Endobronchial miRNAs as biomarkers in lung cancer chemoprevention

miR-520a-5p regulates Frizzled 9 expression and mediates effects of cigarette smoke and iloprost chemoprevention

Expression of Frizzled 9 (FZD9) is critical to the activity of the lung cancer chemoprevention agent and prostacyclin analogue, iloprost. FZD9 is required in lung epithelial cells for iloprost to activate peroxisome proliferator activated receptor gamma (PPARG) and related anti-tumor signaling. We aimed to investigate which miRNA regulate FZD9 in the context of cigarette smoke exposure and iloprost treatment. We found that miR-520a-5p binds the FZD9 3’UTR in lung cell lines and alters activity and expression of FZD9 downstream targets. Cigarette smoke condensate (CSC) increases expression of miR-520a-5p, while iloprost decreases expression. Cancer promoting effects of a miR-520a-5p mimic were rescued with iloprost treatment, and effects of cigarette smoke were partially rescued with a miR-520a-5p inhibitor. Here we confirm miR-520a-5p as a regulator of FZD9 activity and a mediator of CSC and iloprost effects in the lung. Targeting miR-520a-5p could be an approach to restoring FZD9 expression and improving response to iloprost lung cancer chemoprevention.

Prostacyclin and EMT Pathway Markers for Monitoring Response to Lung Cancer Chemoprevention

Lung cancer is the leading cause of cancer death worldwide and global burden could be reduced through targeted application of chemoprevention. The development of squamous lung carcinoma has been linked with persistent, high-grade bronchial dysplasia. Bronchial histology improved in former smokers in a chemoprevention trial with the prostacyclin analogue iloprost. Prostacyclin acts through peroxisome proliferator-activated receptor gamma (PPARγ) to reverse epithelial to mesenchymal transition and promote anticancer signaling. We hypothesized that the prostacyclin signaling pathway and EMT could provide response markers for prostacyclin chemoprevention of lung cancer. Human bronchial epithelial cells were treated with cigarette smoke condensate (CSC) or iloprost for 2 weeks, CSC for 16 weeks, or CSC for 4 weeks followed by 4 weeks of CSC and/or iloprost, and RNA was extracted. Wild-type or prostacyclin synthase transgenic mice were exposed to 1 week of cigarette smoke or one injection of urethane, and RNA was extracted from the lungs. We measured potential markers of prostacyclin and iloprost efficacy in these models. We identified a panel of markers altered by tobacco carcinogens and inversely affected by prostacyclin, including PPARγ, 15PGDH, CES1, COX-2, ECADHERIN, SNAIL, VIMENTIN, CRB3, MIR34c, and MIR221 These data introduce a panel of potential markers for monitoring interception of bronchial dysplasia progression during chemoprevention with prostacyclin. Chemoprevention is a promising approach to reduce lung cancer mortality in a high-risk population. Identifying markers for targeted use is critical for success in future clinical trials of prostacyclin for lung cancer chemoprevention. Cancer Prev Res; 11(10); 643-54. ©2018 AACR.

microRNA-340 influences cell proliferation, apoptosis and invasion by targeting NF-κB1 in gastric cancer

Gastric cancer is a serious threat to human health, and its pathogenesis may be regulated by a variety of mRNAs. Abnormal expression of microRNA-340 has been frequently reported in many malignant neoplasms, while the molecular mechanism of miR-340 has not been explored in gastric cancer. In this study, the mRNA level of miR-340 was determined by real-time PCR in GC cell lines. The miR-340 mimic was transiently transfected into GC cells by using Lipofectamine™ 2000 reagent. The BrdU-ELISA results showed that introduction of miR-340 inhibited cell proliferation. It was demonstrated that miR-340 mimic arrested cell cycle progression and promoted apoptosis of MKN-45 and BGC-823 cells. In addition, the overexpression of miR-340 could inhibit invasion and EMT of MKN-45 and BGC-823 cells. The expression of NF-κB1 was evidently reduced by up-regulation of miR-340. Luciferase reporter assay further confirmed that miR-340 could directly target the 3'UTR of NF-κB1. Moreover, overexpression of NF-κB1 transfected with miR-340 mimic partially reversed the inhibitory of miR-340 mimic in MKN-45 and BGC-823 cells. In conclusion, miR-340 induced cell apoptosis and inhibited invasion by down-regulation of NF-κB1, which might be a potential target in treatment and prevention of gastric cancer.

Helicase-like transcription factor expression is associated with a poor prognosis in Non-Small-Cell Lung Cancer (NSCLC)

Background

The relapse rate in early stage non-small cell lung cancer (NSCLC) after surgical resection is high. Prognostic biomarkers may help identify patients who may benefit from additional therapy. The Helicase-like Transcription Factor (HLTF) is a tumor suppressor, altered in cancer either by gene hypermethylation or mRNA alternative splicing. This study assessed the expression and the clinical relevance of wild-type (WT) and variant forms of HLTF RNAs in NSCLC.

