Identification of microRNAs as potential biomarker for gastric cancer by system biological analysis. Biomed Res Int. 2014;2014:901428. [PMID: 24982912 PMCID: PMC4058523 DOI: 10.1155/2014/901428]

The Double Face of miR-708: A Pan-Cancer Player with Dissociative Identity Disorder

Over the last decades, accumulating evidence has shown tumor-dependent profiles of miR-708, being either up- or downregulated, and thus, acting as a "Janus" regulator of oncogenic pathways. Herein, its functional duality was assessed through a thorough review of the literature and further validation in silico using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In the literature, miR-708 was found with an oncogenic role in eight tumor types, while a suppressor tumor role was described in seven cancers. This double profile was also found in TCGA and GEO databases, with some tumor types having a high expression of miR-708 and others with low expression compared with non-tumor counterparts. The investigation of validated targets using miRBase, miRTarBase, and miRecords platforms, identified a total of 572 genes that appeared enriched for PI3K-Akt signaling, followed by cell cycle control, p53, Apellin and Hippo signaling, endocrine resistance, focal adhesion, and cell senescence regulations, which are all recognized contributors of tumoral phenotypes. Among these targets, a set of 15 genes shared by at least two platforms was identified, most of which have important roles in cancer cells that influence either tumor suppression or progression. In a clinical scenario, miR-708 has shown to be a good diagnostic and prognosis marker. However, its multitarget nature and opposing roles in diverse human tumors, aligned with insufficient experimental data and the lack of proper delivery strategies, hamper its potential as a sequence-directed therapeutic.

Inhibitory role of LINC00332 in gastric cancer progression through regulating cell EMT and stemness

OBJECTIVE

Gastric cancer (GC) is one of the most common lethal malignancies worldwide. The molecular mechanisms underlying GC early detection are poorly understood. Identifying potential coding and non-coding markers and related pathways in the GC progression is essential. Some Long non-coding RNAs (lncRNAs) reportedly play vital roles during gastric GC development. However, the clinical significance and biological function of LINC00332 in GC remain largely unclear.

METHODS

The gene expression patterns of GC from an RNAseq dataset (GSE122401) were retrieved from the Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) and lncRNAs (DELs) between normal and GC samples through several bioinformatic analysis. The expression of LINC00332 and MMP-13 as a target gene was quantified in fresh frozen tissues obtained from GC patients. In addition, we investigated the potential function of LINC00332 in silico and in vitro.

RESULTS

The expressions of LINC00332 and MMP-13 were significantly downregulated and upregulated in GC tissues, respectively. A significant inverse correlation between LINC00332 and MMP-13 mRNA expression was observed in tumor samples. The mRNA expression level of mesenchymal markers, stem cell factors, and MMP genes were significantly decreased after the LINC00332 ectopic expression, while epithelial markers expression was significantly increased. The LINC00332 overexpression markedly repressed proliferation, migration, and invasion and did not induce apoptosis in AGS cells. In addition, LINC00332 overexpression notably promoted the E-cadherin protein expression. Moreover, LINC00332 significantly decreased the cisplatin resistance.

CONCLUSION

Our findings indicated that LINC00332 may be a critical anti-EMT factor and provided a new efficient therapeutic strategy for GC treatment.

Expression Profiles of Circulating MicroRNAs in XELOX-Chemotherapy-Induced Peripheral Neuropathy in Patients with Advanced Gastric Cancer

Gastric cancer (GC) is one of the most common cancers and a leading cause of cancer deaths around the world. Chemotherapy is one of the most effective treatments for cancer patients, and has remarkably enhanced survival rates. However, it has many side effects. Recently, microRNAs (miRNAs) have been intensively studied as potential biomarkers for cancer diagnosis and treatment monitoring. However, definitive biomarkers in chemotherapy-induced peripheral neuropathy (CIPN) are still lacking. The aim of this study was to identify the factors significant for neurological adverse events in GC patients receiving XELOX (oxaliplatin and capecitabine) chemotherapy. The results show that XELOX chemotherapy induces changes in the expression of hsa-miR-200c-3p, hsa-miR-885-5p, and hsa-miR-378f. Validation by qRT-PCR demonstrated that hsa-miR-378f was significantly downregulated in CIPN. Hsa-miR-378f was identified as showing a statistically significant correlation in GC patients receiving XELOX chemotherapy according to the analysis of differentially expressed (DE) miRNAs. Furthermore, 34 potential target genes were predicted using a web-based database for miRNA target prognostication and functional annotations. The identified genes are related to the peptidyl-serine phosphorylation and regulation of alternative mRNA splicing with enrichment in the gastric cancer, neurotrophin, MAPK, and AMPK signaling pathways. Collectively, these results provide information useful for developing promising strategies for the treatment of XELOX-chemotherapy-induced peripheral neuropathy.

