ER-negative Breast Cancer Patients Research Articles

CD10 expression as a potential predictor of pathological complete response in ER-negative and triple-negative breast cancer patients treated with anthracycline-based neoadjuvant chemotherapy

BackgroundNeoadjuvant chemotherapy (NCT) can induce a pathological complete response (pCR) in breast cancer patients, leading to improved outcomes. However, predicting which patients will achieve pCR remains a challenge. CD10, a myoepithelial marker, has shown diagnostic and prognostic value in metastatic tumors. Its potential as a predictor of chemosensitivity to anthracycline-based NCT in breast cancer is unknown. AimThis retrospective study aimed to investigate the potential of CD10 cancer cell expression as a predictive marker of chemosensitivity in breast cancers treated with anthracycline-based neoadjuvant chemotherapy. MethodsWe analyzed 130 patients with invasive ductal carcinoma who received anthracycline-based NCT. CD10 expression was assessed by immunohistochemistry on pre-treatment biopsies. Statistical analysis evaluated the association between CD10 expression and pCR rates. ResultsUnivariate analysis revealed that ER-positive and CD10-negative tumors had lower pCR rates [OR 7.4830 (95% CI 2.7762–20.1699); p = 0.0001]. Multivariate analysis confirmed ER status as a strong predictor of poor response [OR 0.085 (95% CI 0.024–0.30); p < 0.001] and CD10 expression as a predictor of a favourable response [OR 0.11 (0.8–0.19); p = 0.049]. CD10 expression significantly predicted pCR in ER-negative cases [OR 0.1098 (0.0268–0.4503); p = 0.0022] and triple-negative breast cancer [OR 0.0966 (95% CI 0.0270–0.3462); p = 0.0003]. Concordance was observed between core biopsies and excised samples. ConclusionPositive CD10 cancer cell expression may predict increased response to anthracycline-based neoadjuvant chemotherapy in ER-negative and triple-negative breast cancer cases. Further research is needed to validate these findings in larger cohorts and determine the clinical utility of CD10 as a predictive marker.

Immunolocalization of Cytoplasmic ER in ER-negative Breast Carcinoma as a Potent Favorable Prognostic Predictor.

It is known that estrogen receptor (ER) has extranuclear signaling functions in addition to classical genomic pathway, and estrogenic actions have been reported in ER-negative breast carcinoma cells. However, significance of cytoplasmic-ER immunoreactivity has not been reported in ER-negative breast carcinoma tissues. We immunolocalized cytoplasmic ER in 155 ER-negative breast carcinoma tissues and evaluated its clinicopathological significance including the prognosis. As a comparative cohort set, we also used 142 ER-positive breast carcinomas. Cytoplasmic-ER immunoreactivity was detected in the carcinoma cells, but not in the non-neoplastic mammary epithelium. Cytoplasmic-ER immunoreactivity was positive in the 35 out of 155 (23%) ER-negative breast carcinoma cases, whereas it was detected only in 2 out of 142 (1.4%) ER-positive cases. Cytoplasmic ER status was positively associated with cytoplasmic-PR status, but inversely associated with Ki67 labeling index or distant free-relapse survival rate. Moreover, cytoplasmic-ER status turned out to be an independent good prognostic factor for both distant relapse-free survival and breast cancer specific survival. These findings suggested that cytoplasmic ER plays important roles in the ER-negative breast carcinoma, and cytoplasmic ER is a potent good prognostic factor. Among the ER-negative breast cancer patients, clinical benefit of chemotherapy may be limited in the cytoplasmic-ER positive cases.

Breast cancer patients are at increased risk of developing uterine serous cancer: Implications for counseling - SEER analysis (402)

