Tumor cell intrinsic and extrinsic features predict prognosis in estrogen receptor positive breast cancer

Although estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay (our optimized random forest model AUC = 0.841, Oncotype DX model AUC = 0.792, p = 0.04). As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.     

Human breast cancer associated fibroblasts exhibit subtype specific gene expression profiles

ABSTRACT: BACKGROUND: Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. METHODS: To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. RESULTS: We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER + cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs likely contribute to the enhanced migration of breast cancer cells in transwell assays and may contribute to the unfavorable prognosis of Her2+ breast cancer. CONCLUSIONS: These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer.     

Worldwide variations in EGFR somatic mutations: a challenge for personalized medicine

Two studies recently reported around 10% of EGFR activating mutations in triple negative breast cancers from Asian patients. However, we did not find any EGFR activating mutation in a series of 229 breast tumor samples from European patients. Like in lung cancer, the EGFR mutation profiles seem to be related to the ethnical origin of patients. This is an important point that should be considered when developing anti-EGFR therapies.     

Folate Receptor-α (FOLR1) Expression and Function in Triple Negative Tumors

Folate receptor alpha (FOLR1) has been identified as a potential prognostic and therapeutic target in a number of cancers. A correlation has been shown between intense overexpression of FOLR1 in breast tumors and poor prognosis, yet there is limited examination of the distribution of FOLR1 across clinically relevant breast cancer subtypes. To explore this further, we used RNA-seq data from multiple patient cohorts to analyze the distribution of FOLR1 mRNA across breast cancer subtypes comprised of estrogen receptor positive (ER+), human epidermal growth factor receptor positive (HER2+), and triple negative (TNBC) tumors. FOLR1 expression varied within breast tumor subtypes; triple negative/basal tumors were significantly associated with increased expression of FOLR1 mRNA, compared to ER+ and HER2+ tumors. However, subsets of high level FOLR1 expressing tumors were observed in all clinical subtypes. These observations were supported by immunohistochemical analysis of tissue microarrays, with the largest number of 3+ positive tumors and highest H-scores of any subtype represented by triple negatives, and lowest by ER+ tumors. FOLR1 expression did not correlate to common clinicopathological parameters such as tumor stage and nodal status. To delineate the importance of FOLR1 overexpression in triple negative cancers, RNA-interference was used to deplete FOLR1 in overexpressing triple negative cell breast lines. Loss of FOLR1 resulted in growth inhibition, whereas FOLR1 overexpression promoted folate uptake and growth advantage in low folate conditions. Taken together, our data suggests patients with triple negative cancers expressing high FOLR1 expression represent an important population of patients that may benefit from targeted anti-FOLR1 therapy. This may prove particularly helpful for a large number of patients who would typically be classified as triple negative and who to this point have been left without any targeted treatment options.     

Synthesis, characterization, molecular docking and cytotoxic activity of novel plumbagin hydrazones against breast cancer cells

Novel plumbagin hydrazonates were prepared, structurally characterized and evaluated for anti-proliferative activity against estrogen receptor-positive MCF-7 and triple negative MDA-MB-231 and MDA-MB-468 breast cancer cell lines which exhibited superior inhibitory activity than parent plumbagin compound. Molecular docking studies indicated that hydroxyl groups on plumbagin and hydrazonate side chain favor additional hydrogen bonding interactions with amino acid residues in p50-subunit of NF-κB protein and these compounds inhibited NF-κB expression which may be responsible for the enhanced anti-proliferative activity. These compounds were found to be more effective against triple negative breast cancer cells and might serve as a starting point for building future strategies against triple negative breast cancers which are known for their increased drug resistance and poor prognosis of breast cancer patients.     

Molecular Characteristics and Metastasis Predictor Genes of Triple-Negative Breast Cancer: A Clinical Study of Triple-Negative Breast Carcinomas

Background

Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.

Methodology/Principal Findings

Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04–5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.

Conclusions/Significance

Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.     

