Studies Of Triple Negative Breast Cancer Research Articles

Stemness of Cancer: A Study of Triple-negative Breast Cancer From a Neuroscience Perspective.

Stemness, giving cancer cells massive plasticity enabling them to survive in dynamic (e.g. hypoxic) environments and become resistant to treatment, especially chemotherapy, is an important property of aggressive tumours. Here, we review some essentials of cancer stemness focusing on triple-negative breast cancer (TNBC), the most aggressive form of all breast cancers. TNBC cells express a range of genes and mechanisms associated with stemness, including the fundamental four "Yamanaka factors". Most of the evidence concerns the transcription factor / oncogene c-Myc and an interesting case is the expression of the neonatal splice variant of voltage-gated sodium channel subtype Nav1.5. On the whole, measures that reduce the stemness make cancer cells less aggressive, reducing their invasive/metastatic potential and increasing/restoring their chemosensitivity. Such measures include gene silencing techniques, epigenetic therapies as well as novel approaches like optogenetics aiming to modulate the plasma membrane voltage. Indeed, simply hyperpolarizing their membrane potential can make stem cells differentiate. Finally, we give an overview of the clinical aspects and exploitation of cancer/TNBC stemness, including diagnostics and therapeutics. In particular, personalised mRNA-based therapies and mechanistically meaningful combinations are promising and the emerging discipline of 'cancer neuroscience' is providing novel insights to both fundamental issues and clinical applications.

Abstract PL-01: Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability

Abstract Chromosomal instability (CIN) is a poor prognostic feature with high prevalence in breast cancer and is responsible for driving Somatic Copy Number Aberrations and Intratumour Heterogeneity (ITH) within subclones during breast cancer evolution. We have observed that SCNAs are enriched in metastatic samples, including gains in chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. However, there have thus far been no prospective, comprehensive studies of intratumor heterogeneity in breast cancer. We will present data from TRACERx Breast/SCANDARE a prospective, multicentre study of triple-negative breast cancer (TNBC) in which multi-region biopsies have been collected from primary TNBC prior to neoadjuvant treatment, and at longitudinal time points including surgery and relapse. We find prevalent intratumor heterogeneity in somatic mutations and SCNAs in the primary tumor prior to treatment. We have leveraged the rich clinical annotation in this cohort to correlate intratumor heterogeneity scores with key clinical outcomes, including treatment response (pathological complete response to neoadjuvant chemotherapy) and survival. We find that CIN manifests as oncogenic amplification on extrachromosomal DNA (ecDNA), which plays a pivotal role in driving drug resistance and tumor evolution. Through analysis of Whole Genome Sequencing data from 2936 breast tumors from the Genomics England breast cancer cohort, we have identified focal amplifications driven by ecDNA in 46.4% of HER2+ breast cancers. EcDNA were enriched in metastatic tumors and was associated with poor clinical outcomes. In addition to oncogenic amplifications such as HER2 derived from ecDNA during cancer evolution, ecDNAs contained immunomodulatory genes associated with reduced T cell infiltration. Further Immune-modulation by CIN results from loss of heterozygosity of the HLA locus (HLA LOH) and is a prevalent subclonal event in breast cancer. CIN is further drives haploid LOH, resulting in the high prevalence of whole genome doubling and further CIN in TNBC. Tumors are heterogeneous compositions of distinct clones with different compliments of SCNAs and varying levels of fitness, hence measuring the proliferation of individual clones to predict future evolutionary outcomes is likely to be critical. We have developed SPRINTER (Single-cell Proliferation Rate Inference in Non-homogeneous Tumours through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing data. We applied SPRINTER to 42,009 triple negative breast cancer cells, demonstrating significant proliferative heterogeneity between distinct tumor clones. Importantly, we show a correlation between higher proliferation rates and increased rates of somatic variants, suggesting proliferation links to clone evolvability. Taken together, these complimentary analyses provide evidence for the importance of CIN in driving ITH, selection, metastasis and immune evasion and provide a framework to determine recurrent evolutionary patterns in breast cancer evolution. Citation Format: C. Swanton. Breast Cancer Evolution, Immune Evasion and Metastasis Driven by Chromosomal Instability [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PL-01.

