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Background: Clinical trials of HER2-directed therapy that omit neoadjuvant conventional chemotherapy for HER+ breast cancer demonstrate that a subset of patients still obtains a pCR. Identifying tumor characteristics which predict pCR may help select patients for de-escalated neoadjuvant dual HER2-targeted treatment without chemotherapy. This is the first study evaluating the HER2/CEP17 ratio by FISH as a biomarker to predict pCR among patients who received neoadjuvant anti-HER2 regimens without chemotherapy., Patients and Methods: Data from patients with locally advanced HER2+ breast cancer who received neoadjuvant dual HER2-targeted therapy without conventional chemotherapy from a single center was retrospectively reviewed. All patients were enrolled in one of 3 clinical trials evaluating chemotherapy de-escalation. Logistic regression modeling assessed for a relationship between the HER2/CEP17 FISH ratio obtained from baseline tissue biopsy and pCR based on pathology at the time of definitive breast surgery following neoadjuvant treatment., Results: Following neoadjuvant treatment with dual HER2-targeted therapies in 56 patients, the probability of pCR was 73% among patients with a HER2 ratio of 13.1 compared to a probability of 38% among patients with HER2 ratio of 5.5 (OR 4.14, 95% CI 1.44-11.89; P = .012). This positive association persisted after controlling for different treatment regimens administered (OR 2.87, 95% CI 0.9-9.18, P = .020)., Conclusions: These data found a positive association between the HER2/CEP17 FISH ratio and pCR following neoadjuvant dual HER2-targeted therapy without chemotherapy. Larger prospective studies are needed to validate the HER2 ratio as a biomarker to select patients for neoadjuvant dual anti-HER2 therapy without chemotherapy., (© The Author(s) 2022. Published by Oxford University Press.)

Background: Robust and reliable prognosis prediction models have not been developed and validated for Asian patients with breast cancer, a rapidly growing yet understudied population in the United States., Methods: We used longitudinal data from the Shanghai Breast Cancer Survival Study, a population-based prospective cohort study (n = 5042), to develop prediction models for 5- and 10-year disease-free survival (DFS) and overall survival (OS). The initial models considered age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, and estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status. We then evaluated whether the addition of modifiable lifestyle factors (physical activity, soy isoflavones intake, and postdiagnostic weight change) improved the models. All final models have been validated internally and externally in the National Cancer Database when applicable., Results: Our final models included age at diagnosis, tumor grade, tumor size, number of positive nodes, TNM stage, chemotherapy, tamoxifen therapy, ER status, PR status, 6-month postdiagnostic weight change, interaction between ER status and tamoxifen therapy, and interaction between age and TNM stage. The internal validation yielded C-statistics of 0.76, 0.74, 0.78, and 0.75 for 5-year DFS, 10-year DFS, 5-year OS, and 10-year OS, respectively. The external validation yielded C-statistics of 5- and 10-year OS both at 0.78 for Chinese ethnicity, 0.79 for East Asian ethnicity, and 0.75 and 0.76 for all ethnic groups combined., Conclusion: We developed prediction models for breast cancer prognosis from a large prospective study. Our prognostic models performed very well in women from the United States-particularly in Asian American women-and demonstrated high prediction accuracy and generalizability., (© 2021 American Cancer Society.)

Ductal carcinoma in situ (DCIS) is the most common type of pre-invasive breast cancer diagnosed in women. Because the majority of DCIS cases are unlikely to progress to invasive breast cancer, many women are over-treated for DCIS. By understanding the molecular basis of early stage breast cancer progression, we may identify better prognostic factors and design treatments tailored specifically to the predicted outcome of DCIS. Chemokines are small soluble molecules with complex roles in inflammation and cancer progression. Previously, we demonstrated that CCL2/CCR2 chemokine signaling in breast cancer cell lines regulated growth and invasion through p42/44MAPK and SMAD3 dependent mechanisms. Here, we sought to determine the clinical and functional relevance of CCL2/CCR2 signaling proteins to DCIS progression. Through immunostaining analysis of DCIS and IDC tissues, we show that expression of CCL2, CCR2, phospho-SMAD3 and phospho-p42/44MAPK correlate with IDC. Using PDX models and an immortalized hDCIS.01 breast epithelial cell line, we show that breast epithelial cells with high CCR2 and high CCL2 levels form invasive breast lesions that express phospho-SMAD3 and phospho-p42/44MAPK. These studies demonstrate that increased CCL2/CCR2 signaling in breast tissues is associated with DCIS progression, and could be a signature to predict the likelihood of DCIS progression to IDC.

