Rescue of internalization-defective platelet-activating factor receptor function by EBP50/NHERF1

Platelet-activating factor (PAF) is a potent phospholipid mediator involved in specific disease states such as allergic asthma, atherosclerosis and psoriasis. The human PAF receptor (PAFR) is a member of the G protein-coupled receptor (GPCR) family. Following PAF stimulation, cells become rapidly desensitized; this refractory state can be maintained for hours and is dependent on PAFR phosphorylation, internalization and trafficking. EBP50/NHERF1 has been found to interact with a variety of proteins and these interactions are involved in a growing range of functions including the assembly of signalling complexes, receptor recycling and transport of proteins to the cell surface. Crucial roles of EBP50 in GPCR physiology include its involvement in internalization, recycling, and downregulation. We were interested in identifying the role of EBP50 in PAFR trafficking. Our results showed that EBP50 binds the PAFR in its basal state, while stimulation decreased the ratio of interaction between the two proteins. We also demonstrated that EBP50 could bind PAFR via its PDZ 2 domain. In addition, we studied the role of EBP50 in various functions of the PAFR such as PAF-induced inositol phosphate accumulation and receptor internalization: EBP50 decreased the WT PAFR response and rescued the function of internalization-deficient mutant receptors, as previously described for the arrestins and the GRKs. These results suggest new roles for EBP50, some of which could help understanding the complex formation after receptor activation.     

CDKN1C as a prognostic biomarker correlated with immune infiltrates and therapeutic responses in breast cancer patients

Breast cancer (BC) prognosis and therapeutic sensitivity could not be predicted efficiently. Previous evidence have shown the vital roles of CDKN1C in BC. Therefore, we aimed to construct a CDKN1C-based model to accurately predicting overall survival (OS) and treatment responses in BC patients. In this study, 995 BC patients from The Cancer Genome Atlas database were selected. Kaplan-Meier curve, Gene set enrichment and immune infiltrates analyses were executed. We developed a novel CDKN1C-based nomogram to predict the OS, verified by the time-dependent receiver operating characteristic curve, calibration curve and decision curve. Therapeutic response prediction was followed based on the low- and high-nomogram score groups. Our results indicated that low-CDKN1C expression was associated with shorter OS and lower proportion of naïve B cells, CD8 T cells, activated NK cells. The predictive accuracy of the nomogram for 5-year OS was superior to the tumour-node-metastasis stage (area under the curve: 0.746 vs. 0.634, p < 0.001). The nomogram exhibited excellent predictive performance, calibration ability and clinical utility. Moreover, low-risk patients were identified with stronger sensitivity to therapeutic agents. This tool can improve BC prognosis and therapeutic responses prediction, thus guiding individualized treatment decisions.     

NHERF1/EBP50 controls lactation by establishing basal membrane polarity complexes with prolactin receptor

The development of the lactating mammary gland is a complex multifactorial process occurring in mammals during pregnancy. We show here that this process requires NHERF1/EBP50 (Na/H exchanger regulatory factor 1/ERM-binding phosphoprotein 50) expression and that successful lactation depends on NHERF1 allele copy number, with rates of 50 and 20% in NHERF1(+/−) and (−/−) mice, respectively. The prolactin receptor (PRLR)-STAT5 signaling provides the central axis triggering the differentiation of secretory mammary alveolar cells. In successfully lactating glands, NHERF1 is massively upregulated and forms complexes with PRLR, but also with β-catenin, E-cadherin and ezrin at the alveolar basal membrane, establishing basal polarity. In NHERF1-deficient glands, the basal polarity is disrupted, the PRLR levels and basal membrane localization are abolished, and the downstream STAT5 activation collapses with consequent reduction of milk protein synthesis. NHERF1/EBP50, a protein deregulated in breast cancer, thus emerges as an important physiological mediator of milk secretion, by engagement of PRLR in multimeric complexes at the alveolar basal membrane with subsequent network activation leading to cell differentiation.     

