HER2 Subtype Research Articles

Analysis of the molecular subtypes of preoperative core needle biopsy and surgical specimens in invasive breast cancer.

BackgroundAccurate molecular classification of breast core needle biopsy (CNB) tissue is important for determining neoadjuvant systemic therapies for invasive breast cancer. The researchers aimed to evaluate the concordance rate (CR) of molecular subtypes between CNBs and surgical specimens.MethodsThis study was conducted with invasive breast cancer patients who underwent surgery after CNB at Seoul St. Mary’s Hospital between December 2014 and December 2017. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki67 were analyzed using immunohistochemistry. ER and PR were evaluated by Allred score (0–8). HER2 was graded from 0 to +3, and all 2+ cases were reflex tested with silver in situ hybridization. The labeling index of Ki67 was counted by either manual scoring or digital image analysis. Molecular subtypes were classified using the above surrogate markers.ResultsIn total, 629 patients were evaluated. The CRs of ER, PR, HER2, and Ki67 were 96.5% (kappa, 0.883; p<.001), 93.0% (kappa, 0.824; p<.001), 99.7% (kappa, 0.988; p<.001), and 78.7% (kappa, 0.577; p<.001), respectively. Digital image analysis of Ki67 in CNB showed better concordance with Ki67 in surgical specimens (CR, 82.3%; kappa, 0.639 for digital image analysis vs. CR, 76.2%; kappa, 0.534 for manual counting). The CRs of luminal A, luminal B, HER2, and triple negative types were 89.0%, 70.0%, 82.9%, and 77.2%, respectively. ConclusionsCNB was reasonably accurate for determining ER, PR, HER2, Ki67, and molecular subtypes. Using digital image analysis for Ki67 in CNB produced more accurate molecular classifications.

Prediction of clusters of miRNA binding sites in mRNA candidate genes of breast cancer subtypes.

The development of breast cancer (BC) subtypes is controlled by distinct sets of candidate genes, and the expression of these genes is regulated by the binding of their mRNAs with miRNAs. Predicting miRNA associations and target genes is thus essential when studying breast cancer. The MirTarget program identifies the initiation of miRNA binding to mRNA, the localization of miRNA binding sites in mRNA regions, and the free energy from the binding of all miRNA nucleotides with mRNA. Candidate gene mRNAs have clusters (miRNA binding sites with overlapping nucleotide sequences). mRNAs of EPOR, MAZ and NISCH candidate genes of the HER2 subtype have clusters, and there are four clusters in mRNAs of MAZ, BRCA2 and CDK6 genes. Candidate genes of the triple-negative subtype are targets for multiple miRNAs. There are 11 sites in CBL mRNA, five sites in MMP2 mRNA, and RAB5A mRNA contains two clusters in each of the three sites. In SFN mRNA, there are two clusters in three sites, and one cluster in 21 sites. Candidate genes of luminal A and B subtypes are targets for miRNAs: there are 21 sites in FOXA1 mRNA and 15 sites in HMGA2 mRNA. There are clusters of five sites in mRNAs of ITGB1 and SOX4 genes. Clusters of eight sites and 10 sites are identified in mRNAs of SMAD3 and TGFB1 genes, respectively. Organizing miRNA binding sites into clusters reduces the proportion of nucleotide binding sites in mRNAs. This overlapping of miRNA binding sites creates a competition among miRNAs for a binding site. From 6,272 miRNAs studied, only 29 miRNAs from miRBase and 88 novel miRNAs had binding sites in clusters of target gene mRNA in breast cancer. We propose using associations of miRNAs and their target genes as markers in breast cancer subtype diagnosis.

79P - Parkin, APEX1 and BCL2L1 tissue expression in southern Brazilian patients with different breast cancer molecular subtypes

BackgroundBreast cancer is the most commonly occurring cancer in women and is the leading cause of cancer death in women in Brazil. Despite being widely studied, it is a disease that is not yet fully understood in its complexity. On the other hand, changes in parkin (parkin RBR E3 ubiquitin protein ligase) expression patterns have been described in several diseases, including breast cancer. Nevertheless, the association of these changes with cancer prognostic and predictive factors remains unclear. Also, parkin regulates APEX1 (apurinic/apyrimidinic endodeoxyribonuclease 1), a protein crucial for repair of oxidized DNA damage, and BCL2L1 (BCL2 like 1), an apoptotic regulator. Both proteins were related to breast cancer. MethodsImmunohistochemical analysis of Parkin, APEX1 and BCL2L1expression were performed in different breast cancer ductal invasive samples from Southern Brazilian patients to characterize their patterns and explore its association with clinical features and disease outcome.Therefore, 112 samples were organized into 15 Tissue Micro Arrays. The samples were classified in four molecular subtypes based on clinicopathological criteria (46 Luminal B, 24 Luminal A, 24 Basal and 18 HER2). These samples were obtained from Hospital Nossa Senhora das Graças (Curitiba, PR, Brazil) patients who were followed from 5 to 18 years. ResultsParkin, APEX1 and BCL2L1 showed different expression patterns between the subtypes assessed. While in Luminal A and B APEX1 expression was increased, parkin expression was higher among Basal and HER2 subtypes. BCL2L1 expression was increased mainly in HER2 subtype. When regarding to estrogen (ER) and progesterone (PR) receptors, APEX1 was more expressed in ER/PR-positive samples, whereas Parkin and BCL2L1 in negative ones. No such difference was observed considering only HER2. BCL2L1 expression pattern was significantly associated with disease-free survival time independent of molecular subtypes, lymph node status and tumor size (p=0.020). The higher the expression levels of BCL2L1, the shorter the disease-free survival time. ConclusionsThe expression of BCL2L1 is direclty associated with relapse of ductal invasive breast tumors, independently of other clinical variables. Legal entity responsible for the studyPontifícia Universidade Católica do Paraná (PUCPR). FundingHas not received any funding. DisclosureAll authors have declared no conflicts of interest.

