Breast Cancer Patient Datasets Research Articles

Using an in-vivo syngeneic spontaneous metastasis model identifies ID2 as a promoter of breast cancer colonisation in the brain

BackgroundDissemination of breast cancers to the brain is associated with poor patient outcome and limited therapeutic options. In this study we sought to identify novel regulators of brain metastasis by profiling mouse mammary carcinoma cells spontaneously metastasising from the primary tumour in an immunocompetent syngeneic host.Methods4T1 mouse mammary carcinoma sublines derived from primary tumours and spontaneous brain and lung metastases in BALB/c mice were subject to genome-wide expression profiling. Two differentially expressed genes, Id2 and Aldh3a1, were validated in in-vivo models using mouse and human cancer cell lines. Clinical relevance was investigated in datasets of breast cancer patients with regards to distant metastasis-free survival and brain metastasis relapse-free survival. The role of bone morphogenetic protein (BMP)7 in regulating Id2 expression and promoting cell survival was investigated in two-dimensional and three-dimensional in-vitro assays.ResultsIn the spontaneous metastasis model, expression of Id2 and Aldh3a1 was significantly higher in 4T1 brain-derived sublines compared with sublines from lung metastases or primary tumour. Downregulation of expression impairs the ability of cells to colonise the brain parenchyma whereas ectopic expression in 4T1 and human MDA-MB-231 cells promotes dissemination to the brain following intracardiac inoculation but has no impact on the efficiency of lung colonisation. Both genes are highly expressed in oestrogen receptor (ER)-negative breast cancers and, within this poor prognosis sub-group, increased expression correlates with reduced distant metastasis-free survival. ID2 expression also associates with reduced brain metastasis relapse-free survival. Mechanistically, BMP7, which is present at significantly higher levels in brain tissue compared with the lungs, upregulates ID2 expression and, after BMP7 withdrawal, this elevated expression is retained. Finally, we demonstrate that either ectopic expression of ID2 or BMP7-induced ID2 expression protects tumour cells from anoikis.ConclusionsThis study identifies ID2 as a key regulator of breast cancer metastasis to the brain. Our data support a model in which breast cancer cells that have disseminated to the brain upregulate ID2 expression in response to astrocyte-secreted BMP7 and this serves to support metastatic expansion. Moreover, elevated ID2 expression identifies breast cancer patients at increased risk of developing metastatic relapse in the brain.

Functional Proteomics of Breast Cancer Metabolism Identifies GLUL as Responder during Hypoxic Adaptation.

Hypoxia as well as metabolism are central hallmarks of cancer, and hypoxia-inducible factors (HIFs) and metabolic effectors are crucial elements in oxygen-compromised tumor environments. Knowledge of changes in the expression of metabolic proteins in response to HIF function could provide mechanistic insights into adaptation to hypoxic stress, tumorigenesis, and disease progression. We analyzed time-resolved alterations in metabolism-associated protein levels in response to different oxygen potentials across breast cancer cell lines. Effects on the cellular metabolism of both HIF-dependent and -independent processes were analyzed by reverse-phase protein array profiling and a custom statistical model. We revealed a strong induction of glucose transporter 1 (GLUT1) and lactate dehydrogenase A (LDHA) as well as reduced glutamate-ammonia ligase (GLUL) protein levels across all cell lines tested as consistent changes upon hypoxia induction. Low GLUL protein levels were correlated with aggressive molecular subtypes in breast cancer patient data sets and also with hypoxic tumor regions in a xenograft mouse tumor model. Moreover, low GLUL expression was associated with poor survival in breast cancer patients and with high HIF-1α-expressing patient subgroups. Our data reveal time-resolved changes in the regulation of metabolic proteins under oxygen-deprived conditions and elucidate GLUL as a strong responder to HIFs and the hypoxic environment.

Regression adjustment for treatment effect with multicollinearity in high dimensions

Randomized experiment is an important tool for studying the Average Treatment Effect (ATE). This paper considers the regression adjustment estimation of the Sample Average Treatment Effect (SATE) in high-dimensional case, where the multicollinearity problem is often encountered and needs to be properly handled. Many existing regression adjustment methods fail to achieve satisfactory performances. To solve this issue, an Elastic-net adjusted estimator for SATE is proposed under the Rubin causal model of randomized experiments with multicollinearity in high dimensions. The asymptotic properties of the proposed SATE estimator are shown under some regularity conditions, and the asymptotic variance is proved to be not greater than that of the unadjusted estimator. Furthermore, Neyman-type conservative estimators for the asymptotic variance are proposed, which yields tighter confidence intervals than both the unadjusted and the Lasso-based adjusted estimators. Some simulation studies are carried out to show that the Elastic-net adjusted method is better in addressing collinearity problem than the existing methods. The advantages of our proposed method are also shown in analyzing the dataset of HER2 breast cancer patients.

Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Nonmass-enhancing (NME) lesions constitute a diagnostic challenge in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer-aided diagnosis (CAD) systems provide physicians with advanced tools for analysis, assessment, and evaluation that have a significant impact on the diagnostic performance. Here, we propose a new approach to address the challenge of NME lesion detection and segmentation, taking advantage of independent component analysis (ICA) to extract data-driven dynamic lesion characterizations. A set of independent sources was obtained from the DCE-MRI dataset of breast cancer patients, and the dynamic behavior of the different tissues was described by multiple dynamic curves, together with a set of eigenimages describing the scores for each voxel. A new test image is projected onto the independent source space using the unmixing matrix, and each voxel is classified by a support vector machine (SVM) that has already been trained with manually delineated data. A solution to the high false-positive rate problem is proposed by controlling the SVM hyperplane location, outperforming previously published approaches.

Tree-based machine learning algorithms identified minimal set of miRNA biomarkers for breast cancer diagnosis and molecular subtyping

Breast cancer is a complex disease and its effective treatment needs affordable diagnosis and subtyping signatures. While the use of machine learning approach in clinical computation biology is still in its infancy, the prevalent approach in identifying molecular biomarkers remains to be screening of all biomarkers by differential expression analysis. Many of these attempts used miRNAs expression data in breast cancer and amounted to the multitude of differentially expressed miRNAs in this cancer; hence, the minimal set of miRNA biomarkers to classify breast cancer is yet to be identified.Availability of diverse and vast amount of cancer datasets like The Cancer Genome Atlas facilitated the molecular profiling of patients' tumors and introduced new challenges like clinical grade interpretations from big data. In this study, miRNA expression dataset of breast cancer patients from TCGA database was used to develop prediction models from which miRNA biomarkers were identified for diagnosis and molecular subtyping of this cancer. I took the advantage of interpretability of tree-based classification models to extract their rules and identify minimal set of biomarkers in this cancer.Empirical negative control miRNAs in breast cancer obtained and used to normalize the dataset. Tree-based machine learning models trained in my analysis used hsa-miR-139 with hsa-miR-183 to classify breast tumors from normal samples, and hsa-miR4728 with hsa-miR190b to further classify these tumors into three major subtypes of breast cancer. In addition to the proposed biomarkers, the most important miRNAs in breast cancer classification were also presented.

Abstract LB-282: Dynamic regulation of CD73 expression in cancer associated fibroblasts enforces immunosuppression via a feedforward adenosinergic pathway

Abstract CD73 is the major extracellular adenosine-generating ecto-5'-nucleotidase (Nt5e) that metabolizes extracellular (e) AMP and generates immunosuppressive adenosine (eADO). Elevated CD73 expression is often exploited by tumors and other cellular constituents of the tumor microenvironment (TME) as a mechanism of immune evasion. Clinically, a high level of CD73 expression in the tumor microenvironment (TME) is linked to poor prognosis. Experimental evidence also demonstrates that host CD73 activity in both hematopoietic and non-hematopoietic compartments augments the suppressive milieu of the TME. Nevertheless, the identities of CD73-expressing non-hematopoietic cells and factors that regulate CD73 activity of these cells have yet to be clearly defined. Our recent results unravel that cancer associated fibroblasts (CAFs) constitute a crucial non-hematopoietic CD73hi compartment in the TME of human colorectal cancer (CRC) and murine MC38 CRC and EG7 lymphoma ectopic models. Strikingly, the CD73 expression profile among cohorts of published human CRC and breast cancer patient data sets confirmed its significant positive association with that of CAF-related markers, both of which are negatively correlated with poor survival. Cellular and transcriptomic analyses of CAFs in the EG7 TME reveal that CD73 expression in CAFs increases progressively during tumor progression, associated with elevated tissue hypoxia. Mechanistically, we demonstrate that the progressive elevation of CD73 expression in CAFs during tumor progression is caused by elevated eADO in the TME, which is resulted by the hypoxia/necrosis-associated eATP release. Furthermore, this eADO/adenosingeric pathway-induced CD73 upregulation in CAFs is mostly mediated by activation of A2BR and downstream MAPK signaling, which exacerbates eADO accumulation and serves as a feedforward loop of re-enforcing the immunosuppressive TME. Our study demonstrated that clinically and experimentally, high level of CD73 expression in CAFs represents another crucial immune checkpoint in the TME. Targeted inactivation or blockade of A2BR signaling may serve as a new strategy to prevent or alleviate the initiation of the eADO-CD73-associated amplification of immunosuppression in the TME, thereby improving the outcome of immunotherapy. Citation Format: Miao Yu, Gang Guo, Lei Huang, Libin Deng, Roni Bollag, Andrew Mellor, Huidong Shi, Yan Cui. Dynamic regulation of CD73 expression in cancer associated fibroblasts enforces immunosuppression via a feedforward adenosinergic pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-282.

