BCAR4 induces antioestrogen resistance but sensitises breast cancer to lapatinib

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

BCAR4 Expression as a Predictive Biomarker for Endocrine Therapy Resistance in Breast Cancer

BACKGROUND

Breast cancer, particularly the estrogen receptor positive (ER+) subtype, remains a leading cause of cancer-related death among women. Endocrine therapy is the most effective treatment for ER+ breast cancer; however, the development of resistance presents a significant challenge. This study explored the role of the breast cancer antiestrogen resistance 4 (BCAR4) gene as a potential driver of resistance and a pivotal biomarker in breast cancer.

PATIENTS AND METHODS

The researchers undertook a comprehensive analysis of 1743 patients spanning 6 independent cohorts. They examined the association of BCAR4 expression with patient outcomes across all breast cancer types and the PAM50 molecular subtypes. The relationship between elevated BCAR4 expression and resistance to endocrine therapy including AIs, the prevailing standard-of-care for endocrine therapy, was also investigated.

RESULTS

This meta-analysis corroborated the link between BCAR4 expression and adverse outcomes as well as resistance to endocrine therapy in breast cancer. Notably, BCAR4 expression is clinically significant in luminal A and B subtypes. Additionally, an association between BCAR4 expression and resistance to AI treatment was discerned.

CONCLUSION

This study expands on previous findings by demonstrating that BCAR4 expression is associated with resistance to newer therapies. The identification of patients with intrinsic resistance to hormone therapy is crucial to avoid ineffective treatment strategies. These findings contribute to our understanding of endocrine therapy resistance in breast cancer and could potentially guide the development of more effective treatment strategies.

Molecular Mechanisms of Anti-Estrogen Therapy Resistance and Novel Targeted Therapies

Breast cancer (BC) is the most commonly diagnosed cancer in women, constituting one-third of all cancers in women, and it is the second leading cause of cancer-related deaths in the United States. Anti-estrogen therapies, such as selective estrogen receptor modulators, significantly improve survival in estrogen receptor-positive (ER+) BC patients, which represents about 70% of cases. However, about 60% of patients inevitably experience intrinsic or acquired resistance to anti-estrogen therapies, representing a major clinical problem that leads to relapse, metastasis, and patient deaths. The resistance mechanisms involve mutations of the direct targets of anti-estrogen therapies, compensatory survival pathways, as well as alterations in the expression of non-coding RNAs (e.g., microRNA) that regulate the activity of survival and signaling pathways. Although cyclin-dependent kinase 4/6 and phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) inhibitors have significantly improved survival, the efficacy of these therapies alone and in combination with anti-estrogen therapy for advanced ER+ BC, are not curative in advanced and metastatic disease. Therefore, understanding the molecular mechanisms causing treatment resistance is critical for developing highly effective therapies and improving patient survival. This review focuses on the key mechanisms that contribute to anti-estrogen therapy resistance and potential new treatment strategies alone and in combination with anti-estrogen drugs to improve the survival of BC patients.

Oncogenic fusion of BCAR4 activates EGFR signaling and is sensitive to dual inhibition of EGFR/HER2

We previously reported CD63-BCAR4 fusion as a novel oncogene that significantly enhanced cell migration and metastasis in lung cancer. To identify effective inhibitors of metastatic activity induced by BCAR4 fusion, we screened a drug library of 381 FDA-approved compounds. The effect of drugs on cell migration was evaluated by monitoring wound healing. Drugs that decreased the cellular mobility of fusion-overexpressing cells compared with that of control cells were selected as candidates. Library screening revealed that erlotinib, canertinib, and lapatinib demonstrated inhibitory effects on cell migration. Activation of the EGFR signaling pathway was detected after ectopic expression of CD63-BCAR4 in normal bronchial epithelial cells, as observed by the increased phosphorylation of tyrosine residues in the EGFR protein. We also confirmed increased levels of the phosphorylated EGFR protein in resected tumors from mice injected with CD63-BCAR4 overexpressing cells. Tyrosine kinase inhibitors (TKIs) of the EGFR family significantly inhibit the migration of BCAR4 fusion-overexpressing cells and induce apoptosis at high concentrations. Among the EGFR family TKIs, canertinib, a dual EGFR/HER2 inhibitor, showed the best inhibitory effect on the migration and viability of BCAR4 fusion-overexpressing cells. We examined the effect of canertinib in vivo using a mouse xenograft model. Oral administration of canertinib to xenografted mice reduced tumor growth induced by the CD63-BCAR4 fusion gene. In addition, canertinib treatment restored E-cadherin expression and reduced the expression of epithelial-mesenchymal transition regulatory factors such as Slug and Snail. Taken together, these results suggest that EGFR/HER2 inhibitors are potential therapeutic options for BCAR4 fusion-harboring lung cancer patients, even in the absence of EGFR mutations.

lncRNA-disease association prediction based on matrix decomposition of elastic network and collaborative filtering

In recent years, with the continuous development and innovation of high-throughput biotechnology, more and more evidence show that lncRNA plays an essential role in biological life activities and is related to the occurrence of various diseases. However, due to the high cost and time-consuming of traditional biological experiments, the number of associations between lncRNAs and diseases that rely on experiments to verify is minimal. Computer-aided study of lncRNA-disease association is an important method to study the development of the lncRNA-disease association. Using the existing data to establish a prediction model and predict the unknown lncRNA-disease association can make the biological experiment targeted and improve its accuracy of the biological experiment. Therefore, we need to find an accurate and efficient method to predict the relationship between lncRNA and diseases and help biologists complete the diagnosis and treatment of diseases. Most of the current lncRNA-disease association predictions do not consider the model instability caused by the actual data. Also, predictive models may produce data that overfit is not considered. This paper proposes a lncRNA-disease association prediction model (ENCFLDA) that combines an elastic network with matrix decomposition and collaborative filtering. This method uses the existing lncRNA-miRNA association data and miRNA-disease association data to predict the association between unknown lncRNA and disease, updates the matrix by matrix decomposition combined with the elastic network, and then obtains the final prediction matrix by collaborative filtering. This method uses the existing lncRNA-miRNA association data and miRNA-disease association data to predict the association of unknown lncRNAs with diseases. First, since the known lncRNA-disease association matrix is very sparse, the cosine similarity and KNN are used to update the lncRNA-disease association matrix. The matrix is then updated by matrix decomposition combined with an elastic net algorithm, to increase the stability of the overall prediction model and eliminate data overfitting. The final prediction matrix is then obtained through collaborative filtering based on lncRNA.Through simulation experiments, the results show that the AUC value of ENCFLDA can reach 0.9148 under the framework of LOOCV, which is higher than the prediction result of the latest model.

LncRNA BCAR4 expression and predicts the clinical response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

BACKGROUND

Neoadjuvant chemotherapy (NAC) is an important treatment for locally advanced breast cancer (LABC). However, there are no effective biomarkers to predict the efficacy. Therefore, there is an urgent need for new biomarkers to predict the response of LABC to NAC. LncRNA BCAR4 has been detected in a variety of malignant tumor tissues and used as a new biomarker for diagnosis and prognosis. However, LncRNA BCAR4 predicts the response of LABC to NAC is unclear.

OBJECTIVE

Explore the predictive effect of LncRNA BCAR4 on the efficacy of NAC for LABC in three different evaluation systems.

METHODS

First, the TCGA database was used to analyze the expression of LncRNA BCAR4 in 33 kinds of malignant tumors, and further explore its expression in breast cancer and its impact on the survival and prognosis of breast cancer. Furthermore, quantitative methods were used to measure the expression level of LncRNA BCAR4 in cancer tissues of 48 LABC patients, and the correlation between LncRNA BCAR4 and clinicopathological status and response to NAC under the evaluation system of 3, RECIST1.1, Miller-Payne (MP) score and whether it reaches pCR,was analyzed.

