Qiong Gao

GDNF–RET Signaling in ER-Positive Breast Cancers Is a Key Determinant of Response and Resistance to Aromatase Inhibitors

Most breast cancers at diagnosis are estrogen receptor-positive (ER(+)) and depend on estrogen for growth and survival. Blocking estrogen biosynthesis by aromatase inhibitors has therefore become a first-line endocrine therapy for postmenopausal women with ER(+) breast cancers. Despite providing substantial improvements in patient outcome, aromatase inhibitor resistance remains a major clinical challenge. The receptor tyrosine kinase, RET, and its coreceptor, GFRα1, are upregulated in a subset of ER(+) breast cancers, and the RET ligand, glial-derived neurotrophic factor (GDNF) is upregulated by inflammatory cytokines. Here, we report the findings of a multidisciplinary strategy to address the impact of GDNF-RET signaling in the response to aromatase inhibitor treatment. In breast cancer cells in two-dimensional and three-dimensional culture, GDNF-mediated RET signaling is enhanced in a model of aromatase inhibitor resistance. Furthermore, GDNF-RET signaling promoted the survival of aromatase inhibitor-resistant cells and elicited resistance in aromatase inhibitor-sensitive cells. Both these effects were selectively reverted by the RET kinase inhibitor, NVP-BBT594. Gene expression profiling in ER(+) cancers defined a proliferation-independent GDNF response signature that prognosed poor patient outcome and, more importantly, predicted poor response to aromatase inhibitor treatment with the development of resistance. We validated these findings by showing increased RET protein expression levels in an independent cohort of aromatase inhibitor-resistant patient specimens. Together, our results establish GDNF-RET signaling as a rational therapeutic target to combat or delay the onset of aromatase inhibitor resistance in breast cancer.

Tumour cell-derived Wnt7a recruits and activates fibroblasts to promote tumour aggressiveness.

Stromal fibroblast recruitment to tumours and activation to a cancer-associated fibroblast (CAF) phenotype has been implicated in promoting primary tumour growth and progression to metastatic disease. However, the mechanisms underlying the tumour:fibroblast crosstalk that drive the intertumoural stromal heterogeneity remain poorly understood. Using in vivo models we identify Wnt7a as a key factor secreted exclusively by aggressive breast tumour cells, which induces CAF conversion. Functionally, this results in extracellular matrix remodelling to create a permissive environment for tumour cell invasion and promotion of distant metastasis. Mechanistically, Wnt7a-mediated fibroblast activation is not dependent on classical Wnt signalling. Instead, we demonstrate that Wnt7a potentiates TGFβ receptor signalling both in 3D in vitro and in vivo models, thus highlighting the interaction between two of the key signalling pathways in development and disease. Importantly, in clinical breast cancer cohorts, tumour cell Wnt7a expression correlates with a desmoplastic, poor-prognosis stroma and poor patient outcome.

MoKCa database—mutations of kinases in cancer

Members of the protein kinase family are amongst the most commonly mutated genes in human cancer, and both mutated and activated protein kinases have proved to be tractable targets for the development of new anticancer therapies The MoKCa database (Mutations of Kinases in Cancer, http://strubiol.icr.ac.uk/extra/mokca) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer. Somatic mutation data from tumours and tumour cell lines have been mapped onto the crystal structures of the affected protein domains. Positions of the mutated amino-acids are highlighted on a sequence-based domain pictogram, as well as a 3D-image of the protein structure, and in a molecular graphics package, integrated for interactive viewing. The data associated with each mutation is presented in the Web interface, along with expert annotation of the detailed molecular functional implications of the mutation. Proteins are linked to functional annotation resources and are annotated with structural and functional features such as domains and phosphorylation sites. MoKCa aims to provide assessments available from multiple sources and algorithms for each potential cancer-associated mutation, and present these together in a consistent and coherent fashion to facilitate authoritative annotation by cancer biologists and structural biologists, directly involved in the generation and analysis of new mutational data.

An in vivo functional screen identifies ST6GalNAc2 sialyltransferase as a breast cancer metastasis suppressor.

To interrogate the complex mechanisms involved in the later stages of cancer metastasis, we designed a functional in vivo RNA interference (RNAi) screen combined with next-generation sequencing. Using this approach, we identified the sialyltransferase ST6GalNAc2 as a novel breast cancer metastasis suppressor. Mechanistically, ST6GalNAc2 silencing alters the profile of O-glycans on the tumor cell surface, facilitating binding of the soluble lectin galectin-3. This then enhances tumor cell retention and emboli formation at metastatic sites leading to increased metastatic burden, events that can be completely blocked by galectin-3 inhibition. Critically, elevated ST6GALNAC2, but not galectin-3, expression in estrogen receptor-negative breast cancers significantly correlates with reduced frequency of metastatic events and improved survival. These data demonstrate that the prometastatic role of galectin-3 is regulated by its ability to bind to the tumor cell surface and highlight the potential of monitoring ST6GalNAc2 expression to stratify patients with breast cancer for treatment with galectin-3 inhibitors.