Interaction of carboxyl-terminal peptides of cytosolic-tail of apactin with PDZ domains of NHERF/EBP50 and PDZK-1/CAP70

The C-terminal PDZ-binding motifs are required for polarized apical/basolateral localization of many membrane proteins. Ezrin–radixin–moesin (ERM) proteins regulate the organization and function of specific cortical structures in polarized epithelial cells by connecting filamentous (F)-actin to plasma membrane proteins through EBP50. Previous work showed that the membrane phosphoprotein apactin (an 80-kDa type I membrane protein derived from pro-Muclin) is associated with the acinar cell apical actin cytoskeleton and that this association is modulated by changes in the phosphorylation state of the apactin cytosolic tail. The carboxyl-terminal amino acids of apactin (–STKL–COOH) are predicted to form a type I PDZ-binding domain, similar to that of CFTR (–DTRL–COOH). Pairwise sequence comparison between NHERF/EBP50 and PDZK1/CAP70 PDZ domains reveals significant identity among the 83 amino-acid residues (12–92) of EBP50 and CAP70 (241–323), which are involved in the interaction with the carboxyl-terminal peptides (STKL–COOH and phosphomimetics) of apactin. Hence, the specificity and affinity of interactions are identical between them, which is corroborated with the two hybrid results. Substitution of all the four-carboxyl-terminal amino acids in the wild type to Ala reduces the interaction. Only the carbonyl oxygen and amide nitrogen of Ala are found to be involved in hydrogen bonding. Further, truncation of the wild carboxyl-terminal peptide to RGQPP–COOH, showed very low affinity of interaction with PDZ1 domain. Only the atom O^ε1 of Gln-2 hydrogen bonds with N^ε2 of His72 of PDZ domain. Ser-3 amino acid in wild type apactin protein (STKL–COOH) is not involved in hydrogen bonding with PDZ1 domain. However, substitution of Ser-3 to Asp-3 in PDTKL–COOH peptide increases the affinity of interaction of PDTKL–COOH with PDZ1 domain. Thus, carboxyl-terminal Asp(D) -3, Thr(T) -2, Lys(K) -1 and Leu(L) 0 are involved in numerous interactions with PDZ1 domains of NHERF/EBP50 and PDZK1/CAP70.     

p27Kip1 as a prognostic factor in breast cancer: a systematic review and meta‐analysis

The aim of this study was to comprehensively evaluate via a meta‐analysis the association between p27 expression and clinical outcome in breast cancer patients. We conducted a meta‐analysis of 20 studies (n= 6463 patients) that evaluated the correlation between p27 expression and indicators of breast cancer clinical outcome, including overall survival (OS), disease‐free survival (DFS) and relapse‐free survival (RFS). Data pooling was performed by RevMan 4.2. A total of 60% (9 of 15) of the studies showed a significant association between p27 high expression and OS, whereas 25% (2 of 8) and 60% (3 of 5) studies demonstrated a correlation between p27 high expression and DFS and RFS, respectively. The relative risks (RRs) were 1.34 (1.26–1.42) for OS (P < 0.00001), 1.27 (1.10–1.47) for DFS (P= 0.001) and 1.49 (0.92–2.42) for RFS (P= 0.10). In lymph node‐negative breast cancer patients, the RRs for OS and RFS were 1.84 (1.30–2.59; P= 0.0005) and 1.30 (0.20–8.50; P= 0.78), respectively. In lymph node‐positive breast cancer patients, the RRs for OS and RFS were 2.99 (1.77–5.07; P < 0.0001) and 1.49 (0.80–2.77; P= 0.21), respectively. This meta‐analysis indicates that reduced p27 is an independent prognostic factor for poor overall and disease‐free cancer survival.     

A prognostic eight-lncRNA expression signature in predicting recurrence of ER-positive breast cancer receiving endocrine therapy