RESULTS

TCGA data analysis found that LncRNA is highly expressed in a variety of malignant tumor tissues, including breast cancer. And relatively low expression, the shorter the overall survival time of high expression patients. The high expression of LncRNA BCAR4 is related to the size of the tumor, and there are differences in expression between stage I and other stages, but there is no obvious correlation with the positive lymph node and hormone receptor status. Among the three evaluation systems, only in the RECIST 1.1 evaluation system LncRNA BCAR4 has a predictive effect on NAC for LABC. The expression of LncRNA BCAR4 has no significant correlation with clinical stage, Ki-67% and hormone receptor status, and has no significant correlation with whether patients with locally advanced breast cancer obtain pCR during neoadjuvant chemotherapy.

CONCLUSION

LncRNA BCAR4 is highly expressed in LABC tissues and may be an effective marker for predicting the efficacy of NAC for LABC.

LncRNA RUSC1-AS1 promotes osteosarcoma progression through regulating the miR-340-5p and PI3K/AKT pathway

Dysregulation of long noncoding RNA (lncRNA) is frequently involved in the progression and development of osteosarcoma. LncRNA RUSC1-AS1 is reported to be upregulated and acts as an oncogene in hepatocellular carcinoma, cervical cancer and breast cancer. However, its role in osteosarcoma has not been studied yet. In the present study, we investigated the role of RUSC1-AS1 in osteosarcoma both in vitro and in vivo. The results showed that the expression of RUSC1-AS1 was significantly upregulated in osteosarcoma cell line U2OS and HOS compared to that in human osteoblast cell line hFOB1.19. Similar results were found in human samples. Silencing RUSC1-AS1 by siRNA significantly inhibited U2OS and HOS cell proliferation and invasion, measured by CCK-8 and transwell assay. Besides, knockdown of RUSC1-AS1 increased cell apoptosis in osteosarcoma cell lines. In addition, RUSC1-AS1 promoted the epithelial-mesenchymal transition (EMT) process of osteosarcoma cells. In vivo experiments confirmed that RUSC1-AS1 knockdown had an inhibitory effect on osteosarcoma tumor growth. Mechanically, we showed that RUSC1-AS1 directly binds to and inhibits miR-340-5p and activates the PI3K/AKT signaling pathway. In conclusion, our study demonstrated that RUSC1-AS1 promoted osteosarcoma development both in vitro and in vivo through sponging to miR-340-5p and activating the PI3K/AKT signaling pathway. Therefore, RUSC1-AS1 becomes a potential therapeutic target for osteosarcoma.

The role of long non-coding RNA BCAR4 in human cancers

Long non-coding RNA (lncRNA) is a type of non-coding RNA with length of nucleotides > 200 bp. Increasing evidences show that lncRNA breast cancer antiestrogen resistance 4 (BCAR4) plays an important role in the occurrence and development of various human cancers. It is found that BCAR4 is highly expressed in diverse tumor tissues and cells, and the high expression of BCAR4 is usually associated with poor prognosis. BCAR4 is considered as an oncogene in human cancers. By competing endogenous RNA (ceRNA) mechanism and regulating different signaling pathways, BCAR4 participates in the proliferation, apoptosis, migration, invasion, epithelial-mesenchymal transition (EMT), metastasis and tumorigenesis of different cancers. In addition, overexpression of BCAR4 promotes drug resistance of tumor cells. Therefore, BCAR4 is a promising biomarker for cancer diagnosis and prognosis, and it is a potential target for cancer therapy. This paper reviews studies focusing on the relationship between BCAR4 and cancers in recent years and aims to summarize the effect and mechanism of BCAR4 in human cancers.

New insights into long non-coding RNAs in breast cancer: Biological functions and therapeutic prospects

Breast cancer (BC) has become one of the most common malignant tumors in the world, seriously endangering women's health and life. However, the underlying molecular mechanisms of BC remain unclear. Over the past decade, long non-coding RNAs (lncRNAs) were gradually discovered and appreciated to play pivotal regulatory role in the progression of BC. It has been demonstrated that lncRNAs are implicated in regulating plenty of biological phenomena including cell proliferation, apoptosis, invasion and metastasis by interacting with DNA, RNA or proteins. In addition to these, the function of lncRNAs in tumor resistance has increasingly attracted more attention. In this review, we summarized the emerging impact of lncRNAs on the occurrence and progression of human BC, specifically focusing on the functions and mechanisms of them, with the aim of exploring the potential value of lncRNAs as oncogenic drivers or tumor suppressors. Furthermore, the potential clinical application of lncRNAs as diagnostic biomarkers and therapeutic targets in BC was also discussed.

Evaluating human epidermal growth factor receptor 2 roles in the efficacy of Tamoxifen treatment in breast cancer, a systematic review

PURPOSE

Hormone therapy with Tamoxifen is an effective treatment that can decrease recurrence rate and mortality. Numerous molecular mechanisms can modify the response to Tamoxifen. The objective of this study was to determine Tamoxifen efficacy on patients' recurrence and mortality rates, according to the human epidermal growth factor receptor 2 (HER2) status.

METHODS

In this meta-analysis of published studies, relapse and death rates were measured in both HER2 negative and positive patients treated with Tamoxifen. Besides, the relative risk of treatment with Tamoxifen compared to no Tamoxifen treatment was evaluated in both HER2 positive and negative patients.

RESULTS

There was an increased risk of recurrence in HER2 positive patients who received Tamoxifen compared with HER2 negative ones (RR = 1.63, p value < 0.001). Tamoxifen treatment is associated with decreased relapse rate (RR = 0.70, p value < 0.001); however, it did not effect on HER2 positive ones (RR = 1, p value = 0.99).

CONCLUSION

According to the analysis result, the relapse rate in breast cancer patients who were treated with Tamoxifen depends on the HER2 situation. Despite the limited sample size, it is revealed that Tamoxifen can decrease the relapse rate only in HER2 negative patients.

Long non-coding RNA BCAR4 aggravated proliferation and migration in esophageal squamous cell carcinoma by negatively regulating p53/p21 signaling pathway

Long non-coding RNA breast cancer antiestrogen resistance 4 (lncRNA BCAR4) is an independent factor on the survival prognosis of patients with multiple cancers. However, the role of lncRNA BCAR4 in esophageal squamous cell cancer (ESCC) remains unknown. Here, we unraveled that lncRNA BCAR4 was upregulated in ESCC and predicted poor prognosis. Functionally, lncRNA BCAR4 knockdown induced cell apoptosis and G1/S arrest, while inhibited cell proliferation and migration in vitro; conversely, overexpressing lncRNA BCAR4 promoted proliferation and metastasis. Mechanistically, lncRNA BCAR4 sponged miR-139-3p to upregulate ELAVL1, thereby inhibiting p53/p21 pathway in ESCC cells. In conclusion, lncRNA BCAR4 promotes ESCC tumorigenesis via regulating p53/p21 signaling pathway and develops a brand-new biomarker and medicine target for ESCC.