Poly-ADP-ribose polymerase (PARP) inhibitors are active against cells and tumors with defects in homology-directed repair as a result of synthetic lethality. PARP inhibitors (PARPi) have been suggested to act by either catalytic inhibition or by PARP localization in chromatin. In this study, we treat BRCA1 mutant cells derived from a patient with triple negative breast cancer and control cells for three weeks with veliparib, a PARPi, to determine if treatment with this drug induces increased levels of mutations and/or an inflammatory response. We show that long-term treatment with PARPi induces an inflammatory response in HCC1937 BRCA1 mutant cells. The levels of chromatin-bound PARP1 in the BRCA1 mutant cells correlate with significant upregulation of inflammatory genes and activation of the cyclic GMP-AMP synthase (cGAS)/signaling effector stimulator of interferon genes (STING pathway). In contrast, an increased mutational load is induced in BRCA1-complemented cells treated with a PARPi. Our results suggest that long-term PARP inhibitor treatment may prime both BRCA1 mutant and wild-type tumors for positive responses to immune checkpoint blockade, but by different underlying mechanisms., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: We evaluated the prognostic value of lymph node ratio (LNR) for the survival of breast cancer patients using Bayesian inference., Methods: Data on 5,279 women with infiltrating duct and lobular carcinoma breast cancer, diagnosed from 2006-2010, was obtained from the NCI SEER Cancer Registry. A prognostic modeling framework was proposed using Bayesian inference to estimate the impact of LNR in breast cancer survival. Based on the proposed model, we then developed a web application for estimating LNR and predicting overall survival., Results: The final survival model with LNR outperformed the other models considered (C-statistic 0.71). Compared to directly measured LNR, estimated LNR slightly increased the accuracy of the prognostic model. Model diagnostics and predictive performance confirmed the effectiveness of Bayesian modeling and the prognostic value of the LNR in predicting breast cancer survival., Conclusion: The estimated LNR was found to have a significant predictive value for the overall survival of breast cancer patients., Significance: We used Bayesian inference to estimate LNR which was then used to predict overall survival. The models were developed from a large population-based cancer registry. We also built a user-friendly web application for individual patient survival prognosis. The diagnostic value of the LNR and the effectiveness of the proposed model were evaluated by comparisons with existing prediction models.

Using an ORF kinome screen in MCF-7 cells treated with the CDK4/6 inhibitor ribociclib plus fulvestrant, we identified FGFR1 as a mechanism of drug resistance. FGFR1-amplified/ER+ breast cancer cells and MCF-7 cells transduced with FGFR1 were resistant to fulvestrant ± ribociclib or palbociclib. This resistance was abrogated by treatment with the FGFR tyrosine kinase inhibitor (TKI) lucitanib. Addition of the FGFR TKI erdafitinib to palbociclib/fulvestrant induced complete responses of FGFR1-amplified/ER+ patient-derived-xenografts. Next generation sequencing of circulating tumor DNA (ctDNA) in 34 patients after progression on CDK4/6 inhibitors identified FGFR1/2 amplification or activating mutations in 14/34 (41%) post-progression specimens. Finally, ctDNA from patients enrolled in MONALEESA-2, the registration trial of ribociclib, showed that patients with FGFR1 amplification exhibited a shorter progression-free survival compared to patients with wild type FGFR1. Thus, we propose breast cancers with FGFR pathway alterations should be considered for trials using combinations of ER, CDK4/6 and FGFR antagonists.