<b>Objectives:</b> Several studies have investigated whether patients with prior breast cancer (BC) are at increased risk for endometrial cancer/uterine serous cancer (USC). We aimed to study the relationship between previous BC and uterine serous carcinoma (USC) and analyze the effect of prior BC on the incidence and prognosis of USC patients. <b>Methods:</b> With permission of the Surveillance, Epidemiology and End Results (SEER) program of the United States National Cancer Institute, clinical-pathologic information of women diagnosed with BC and following USC were analyzed. The recorded data included age at diagnosis, stage of disease, cause of death, interval time between BC and USC diagnosis, and overall survival. Further analysis was performed according to estrogen receptor status. <b>Results:</b> The SEER database included 10021 patients with USC during the years 1975-2015. Among the patients, 698 (6.96%) had been previously diagnosed with breast cancer (BC). The incidence of USC in patients with BC history was 57 times higher than in women without BC history (p value < 0.001). The incidence of USC did not differ between ER positive and ER negative BC patients (p. value 0.94). The mean survival of USC patients with previous BC history was eight years (96 months, 95% CI: 85.7-106.2), while for USC patients with no BC history the mean survival was 10.6 years (127 months, 95% CI: 124.0-130.8), suggesting a superior survival rate for USC patients with no history of BC (p. value=0.002). Fig. 1 <b>Conclusions:</b> Our results highlight the relationship between BC and USC, suggesting an increased risk for USC among BC patients. This clinical association should be introduced to BC patients, and physicians should be alert to any EC presenting symptom in BC survivors.

Breast Cancer Patients Are at Increased Risk of Developing Uterine Serous Cancer: Implications for Counseling – A SEER Analysis

Introduction: Several studies have investigated whether patients with prior breast cancer (BC) are at an increased risk for endometrial cancer (EC)/uterine serous cancer (USC). We aimed to study this relationship and analyze the effect of prior BC on the incidence and prognosis of USC patients. Methods: With permission of the Surveillance, Epidemiology, and End Results (SEER) program of the US National Cancer Institute, clinicopathological information of women diagnosed with BC and following USC were analyzed. The recorded data included age at diagnosis, stage of disease, cause of death, interval time between BC and USC diagnosis, and overall survival. Results: The SEER database included 10,021 patients with USC during the years 1975–2015. 698 (6.96%) of these patients had been previously diagnosed with BC. The incidence of USC in patients with BC history was 57 times higher than in women without BC history (p value <0.001). The incidence of USC did not differ between estrogen receptor (ER)-positive and ER-negative BC patients (p value 0.94). The mean survival of USC patients with previous BC history was 8 years (96 months, 95% CI: 85.7–106.2), shorter than in USC patients with no BC history, presenting a mean survival of 10.6 years (127 months, 95% CI: 124.0–130.8) (p value = 0.002). Conclusion: Our results highlight the relationship between BC and USC, suggesting an increased risk for USC among BC patients. This clinical association should be introduced to BC patients, and physicians should be alert to any EC presenting symptom in BC survivors.

Impact of Diabetes on Patient Outcomes in Breast Cancer Patients

Background: Diabetes and the etiology of breast cancer are clearly associated. However, the impact of diabetes on prognosis is not yet understood. Therefore, we conducted a retrospective cohort study to examine the relationship between diabetes and patient outcomes in breast cancer patients. Methods: We investigated 332 Japanese women with breast cancer who underwent curative surgery at our hospital. Patients without sufficient clinical information including hemoglobin A1c (HbA1c) and those with an observation period of less than 1 year were excluded. Results: Among the patients examined, 106 had diabetes at the time of their breast cancer diagnosis. Among the 296 patients with invasive breast carcinoma, 36 patients developed distant metastases during the mean observation period of 45 months. Sixteen patients died due to breast cancer, while 13 died of other causes. Multivariate analysis revealed that diabetes, tumor size, and estrogen receptor (ER) status were independent factors related to distant metastasis-free survival (DMFS) (p = 0.038, p < 0.001, and p = 0.006, respectively). Kaplan-Meier curve analysis revealed that diabetes negatively affected the outcomes of ER-negative breast cancer patients both in DMFS and overall survival (p = 0.045 and p = 0.029, respectively). Meanwhile, patient outcomes did not differ according to the level of HbA1c in diabetes patients. Conclusion: Patients with diabetes had a significantly shorter DMFS, and the negative effect of diabetes on patient outcomes was more evident in ER-negative breast cancer. Our data indicates the importance of primary prevention of diabetes for breast cancer patients.

Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic and Neoadjuvant Chemotherapy Relevant Signatures.