Methods

We analyzed online databases (TCGA, COSMIC) for HLTF alterations in NSCLC and assessed WT and spliced HLTF mRNAs expression by RT-ddPCR in 39 lung cancer cell lines and 171 patients with resected stage I-II NSCLC.

Results

In silico analyses identified HLTF gene alterations more frequently in lung squamous cell carcinoma than in adenocarcinoma. In cell lines and in patients, WT and I21R HLTF mRNAs were detected, but the latter at lower level. The subgroup of 25 patients presenting a combined low WT HLTF expression and a high I21R HLTF expression had a significantly worse disease-free survival than the other 146 patients in univariate (HR 1.96, CI 1.17–3.30; p = 0.011) and multivariate analyses (HR 1.98, CI 1.15–3.40; p = 0.014).

Conclusion

A low WT HLTF expression with a high I21R HLTF expression is associated with a poor DFS.

Platelet-targeted pharmacologic treatments as anti-cancer therapy

Platelets act as multifunctional cells participating in immune response, inflammation, allergy, tissue regeneration, and lymphoangiogenesis. Among the best-established aspects of a role of platelets in non-hemostatic or thrombotic disorders, there is their participation in cancer invasion and metastasis. The interaction of many different cancer cells with platelets leads to platelet activation, and on the other hand platelet activation is strongly instrumental to the pro-carcinogenic and pro-metastatic activities of platelets. It is thus obvious that over the last years a lot of interest has focused on the possible chemopreventive effect of platelet-targeted pharmacologic treatments. This article gives an overview of the platelet-targeted pharmacologic approaches that have been attempted in the prevention of cancer development, progression, and metastasis, including the application of anti-platelet drugs currently used for cardiovascular disease and of new and novel pharmacologic strategies. Despite the fact that very promising results have been obtained with some of these approaches in pre-clinical models, with the exclusion of aspirin, clinical evidence of a beneficial effect of anti-platelet agents in cancer is however still largely missing. Future studies with platelet-targeted drugs in cancer must carefully deal with design issues, and in particular with the careful selection of patients, and/or explore novel platelet targets in order to provide a solution to the critical issue of the risk/benefit profile of long-term anti-platelet therapy in the prevention of cancer progression and dissemination.

A novel approach for predicting microRNA-disease associations by unbalanced bi-random walk on heterogeneous network

MicroRNAs (miRNAs) play a critical role by regulating their targets in post-transcriptional level. Identification of potential miRNA-disease associations will aid in deciphering the pathogenesis of human polygenic diseases. Several computational models have been developed to uncover novel miRNA-disease associations based on the predicted target genes. However, due to the insufficient number of experimentally validated miRNA-target interactions as well as the relatively high false-positive and false-negative rates of predicted target genes, it is still challenging for these prediction models to obtain remarkable performances. The purpose of this study is to prioritize miRNA candidates for diseases. We first construct a heterogeneous network, which consists of a disease similarity network, a miRNA functional similarity network and a known miRNA-disease association network. Then, an unbalanced bi-random walk-based algorithm on the heterogeneous network (BRWH) is adopted to discover potential associations by exploiting bipartite subgraphs. Based on 5-fold cross validation, the proposed network-based method achieves AUC values ranging from 0.782 to 0.907 for the 22 human diseases and an average AUC of almost 0.846. The experiments indicated that BRWH can achieve better performances compared with several popular methods. In addition, case studies of some common diseases further demonstrated the superior performance of our proposed method on prioritizing disease-related miRNA candidates.

Noncoding RNA Profiles in Tobacco- and Alcohol-Associated Diseases

Tobacco and alcohol are the leading environmental risk factors in the development of human diseases, such as cancer, cardiovascular disease, and liver injury. Despite the copious amount of research on this topic, by 2030, 8.3 million deaths are projected to occur worldwide due to tobacco use. The expression of noncoding RNAs, primarily microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), is modulated by tobacco and alcohol consumption. Drinking alcohol and smoking cigarettes can modulate the expression of miRNAs and lncRNAs through various signaling pathways, such as apoptosis, angiogenesis, and inflammatory pathways—primarily interleukin 6 (IL-6)/signal transducer and activator of transcription 3 (STAT3), which seems to play a major role in the development of diseases associated with these risk factors. Since they may be predictive and prognostic biomarkers, they can be used both as predictors of the response to therapy and as a targeted therapy. Further, circulating miRNAs might be valuable noninvasive tools that can be used to examine diseases that are related to the use of tobacco and alcohol. This review discusses the function of noncoding RNAs in cancer and other human tobacco- and alcohol-associated diseases.

miR-221/222 Are Involved in Response to Sunitinib Treatment in Metastatic Renal Cell Carcinoma