Abstract 4179: A novel approach for antimetastatic therapies against TNBC utilizing a physiologic suppressor

Abstract Metastatic progression of tumors is the major cause of death in patients with triple-negative breast cancer (TNBC). However, since metastasis is a multistep process, unraveling its complexity is a major challenge. One effective way of tackling this question is to study natural blockers of the metastatic process, metastasis suppressors, and identify the mechanisms by which they regulate metastasis. Raf kinase inhibitory protein (RKIP), a protein that regulates kinase activity, is a suppressor of TNBC metastasis. Although RKIP inhibits the activity of key kinases such as Raf-1, GRK2, NIK/IKK in cultured cells, the kinase targets of RKIP in tumors are not known. To address this question, we used a mass spectrometry approach involving inhibitor-conjugated beads to identify kinases that are downregulated by RKIP in human TNBC xenograft tumors. Our results identified a network of stress kinases targeted by RKIP, including kinases that have not been previously reported as RKIP targets. In order to unravel the effect of this stress network on metastatic gene expression, we investigated genes that correlate with RKIP expression in TCGA breast cancer patient data set. We identified prometastatic genes such as APC and DOCK4 as novel RKIP targets in in vitro and in vivo models of TNBC. We also demonstrated these genes are downstream of the RKIP-stress network. Finally, by using a high-throughput invasion assay, we developed a low-dose multidrug cocktail of small-molecule kinase inhibitors that mimic RKIP's antimetastatic role in TNBCs. Elucidating RKIP function at a systems level reveals the interplay between key metastatic signaling cascades, particularly in relation to cell motility and invasion. Our findings suggest that the low-dose multidrug combination that targets a network of stress kinases is a viable antimetastatic therapy for TNBC patients. Citation Format: Ali Ekrem Yesilkanal, Daniel C. Rabe, Payal Tiwari, Casey Frankenberger, Gary L. Johnson, Marsha Rosner. A novel approach for antimetastatic therapies against TNBC utilizing a physiologic suppressor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4179.

A Feasibility Study on the Identification of Postlumpectomy Seromas by a Radiation Therapist Compared with That by Radiation Oncologists in Radiation Therapy Planning for Early Stage Breast Cancer

IntroductionComputed tomography (CT) simulation is currently used to identify the tumour bed in patients with early stage breast cancer requiring whole-breast and boost radiation therapy. Postlumpectomy breast seromas as visible on CT data have been identified as a proxy for the tumour bed. This study aims to quantify the incidence of postsurgical tumour bed seromas identified at CT simulation and report how well a radiation therapist (RT) is able to identify these seromas compared with those contoured by radiation oncologists (ROs). Methods and MaterialsA study was undertaken on electronic patient records and the CT-simulation datasets of early stage breast cancer patients treated in 2013 at the Calvary Mater Newcastle to identify the presence of seromas. Patient and tumour characteristics were reviewed. Data analysed included seroma volumes, as contoured by the ROs, as part of the standard voluming procedure. One RT rated seroma visibility based on the level of difficulty when viewing the seroma. ResultsOut of 108 CT datasets, an RT was able to identify the presence of a seroma in 102 cases vs. 104 as contoured by ROs. The number of observed agreements was 106 (98.15% of the observations), and the number of agreements expected by chance was 98.4 (91.15% of the observations). The Kappa statistics equalled 0.791 (SE of kappa = 0.143). The strength of agreement is considered to be “substantial.” ConclusionRTs play an integral role in contouring during the planning process, and there is scope to expand this role. This research introduced the first step by confirming that a radiation therapist is able to identify seromas on CT-simulation data when compared those contoured by an RO.