Immune response which involves distinct immune cells is associated with prognosis of breast cancer. Nonetheless, less study have determined the associations of different types of immune cells with patient survival and treatment response. In this study, A total of 1,502 estrogen receptor(ER)-negative breast cancers from public databases were used to infer the proportions of 22 subsets of immune cells. Another 320 ER-negative breast cancer patients from Guangdong Provincial People’s Hospital were also included and divided into the testing and validation cohorts. CD8+ T cells, CD4+ T cells, B cells, and M1 macrophages were associated with favourable outcome (all p <0.01), whereas Treg cells were strongly associated with poor outcome (p = 0.005). Using the LASSO model, we classified patients into the stromal immunotype A and B subgroups according to immunoscores. The 10 years OS and DFS rates were significantly higher in the immunotype A subgroup than immunotype B subgroup. Stromal immunotype was identified as an independent prognostic indicator in multivariate analysis in all cohorts and was also related to pathological complete response(pCR) after neoadjuvant chemotherapy. The nomogram that integrated the immunotype and clinicopathologic features showed good predictive accuracy for pCR and discriminatory power. The stromal immunotype A subgroup had higher expression levels of immune checkpoint molecules (PD-L1, PD-1, and CTLA-4) and cytokines (IL-2, INF-γ, and TGF-β). In addition, patients with immunotype A and B diseases had distinct mutation signatures. Therefore, The stromal immunotypes could predict survival and responses of ER-negative breast cancer patients to neoadjuvant chemotherapy.

Functional Characterization of the Orphan Nuclear Receptor TLX in Triple Negative Breast Cancer

Abstract Despite the development of various therapeutic strategies, breast cancer persists as the second leading cause of cancer-related death among women in the United States. While endocrine modulation and monoclonal antibody therapy have proved to be indispensable modes of intervention for hormone receptor (HR)-positive and HER-2 positive patients, the triple negative breast cancer (TNBC) patient population do not respond to these therapies. As TNBC is considered one of the most challenging subtypes of breast cancer to treat, there is a significant need for the development of targeted therapeutics. Due to their well-known amenability to small-molecule modulation, we investigated whether any nuclear receptors beyond those that are traditionally studied in breast cancer (e.g. ER, PR, and AR), may represent a novel target in the TNBC patient population. Analysis of clinical data revealed that expression of the orphan nuclear receptor TLX (NR2E1) was positively correlated with relapse-free survival, distant metastasis-free survival, and overall survival in both ER-negative and basal-like breast cancer patients. Therefore, we hypothesized that TLX could influence the pathophysiology of TNBC. To interrogate this hypothesis, we established TNBC cells with stable expression of TLX in order to identify direct regulatory targets, as well as the precise physiological mechanism(s) TLX may be regulating. To date, our work has revealed that TLX inhibits proliferation, slows migration, alters chemosensitivity, and impairs cell cycle progression in TNBC cells. In agreement with these findings, our work has also revealed that TLX is capable of modulating the expression of several genes that are known to regulate the processes of growth, migration, and cell cycle. Taken together, our early work supports our hypothesis, and provides valuable insight into the potential pro-survival function of TLX in TNBC. Ongoing work will continue to probe the mechanisms by which TLX impacts breast cancer biology, and establish whether the growth-inhibitory effects translate to in vivo models. As prior work has demonstrated that TLX’s transcriptional activity can be regulated by both synthetic and natural ligands, the results of our work would provide the foundational data necessary for the development of a TLX-based therapy for a patient population with limited therapeutic options and a poor prognostic outlook.

Abstract PS4-11: Identification and validation of stromal immunotype predict survival and benefit from neoadjuvant chemotherapy in patients of breast cancer