Sunitinib is a multitargeting tyrosine kinase inhibitor used for metastatic renal cancer. There are no biomarkers that can predict sunitinib response. Such markers are needed to avoid administration of costly medication with side effects to patients who would not benefit from it. We compared global miRNA expression between patients with a short (≤12 months) versus prolonged (>12 months) progression-free survival (PFS) under sunitinib as first-line therapy for metastatic renal cell carcinoma. We identified a number of differentially expressed miRNAs and developed miRNA statistical models that can accurately distinguish between the two groups. We validated our models in the discovery set and an independent set of 57 patients. Target prediction and pathway analysis showed that these miRNAs are involved in vascular endothelial growth factor (VEGF), TGFβ, and mammalian target of rapamycin (mTOR)-mediated signaling and cell-cell communication. We tested the effect of these miRNAs on cellular proliferation and angiogenesis. We validated the negative correlation between miR-221 and its target, VEGFR2.miR-221 overexpression was associated with a poor PFS while its target, VEGFR2 was associated with longer survival. Gain of function experiments showed that miR-221 and miR-222 decreased angiogenesis and cellular proliferation in human umbilical vein endothelial cells (HUVEC) while increasing cellular proliferation in ACHN cells. miRNAs represent potential predictive markers for sunitinib response.

Prediction of potential disease-associated microRNAs based on random walk

MOTIVATION

Identifying microRNAs associated with diseases (disease miRNAs) is helpful for exploring the pathogenesis of diseases. Because miRNAs fulfill function via the regulation of their target genes and because the current number of experimentally validated targets is insufficient, some existing methods have inferred potential disease miRNAs based on the predicted targets. It is difficult for these methods to achieve excellent performance due to the high false-positive and false-negative rates for the target prediction results. Alternatively, several methods have constructed a network composed of miRNAs based on their associated diseases and have exploited the information within the network to predict the disease miRNAs. However, these methods have failed to take into account the prior information regarding the network nodes and the respective local topological structures of the different categories of nodes. Therefore, it is essential to develop a method that exploits the more useful information to predict reliable disease miRNA candidates.

RESULTS

miRNAs with similar functions are normally associated with similar diseases and vice versa. Therefore, the functional similarity between a pair of miRNAs is calculated based on their associated diseases to construct a miRNA network. We present a new prediction method based on random walk on the network. For the diseases with some known related miRNAs, the network nodes are divided into labeled nodes and unlabeled nodes, and the transition matrices are established for the two categories of nodes. Furthermore, different categories of nodes have different transition weights. In this way, the prior information of nodes can be completely exploited. Simultaneously, the various ranges of topologies around the different categories of nodes are integrated. In addition, how far the walker can go away from the labeled nodes is controlled by restarting the walking. This is helpful for relieving the negative effect of noisy data. For the diseases without any known related miRNAs, we extend the walking on a miRNA-disease bilayer network. During the prediction process, the similarity between diseases, the similarity between miRNAs, the known miRNA-disease associations and the topology information of the bilayer network are exploited. Moreover, the importance of information from different layers of network is considered. Our method achieves superior performance for 18 human diseases with AUC values ranging from 0.786 to 0.945. Moreover, case studies on breast neoplasms, lung neoplasms, prostatic neoplasms and 32 diseases further confirm the ability of our method to discover potential disease miRNAs.

AVAILABILITY AND IMPLEMENTATION

A web service for the prediction and analysis of disease miRNAs is available at http://bioinfolab.stx.hk/midp/.

MicroRNAs in lung cancer

MicroRNAs have become recognized as key players in the development of cancer. They are a family of small non-coding RNAs that can negatively regulate the expression of cancer-related genes by sequence-selective targeting of mRNAs, leading to either mRNA degradation or translational repression. Lung cancer is the leading cause of cancer-related death worldwide with a substantially low survival rate. MicroRNAs have been confirmed to play roles in lung cancer development, epithelial-mesenchymal transition and response to therapy. They are also being studied for their future use as diagnostic and prognostic biomarkers and as potential therapeutic targets. In this review we focus on the role of dysregulated microRNA expression in lung tumorigenesis. We also discuss the role of microRNAs in therapeutic resistance and as biomarkers. We further look into the progress made and challenges remaining in using microRNAs for therapy in lung cancer.

Updates and controversies in the rapidly evolving field of lung cancer screening, early detection, and chemoprevention

Lung cancer remains the leading cause of cancer-related death in the United States. Cigarette smoking is a well-recognized risk factor for lung cancer, and a sustained elevation of lung cancer risk persists even after smoking cessation. Despite identifiable risk factors, there has been minimal improvement in mortality for patients with lung cancer primarily stemming from diagnosis at a late stage when there are few effective therapeutic options. Early detection of lung cancer and effective screening of high-risk individuals may help improve lung cancer mortality. While low dose computerized tomography (LDCT) screening of high risk smokers has been shown to reduce lung cancer mortality, the high rates of false positives and potential for over-diagnosis have raised questions on how to best implement lung cancer screening. The rapidly evolving field of lung cancer screening and early-detection biomarkers may ultimately improve the ability to diagnose lung cancer in its early stages, identify smokers at highest-risk for this disease, and target chemoprevention strategies. This review aims to provide an overview of the opportunities and challenges related to lung cancer screening, the field of biomarker development for early lung cancer detection, and the future of lung cancer chemoprevention.