Ensemble learning model for identifying the hallmark genes of NFκB/TNF signaling pathway in cancers

BackgroundThe nuclear factor kappa B (NFκB) regulatory pathways downstream of tumor necrosis factor (TNF) play a critical role in carcinogenesis. However, the widespread influence of NFκB in cells can result in off-target effects, making it a challenging therapeutic target. Ensemble learning is a machine learning technique where multiple models are combined to improve the performance and robustness of the prediction. Accordingly, an ensemble learning model could uncover more precise targets within the NFκB/TNF signaling pathway for cancer therapy.MethodsIn this study, we trained an ensemble learning model on the transcriptome profiles from 16 cancer types in the TCGA database to identify a robust set of genes that are consistently associated with the NFκB/TNF pathway in cancer. Our model uses cancer patients as features to predict the genes involved in the NFκB/TNF signaling pathway and can be adapted to predict the genes for different cancer types by switching the cancer type of patients. We also performed functional analysis, survival analysis, and a case study of triple-negative breast cancer to demonstrate our model's potential in translational cancer medicine.ResultsOur model accurately identified genes regulated by NFκB in response to TNF in cancer patients. The downstream analysis showed that the identified genes are typically involved in the canonical NFκB-regulated pathways, particularly in adaptive immunity, anti-apoptosis, and cellular response to cytokine stimuli. These genes were found to have oncogenic properties and detrimental effects on patient survival. Our model also could distinguish patients with a specific cancer subtype, triple-negative breast cancer (TNBC), which is known to be influenced by NFκB-regulated pathways downstream of TNF. Furthermore, a functional module known as mononuclear cell differentiation was identified that accurately predicts TNBC patients and poor short-term survival in non-TNBC patients, providing a potential avenue for developing precision medicine for cancer subtypes.ConclusionsIn conclusion, our approach enables the discovery of genes in NFκB-regulated pathways in response to TNF and their relevance to carcinogenesis. We successfully categorized these genes into functional groups, providing valuable insights for discovering more precise and targeted cancer therapeutics.

IRE1α Disruption in Triple-Negative Breast Cancer Cooperates with Antiangiogenic Therapy by Reversing ER Stress Adaptation and Remodeling the Tumor Microenvironment.

Cancer cells exploit the unfolded protein response (UPR) to mitigate endoplasmic reticulum (ER) stress caused by cellular oncogene activation and a hostile tumor microenvironment (TME). The key UPR sensor IRE1α resides in the ER and deploys a cytoplasmic kinase-endoribonuclease module to activate the transcription factor XBP1s, which facilitates ER-mediated protein folding. Studies of triple-negative breast cancer (TNBC)-a highly aggressive malignancy with a dismal posttreatment prognosis-implicate XBP1s in promoting tumor vascularization and progression. However, it remains unknown whether IRE1α adapts the ER in TNBC cells and modulates their TME, and whether IRE1α inhibition can enhance antiangiogenic therapy-previously found to be ineffective in patients with TNBC. To gauge IRE1α function, we defined an XBP1s-dependent gene signature, which revealed significant IRE1α pathway activation in multiple solid cancers, including TNBC. IRE1α knockout in TNBC cells markedly reversed substantial ultrastructural expansion of their ER upon growth in vivo. IRE1α disruption also led to significant remodeling of the cellular TME, increasing pericyte numbers while decreasing cancer-associated fibroblasts and myeloid-derived suppressor cells. Pharmacologic IRE1α kinase inhibition strongly attenuated growth of cell line-based and patient-derived TNBC xenografts in mice and synergized with anti-VEGFA treatment to cause tumor stasis or regression. Thus, TNBC cells critically rely on IRE1α to adapt their ER to in vivo stress and to adjust the TME to facilitate malignant growth. TNBC reliance on IRE1α is an important vulnerability that can be uniquely exploited in combination with antiangiogenic therapy as a promising new biologic approach to combat this lethal disease. SIGNIFICANCE: Pharmacologic IRE1α kinase inhibition reverses ultrastructural distension of the ER, normalizes the tumor vasculature, and remodels the cellular TME, attenuating TNBC growth in mice.

