Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning

Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they provide a wealth of information about gene expression at the cell level, but they are expensive, hindering their use in large-scale clinical oncology studies. Predicting gene expression from hematoxylin and eosin stained histology images provides a more affordable alternative for such studies. Here we present BrST-Net, a deep learning framework for predicting gene expression from histopathology images using spatial transcriptomics data. Using this framework, we trained and evaluated four distinct state-of-the-art deep learning architectures, which include ResNet101, Inception-v3, EfficientNet (with six different variants), and vision transformer (with two different variants), all without utilizing pretrained weights for the prediction of 250 genes. To enhance the generalisation performance of the main network, we introduce an auxiliary network into the framework. Our methodology outperforms previous studies, with 237 genes identified with positive correlation, including 24 genes with a median correlation coefficient greater than 0.50. This is a notable improvement over previous studies, which could predict only 102 genes with positive correlation, with the highest correlation values ranging from 0.29 to 0.34.

MCP-1 expression in breast cancer and its association with distant relapse

BACKGROUND

Distant relapse of breast cancer complicates management of the disease and accounts for 90% of breast cancer-related deaths. Monocyte chemoattractant protein-1 (MCP-1) has critical roles in breast cancer progression and is widely accepted as a pro-metastatic chemokine.

METHODS

This study explored MCP-1 expression in the primary tumour of 251 breast cancer patients. A simplified 'histoscore' was used to determine if each tumour had high or low expression of MCP-1. Patient breast cancers were retrospectively staged based on available patient data. p < 0.05 was used to determine significance and changes in hazard ratios between models were considered.

RESULTS

Low MCP-1 expression in the primary tumour was associated with breast cancer-related death with distant relapse in ER- breast cancers (p < 0.01); however, this was likely a result of most low MCP-1-expressing ER- breast cancers being Stage III or Stage IV, with high MCP-1 expression in the primary tumour significantly correlated with Stage I breast cancers (p < 0.05). Expression of MCP-1 in the primary ER- tumours varied across Stage I, II, III and IV and we highlighted a switch in MCP-1 expression from high in Stage I ER- cancers to low in Stage IV ER- cancers.

CONCLUSION

This study has emphasised a critical need for further investigation into MCP-1's role in breast cancer progression and improved characterisation of MCP-1 in breast cancers, particularly in light of the development of anti-MCP-1, anti-metastatic therapies.

hist2RNA: An Efficient Deep Learning Architecture to Predict Gene Expression from Breast Cancer Histopathology Images

Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC). However, in the clinic, molecular profiling is primarily used for ER+ breast cancer, which is costly, tissue destructive, requires specialised platforms, and takes several weeks to obtain a result. Deep learning algorithms can effectively extract morphological patterns in digital histopathology images to predict molecular phenotypes quickly and cost-effectively. We propose a new, computationally efficient approach called hist2RNA inspired by bulk RNA sequencing techniques to predict the expression of 138 genes (incorporated from 6 commercially available molecular profiling tests), including luminal PAM50 subtype, from hematoxylin and eosin (H&E)-stained whole slide images (WSIs). The training phase involves the aggregation of extracted features for each patient from a pretrained model to predict gene expression at the patient level using annotated H&E images from The Cancer Genome Atlas (TCGA, n = 335). We demonstrate successful gene prediction on a held-out test set (n = 160, corr = 0.82 across patients, corr = 0.29 across genes) and perform exploratory analysis on an external tissue microarray (TMA) dataset (n = 498) with known IHC and survival information. Our model is able to predict gene expression and luminal PAM50 subtype (Luminal A versus Luminal B) on the TMA dataset with prognostic significance for overall survival in univariate analysis (c-index = 0.56, hazard ratio = 2.16 (95% CI 1.12-3.06), p < 5 × 10^-3), and independent significance in multivariate analysis incorporating standard clinicopathological variables (c-index = 0.65, hazard ratio = 1.87 (95% CI 1.30-2.68), p < 5 × 10^-3). The proposed strategy achieves superior performance while requiring less training time, resulting in less energy consumption and computational cost compared to patch-based models. Additionally, hist2RNA predicts gene expression that has potential to determine luminal molecular subtypes which correlates with overall survival, without the need for expensive molecular testing.

Survival prediction in triple negative breast cancer using multiple instance learning of histopathological images

Computational pathology is a rapidly expanding area for research due to the current global transformation of histopathology through the adoption of digital workflows. Survival prediction of breast cancer patients is an important task that currently depends on histopathology assessment of cancer morphological features, immunohistochemical biomarker expression and patient clinical findings. To facilitate the manual process of survival risk prediction, we developed a computational pathology framework for survival prediction using digitally scanned haematoxylin and eosin-stained tissue microarray images of clinically aggressive triple negative breast cancer. Our results show that the model can produce an average concordance index of 0.616. Our model predictions are analysed for independent prognostic significance in univariate analysis (hazard ratio = 3.12, 95% confidence interval [1.69,5.75], p < 0.005) and multivariate analysis using clinicopathological data (hazard ratio = 2.68, 95% confidence interval [1.44,4.99], p < 0.005). Through qualitative analysis of heatmaps generated from our model, an expert pathologist is able to associate tissue features highlighted in the attention heatmaps of high-risk predictions with morphological features associated with more aggressive behaviour such as low levels of tumour infiltrating lymphocytes, stroma rich tissues and high-grade invasive carcinoma, providing explainability of our method for triple negative breast cancer.