369P - Metabolic tumour volume by 18F-FDG PET/CT is an independent prognostic factor in metastatic breast cancer

BackgroundMetabolic tumor volume(MTV) measured by (18)F-fluorodeoxyglucose positron emission tomography/computed tomography(FDG PET/CT) was correlated with prognosis in various cancers. The aim of this study was to investigate the prognostic value of MTV in metastatic breast cancer (MBC). MethodsWe retrospectively reviewed 172 patients who underwent FDG PET/CT at diagnosis of MBC at a single center. MTV for the whole body tumor lesions were measured by FDG PET/CT. The prognostic significance of MTV and other clinicopathological variables for progression free survival (PFS) to the first line palliative treatment(1L-PFS) was assessed by Kaplan-Meier method and Cox proportional hazards regression analysis. ResultsMedian age was 45 years (range 27-71). 76 patients had hormone receptor-positive(HR+)/human epidermal receptor-2 negative(HER2-) disease, 55 patients had HER2+ and 41 patients had triple negative breast cancer(TNBC). In the univariate analysis, TNBC subtype and higher MTV was associated with worse 1L-PFS. On multivariate analysis adjusted for age, presence of visceral metastases, and liver involvement, indepent predictive factors associated with decreased 1L-PFS were TNBC (HR 2.724 versus HR+/HER2 subtype, p=0.002) and MTV (HR 1.165 with doubling of MTV, p=0.001). ConclusionsMTV, a volumetric parameter of FDG PET/CT, is an important independent prognostic factor for PFS to the first line palliative treatment, irrespective of tumor subtype, in patients with MBC. Legal entity responsible for the studyThe authors. FundingHas not received any funding. DisclosureY.H. Park: Advisory / Consultancy, Research grant / Funding (self): AstraZeneca; Advisory / Consultancy, Research grant / Funding (self): Pfizer; Advisory / Consultancy, Research grant / Funding (self): Eisai; Advisory / Consultancy, Research grant / Funding (self): Novartis; Research grant / Funding (self): Roche. All other authors have declared no conflicts of interest.

A clinical study on synchronous relation between ductal CA in situ and invasive ductal carcinoma of breast

Introduction: We have lot of studies regarding Ductal Carcinoma in Situ (DCIS) succeeding into Invasive Ductal Carcinoma (IDC) of the breast. Still, there is hardly any study on the coexistence of both and its clinical significance. The aim of this study is to evaluate the clinical and pathological parameters of synchronous DCIS and IDC to estimate the prognostic factors. Materials and Methods: Total 42 patients with a final diagnosis of synchronous DCIS and IDC diagnosed in 20015-18 were included in the study. Statistical analysis was done using SPSS software utilizing the appropriate analytical methods. Results: Majority of the patients in this study group presented with early breast cancer (64.3%).48% were Her2 subtype and 31% were triple negative. Grade 3 lesions were more common (57%). 81% of the IDC associated histology was Not Otherwise Specified (NOS) type. Recurrence was common in node positive disease (59.5%), those with lymphovascular emboli (59.5%) and perinodal spread (76%) on histopathological examination. Conclusion: Synchronous DCIS and IDC disease being appears to have a destructive nature compared to the course of IDC alone being. Prognostic factors linking to IDC appears to associate well with recurrence than that of the prognostic factors of DCIS module in such synchronous setting.