We hypothesize that the relative mitochondria copy number (MTCN) can be estimated by comparing the abundance of mitochondrial DNA to nuclear DNA reads using high throughput sequencing data. To test this hypothesis, we examined relative MTCN across 13 breast cancer cell lines using the RT-PCR based NovaQUANT Human Mitochondrial to Nuclear DNA Ratio Kit as the gold standard. Six distinct computational approaches were used to estimate the relative MTCN in order to compare to the RT-PCR measurements. The results demonstrate that relative MTCN correlates well with the RT-PCR measurements using exome sequencing data, but not RNA-seq data. Through analysis of copy number variants (CNVs) in The Cancer Genome Atlas, we show that the two nuclear genes used in the NovaQUANT assay to represent the nuclear genome often experience CNVs in tumor cells, questioning the accuracy of this gold-standard method when it is applied to tumor cells., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Inhibition of proliferation in estrogen receptor-positive (ER + ) breast cancers after short-term antiestrogen therapy correlates with long-term patient outcome. We profiled 155 ER + /human epidermal growth factor receptor 2-negative (HER2 - ) early breast cancers from 143 patients treated with the aromatase inhibitor letrozole for 10 to 21 days before surgery. Twenty-one percent of tumors remained highly proliferative, suggesting that these tumors harbor alterations associated with intrinsic endocrine therapy resistance. Whole-exome sequencing revealed a correlation between 8p11-12 and 11q13 gene amplifications, including FGFR1 and CCND1 , respectively, and high Ki67. We corroborated these findings in a separate cohort of serial pretreatment, postneoadjuvant chemotherapy, and recurrent ER + tumors. Combined inhibition of FGFR1 and CDK4/6 reversed antiestrogen resistance in ER + FGFR1 / CCND1 coamplified CAMA1 breast cancer cells. RNA sequencing of letrozole-treated tumors revealed the existence of intrachromosomal ESR1 fusion transcripts and increased expression of gene signatures indicative of enhanced E2F-mediated transcription and cell cycle processes in cancers with high Ki67. These data suggest that short-term preoperative estrogen deprivation followed by genomic profiling can be used to identify druggable alterations that may cause intrinsic endocrine therapy resistance., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The rapid progress in high-throughput sequencing has significantly enriched our capacity for studying the mitochondrial DNA (mtDNA). In addition to performing specific mitochondrial targeted sequencing, an increasingly popular alternative approach is using the off-target reads from exome sequencing to infer mtDNA variants, including single nucleotide polymorphisms (SNPs) and heteroplasmy. However, the effectiveness and practicality of this approach have not been tested. Recently, RNAseq data have also been suggested as a good source for alternative data mining, but whether mitochondrial variants can be detected from RNAseq data has not been validated. We designed a study to evaluate the practicability of mtDNA variant detection using exome and RNA sequencing data. Five breast cancer cell lines were sequenced through mitochondrial targeted, exome, and RNA sequencing. Mitochondrial targeted sequencing was used as the gold standard to compute the validation and false discovery rates of SNP and heteroplasmy detection in exome and RNAseq data. We found that exome and RNA sequencing can accurately detect mitochondrial SNPs. However, the lower false discovery rate makes exome sequencing a better choice for heteroplasmy detection than RNAseq. Furthermore, we examined three alignment strategies and found that aligning reads directly to the mitochondrial reference genome or aligning reads to the nuclear and mitochondrial references genomes simultaneously produced the best results, and that aligning to the nuclear genome first and afterwards to the mitochondrial genome performed poorly. In conclusion, our study provides important guidelines for future studies that intend to use either exome sequencing or RNAseq data to infer mitochondrial SNPs and heteroplasmy., (© The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Systemic off-target toxicities, including neurotoxicity, are prevalent side effects in cancer patients treated with a number of otherwise highly efficacious anticancer drugs. In the current study, we have: (1) developed a new analytical metric for the in vivo preclinical assessment of systemic toxicities/neurotoxicity of new drugs and delivery systems; and (2) evaluated, in mice, the in vivo efficacy and toxicity of a versatile and modular NanoDendron (ND) drug delivery and imaging platform that we recently developed. Our paclitaxel-carrying ND prodrug, ND(PXL), is activated following proteolytic cleavage by MMP9, resulting in localized cytotoxic chemotherapy. Using click chemistry, we combined ND(PXL) with a traceable beacon, ND(PB), yielding ND(PXL)-ND(PB) that functions as a theranostic compound. In vivo fluorescence FRET imaging of this theranostic platform was used to confirm localized delivery to tumors and to assess the efficiency of drug delivery to tumors, achieving 25-30% activation in the tumors of an immunocompetent mouse model of breast cancer. In this model, ND-drug exhibited anti-tumor efficacy comparable to nab-paclitaxel, a clinical formulation. In addition, we combined neurobehavioral metrics of nociception and sensorimotor performance of individual mice to develop a novel composite toxicity score that reveals and quantifies peripheral neurotoxicity, a debilitating long-term systemic toxicity of paclitaxel therapy. Importantly, mice treated with nab-paclitaxel developed changes in behavioral metrics with significantly higher toxicity scores indicative of peripheral neuropathy, while mice treated with ND(PXL) showed no significant changes in behavioral responses or toxicity score. Our ND formulation was designed to be readily adaptable to incorporate different drugs, imaging modalities and/or targeting motifs. This formulation has significant potential for preclinical and clinical tools across multiple disease states. The studies presented here report a novel toxicity score for assessing peripheral neuropathy and demonstrate that our targeted, theranostic NDs are safe and effective, providing localized tumor delivery of a chemotherapeutic and with reduced common neurotoxic side-effects., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Importance: Accredited breast centers in the United States are measured on performance of breast conservation surgery (BCS) in the majority of women with early-stage breast cancer. Prior research in regional and limited national cohorts suggests a recent shift toward increasing performance of mastectomy in patients eligible for BCS., Objective: To examine whether mastectomy rates in patients eligible for BCS are increasing over time nationwide, and are associated with coincident increases in breast reconstruction and bilateral mastectomy for unilateral disease., Design, Setting, and Participants: We performed a retrospective cohort study of temporal trends in performance of mastectomy for early-stage breast cancer using multivariable logistic regression modeling to adjust for pertinent covariates and interactions. We studied more than 1.2 million adult women treated at centers accredited by the American Cancer Society and the American College of Surgeons Commission on Cancer from January 1, 1998, to December 31, 2011, using the National Cancer Data Base., Exposures: Year of breast cancer diagnosis., Main Outcomes and Measures: Proportion of women with early-stage breast cancer who underwent mastectomy. Secondary outcome measures include temporal trends in breast reconstruction and bilateral mastectomy for unilateral disease., Results: A total of 35.5% of the study cohort underwent mastectomy. The adjusted odds of mastectomy in BCS-eligible women increased 34% during the most recent 8 years of the cohort, with an odds ratio of 1.34 (95% CI, 1.31-1.38) in 2011 relative to 2003. Rates of increase were greatest in women with clinically node-negative disease (odds ratio, 1.38; 95% CI, 1.34-1.41) and in situ disease (odds ratio, 2.05; 95% CI, 1.95-2.15). In women undergoing mastectomy, rates of breast reconstruction increased from 11.6% in 1998 to 36.4% in 2011 (P < .001 for trend). Rates of bilateral mastectomy for unilateral disease increased from 1.9% in 1998 to 11.2% in 2011 (P < .001)., Conclusions and Relevance: In the past decade, there have been marked trends toward higher proportions of BCS-eligible patients undergoing mastectomy, breast reconstruction, and bilateral mastectomy. The greatest increases are seen in women with node-negative and in situ disease. Mastectomy rates do not yet exceed current American Cancer Society/American College of Surgeons Commission on Cancer accreditation benchmarks. Further research is needed to understand factors associated with these trends and their implications for performance measurement in American Cancer Society/American College of Surgeons Commission on Cancer centers.