ALTEN: A High-Fidelity Primary Tissue-Engineering Platform to Assess Cellular Responses Ex Vivo

To fully investigate cellular responses to stimuli and perturbations within tissues, it is essential to replicate the complex molecular interactions within the local microenvironment of cellular niches. Here, the authors introduce Alginate-based tissue engineering (ALTEN), a biomimetic tissue platform that allows ex vivo analysis of explanted tissue biopsies. This method preserves the original characteristics of the source tissue's cellular milieu, allowing multiple and diverse cell types to be maintained over an extended period of time. As a result, ALTEN enables rapid and faithful characterization of perturbations across specific cell types within a tissue. Importantly, using single-cell genomics, this approach provides integrated cellular responses at the resolution of individual cells. ALTEN is a powerful tool for the analysis of cellular responses upon exposure to cytotoxic agents and immunomodulators. Additionally, ALTEN's scalability using automated microfluidic devices for tissue encapsulation and subsequent transport, to enable centralized high-throughput analysis of samples gathered by large-scale multicenter studies, is shown.

Multiplexed immunofluorescence identifies high stromal CD68+PD-L1+ macrophages as a predictor of improved survival in triple negative breast cancer

Triple negative breast cancer (TNBC) comprises 10-15% of all breast cancers and has a poor prognosis with a high risk of recurrence within 5 years. PD-L1 is an important biomarker for patient selection for immunotherapy but its cellular expression and co-localization within the tumour immune microenvironment and associated prognostic value is not well defined. We aimed to characterise the phenotypes of immune cells expressing PD-L1 and determine their association with overall survival (OS) and breast cancer-specific survival (BCSS). Using tissue microarrays from a retrospective cohort of TNBC patients from St George Hospital, Sydney (n = 244), multiplexed immunofluorescence (mIF) was used to assess staining for CD3, CD8, CD20, CD68, PD-1, PD-L1, FOXP3 and pan-cytokeratin on the Vectra Polaris™ platform and analysed using QuPath. Cox multivariate analyses showed high CD68+PD-L1+ stromal cell counts were associated with improved prognosis for OS (HR 0.56, 95% CI 0.33-0.95, p = 0.030) and BCSS (HR 0.47, 95% CI 0.25-0.88, p = 0.018) in the whole cohort and in patients receiving chemotherapy, improving incrementally upon the predictive value of PD-L1+ alone for BCSS. These data suggest that CD68+PD-L1+ status can provide clinically useful prognostic information to identify sub-groups of patients with good or poor prognosis and guide treatment decisions in TNBC.

Id Proteins Promote a Cancer Stem Cell Phenotype in Mouse Models of Triple Negative Breast Cancer via Negative Regulation of Robo1

Breast cancers display phenotypic and functional heterogeneity and several lines of evidence support the existence of cancer stem cells (CSCs) in certain breast cancers, a minor population of cells capable of tumor initiation and metastatic dissemination. Identifying factors that regulate the CSC phenotype is therefore important for developing strategies to treat metastatic disease. The Inhibitor of Differentiation Protein 1 (Id1) and its closely related family member Inhibitor of Differentiation 3 (Id3) (collectively termed Id) are expressed by a diversity of stem cells and are required for metastatic dissemination in experimental models of breast cancer. In this study, we show that ID1 is expressed in rare neoplastic cells within ER-negative breast cancers. To address the function of Id1 expressing cells within tumors, we developed independent murine models of Triple Negative Breast Cancer (TNBC) in which a genetic reporter permitted the prospective isolation of Id1+ cells. Id1+ cells are enriched for self-renewal in tumorsphere assays in vitro and for tumor initiation in vivo. Conversely, depletion of Id1 and Id3 in the 4T1 murine model of TNBC demonstrates that Id1/3 are required for cell proliferation and self-renewal in vitro, as well as primary tumor growth and metastatic colonization of the lung in vivo. Using combined bioinformatic analysis, we have defined a novel mechanism of Id protein function via negative regulation of the Roundabout Axon Guidance Receptor Homolog 1 (Robo1) leading to activation of a Myc transcriptional programme.

Elevated levels of tumour apolipoprotein D independently predict poor outcome in breast cancer patients

AIMS

Apolipoprotein D (ApoD) is a protein that is regulated by androgen and oestrogen, and is a major constituent of breast cysts. Although ApoD has been reported to be a marker of breast cancer, its prognostic importance in invasive breast cancer is unclear. The aim of this study was to investigate the relationship between ApoD protein expression, oestrogen receptor-α (ERα) expression and androgen receptor (AR) expression in predicting breast cancer outcome.

METHODS AND RESULTS

ApoD levels were measured by the use of immunohistochemistry and video image analysis on tissue sections from a breast cancer cohort (n = 214). We assessed the associations of ApoD expression with disease-free survival (DFS), metastasis-free survival (MFS), and overall survival (OS). We also assessed the relationship between ApoD expression, AR expression and ERα expression in predicting OS. ApoD expression (>1% ApoD positivity) was found in 72% (154/214) of tissues. High ApoD positivity (≥20.7%, fourth quartile) was an independent predictor of MFS and OS, and conferred a 2.2-fold increased risk of developing metastatic disease and a 2.1-fold increased risk of breast cancer-related death. ApoD positivity was not associated with AR or ERα nuclear positivity. However, patients with (≥1%) ERα-positive cancers with low (<20.7%) ApoD positivity, or those showing high (≥78%) AR positivity and low (<20.7%) ApoD positivity had better OS than other patient groups.

CONCLUSIONS

ApoD expression could be used to predict breast cancer prognosis independently of ERα and AR expression.