Long noncoding RNAs (lncRNAs) have the main role in the tumorigenesis of breast cancer. In the present study, lncRNA expression profiling was collected to identify a lncRNA expression signature from the Gene Expression Omnibus database. An eight-lncRNA signature was established to predict the survival of patients with estrogen receptor (ER)-positive breast cancer receiving endocrine therapy. Patients were separated into a low-risk group and a high-risk group based on this signature. Patients in high-risk group have worse survival compared to those in low-risk group using Kaplan–Meier curve analysis with log-rank test. Receiver operating characteristic analysis suggested good diagnostic efficiency of the eight-lncRNA signature. When adjusting the clinical features, including age, grade, lymph node status, and tumor size, this signature was independently associated with the relapse-free survival. The prognostic value of the lncRNA prognostic model was then validated in validation sets. When validated in a cohort of patients treated with neoadjuvant chemotherapy and endocrine therapy, this signature demonstrated good performance as well. Besides, we have built a nomogram that integrated the conventional clinicopathological features and the eight-lncRNA-based signature. To sum up, our results indicated that the eight-lncRNA prognostic model was a reliable tool to group patients at high and low risk of disease relapse. This signature may have possible implication in prognostic evaluations of patients with ER-positive breast cancer receiving endocrine therapy.     

Promoter hypermethylation of the CFTR gene as a novel diagnostic and prognostic marker of breast cancer

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer‐related deaths among women. New biomarkers with definite diagnostic and prognostic efficacy are urgently needed. Here, we showed that the promoter of the cystic fibrosis transmembrane conductance regulator (CFTR) was hypermethylated in breast cancer. The messenger RNA level of CFTR was downregulated in breast cancer. Notably, all 19 breast cancer patients with hypermethylated CFTR were diagnosed with invasive carcinoma. Moreover, CFTR was upregulated in decitabine (10 μM) treated breast cancer cells. Overexpression of CFTR inhibited cell growth whereas knockdown of CFTR promoted cell invasion. In the tissue array analysis, the CFTR protein level decreased significantly in breast cancer and low CFTR protein level correlated with poor survival with a P‐value of 0.034. Thus, promoter hypermethylation of the CFTR gene might be a novel diagnostic marker of breast cancer.     

Breast cancer-derived K172N,D301V mutations abolish Na/H exchanger regulatory factor 1 inhibition of platelet-derived growth factor receptor signaling

Na⁺/H⁺ exchanger regulatory factor 1 (NHERF1) is a scaffold protein known to interact with a number of cancer-related proteins. nherf1 Mutations (K172N and D301V) were recently identified in breast cancer cells. To investigate the functional properties of NHERF1, wild-type and cancer-derived nherf1 mutations were stably expressed in SKMES-1 cells respectively. NHERF1-wt overexpression suppressed the cellular malignant phenotypes, including proliferation, migration, and invasion. nherf1 Mutations (K172N and D301V) caused complete or partial loss of NHERF1 functions by affecting the PTEN/NHERF1/PDGFRβ complex formation, inactivating NHERF1 inhibition of PDGF-induced AKT and ERK activation, and attenuating the tumor-suppressor effects of NHERF1-wt. These results further demonstrated the functional consequences of breast cancer-derived nherf1 mutations (K172N and D301V), and suggested the causal role of NHERF1 in tumor development and progression.     

E-cadherin deregulation in breast cancer

E-cadherin protein (CDH1 gene) integrity is fundamental to the process of epithelial polarization and differentiation. Deregulation of the E-cadherin function plays a crucial role in breast cancer metastases, with worse prognosis and shorter overall survival. In this narrative review, we describe the inactivating mechanisms underlying CDH1 gene activity and its possible translation to clinical practice as a prognostic biomarker and as a potential targeted therapy.     

Aberrant expression of Arpin in human breast cancer and its clinical significance

Arpin (Arp2/3 complex inhibitor), a novel protein found in 2013, plays a pivotal role in cell motility and migration. However, the precise role of Arpin in cancer is unclear. This study investigated the expression of Arpin in breast cancer and evaluated its correlation with the characteristics of clinical pathology and prognosis of breast cancer patients. Immunohistochemistry (IHC) for Arpin protein was performed on formalin‐fixed, paraffin‐embedded 176 breast cancer tissues and 43 normal breast tissues while qRT‐PCR for Arpin mRNA with 104 paired tumour and paratumoural tissues from breast cancer patients respectively. The association of Arpin expression with clinical pathological features and survival was assessed in a retrospective cohort analysis of patients. The results showed that the expression of Arpin protein in cancer tissues was lower compared to that in normal breast and the expression of Arpin mRNA was also lower in cancer tissues than that in the matched paratumoural tissues. Among the 176 breast cancer patients, the lower expression of Arpin was significantly associated with advanced tumour, nodes and metastasis system stage, and the reduced Arpin expression was strongly associated with axillary lymph node metastasis using univariate and multivariate logistic regression analysis [odds ratio: 3.242; 95% confidence interval (CI): 1.526, 6.888; P < 0.05]. Furthermore, Arpin expression was an independent risk factor for recurrence‐free survival (HR: 0.373; 95% CI: 0.171, 0.813; P < 0.05). As Arpin expression was first examined in human breast cancer tissues with qRT‐PCR and IHC, our results suggest that Arpin downregulation may contribute to the initiation and development of breast cancer metastasis. Therefore, as a potential predictive marker, Arpin deserves future studies.     