Abstract Background Immune infiltration of breast cancer is associated with clinical outcome. A growing number of research suggests the immune response were composed by variously functionally distinct immune cell. But it’s not clear which kinds of cell play the important role. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast cancer influence survival and treatment response, and construct a stromal immunotype which could predict the response of neoadjuvant therapy and survival. Patients and Methods A total of 1502 ER negative breast cancers from TCGA and METABRIC cohort were used to infer the proportions of 22 subsets of immune cells, Another 320 ER negative breast cancer patients from Guangdong Provincial People’s Hospital in the validation cohort were also included in the study. Immune cell infiltration was evaluated by immunohistochemical staining or CIBERSORT method, Five immune features were selected out of 22 immune features to construct immunotype based on LASSO Cox regression model. ResultOf the cell subsets investigated, CD8+ T cells (hazard ratio [HR] = 0.064, 95% CI 0.018-0.234; p &amp;lt; 0.001), CD4+ T cells (HR 0.072, 95% CI 0.013-0.382; p = 0.002), B cells (HR 0.04, 95% CI 0.005-0.340; p = 0.003) , M1 macrophages(HR 0.09, 95% CI 0.016-0.502; p = 0.006) were associated with favourable outcome. T regulatory cells(HR 10.791, 95% CI 2.059-58.444; p = 0.005) emerged as the most strongly associated with poor outcome. Using the LASSO model, we classified ER negative breast cancer patients into stromal immunotype A subgroup (CD8+T cellshigh CD4+T cellshigh B cellhigh M1 macrophageshigh Treglow) and stromal immunotype B subgroup (CD8+T cellslow CD4+T cellslow B celllow M1 macrophageslow Treg high). Significant differences were found between immunotype A and immunotype B in the combined cohort with 10-year overall survival (66.2% vs. 49.8%; P&amp;lt;0.001) and 10-year disease-free survival (63.8% vs. 44.4%; P&amp;lt;0.001). Stromal immunotype was revealed to be an independent prognostic indicator in multivariate analysis in all cohorts separately, and also showed to be related to pCR in neoadjuvant chemotherapy. Finally, stromal immunotype A showed higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4) expression and three important cytokines expression profiles (IL-2, INF-γ and TGF-β). Conclusion The stromal immunotypes could predict survival and recurrence of ER negative breast cancer patients effectively. Furthermore, the immunotypes might be a practical predictive tool for immunotherapy and neoadjuvant chemotherapy. Citation Format: Fei Ji, Ciqiu Yang, Liulu Zhang, Mei Yang, Jieqing Li, Hongfei Gao, Teng Zhu, Minyi Cheng, Kun Wang. Identification and validation of stromal immunotype predict survival and benefit from neoadjuvant chemotherapy in patients of breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-11.

MiRNA-mediated alteration of sulfatase modifying factor 1 expression using self-assembled branched DNA nanostructures.

Sulfatase enzymes catalyze sulfate ester hydrolysis, thus deficiencies of sulfatases lead to the accumulation of biomolecules resulting in several disorders. One of the important sulfatases is estrone sulfatase that converts inactive estrone sulfate to active estradiol. Posttranslational modification of highly conserved cysteine residue leads to unique formylglycine in the active site of sulfatases being critical for its catalytic activity. The essential factor responsible for this modification of sulfatase is Sulfatase-Modifying Factor 1 (SUMF1). The role of estrone sulfatase is well evident in breast cancer progression. However, the function and regulation of SUMF1 in cancer are not studied. In the present study, for the first time, we have assessed the expression of SUMF1 in breast cancer and report the oncogenic behavior upon overexpression of SUMF1. Although increased expression or activity of SUMF1 is anticipated based on its function, the expression of SUMF1 was found to be reduced in breast cancer cells at both mRNA and protein levels. An estrogen receptor (ER) dependent expression of SUMF1 was observed and higher SUMF1 expression is associated with improved breast cancer patient survival in ER-positive cases. However, high SUMF1 expression leads to reduced median survival in ER-negative breast cancer patients. Putative binding sites for miRNAs-106b-5p, 128-3p and 148b-3p were found at 3′-UTR of SUMF1. Since self-assembled branched DNA (bDNA) structures have emerged as a highly efficient strategy for targeting multiple miRNAs simultaneously, we studied the alteration in SUMF1 expression using bDNA nanostructures with a complementary sequence to miRNAs. The findings suggest the involvement of co-regulators and repressors in miRNA-mediated SUMF1 expression in breast cancer cells and reveal the therapeutic potential of SUMF1 in endocrine-related malignancies.