WGRCMF: A Weighted Graph Regularized Collaborative Matrix Factorization Method for Predicting Novel LncRNA-Disease Associations

In recent years, many human diseases have been determined to be associated with certain lncRNAs. Only a small percentage of all lncRNA-disease associations (LDAs) have been discovered by researchers. Predicting novel LDAs is time-consuming and costly. It is crucial to propose a method that can effectively identify potential LDAs to solve this problem based on the available datasets. Although some current methods can effectively predict potential LDAs, the prediction accuracy needs to be improved, and there are few known associations. Moreover, there are notable errors in the method of constructing the network and the bipartite graph, which interfere with the final results. A weighted graph regularized collaborative matrix factorization (WGRCMF) method is proposed to predict novel LDAs. We introduce the graph regularization terms into the collaborative matrix factorization. Considering that manifold learning can recover low-dimensional manifold structures from high-dimensional sampled data, we can find low-dimensional manifolds in high-dimensional space. In addition, a weight matrix is also introduced into the method, the significance of which is to prevent unknown associations from contributing to the final prediction matrix. Finally, the prediction accuracy of this method is better than those of other methods. In several cancer cases, we implemented the corresponding simulation experiments. According to the experimental results, the proposed method is feasible and effective.

A fusion of CD63-BCAR4 identified in lung adenocarcinoma promotes tumorigenicity and metastasis

Background

Recently, fusion variants of the breast cancer anti-oestrogen-resistance 4 (BCAR4) gene were recurrently discovered in lung adenocarcinoma from the genome-wide studies. However, the functional characterisation of BCAR4 fusion has not been investigated.

Methods

Based on the analysis of RNA-sequencing data, we identified a fusion transcript of CD63–BCAR4 in a Korean patient with lung adenocarcinoma who did not harbour any known activating mutations in EGFR and KRAS genes. To investigate the oncogenic effect of CD63–BCAR4, in vitro and in vivo animal experiments were performed.

Results

In vitro experiments showed strongly enhanced cell migration and proliferation by the exogenous expression of CD63–BCAR4 protein in bronchial epithelial cells. Cell migration was notably reduced after knockdown of BCAR4 fusion by small-interfering RNA. The tumorigenic and metastatic capability of the CD63–BCAR4 fusion was confirmed by using the mouse xenograft model. Fusion-overexpressed cells result in metastasis to the liver and lung as well as the primary tumours after subcutaneous injection into mice. Cyclin D1, MMP1, Slug and mesenchymal markers were significantly increased after CD63–BCAR4 overexpression in the in vitro and in vivo experiments.

Conclusions

Taken together, our results suggest a newly identified fusion gene, CD63–BCAR4 as a potential novel oncogene in lung adenocarcinoma.

Variant in BCAR4 gene correlated with the breast cancer susceptibility and mRNA expression of lncRNA BCAR4 in Chinese Han population

BACKGROUND

Long non-coding RNA (LncRNA) Breast cancer anti-estrogen resistance 4 (BCAR4) has been shown to participate in the biological progress of various cancers including breast cancer. Genetic Polymorphisms in BCAR4 may have an influence on the progress of breast cancer, but it is rarely studied.

METHODS

In our epidemiology study, three tagging SNPs (rs4561483, rs11649623 and rs13334967) in lncRNA BCAR4 were selected for genotyping among 487 breast cancer cases and 489 healthy controls. And quantitative real-time PCR (qRT-PCR) was performed to evaluate the relative mRNA expression of BCAR4 in different genotypes of the significant locus rs13334967.

RESULTS

We found that BCAR4 rs13334967 is associated with lower breast cancer risk both in codominant model (AT vs AA, OR 0.632, 95% CI 0.429-0.931, TT vs AA, OR 0.731, 95% CI 0.511-0.990) and dominant model (AT + TT vs AA, OR 0.798, 95% CI 0.571-0.970). The further results of qRT-PCR displayed that carriers with rs13334967 AT, TT genotype have lower BCAR4 mRNA expression compared with AA genotype.

CONCLUSION

The research study implied that BCAR4 rs13334967 was correlated with the susceptibility to breast cancer and may impact the mRNA expression of BCAR4. LncRNA BCAR4 may be a potential biomarker and therapeutic target for breast cancer.

Connecting the Missing Dots: ncRNAs as Critical Regulators of Therapeutic Susceptibility in Breast Cancer

Whether acquired or de novo, drug resistance remains a significant hurdle in achieving therapeutic success in breast cancer (BC). Thus, there is an urge to find reliable biomarkers that will help in predicting the therapeutic response. Stable and easily accessible molecules such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are regarded as valuable prognostic biomarkers and therapeutic targets since they act as crucial regulators of the various mechanisms involved in BC drug resistance. Here, we reviewed the current literature on ncRNAs as mediators of resistance to systemic therapies in BC. Interestingly, upon integrating data results from individual studies, we concluded that miR-221, miR-222, miR-451, Urothelial Carcinoma Associated 1 (UCA1), and Growth arrest-specific 5 (GAS5) are strong candidates as prognostic biomarkers and therapeutic targets since they are regulating multiple drug resistance phenotypes in BC. However, further research around their clinical implications is needed to validate and integrate them into therapeutic applications. Therefore, we believe that our review may provide relevant evidence for the selection of novel therapeutic targets and prognostic biomarkers for BC and will serve as a foundation for future translational research in the field.

Long non-coding RNA regulation of TRAIL in breast cancer: A tangle of non-coding threads

Breast cancer is a complex disease posing a serious threat to the female population worldwide. A complex molecular landscape and tumor heterogeneity render breast cancer cells resistant to drugs and able to promote metastasis and invasiveness. Despite the recent advancements in diagnostics and drug discovery, finding an effective cure for breast cancer is still a major challenge. Positive and negative regulation of apoptosis has been a subject of extensive study over the years. Numerous studies have shed light on the mechanisms that impede the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) signaling cascade. Long non-coding RNAs (lncRNAs) have been implicated in the orchestration, development, proliferation, differentiation and metastasis of breast cancer. However, the roles of lncRNAs in fine-tuning apoptosis regulating machinery in breast cancer remain to be elucidated. The present review illuminates the roles of these molecules in the regulation of breast cancer and the interplay between lncRNA and TRAIL in breast cancer. The present review also attempts to reveal their role in the regulation of apoptosis in breast cancer appears a promising approach for the development of new diagnostic and therapeutic regimens.

Long non-coding RNA BCAR4 promotes liver cancer progression by regulating proliferation, migration and invasion

Liver cancer (LC) is one of the primary contributors of cancer-associated death worldwide. Long non-coding RNAs (lncRNAs) have been shown to participate in almost every aspect of cell biology and serve fundamental roles in carcinogenesis and cancer progression, including in LC. However, the clinical significance and functional role of the lncRNA breast cancer anti-estrogen resistance 4 (BCAR4) in LC have not yet been identified. The present study measured the expression levels of BCAR4 in LC cells and tissues, and discovered that BCAR4 was upregulated in LC tissues compared with adjacent normal tissues. Furthermore, high BCAR4 expression was associated with the presence of multiple tumors and advanced Tumor-Node-Metastasis stages (III/IV). Survival analysis found that high BCAR4 expression indicated poor overall survival (OS) and progression-free survival (PFS). By analyzing the risk factors of poor OS and PFS using univariate analysis and multivariate analysis, high BCAR4 expression was revealed to be an independent risk factor of poor prognosis. In addition, the role of BCAR4 was further investigated in vitro, which revealed overexpression of BCAR4 to markedly promote the proliferation, migration and invasion of LC cells. Conversely, the loss of BCAR4 expression repressed the proliferation, migration and invasion of LC cells. In conclusion, BCAR4 is overexpressed in LC and is associated with LC progression. Therefore, BCAR4 may be used as a potential prognostic marker in LC.