Abstract 4506: UPR biomarker expression correlates with inhibition of migration of TNBC cells treated with low doses of chemotherapy

Abstract Much attention has been directed to the study of triple-negative breast cancer (TNBC) because of its short disease-free interval from diagnosis and more aggressive course in the metastatic setting. TNBC also lacks specific target receptors for treatment. Third-generation metronomic chemotherapy using available agents that target DNA repair complexes (i.e., taxanes), and cell proliferation (i.e., anthracycline) have shown promise results. However, specific regimens for TNBC at the different disease stages have not been clearly defined. Therefore, researchers are seeking molecular biomarkers to predict response to current chemotherapeutic agents. In a previous study of TNBC, we demonstrated that low doses of anthracyclines and taxanes, which are known to increase endoplasmic reticulum stress, increased tumor cell expression of glucose-regulated protein 78 (GRP78), a key regulator of the unfolding protein response (UPR), resulting in tumor cell apoptosis. GRP78 gene expression is upregulated via CREB2L1, an endoplasmic reticulum transmembrane transcription factor and member of the CREB/ATF family of transcription factors. CREB3L1 is a metastatic suppressor and functions as a transducer of UPR. The aim of the present study was to investigate the effect of low doses of doxorubicin and paclitaxel on UPR activation in metastatic TNBC cells by determining CREB3L1 protein expression in correlation to cell-surface GRP78 expression. Furthermore, we related CREB3L1 and cell-surface GRP78 expression with the migration potential of the cells in response to treatment. We found that metronomic doses of doxorubicin significantly induced CREB3L1 and cell surface GRP78 expression in TNBC cells. CREB3L1 increased by 2.5-fold in MDAMB231 and by 3-fold in MDAMB468 (p<0.04); GRP78 increased by 3.7-fold and 6.1-fold, respectively (p<0.01). Similar results were obtained with low doses of paclitaxel. A strong correlation was observed between CREB3L1 and cell-surface GRP78 protein expression. The increased expression of both proteins in MDAMB231 (highly metastatic) and MDAMB468 (moderated metastatic) was associated with significant inhibition of the migration capacity of the treated TNBC cells. In contrast, the migration capacity of treated estrogen-positive MCF7 cells (non-metastatic) and Her2- positive BT474 cells (highly metastatic) was poorly inhibited, coinciding with a non-significant increase in CREB3L1 and GRP78 expression. The results demonstrated that the drug effect via the UPR was specific for TNBC and unrelated to the metastatic profile of the cells. This study is the first stage in the identification of UPR-related biomarkers of beneficial outcome of metronomic chemotherapy for TNBC. Future mechanistic studies should focus on the possible use of cell surface GRP78 and CREB3L1 as targets for combination therapies. Citation Format: Annat Raiter, Julia Lipovetsky, Britta Hardy, Rinat Yerushalmi. UPR biomarker expression correlates with inhibition of migration of TNBC cells treated with low doses of chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4506. doi:10.1158/1538-7445.AM2017-4506

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods.

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients. This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation. The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics. Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Clinicopathological and Molecular Study of Triple-Negative Breast Cancer in Algerian Patients.

Triple-negative breast cancer (TNBC) is associated with aggressive tumor behavior, poor prognosis and BRCA1 mutations. There are limited data regarding TNBC among Algerian women. In this study, we sought to determine clinical and tumor characteristics associated with TNBC. We also screened for the prevalence of BRCA1 mutations in unselected cohort of TNBC patients. Clinical and tumor characteristics data of 877 breast cancer patients diagnosed between 2011 and 2015, were collected from cancer registry of public hospital of Rouiba. Patients were divided in two groups: those with TNBC and those with other breast cancer subtypes. Differences between the two groups with regard to clinical and tumor characteristics were compared using Fisher's exact test. BRCA1 mutations analysis was performed in unselected cohort of 103 women with TNBC, including all exons where a mutation was previously found in Algerian population (exons 2, 3, 5, 11). The median age at diagnosis for TNBC and non-TNBC patients was 47.4years and 49.4years, respectively. The proportion of TNBC was 19.95%. Our data showed significant differences in menopausal status, TNM stage, histological type, tumor histological grade, Ki67 expression and family history of breast cancer between TNBC and non-TNBC patients. Four distinct deleterious mutations in BRCA1 gene were detected in eight young TNBC patients. TNBC is associated with young age, poor histopathological characteristics and family history of breast cancer. BRCA1 mutations have been detected in young TNBC patients. TNBC phenotype should be added as criterion to screen for BRCA1 mutations in Algerian women.