A Novel Model to Combine Clinical and Pathway-Based Transcriptomic Information for the Prognosis Prediction of Breast Cancer

Breast cancer is the most common malignancy in women worldwide. With the increasing awareness of heterogeneity in breast cancers, better prediction of breast cancer prognosis is much needed for more personalized treatment and disease management. Towards this goal, we have developed a novel computational model for breast cancer prognosis by combining the Pathway Deregulation Score (PDS) based pathifier algorithm, Cox regression and L1-LASSO penalization method. We trained the model on a set of 236 patients with gene expression data and clinical information, and validated the performance on three diversified testing data sets of 606 patients. To evaluate the performance of the model, we conducted survival analysis of the dichotomized groups, and compared the areas under the curve based on the binary classification. The resulting prognosis genomic model is composed of fifteen pathways (e.g. P53 pathway) that had previously reported cancer relevance, and it successfully differentiated relapse in the training set (log rank p-value = 6.25e-12) and three testing data sets (log rank p-value<0.0005). Moreover, the pathway-based genomic models consistently performed better than gene-based models on all four data sets. We also find strong evidence that combining genomic information with clinical information improved the p-values of prognosis prediction by at least three orders of magnitude in comparison to using either genomic or clinical information alone. In summary, we propose a novel prognosis model that harnesses the pathway-based dysregulation as well as valuable clinical information. The selected pathways in our prognosis model are promising targets for therapeutic intervention.     

Long non‐coding RNA ZEB2‐AS1 promotes the proliferation,metastasis and epithelial mesenchymal transition in triple‐negative breast cancer by epigenetically activating ZEB2

The triple‐negative breast cancer is the most malignant type of breast cancer. Its pathogenesis and prognosis remain poor despite the significant advances in breast cancer diagnosis and therapy. Meanwhile, long noncoding RNAs (LncRNAs) play a pivotal role in the progression of malignant tumors. In this study, we found that LncRNA‐ZEB2‐AS1 was dramatically up‐regulated in our breast cancer specimens and cells (MDA231), especially in metastatic tumor specimens and highly invasive cells, and high lncRNA‐ZEB2‐AS1 expression is associated with clinicopathologic features and short survival of breast cancer patients. LncRNA‐ZEB2‐AS1 promotes the proliferation and metastasis of MDA231 cells in SCID mice. Thus, it is regarded as an oncogene in triple‐negative breast cancer. It is mainly endo‐nuclear and situated near ZEB2, positively regulating ZEB2 expression and activating the epithelial mesenchymal transition via the PI3K/Akt/GSK3β/Zeb2 signaling pathway. Meanwhile, EGF‐induced F‐actin polymerization in MDA231 cells can be suppressed by reducing lncRNA‐ZEB2‐AS1 expression. The migration and invasion of triple‐negative breast cancer can be altered through cytoskeleton rearrangement. In summary, we demonstrated that lncRNA‐ZEB2‐AS1 is an important factor affecting the development of triple‐negative breast cancer and thus a potential oncogene target.     

Reciprocal Regulation of Annexin A2 and EGFR with Her-2 in Her-2 Negative and Herceptin-Resistant Breast Cancer

Alternative survival pathways are commonly seen to be upregulated upon inhibition of receptor tyrosine kinases (RTK), including Her-2. It is established that treatment with Herceptin leads to selective overexpression and activation of epidermal growth factor receptor (EGFR) and Src which further contributes to oncogenesis in Herceptin resistant and triple negative breast cancer (TNBC) patients. Here, we show a co-regulated upregulation in the expression of Annexin A2 (AnxA2), a known substrate of Src and one of the regulators of EGFR receptor endocytosis, in Herceptin resistant and Her-2 negative breast cancer. Immunohistochemical expression analysis revealed a reciprocal regulation between Her-2 and AnxA2 in breast cancer clinical samples as well as in cell lines as confirmed by protein and RNA analysis. The siRNA and Herceptin mediated downregulation/inhibition of Her-2 in Her-2 amplified cells induced AnxA2 expression and membrane translocation. In this study we report a possible involvement of AnxA2 in maintaining constitutively activated EGFR downstream signaling intermediates and hence in cell proliferation, migration and viability. This effect was consistent in Herceptin resistant JIMT-1 cells as well as in Her-2 negative breast cancer. The siRNA mediated AnxA2 downregulation leads to increased apoptosis, decreased cell viability and migration. Our studies further indicate the role of AnxA2 in EGFR-Src membrane bound signaling complex and ligand induced activation of downstream signaling pathways. Targeting this AnxA2 dependent positive regulation of EGFR signaling cascade may be of therapeutic value in Her-2 negative breast cancer.     