Abstract P1-01-22: TGFβ-Smad3-TMEPAI axis drives the tumor progression of triple negative breast cancer

Abstract Background: In the absence of mutations and/or deletions in the TGF-β signaling molecules, how triple negative breast cancer (TNBC) cells become resistant to growth inhibitory signaling of TGF-β was addressed by screening of several TNBC cell lines for Smad proteins involved in TGF-β signaling. Unexpectedly, altered Smad2 and Smad3 protein levels were detected in breast cancer cells relative to normal mammary epithelial cells, suggesting a novel mechanism to escape from TGF-β mediated growth inhibition. In order to reflect the true functional status of the endogenous molecules, Smad2 or Smad3 were individually knocked down and tested its effect on pro-oncogenic behavior of TGF-β. Materials and Methods: All cell lines were cultured according to the recommended standard procedures. TMEPAI knockdown was achieved by using lentiviral vectors and knockdown of Smad2 and Smad3 was achieved by using retroviral vectors. DNA transfections and luciferase assays were performed according to vendor instructions. Cell proliferation was measured by quantitation of total cellular DNA. Immunoblotting, invasion and immunohistochemical assays were performed using standard methods. Bioinformatics: Triple negative breast cancer patient dataset (GSE58812) was used to compare Smad2, Smad3, Smad4 and TMEPAI/PMEPA1 expressions correlated with overall survival using the PROGgene tool by using median gene expression value as a dividing point. Results: While Smad2 deficiency has no effect on breast cancer cell behavior, Smad3 deficiency reduced growth and invasion capacity of breast cancer cells. Interestingly, Smad3 deficiency was associated with reduced gene expressions of transmembrane prostate androgen induced (TMEPAI or PMEPA1) gene and EMT inducing transcription factors and increased expression of cell cycle inhibitors. In contrast, Smad2 deficiency had opposite effect on these regulators. Importantly, the decreased growth and invasion and their associated gene expressions in Smad3 knockdown cells were largely reversed by overexpression of TMEPAI. Meta-analysis of Jezequel dataset of triple negative breast cancer patients suggested higher TMEPAI/PMEPA1 and lower Smad2 expressions are significantly associated with decreased survival. Our results support the idea that development of several triple negative breast cancers may involve expansion of cell populations with altered Smad2 and Smad3 levels resulting in Smad3 dependent expression of TMEPAI, which provides a competitive advantage for cancer cells to grow and metastasize in presence of TGF-β. Moreover, following meta-analysis of published microarray datasets in lung and gastric cancers also revealed that increased TMEPAI and Smad3 expression and decreased Smad2 expressions were significantly associated with poorer patient prognosis in non-small cell lung adenocarcinomas and gastric cancers suggesting universality of this phenomenon. Conclusion: We identified TGF-β-Smad3-TMEPAI signaling axis as a driver of tumor progression in triple negative breast cancer. Our results suggest that novel therapeutics targeting TMEPAI will selectively inhibit oncogenic activity of TGF-β and promote its tumor suppressive activity in treating TNBC. Citation Format: Saikumar P, Singha PK, Pandeswara S, Manjeri VA. TGFβ-Smad3-TMEPAI axis drives the tumor progression of triple negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-01-22.

MTA1 is a novel regulator of autophagy that induces tamoxifen resistance in breast cancer cells

ABSTRACTTamoxifen is commonly used to treat patients with ESR/ER-positive breast cancer, but its therapeutic benefit is limited by the development of resistance. Recently, alterations in macroautophagy/autophagy function were demonstrated to be a potential mechanism for tamoxifen resistance. Although MTA1 (metastasis-associated 1) has been implicated in breast tumorigenesis and metastasis, its role in endocrine resistance has not been studied. Here, we report that the level of MTA1 expression was upregulated in the tamoxifen resistant breast cancer cell lines MCF7/TAMR and T47D/TR, and knockdown of MTA1 sensitized the cells to 4-hydroxytamoxifen (4OHT). Moreover, knockdown of MTA1 significantly decreased the enhanced autophagy flux in the tamoxifen resistant cell lines. To confirm the role of MTA1 in the development of tamoxifen resistance, we established a cell line, MCF7/MTA1, which stably expressed MTA1. Compared with parental MCF7, MCF7/MTA1 cells were more resistant to 4OHT-induced growth inhibition in vitro and in vivo, and showed increased autophagy flux and higher numbers of autophagosomes. Knockdown of ATG7 or cotreatment with hydroxychloroquine, an autophagy inhibitor, restored sensitivity to 4OHT in both the MCF7/MTA1 and tamoxifen resistant cells. In addition, AMP-activated protein kinase (AMPK) was activated, probably because of an increased AMP:ATP ratio and decreased expression of mitochondrial electron transport complex components. Finally, publicly available breast cancer patient datasets indicate that MTA1 levels correlate with poor prognosis and development of recurrence in patients with breast cancer treated with tamoxifen. Overall, our findings demonstrated that MTA1 induces AMPK activation and subsequent autophagy that could contribute to tamoxifen resistance in breast cancer.