High-throughput «Omics» technologies: New tools for the study of triple-negative breast cancer

Triple negative breast cancer (TNBC) represents about 15% to 20% of all breast cancers and is typically associated with poorer outcome than other breast cancer subtypes. The heterogeneity of this breast cancer subtype and present lack of clinically established targeted therapies further complicates treatment of patients. The treatment of TNBC emphasizes enhancing health care and developing personalized medicine. To respond to this need, the researchers have turned their attention to a different approach to scientific enquiry: the era of “big biology” and the integrative study of biological systems, also called “Omics” technologies. The term omics comprises different fields of molecular studies and characterizes a global view on biological molecules such as DNA, RNA, proteins, and metabolites. Combined “omics” approach offers a major tool for the understanding of a challenging cancer model, TNBC. This review discusses the different discoveries made using omics technologies concerning the molecular mechanisms underlying TNBC phenotypic heterogeneity, and their potential transfer to clinical applications.

Abstract P3-07-25: Improved clinical outcomes on enzalutamide observed in patients with PREDICT AR+ triple-negative breast cancer: prognosis or prediction?

Abstract Background: A novel genomic signature that identifies androgen receptor (AR)-driven disease (PREDICT AR) is being developed for its ability to select patients (pts) who may benefit from enzalutamide (ENZA), a potent AR inhibitor.1 In a phase 2 study of triple-negative breast cancer (TNBC) pts treated with ENZA (NCT01889238) ≈ half of pts had PREDICT AR+ TNBC, with improved clinical outcomes in this sub-population.2 Because pts with hormonally driven (estrogen-receptor/progesterone-receptor[ER/PR]+) BC are thought to have a better prognosis, we investigated whether the outcomes observed in pts with PREDICT AR+ TNBC could be explained by prognosis alone. Methods: PREDICT AR was assessed on advanced TNBC from 118 ENZA-treated pts.2 Because the duration of treatment (Tx) typically decreases with each subsequent Tx, exploratory analyses included median progression-free survival (mPFS) on ENZA vs duration of Tx prior to ENZA (used as a PFS surrogate) in pts who had received ≤1 prior Tx (data cutoff 24Mar15). Baseline characteristics by PREDICT AR status were also evaluated. An independent non-ENZA-Tx TNBC data set (after neo/adjuvant Tx)3 was probed for PREDICT AR status and clinical outcomes. Results: ENZA-Tx pts with PREDICT AR+ TNBC (n=56; 47%) were older (66 years vs 52 years), had a longer disease-free interval (DFI) (37 vs 20 months), more bone involvement (57% vs 24%), were more likely to have had prior ER/PR+ BC (30% vs 8%), and a longer median duration on the first-line Tx (29 vs 19 weeks[wks]) vs pts with PREDICT AR- TNBC (n=62;53%). Table 1. mPFS from ENZA-Tx pts and duration of prior Tx by PREDICT AR status and line of Tx.PREDICT AR StatusTx prior to ENZAmPFS on ENZA (wks)Median duration of prior Tx (wks)PREDICT AR+ (n=26)No prior Tx (n=10)32-- 1 prior Tx (n=16)4034PREDICT AR- (n=36)No prior Tx (n=11)8-- 1 prior Tx (n=25)1317 The prevalence of PREDICT AR+ primary TNBC from the non-ENZA-Tx dataset was 51% (n=182). DFI after neo/adjuvant therapy was not statistically different (p=0.605) between pts with PREDICT AR+ vs PREDICT AR- TNBC, and pathologic complete response rates were 23% vs 38% in PREDICT AR+ vs PREDICT AR- TNBC, respectively. Conclusion: mPFS in pts with PREDICT AR+ TNBC who received first-line ENZA was longer than first-line Tx duration in those who received prior Tx (32 vs 29 weeks). In pts with PREDICT AR+ TNBC who received second-line ENZA, mPFS was longer than the median duration of their first-line Tx (40 vs 34 weeks). This trend was not observed in pts with PREDICT AR- TNBC. Key demographic differences did not explain these outcomes, suggesting benefit from ENZA. Duration of first-line non-ENZA-Tx was shorter in pts with PREDICT AR- TNBC vs pts with PREDICT AR+ TNBC who received second-line ENZA (17 vs 34 weeks), suggesting a better prognosis in pts with PREDICT AR+ advanced TNBC; however, PREDICT AR status was not associated with DFI following neo/adjuvant treatment for primary TNBC. PREDICT AR may identify a hormonally driven subset of pts with advanced TNBC who have a better prognosis and who may benefit from ENZA. 1. Parker J et al. J Clin Oncol 2015;33(suppl): abstr 1083. 2. Traina TA et al. J Clin Oncol 2015;33(suppl): abstr 1003. 3. Hatzis C et al. JAMA 2011;305:1873-1881. Citation Format: Miller K, Krop I, Schwartzberg L, Abramson V, Garcia-Estevez L, Eakle J, Nanda R, Yardley D, Ademuyiwa F, Chan S, Crown J, Danso M, Gelmon K, Ma L, Martinez-Janez N, Gradishar W, Steinberg J, Tudor IC, Uppal H, Paton VE, Parker J, Hudis CA, Traina TA. Improved clinical outcomes on enzalutamide observed in patients with PREDICT AR+ triple-negative breast cancer: prognosis or prediction?. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P3-07-25.

Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer

Triple-negative (TN) breast cancer is an aggressive subtype of breast cancer associated with a unique set of epidemiologic and genetic risk factors. We conducted a two-stage genome-wide association study of TN breast cancer (stage 1: 1529 TN cases, 3399 controls; stage 2: 2148 cases, 1309 controls) to identify loci that influence TN breast cancer risk. Variants in the 19p13.1 and PTHLH loci showed genome-wide significant associations (P < 5 × 10(-) (8)) in stage 1 and 2 combined. Results also suggested a substantial enrichment of significantly associated variants among the single nucleotide polymorphisms (SNPs) analyzed in stage 2. Variants from 25 of 74 known breast cancer susceptibility loci were also associated with risk of TN breast cancer (P < 0.05). Associations with TN breast cancer were confirmed for 10 loci (LGR6, MDM4, CASP8, 2q35, 2p24.1, TERT-rs10069690, ESR1, TOX3, 19p13.1, RALY), and we identified associations with TN breast cancer for 15 additional breast cancer loci (P < 0.05: PEX14, 2q24.1, 2q31.1, ADAM29, EBF1, TCF7L2, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, BRCA2, RAD51L1-rs2588809, MKL1). Further, two SNPs independent of previously reported signals in ESR1 [rs12525163 odds ratio (OR) = 1.15, P = 4.9 × 10(-) (4)] and 19p13.1 (rs1864112 OR = 0.84, P = 1.8 × 10(-) (9)) were associated with TN breast cancer. A polygenic risk score (PRS) for TN breast cancer based on known breast cancer risk variants showed a 4-fold difference in risk between the highest and lowest PRS quintiles (OR = 4.03, 95% confidence interval 3.46-4.70, P = 4.8 × 10(-) (69)). This translates to an absolute risk for TN breast cancer ranging from 0.8% to 3.4%, suggesting that genetic variation may be used for TN breast cancer risk prediction.

Abstract 690: Discovery and preliminary validation of novel early detection biomarkers for triple-negative breast cancer using preclinical plasma samples from the Women's Health Initiative observational study

Abstract Background: One approach to develop new tools for detecting cancer early is through the identification and validation of blood-based cancer specific biomarkers. In applying this approach to breast cancer one potential challenge is the disease's considerable heterogeneity. Triple-negative (TN) breast cancer is a particularly lethal breast cancer subtype that is known to have a unique biology. Consequently, there is a clinical need to discover early detection biomarkers for TN disease, and such biomarkers may be more readily identifiable given the more aggressive nature and growth patterns of these tumors. Objective: To discover and initially validate novel TN breast cancer specific early detection biomarkers using preclinical plasma samples. Methods: We conducted a nested case-control study of TN breast cancer within the Women's Health Initiative (WHI) Observational Study (OS) consisting of 28 TN cases whose blood was drawn 17 months prior to their breast cancer diagnosis and an equal number of matched controls. The 28 matched sets were equally divided into a training set, used for discovery, and an independent test set, used for validation, and interrogated using a customized antibody microarray. Results: In the training set, of the 915 antibodies assessed, 55 (6.0%) were statistically significantly different between cases and controls at p&amp;lt;0.05 and in the test set 128 (14.0%) were statistically different. Of the 55 candidates identified in the training set, 15 were validated in the test set at p&amp;lt;0.05. Of these 15 candidates, 13 had higher levels in cases compared to controls. The candidates with the strongest signals included myosin-5A (log2 ratio=1.26), arfaptin-2 (log2 ratio=1.02), integrin-beta1 (log2 ratio=0.99), phosphoserine aminotransferase (log2 ratio=0.94), beta-catenin (log2 ratio=0.92), mast/stem cell growth factor receptor (log2 ratio=0.90), and IGFBP-2 (log2 ratio=−1.18). Conclusions: Several unique, novel candidate early detection biomarkers specific to TN breast cancer were discovered and initially validated in preclinical samples. These findings warrant validation in additional sets of TN cases and controls to further evaluate their potential clinical significance. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 690. doi:1538-7445.AM2012-690