miR-155 drives metabolic reprogramming of ER+ breast cancer cells following long-term estrogen deprivation and predicts clinical response to aromatase inhibitors

Aromatase inhibitors (AI) have become the first-line endocrine treatment of choice for postmenopausal estrogen receptor-positive (ER(+)) breast cancer patients, but resistance remains a major challenge. Metabolic reprogramming is a hallmark of cancer and may contribute to drug resistance. Here, we investigated the link between altered breast cancer metabolism and AI resistance using AI-resistant and sensitive breast cancer cells, patient tumor samples, and AI-sensitive human xenografts. We found that long-term estrogen deprivation (LTED), a model of AI resistance, was associated with increased glycolysis dependency. Targeting the glycolysis-priming enzyme hexokinase-2 (HK2) in combination with the AI, letrozole, synergistically reduced cell viability in AI-sensitive models. Conversely, MCF7-LTED cells, which displayed a high degree of metabolic plasticity, switched to oxidative phosphorylation when glycolysis was impaired. This effect was ER dependent as breast cancer cells with undetectable levels of ER failed to exhibit metabolic plasticity. MCF7-LTED cells were also more motile than their parental counterparts and assumed amoeboid-like invasive abilities upon glycolysis inhibition with 2-deoxyglucose (2-DG). Mechanistic investigations further revealed an important role for miR-155 in metabolic reprogramming. Suppression of miR-155 resulted in sensitization of MCF7-LTED cells to metformin treatment and impairment of 2-DG-induced motility. Notably, high baseline miR-155 expression correlated with poor response to AI therapy in a cohort of ER(+) breast cancers treated with neoadjuvant anastrozole. These findings suggest that miR-155 represents a biomarker potentially capable of identifying the subset of breast cancers most likely to adapt to and relapse on AI therapy.

Cholesterol biosynthesis pathway as a novel mechanism of resistance to estrogen deprivation in estrogen receptor-positive breast cancer.

BackgroundTherapies targeting estrogenic stimulation in estrogen receptor-positive (ER+) breast cancer (BC) reduce mortality, but resistance remains a major clinical problem. Molecular studies have shown few high-frequency mutations to be associated with endocrine resistance. In contrast, expression profiling of primary ER+ BC samples has identified several promising signatures/networks for targeting.MethodsTo identify common adaptive mechanisms associated with resistance to aromatase inhibitors (AIs), we assessed changes in global gene expression during adaptation to long-term estrogen deprivation (LTED) in a panel of ER+ BC cell lines cultured in 2D on plastic (MCF7, T47D, HCC1428, SUM44 and ZR75.1) or in 3D on collagen (MCF7) to model the stromal compartment. Furthermore, dimethyl labelling followed by LC-MS/MS was used to assess global changes in protein abundance. The role of target genes/proteins on proliferation, ER-mediated transcription and recruitment of ER to target gene promoters was analysed.ResultsThe cholesterol biosynthesis pathway was the common upregulated pathway in the ER+ LTED but not the ER– LTED cell lines, suggesting a potential mechanism dependent on continued ER expression. Targeting the individual genes of the cholesterol biosynthesis pathway with siRNAs caused a 30–50 % drop in proliferation. Further analysis showed increased expression of 25-hydroxycholesterol (HC) in the MCF7 LTED cells. Exogenous 25-HC or 27-HC increased ER-mediated transcription and expression of the endogenous estrogen-regulated gene TFF1 in ER+ LTED cells but not in the ER– LTED cells. Additionally, recruitment of the ER and CREB-binding protein (CBP) to the TFF1 and GREB1 promoters was increased upon treatment with 25-HC and 27-HC. In-silico analysis of two independent studies of primary ER+ BC patients treated with neoadjuvant AIs showed that increased expression of MSMO1, EBP, LBR and SQLE enzymes, required for cholesterol synthesis and increased in our in-vitro models, was significantly associated with poor response to endocrine therapy.ConclusionTaken together, these data provide support for the role of cholesterol biosynthesis enzymes and the cholesterol metabolites, 25-HC and 27-HC, in a novel mechanism of resistance to endocrine therapy in ER+ BC that has potential as a therapeutic target.

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

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.

Embryonic mammary signature subsets are activated in Brca1 -/- and basal-like breast cancers