Saccharomyces cerevisiae-like 1 (SEC14L1) is a prognostic factor in breast cancer associated with lymphovascular invasion

Lymphovascular invasion is strongly related to breast cancer metastasis. However, the underlying mechanisms of lymphovascular invasion and its driver molecules in breast cancer remain to be defined. In this study, we explore differential expression of genes in large molecularly characterized and clinically annotated datasets of invasive breast cancer patients (n = 8056) coupled with histological review and strict definition for lymphovascular invasion status. The METABRIC series was used to identify genes associated with lymphovascular invasion, as defined using hematoxylin and eosin staining supplemented by immunohistochemistry, at the genomic/transcriptomic levels. Saccharomyces cerevisiae-like 1 (SEC14L1) was identified as one of the most significant genes associated with lymphovascular invasion. The prognostic significance of SEC14L1 gene copy number and mRNA expression was further investigated in the METABRIC series and externally validated using the Breast Cancer Gene-Expression Miner v4.0. Protein expression of SEC14L1 was also assessed using immunohistochemistry in series of early stage breast cancer using tissue microarrays. SEC14L1 gene copy number gain was significantly associated with high histological grade and poor outcome. SEC14L1 mRNA expression showed positive association with higher grade, lymph node metastasis, and poor outcome. SEC14L1 protein overexpression was significantly associated with lymphovascular invasion (p < 0.0001), higher grade (p = 0.011), HER2 positivity (p = 0.036), and shorter survival (p = 0.00075). Our findings specify SEC14L1 as an independent prognostic factor in breast cancer. Its association, at both transcriptome and protein expression levels, with lymphovascular invasion and outcome could imply an important role in tumor progression. A further mechanistic insight into its molecular roles including potential therapeutic utility is warranted.

AMPH-1 is critical for breast cancer progression.

Amphiphysin 1 (AMPH-1) is a nerve terminals-enriched protein involved in endocytosis, and we observe that its expression is increased in breast cancer tumor in compared with normal breast. However, its function in breast cancer is unknown. Here we aim to explore the role of AMPH-1 in breast cancer cells. Knockdown of AMPH-1 in breast cancer cells promotes cell proliferation, cell cycle progression and cell migration, and attenuates cell apoptosis. Of note, knockdown of AMPH-1 promotes breast cancer progression in xenograft mouse model. These oncogenic phenotypes may be partially due to the activated EMT and ERK pathways after inhibition of AMPH-1. Oncomine analyses of multiple breast cancer patient datasets show that reduced AMPH-1 mRNA level is significantly associated with breast cancer patients having metastatic events, advanced stage, poor clinical outcomes, and Paclitaxel+FEC treatment resistance. In summary, our results identified the anti-oncogenic function of AMPH-1 in breast cancer in vitro and in vivo. Activation of AMPH-1 may be a promising approach to treat breast cancer patients.

Glucose-6-phosphate dehydrogenase and transketolase modulate breast cancer cell metabolic reprogramming and correlate with poor patient outcome.

The pentose phosphate pathway is a fundamental metabolic pathway that provides cells with ribose and NADPH required for anabolic reactions — synthesis of nucleotides and fatty acids — and maintenance of intracellular redox homeostasis. It plays a key role in tumor metabolic reprogramming and has been reported to be deregulated in different types of tumors. Herein, we silenced the most important enzymes of this pathway — glucose-6-phosphate dehydrogenase (G6PD) and transketolase (TKT) — in the human breast cancer cell line MCF7. We demonstrated that inhibition of G6PD, the oxidative branch-controlling enzyme, reduced proliferation, cell survival and increased oxidative stress. At the metabolic level, silencing of both enzymes reduced ribose synthesis. G6PD silencing in particular, augmented the glycolytic flux, reduced lipid synthesis and increased glutamine uptake, whereas silencing of TKT reduced the glycolytic flux. Importantly, we showed using breast cancer patient datasets that expression of both enzymes is positively correlated and that high expression levels of G6PD and TKT are associated with decreased overall and relapse-free survival. Altogether, our results suggest that this metabolic pathway could be subjected to therapeutic intervention to treat breast tumors and warrant further investigation.