Breast cancer risk factors and their effects on survival: a Mendelian randomisation study

BackgroundObservational studies have investigated the association of risk factors with breast cancer prognosis. However, the results have been conflicting and it has been challenging to establish causality due to potential residual confounding. Using a Mendelian randomisation (MR) approach, we aimed to examine the potential causal association between breast cancer-specific survival and nine established risk factors for breast cancer: alcohol consumption, body mass index, height, physical activity, mammographic density, age at menarche or menopause, smoking, and type 2 diabetes mellitus (T2DM).MethodsWe conducted a two-sample MR analysis on data from the Breast Cancer Association Consortium (BCAC) and risk factor summary estimates from the GWAS Catalog. The BCAC data included 86,627 female patients of European ancestry with 7054 breast cancer-specific deaths during 15 years of follow-up. Of these, 59,378 were estrogen receptor (ER)-positive and 13,692 were ER-negative breast cancer patients. For the significant association, we used sensitivity analyses and a multivariable MR model. All risk factor associations were also examined in a model adjusted by other prognostic factors.ResultsIncreased genetic liability to T2DM was significantly associated with worse breast cancer-specific survival (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.03–1.17, P value [P] = 0.003). There were no significant associations after multiple testing correction for any of the risk factors in the ER-status subtypes. For the reported significant association with T2DM, the sensitivity analyses did not show evidence for violation of the MR assumptions nor that the association was due to increased BMI. The association remained significant when adjusting by other prognostic factors.ConclusionsThis extensive MR analysis suggests that T2DM may be causally associated with worse breast cancer-specific survival and therefore that treating T2DM may improve prognosis.

Kinase–substrate Edge Biomarkers Provide A More Accurate Prognostic Prediction in ER-negative Breast Cancer

The estrogen receptor (ER)-negative breast cancer subtype is aggressive with few treatment options available. To identify specific prognostic factors for ER-negative breast cancer, this study included 705,729 and 1034 breast invasive cancer patients from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. To identify key differential kinase–substrate node and edge biomarkers between ER-negative and ER-positive breast cancer patients, we adopted a network-based method using correlation coefficients between molecular pairs in the kinase regulatory network. Integrated analysis of the clinical and molecular data revealed the significant prognostic power of kinase–substrate node and edge features for both subtypes of breast cancer. Two promising kinase–substrate edge features, CSNK1A1–NFATC3 and SRC–OCLN, were identified for more accurate prognostic prediction in ER-negative breast cancer patients.

Expression of MTDH and IL-10 Is an Independent Predictor of Worse Prognosis in ER-Negative or PR-Negative Breast Cancer Patients.

(1) Background: Tumor hypoxia leads to metastasis and certain immune responses, and interferes with normal biological functions. It also affects glucose intake, down-regulates oxidative phosphorylation, and inhibits fatty-acid desaturation regulated by hypoxia-inducible factor 1α (HIF-1α). Although tumor hypoxia has been found to promote tumor metastasis, the roles of HIF-1α-regulated genes and their application are not completely integrated in clinical practice. (2) Methods: We examined the correlation between HIF-1α, metadherin (MTDH), and interleukin (IL)-10 mRNA expression, as well as their expression patterns in the prognosis of breast cancer using the Gene Expression Profiling Interactive Analysis (GEPIA) databases via a web interface; tissue microarrays (TMAs) were stained for MTDH and IL-10 protein expression using immunohistochemistry. (3) Results: HIF-1α, MTDH, and IL-10 mRNA expression are highly correlated and strongly associated with poor prognosis. MTDH and IL-10 protein expression of breast cancer patients usually harbored negative estrogen receptor (ER) or progesterone receptor (PR) status, and late-stage tumors have higher IL-10 expression. With regard to MTDH and IL-10 protein expression status for using univariate and multivariate analysis, the results showed that the protein expression of MTDH and IL-10 in ER-negative or PR-negative breast cancer patients have the worse prognosis. (4) Conclusions: we propose a new insight into hypoxia tumors in the metabolism and immune evidence for breast cancer therapy.

Digital Image Analysis of Ki-67 Stained Tissue Microarrays and Recurrence in Tamoxifen-Treated Breast Cancer Patients.