IntroductionCancer is often suggested to result from development gone awry. Links between normal embryonic development and cancer biology have been postulated, but no defined genetic basis has been established. We recently published the first transcriptomic analysis of embryonic mammary cell populations. Embryonic mammary epithelial cells are an immature progenitor cell population, lacking differentiation markers, which is reflected in their very distinct genetic profiles when compared with those of their postnatal descendents.MethodsWe defined an embryonic mammary epithelial signature that incorporates the most highly expressed genes from embryonic mammary epithelium when compared with the postnatal mammary epithelial cells. We looked for activation of the embryonic mammary epithelial signature in mouse mammary tumors that formed in mice in which Brca1 had been conditionally deleted from the mammary epithelium and in human breast cancers to determine whether any genetic links exist between embryonic mammary cells and breast cancers.ResultsSmall subsets of the embryonic mammary epithelial signature were consistently activated in mouse Brca1-/- tumors and human basal-like breast cancers, which encoded predominantly transcriptional regulators, cell-cycle, and actin cytoskeleton components. Other embryonic gene subsets were found activated in non-basal-like tumor subtypes and repressed in basal-like tumors, including regulators of neuronal differentiation, transcription, and cell biosynthesis. Several embryonic genes showed significant upregulation in estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and/or grade 3 breast cancers. Among them, the transcription factor, SOX11, a progenitor cell and lineage regulator of nonmammary cell types, is found highly expressed in some Brca1-/- mammary tumors. By using RNA interference to silence SOX11 expression in breast cancer cells, we found evidence that SOX11 regulates breast cancer cell proliferation and cell survival.ConclusionsSpecific subsets of embryonic mammary genes, rather than the entire embryonic development transcriptomic program, are activated in tumorigenesis. Genes involved in embryonic mammary development are consistently upregulated in some breast cancers and warrant further investigation, potentially in drug-discovery research endeavors.

AKT Antagonist AZD5363 Influences Estrogen Receptor Function in Endocrine-Resistant Breast Cancer and Synergizes with Fulvestrant (ICI182780) In Vivo

PI3K/AKT/mTOR signaling plays an important role in breast cancer. Its interaction with estrogen receptor (ER) signaling becomes more complex and interdependent with acquired endocrine resistance. Targeting mTOR combined with endocrine therapy has shown clinical utility; however, a negative feedback loop exists downstream of PI3K/AKT/mTOR. Direct blockade of AKT together with endocrine therapy may improve breast cancer treatment. AZD5363, a novel pan-AKT kinase catalytic inhibitor, was examined in a panel of ER+ breast cancer cell lines (MCF7, HCC1428, T47D, ZR75.1) adapted to long-term estrogen deprivation (LTED) or tamoxifen (TamR). AZD5363 caused a dose-dependent decrease in proliferation in all cell lines tested (GI50 < 500 nmol/L) except HCC1428 and HCC1428-LTED. T47D-LTED and ZR75-LTED were the most sensitive of the lines (GI50 ∼100 nmol/L). AZD5363 resensitized TamR cells to tamoxifen and acted synergistically with fulvestrant. AZD5363 decreased p-AKT/mTOR targets leading to a reduction in ERα-mediated transcription in a context-specific manner and concomitant decrease in recruitment of ER and CREB-binding protein (CBP) to estrogen response elements located on the TFF1, PGR, and GREB1 promoters. Furthermore, AZD5363 reduced expression of cell-cycle–regulatory proteins. Global gene expression highlighted ERBB2-ERBB3, ERK5, and IGFI signaling pathways driven by MYC as potential feedback-loops. Combined treatment with AZD5363 and fulvestrant showed synergy in an ER+ patient-derived xenograft and delayed tumor progression after cessation of therapy. These data support the combination of AZD5363 with fulvestrant as a potential therapy for breast cancer that is sensitive or resistant to E-deprivation or tamoxifen and that activated AKT is a determinant of response, supporting the need for clinical evaluation. Mol Cancer Ther; 14(9); 2035–48. ©2015 AACR.

Mouse mammary stem cells express prognostic markers for triple-negative breast cancer

IntroductionTriple-negative breast cancer (TNBC) is a heterogeneous group of tumours in which chemotherapy, the current mainstay of systemic treatment, is often initially beneficial but with a high risk of relapse and metastasis. There is currently no means of predicting which TNBC will relapse. We tested the hypothesis that the biological properties of normal stem cells are re-activated in tumour metastasis and that, therefore, the activation of normal mammary stem cell-associated gene sets in primary TNBC would be highly prognostic for relapse and metastasis.MethodsMammary basal stem and myoepithelial cells were isolated by flow cytometry and tested in low-dose transplant assays. Gene expression microarrays were used to establish expression profiles of the stem and myoepithelial populations; these were compared to each other and to our previously established mammary epithelial gene expression profiles. Stem cell genes were classified by Gene Ontology (GO) analysis and the expression of a subset analysed in the stem cell population at single cell resolution. Activation of stem cell genes was interrogated across different breast cancer cohorts and within specific subtypes and tested for clinical prognostic power.ResultsA set of 323 genes was identified that was expressed significantly more highly in the purified basal stem cells compared to all other cells of the mammary epithelium. A total of 109 out of 323 genes had been associated with stem cell features in at least one other study in addition to our own, providing further support for their involvement in the biology of this cell type. GO analysis demonstrated an enrichment of these genes for an association with cell migration, cytoskeletal regulation and tissue morphogenesis, consistent with a role in invasion and metastasis. Single cell resolution analysis showed that individual cells co-expressed both epithelial- and mesenchymal-associated genes/proteins. Most strikingly, we demonstrated that strong activity of this stem cell gene set in TNBCs identified those tumours most likely to rapidly progress to metastasis.ConclusionsOur findings support the hypothesis that the biological properties of normal stem cells are drivers of metastasis and that these properties can be used to stratify patients with a highly heterogeneous disease such as TNBC.