Ror2 Signaling and Its Relevance in Breast Cancer Progression.

Breast cancer is a heterogeneous disease and has been classified into five molecular subtypes based on gene expression profiles. Signaling processes linked to different breast cancer molecular subtypes and different clinical outcomes are still poorly understood. Aberrant regulation of Wnt signaling has been implicated in breast cancer progression. In particular Ror1/2 receptors and several other members of the non-canonical Wnt signaling pathway were associated with aggressive breast cancer behavior. However, Wnt signals are mediated via multiple complex pathways, and it is clinically important to determine which particular Wnt cascades, including their domains and targets, are deregulated in poor prognosis breast cancer. To investigate activation and outcome of the Ror2-dependent non-canonical Wnt signaling pathway, we overexpressed the Ror2 receptor in MCF-7 and MDA-MB231 breast cancer cells, stimulated the cells with its ligand Wnt5a, and we knocked-down Ror1 in MDA-MB231 cells. We measured the invasive capacity of perturbed cells to assess phenotypic changes, and mRNA was profiled to quantify gene expression changes. Differentially expressed genes were integrated into a literature-based non-canonical Wnt signaling network. The results were further used in the analysis of an independent dataset of breast cancer patients with metastasis-free survival annotation. Overexpression of the Ror2 receptor, stimulation with Wnt5a, as well as the combination of both perturbations enhanced invasiveness of MCF-7 cells. The expression–responsive targets of Ror2 overexpression in MCF-7 induced a Ror2/Wnt module of the non-canonical Wnt signaling pathway. These targets alter regulation of other pathways involved in cell remodeling processing and cell metabolism. Furthermore, the genes of the Ror2/Wnt module were assessed as a gene signature in patient gene expression data and showed an association with clinical outcome. In summary, results of this study indicate a role of a newly defined Ror2/Wnt module in breast cancer progression and present a link between Ror2 expression and increased cell invasiveness.

Hypoxia Selectively Enhances Integrin α5β1 Receptor Expression in Breast Cancer to Promote Metastasis.

Metastasis is the leading cause of breast cancer mortality. Previous studies have implicated hypoxia-induced changes in the composition and stiffness of the extracellular matrix (ECM) in the metastatic process. Therefore, the contribution of potential ECM-binding receptors in this process was explored. Using a bioinformatics approach, the expression of all integrin receptor subunits, in two independent breast cancer patient datasets, were analyzed to determine whether integrin status correlates with a validated hypoxia-inducible gene signature. Subsequently, a large panel of breast cancer cell lines was used to validate that hypoxia induces the expression of integrins that bind to collagen (ITGA1, ITGA11, ITGB1) and fibronectin (ITGA5, ITGB1). Hypoxia-inducible factors (HIF-1 and HIF-2) are directly required for ITGA5 induction under hypoxic conditions, which leads to enhanced migration and invasion of single cells within a multicellular 3D tumor spheroid but did not affect migration in a 2D microenvironment. ITGB1 expression requires HIF-1α, but not HIF-2α, for hypoxic induction in breast cancer cells. ITGA5 (α5 subunit) is required for metastasis to lymph nodes and lungs in breast cancer models, and high ITGA5 expression in clinical biopsies is associated with an increased risk of mortality.Implications: These results reveal that targeting ITGA5 using inhibitors that are currently under consideration in clinical trials may be beneficial for patients with hypoxic tumors. Mol Cancer Res; 15(6); 723-34. ©2017 AACR.