Mutations in the PIK3CA gene are common in breast cancer and represent a clinically useful therapeutic target. Several larger, population-based studies have shown a positive prognostic significance associated with these mutations. This study aims to further identify characteristics of patients harboring PIK3CA mutations while evaluating the clinical impact of genomic testing for these mutations. Tumors from 312 patients at Vanderbilt-Ingram Cancer Center were analyzed for PIK3CA mutations using a multiplex screening assay (SNaPshot). Mutation rates, receptor status, histopathologic characteristics, and time to recurrence were assessed. The number of patients participating in clinical trials, specifically trials relating to the PIK3CA mutation, was examined. Statistically significant differences between wild-type and mutated tumors were determined using the Wilcoxon, Pearson, and Fischer exact tests. The PIK3CA mutation was found in 25 % of tumors tested. Patients with PIK3CA mutations were significantly more likely to express hormone receptors, be of lower combined histological grade, and have a reduced time to recurrence. Patients found to have a PIK3CA mutation were significantly more likely to enter a PIK3CA-specific clinical trial. In addition to confirming previously established positive prognostic characteristics of tumors harboring PIK3CA mutations, this study demonstrates the feasibility and utility of mutation profiling in a clinical setting. PIK3CA mutation testing impacted treatment and resulted in more patients entering mutation-specific clinical trials.

Background: Robust transcriptional signatures in cancer can be identified by data similarity-driven meta-analysis of gene expression profiles. An unbiased data integration and interrogation strategy has not previously been available., Methods and Findings: We implemented and performed a large meta-analysis of breast cancer gene expression profiles from 223 datasets containing 10,581 human breast cancer samples using a novel data similarity-based approach (iterative EXALT). Cancer gene expression signatures extracted from individual datasets were clustered by data similarity and consolidated into a meta-signature with a recurrent and concordant gene expression pattern. A retrospective survival analysis was performed to evaluate the predictive power of a novel meta-signature deduced from transcriptional profiling studies of human breast cancer. Validation cohorts consisting of 6,011 breast cancer patients from 21 different breast cancer datasets and 1,110 patients with other malignancies (lung and prostate cancer) were used to test the robustness of our findings. During the iterative EXALT analysis, 633 signatures were grouped by their data similarity and formed 121 signature clusters. From the 121 signature clusters, we identified a unique meta-signature (BRmet50) based on a cluster of 11 signatures sharing a phenotype related to highly aggressive breast cancer. In patients with breast cancer, there was a significant association between BRmet50 and disease outcome, and the prognostic power of BRmet50 was independent of common clinical and pathologic covariates. Furthermore, the prognostic value of BRmet50 was not specific to breast cancer, as it also predicted survival in prostate and lung cancers., Conclusions: We have established and implemented a novel data similarity-driven meta-analysis strategy. Using this approach, we identified a transcriptional meta-signature (BRmet50) in breast cancer, and the prognostic performance of BRmet50 was robust and applicable across a wide range of cancer-patient populations.

Background: When using Illumina high throughput short read data, sometimes the genotype inferred from the positive strand and negative strand are significantly different, with one homozygous and the other heterozygous. This phenomenon is known as strand bias. In this study, we used Illumina short-read sequencing data to evaluate the effect of strand bias on genotyping quality, and to explore the possible causes of strand bias., Result: We collected 22 breast cancer samples from 22 patients and sequenced their exome using the Illumina GAIIx machine. By comparing the consistency between the genotypes inferred from this sequencing data with the genotypes inferred from SNP chip data, we found that, when using sequencing data, SNPs with extreme strand bias did not have significantly lower consistency rates compared to SNPs with low or no strand bias. However, this result may be limited by the small subset of SNPs present in both the exome sequencing and the SNP chip data. We further compared the transition and transversion ratio and the number of novel non-synonymous SNPs between the SNPs with low or no strand bias and those with extreme strand bias, and found that SNPs with low or no strand bias have better overall quality. We also discovered that the strand bias occurs randomly at genomic positions across these samples, and observed no consistent pattern of strand bias location across samples. By comparing results from two different aligners, BWA and Bowtie, we found very consistent strand bias patterns. Thus strand bias is unlikely to be caused by alignment artifacts. We successfully replicated our results using two additional independent datasets with different capturing methods and Illumina sequencers., Conclusion: Extreme strand bias indicates a potential high false-positive rate for SNPs.