276P - The prognostic significance of preoperative tumour marker (CEA, CA15-3) elevation in breast cancer patients

BackgroundTumour markers are widely used for screening and monitoring cancers. CA 15-3 and CEA are FDA-approved tumour markers for monitoring breast cancer. However, the prognostic efficacy of preoperative elevation of CEA and CA15-3 levels in breast cancer remains controversial. MethodsWe retrospectively analyzed the clinicopathological parameters and preoperative serum CEA and CA 15-3 level of 149,238 patients of Korean Breast Cancer Society Registry (KBCSR) Database who underwent surgery between January 2000 and December 2015. ResultsThe patients with elevated CA 15-3/CEA level had shown more advanced T stage and N stage, ER negativity, PR negativity and HER2 positivity compared the patients with normal CA15-3/CEA levels. The patients with elevated CA 15-3/CEA level had worse OS than the patients with normal CA 15-3/CEA level. In survival analysis, both elevated group had worst prognosis compared other groups. In subgroup analysis by subtypes, in luminal A, both elevated group had hazard ratio (HR) 2.14 (95% CI 1.01-4.55), only CA 15-3 elevated had HR 2.38 (95% CI 1.58-3.58) and only CEA elevated group had HR 1.79 (95% CI, 1.20-2.68), compared normal group. In luminal B, both elevated group had HR 3.99 (95% CI 2.23-7.16), only CA 15-3 elevated had HR 2.38 (95% CI 1.58-3.58) and only CEA elevated group had HR 1.79 (95% CI, 1.20-2.68), compared normal group. In HER2 subtype group, elevated CEA level was the only independent prognostic factor. However, in TNBC, elevated preoperative CEA and CA 15-3 level were not a significant prognostic factor for OS. ConclusionsThe elevation of preoperative tumor markers was associated with aggressive characteristic and worse overall survival. Preoperative tumor markers predicted the prognosis of the patients and showed differences according to subtypes. In luminal breast cancer, the CA 15-3 elevation has higher hazard ratio than the CEA elevation and the patients with both tumor markers showed the worst prognosis. Legal entity responsible for the studyThe authors. FundingHas not received any funding. DisclosureAll authors have declared no conflicts of interest.

HER2 Expression Discordance between Ductal Carcinoma In situ and Invasive Breast Carcinoma. How to Analyze Oncotype DX

Although histologically invasive breast carcinomas can be of no special subtype (ductal) or of special subtypes (as lobular carcinoma), based on their immunohistochemical and molecular features, they are subclassified in four different groups: luminal A, luminal B (with and without HER2 overexpression), HER2 subtype and triple negative. They vary in their gene expression signature, biological potential and clinical course. Luminal A subtype is considered to have a better prognosis and most are treated with hormone therapy alone after surgery because they express hormone receptors and show a low proliferation index. Oncotype DX (ODX) is a molecular score assay that estimates recurrence risk for early-stage hormone receptor-positive, human epidermal growth factor receptor 2 (HER2) negative breast cancer. It can predict which tumours may benefit from adjuvant chemotherapy. It has been reported that occasionally a breast carcinoma can have immunohistochemical and molecular differences between the in situ and the invasive components. We report one case that may lead us to misinterpret ODX results, where the in situ ductal component amplified HER2 gene while invasive component did not. Therefore, carefulness must be taken when evaluating ODX results, and be sure that we are evaluating the invasive component.

Tumor Heterogeneity Regarding Radiosensitivity, Recurrence Risk, and Immune-Checkpoint in Breast Cancer: Transcriptome Analysis of Single-cell RNA Sequencing Data

Tumor heterogeneity has been recently revealed in an advent of single-cell RNA sequencing. In this study, we investigate the heterogeneity of intrinsic tumor radiosensitivity, recurrence risk, and immune checkpoint in breast cancer patients. We investigated single-cell mRNA sequencing data from GEO database (GSE75688). Subtypes of each tumor cell were classified by using PAM50 gene signature. OncoType DX and Endopredict gene signatures were used to estimate enrichment score and to assess the recurrence risk for each cell. Gene Set Variation Analysis (GSVA) were performed across cells using radiosensitivity gene signatures including both RSI (Radiosensitivity Index) and 31-gene. Computational approach facilitated to identify intercellular communication between tumor and immune cells using the database of immune checkpoint ligand-receptor gene pairs. GSVA analysis showed that mean recurrence risk score of cells were different according to PAM50 breast cancer subtype, and cells were classified as basal subtype demonstrated higher risk recurrence score compared to those of other subtypes (P<0.001). Heterogeneity of recurrence risk was observed more frequently in luminal A subtype compared to basal/HER2 positive subtypes. Radioresistant tumor cells, representing high enrichment score of RSI, were more commonly found in basal type compared to those of other subtypes (P=0.029). RSI score was varied among cells from patient to patient, indicating the heterogeneity of intrinsic tumor radiosensitivity. There were significant correlations in a single cell resolution between RSI and 31-gene radiosensitivity (Pearson's r=0.25), between RSI and Endopredict risk score (r=0.26), and between OncoType DX and Endopredict enrichment scores (r=0.61), respectively. Most of the PD-L1 expressed cells were classified into high-risk recurrence group (92.8 % for Endopredict and 100% for OncoTypeDX). Network plot showed the increased number of immune-checkpoint ligand-receptor interactions between tumor and immune cells in patients with basal or HER2 type compared to luminal subtype. Compared to patients with luminal subtype, PD-L1 ligand-receptor interactions between tumor and T-cells were differentially increased in patients with HER2 subtype, and CTLA-4 ligand-receptor interactions in patients with basal subtype. Most radioresistant tumor cells showed basal subtype or PD-L1 expression. PD-L1 expressed cells were enriched in the high-risk or basal/HER2/luminal B subtype. The different pattern of cross-talk between tumor and immune cells were associated with molecular subtype. Our results demonstrated the heterogeneity of intrinsic tumor radiosensitivity, recurrence risks, and cross-talk in a single cell level in breast cancer patients.