LncRNA MIR503HG inhibits cell migration and invasion via miR‐103/OLFM4 axis in triple negative breast cancer

Long non‐coding RNA MIR503 host gene (MIR503HG) is located on chromosome Xq26.3, and has been found to be deregulated in many types of human malignancy and function as tumour suppressor or promoter based on cancer types. The role of MIR503HG in breast cancer was still unknown. In our study, we found MIR503HG expression was significantly decreased in triple‐negative breast cancer tissues and cell lines. Furthermore, we observed low MIR503HG expression was correlated with late clinical stage, lymph node metastasis and distant metastasis. In the survival analysis, we observed that triple‐negative breast cancer patients with low MIR503HG expression had a statistically significant worse prognosis compared with those with high MIR503HG expression, and low MIR503HG expression was a poor independent prognostic factor for overall survival in triple‐negative breast cancer patients. The study in vitro suggested MIR503HG inhibits cell migration and invasion via miR‐103/OLFM4 axis in triple negative breast cancer. In conclusion, MIR503HG functions as a tumour suppressive long non‐coding RNA in triple negative breast cancer.     

Many new down‐ and up‐regulatory signaling pathways,from known cancer progression suppressors to matrix metalloproteinases,differ widely in cells of various cancers

Previously we detected new signaling pathways, some downregulatory and others upregulatory, from seven known suppressors of cancer progression to the expression of eight cancer‐promoting matrix metalloproteinases (MMPs) in breast cancer cells. The goals of the present study were to test whether the preceding observations occur only in breast cancer cells and, if not, whether the same downregulatory and upregulatory signaling pathways are active in cells of other human cancers, focusing on activator protein‐2α, E‐cadherin, fibulin1D, interleukin 4, p16^INK4α, p53, PTEN, and RKIP, and on MMP1, MMP2, MMP7, MMP13, MMP14, MMP16, MMP19, and MMP25. To this end, in the present study we tested the effects of raising the cellular levels of wild‐type copies of these known suppressors of cancer progression on the expression of these MMPs. This study yielded several unexpected results. We have detected 53 new signaling pathways in cells of prostate, brain, lung, ovarian and breast human cancers, with an abundance of signaling pathways as high as ～40% of the cancer progression regulator/MMP pairs tested in cells of prostate and breast cancers. Cells of various cancers differed widely and sequence‐specifically in the identity of their signaling pathways, so that almost 90% of the pathways were different in cells from one cancer to another. In each of 18 out of 51 signaling pathways, a known suppressor of cancer progression stimulated, rather than inhibited, the expression of a cancer‐promoting MMP. Ten signaling pathways were upregulatory in cells of some cancers and downregulatory in cells of other cancers. J. Cell. Physiol. 224: 549–558, 2010. © 2010 Wiley‐Liss, Inc.     

Exploring metabolic pathway disruption in the subchronic phencyclidine model of schizophrenia with the Generalized Singular Value Decomposition

Background

One of the major goals in gene and protein expression profiling of cancer is to identify biomarkers and build classification models for prediction of disease prognosis or treatment response. Many traditional statistical methods, based on microarray gene expression data alone and individual genes' discriminatory power, often fail to identify biologically meaningful biomarkers thus resulting in poor prediction performance across data sets. Nonetheless, the variables in multivariable classifiers should synergistically interact to produce more effective classifiers than individual biomarkers.

Results

We developed an integrated approach, namely network-constrained support vector machine (netSVM), for cancer biomarker identification with an improved prediction performance. The netSVM approach is specifically designed for network biomarker identification by integrating gene expression data and protein-protein interaction data. We first evaluated the effectiveness of netSVM using simulation studies, demonstrating its improved performance over state-of-the-art network-based methods and gene-based methods for network biomarker identification. We then applied the netSVM approach to two breast cancer data sets to identify prognostic signatures for prediction of breast cancer metastasis. The experimental results show that: (1) network biomarkers identified by netSVM are highly enriched in biological pathways associated with cancer progression; (2) prediction performance is much improved when tested across different data sets. Specifically, many genes related to apoptosis, cell cycle, and cell proliferation, which are hallmark signatures of breast cancer metastasis, were identified by the netSVM approach. More importantly, several novel hub genes, biologically important with many interactions in PPI network but often showing little change in expression as compared with their downstream genes, were also identified as network biomarkers; the genes were enriched in signaling pathways such as TGF-beta signaling pathway, MAPK signaling pathway, and JAK-STAT signaling pathway. These signaling pathways may provide new insight to the underlying mechanism of breast cancer metastasis.