Abstract B24: Genomic prediction of response to PARP inhibition in breast cancer

Abstract Efficacy of PARP inhibition has been demonstrated in several cancer types including prostate, ovarian, and breast. Most recently, anti-PARP therapy was shown to be effective in combination with carboplatin in triple-negative breast cancer patients in the neoadjuvant setting. However, it is not yet well known which subset of triple-negative breast cancers will benefit from single-agent anti-PARP therapy. We determined the therapeutic efficacy of three PARP inhibitors: veliparib, olaparib, and BMN 673, in a panel of eight triple-negative breast cancer cell lines. We used a 10-day in-vitro assay, after which we fixed the cells and determined 53BP1 expression using immunofluorescence and high-content imaging. We used cell counts to derive IC50 values and enumerated 53BP1 foci per cell to determine EC50 values. We used pre-treatment whole-transcriptome data to identify genes associated with 53BP1 response using gene set enrichment and pathway enrichment analysis. We determined the prevalence of these genes in a dataset of triple-negative breast cancer patients, and performed survival analysis. We found PARP inhibition to be effective in both BRCA-mutant and BRCA wild-type breast cancer cell lines. BMN 673 was the most potent PARP inhibitor, with the lowest concentrations required for DNA damage (measured by 53BP1 expression) and cell kill (measured by cell count), followed by olaparib, and then veliparib. We found a strong correlation between the IC50 values for cell count and the EC50 values for 53BP1 response. We identified a gene set associated with 53BP1 response, which was involved with three major pathways: DNA repair, cell cycle, and programmed cell death. These genes were found to be downregulated in triple-negative breast cancer patients. Patients with aberrations in these genes demonstrated poorer overall survival (P = 0.03). In conclusion, we identified a gene set involved with DNA repair, cell-cycle, and programmed cell death, which was associated with poor outcomes in triple-negative breast cancer patients that could potentially benefit from anti-PARP therapy. Citation Format: Saima Hassan, Amanda Esch, Laura M. Heiser, Joe W. Gray. Genomic prediction of response to PARP inhibition in breast cancer [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr B24.

Use of axillary lymph node dissection (ALND) in patients with micrometastatic breast cancer

BackgroundSentinel lymph node (SLN) biopsy is the current prognostic tool for clinically node-negative breast cancer patients. If the SLN reveals macrometastasis, axillary lymph node dissection (ALND) is recommended. However, the use of ALND in patients with micrometastasis is debated. The objective of this study was to assess the utilization of ALND in the treatment of micrometastatic breast cancer. MethodsAn IRB approved, retrospective study of a pooled dataset of breast cancer patients with micrometastatic disease on SLN biopsy was performed. Patients diagnosed from 1999-2016 were identified via query of a single-institution National Comprehensive Cancer Network (NCCN) breast cancer database as well as a prospective tumor board. ResultsA total of 91 patients were diagnosed with micrometastatic nodal disease. The median age at diagnosis was 56 y (range: 31-85); median follow-up time was 47 mo (range: 0-203 mo). 42/91(46.2%) patients had ALND of which 37/42 (88.1%) were a second operation; 3/42(7.1%) patients had additional positive nodes found at ALND. 44/91 (48.4%) patients received radiation. 7/91 (7.7%) patients had a recurrence, 5/7 local, including one axillary (2.1%; patient declined ALND). ConclusionsGiven that the risk of lymphedema after ALND ranges between 20%-53%, the morbidity of ALND may far exceed the likelihood of detecting further nodal involvement in women with micrometastatic disease: 7.1% in this series.

Targeting of apoptotic pathways by SMAC or BH3 mimetics distinctly sensitizes paclitaxel-resistant triple negative breast cancer cells.

Standard chemotherapy is the only systemic treatment for triple-negative breast cancer (TNBC), and despite the good initial response, resistance remains a major therapeutic obstacle. Here, we employed a High-Throughput Screen to identify targeted therapies that overcome chemoresistance in TNBC. We applied short-term paclitaxel treatment and screened 320 small-molecule inhibitors of known targets to identify drugs that preferentially and efficiently target paclitaxel-treated TNBC cells. Among these compounds the SMAC mimetics (BV6, Birinapant) and BH3-mimetics (ABT-737/263) were recognized as potent targeted therapy for multiple paclitaxel-residual TNBC cell lines. However, acquired paclitaxel resistance through repeated paclitaxel pulses result in desensitization to BV6, but not to ABT-263, suggesting that short- and long-term paclitaxel resistance are mediated by distinct mechanisms. Gene expression profiling of paclitaxel-residual, -resistant and naïve MDA-MB-231 cells demonstrated that paclitaxel-residual, as opposed to -resistant cells, were characterized by an apoptotic signature, with downregulation of anti-apoptotic genes (BCL2, BIRC5), induction of apoptosis inducers (IL24, PDCD4), and enrichment of TNFα/NF-κB pathway, including upregulation of TNFSF15, coupled with cell-cycle arrest. BIRC5 and FOXM1 downregulation and IL24 induction was also evident in breast cancer patient datasets following taxane treatment. Exposure of naïve or paclitaxel-resistant cells to supernatants of paclitaxel-residual cells sensitized them to BV6, and treatment with TNFα enhanced BV6 potency, suggesting that sensitization to BV6 is mediated, at least partially, by secreted factor(s). Our results suggest that administration of SMAC or BH3 mimetics following short-term paclitaxel treatment could be an effective therapeutic strategy for TNBC, while only BH3-mimetics could effectively overcome long-term paclitaxel resistance.