T-cell receptors provide potential prognostic signatures for breast cancer

Although T-cell receptors (TCRs) are related to the progression of breast cancer (BC), their prognostic values remain unclear. We downloaded the messenger RNA (mRNA) profiles and corresponding clinical information of 1413 BC patients from the Cancer Genome Atlas and Gene Expression Omnibus database, respectively. The different expression analysis of 104 TCRs in BC samples was performed, and the consensus clustering based on 104 TCRs was performed by using the K-mean method of R language. Univariate cox regression analysis was used to screen TCRs significantly associated with the prognosis of BC, and LASSO Cox analysis was applied to optimize key TCRs. The risk score was calculated using the prognostic model constructed based on six optimal TCRs, and multivariate Cox regression analysis was used to determine whether it was an independent prognostic signature. Finally, the nomogram was constructed to predict the overall survival of BC patients. Six optimal TCRs (ZAP70, GRAP2, NFKBIE, IFNG, NFKBIA, and PAK5), which were favorable for the prognosis of BC patients, were screened. Risk score could reliably predict the prognosis of BC patients as an independent prognostic signature. In addition, when bringing into two independent prognostic signatures, age and risk score, the nomogram model could better predict the overall survival of BC patients. Our results suggested that the poor prognosis of BC patients with high risk might be due to an immunosuppressive microenvironment. In summary, a prognostic risk model based on six TCRs was established and could efficiently predict the prognosis of BC patients.     

Comprehensive analysis of autophagy‐related prognostic genes in breast cancer

Accumulating evidence revealed that autophagy played vital roles in breast cancer (BC) progression. Thus, the aim of this study was to investigate the prognostic value of autophagy‐related genes (ARGs) and develop a ARG‐based model to evaluate 5‐year overall survival (OS) in BC patients. We acquired ARG expression profiling in a large BC cohort (N = 1007) from The Cancer Genome Atlas (TCGA) database. The correlation between ARGs and OS was confirmed by the LASSO and Cox regression analyses. A predictive model was established based on independent prognostic variables. Thus, time‐dependent receiver operating curve (ROC), calibration plot, decision curve and subgroup analysis were conducted to determine the predictive performance of ARG‐based model. Four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were identified using the LASSO and multivariate Cox regression analyses. A ARG‐based model was constructed based on the four ARGs and two clinicopathological risk factors (age and TNM stage), dividing patients into high‐risk and low‐risk groups. The 5‐year OS of patients in the low‐risk group was higher than that in the high‐risk group (P < 0.0001). Time‐dependent ROC at 5 years indicated that the four ARG–based tool had better prognostic accuracy than TNM stage in the training cohort (AUC: 0.731 vs 0.640, P < 0.01) and validation cohort (AUC: 0.804 vs 0.671, P < 0.01). The mutation frequencies of the four ARGs (ATG4A, IFNG, NRG1 and SERPINA1) were 0.9%, 2.8%, 8% and 1.3%, respectively. We built and verified a novel four ARG–based nomogram, a credible approach to predict 5‐year OS in BC, which can assist oncologists in determining effective therapeutic strategies.     