Despite available demographic data on the factors that contribute to breast cancer mortality in large population datasets, local patterns are often overlooked. Such local information could provide a valuable metric by which regional community health resources can be allocated to reduce breast cancer mortality. We used national and statewide datasets to assess geographical distribution of breast cancer mortality rates and known risk factors influencing breast cancer mortality in middle Tennessee. Each county in middle Tennessee, and each ZIP code within metropolitan Davidson County, was scored for risk factor prevalence and assigned quartile scores that were used as a metric to identify geographic areas of need. While breast cancer mortality often correlated with age and incidence, geographic areas were identified in which breast cancer mortality rates did not correlate with age and incidence, but correlated with additional risk factors, such as mammography screening and socioeconomic status. Geographical variability in specific risk factors was evident, demonstrating the utility of this approach to identify local areas of risk. This method revealed local patterns in breast cancer mortality that might otherwise be overlooked in a more broadly based analysis. Our data suggest that understanding the geographic distribution of breast cancer mortality, and the distribution of risk factors that contribute to breast cancer mortality, will not only identify communities with the greatest need of support, but will identify the types of resources that would provide the most benefit to reduce breast cancer mortality in the community.

VAPB (VAMP- associated protein B) is an ER protein that regulates multiple biological functions. Although aberrant expression of VAPB is associated with breast cancer, its function in tumor cells is poorly understood. In this report, we provide evidence that VAPB regulates breast tumor cell proliferation and AKT activation. VAPB protein expression is elevated in primary and metastatic tumor specimens, and VAPB mRNA expression levels correlated negatively with patient survival in two large breast tumor datasets. Overexpression of VAPB in mammary epithelial cells increased cell growth, whereas VAPB knockdown in tumor cells inhibited cell proliferation in vitro and suppressed tumor growth in orthotopic mammary gland allografts. The growth regulation of mammary tumor cells controlled by VAPB appears to be mediated, at least in part, by modulation of AKT activity. Overexpression of VAPB in MCF10A-HER2 cells enhances phosphorylation of AKT. In contrast, knockdown of VAPB in MMTV-Neu tumor cells inhibited pAKT levels. Pharmacological inhibition of AKT significantly reduced three-dimensional spheroid growth induced by VAPB. Collectively, the genetic, functional and mechanistic analyses suggest a role of VAPB in tumor promotion in human breast cancer.

Estrogen receptor α (ER)-positive breast cancers adapt to hormone deprivation and become resistant to antiestrogens. In this study, we sought to identify kinases essential for growth of ER(+) breast cancer cells resistant to long-term estrogen deprivation (LTED). A kinome-wide siRNA screen showed that the insulin receptor (InsR) is required for growth of MCF-7/LTED cells. Knockdown of InsR and/or insulin-like growth factor-I receptor (IGF-IR) inhibited growth of 3 of 4 LTED cell lines. Inhibition of InsR and IGF-IR with the dual tyrosine kinase inhibitor OSI-906 prevented the emergence of hormone-independent cells and tumors in vivo, inhibited parental and LTED cell growth and PI3K/AKT signaling, and suppressed growth of established MCF-7 xenografts in ovariectomized mice, whereas treatment with the neutralizing IGF-IR monoclonal antibody MAB391 was ineffective. Combined treatment with OSI-906 and the ER downregulator fulvestrant more effectively suppressed hormone-independent tumor growth than either drug alone. Finally, an insulin/IGF-I gene expression signature predicted recurrence-free survival in patients with ER(+) breast cancer treated with the antiestrogen tamoxifen. We conclude that therapeutic targeting of both InsR and IGF-IR should be more effective than targeting IGF-IR alone in abrogating resistance to endocrine therapy in breast cancer., (©2011 AACR.)

We report that IL-17 significantly increases the secretion of CXCL1 and CXCL5 from mammary carcinoma cells, which is downregulated by TGF-β through the type II TGF-β receptor (TβRII). Carcinoma cells with conditional knockout of TβRII (Tgfbr2(KO)) have enhanced sensitivity to IL-17a in the stimulation of chemokine secretion. During polyoma middle T (PyMT) induced tumor progression, levels of Th17 inducing cytokines TGF-β, IL-6, IL-23 were increased in PyMT/Tgfbr2(KO) tumors, which was associated with an increased number of Th17 cells. IL-17 increased the suppressive function of MDSCs on T cells through the upregulation of Arg, IDO, and COX2. Treatment of PyMT/Tgfbr2(KO) mice with anti-IL-17 Ab decreased carcinoma growth and metastatic burden. Analysis of human breast cancer transcriptome databases showed a strong association between IL-17 gene expression and poor outcome in lymph node positive, estrogen receptor negative or luminal B subtypes suggesting potential therapeutic approaches.

Most estrogen receptor α (ER)-positive breast cancers initially respond to antiestrogens, but many eventually become estrogen-independent and recur. We identified an estrogen-independent role for ER and the CDK4/Rb/E2F transcriptional axis in the hormone-independent growth of breast cancer cells. ER downregulation with fulvestrant or small interfering RNA (siRNA) inhibited estrogen-independent growth. Chromatin immunoprecipitation identified ER genomic binding activity in estrogen-deprived cells and primary breast tumors treated with aromatase inhibitors. Gene expression profiling revealed an estrogen-independent, ER/E2F-directed transcriptional program. An E2F activation gene signature correlated with a lesser response to aromatase inhibitors in patients' tumors. siRNA screening showed that CDK4, an activator of E2F, is required for estrogen-independent cell growth. Long-term estrogen-deprived cells hyperactivate phosphatidylinositol 3-kinase (PI3K) independently of ER/E2F. Fulvestrant combined with the pan-PI3K inhibitor BKM120 induced regression of ER(+) xenografts. These data support further development of ER downregulators and CDK4 inhibitors, and their combination with PI3K inhibitors for treatment of antiestrogen-resistant breast cancers., (©2011 AACR.)

Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem-like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted "driver" signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.

Purpose: Although most patients with estrogen receptor α (ER)-positive breast cancer initially respond to endocrine therapy, many ultimately develop resistance to antiestrogens. However, mechanisms of antiestrogen resistance and biomarkers predictive of such resistance are underdeveloped., Experimental Design: We adapted four ER(+) human breast cancer cell lines to grow in an estrogen-depleted medium. A gene signature of estrogen independence was developed by comparing expression profiles of long-term estrogen-deprived (LTED) cells to their parental counterparts. We evaluated the ability of the LTED signature to predict tumor response to neoadjuvant therapy with an aromatase inhibitor and disease outcome following adjuvant tamoxifen. We utilized Gene Set Analysis (GSA) of LTED cell gene expression profiles and a loss-of-function approach to identify pathways causally associated with resistance to endocrine therapy., Results: The LTED gene expression signature was predictive of high tumor cell proliferation following neoadjuvant therapy with anastrozole and letrozole, each in different patient cohorts. This signature was also predictive of poor recurrence-free survival in two studies of patients treated with adjuvant tamoxifen. Bioinformatic interrogation of expression profiles in LTED cells revealed a signature of MYC activation. The MYC activation signature and high MYC protein levels were both predictive of poor outcome following tamoxifen therapy. Finally, knockdown of MYC inhibited LTED cell growth., Conclusions: A gene expression signature derived from ER(+) breast cancer cells with acquired hormone independence predicted tumor response to aromatase inhibitors and associated with clinical markers of resistance to tamoxifen. Activation of the MYC pathway was associated with this resistance.

It is well known that tumor-derived proangiogenic factors induce neovascularization to facilitate tumor growth and malignant progression. However, the concept of "angiocrine" signaling, in which signals produced by endothelial cells elicit tumor cell responses distinct from vessel function, has been proposed, yet remains underinvestigated. Here, we report that angiocrine factors secreted from endothelium regulate tumor growth and motility. We found that Slit2, which is negatively regulated by endothelial EphA2 receptor, is one such tumor suppressive angiocrine factor. Slit2 activity is elevated in EphA2-deficient endothelium. Blocking Slit activity restored angiocrine-induced tumor growth/motility, whereas elevated Slit2 impaired growth/motility. To translate our findings to human cancer, we analyzed EphA2 and Slit2 expression in human cancer. EphA2 expression inversely correlated with Slit2 in the vasculature of invasive human ductal carcinoma samples. Moreover, analysis of large breast tumor data sets revealed that Slit2 correlated positively with overall and recurrence-free survival, providing clinical validation for the tumor suppressor function for Slit2 in human breast cancer. Together, these data support a novel, clinically relevant mechanism through which EphA2 represses Slit2 expression in endothelium to facilitate angiocrine-mediated tumor growth and motility by blocking a tumor suppressive signal.

Breast cancer often metastasizes to bone causing osteolytic bone resorption which releases active TGFβ. Because TGFβ favors progression of breast cancer metastasis to bone, we hypothesized that treatment using anti-TGFβ antibody may reduce tumor burden and rescue tumor-associated bone loss in metastatic breast cancer. In this study we have tested the efficacy of an anti-TGFβ antibody 1D11 preventing breast cancer bone metastasis. We have used two preclinical breast cancer bone metastasis models, in which either human breast cancer cells or murine mammary tumor cells were injected in host mice via left cardiac ventricle. Using several in vivo, in vitro and ex vivo assays, we have demonstrated that anti-TGFβ antibody treatment have significantly reduced tumor burden in the bone along with a statistically significant threefold reduction in osteolytic lesion number and tenfold reduction in osteolytic lesion area. A decrease in osteoclast numbers (p = 0.027) in vivo and osteoclastogenesis ex vivo were also observed. Most importantly, in tumor-bearing mice, anti-TGFβ treatment resulted in a twofold increase in bone volume (p<0.01). In addition, treatment with anti-TGFβ antibody increased the mineral-to-collagen ratio in vivo, a reflection of improved tissue level properties. Moreover, anti-TGFβ antibody directly increased mineralized matrix formation in calverial osteoblast (p = 0.005), suggesting a direct beneficial role of anti-TGFβ antibody treatment on osteoblasts. Data presented here demonstrate that anti-TGFβ treatment may offer a novel therapeutic option for tumor-induced bone disease and has the dual potential for simultaneously decreasing tumor burden and rescue bone loss in breast cancer to bone metastases. This approach of intervention has the potential to reduce skeletal related events (SREs) in breast cancer survivors.