The Magnitude of Androgen Receptor Positivity in Breast Cancer Is Critical for Reliable Prediction of Disease Outcome

Purpose: Consensus is lacking regarding the androgen receptor (AR) as a prognostic marker in breast cancer. The objectives of this study were to comprehensively review the literature on AR prognostication and determine optimal criteria for AR as an independent predictor of breast cancer survival.Experimental Design: AR positivity was assessed by immunostaining in two clinically validated primary breast cancer cohorts [training cohort, n = 219; validation cohort, n = 418; 77% and 79% estrogen receptor alpha (ERα) positive, respectively]. The optimal AR cut-point was determined by ROC analysis in the training cohort and applied to both cohorts.Results: AR was an independent prognostic marker of breast cancer outcome in 22 of 46 (48%) previous studies that performed multivariate analyses. Most studies used cut-points of 1% or 10% nuclear positivity. Herein, neither 1% nor 10% cut-points were robustly prognostic. ROC analysis revealed that a higher AR cut-point (78% positivity) provided optimal sensitivity and specificity to predict breast cancer survival in the training (HR, 0.41; P = 0.015) and validation (HR, 0.50; P = 0.014) cohorts. Tenfold cross-validation confirmed the robustness of this AR cut-point. Patients with ERα-positive tumors and AR positivity ≥78% had the best survival in both cohorts (P < 0.0001). Among the combined ERα-positive cases, those with comparable or higher levels of AR (AR:ERα-positivity ratio >0.87) had the best outcomes (P < 0.0001).Conclusions: This study defines an optimal AR cut-point to reliably predict breast cancer survival. Testing this cut-point in prospective cohorts is warranted for implementation of AR as a prognostic factor in the clinical management of breast cancer. Clin Cancer Res; 24(10); 2328-41. ©2018 AACR.

Andy's Algorithms: new automated digital image analysis pipelines for FIJI

Quantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy's Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3'-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy's Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy's algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy's Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm .

MCL-1 inhibition provides a new way to suppress breast cancer metastasis and increase sensitivity to dasatinib

BACKGROUND

Metastatic disease is largely resistant to therapy and accounts for almost all cancer deaths. Myeloid cell leukemia-1 (MCL-1) is an important regulator of cell survival and chemo-resistance in a wide range of malignancies, and thus its inhibition may prove to be therapeutically useful.

METHODS

To examine whether targeting MCL-1 may provide an effective treatment for breast cancer, we constructed inducible models of BIMs2A expression (a specific MCL-1 inhibitor) in MDA-MB-468 (MDA-MB-468-2A) and MDA-MB-231 (MDA-MB-231-2A) cells.

RESULTS

MCL-1 inhibition caused apoptosis of basal-like MDA-MB-468-2A cells grown as monolayers, and sensitized them to the BCL-2/BCL-XL inhibitor ABT-263, demonstrating that MCL-1 regulated cell survival. In MDA-MB-231-2A cells, grown in an organotypic model, induction of BIMs2A produced an almost complete suppression of invasion. Apoptosis was induced in such a small proportion of these cells that it could not account for the large decrease in invasion, suggesting that MCL-1 was operating via a previously undetected mechanism. MCL-1 antagonism also suppressed local invasion and distant metastasis to the lung in mouse mammary intraductal xenografts. Kinomic profiling revealed that MCL-1 antagonism modulated Src family kinases and their targets, which suggested that MCL-1 might act as an upstream modulator of invasion via this pathway. Inhibition of MCL-1 in combination with dasatinib suppressed invasion in 3D models of invasion and inhibited the establishment of tumors in vivo.

CONCLUSION

These data provide the first evidence that MCL-1 drives breast cancer cell invasion and suggests that MCL-1 antagonists could be used alone or in combination with drugs targeting Src kinases such as dasatinib to suppress metastasis.

ELF5 Drives Lung Metastasis in Luminal Breast Cancer through Recruitment of Gr1+ CD11b+ Myeloid-Derived Suppressor Cells

During pregnancy, the ETS transcription factor ELF5 establishes the milk-secreting alveolar cell lineage by driving a cell fate decision of the mammary luminal progenitor cell. In breast cancer, ELF5 is a key transcriptional determinant of tumor subtype and has been implicated in the development of insensitivity to anti-estrogen therapy. In the mouse mammary tumor virus-Polyoma Middle T (MMTV-PyMT) model of luminal breast cancer, induction of ELF5 levels increased leukocyte infiltration, angiogenesis, and blood vessel permeability in primary tumors and greatly increased the size and number of lung metastasis. Myeloid-derived suppressor cells, a group of immature neutrophils recently identified as mediators of vasculogenesis and metastasis, were recruited to the tumor in response to ELF5. Depletion of these cells using specific Ly6G antibodies prevented ELF5 from driving vasculogenesis and metastasis. Expression signatures in luminal A breast cancers indicated that increased myeloid cell invasion and inflammation were correlated with ELF5 expression, and increased ELF5 immunohistochemical staining predicted much shorter metastasis–free and overall survival of luminal A patients, defining a group who experienced unexpectedly early disease progression. Thus, in the MMTV-PyMT mouse mammary model, increased ELF5 levels drive metastasis by co-opting the innate immune system. As ELF5 has been previously implicated in the development of antiestrogen resistance, this finding implicates ELF5 as a defining factor in the acquisition of the key aspects of the lethal phenotype in luminal A breast cancer.

Up-regulation of the transcription factor ELF5 in tumors helps to create a micro-environment that recruits the innate immune system and increases vascular permeability, leading to increased metastasis in luminal breast cancer. Together with its role in anti-estrogen resistance, this suggests that ELF5 is a major driver of a lethal phenotype.

The transcription factor Elf5 defines hormone-insensitive and endocrine-therapy–resistant breast cancer. In this study, we have discovered that ELF5 drives the spread of tumor cells to the lungs. We demonstrate that the underlying mechanism for this metastatic spread is via recruitment of the innate immune system. Interestingly, this effect is able to overcome the other tumor-suppressive effects of ELF5 on cancer cells, such as reduced proliferation, motility, and invasion. This important finding challenges the more conventional view that the most potent determinant of metastatic activity lies within the cancer cell. We clearly demonstrate that the innate immune system strongly influences the metastatic activity of cancer cells despite their cell-intrinsic spread potential. Our previous work demonstrated that in luminal breast cancer, ELF5 is a key determinant of antiestrogen therapy resistance. Here, we show that the metastatic mechanism driven by ELF5 is most important in luminal breast cancer patients, in whom higher ELF5 expression is associated with low presence of cytotoxic T lymphocytes, an immune cell population responsible for tumor rejection. Thus, we now see that ELF5 may be behind the two most important processes that cause luminal breast cancers to progress towards the lethal phenotype; resistance to antiestrogen therapy and the development of metastatic activity. This understanding could pave the way for new therapeutic strategies to be devised and new predictive tests to be developed.