Comprehensive analysis of novel three-long noncoding RNA signatures as a diagnostic and prognostic biomarkers of human triple-negative breast cancer

Currently, traditional predictors of prognosis (tumor size, nodal status, progesterone receptor [PR], estrogen receptor [ER], or human epidermal growth factor receptor-2 [HER2]) are insufficient for precise survival prediction for triple-negative breast cancer (TNBC). Long noncoding RNAs (lncRNAs) have been observed to exert critical functions in cancer, including in TNBC. Nevertheless, systematically tracking expression-based lncRNA biomarkers based on the sequence data for the prediction of prognosis in TNBC has not yet been investigated. To ascertain whether biomarkers exist that can distinguish TNBC from adjacent normal tissue or nTNBC, we implemented a comprehensive analysis of lncRNA expression profiles and clinical data of 1097 BC samples from The Cancer Genome Atlas database. A total of 1510 differentially expressed lncRNAs in normal and TNBC samples were extracted. Similarly, 672 differentially expressed lncRNAs between nTNBC and TNBC samples were detected. The receiver operating characteristic curve analysis indicated that three upregulated lncRNAs (AC091043.1, AP000924.1, and FOXCUT) may be of strong diagnostic value for predicting the existence of TNBC in the training and validation sets (area under the curve (AUC > 0.85). Kaplan-Meier analysis demonstrated that the other three lncRNAs (AC010343.3, AL354793.1, and FGF10-AS1) were associated with the prognosis of TNBC patients (P < 0.05). We used the three overall survival (OS)-related lncRNAs to establish a three-lncRNA signature. Multivariate Cox regression analysis suggested that the three-lncRNA signature was a prognostic factor independent of other clinical variables ( P < 0.01) for predicting OS in TNBC patients that could be utilized to classify patients into high- or low-risk subgroups. Our results might provide efficient signatures for clinical diagnosis and prognostic evaluation of TNBC.     

Validation of CSN1S1 transcriptional expression,promoter methylation,and prognostic power in breast cancer using independent datasets

Breast cancer ranked second among most frequent cancer in the world playing a significant role in mortality rate. Having prior knowledge on differentially expressed genes in breast cell carcinoma elucidated important indications to understand the molecular mechanism underneath breast carcinogenesis. In this study we have investigated the distinguished CSN1S1 expression in human breast cancer. We have analyzed CSN1S1 mRNA expression between cancer and normal tissues using TCGA datasets. Moreover, analysis including promoter methylation, mutations, prognosis, co-expression, gene ontology, and pathways of CSN1S1 were performed by the TCGA Wanderer, UCSC Xena, cBioPortal, PrognoScan, UALCAN, and Enricher server. We have observed low mRNA expression and high promoter methylation of CSN1S1 in cancer tissues compared to normal tissues. Furthermore, we have also identified low mRNA expression in clinicopathological patients, as well as 9 deleterious mutations with highly co-expressed protein MRC1, and significantly related signaling pathways. We have found a positive correlation between the lower expression of CSN1S1 and patients surviving with breast cancer. Here we have concluded that CSN1S1 acts as a biomarker for the surveillance and prognosis of breast cancer, and also works as a novel therapeutic target at the molecular and pathway levels.     

Osteopontin in metastatic lesions as a prognostic marker in ovarian cancers

Summary Osteopontin (OPN) is expressed in various human cancers and associated with tumor progression, invasion and metastasis in many manners. The purpose of this study is to investigate the clinical significance of OPN expression in metastatic lesions of ovarian cancers, since the prognosis of the patients with peritoneal dissemination is extremely poor. In primary tumors and peritoneal metastatic lesions from 40 patients with stage III ovarian cancers, the protein levels of OPN and histoscores were determined by enzyme immunoassay and immunohistochemistry, respectively. Immunohistochemical staining revealed OPN was distributed in the cytoplasm and nuclear compartments of the cancer and stromal cells within and around the tumor. The OPN level was significantly (p < 0.05) increased in 32 of 40 metastatic lesions of ovarian cancers. The OPN increased cases identified by immunohistochemical staining were consistent with those identified by the sandwich immunoassay. The prognosis of the 32 patients with significant increase of OPN in ovarian cancers was extremely poor, whereas the 36-month survival rate of the 8 patients with no increase of OPN was 75%. Multivariate analysis revealed that the levels of OPN were independent predictors of prognosis from clinical characteristics (age, lesion size, histological types). OPN might be associated with peritoneal metastasis and its advancement, and that the OPN level in metastatic lesion may be a prognostic indicator in ovarian cancers.