MET ectodomain shedding is associated with poor disease-free survival of patients diagnosed with oral squamous cell carcinoma

Ectodomain shedding unleashes the aggressive nature of the MET oncogene product. Using specific C- and N-terminal MET antibodies (D1C2 and A2H2-3), MET protein status (i.e., no MET, decoy MET, transmembranous C-terminal MET with or without the ectodomain) was investigated in oral squamous cell carcinoma. For the cancers showing transmembranous C-terminal MET, the impact of ectodomain shedding on prognosis was investigated. To examine ectodomain shedding, reduced lysates of oral squamous cell carcinoma cell lines were immunoblotted using D1C2 and an ELISA was performed on culture media using A2H2-3. In addition, reduced lysates of fresh frozen tissues of 30 oral squamous cell carcinoma were immunoblotted using D1C2 and immunohistochemistry was performed on corresponding formalin-fixed paraffin-embedded tissues using both antibodies on parallel sections. To examine MET protein status, differences between membranous D1C2 and A2H2-3 immunoreactivities were scored using parallel tissue microarray sections representing 156 oral squamous cell carcinoma. The prognostic value of ectodomain shedding was examined using Cox regression analysis for disease-free survival and overall survival. Ectodomain shedding was observed in all cell lines, 43% (n = 13) of fresh frozen and 50% (n = 15) of formalin-fixed paraffin-embedded cancers (27% overlap, n = 8). The tissue microarray showed no MET in 23% (n = 36), decoy MET in 9% (n = 14), and transmembranous C-terminal MET in 68% (n = 106) of examined cancers. Within the latter group, ectodomain shedding occurs in 36% (n = 38) of the cases and is independently associated with poor disease-free survival (HR = 2.41; 95% CI, 1.35-4.30 and P = 0.003)-though not overall survival (HR = 1.64; 95% CI, 0.92-2.94 and P = 0.095)-after correcting for factors known to influence survival. In conclusion, MET ectodomain shedding occurs in transmembranous C-terminal MET positive oral squamous cell carcinoma and is independently associated with disease-free survival. These findings might aid in designing companion diagnostics for targeted therapies directed against MET.

Long Noncoding RNAs Involved in the Endocrine Therapy Resistance of Breast Cancer

Long noncoding RNAs (lncRNAs) are defined as RNAs longer than 200 nucleotides that do not encode proteins. Recent studies have demonstrated that numerous lncRNAs are expressed in humans and play key roles in the development of various types of cancers. Intriguingly, some lncRNAs have been demonstrated to be involved in endocrine therapy resistance for breast cancer through their own mechanisms, suggesting that lncRNAs could be promising new biomarkers and therapeutic targets of breast cancer. Here, we summarize the functions and mechanisms of lncRNAs related to the endocrine therapy resistance of breast cancer.

Inferring LncRNA-disease associations based on graph autoencoder matrix completion

Accumulating studies have indicated that long non-coding RNAs (lncRNAs) play crucial roles in large amount of biological processes. Predicting lncRNA-disease associations can help biologist to understand the molecular mechanism of human disease and benefit for disease diagnosis, treatment and prevention. In this paper, we introduce a computational framework based on graph autoencoder matrix completion (GAMCLDA) to identify lncRNA-disease associations. In our method, the graph convolutional network is utilized to encode local graph structure and features of nodes for learning latent factor vectors of lncRNA and disease. Further, the inner product of lncRNA factor vector and disease factor vector is used as decoder to reconstruct the lncRNA-disease association matrix. In addition, the cost-sensitive neural network is utilized to deal with the imbalance between positive and negative samples. The experimental results show GAMLDA outperforms other state-of-the-art methods in prediction performance which is evaluated by AUC value, AUPR value, PPV and F1-score. Moreover, the case study shows our method is the effectively tool for potential lncRNA-disease prediction.

LncRNA BCAR4 promotes liver cancer progression by upregulating ANAPC11 expression through sponging miR‑1261

Liver cancer is a malignant tumor that occurs in the liver and can be divided into primary and secondary liver cancer. Long non-coding RNA (lncRNA) breast cancer anti-estrogen resistance 4 (BCAR4) has been demonstrated to promote the development of various types of cancer. However, the function of lncRNA BCAR4 in liver cancer remains unclear. In the present study, the expression of lncRNA BCAR4 was notably elevated in liver cancer compared with adjacent non-tumor tissues. Functional in vitro assays demonstrated that knockdown of lncRNA BCAR4 inhibited the proliferation, migration and invasion of Huh-7 cells. In addition, lncRNA BCAR4 was demonstrated to directly bind to microRNA (miR)-1261, and miR-1261 expression negatively correlated with the expression of lncRNA BCAR4. Through bioinformatics analysis, lncRNA BCAR4 was predicted to target anaphase-promoting complex subunit 11 (ANAPC11) through miR-1261. In addition, the results demonstrated that lncRNA BCAR4 increased the expression of ANAPC11 by inhibiting miR-1261 expression. Consistently, overexpression of ANAPC11 or inhibition of miR-1261 significantly rescued liver cancer cell proliferation induced by knockdown of lncRNA BCAR4. Collectively, the results of the present study demonstrated that lncRNA BCAR4 may promote liver cancer development by directly binding to miR-1261 and targeting ANAPC11.

LncRNA NONHSAT141924 promotes paclitaxel chemotherapy resistance through p-CREB/Bcl-2 apoptosis signaling pathway in breast cancer

Breast cancer is the most prevalent malignant neoplasm among women worldwide. Despite continuous improvement of breast cancer individualized comprehensive therapy, local recurrence and distant metastasis still remain the challenges due to the development of acquired drug-resistance. Long non-coding RNAs (LncRNAs) is known to participated in the development of breast cancer. However, the mechanisms of LncRNAs involving in drug-resistance of breast cancer during chemotherapy remain to be further elucidated. Aiming to screen for candidate LncRNAs responsible for breast cancer mechanism, we first investigated the expression patterns of LncRNAs and mRNAs in paired breast cancer tissues and normal tissues using Agilent Human lncRNA array. The microarray results clearly demonstrated multiple differentially expressed mRNAs and LncRNAs including LncRNA NONHSAT141924. The remarkable up-regulation of LncRNA NONHSAT141924 in breast cancer MCF-7 was further confirmed by quantitative real-time PCR. GO and KEGG pathway analysis demonstrated that LncRNA NONHSAT141924 was most closely associated with paclitaxel (PTX)-resistant phenotype. To further explore the mechanism by which LncRNA NONHSAT141924 contributes to PTX-resistant characteristics, LncRNA NONHSAT141924 was transfected into MCF-7 breast cancer cell line. Overexpression of LncRNA NONHSAT141924 significantly reduced MCF-7 cell survivability through modulation of p-CREB/Bcl-2 apoptosis signaling pathway, one of the major pathways participated in LncRNAs-mediated chemotherapy resistance. Taken together, our study provides a new LncRNA-mediated regulatory mechanism for PTX-resistance of breast cancer and suggests that therapeutic inhibition of LncRNA NONHSAT141924 might be an efficient strategy for PTX-resistant breast cancer treatment.

Integration of Comprehensive Genomic Analysis and Functional Screening of Affected Molecular Pathways to Inform Cancer Therapy

OBJECTIVE

To select optimal therapies based on the detection of actionable genomic alterations in tumor samples is a major challenge in precision medicine.

METHODS

We describe an effective process (opened December 1, 2017) that combines comprehensive genomic and transcriptomic tumor profiling, custom algorithms and visualization software for data integration, and preclinical 3-dimensiona ex vivo models for drug screening to assess response to therapeutic agents targeting specific genomic alterations. The process was applied to a patient with widely metastatic, weakly hormone receptor positive, HER2 nonamplified, infiltrating lobular breast cancer refractory to standard therapy.