Genomic pathways modulated by Twist in breast cancer

BackgroundThe basic helix-loop-helix transcription factor TWIST1 (Twist) is involved in embryonic cell lineage determination and mesodermal differentiation. There is evidence to indicate that Twist expression plays a role in breast tumor formation and metastasis, but the role of Twist in dysregulating pathways that drive the metastatic cascade is unclear. Moreover, many of the genes and pathways dysregulated by Twist in cell lines and mouse models have not been validated against data obtained from larger, independant datasets of breast cancer patients.MethodsWe over-expressed the human Twist gene in non-metastatic MCF-7 breast cancer cells to generate the estrogen-independent metastatic breast cancer cell line MCF-7/Twist. These cells were inoculated in the mammary fat pad of female severe compromised immunodeficient mice, which subsequently formed xenograft tumors that metastasized to the lungs. Microarray data was collected from both in vitro (MCF-7 and MCF-7/Twist cell lines) and in vivo (primary tumors and lung metastases) models of Twist expression. Our data was compared to several gene datasets of various subtypes, classes, and grades of human breast cancers.ResultsOur data establishes a Twist over-expressing mouse model of breast cancer, which metastasizes to the lung and replicates some of the ontogeny of human breast cancer progression. Gene profiling data, following Twist expression, exhibited novel metastasis driver genes as well as cellular maintenance genes that were synonymous with the metastatic process. We demonstrated that the genes and pathways altered in the transgenic cell line and metastatic animal models parallel many of the dysregulated gene pathways observed in human breast cancers.ConclusionsAnalogous gene expression patterns were observed in both in vitro and in vivo Twist preclinical models of breast cancer metastasis and breast cancer patient datasets supporting the functional role of Twist in promoting breast cancer metastasis. The data suggests that genetic dysregulation of Twist at the cellular level drives alterations in gene pathways in the Twist metastatic mouse model which are comparable to changes seen in human breast cancers. Lastly, we have identified novel genes and pathways that could be further investigated as targets for drugs to treat metastatic breast cancer.

Long-Term Disease-Free Survival of Non-Metastatic Breast Cancer Patients in Iran: A Survival Model with Competing Risks Taking Cure Fraction and Frailty into Account

Introduction:Survival modeling is a very important tool to detect risk factors and provide a basis for health care planning. However, cancer data may have properties leading to distorted results with routine methods. Therefore, this study aimed to cover specific factors (competing risk, cure fraction and heterogeneity) with a real dataset of Iranian breast cancer patients using a competing risk-cure-frailty model.Materials and methods:For this historical cohort study, information for 550 Iranian breast cancer patients who underwent surgery for tumor removal from 2001 to 2007 and were followed up to March 2017, was analyzed using R 3.2 software.Results:In contrast to T-stage and N-stage, hormone receptor status did not have any significant effect on the cure fraction (long-term disease-free survival). However, T-stage, N-stage and hormone receptor status all had a significant effect on short-term disease-free survival so that the hazard of loco-regional relapse or distant metastasis in cases positive for a hormone receptor was only 0.3 times that for their negative hormone receptor counterparts. The likelihood of locoregional relapse in the first quartile of follow up was nearly twice that of other quartiles. The least cumulative incidence of time to locoregional relapse was for cases with a positive hormone receptor, low N stage and low T stage. The effect of frailty term was significant in this study and a model with frailty appeared more appropriate than a model without, based on the Akaike information criterion (AIC); values for the frailty model and one without the frailty parameter were 1370.39 and 1381.46, respectively.Conclusions:The data from this study indicate ae necessity to consider competing risk, cure fraction and heterogeneity in survival modeling. The competing risk-cure-frailty model can cover complex situations with survival data.