A study of triple-negative breast cancer at a cancer institute in India.

e11548 Background: Triple negative breast cancer (TNBC) has been identified as an independent poor prognostic factor for survival. Data from India is lacking. The aim of this study was to compare the clinico-pathological characteristics and treatment outcomes of patients with TNBC and non-TNBC. Methods: We did a retrospective study of 636 patients with invasive breast cancer between June 2005 and July 2009 in whom estrogen receptor, progesterone receptor and Her-2Neu status were available. Event free survival (EFS) and overall survival (OS) were defined as the time period from diagnosis to occurrence of event and death respectively. Relapse, progression or metachronous breast cancer were taken as events. Chi-square/Fischer Exact test for categorical and t-test for non-categorical variables, Kaplan-Meier curves and log-rank test for survival analysis and Cox proportional hazards model for univariate and multivariate analysis were used. Results: 155(24.4%) patients had TNBC. Patients with TNBC had significantly lower median age (46.6 vs 49.8 yrs; p=0.005, 95% CI: 0.98 to 5.38) and higher proportion of high grade tumors as compared to non-TNBC group (43% vs 23.5%; p<0.0001). The proportion of premenopausal to post-menopausal women (1.2:1 vs 0.9:1; p=0.139), median tumor size (5.2 vs 5.1 cms; p=0.685,95% CI: -0.762 to 0.5), node positivity rate (61.7% vs 65.2%;p=0.5), stage distribution (2.8%, 31.8%, 47.7%, 17.7% vs 2.3%, 27.8%, 49.1%, 20.8% for Stage I, II, III and IV respectively; p=0.8) were not significantly different between TNBC and non-TNBC groups. After a median follow-up of 22 months, the 3 year EFS was significantly lower in TNBC group (60% vs 68%; log rank p=0.0362). 3 year OS was lower in TNBC group but not statistically significant (74% vs 84%; p=0.139). Age<49 yrs, higher nodal stage and larger tumor size (>5cms) but not triple negativity were significant negative prognostic factors by multivariate analysis for EFS and OS. Conclusions: TNBC is significantly associated with younger age and high grade tumors. Triple negativity was a significant poor prognostic factor by univariate analysis for EFS but not OS. This may be due to small sample size and rather short follow-up.

Abstract 1806: Efficacy of MM121 in ER+ and triple negative breast cancer studies

Abstract In women, breast cancer is among the most common cancers and the fifth most common cause of cancer deaths. Due to the heterogeneity of the disease, 10-year progression free survival can vary widely with stage and type from 98% to 10%. We present data showing that MM-121, a fully human monoclonal anti-ErbB3 antibody, is efficacious in studies of both hormone dependent (ER+) and triple negative (ER-,PR-, Low Erb2) breast cancer lines that express the molecular profile consistent with MM-121 response (co-expression of ErbB3 and HRG). Using a combination of computational and experimental approaches, ErbB3 was identified as a critical transducer of oncogenic signaling leading to the development of MM-121, a first in class anti-ErbB3 antibody. We have previously demonstrated that MM-121, when used as a single agent, inhibits heregulin-induced signaling events in human cancer cell lines. Moreover, MM-121 caused dose-dependent inhibition of tumor growth in multiple xenograft models of human cancer, including ovarian, renal cell, pancreatic, lung, and prostate cancer. Estrogen dependent, or ER+ breast cancers, make up about 80% of breast cancers. A standard treatment for ER+ breast cancer includes hormone therapy; however a substantial number of ER+ breast cancers eventually develop resistance requiring additional treatments. Here we show that in ER+ breast cancer cells, MM-121 can block HRG induced ErbB3 activation and VEGF secretion as well as HGF induced pErbB3 in vitro. Additionally, in ER+ breast cancer xenograft models, MM121 is effective in combination with both chemotherapy agents and targeted therapies and may be effective in ER+ breast cancers that are refractory to hormone treatment. The triple negative breast cancers are characterized by poor prognosis, aggressiveness, and reduced responsiveness to standard treatments. MM-121 used as a single agent therapy was able to suppress tumor growth in triple negative primary human tumors, when grown as xenografts suggesting that MM-121 monotherapy may be clinically efficacious in triple negative breast cancers. Together, these data suggest that MM-121, when used as a single agent or in combination with other therapies, could offer significant clinical benefit to both ER+ and triple negative breast cancer patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1806.