RESULTS

Clinical testing of liver metastasis identified BRIP1, NF1, CDH1, RB1, and TP53 mutations pointing to potential therapies including PARP, MEK/RAF, and CDK inhibitors. The comprehensive genomic analysis identified 395 mutations and several structural rearrangements that resulted in loss of function of 36 genes. Meta-analysis revealed biallelic inactivation of TP53, CDH1, FOXA1, and NIN, whereas only one allele of NF1 and BRIP1 was mutated. A novel ERBB2 somatic mutation of undetermined significance (P702L), high expression of both mutated and wild-type ERBB2 transcripts, high expression of ERBB3, and a LITAF-BCAR4 fusion resulting in BCAR4 overexpression pointed toward ERBB-related therapies. Ex vivo analysis validated the ERBB-related therapies and invalidated therapies targeting mutations in BRIP1 and NF1. Systemic patient therapy with afatinib, a HER1/HER2/HER4 small molecule inhibitor, resulted in a near complete radiographic response by 3 months.

CONCLUSION

Unlike clinical testing, the combination of tumor profiling, data integration, and functional validation accurately assessed driver alterations and predicted effective treatment.

The Role of Long Noncoding RNAs in Antiestrogen Resistance in Breast Cancer: An Overview and Update

As a standard treatment, endocrine therapy has dramatically enhanced the prognosis of patients with estrogen receptor (ER)-positive breast cancer, which accounts for nearly 70% of all breast cancers. Antiestrogen drugs such as tamoxifen and aromatase inhibitors are the standard treatment options for ERα-positive breast cancer. However, acquired antiestrogen resistance is still the leading cause of disease recurrence and progression. Evidence has shown that long noncoding RNAs (lncRNAs) play an essential role in the development of antiestrogen resistance in ER-positive breast cancer and can serve as biomarkers or potential therapeutic targets. This review highlights the role of lncRNAs in the development of antiestrogen resistance in breast cancer.

Toward a holistic view of multiscale breast cancer molecular biomarkers

Powered by rapid technology developments, biomarkers become increasingly diverse, including those detected at genomic, transcriptomic, proteomic, metabolomic and cellular levels. While diverse sets of biomarkers have been utilized in breast cancer predisposition, diagnosis, prognosis, treatment and management, recent additions derived from lincRNA, circular RNA, circulating DNA together with its methylated and hydroxymethylated forms and immune signatures are likely to further transform clinical practice. Here, we take breast cancer as an example of heterogeneous diseases that require many informed decisions from treatment to care to review the huge variety of biomarkers. By assessing the advantages and limitations of modern biomarkers in diverse use scenarios, this article outlines the prospects and challenges of releasing complimentary advantages by augmentation of multiscale molecular biomarkers.

The Value of LncRNA BCAR4 as a Prognostic Biomarker on Clinical Outcomes in Human Cancers

Background: This updated meta-analysis aimed to analyze available data to explore the prognostic value of long noncoding RNA breast cancer anti-estrogen resistance 4 (BCAR4) in various human malignancies. Methods: Literature retrieval was performed by systematic searching several authoritative databases, including Pubmed, PMC database, Web of Science, the Cochrane Library, Embase, and CNKI database up to Feb 10, 2019. Data were extracted and subsequently crosschecked, and discrepancies were discussed to reach consensus. Quality of the eligible studies was evaluated by Newcastle-Ottawa Scale (NOS). The fixed- or random-effects model was used to calculate the pooled the hazard ratios (HRs) or odds ratios (ORs) and the 95% confidence interval (95% CI). Publication bias was detected by using Begg's funnel plot and Egger's test. Results: A total 1,128 cancer patients from thirteen studies were included and pooled in the present meta-analysis. High expression levels of BCAR4 were correlated with unfavorable overall survival (OS) (HR=2.23, 95% CI: 1.84-2.71), but not progression-free survival (PFS) (HR=1.30, 95% CI: 0.80-2.11). Subgroup stratified analysis showed that tumor type, sample size, follow-up months, and survival analysis method did not alter the predictive value of BCAR4 on OS in various cancers. Furthermore, elevated BCAR4 level was markedly correlated with advanced clinical stage (III/IV) (OR=3.28, 95% CI: 2.33-4.60), and dramatically predicted lymph node metastasis (OR=3.00, 95% CI: 1.95-4.63, P<0.00001) and distant metastasis (OR=3.36, 95% CI: 1.88-5.98, P<0.0001), but not associated with age, gender or tumor size. No obvious heterogeneity was noted for correlation between BCAR4 expression and OS across these studies. Conclusions: High expression of BCAR4 was correlated with unfavorable overall survival outcome and clinical features including metastasis and progression, implicating an independent prognostic value for BCAR4 in human cancers.

LINC00309 is associated with short disease-free survival in breast cancer

Background

Long non-coding RNAs play an important role in breast cancer. Even with adjuvant hormone therapy, patients with estrogen receptor positive breast cancer can present with recurrences and distant metastases. We investigated whether the expression of a novel long non-coding RNA LINC00309 can predict the outcome of breast cancer, especially for hormone-receptor positive patients.

Methods

This retrospective study collected 290 breast cancer patients including 161 patients with hormone-positive. qPCR was performed to detect the expression of LINC00309. Kaplan–Meier and Cox risk proportion model were applied to disclose the function of LINC00309 for breast cancer prognosis.

Results

LINC00309 high expression was an independent predictor for worse disease-free survival (HR = 2.127; 95% CI 1.074–4.212; p = 0.030) and associated with a shorter disease-free survival (p = 0.027), especially in hormone-positive breast cancer patients (p = 0.001). Also LINC00309 high expression was associated with a shorter disease-free survival both in selective estrogen receptor modulator related hormone therapy (p = 0.025) and aromatase inhibitors related hormone therapy (p = 0.048). Moreover, LINC00309 was an independent predictor of worse disease-free survival in hormone-receptor positive breast cancer patients on univariate (HR = 4.505; 95% CI 1.722–11.785; p = 0.002) and multivariate (HR = 4.159; 95% CI 1.537–11.251; p = 0.005) analyses.

Conclusion

In breast cancer, Linc00309 is significantly associated with poor prognosis and may represent a new marker of prognosis.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0887-x) contains supplementary material, which is available to authorized users.

Matrix factorization-based data fusion for the prediction of lncRNA-disease associations

Motivation

Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be.

Results

To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological entities.

Availability and implementation

The source code for MFLDA is available at: http://mlda.swu.edu.cn/codes.php? name = MFLDA.

Contact

gxyu@swu.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Prognostic value of long non-coding RNA breast cancer anti-estrogen resistance 4 in human cancers: A meta-analysis

BACKGROUND

Since long non-coding RNA breast cancer anti-estrogen resistance 4 (lncRNA BCAR4) is dysregulated in various types of cancers, we conducted a meta-analysis to determine its prognostic value in cancer.

METHODS

PubMed, EMBASE database, and CENTRAL were systematically searched.Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were collected to estimate the prognostic value. Odds ratios (ORs) and their 95% CIs were used to assess the association between lncRNA BCAR4 expression and clinicopathological features, including tumor size, differentiation, lymph node metastasis, distant metastasis, and tumor stage.

RESULTS

Ten studies with 890 patients were included in this meta-analysis. The pooled results indicated that high lncRNA BCAR4 expression was associated with poor overall survival (OS) (HR 2.80, 95% CI: 2.08-3.78; P < .001). Overexpression of lncRNA BCAR4 was related to lymph node metastasis (OR 3.68, 95% CI: 2.25-6.00; P < .001), high tumor stage (OR 3.19, 95% CI: 1.98-5.13; P < .001), and distant metastasis (OR 3.83, 95% CI: 2.15-6.82; P < .001), but not to tumor size.

CONCLUSIONS

Therefore, lncRNA BCAR4 overexpression is associated with poor OS and advanced clinicopathological features, and lncRNA BCAR4 may be a novel prognostic biomarker in cancer patients. However, further high-quality studies are needed to confirm these findings.