Pre-clinical studies provide compelling evidence that Eph family receptor tyrosine kinases (RTKs) and ligands promote cancer growth, neovascularization, invasion, and metastasis. Tumor suppressive roles have also been reported for the receptors, however, creating a potential barrier for clinical application. Determining how these observations relate to clinical outcome is a crucial step for translating the biological and mechanistic data into new molecularly targeted therapies. We investigated eph and ephrin expression in human breast cancer relative to endpoints of overall and/or recurrence-free survival in large microarray datasets. We also investigated protein expression in commercial human breast tissue microarrays (TMA) and Stage I prognostic TMAs linked to recurrence outcome data. We found significant correlations between ephA2, ephA4, ephA7, ephB4, and ephB6 and overall and/or recurrence-free survival in large microarray datasets. Protein expression in TMAs supported these trends. While observed no correlation between ephrin ligand expression and clinical outcome in microarray datasets, ephrin-A1 and EphA2 protein co-expression was significantly associated with recurrence in Stage I prognostic breast cancer TMAs. Our data suggest that several Eph family members are clinically relevant and tractable targets for intervention in human breast cancer. Moreover, profiling Eph receptor expression patterns in the context of relevant ligands and in the context of stage may be valuable in terms of diagnostics and treatment.

Background: Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population., Methods: We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided., Results: Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population., Conclusion: A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs.

Many breast cancers exhibit a degree of dependence on estrogen for tumor growth. Although several therapies have been developed to treat individuals with estrogen-dependent breast cancers, some tumors show de novo or acquired resistance, rendering them particularly elusive to current therapeutic strategies. Understanding the mechanisms by which these cancers develop resistance would enable the development of new and effective therapeutics. In order to determine mechanisms of escape from hormone dependence in estrogen receptor-positive (ER-positive) breast cancer, we established 4 human breast cancer cell lines after long-term estrogen deprivation (LTED). LTED cells showed variable changes in ER levels and sensitivity to 17beta-estradiol. Proteomic profiling of LTED cells revealed increased phosphorylation of the mammalian target of rapamycin (mTOR) substrates p70S6 kinase and p85S6 kinase as well as the PI3K substrate AKT. Inhibition of PI3K and mTOR induced LTED cell apoptosis and prevented the emergence of hormone-independent cells. Using reverse-phase protein microarrays, we identified a breast tumor protein signature of PI3K pathway activation that predicted poor outcome after adjuvant endocrine therapy in patients. Our data suggest that upon adaptation to hormone deprivation, breast cancer cells rely heavily on PI3K signaling. Our findings also imply that acquired resistance to endocrine therapy in breast cancer may be abrogated by combination therapies targeting both ER and PI3K pathways.

Introduction: Paclitaxel is a widely used drug in the treatment of patients with locally advanced and metastatic breast cancer. However, only a small portion of patients have a complete response to paclitaxel-based chemotherapy, and many patients are resistant. Strategies that increase sensitivity and limit resistance to paclitaxel would be of clinical use, especially for patients with triple-negative breast cancer (TNBC)., Methods: We generated a gene set from overlay of the druggable genome and a collection of genomically deregulated gene transcripts in breast cancer. We used loss-of-function RNA interference (RNAi) to identify gene products in this set that, when targeted, increase paclitaxel sensitivity. Pharmacological agents that targeted the top scoring hits/genes from our RNAi screens were used in combination with paclitaxel, and the effects on the growth of various breast cancer cell lines were determined., Results: RNAi screens performed herein were validated by identification of genes in pathways that, when previously targeted, enhanced paclitaxel sensitivity in the pre-clinical and clinical settings. When chemical inhibitors, CCT007093 and mithramycin, against two top hits in our screen, PPMID and SP1, respectively, were used in combination with paclitaxel, we observed synergistic growth inhibition in both 2D and 3D breast cancer cell cultures. The transforming growth factor beta (TGFbeta) receptor inhibitor, LY2109761, that targets the signaling pathway of another top scoring hit, TGFbeta1, was synergistic with paclitaxel when used in combination on select breast cancer cell lines grown in 3D culture. We also determined the relative paclitaxel sensitivity of 22 TNBC cell lines and identified 18 drug-sensitive and four drug-resistant cell lines. Of significance, we found that both CCT007093 and mithramycin, when used in combination with paclitaxel, resulted in synergistic inhibition of the four paclitaxel-resistant TNBC cell lines., Conclusions: RNAi screening can identify druggable targets and novel drug combinations that can sensitize breast cancer cells to paclitaxel. This genomic-based approach can be applied to a multitude of tumor-derived cell lines and drug treatments to generate requisite pre-clinical data for new drug combination therapies to pursue in clinical investigations.