Quantifying Risk Pathway Crosstalk Mediated by miRNA to Screen Precision drugs for Breast Cancer Patients.

Breast cancer has become the most common cancer that leads to women’s death. Breast cancer is a complex, highly heterogeneous disease classified into various subtypes based on histological features, which determines the therapeutic options. System identification of effective drugs for each subtype remains challenging. In this work, we present a computational network biology approach to screen precision drugs for different breast cancer subtypes by considering the impact intensity of candidate drugs on the pathway crosstalk mediated by miRNAs. Firstly, we constructed and analyzed the subtype-specific risk pathway crosstalk networks mediated by miRNAs. Then, we evaluated 36 Food and Drug Administration (FDA)-approved anticancer drugs by quantifying their effects on these subtype-specific pathway crosstalk networks and combining with survival analysis. Finally, some first-line treatments of breast cancer, such as Paclitaxel and Vincristine, were optimized for each subtype. In particular, we performed precision screening of subtype-specific therapeutic drugs and also confirmed some novel drugs suitable for breast cancer treatment. For example, Sorafenib was applicable for the basal subtype treatment, Irinotecan was optimum for Her2 subtype treatment, Vemurafenib was suitable for the LumA subtype treatment, and Vorinostat could apply to LumB subtype treatment. In addition, the mechanism of these optimal therapeutic drugs in each subtype of breast cancer was further dissected. In summary, our study offers an effective way to screen precision drugs for various breast cancer subtype treatments. We also dissected the mechanism of optimal therapeutic drugs, which may provide novel insight into the precise treatment of cancer and promote researches on the mechanisms of action of drugs.

The prognostic significance of preoperative tumor marker (CEA, CA15-3) elevation in breast cancer patients: data from the Korean Breast Cancer Society Registry.

Tumor markers such as carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) are widely used for monitoring breast cancer. However, the prognostic efficacy of preoperative elevations of CEA and CA15-3 levels in breast cancer patients remains controversial. We retrospectively analyzed the clinicopathological parameters of 149,238 patients in the Korean Breast Cancer Society Registry Database who underwent surgery between January 2000 and December 2015. The patients with elevated CA15-3/CEA levels had worse overall survival (OS) than the patients with normal CA15-3/CEA levels. For the luminal A subtype, the CA15-3- and CEA-elevated group had a hazard ratio (HR) of 2.14 (95% CI 1.01-4.55). The CA15-3-elevated group had an HR of 2.38 (95% CI 1.58-3.58) and the CEA-elevated group had an HR of 1.79 (95% CI 1.20-2.68) compared to the normal group. For the luminal B subtype, the CA15-3- and CEA-elevated group had an HR of 3.99 (95% CI 2.23-7.16), whereas the CA15-3-elevated group had an HR of 2.38 (95% CI 1.58-3.58) and the CEA-elevated group had an HR of 1.79 (95% CI 1.20-2.68). For the HER2 subtype, elevated CEA level was the only independent prognostic factor. However, for the triple-negative breast cancer (TNBC) subtype, elevated preoperative CEA and CA15-3 levels were not significant prognostic factors for OS. Preoperative CEA and CA15-3 levels showed varying prognostic ability according to breast cancer subtype. Preoperative CA15-3 and CEA elevation are significant prognostic factors for luminal breast cancer, but they were not significant factors for TNBC.

Abstract 4700: Quantification of intratumoral heterogeneity in individual luminal A breast cancers from whole transcriptome data through semi-supervised learning