MicroRNA-Related DNA Repair/Cell-Cycle Genes Independently Associated With Relapse After Radiation Therapy for Early Breast Cancer

PURPOSE

Local recurrence and distant failure after adjuvant radiation therapy for breast cancer remain significant clinical problems, incompletely predicted by conventional clinicopathologic markers. We had previously identified microRNA-139-5p and microRNA-1274a as key regulators of breast cancer radiation response in vitro. The purpose of this study was to investigate standard clinicopathologic markers of local recurrence in a contemporary series and to establish whether putative target genes of microRNAs involved in DNA repair and cell cycle control could better predict radiation therapy response in vivo.

METHODS AND MATERIALS

With institutional ethics board approval, local recurrence was measured in a contemporary, prospectively collected series of 458 patients treated with radiation therapy after breast-conserving surgery. Additionally, independent publicly available mRNA/microRNA microarray expression datasets totaling >1000 early-stage breast cancer patients, treated with adjuvant radiation therapy, with >10 years of follow-up, were analyzed. The expression of putative microRNA target biomarkers--TOP2A, POLQ, RAD54L, SKP2, PLK2, and RAG1--were correlated with standard clinicopathologic variables using 2-sided nonparametric tests, and to local/distant relapse and survival using Kaplan-Meier and Cox regression analysis.

RESULTS

We found a low rate of isolated local recurrence (1.95%) in our modern series, and that few clinicopathologic variables (such as lymphovascular invasion) were significantly predictive. In multiple independent datasets (n>1000), however, high expression of RAD54L, TOP2A, POLQ, and SKP2 significantly correlated with local recurrence, survival, or both in univariate and multivariate analyses (P<.001). Low RAG1 expression significantly correlated with local recurrence (multivariate, P=.008). Additionally, RAD54L, SKP2, and PLK2 may be predictive, being prognostic in radiation therapy-treated patients but not in untreated matched control individuals (n=107; P<.05).

CONCLUSIONS

Biomarkers of DNA repair and cell cycle control can identify patients at high risk of treatment failure in those receiving radiation therapy for early breast cancer in independent cohorts. These should be further investigated prospectively, especially TOP2A and SKP2, for which targeted therapies are available.

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

INTRODUCTION

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

METHOD

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

RESULTS

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

CONCLUSIONS

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.

Assessment of DNA methylation profiling and copy number variation as indications of clonal relationship in ipsilateral and contralateral breast cancers to distinguish recurrent breast cancer from a second primary tumour

BACKGROUND

Patients with breast cancer have an increased risk of developing subsequent breast cancers. It is important to distinguish whether these tumours are de novo or recurrences of the primary tumour in order to guide the appropriate therapy. Our aim was to investigate the use of DNA methylation profiling and array comparative genomic hybridization (aCGH) to determine whether the second tumour is clonally related to the first tumour.

METHODS

Methylation-sensitive high-resolution melting was used to screen promoter methylation in a panel of 13 genes reported as methylated in breast cancer (RASSF1A, TWIST1, APC, WIF1, MGMT, MAL, CDH13, RARβ, BRCA1, CDH1, CDKN2A, TP73, and GSTP1) in 29 tumour pairs (16 ipsilateral and 13 contralateral). Using the methylation profile of these genes, we employed a Bayesian and an empirical statistical approach to estimate clonal relationship. Copy number alterations were analysed using aCGH on the same set of tumour pairs.

RESULTS

There is a higher probability of the second tumour being recurrent in ipsilateral tumours compared with contralateral tumours (38 % versus 8 %; p <0.05) based on the methylation profile. Using previously reported recurrence rates as Bayesian prior probabilities, we classified 69 % of ipsilateral and 15 % of contralateral tumours as recurrent. The inferred clonal relationship results of the tumour pairs were generally concordant between methylation profiling and aCGH.

CONCLUSION

Our results show that DNA methylation profiling as well as aCGH have potential as diagnostic tools in improving the clinical decisions to differentiate recurrences from a second de novo tumour.

Global characterization of signalling networks associated with tamoxifen resistance in breast cancer

Acquired resistance to the anti-estrogen tamoxifen remains a significant challenge in breast cancer management. In this study, we used an integrative approach to characterize global protein expression and tyrosine phosphorylation events in tamoxifen-resistant MCF7 breast cancer cells (TamR) compared with parental controls. Quantitative mass spectrometry and computational approaches were combined to identify perturbed signalling networks, and candidate regulatory proteins were functionally interrogated by siRNA-mediated knockdown. Network analysis revealed that cellular metabolism was perturbed in TamR cells, together with pathways enriched for proteins associated with growth factor, cell-cell and cell matrix-initiated signalling. Consistent with known roles for Ras/MAPK and PI3-kinase signalling in tamoxifen resistance, tyrosine-phosphorylated MAPK1, SHC1 and PIK3R2 were elevated in TamR cells. Phosphorylation of the tyrosine kinase Yes and expression of the actin-binding protein myristoylated alanine-rich C-kinase substrate (MARCKS) were increased two- and eightfold in TamR cells respectively, and these proteins were selected for further analysis. Knockdown of either protein in TamR cells had no effect on anti-estrogen sensitivity, but significantly decreased cell motility. MARCKS expression was significantly higher in breast cancer cell lines than normal mammary epithelial cells and in ER-negative versus ER-positive breast cancer cell lines. In primary breast cancers, cytoplasmic MARCKS staining was significantly higher in basal-like and HER2 cancers than in luminal cancers, and was independently predictive of poor survival in multivariate analyses of the whole cohort (P < 0.0001) and in ER-positive patients (P = 0.0005). These findings provide network-level insights into the molecular alterations associated with the tamoxifen-resistant phenotype, and identify MARCKS as a potential biomarker of therapeutic responsiveness that may assist in stratification of patients for optimal therapy.