Purpose/objectives: To identify factors associated with diagnostic delay after an incomplete or abnormal mammogram among women participating in a state mammography screening program., Research Approach: Retrospective case-control design using bivariate and multivariate logistic regression analyses to explore the associations between age, race, ethnicity, marital status, breast cancer history, and self-reported breast symptoms and delay., Setting: A statewide program of free screening mammography for women who are under- or uninsured., Participants: 11,460 women enrolled in a free, statewide screening program from 2002-2006., Methodologic Approach: Using the Tennessee Breast and Cervical Cancer Screening Program database, further analyses were conducted., Main Research Variables: The outcome measure was delay in completion of all diagnostic tests and was defined as women who did not complete testing within 60 days., Findings: Thirty-seven percent of women required follow-up, and of a subset used in the analysis, 30% experienced delay of more than 60 days. Controlling for marital status, age, and breast cancer history, women who experienced delay were more likely to be African American versus Caucasian (odds ratio [OR] = 1.45, 95% confidence interval [CI] = 1.13, 1.85) or Hispanic (OR = 0.72, 95% CI = 0.55, 0.93) and to have self-reported breast symptoms (OR = 1.50, 95% CI = 1.27, 1.77)., Conclusions: In a sample of women with low income needing mammography follow-up, delay was associated with three intrapersonal variables, potentially reducing the effectiveness of mammography screening for women who were African American, or Hispanic, or had self-reported breast symptoms., Interpretation: Nurses providing cancer screening examinations are uniquely positioned to assess the knowledge, beliefs, and resources of women using the program and to navigate women through barriers to completion. Knowledge of factors associated with delay is valuable for planning interventions and allocating program resources.

In human breast cancer, loss of carcinoma cell-specific response to TGF-beta signaling has been linked to poor patient prognosis. However, the mechanisms through which TGF-beta regulates these processes remain largely unknown. In an effort to address this issue, we have now identified gene expression signatures associated with the TGF-beta signaling pathway in human mammary carcinoma cells. The results strongly suggest that TGF-beta signaling mediates intrinsic, stromal-epithelial, and host-tumor interactions during breast cancer progression, at least in part, by regulating basal and oncostatin M-induced CXCL1, CXCL5, and CCL20 chemokine expression. To determine the clinical relevance of our results, we queried our TGF-beta-associated gene expression signatures in 4 human breast cancer data sets containing a total of 1,319 gene expression profiles and associated clinical outcome data. The signature representing complete abrogation of TGF-beta signaling correlated with reduced relapse-free survival in all patients; however, the strongest association was observed in patients with estrogen receptor-positive (ER-positive) tumors, specifically within the luminal A subtype. Together, the results suggest that assessment of TGF-beta signaling pathway status may further stratify the prognosis of ER-positive patients and provide novel therapeutic approaches in the management of breast cancer.

Purpose: To administer the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor erlotinib to patients with operable untreated breast cancer during the immediate preoperative period and to measure an antiproliferative and/or a proapoptotic effect in the post-therapy specimen and determine a biomarker profile associated with evidence of erlotinib-mediated cellular activity., Patients and Methods: Newly diagnosed patients with stages I to IIIA invasive breast cancer were treated with erlotinib 150 mg/d orally for 6 to 14 days until the day before surgery. Erlotinib plasma levels were measured by tandem mass spectrometry the day of surgery. Drug-induced changes in tumor cell proliferation and apoptosis were assessed by Ki67 immunohistochemistry and terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate-biotin nick-end labeling analysis, respectively, in biopsies from the pretherapy and surgical specimens. Biopsies were also evaluated for P-EGFR, P-HER-2, P-MAPK, P-Akt, P-S6, and S118 P-ER alpha., Results: In drug-sensitive PC9 xenografts, 5 days of treatment with erlotinib were enough to induce a maximal inhibition of cell proliferation and induction of apoptosis. Forty-one patients completed preoperative treatment with erlotinib. Grade

EphA2 belongs to a unique family of receptor tyrosine kinases that play critical roles in development and disease. Since EphA2 is required for ephrin-A1 ligand-induced vascular remodeling and is overexpressed in a variety of vascularized human adenocarcinomas, we assessed tumor angiogenesis and metastatic progression in EphA2-deficient host animals. 4T1 metastatic mammary adenocarcinoma cells transplanted subcutaneously and orthotopically into EphA2-deficient female mice displayed decreased tumor volume, tumor cell survival, microvascular density, and lung metastasis relative to tumor-bearing littermate controls. To determine if the phenotype in EphA2-deficient mice was endothelial cell intrinsic, we also analyzed endothelial cells isolated from EphA2-deficient animals for their ability to incorporate into tumor vessels in vivo, as well as to migrate in response to tumor-derived signals in vitro. EphA2-deficient endothelial cells displayed impaired survival and failed to incorporate into tumor microvessels in vivo, and displayed impaired tumor-mediated migration in vitro relative to controls. These data suggest that host EphA2 receptor tyrosine kinase function is required in the tumor microenvironment for tumor angiogenesis and metastatic progression.

Black women have the highest mortality for breast cancer. Our hypothesis is that racial disparities in breast cancer survival persist after controlling for stage of disease and treatment at both a city hospital as well as at a university hospital. Data from tumor registries of breast cancer patients at a city hospital and a university center were analyzed for overall and disease-specific survival, controlling for stage and treatment. Black patients presented with more advanced stages and had significantly worse survival compared with whites. After controlling for stage of disease and treatment, a difference in survival persisted for stage II patients, with blacks doing worse than whites at both institutions. Although there were socioeconomic differences, race was an independent prognostic factor, with black patients having the worse prognosis. The lower survival of black women with breast cancer is only partially explained by their advanced stage at diagnosis. Black women with potentially curable stage II cancer had a lower survival that is not explained by the variables measured.