PurposeThe proliferation marker Ki-67 has been used as a prognostic marker to separate low- and high-risk breast cancer subtypes and guide treatment decisions for adjuvant chemotherapy. The association of Ki-67 with response to tamoxifen therapy is unclear. High-throughput automated scoring of Ki-67 might enable standardization of quantification and definition of clinical cut-off values. We hypothesized that digital image analysis (DIA) of Ki-67 can be used to evaluate proliferation in breast cancer tumors, and that Ki-67 may be associated with tamoxifen resistance in early-stage breast cancer.Patients and MethodsHere, we apply DIA technology from Visiopharm using a custom designed algorithm for quantifying the expression of Ki-67, in a case–control study nested in the Danish Breast Cancer Group clinical database, consisting of stages I, II, or III breast cancer patients of 35–69 years of age, diagnosed during 1985–2001, in the Jutland peninsula, Denmark. We assessed DIA-Ki-67 score on tissue microarrays (TMAs) from breast cancer patients in a case–control study including 541 ER-positive and 300 ER-negative recurrent cases and their non-recurrent controls, matched on ER-status, cancer stage, menopausal status, year of diagnosis, and county of residence. We used logistic regression to estimate odds ratios and associated 95% confidence intervals to determine the association of Ki-67 expression with recurrence risk, adjusting for matching factors, chemotherapy, type of surgery, receipt of radiation therapy, age category, and comorbidity.ResultsKi-67 was not associated with increased risk of recurrence in tamoxifen-treated patients (ORadj =0.72, 95% CI 0.54, 0.96) or ER-negative patients (ORadj =0.85, 95% CI 0.54, 1.34).ConclusionOur findings suggest that Ki-67 digital image analysis in TMAs is not associated with increased risk of recurrence among tamoxifen-treated ER-positive breast cancer or ER-negative breast cancer patients. Overall, our findings do not support an increased risk of recurrence associated with Ki-67 expression.

Twist-mediated PAR1 induction is required for breast cancer progression and metastasis by inhibiting Hippo pathway

Breast cancer is considered to be the most prevalent cancer in women worldwide, and metastasis is the primary cause of death. Protease-activated receptor 1 (PAR1) is a GPCR family member involved in the invasive and metastatic processes of cancer cells. However, the functions and underlying mechanisms of PAR1 in breast cancer remain unclear. In this study, we found that PAR1 is highly expressed in high invasive breast cancer cells, and predicts poor prognosis in ER-negative and high-grade breast cancer patients. Mechanistically, Twist transcriptionally induces PAR1 expression, leading to inhibition of Hippo pathway and activation of YAP/TAZ; Inhibition of PAR1 suppresses YAP/TAZ-induced epithelial-mesenchymal transition (EMT), invasion, migration, cancer stem cell (CSC)-like properties, tumor growth and metastasis of breast cancer cells in vitro and in vivo. These findings suggest that PAR1 acts as a direct transcriptionally target of Twist, can promote EMT, tumorigenicity and metastasis by controlling the Hippo pathway; this may lead to a potential therapeutic target for treating invasive breast cancer.

Identification and validation of stromal immunotype predict survival and benefit from neoadjuvant chemotherapy in patients of breast cancer.

e15261 Background: Immune infiltration of breast cancer is associated with clinical outcome. A growing number of research suggests the diversity of functionally distinct cell types that make up the immune response. The aim of this study was to determine whether differences in the cellular composition of the immune infiltrate in breast cancer influence survival and treatment response, and construct the stromal immunotype which could improve prediction of neoadjuvant therapy and survival. Methods: A total of 1502 ER negative breast cancers from TCGA and METABRIC cohort were used to infer the proportions of 22 subsets of immune cells, Another 200 ER negative breast cancer patients from Guangdong Provincial People’s Hospital in the validation cohort were also included in the study. Immune cell infiltration was evaluated by immunohistochemical staining or CIBERSORT method, Five immune features were selected out of 22 immune features to construct immunotype based on LASSO Cox regression model. Results: Of the cell subsets investigated, CD8+ T cells (p &lt; 0.001), CD4+ T cells (p = 0.002), B cells (p = 0.003), M1 macrophages(p = 0.006) were associated with favourable outcome. T regulatory cells(p = 0.005) emerged as the most strongly associated with poor outcome. T regulatory cells were associated with pathological complete response to neoadjuvant chemotherapy (p = 0.012). Using the LASSO model, we classified ER negative breast cancer patients into stromal immunotype A subgroup (CD8+Thigh CD4+Thigh B cellhigh M1 macrophagehigh Treglow) and stromal immunotype B subgroup (CD8+Tlow CD4+Tlow B celllow M1 macrophagelow Treg high). Significant differences were found between immunotype A and immunotype B in the combined cohort with 10-year overall survival (66.2% vs. 49.8%; P &lt; 0.001) and 10-year disease-free survival (63.8% vs. 44.4%; P &lt; 0.001). Stromal immunotype was revealed to be an independent prognostic indicator in multivariate analysis in all cohorts separately, and also showed to be related to pCR in neoadjuvant chemotherapy. Finally, stromal immunotype A showed higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4) expression and three important cytokines expression profiles (IL-2, INF-γ and TGF-β). Conclusions: The stromal immunotypes could predict survival and recurrence of ER negative breast cancer patients effectively. Furthermore, the immunotypes might be a practical predictive tool for immunotherapy.