Transcription factor ATF3 links host adaptive response to breast cancer metastasis

Host response to cancer signals has emerged as a key factor in cancer development; however, the underlying molecular mechanism is not well understood. In this report, we demonstrate that activating transcription factor 3 (ATF3), a hub of the cellular adaptive response network, plays an important role in host cells to enhance breast cancer metastasis. Immunohistochemical analysis of patient tumor samples revealed that expression of ATF3 in stromal mononuclear cells, but not cancer epithelial cells, is correlated with worse clinical outcomes and is an independent predictor for breast cancer death. This finding was corroborated by data from mouse models showing less efficient breast cancer metastasis in Atf3-deficient mice than in WT mice. Further, mice with myeloid cell-selective KO of Atf3 showed fewer lung metastases, indicating that host ATF3 facilitates metastasis, at least in part, by its function in macrophage/myeloid cells. Gene profiling analyses of macrophages from mouse tumors identified an ATF3-regulated gene signature that could distinguish human tumor stroma from distant stroma and could predict clinical outcomes, lending credence to our mouse models. In conclusion, we identified ATF3 as a regulator in myeloid cells that enhances breast cancer metastasis and has predictive value for clinical outcomes.

Prognostic interaction between expression of p53 and estrogen receptor in patients with node-negative breast cancer: results from IBCSG Trials VIII and IX

INTRODUCTION

The prognostic significance of p53 protein expression in early breast cancer remains uncertain, with some but not all studies finding an association with poorer outcomes. Estrogen receptor (ER) expression is both a positive prognostic marker and predictive of response to endocrine therapies. The relationship between these biomarkers is unknown.

METHODS

We constructed tissue microarrays (TMAs) from available pathological material from 1113 patients participating in two randomized clinical trials comparing endocrine therapy alone versus chemo-endocrine therapy in node-negative breast cancer. Expression of p53 defined as >10% positive nuclei was analyzed together with prior immunohistochemical assays of ER performed at central pathological review of whole tumor sections.

RESULTS

ER was present (i.e. >1% positive tumor cell nuclei) in 80.1% (880/1092). p53 expression was significantly more frequent when ER was absent, 125/212 (59%) than when ER was present, 171/880 (19%), p <0.0001. A significant qualitative interaction was observed such that p53 expression was associated with better disease-free survival (DFS) and overall survival (OS) among patients whose tumors did not express ER, but worse DFS and OS among patients whose tumors expressed ER. The interaction remained significant after allowance for pathologic variables, and treatment. Similar effects were seen when luminal and non-luminal intrinsic subtypes were compared.

CONCLUSIONS

Interpretation of the prognostic significance of p53 expression requires knowledge of concurrent expression of ER. The reason for the interaction between p53 and ER is unknown but may reflect qualitatively different p53 mutations underlying the p53 expression in tumors with or without ER expression.

TRIAL REGISTRATION

Current Controlled Trials ACTRN12607000037404 (Trial VIII) and ACTRN12607000029493 (Trial IX).

Prediction of outcome of early ER+ breast cancer is improved using a biomarker panel, which includes Ki-67 and p53

Background:

The aim of this study is to determine whether immunohistochemical (IHC) assessment of Ki67 and p53 improves prognostication of oestrogen receptor-positive (ER+) breast cancer after breast-conserving therapy (BCT). In all, 498 patients with invasive breast cancer from a randomised trial of BCT with or without tumour bed radiation boost were assessed using IHC.

Methods:

The ER+ tumours were classified as ‘luminal A’ (LA): ER+ and/or PR+, Ki-67 low, p53−, HER2− or ‘luminal B’ (LB): ER+ and/or PR+and/or Ki-67 high and/or p53+ and/or HER2+. Kaplan–Meier and Cox proportional hazards methodology were used to ascertain relationships to ispilateral breast tumour recurrence (IBTR), locoregional recurrence (LRR), distant metastasis-free survival (DMFS) and breast cancer-specific survival (BCSS).

Results:

In all, 73 patients previously LA were re-classified as LB: a greater than four-fold increase (4.6–19.3%) compared with ER, PR, HER2 alone. In multivariate analysis, the LB signature independently predicted LRR (hazard ratio (HR) 3.612, 95% CI 1.555–8.340, P=0.003), DMFS (HR 3.023, 95% CI 1.501–6.087, P=0.002) and BCSS (HR 3.617, 95% CI 1.629–8.031, P=0.002) but not IBTR.

Conclusion:

The prognostic evaluation of ER+ breast cancer is improved using a marker panel, which includes Ki-67 and p53. This may help better define a group of poor prognosis ER+ patients with a greater probability of failure with endocrine therapy.

Recruitment of regulatory T cells is correlated with hypoxia-induced CXCR4 expression, and is associated with poor prognosis in basal-like breast cancers

Introduction

Basal-like breast cancers behave more aggressively despite the presence of a dense lymphoid infiltrate. We hypothesised that immune suppression in this subtype may be due to T regulatory cells (Treg) recruitment driven by hypoxia-induced up-regulation of CXCR4 in Treg.

Methods

Immunoperoxidase staining for FOXP3 and CXCL12 was performed on tissue microarrays from 491 breast cancers. The hypoxia-associated marker carbonic anhydrase IX (CA9) and double FOXP3/CXCR4 staining were performed on sections from a subset of these cancers including 10 basal-like and 11 luminal cancers matched for tumour grade.