Cervical cancer

Each year, more than half a million women are diagnosed with cervical cancer and the disease results in over 300 000 deaths worldwide. High-risk subtypes of the human papilloma virus (HPV) are the cause of the disease in most cases. The disease is largely preventable. Approximately 90% of cervical cancers occur in low-income and middle-income countries that lack organised screening and HPV vaccination programmes. In high-income countries, cervical cancer incidence and mortality have more than halved over the past 30 years since the introduction of formal screening programmes. Treatment depends on disease extent at diagnosis and locally available resources, and might involve radical hysterectomy or chemoradiation, or a combination of both. Conservative, fertility-preserving surgical procedures have become standard of care for women with low-risk, early-stage disease. Advances in radiotherapy technology, such as intensity-modulated radiotherapy, have resulted in less treatment-related toxicity for women with locally-advanced disease. For women with metastatic or recurrent disease, the overall prognosis remains poor; nevertheless, the incorporation of the anti-VEGF agent bevacizumab has been able to extend overall survival beyond 12 months. Preliminary results of novel immunotherapeutic approaches, similarly to other solid tumours, have shown promising results so far.

Long noncoding RNA ATB promotes the epithelial-mesenchymal transition by upregulating the miR-200c/Twist1 axe and predicts poor prognosis in breast cancer

Recent studies indicate that the long noncoding RNA ATB (lncATB) can induce the epithelial−mesenchymal transition (EMT) in cancer cells, but the specific cellular targets of lncATB require further investigation. In the present study, the upregulation of lncATB in breast cancer cells was validated in a TGF-β-induced EMT model. Gain- and loss-of-function studies demonstrated that lncATB enhanced cell migration, invasion and clonogenicity in vitro and in vivo. LncATB promoted the EMT by acting as a sponge for the miR-200 family and restoring Twist1 expression. Subsequently, the clinical significance of lncATB was investigated in a cohort of breast cancer patients (N = 131). Higher lncATB expression was correlated with increased nodal metastasis (P = 0.036) and advanced clinical stage (P = 0.011) as well as shorter disease-free survival (P = 0.043) and overall survival (P = 0.046). These findings define Twist1 as a major target of lncATB in the induction of the EMT and highlight lncATB as a biomarker in breast cancer patients.

Long non-coding RNAs: implications in targeted diagnoses, prognosis, and improved therapeutic strategies in human non- and triple-negative breast cancer

Triple-negative breast cancer (TNBC) has been clinically difficult to manage because of tumor aggressiveness, cellular and histological heterogeneity, and molecular mechanisms’ complexity. All this in turn leads us to evaluate that tumor biological behavior is not yet fully understood. Additionally, the heterogeneity of tumor cells represents a great biomedicine challenge in terms of the complex molecular—genetical-transcriptional and epigenetical—mechanisms, which have not been fully elucidated on human solid tumors.

Recently, human breast cancer, but specifically TNBC is under basic and clinical-oncology research in the discovery of new molecular biomarkers and/or therapeutic targets to improve treatment responses, as well as for seeking algorithms for patient stratification, seeking a positive impact in clinical-oncology outcomes and life quality on breast cancer patients.

In this sense, important knowledge is emerging regarding several cancer molecular aberrations, including higher genetic mutational rates, LOH, CNV, chromosomal, and epigenetic alterations, as well as transcriptome aberrations in terms of the total gene-coding ribonucleic acids (RNAs), known as mRNAs, as well as non-coding RNA (ncRNA) sequences. In this regard, novel investigation fields have included microRNAs (miRNAs), as well as long ncRNAs (lncRNAs), which have been importantly related and are likely involved in the induction, promotion, progression, and/or clinical therapeutic response trackers of TNBC. Based on this, in general terms according with the five functional archetype classification, the lncRNAs may be involved in the regulation of several molecular mechanisms which include genetic expression, epigenetic, transcriptional, and/or post-transcriptional mechanisms, which are nowadays not totally understood.

Here, we have reviewed the main dis-regulated and functionally non- and well-characterized lncRNAs and their likely involvement, from a molecular enrichment and mechanistic point of view, as tumor biomarkers for breast cancer and its specific histological subtype, TNBC. In reference to the abovementioned, it has been described that some lncRNA expression profiles correspond or are associated with the TNBC histological subtype, potentially granting their use for TNBC malignant progression, diagnosis, tumor clinical stage, and likely therapy. Based on this, lncRNAs have been proposed as potential biomarkers which might represent potential predictive tools in the differentiated breast carcinomas versus TNBC malignant disease. Finally, elucidation of the specific or multi-functional archetypal of lncRNAs in breast cancer and TNBC could be fundamental, as these molecular intermediary-regulator “lncRNAs” are widely involved in the genome expression, epigenome regulation, and transcriptional and post-transcriptional tumor biology, which in turn will probably represent a new prospect in clinical and/or therapeutic molecular targets for the oncological management of breast carcinomas in general and also for TNBC patients.

Deciphering the roles of lncRNAs in breast development and disease

Breast cancer is the second leading cause of cancer related deaths in women. It is therefore important to understand the mechanisms underlying breast cancer development as well as raises the need for enhanced, non-invasive strategies for novel prognostic and diagnostic methods. The emergence of long non-coding RNAs (lncRNAs) as potential key players in neoplastic disease has received considerable attention over the past few years. This relatively new class of molecular regulators has been shown from ongoing research to act as critical players for key biological processes. Deregulated expression levels of lncRNAs have been observed in a number of cancers including breast cancer. Furthermore, lncRNAs have been linked to breast cancer initiation, progression, metastases and to limit sensitivity to certain targeted therapeutics. In this review we provide an update on the lncRNAs associated with breast cancer and mammary gland development and illustrate the versatility of such lncRNAs in gene control, differentiation and development both in normal physiological conditions and in diseased states. We also highlight the therapeutic and diagnostic potential of lncRNAs in cancer.

The long non-coding RNA EPB41L4A-AS2 inhibits tumor proliferation and is associated with favorable prognoses in breast cancer and other solid tumors

EPB41L4A-AS2 is a novel long non-coding RNA of unknown function. In this study, we investigated the expression of EPB41L4A-AS2 in breast cancer tissues and evaluated its relationship with the clinicopathological features and prognosis of patients with breast cancer. This entailed conducting a meta-analysis and prognosis validation study using two cohorts from the Gene Expression Omnibus (GEO). In addition, we assessed EPB41L4A-AS2 expression and its relationship with the clinicopathological features of renal and lung cancers using the Cancer Genome Atlas cohort and a GEO dataset. We also clarified the role of EPB41L4A-AS2 expression in mediating cancer cell proliferation in breast, renal, and lung cancer cell lines transfected with an EPB41L4A-AS2 expression vector. We found that high EPB41L4A-AS2 expression is associated with favorable disease outcomes. Gene ontology enrichment analysis revealed that EPB41L4A-AS2 may be involved in processes associated with tumor biology. Finally, overexpression of EPB41L4A-AS2 inhibited tumor cell proliferation in breast, renal, and lung cancer cell lines. Our clinical and in vitro results suggest that EPB41L4A-AS2 inhibits solid tumor formation and that evaluation of this long non-coding RNA may have prognostic value in the clinical management of such malignancies.