A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy.

For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (P < 0.01; HR = 3.84; 95% CI = 1.91–7.70) in GSE25055. Similar results were obtained in GSE25065. Moreover, in the integrated data of the two datasets with 94 responders and 21 extremely resistant samples identified from RD patients, the former had significantly longer DRFS than the latter (P < 0.01; HR = 2.22; 95% CI = 1.26–3.90). In summary, our signature could effectively identify patients who completely respond to PAC NAC, as well as cases of extreme resistance, which can assist decision-making on the clinical therapy for these patients.

The G Protein-Coupled Estrogen Receptor (GPER) Expression Correlates with Pro-Metastatic Pathways in ER-Negative Breast Cancer: A Bioinformatics Analysis.

The G protein-coupled estrogen receptor (GPER, formerly known as GPR30) is a seven-transmembrane receptor that mediates estrogen signals in both normal and malignant cells. In particular, GPER has been involved in the activation of diverse signaling pathways toward transcriptional and biological responses that characterize the progression of breast cancer (BC). In this context, a correlation between GPER expression and worse clinical-pathological features of BC has been suggested, although controversial data have also been reported. In order to better assess the biological significance of GPER in the aggressive estrogen receptor (ER)-negative BC, we performed a bioinformatics analysis using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation and the statistical analysis were carried out with R studio base functions and the tidyverse package. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the Database for Annotation, Visualization and Integrated Discovery (DAVID) website, whereas gene set enrichment analysis (GSEA) was performed with the R package phenoTest. The survival analysis was determined with the R package survivALL. Analyzing the expression data of more than 2500 primary BC, we ascertained that GPER levels are associated with pro-migratory and metastatic genes belonging to cell adhesion molecules (CAMs), extracellular matrix (ECM)-receptor interaction, and focal adhesion (FA) signaling pathways. Thereafter, evaluating the disease-free interval (DFI) in ER-negative BC patients, we found that the subjects expressing high GPER levels exhibited a shorter DFI in respect to those exhibiting low GPER levels. Overall, our results may pave the way to further dissect the network triggered by GPER in the breast malignancies lacking ER toward a better assessment of its prognostic significance and the action elicited in mediating the aggressive features of the aforementioned BC subtype.

Genistein Inhibits Proliferation of BRCA1 Mutated Breast Cancer Cells: The GPR30-Akt Axis as a Potential Target.

BackgroundBRCA1 mutated breast cancer cells exhibit the elevated cell proliferation and the higher metastatic potential. G protein-coupled receptor 30 (GPR30) has been shown to regulate growth of hormonally responsive cancers, such as ovarian and breast cancers, and high expression of GPR30 is found in estrogen receptor (ER)-negative breast cancer cells. ER-negative breast cancer patients often have a mutation in the tumor suppressor gene, BRCA1. This study explored antiproliferative effects of genistein, a chemopreventive isoflavone present in legumes, and underlying molecular mechanisms in triple negative breast cancer cells with or without functionally active BRCA1.MethodsExpression of BRCA1, GPR30 and Nrf2 was measured by Western blot analysis. Reactive oxygen species (ROS) accumulation was monitored by using the fluorescence-generating probe, 2’,7’-dichlorofluorescein diacetate. The effects of genistein on breast cancer cell viability and proliferation were assessed by the MTT, migration and clonogenic assays.ResultsThe expression of GPR30 was dramatically elevated at both transcriptional and translational levels in BRCA1 mutated breast cancer cells compared to cells with wild-type BRCA1. Notably, there was diminished Akt phosporylation in GPR30 silenced cells. Treatment of BRCA1 silenced breast cancer cells with genistein resulted in the down-regulation of GPR30 expression and the inhibition of Akt phosphorylation as well as the reduced cell viability, migration and colony formation. Genistein caused cell cycle arrest at the G2/M phase in BRCA1-mutant cells through down-regulation of cyclin B1 expression. Furthermore, BRCA1-mutant breast cancer cells exhibited higher levels of intracellular ROS than those in the wild-type cells. Genistein treatment lowered the ROS levels through up-regulation of Nrf2 expression.ConclusionsLack of functional BRCA1 activates GPR30 signaling, thereby stimulating Akt phosphorylation and cell proliferation. Genistein induces G2/M phase arrest by down-regulating cyclin B1 expression, which is attributable to its suppression of GPR30 activation and Akt phosphorylation in BRCA1 impaired breast cancer cells.