Abstract Introduction PAM50 gene profiling assigns individual breast cancers (BCas) to one of five intrinsic subtypes. However, individual tumors vary in their adherence to the assigned subtype, and a subset of these may show admixture with another subtype. We developed a novel metric to quantify this intratumoral heterogeneity using whole transcriptome expression data of individual BCas and studied specific pairwise admixtures for Luminal A (LumA) cases. Methods We obtained whole transcriptome expression data and PAM50 labels of 1081 and 1980 BCa cases from TCGA and METABRIC cohorts, respectively. We combined the two datasets, by identifying a common gene set. METABRIC data was pre-processed to normalize and log-transform expression levels and remove batch effects. For each case, the combined cohort had expression data of 11,379 genes, and probabilities of its adherence to each of the four major subtypes were computed using semi-supervised non-negative matrix factorization. The four probabilities obtained for each case were then combined using the proposed Aggregated Differential Sum (ADS) metric. For each subtype, the cases were subsequently stratified into pure, neither and admixed categories by computing ADS tertiles. For every case, we did comparative analysis of the ADS terms to identify the specific alternate molecular subtype for pairwise admixture analysis. Results Using the proposed ADS criteria, pure and admixed LumA cases spanned tertile 1 (T1) and 3 (T3), respectively. Compared to admixed cases, pure LumA cases were younger and had favorable clinical characteristics including a surrogate LumA profile (ER/PR+ and HER2-), smaller tumor size, lower stage, less prevalence of TP53 mutations, and high likelihood of PIK3CA and CBFB mutations. Kaplan-Meier curves and Cox proportional hazard analysis showed that the admixed cases had worse overall survival and higher mortality risk compared to their pure counterparts. Pairwise admixture analysis revealed that 59% (n=226), 27% (103) and 15% (55) LumA cases in T3 were admixed with Luminal B, Basal and HER2 subtype, respectively. LumA cases admixed with HER2 showed worst tumor characteristics, survival outcomes and highest mortality risk followed by, in order, the admixture with Luminal B and Basal subtypes. Conclusion Our results demonstrate that stratification of LumA BCas by subtype purity using ADS identifies the admixed cases which usually have worse tumor characteristics and survival outcomes. LumA cases were predominantly admixed with Luminal B subtype followed by Basal and HER2 subtypes. Eventually, we will use the pure cases to train computer vision classifiers for morphological identification of subtype admixture in routine H&amp;E images. This would be a cost-effective complement to molecular subtyping that could take advantage of the spatial information available in whole slide images. Citation Format: Neeraj Kumar, Yash Dharmamer, Amit Sethi, Peter Gann. Quantification of intratumoral heterogeneity in individual luminal A breast cancers from whole transcriptome data through semi-supervised learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4700.

Relation of AURKB over-expression to low survival rate in BCRA and reversine-modulated aurora B kinase in breast cancer cell lines

BackgroundNew therapeutic drug for breast cancer (BRCA), especially triple negative BRCA (TNBC), is urgently needed. Even though 2-(4-morpholinoanilino)-6-cyclohexylaminopurine (reversine) is an aurora kinase inhibitor, it also inhibits some cancer cells and human BRCA cells. However, the potential roles of reversine as a novel therapeutic agent for the treatment of BRCA remains unknown and must be further investigation. Thus, the relationship of reversine to aurora kinase in BCRA has not been reported. The relationship between AURKB and survival rate in BRCA has never been reported. Herein, we tested the roles of reversine on different BRCA cell line subtypes. We also investigated the relationship between AURKB and survival rate in BRCA as well as reversine to Aurora kinase expression in BCRA cell lines, including TNBC subtype, 4T1, MDA-MB-231, and luminal subtype MCF-7.MethodsCell viability and apoptosis were detected using Cell Counting Kit-8 and flow cytometry analysis, respectively. Apoptotic and tumor-related proteins were tested using Western blot analysis. Important microRNAs that regulate BRCA were analyzed using RT-PCR. UALCAN public databases were used to analyze the targeted gene profiles, and the PROGgeneV2 database was used to study the prognostic implications of genes.ResultsReversine inhibits cell proliferation and induces cell apoptosis by modulating caspase-3 and bax/bcl-2 among the three cell lines. Data from the UALCAN public database show that BRCA tissues expressed high gene levels of AURKB, TIMP1, MMP9, and TGFB1 compared with the normal tissue. Among the over-expressed genes in BRCA, AURKB ranks 9th in TNBC, 49th in luminal subtype, and 48th in HER2 subtype. High AURKB level in BRCA is highly related to the low survival rate in patients displayed in 18 databases searched via PROGgeneV2. The protein levels of aurora B kinase (Aurora B), which is encoded by AURKB gene, are highly suppressed by reversine in the three cell lines. The tumor-related proteins TGF-β1, TIMP1, and MMP9 are partially suppressed by reversine but with different sensitivity in the three cell lines. The reversine-affected microRNAs, such as miR129-5p, miR-199a-3p, and miR-3960, in MDA-MB-231 cell line might be the research targets in TNBC regulation.ConclusionsIn BRCA, the level of AURKB are over-expressed and is related to low survival rate. Reversine contributes to anti-growth effect in BRCA cell lines, especially for TNBC, by modulating the aurora B. However, the invasiveness, metastasis, and anti-tumor effects of reversine in vivo and in vitro must be further investigated.

Molecular characteristics of breast cancer according to clinicopathological factors.