Results

High Treg infiltration correlated with tumour CXCL12 positivity (OR 1.89, 95% CI 1.22 to 2.94, P = 0.004) and basal phenotype (OR 3.14, 95% CI 1.08 to 9.17, P = 0.004) in univariate and multivariate analyses. CXCL12 positivity correlated with improved survival (P = 0.005), whereas high Treg correlated with shorter survival for all breast cancers (P = 0.001), luminal cancers (P < 0.001) and basal-like cancers (P = 0.040) that were confirmed in a multivariate analysis (OR 1.61, 95% CI 1.02 to 2.53, P = 0.042). In patients treated with hormone therapy, high Treg were associated with a shorter survival in a multivariate analysis (OR 1.78, 95% CI 1.01 to 3.15, P = 0.040). There was a tendency for luminal cancers to show CXCL12 expression (102/138, 74%) compared to basal-like cancers (16/27, 59%), which verged on statistical significance (P = 0.050). Up-regulation of CXCR4 in Treg correlated with the basal-like phenotype (P = 0.029) and tumour hypoxia, as indicated by CA9 expression (P = 0.049).

Conclusions

Our data show that in the setting of hypoxia and CXCR4 up-regulation in Treg, CXCL12 expression may have the negative consequence of enhancing Treg recruitment and suppressing the anti-tumour immune response.

The expression of the ubiquitin ligase SIAH2 (seven in absentia homolog 2) is mediated through gene copy number in breast cancer and is associated with a basal-like phenotype and p53 expression

Introduction

The seven in absentia homolog 2 (SIAH2) protein plays a significant role in the hypoxic response by regulating the abundance of hypoxia-inducible factor-α; however, its role in breast carcinoma is unclear. We investigated the frequency and expression pattern of SIAH2 in two independent cohorts of sporadic breast cancers.

Methods

Immunohistochemical evaluation of SIAH2protein expression was conducted in normal breast tissues and in tissue microarrays comprising ductal carcinoma in situ (DCIS) and a cohort of invasive breast carcinomas. Correlation analysis was performed between SIAH2 and clinicopathological variables and intrinsic breast cancer subgroups and validated in a cohort of 293 invasive ductal carcinomas. Promoter methylation, gene copy number and mRNA expression of SIAH2 were determined in a panel of basal-like tumors and cell lines.

Results

There was a significant increase in nuclear SIAH2 expression from normal breast tissues through to DCIS and progression to invasive cancers. A significant inverse correlation was apparent between SIAH2 and estrogen receptor and progesterone receptor and a positive association with tumor grade, HER2, p53 and an intrinsic basal-like subtype. Logistic regression analysis confirmed the significant positive association between SIAH2 expression and the basal-like phenotype. No SIAH2 promoter methylation was identified, yet there was a significant correlation between SIAH2 mRNA and gene copy number. SIAH2-positive tumors were associated with a shorter relapse-free survival in univariate but not multivariate analysis.

Conclusions

SIAH2 expression is upregulated in basal-like breast cancers via copy number changes and/or transcriptional activation by p53 and is likely to be partly responsible for the enhanced hypoxic drive through abrogation of the prolyl hydroxylases.

Abstract S6-8: Hedgehog Ligand Overexpression Predicts Poor Outcome in Breast Cancer and Is a Potential Therapeutic Target for Metastatic Disease

Background: The Hh signalling pathway plays an important role in a number of malignancies, and accumulating data suggest it contributes significantly to the development and progression of breast cancer. However, there is scant data regarding the clinical significance of its dysregulation in breast cancer and its functional effects in breast cancer models.

Methods: We investigated the clinical significance of the expression of Hh pathway components using immunohistochemistry in a well-characterised cohort of 279 patients with invasive ductal carcinoma (IDC) to determine its prognostic significance. A murine mammary cancer allograft model based on the M6 cell line, derived from the C3/SV40T transgenic mouse was used to determine the effects of Shh overexpression on tumour growth in vitro and in vivo. Finally, the therapeutic potential of Hh blockade using the monoclonal antibody 5E1 was also explored in two mouse mammary carcinoma models; the M6 allograft model and the highly metastatic 4T1 cell line in immunocompetent Balb/C mice.

Results: High Hh ligand expression was observed in 34% of IDC and was associated with increased risk of breast cancer recurrence (HR 1.95, p=0.0004) and breast cancer specific death (HR 2.3, p=0.0002). High Hh expression was also associated with the basal-like subtype (p=0.004). Overexpression of Hh ligand in M6 cells transplanted to fat pads of immunodeficient mice resulted in a 4 fold increase in tumor volume (p= 0.006) and was associated with upregulation of the canonical Hh target genes Gli1 and HHIP. However, Shh promoted peritumoral lymphatic invasion in 4/5 mice compared to only 1/5 in the vector control group and was associated with a significantly shorter time to the development of metastatic disease (p=0.0004). M6 cells overexpressing Hh ligand showed no change in proliferation, self renewal or migration in vitro, suggesting a requirement for stromal interaction in Hh-dependent tumor promotion. Finally, we found that the enhanced tumor growth conferred by Hh ligand overexpression could be blocked by administration of a neutralizing antibody to Hh ligand. Furthermore, using a metastatic mammary carcinoma isograft model (4T1) that endogenously expresses Hh ligand, we demonstrate that Hh blockade resulted in smaller lung metastatic deposits (p=0.045).

Conclusions: We found that high Hh ligand is associated with a poor prognosis in IDC. Overexpression of Hh ligand promotes murine mammary tumor growth, which requires stromal interaction, as well as lymphatic vessel invasion. Finally, we demonstrate that blockade of the Hh ligand is a potential therapy in metastatic breast carcinoma.

Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr S6-8.

High Notch1 protein expression is an early event in breast cancer development and is associated with the HER-2 molecular subtype

AIMS

Activation of Notch signalling results in hyperplasia and tumorigenesis in murine mammary epithelium. However, there is little information regarding the expression of Notch1 in premalignant lesions and early breast cancer. We investigated expression of Notch1 in breast cancer development and its association with molecular subtypes.