Conclusions

We have developed a network-based approach for cancer biomarker identification, netSVM, resulting in an improved prediction performance with network biomarkers. We have applied the netSVM approach to breast cancer gene expression data to predict metastasis in patients. Network biomarkers identified by netSVM reveal potential signaling pathways associated with breast cancer metastasis, and help improve the prediction performance across independent data sets.     

不同分子分型乳腺癌患者血清IGFBP-3、Angptl-2表达水平及其与骨转移、预后的相关性

摘要 目的：分析不同分子分型乳腺癌患者血清胰岛素样生长因子结合蛋白3（IGFBP-3）、生成素养蛋白2（Angptl-2）表达水平及其与骨转移、预后的相关性。方法：选取2018年3月-2021年3月东南大学附属中大医院收治的128例乳腺癌骨转移患者进行研究,其中包括Luminal A型50例、42例Luminal B型（HER-2阴性）42例、HER-2过表达型16例、三阴性乳腺癌（TNBC）20例,并分析4种分子分型乳腺癌的临床病理特征,同时采用酶联免疫吸附法检测其血清IGFBP-3、Angptl-2表达水平;随访24个月后记录两组患者的预后情况,并采用多因素Logistic模型分析影响4种分子分型乳腺癌骨转移患者预后的独立危险因素,以及血清IGFBP-3、Angptl-2与不同分子分型乳腺癌骨转移患者预后的相关性。结果：Luminal A型、Luminal B型、HER-2过表达型、TNBC型TNM分期、淋巴结转移比较,差异有统计学意义（P＜0.05）。与Luminal A型、Luminal B型、TNBC型乳腺癌骨转移患者相比,HER-2过表达型乳腺癌骨转移患者的血清IGFBP-3表达水平较低,Angptl-2表达水平较高（P＜0.05）。Luminal A型、Luminal B型、HER-2过表达型、TNBC型乳腺癌骨转移患者的死亡率分别为13.46%、38.46%、23.08%、25.00%。多因素Logistic结果显示,TNM分期、淋巴结转移、血清IGFBP-3、Angptl-2均是影响不同分子分型乳腺癌骨转移患者预后的独立危险因素（P＜0.05）。血清IGFBP-3异常高表达提示4种分子分型乳腺癌骨转移患者的不良预后,而Angptl-2表达水平与4种分子分型乳腺癌的预后呈正相关性（P＜0.05）。针对不同分子分型乳腺癌骨转移患者的预后预测中,血清IGFBP-3、Angptl-2、IGFBP-3+Angptl-2均呈现AUC＞0.75。结论：血清IGFBP-3、Angptl-2可作为HER-2过表达乳腺癌骨转移患者的潜在生物标志物;同时还可根据血清IGFBP-3、Angptl-2表达水平预测不同分子分型乳腺癌骨转移患者的预后。     

Lipophilic statins antagonistically alter the major epithelial-to-mesenchymal transition signaling pathways in breast cancer stem–like cells via inhibition of the mevalonate pathway

