deemed statistically insignificant (0.071), suggesting further stratification of this cluster is necessary. The remaining two TCGA clusters (467) shared an average silhouette width of 0.39, using Bray's dissimilarity index. Differential abundance analysis of the two clusters after Bonferroni correction identified 450 significant species. The biomes were represented by 63 triple negative, 93 HER2+, 258 Luminal, and 50 tumor adjacent normals. Concordant cluster assignment was observed in 93.7 +/- 7.3% of the normal-tumor pairings, averaged across clinical subtypes. We observed clear delineation of biome populations at the order taxonomic level, which was not associated with the clinical subtype or the tumor/tumor adjacent pairings. We found enrichment of Burkholderiales in the first biome and enrichment of Bacillales and Lactobacillales within the second biome. The second biome appears to be deplete of representatives from the Asian population (p value 0.005) and survival associations were observed to be significantly reduced for HER2 patients associated with Biome 1 (p value 0.025). Geneset enrichment analysis of the expression signatures indicated drug metabolism and chemical carcinogenesis pathways to be associated with biome 2. CONCLUSIONS: In our study, we observed two significantly different microbiomes among TCGA breast cancer samples that were not associated with the clinical subtypes. Current efforts include validating these biomes, using 16S sequencing on matching fresh frozen paraffin embedded samples. Additionally, we are evaluating the influence of the biomes in independent adjuvant and neo-adjuvant studies with next generation sequencing data. Citation Format: Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, James N. Ingle, Matthew P. Goetz, Krishna R. Kalari. Distinct microbiome populations within breast cancer microenvironments. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3298.

Abstract Background: Triple negative breast cancer (TNBC) accounts for approximately 20% of all breast cancer diagnoses. Clinical management of TNBC is limited to surgery, chemotherapy and radiation due to lack of estrogen receptor alpha and HER2 expression. Recently, we have shown that approximately 40% of TNBCs express estrogen receptor beta (ERβ) and have begun to explore the possibility that this receptor could be utilized as a novel therapeutic target for this disease. Methods: To examine the biological functions of ERβ in TNBC, novel ERβ expressing TN cell lines (MDA-MB-231 and Hs578T) were developed. In vitro experiments were employed to determine alterations in the global gene expression profiles, biological pathways, proliferation rates, and cell cycle progression following estrogen or ERβ-specific agonist treatment. Cell line xenografts were also established in athymic ovariectomized nude mice to examine tumoral responses to ERβ targeting agents and to investigate gene and protein expression patterns as well as potential serum biomarkers indicative of therapeutic response. Additionally, using the resources of the Mayo Clinic Breast Cancer Genome Guided Therapy Study (BEAUTY), we have identified, and begun to analyze, ERβ+ and ERβ- patient derived xenografts (PDX) established from women with TNBC. Results: Our studies have revealed that both estrogen and multiple ERβ-specific agonists elicit significant anti-proliferative effects in ERβ+ TNBC cells primarily through a G1/S phase cell cycle arrest. These anti-proliferative effects appear to be mediated by cystatins, a family of small secreted cysteine protease inhibitors which are highly induced following estrogen and ERβ-specific agonist treatment. Conditioned media isolated from estrogen or ERβ-specific agonist treated cells decreased the proliferation rates of multiple non-ERβ expressing cell lines; effects that were completely reversed when cystatins were depleted from the media. In addition, we have shown that activation of ERβ, and the subsequent induction of cystatin gene expression, leads to suppression of canonical TGFβ signaling through multiple mechanisms including suppression of TGFβR2 expression, induction of Smad7 expression and blockade of TGFβ ligand-mediated activation of this pathway both in vitro and in vivo. Finally, ERβ+ TNBC PDXs exhibit significantly decreased tumor growth rates in estrogen-treated mice compared to ERβ- TN breast tumors. Conclusions: Our in vitro and in vivo data show that estrogen and ERβ-specific agonists elicit anti-cancer effects in ERβ+ TNBC. These effects appear to be mediated, in part, by cystatins through their inhibitory effects on canonical TGFB signaling, a pathway known to drive TNBC progression. Importantly, these data lay the foundation for studies aimed at examining the ability to therapeutically target ERβ in TNBC patients. Citation Format: Reese J, Bruinsma E, Subramaniam M, Suman V, Pitel K, Kalari K, Yu J, Wang L, Goetz M, Ingle J, Hawse J. ERβ elicits tumor suppressive effects in triple negative breast cancer through the induction of cystatins and suppression of TGFβ signaling. [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 P5-04-01.

Abstract We previously reported, on the basis of a genome-wide association study for aromatase inhibitor-induced musculoskeletal symptoms, that single-nucleotide polymorphisms (SNPs) near the T-cell leukemia/lymphoma 1A (TCL1A) gene were associated with aromatase inhibitor-induced musculoskeletal pain and with estradiol (E2)-induced TCL1A expression. Furthermore, variation in TCL1A expression influenced the downstream expression of proinflammatory cytokines and cytokine receptors. Specifically, the top hit genome-wide association study SNP, rs11849538, created a functional estrogen response element (ERE) that displayed estrogen receptor (ER) binding and increased E2 induction of TCL1A expression only for the variant SNP genotype. In the present study, we pursued mechanisms underlying the E2-SNP-dependent regulation of TCL1A expression and, in parallel, our subsequent observations that SNPs at a distance from EREs can regulate ERα binding and that ER antagonists can reverse phenotypes associated with those SNPs. Specifically, we performed a series of functional genomic studies using a large panel of lymphoblastoid cell lines with dense genomic data that demonstrated that TCL1A SNPs at a distance from EREs can modulate ERα binding and expression of TCL1A as well as the expression of downstream immune mediators. Furthermore, 4-hydroxytamoxifen or fulvestrant could reverse these SNP-genotype effects. Similar results were found for SNPs in the IL17A cytokine and CCR6 chemokine receptor genes. These observations greatly expand our previous results and support the existence of a novel molecular mechanism that contributes to the complex interplay between estrogens and immune systems. They also raise the possibility of the pharmacological manipulation of the expression of proinflammatory cytokines and chemokines in a SNP genotype-dependent fashion.