METHODS AND RESULTS

Immunohistochemical expression of Notch1 was determined in a murine model of mammary carcinogenesis and in breast tissue from two cohorts of breast cancer patients, the first (n=222) comprising a histological progression series and the second an outcome series of 228 patients with operable invasive ductal carcinoma. Enhanced expression of Notch1 protein was an early event in both murine and human breast cancer development with progressive increases in expression with the development of hyperplasia and malignancy. High Notch1 was not prognostic in the outcome cohort. There was, however, a highly significant association of high Notch1 protein with the HER-2 molecular subtype of breast cancer (P=0.008).

CONCLUSIONS

These data demonstrate that aberrant Notch regulation is an early event in mammary carcinogenesis and is associated with the HER-2 molecular subtype of breast cancer, and suggest the Notch signalling pathway may be a potential therapeutic target worthy of further investigation.

Cytoplasmic localization of beta-catenin is a marker of poor outcome in breast cancer patients

Beta-catenin is involved in cell adhesion through catenin-cadherin complexes and as a transcriptional regulator in the Wnt signaling pathway. Its deregulation is important in the genesis of a number of human malignancies, particularly colorectal cancer. A range of studies has been undertaken in breast cancer, with contradictory associations reported among beta-catenin expression, clinicopathologic variables, and disease outcome. We undertook an immunohistochemical study measuring the levels and subcellular localization of beta-catenin in 292 invasive ductal breast cancers with known treatment and outcome. No association with breast cancer-specific death was observed for cytoplasmic or membrane expression alone; however, a continuous score representing both locations (membrane minus cytoplasmic expression: MTC score) was associated with a worse outcome in univariate analysis (P = 0.004), and approached significance in a multivariate analysis model that included lymph node, progesterone receptor (PR), and HER2 status (P = 0.054). Therefore, the MTC score was used for further statistical analyses due to the importance of both the subcellular location and the levels of expression of beta-catenin. An association was identified between high cytoplasmic expression (low MTC score), and high tumor grade (P = 0.004), positive Ki67 (P = 0.005), negative estrogen receptor (ER) (P = 0.005), positive HER2 (P = 0.04) status, and an active phosphoinositide 3-kinase pathway (P = 0.005), measured as PIK3CA mutations (P = 0.05) or PTEN loss (P = 0.05). Low cytoplasmic expression (high MTC score) was associated with the luminal A subtype (P = 0.004). In conclusion, a low beta-catenin MTC score is associated with an adverse outcome in breast cancer, which may be of mechanistic significance in the disease process.

Loss of STARD10 expression identifies a group of poor prognosis breast cancers independent of HER2/Neu and triple negative status

The phospholipid transfer protein STARD10 cooperates with c-erbB signaling and is overexpressed in Neu/ErbB2 breast cancers. We investigated if STARD10 expression provides additional prognostic information to HER2/neu status in primary breast cancer. A published gene expression dataset was used to determine relationships between STARD10 and HER2 mRNA levels and patient outcome. The central findings were independently validated by immunohistochemistry in a retrospective cohort of 222 patients with breast cancer with a median follow-up of 64 months. Kaplan-Meier and Cox proportional hazards analyses were used for univariate and multivariate analyses. Patients with low STARD10 or high HER2 tumor mRNA levels formed discrete groups each associated with a poor disease-specific survival (p = 0.0001 and p = 0.0058, respectively). In the immunohistochemical study low/absent STARD10 expression i.e. < or = 10% positive cells was observed in 24 of 222 (11%) tumors. In a univariate model, low/absent STARD10 expression was significantly associated with decreased patient survival (p = 0.0008). In multivariate analyses incorporating tumor size, tumor grade, lymph node status, ER, PR and HER2 status, low STARD10 expression was an independent predictor of death from breast cancer (HR: 2.56 (95% CI: 1.27-5.18), p = 0.0086). Furthermore, low/absent STARD10 expression, HER2 amplification and triple negative status were independent prognostic variables. Loss of STARD10 expression may provide an additional marker of poor outcome in breast cancer identifying a subgroup of patients with a particularly adverse prognosis, which is independent of HER2 amplification and the triple negative phenotype.

PI3K pathway activation in breast cancer is associated with the basal-like phenotype and cancer-specific mortality

Breast cancer is a common malignancy with current biological therapies tailored to steroid hormone (ER, PR) and HER2 receptor status. Understanding the biological basis of resistance to current targeted therapies and the identification of new potential therapeutic targets is an ongoing challenge. The PI3K pathway is altered in a high proportion of breast cancers and may contribute to therapeutic resistance. We undertook an integrative study of mutational, copy number and expression analyses of key regulators of the PI3K pathway in a cohort of 292 invasive breast cancer patients with known treatment outcomes. The alterations identified in this cohort included PIK3CA mutations (12/168, i.e. 7%), PIK3CA copy number gain (28/209, i.e. 14%), PTEN loss (73/258, i.e. 28%) and AKT activation (62/258, i.e. 24%). Overall at least 1 parameter was altered in 72% (139/193) of primary breast cancers. PI3K pathway activation was significantly associated with ER negative (p = 0.0008) and PR negative (p = 0.006) status, high tumor grade (p = 0.032) and a "basal-like" phenotype (p = 0.01), where 92% (25/27) of tumors had an altered pathway. In univariate analysis, PI3K pathway aberrations were associated with death from breast cancer; however, this relationship was not maintained in multivariate analysis. No association was identified between an activated pathway and outcome in tamoxifen- or chemotherapy-treated patients. We concluded that >70% of breast cancers have an alteration in at least 1 component of the PI3K pathway and this might be exploited to therapeutic advantage especially in "basal-like" cancers.

Prediction of local recurrence, distant metastases, and death after breast-conserving therapy in early-stage invasive breast cancer using a five-biomarker panel

PURPOSE

To determine the clinical utility of intrinsic molecular phenotype after breast-conserving therapy (BCT) with lumpectomy and whole-breast irradiation with or without a cavity boost.