The purpose of the present study was to evaluate the correlation between molecular factors such as BRCA1 DNA repair associated (BRCA1), checkpoint kinase 2 (CHEK2) and nucleotide binding oligomerization domain containing 2 (NOD2) gene mutations and clinicopathological factors in patients with breast cancer (BC). Prognostic factors were analyzed in BC patients with confirmed BRCA1 (n=73), CHEK2 (n=51) and NOD2 (n=31) mutations. The control group was selected from BC patients without mutations (n=392). The BRCA-associated cancer cases were significantly more often triple negative compared with sporadic cancer (62% vs. 14%; P=0.0001). Luminal B HER2-positive and HER2-positive non-luminal subtypes were observed more often in the control group (33 and 17%). The luminal A subtype was detected in 53% of CHEK2 mutation carriers and 45% of NOD2 mutation carriers. A lower histological grade was observed significantly more often in patients with CHEK2 mutations in comparison with the control group (88 vs. 69%; P=0.003). Lymph nodes without metastases were reported more frequently in NOD2 mutation carriers (74 vs. 54%; P=0.038), in BRCA1 mutations (73 vs. 54%; P=0.004) and, although not significantly, in CHEK2 mutation carriers (69 vs. 54%; P=0.071) compared with the control group. In conclusion, BRCA1 mutation was associated with TNBC and the luminal B HER2 (-) subtype. HER2-positive subtypes were characteristic of the control group. CHEK2 and NOD2 mutation carriers had a more favorable profile of prognostic factors.

Omega-3 fatty acids and ERPR(-) and HER2/neu(+/-) breast cancer prevention.

TPS1589 Background: The most aggressive breast cancer subtypes tend to be estrogen and progesterone receptor negative (ERPR(-)) and human epidermal growth factor receptor type 2 positive (HER2(+)). Women with these breast cancer subtypes (triple negative, ERPR(-)HER2(+)) tend to experience worse clinical outcomes and have a relatively higher risk of recurrence. Our previous research demonstrated that dietary omega-3 (n-3) fatty acids can significantly inhibit ERPR(-) HER2(+) tumorigenesis in MMTV-HER2/neu transgenic mice fed fish oil vs corn oil-based diets. The fish oil diet group developed 30% fewer breast tumors, had lower Ki67 expression, and experienced less mammary atypia relative to the corn oil diet group. Other studies involving diet, nutrition and breast cancer point to the potentially protective effect of an anti-inflammatory diet on the risk of developing ER(-) and HER2(+) breast cancer, further supporting the evidence that the ERPR(-), HER2(±) subtypes may be highly responsive to this bioactive nutrient. Methods: This is a double-blinded, randomized clinical trial of high dose (~5.4 g EPA+DHA) vs low dose (~0.9 g EPA+DHA in fatty acid mix of the typical American diet) of n-3 fatty acids in breast cancer survivors of ERPR(-), HER2(±) breast cancer. Eligible participants will take 5 capsules/day for 12 months, with cellular samples of breast epithelial and/or adipose tissue obtained by fine needle aspirations of the contralateral breast. The study aims to determine whether n-3 fatty acid supplementation will modify fatty acid metabolite content in breast adipose tissue, modulate cytomorphology and/or cell proliferation in breast epithelial cells, affect DNA methylation patterns, and modulate pro- vs anti-inflammatory gene expression patterns in breast adipose tissue. Correlative aims will evaluate possible associations between factors such as breast adipose tissue, red cell membrane fatty acid profiles, BMI, and reported dietary intake. Sample size of 40 participants per arm was calculated to provide at least 80% power to detect a statistically significant difference for each primary endpoint. This study focuses on women survivors of high risk breast cancer subtypes, specifically triple negative or ERPR(-)HER2(+) disease, who are currently without long term adjuvant options. Eligibility criteria include prior diagnosis of ERPR(-) stage 0 to III breast cancer, ≤5 years from completion of standard therapy.The study was closed to accrual in November 2018; less than 9 months of follow-up remain for active study participants. Clinical trial information: NCT02295059.

A Bayesian two-way latent structure model for genomic data integration reveals few pan-genomic cluster subtypes in a breast cancer cohort.