Absent and abundant MET immunoreactivity is associated with poor prognosis of patients with oral and oropharyngeal squamous cell carcinoma

Although the receptor tyrosine kinase (RTK) MET is widely expressed in head and neck squamous cell carcinoma (HNSCC), its prognostic value remains unclear. This might be due to the use of a variety of antibodies and scoring systems. Here, the reliability of five commercial C-terminal MET antibodies (D1C2, CVD13, SP44, C-12 and C-28) was evaluated before examining the prognostic value of MET immunoreactivity in HNSCC. Using cancer cell lines, it was shown that D1C2 and CVD13 specifically detect MET under reducing, native and formalin-fixed paraffin-embedded (FFPE) conditions. Immunohistochemical staining of routinely FFPE oral SCC with D1C2 and CVD13 demonstrated that D1C2 is most sensitive in the detection of membranous MET. Examination of membranous D1C2 immunoreactivity with 179 FFPE oral and oropharyngeal SCC – represented in a tissue microarray – illustrated that staining is either uniform (negative or positive) across tumors or differs between a tumor's center and periphery. Ultimately, statistical analysis revealed that D1C2 uniform staining is significantly associated with poor 5-year overall and disease free survival of patients lacking vasoinvasive growth (HR = 3.019, p < 0.001; HR = 2.559, p < 0.001). These findings might contribute to reliable stratification of patients eligible for treatment with biologicals directed against MET.

LncRNA BCAR4 promotes colon cancer progression via activating Wnt/β-catenin signaling

BCAR4 (Breast Cancer Anti-Estrogen Resistance 4) is a long noncoding RNA that was identified as an oncogene in breast cancer. In our research, we found that the expression level of BCAR4 was upregulated in colon cancer tissues compared to paired normal tissues. What's more, higher BCAR4 expression was correlated with lower survival rate in patients with colon cancer. Mechanistically, we showed that BCAR4 activated Wnt/β-catenin signaling in colon cancer by protecting β-catenin from degradation. We also showed that BCAR4 overexpression promoted cell proliferation and migration in colon cancer. However, silencing BCAR4 inhibited cell growth and promoted apoptosis. Besides, BCAR4 knockdown decreased tumor growth in vivo. These findings indicate that BCAR4 facilitated colon cancer progression by enhancing cell proliferation and inhibiting apoptosis via BCAR4/β-catenin axis. BCAR4 may be a useful new target for treatment of patients with colon cancer.

Somatic Host Cell Alterations in HPV Carcinogenesis

High-risk human papilloma virus (HPV) infections cause cancers in different organ sites, most commonly cervical and head and neck cancers. While carcinogenesis is initiated by two viral oncoproteins, E6 and E7, increasing evidence shows the importance of specific somatic events in host cells for malignant transformation. HPV-driven cancers share characteristic somatic changes, including apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC)-driven mutations and genomic instability leading to copy number variations and large chromosomal rearrangements. HPV-associated cancers have recurrent somatic mutations in phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) and phosphatase and tensin homolog (PTEN), human leukocyte antigen A and B (HLA-A and HLA-B)-A/B, and the transforming growth factor beta (TGFβ) pathway, and rarely have mutations in the tumor protein p53 (TP53) and RB transcriptional corepressor 1 (RB1) tumor suppressor genes. There are some variations by tumor site, such as NOTCH1 mutations which are primarily found in head and neck cancers. Understanding the somatic events following HPV infection and persistence can aid the development of early detection biomarkers, particularly when mutations in precancers are characterized. Somatic mutations may also influence prognosis and treatment decisions.

Potentially functional variants in lncRNAs are associated with breast cancer risk in a Chinese population

Long non-coding RNAs (lncRNAs) participate in the development of breast cancer. Genetic variants in lncRNAs may be involved in their abnormal expressions and associated with cancer risk. In the present study, we performed RNA sequencing on five paired breast cancer tumor and adjacent non-cancerous tissues to obtain differentially expressed lncRNAs. We systematically selected potential regulatory variants of these lncRNAs and investigated the associations between these variants and breast cancer susceptibility in 1486 breast cancer cases and 1519 cancer-free controls in a Chinese population. Eleven lncRNAs were significantly differentially expressed between breast cancer tumor and normal tissues (false discovery rate (FDR) ≤0.05 and fold-change ≥2), including two known lncRNAs HOTAIR and UCA1. We subsequently genotyped 20 variants located on these lncRNAs and identified two variants (rs11471161 in AC104135.3 and rs3751232 in RP11-1060J15.4) associated with breast cancer risk. Logistic regression analysis indicated that the variant allele of rs11471161 was significantly associated with a decreased breast cancer risk (additive model: OR = 0.84, 95%CI = 0.74-0.94, P = 0.004), while the variant allele of rs3751232 showed an increased risk of breast cancer (additive model: OR = 1.20, 95%CI = 1.02-1.40, P = 0.027). Further co-expression analysis indicated that AC104135.3 associated with ERBB2, which promotes the development and progression of breast cancer through overexpression. Together, these results suggest that genetic variants rs11471161 and rs3751232 in AC104135.3, and RP11-1060J15.4, respectively, may influence the susceptibility to breast cancer in the Chinese population. Further functional evaluations and larger studies are warranted to validate these findings.

Integrated genomic and molecular characterization of cervical cancer

Cervical cancer remains one of the leading causes of cancer-related deaths worldwide. Reported here is an extensive molecular characterization of 228 primary cervical cancers, the largest comprehensive genomic study of cervical cancer to date. We observed striking APOBEC mutagenesis patterns and identified SHKBP1, ERBB3, CASP8, HLA-A, and TGFBR2 as novel significantly mutated genes in cervical cancer. We also discovered novel amplifications in immune targets CD274/PD-L1 and PDCD1LG2/PD-L2, and the BCAR4 lncRNA that has been associated with response to lapatinib. HPV integration was observed in all HPV18-related cases and 76% of HPV16-related cases, and was associated with structural aberrations and increased target gene expression. We identified a unique set of endometrial-like cervical cancers, comprised predominantly of HPV-negative tumors with high frequencies of KRAS, ARID1A, and PTEN mutations. Integrative clustering of 178 samples identified Keratin-low Squamous, Keratin-high Squamous, and Adenocarcinoma-rich subgroups. These molecular analyses reveal new potential therapeutic targets for cervical cancers.

Long non-coding RNAs in anti-cancer drug resistance

Chemotherapy is one of the basic treatments for cancers; however, drug resistance is mainly responsible for the failure of clinical treatment. The mechanism of drug resistance is complicated because of interaction among various factors including drug efflux, DNA damage repair, apoptosis and targets mutation. Long non-coding RNAs (lncRNAs) have been a focus of research in the field of bioscience, and the latest studies have revealed that lncRNAs play essential roles in drug resistance in breast cancer, gastric cancer and lung cancer, et al. Dysregulation of multiple targets and pathways by lncRNAs results in the occurrence of chemoresistance. In this review, we will discuss the mechanisms underlying lncRNA-mediated resistance to chemotherapy and the therapeutic potential of lncRNAs in future cancer treatment.

Endocrine therapy resistance in estrogen receptor (ER)-positive breast cancer

Estrogen receptor (ER)-positive breast cancer represents the majority (∼70%) of all breast malignancies. In this subgroup of breast cancers, endocrine therapies are effective both in the adjuvant and recurrent settings, although resistance remains a major issue. Several high-throughput approaches have been used to elucidate mechanisms of resistance and to derive potential predictive markers or alternative therapies. In this review, we cover the state-of-the-art of endocrine-resistance biomarker discovery with regard to the latest technological developments, and discuss current opportunities and restrictions for their implementation into a clinical setting.

