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HORMAD1 expression is usually restricted to germline cells, but it becomes mis-expressed in epithelial cells in ~60% of triple-negative breast cancers (TNBCs), where it is associated with elevated genomic instability (1). HORMAD1 expression in TNBC is bimodal with HORMAD1-positive TNBC representing a biologically distinct disease group. Identification of HORMAD1-driven genetic dependencies may uncover novel therapies for this disease group. To study HORMAD1-driven genetic dependencies, we generated a SUM159 cell line model with doxycycline-inducible HORMAD1 that replicated genomic instability phenotypes seen in HORMAD1-positive TNBC (1). Using small interfering RNA screens, we identified candidate genes whose depletion selectively inhibited the cellular growth of HORMAD1-expressing cells. We validated five genes (ATR, BRIP1, POLH, TDP1 and XRCC1), depletion of which led to reduced cellular growth or clonogenic survival in cells expressing HORMAD1. In addition to the translesion synthesis (TLS) polymerase POLH, we identified a HORMAD1-driven dependency upon additional TLS polymerases, namely POLK, REV1, REV3L and REV7. Our data confirms that out-of-context somatic expression of HORMAD1 can lead to genomic instability and reveals that HORMAD1 expression induces dependencies upon replication stress tolerance pathways, such as translesion synthesis. Our data also suggest that HORMAD1 expression could be a patient selection biomarker for agents targeting replication stress.

Fatty acid synthase (FASN) is commonly overexpressed in prostate cancer and associated with tumour progression. FASN is responsible for de novo synthesis of the fatty acid palmitate; the building block for protein palmitoylation. Recent work has suggested that alongside its established role in promoting cell proliferation FASN may also promote invasion. We now find depletion of FASN expression increases prostate cancer cell adhesiveness, impairs HGF-mediated cell migration and reduces 3D invasion. These changes in motility suggest that FASN can mediate actin cytoskeletal remodelling; a process known to be downstream of Rho family GTPases. Here, we demonstrate that modulation of FASN expression specifically impacts on the palmitoylation of the atypical GTPase RhoU. Impaired RhoU activity in FASN depleted cells leads to reduced adhesion turnover downstream of paxillin serine phosphorylation, which is rescued by addition of exogenous palmitate. Moreover, canonical Cdc42 expression is dependent on the palmitoylation status of RhoU. Thus we uncover a novel relationship between FASN, RhoU and Cdc42 that directly influences cell migration potential. These results provide compelling evidence that FASN activity directly promotes cell migration and supports FASN as a potential therapeutic target in metastatic prostate cancer.

The level of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative (TNBC) and HER2-positive breast cancers convey prognostic information. The importance of systemic immunity to local immunity is unknown in breast cancer. We previously demonstrated that histological alterations in axillary lymph nodes (LNs) carry clinical relevance. Here, we capture local immune responses by scoring TILs at the primary tumor and systemic immune responses by recording the formation of secondary follicles, also known as germinal centers, in 2,857 cancer-free and involved axillary LNs on haematoxylin and eosin (H&E) stained sections from a retrospective cohort of 161 LN-positive triple-negative and HER2-positive breast cancer patients. Our data demonstrate that the number of germinal center formations across all cancer-free LNs, similar to high levels of TILs, is associated with a good prognosis in low TILs TNBC. This highlights the importance of assessing both primary and LN immune responses for prognostication and for future breast cancer research.

Background Lobular carcinoma in situ (LCIS) is a non-invasive breast lesion that is typically found incidentally on biopsy and is often associated with invasive lobular carcinoma (ILC). LCIS is considered by some to be a risk factor for future breast cancer rather than a true precursor lesion. The aim of this study was to identify genetic changes that could be used as biomarkers of progression of LCIS to invasive disease using cases of pure LCIS and comparing their genetic profiles to LCIS which presented contemporaneously with associated ILC, on the hypothesis that the latter represents LCIS that has already progressed. Methods Somatic copy number aberrations (SCNAs) were assessed by SNP array in three subgroups: pure LCIS, LCIS associated with ILC and the paired ILC. In addition exome sequencing was performed on seven fresh frozen samples of LCIS associated with ILC, to identify recurrent somatic mutations. Results The copy number profiles of pure LCIS and LCIS associated with ILC were almost identical. However, four SCNAs were more frequent in ILC than LCIS associated with ILC, including gain/amplification of CCND1. CCND1 protein over-expression assessed by immunohistochemical analysis in a second set of samples from 32 patients with pure LCIS and long-term follow up, was associated with invasive recurrence (P = 0.02, Fisher’s exact test). Exome sequencing revealed that PIK3CA mutations were as frequent as CDH1 mutations in LCIS, but were not a useful biomarker of LCIS progression as they were as frequent in pure LCIS as in LCIS associated with ILC. We also observed heterogeneity of PIK3CA mutations and evidence of sub-clonal populations in LCIS irrespective of whether they were associated with ILC. Conclusions Our data shows that pure LCIS and LCIS co-existing with ILC have very similar SCNA profiles, supporting the hypothesis that LCIS is a true precursor lesion. We have provided evidence that over-expression of CCND1 may identify a subgroup of patients with pure LCIS who are more likely to develop invasive disease, in contrast to PIK3CA mutations, which occur too early in lobular tumorigenesis to be informative. Electronic supplementary material The online version of this article (doi:10.1186/s13058-016-0789-y) contains supplementary material, which is available to authorized users.