Resistance to therapies, recurrence, and metastasis remain challenging issues for breast cancer patients, particularly for triple-negative and breast cancer stem cells. The activation of the epithelial-to-mesenchymal transition (EMT) plays an indispensable role in the poor prognosis of those types. The accumulating proofs indicated that the mevalonate pathway crucially mediates a poor prognosis. Here, the effects of lipophilic 3-hydroxy-3-methyl-glutaryl-coenzyme A inhibitors, atorvastatin, lovastatin, and simvastatin, were investigated on expression and function of a selected profile of EMT-related genes in breast cancer stem–like cells. A nontoxic dose of statins (5 μM for 4 days) significantly (P < 0.05 and >2-fold change) altered expression of 50 of 71 studied genes with a shared cluster of 37 genes that are coding chief operator of signaling pathways in Hippo, Notch, Wnt, proliferation, invasion, angiogenesis, and cell death. They also significantly decreased the levels of Yap/Taz proteins and shifted the expression of vimentin/E-cadherin in favor of induction of differentiation. Statins significantly chemosensitized the treated cells to doxorubicin and also reduced in vitro migration of the cells. Whereas lovastatin and simvastatin significantly decreased the expression of CD44, atorvastatin drastically increased CD24 and caused more wide-ranging impacts. In summary, the statins hold back the process of EMT by the antagonizing of EMT-promoting pathways. High degree of overlapping findings is supportive of the central role of the mevalonate pathway in cancer stem–like cells, but further studies are required to find the optimized chemical structure for the maximum abrogation of orchestrated EMT pathways.     

Anaplastic lymphoma kinase is expressed in different subtypes of human breast cancer

Pleiotrophin (PTN, Ptn) is an 18kDa cytokine expressed in human breast cancers. Since inappropriate expression of Ptn stimulates progression of breast cancer in transgenic mice and a dominant negative PTN reverses the transformed phenotype of human breast cancer cells that inappropriately express Ptn, it is suggested that constitutive PTN signaling in breast cancer cells that inappropriately express Ptn activates pathways that promote a more aggressive breast cancer phenotype. Pleiotrophin signals by inactivating its receptor, the receptor protein tyrosine phosphatase (RPTP)beta/zeta, and, recently, PTN was found to activate anaplastic lymphoma kinase (ALK) through the PTN/RPTPbeta/zeta signaling pathway in PTN-stimulated cells, not through a direct interaction of PTN with ALK and thus not through the PTN-enforced dimerization of ALK. Since full-length ALK is activated in different malignant cancers and activated ALK is a potent oncogenic protein, we examined human breast cancers to test the possibility that ALK may be expressed in breast cancers and potentially activated through the PTN/RPTPbeta/zeta signaling pathway; we now demonstrate that ALK is strongly expressed in different histological subtypes of human breast cancer; furthermore, ALK is expressed in both nuclei and cytoplasm and, in the ;;dotted" pattern characteristic of ALK fusion proteins in anaplastic large cell lymphoma. This study thus supports the possibility that activated ALK may be important in human breast cancers and potentially activated either through the PTN/RPTPbeta/zeta signaling pathway, or, alternatively, as an activated fusion protein to stimulate progression of breast cancer in humans.     

Estrogen receptor-alpha 36 mediates the anti-apoptotic effect of estradiol in triple negative breast cancer cells via a membrane-associated mechanism

17β-Estradiol can promote the growth and development of several estrogen receptor (ER)-negative breast cancers. The effects are rapid and non-genomic, suggesting that a membrane-associated ER is involved. ERα36 has been shown to mediate rapid, non-genomic, membrane-associated effects of 17β-estradiol in several cancer cell lines, including triple negative HCC38 breast cancer cells. Moreover, the effect is anti-apoptotic. The aim of this study was to determine if ERα36 mediates this anti-apoptotic effect, and to elucidate the mechanism involved. Taxol was used to induce apoptosis in HCC38 cells, and the effect of 17β-estradiol pre-treatment was determined. Antibodies to ERα36, signal pathway inhibitors, ERα36 deletion mutants, and ERα36-silencing were used prior to these treatments to determine the role of ERα36 in these effects and to determine which signaling molecules were involved. We found that the anti-apoptotic effect of 17β-estradiol in HCC38 breast cancer cells is in fact mediated by membrane-associated ERα36. We also showed that this signaling occurs through a pathway that requires PLD, LPA, and PI3K; Gαs and calcium signaling may also be involved. In addition, dynamic palmitoylation is required for the membrane-associated effect of 17β-estradiol. Exon 9 of ERα36, a unique exon to ERα36 not found in other identified splice variants of ERα with previously unknown function, is necessary for these effects. This study provides a working model for a mechanism by which estradiol promotes anti-apoptosis through membrane-associated ERα36, suggesting that ERα36 may be a potential membrane target for drug design against breast cancer, particularly triple negative breast cancer.