Long non-coding RNAs: An emerging powerhouse in the battle between life and death of tumor cells

Long non-coding RNAs (lncRNAs) represent a class of non-protein coding transcripts longer than 200 nucleotides that have aptitude for regulating gene expression at the transcriptional, post-transcriptional or epigenetic levels. In recent years, lncRNAs, which are believed to be the largest transcript class in the transcriptomes, have emerged as important players in a variety of biological processes. Notably, the identification and characterization of numerous lncRNAs in the past decade has revealed a role for these molecules in the regulation of cancer cell survival and death. It is likely that this class of non-coding RNA constitutes a critical contributor to the assorted known or/and unknown mechanisms of intrinsic or acquired drug resistance. Moreover, the expression of lncRNAs is altered in various patho-physiological conditions, including cancer. Therefore, lncRNAs represent potentially important targets in predicting or altering the sensitivity or resistance of cancer cells to various therapies. Here, we provide an overview on the molecular functions of lncRNAs, and discuss their impact and importance in cancer development, progression, and therapeutic outcome. We also provide a perspective on how lncRNAs may alter the efficacy of cancer therapy and the promise of lncRNAs as novel therapeutic targets for overcoming chemoresistance. A better understanding of the functional roles of lncRNA in cancer can ultimately translate to the development of novel, lncRNA-based intervention strategies for the treatment or prevention of drug-resistant cancer.

Microarray expression profiling of dysregulated long non-coding RNAs in triple-negative breast cancer

Triple-negative breast cancer (TNBC) represents a collection of malignant breast tumors that are often aggressive and have an increased risk of metastasis and relapse. Long non-coding RNAs are generally defined as RNA transcripts measuring 200 nucleotides or longer that do not encode for any protein. During the past decade, increasing evidence has shown that lncRNAs play important roles in oncogenesis and tumor suppression; however, the roles of lncRNAs in TNBC are poorly understood. To address this issue, we used Agilent human lncRNA microarray chips and bioinformatics tools, including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), to assess lncRNA expression in 3 pairs of TNBC tissues. A dysregulated lncRNA expression profile was identified by microarray and verified by qRT-PCR in 48 pairs of breast cancer subtype tissues. Metastasis is the major cause of cancer-related deaths, including those in TNBC, and the presence of dormant residual disseminated tumor cells (DTC) may be a key factor leading to metastasis. ANKRD30A, a potential target for breast cancer immunotherapy, is currently one of the most used DTC markers. Notably, we found the expression levels of the novel intergenic lncRNA LINC00993 to be associated with the expression levels of ANKRD30A. Furthermore, our qRT-PCR data indicated that the expression of LINC00993 was also associated with the expression of the estrogen receptor. In conclusion, our study identified a set of lncRNAs that were consistently aberrantly expressed in TNBC, and these dysregulated lncRNAs may be involved in the development and/or progression of TNBC.

Breast cancer stem cells programs: enter the (non)-code

Breast tumors exhibit a hierarchical cellular organization driven by several subpopulations of cancer stem cells (CSCs). These breast CSC subpopulations are able to infinitely self-renew and to differentiate, giving rise to tumor heterogeneity. Accumulating evidence show that breast CSCs resist conventional therapies and i`nitiate tumor relapse. The development of anti-CSCs therapies may therefore greatly improve patient survival. A better elucidation of molecular circuitries involved in stemness would offer new relevant targets. Noncoding RNAs, especially microRNAs and long noncoding RNAs, are regulators of cell identity and are notably found deregulated in breast CSCs. This review will focus on noncoding RNAs involved in CSCs biology during breast cancer initiation, maintenance, therapeutic resistance and metastatic progression. Potential clinical applications using noncoding RNAs as biomarkers or therapies will be discussed.

Breast Cancer Anti-Estrogen Resistance 4 (BCAR4) Drives Proliferation of IPH-926 lobular Carcinoma Cells

Background

Most breast cancers depend on estrogenic growth stimulation. Functional genetic screenings in in vitro cell models have identified genes, which override growth suppression induced by anti-estrogenic drugs like tamoxifen. Using that approach, we have previously identified Breast Cancer Anti-Estrogen Resistance 4 (BCAR4) as a mediator of cell proliferation and tamoxifen-resistance. Here, we show high level of expression and function of BCAR4 in human breast cancer.

Methods

BCAR4 mRNA expression was evaluated by (q)RT-PCR in a panel of human normal tissues, primary breast cancers and cell lines. A new antibody raised against C78-I97 of the putative BCAR4 protein and used for western blot and immunoprecipitation assays. Furthermore, siRNA-mediated gene silencing was implemented to study the function of BCAR4 and its downstream targets ERBB2/3.

Results

Except for placenta, all human normal tissues tested were BCAR4-negative. In primary breast cancers, BCAR4 expression was comparatively rare (10%), but associated with enhanced proliferation. Relative high BCAR4 mRNA expression was identified in IPH-926, a cell line derived from an endocrine-resistant lobular breast cancer. Moderate BCAR4 expression was evident in MDA-MB-134 and MDA-MB-453 breast cancer cells. BCAR4 protein was detected in breast cancer cells with ectopic (ZR-75-1-BCAR4) and endogenous (IPH-926, MDA-MB-453) BCAR4 mRNA expression. Knockdown of BCAR4 inhibited cell proliferation. A similar effect was observed upon knockdown of ERBB2/3 and exposure to lapatinib, implying that BCAR4 acts in an ERBB2/3-dependent manner.

Conclusion

BCAR4 encodes a functional protein, which drives proliferation of endocrine-resistant breast cancer cells. Lapatinib, a clinically approved EGFR/ERBB2 inhibitor, counteracts BCAR4-driven tumor cell growth, a clinical relevant observation.

Predicting lncRNA-disease associations and constructing lncRNA functional similarity network based on the information of miRNA

Accumulating experimental studies have indicated that lncRNAs play important roles in various critical biological process and their alterations and dysregulations have been associated with many important complex diseases. Developing effective computational models to predict potential disease-lncRNA association could benefit not only the understanding of disease mechanism at lncRNA level, but also the detection of disease biomarkers for disease diagnosis, treatment, prognosis and prevention. However, known experimentally confirmed disease-lncRNA associations are still very limited. In this study, a novel model of HyperGeometric distribution for LncRNA-Disease Association inference (HGLDA) was developed to predict lncRNA-disease associations by integrating miRNA-disease associations and lncRNA-miRNA interactions. Although HGLDA didn't rely on any known disease-lncRNA associations, it still obtained an AUC of 0.7621 in the leave-one-out cross validation. Furthermore, 19 predicted associations for breast cancer, lung cancer, and colorectal cancer were verified by biological experimental studies. Furthermore, the model of LncRNA Functional Similarity Calculation based on the information of MiRNA (LFSCM) was developed to calculate lncRNA functional similarity on a large scale by integrating disease semantic similarity, miRNA-disease associations, and miRNA-lncRNA interactions. It is anticipated that HGLDA and LFSCM could be effective biological tools for biomedical research.

Mechanisms of endocrine resistance in breast cancer: an overview of the proposed roles of noncoding RNA

Endocrine therapies such as tamoxifen and aromatase inhibitors are the standard treatment options for estrogen receptor-positive breast cancer patients. However, resistance to these agents has become a major clinical obstacle. Potential mechanisms of resistance to endocrine therapies have been identified, often involving enhanced growth factor signaling and changes in the expression or action of the estrogen receptor, but few studies have addressed the role of noncoding RNA (ncRNA). Two important types of ncRNA include microRNA (miRNA) and long noncoding RNA (lncRNA). miRNAs are small RNA molecules that regulate gene expression via translational inhibition or degradation of mRNA transcripts, while lncRNAs are larger RNA molecules that have been shown to play a role in multiple cellular maintenance functions such as protein scaffolding, chromatin looping, and regulation of mRNA stability. Both miRNA and lncRNA have recently impacted the field of breast cancer research as important pieces in the mechanistic puzzle of the genes and pathways involved in breast cancer development and progression. This review serves as an overview of the roles of miRNA and lncRNA in breast cancer progression and the development of endocrine resistance. Ideally, future experiments in the field should include identification of ncRNAs that could be potential therapeutic targets in endocrine-resistant tumors, as well as ncRNA biomarkers that facilitate more tumor-specific treatment options for endocrine-resistant breast cancer patients.