Introduction Triple-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. Methods Mammary 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. Results A 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. Conclusions Our 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. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0539-6) contains supplementary material, which is available to authorized users.

Triple-negative breast cancers (TNBCs) have poor prognosis and lack targeted therapies. Interrogation of genomic datasets identified increased PIM1 copy number-driven expression in TNBC. RNA interference in breast cancer and non-malignant mammary epithelial cell models revealed a PIM1 dependency in TNBC cells for proliferation and apoptotic protection, absent in non-malignant cells. PIM1 knockdown reduced BCL2 expression, and dynamic BH3 profiling analysis revealed that PIM1 prevents mitochondrial-mediated apoptosis in TNBC cell lines. PIM1 expression associates with several MYC-transcriptional signatures and promotes cell population growth through regulation of c-MYC and transcription of MYC-targets, including MCL1. The pan-PIM kinase inhibitor AZD1208 inhibited growth and sensitized TNBC cell lines, xenografts and patient-derived xenografts to standard of care chemotherapy. We identify PIM1 as a malignant cell-selective target in TNBC, illustrating relationships with MYC activation, regulation of anti-apoptotic BCL2 and MCL1, established TNBC oncogenic proteins SHP2 and EPHA2 and cell cycle inhibitor p27. Finally we identify a potential use of PIM1 inhibitors to abrogate TNBC's high threshold to TNBC standard of care chemotherapy induced apoptotic cell death.

Testing the statistical associations between microarray-based gene expression signatures and patient outcome has become a popular approach to infer biological and clinical significance of laboratory observations. Venet and colleagues recently demonstrated that the majority of randomly generated gene signatures are significantly associated with outcome of breast cancer patients, and that this association stems from the fact that a large proportion of the transcriptome is significantly correlated with proliferation, a strong predictor of outcome in breast cancer patients. These findings demonstrate that a statistical association between a gene signature and disease outcome does not necessarily imply biological significance.

Background Genomic copy number changes and regional alterations in epigenetic states have been linked to grade in breast cancer. However, the relative contribution of specific alterations to the pathology of different breast cancer subtypes remains unclear. The heterogeneity and interplay of genomic and epigenetic variations means that large datasets and statistical data mining methods are required to uncover recurrent patterns that are likely to be important in cancer progression. Results We employed ridge regression to model the relationship between regional changes in gene expression and proliferation. Regional features were extracted from tumour gene expression data using a novel clustering method, called genomic distance entrained agglomerative (GDEC) clustering. Using gene expression data in this way provides a simple means of integrating the phenotypic effects of both copy number aberrations and alterations in chromatin state. We show that regional metagenes derived from GDEC clustering are representative of recurrent regions of epigenetic regulation or copy number aberrations in breast cancer. Furthermore, detected patterns of genomic alterations are conserved across independent oestrogen receptor positive breast cancer datasets. Sequential competitive metagene selection was used to reveal the relative importance of genomic regions in predicting proliferation rate. The predictive model suggested additive interactions between the most informative regions such as 8p22-12 and 8q13-22. Conclusions Data-mining of large-scale microarray gene expression datasets can reveal regional clusters of co-ordinate gene expression, independent of cause. By correlating these clusters with tumour proliferation we have identified a number of genomic regions that act together to promote proliferation in ER+ breast cancer. Identification of such regions should enable prioritisation of genomic regions for combinatorial functional studies to pinpoint the key genes and interactions contributing to tumourigenicity.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.