PATIENTS AND METHODS

Four hundred ninety-eight patients with invasive breast cancer were enrolled into a randomized trial of BCT with or without a tumor bed radiation boost. Tumors were classified by intrinsic molecular phenotype as luminal A or B, HER-2, basal-like, or unclassified using a five-biomarker panel: estrogen receptor, progesterone receptor, HER-2, CK5/6, and epidermal growth factor receptor. Kaplan-Meier and Cox proportional hazards methodology were used to ascertain relationships to ipsilateral breast tumor recurrence (IBTR), locoregional recurrence (LRR), distant disease-free survival (DDFS), and death from breast cancer.

RESULTS

Median follow-up was 84 months. Three hundred ninety-four patients were classified as luminal A, 23 were luminal B, 52 were basal, 13 were HER-2, and 16 were unclassified. There were 24 IBTR (4.8%), 35 LRR (7%), 47 distant metastases (9.4%), and 37 breast cancer deaths (7.4%). The overall 5-year disease-free rates for the whole cohort were: IBTR 97.4%, LRR 95.6%, DDFS 92.9%, and breast cancer-specific death 96.3%. A significant difference was observed for survival between subtypes for LRR (P = .012), DDFS (P = .0035), and breast cancer-specific death (P = .0482), but not for IBTR (P = .346).

CONCLUSION

The 5-year and 10-year survival rates varied according to molecular subtype. Although this approach provides additional information to predict time to IBTR, LRR, DDFS, and death from breast cancer, its predictive power is less than that of traditional pathologic indices. This information may be useful in discussing outcomes and planning management with patients after BCT.

Cyclin D1b is aberrantly regulated in response to therapeutic challenge and promotes resistance to estrogen antagonists

Cyclin D1 is a key mediator of cell cycle progression that is aberrantly regulated in multiple cancers, especially in breast cancers. A number of studies have indicated that a polymorphism in a splice donor site in the cyclin D1 gene is associated with alternative splicing and the production of the alternative cyclin D1b transcript. Furthermore, this polymorphism is selectively associated with disease outcomes. However, relatively little is known regarding the protein product of the alternatively spliced message, cyclin D1b. Using antibodies specific for cyclin D1b, it was found that this protein is readily detectable in a number of cancer cell lines and primary breast cancers. Whereas cyclin D1b interacts with cyclin-dependent kinase 4 (CDK4), it is relatively inefficient at mediating RB phosphorylation and cell cycle progression in model systems due to the lack of exon 5 of cyclin D1-encoded sequences. However, cyclin D1b protein levels are not significantly attenuated by DNA damage or antiestrogen treatment, indicating that the protein may have significant effect on the response to such therapeutic modalities. Whereas enforced expression of cyclin D1b was not sufficient to abrogate DNA damage checkpoint responses, it did efficiently overcome cell cycle arrest mediated by antiestrogen therapeutics. This action of cyclin D1b was not associated with effects on estrogen receptor activity, but was rather dependent on functional association with CDK4. Combined, these studies indicate that the cyclin D1b protein is aberrantly regulated and could contribute to therapeutic failure in the context of ER-positive breast cancer.

p27KIP-1, cyclin A and cyclin D1 protein expression in ductal carcinoma in situ of the breast: p27KIP-1 correlates with hormone receptor status but not with local recurrence

Using whole sections of formalin-fixed paraffin-embedded material the expression of p27(KIP-1), cyclin A and cyclin D1 was examined in 60 cases of ductal carcinoma in situ (DCIS) using routine immunohistochemistry with a median follow up of 95 months (range 10-139 months) to identify any association with disease recurrence. Fifty-six patients were treated by local excision and radiotherapy and four by mastectomy without radiotherapy. There was a highly significant positive association between p27(KIP-1) and estrogen receptor/progesterone receptor (ER/PR) status (P = 0.002, P = 0.02) and with p27(KIP-1) and cyclin D1 expression (P = 0.002). A trend between cyclin A and PR status (P = 0.08) was also identified. These findings mirror those described in invasive ductal carcinoma, but there were no associations of any biomarker with histological parameters such as nuclear grade or with local recurrence on univariate analysis, which was present in four of the 56 locally excised group (7.1%). Further examination of a larger cohort may be worthwhile to explore the possible role as adjunctive predictive markers to aid clinical decision making.

c-Myc overexpression and endocrine resistance in breast cancer

The oncoprotein c-Myc is frequently overexpressed in breast cancer and ectopic expression in breast cancer cell lines attenuates responses to antiestrogen treatment. Here, we review preliminary data aimed at further elucidating a potential role for c-Myc in clinical endocrine resistance in breast cancer. Immunohistochemical and semi-quantitative PCR revealed that c-Myc protein and c-myc mRNA were frequently overexpressed in both ER-positive and ER-negative breast carcinoma. Furthermore, both constitutive and inducible c-Myc overexpression in MCF-7 breast cancer cell lines markedly reduced their sensitivity to the growth inhibitory effects of the pure antiestrogen ICI 182,780. In order to identify potential downstream targets of c-Myc that mediate this effect, Affymetrix microarrays were employed to examine the patterns of gene expression shared by MCF-7 cells stimulated by estrogen, or by induction of c-Myc. Approximately 50% of estrogen target genes identified 6h after treatment were also regulated by c-Myc. One novel target, EMU4, was transcriptionally regulated by c-Myc. In addition, there was a strong correlation between c-myc and EMU4 mRNA expression in a battery of breast cancer cell lines. These data confirm that c-Myc overexpression is a common event in breast cancer, and that this is associated with resistance to antiestrogens in vitro. Furthermore, the development of an experimental paradigm for the discovery of c-Myc and estrogen target genes associated with endocrine resistance provides a framework for the discovery and validation of genes involved in estrogen signalling, and c-Myc-mediated-antiestrogen resistance.