Unsupervised clustering is important in disease subtyping, among having other genomic applications. As genomic data has become more multifaceted, how to cluster across data sources for more precise subtyping is an ever more important area of research. Many of the methods proposed so far, including iCluster and Cluster of Cluster Assignments (COCAs), make an unreasonable assumption of a common clustering across all data sources, and those that do not are fewer and tend to be computationally intensive. We propose a Bayesian parametric model for integrative, unsupervised clustering across data sources. In our two-way latent structure model, samples are clustered in relation to each specific data source, distinguishing it from methods like COCAs and iCluster, but cluster labels have across-dataset meaning, allowing cluster information to be shared between data sources. A common scaling across data sources is not required, and inference is obtained by a Gibbs Sampler, which we improve with a warm start strategy and modified density functions to robustify and speed convergence. Posterior interpretation allows for inference on common clusterings occurring among subsets of data sources. An interesting statistical formulation of the model results in sampling from closed-form posteriors despite incorporation of a complex latent structure. We fit the model with Gaussian and more general densities, which influences the degree of across-dataset cluster label sharing. Uniquely among integrative clustering models, our formulation makes no nestedness assumptions of samples across data sources so that a sample missing data from one genomic source can be clustered according to its existing data sources. We apply our model to a Norwegian breast cancer cohort of ductal carcinoma in situ and invasive tumors, comprised of somatic copy-number alteration, methylation and expression datasets. We find enrichment in the Her2 subtype and ductal carcinoma among those observations exhibiting greater cluster correspondence across expression and CNA data. In general, there are few pan-genomic clusterings, suggesting that models assuming a common clustering across genomic data sources might yield misleading results. The model is implemented in an R package called twl ('two-way latent'), available on CRAN. Data for analysis are available within the R package. Supplementary data are available at Bioinformatics online.

Gene Expression and miRNAs Profiling: Function and Regulation in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Breast Cancer.

Breast cancer is the second most common cause of cancer-related deaths among women worldwide. It is a heterogeneous disease with four major molecular subtypes. One of the subtypes, human epidermal growth factor receptor 2 (HER2)-enriched (HER2-positive) is characterized by the absence of estrogen and progesterone receptors and overexpression of HER2 receptor, and accounts for 15–20% of all breast cancers. Despite the anti-HER2 and cytotoxic chemotherapy, HER2 subtype is an aggressive disease with significant mortality. Recent advances in molecular biology techniques, including gene expression profiling, proteomics, and microRNA analysis, have been extensively used to explore the underlying mechanisms behind human breast carcinogenesis and metastasis including HER2-positive breast cancer, paving the way for developing new targeted therapies. This review focuses on recent advances on gene expression and miRNA status in HER2-positive breast cancer.

The Effect of the Leptin and Leptin Receptor Expression on the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.

BackgroundThe purpose of the present study was to evaluate the effect of leptin and leptin receptor (LEPR) expression on the efficacy of neoadjuvant chemotherapy in breast cancer.Material/MethodsThere were 325 breast cancer patients with complete data enrolled in this study. Patients were categorized into 3 groups: pathological complete response group, non-pathological complete response group, and progressive disease group. Immunohistochemistry was performed to determine leptin and its receptor LEPR expression levels that were compared among the 3 groups.ResultsCompared with the non-pathological complete response group, patients in the pathological complete response group had increased leptin and LEPR expression, although the difference was not statistically significant (P=0.194, P=0.110). In addition, the expression of leptin and LEPR in the pathological complete response group was also higher than that in the progressive disease group, and the difference of LEPR expression was statistically significant (P=0.008) while the leptin expression was not (P=0.065). There were more HER2+ breast cancer patients in the pathological complete response group categorized into strong positive, and positive expression of leptin and LEPR compared with the progressive disease group (P<0.05). There were significant differences of leptin and LEPR expression among breast cancer patients under different molecular subtypes HER2+, HR+, and triple negative, in which the triple negative patients had the highest expression of leptin and LEPR. In addition, patients in the progressive disease group had high and low expression of leptin and LEPR: 13.25% versus 11.32% and 13.1% versus 10.42% respectively.ConclusionsOverexpression of leptin and LEPR improved the therapeutic efficacy of neoadjuvant chemotherapy for patients with breast cancer, especially for those with HER2+ subtype. Overexpression of leptin and LEPR was distinct among the different molecular subtypes of breast cancer, suggesting a certain predictive value for breast cancer prognosis.

Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for HER2 (ERBB2)–Positive Breast Cancer