GREM1 is associated with metastasis and predicts poor prognosis in ER-negative breast cancer patients

BackgroundIn breast cancer, activation of bone morphogenetic protein (BMP) signaling and elevated levels of BMP-antagonists have been linked to tumor progression and metastasis. However, the simultaneous upregulation of BMPs and their antagonist, and the fact that both promote tumor aggressiveness seems contradictory and is not fully understood.MethodsWe analyzed the transcriptomes of the metastatic 66cl4 and the non-metastatic 67NR cell lines of the 4T1 mouse mammary tumor model to search for factors that promote metastasis. CRISPR/Cas9 gene editing was used for mechanistic studies in the same cell lines. Furthermore, we analyzed gene expression patterns in human breast cancer biopsies obtained from public datasets to evaluate co-expression and possible relations to clinical outcome.ResultsWe found that mRNA levels of the BMP-antagonist Grem1, encoding gremlin1, and the ligand Bmp4 were both significantly upregulated in cells and primary tumors of 66cl4 compared to 67NR. Depletion of gremlin1 in 66cl4 could impair metastasis to the lungs in this model. Furthermore, we found that expression of Grem1 correlated with upregulation of several stem cell markers in 66cl4 cells compared to 67NR cells. Both in the mouse model and in patients, expression of GREM1 associated with extracellular matrix organization, and formation, biosynthesis and modification of collagen. Importantly, high expression of GREM1 predicted poor prognosis in estrogen receptor negative breast cancer patients. Analyses of large patient cohorts revealed that amplification of genes encoding BMP-antagonists and elevation of the corresponding transcripts is evident in biopsies from more than half of the patients and much more frequent for the secreted BMP-antagonists than the intracellular inhibitors of SMAD signaling.ConclusionIn conclusion, our results show that GREM1 is associated with metastasis and predicts poor prognosis in ER-negative breast cancer patients. Gremlin1 could represent a novel target for therapy.

ER-Negative Breast Cancer Is Highly Responsive to Cholesterol Metabolite Signalling.

Interventions that alter cholesterol have differential impacts on hormone receptor positive- and negative-breast cancer risk and prognosis. This implies differential regulation or response to cholesterol within different breast cancer subtypes. We evaluated differences in side-chain hydroxycholesterol and liver X nuclear receptor signalling between Oestrogen Receptor (ER)-positive and ER-negative breast cancers and cell lines. Cell line models of ER-positive and ER-negative disease were treated with Liver X Receptor (LXR) ligands and transcriptional activity assessed using luciferase reporters, qPCR and MTT. Publicly available datasets were mined to identify differences between ER-negative and ER-positive tumours and siRNA was used to suppress candidate regulators. Compared to ER-positive breast cancer, ER-negative breast cancer cells were highly responsive to LXR agonists. In primary disease and cell lines LXRA expression was strongly correlated with its target genes in ER-negative but not ER-positive disease. Expression of LXR’s corepressors (NCOR1, NCOR2 and LCOR) was significantly higher in ER-positive disease relative to ER-negative, and their knock-down equalized sensitivity to ligand between subtypes in reporter, gene expression and viability assays. Our data support further evaluation of dietary and pharmacological targeting of cholesterol metabolism as an adjunct to existing therapies for ER-negative and ER-positive breast cancer patients.