There has been significant recent interest in understanding the utility of quantitative imaging to delineate breast cancer intrinsic biological factors and therapeutic response. No clinically accepted biomarkers are as yet available for estimation of response to human epidermal growth factor receptor 2 (currently known as ERBB2, but referred to as HER2 in this study)-targeted therapy in breast cancer. To determine whether imaging signatures on clinical breast magnetic resonance imaging (MRI) could noninvasively characterize HER2-positive tumor biological factors and estimate response to HER2-targeted neoadjuvant therapy. In a retrospective diagnostic study encompassing 209 patients with breast cancer, textural imaging features extracted within the tumor and annular peritumoral tissue regions on MRI were examined as a means to identify increasingly granular breast cancer subgroups relevant to therapeutic approach and response. First, among a cohort of 117 patients who received an MRI prior to neoadjuvant chemotherapy (NAC) at a single institution from April 27, 2012, through September 4, 2015, imaging features that distinguished HER2+ tumors from other receptor subtypes were identified. Next, among a cohort of 42 patients with HER2+ breast cancers with available MRI and RNaseq data accumulated from a multicenter, preoperative clinical trial (BrUOG 211B), a signature of the response-associated HER2-enriched (HER2-E) molecular subtype within HER2+ tumors (n = 42) was identified. The association of this signature with pathologic complete response was explored in 2 patient cohorts from different institutions, where all patients received HER2-targeted NAC (n = 28, n = 50). Finally, the association between significant peritumoral features and lymphocyte distribution was explored in patients within the BrUOG 211B trial who had corresponding biopsy hematoxylin-eosin-stained slide images. Data analysis was conducted from January 15, 2017, to February 14, 2019. Evaluation of imaging signatures by the area under the receiver operating characteristic curve (AUC) in identifying HER2+ molecular subtypes and distinguishing pathologic complete response (ypT0/is) to NAC with HER2-targeting. In the 209 patients included (mean [SD] age, 51.1 [11.7] years), features from the peritumoral regions better discriminated HER2-E tumors (maximum AUC, 0.85; 95% CI, 0.79-0.90; 9-12 mm from the tumor) compared with intratumoral features (AUC, 0.76; 95% CI, 0.69-0.84). A classifier combining peritumoral and intratumoral features identified the HER2-E subtype (AUC, 0.89; 95% CI, 0.84-0.93) and was significantly associated with response to HER2-targeted therapy in both validation cohorts (AUC, 0.80; 95% CI, 0.61-0.98 and AUC, 0.69; 95% CI, 0.53-0.84). Features from the 0- to 3-mm peritumoral region were significantly associated with the density of tumor-infiltrating lymphocytes (R2 = 0.57; 95% CI, 0.39-0.75; P = .002). A combination of peritumoral and intratumoral characteristics appears to identify intrinsic molecular subtypes of HER2+ breast cancers from imaging, offering insights into immune response within the peritumoral environment and suggesting potential benefit for treatment guidance.

The PD-1/PD-L1 Axis in HER2+ Ductal Carcinoma In Situ (DCIS) of the Breast.

The aims were to evaluate the programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) axis in ductal carcinoma in situ (DCIS) of the breast. We reviewed 85 pure DCIS cases treated with surgical excision at our institution, including 51 luminal A (estrogen receptor [ER] positive/human epidermal growth factor 2 [HER2] negative), 15 luminal B (ER+/HER2+), 13 HER2 (ER-/HER2+), and six basal-like (ER-/HER2-/CK5/6+). The extent and intensity of PD-1 and PD-L1 immunohistochemical staining in the tumor-infiltrating lymphocytes (TILs) and in the tumor cells were recorded. Our study found that moderate/severe inflammation around DCIS correlated with HER2 expression (20/28 HER2+ cases [71%] vs 21/57 HER2- cases [37%], P = .005). Of interest, over half of the TILs around the HER2 subtype expressed PD-L1 (7/13, 54%). In addition, about one-third of TILs around the HER2 subtype expressed PD-1 (4/13, 31%). These findings suggest that immune-based therapeutic strategies may be used as a potential therapy in DCIS cases with PD-L1 overexpression, especially those of the HER2 molecular subtype.

Role of programmed cell death ligand-1 expression on prognostic and overall survival of breast cancer: A systematic review and meta-analysis.

Recently, the correlation of immunological checkpoint marker programmed cell death ligand-1 (PD-L1) and the prognosis of various cancers has been a research hotspot. The aim of this study is to examine the prognostic effect of PD-L1 in breast cancer. PubMed, EMBASE, Web of Science, the Cochrane Library database were searched for eligible studies and additional hand-searching were reviewed as an augmentation. Pooled hazard ratios (HR) and 95% confidence interval (CI) for overall survival (OS), cancer-specific survival (CSS), disease-free survival (DFS)/recurrence-free survival (RFS), and metastasis-free survival (MFS) were estimated using fixed- or random-effect models. Data from 19 studies involving 12,505 patients were collected. Study quality was assessed according to guidelines for assessing quality in prognostic studies. PD-L1 expression was significantly associated with lymph node metastasis (P < .001), high tumor grade (P < .001), negative hormone receptor (P < .001), human epidermal growth factor receptor 2 (HER2) positivity (P < .001), high Ki67 (P < .001), and high tumor-infiltrating lymphocytes (TILs) (P < .001). PD-L1 expression had no significant impact on CSS (pooled HR 0.83, 95% CI = 0.64-1.09, P = .19) or MFS (pooled HR 1.11, 95% CI = 0.62-1.97, P = .72), but significantly correlated with shortened OS (pooled HR 1.52, 95% CI = 1.14-2.03, P = .004) and DFS (pooled HR 1.31, 95% CI = 1.14-1.51, P < .000). Subgroup analysis showed that not PD-L1 RNA expression, but protein expression was associated with shorter survival, in addition, the adverse prognostic effect of PD-L1 expression remained in luminal A, luminal B, and HER2 subtype, not in basal-like or triple-negative subtype. An elevated PD-L1 expression significantly correlates with high-risk prognostic indicators and decreased survival in patients with breast cancer.