Predicting miRNA-disease associations using improved random walk with restart and integrating multiple similarities

Predicting beneficial and valuable miRNA-disease associations (MDAs) by doing biological laboratory experiments is costly and time-consuming. Proposing a forceful and meaningful computational method for predicting MDAs is essential and captivated many computer scientists in recent years. In this paper, we proposed a new computational method to predict miRNA-disease associations using improved random walk with restart and integrating multiple similarities (RWRMMDA). We used a WKNKN algorithm as a pre-processing step to solve the problem of sparsity and incompletion of data to reduce the negative impact of a large number of missing associations. Two heterogeneous networks in disease and miRNA spaces were built by integrating multiple similarity networks, respectively, and different walk probabilities could be designated to each linked neighbor node of the disease or miRNA node in line with its degree in respective networks. Finally, an improve extended random walk with restart algorithm based on miRNA similarity-based and disease similarity-based heterogeneous networks was used to calculate miRNA-disease association prediction probabilities. The experiments showed that our proposed method achieved a momentous performance with Global LOOCV AUC (Area Under Roc Curve) and AUPR (Area Under Precision-Recall Curve) values of 0.9882 and 0.9066, respectively. And the best AUC and AUPR values under fivefold cross-validation of 0.9855 and 0.8642 which are proven by statistical tests, respectively. In comparison with other previous related methods, it outperformed than NTSHMDA, PMFMDA, IMCMDA and MCLPMDA methods in both AUC and AUPR values. In case studies of Breast Neoplasms, Carcinoma Hepatocellular and Stomach Neoplasms diseases, it inferred 1, 12 and 7 new associations out of top 40 predicted associated miRNAs for each disease, respectively. All of these new inferred associations have been confirmed in different databases or literatures.

Emerging role of RNF2 in cancer: From bench to bedside

RNF2 (also known as ding, Ring1B or Ring2) is a member of the Ring finger protein family, which functions as E3 ubiquitin ligase for monoubiquitination of histone H2A at lysine 119 (H2AK119ub). RNF2 gene is located at the 1q25.3 site of human chromosome and the coding region is composed of 9 exons, encoding 336 amino acids in total. Many studies have demonstrated that overexpressed RNF2 was involved in the pathological progression of multiple cancers and has an impact on their clinical features. For instance, the upregulated expression level of RNF2 is positively correlated with the occurrence and progression of hepatocellular carcinoma, melanoma, prostate cancer, breast cancer, pancreatic cancer, gastric cancer, and bladder urothelial carcinoma, as well as with the radioresistance of lung cancer and chemoresistance of ovarian cancer. This review provides an up-to-date perspective on the relationship between RNF2 and several cancers and highlights recent studies on RNF2 regulation. In particular, the relevant cellular signaling pathways and potential clinical value of RNF2 in cancers are also discussed, suggesting its potential as an epigenetic biomarker and therapeutic target for these cancers.

Computer-aided biomarker discovery for precision medicine: data resources, models and applications

Biomarkers are a class of measurable and evaluable indicators with the potential to predict disease initiation and progression. In contrast to disease-associated factors, biomarkers hold the promise to capture the changeable signatures of biological states. With methodological advances, computer-aided biomarker discovery has now become a burgeoning paradigm in the field of biomedical science. In recent years, the 'big data' term has accumulated for the systematical investigation of complex biological phenomena and promoted the flourishing of computational methods for systems-level biomarker screening. Compared with routine wet-lab experiments, bioinformatics approaches are more efficient to decode disease pathogenesis under a holistic framework, which is propitious to identify biomarkers ranging from single molecules to molecular networks for disease diagnosis, prognosis and therapy. In this review, the concept and characteristics of typical biomarker types, e.g. single molecular biomarkers, module/network biomarkers, cross-level biomarkers, etc., are explicated on the guidance of systems biology. Then, publicly available data resources together with some well-constructed biomarker databases and knowledge bases are introduced. Biomarker identification models using mathematical, network and machine learning theories are sequentially discussed. Based on network substructural and functional evidences, a novel bioinformatics model is particularly highlighted for microRNA biomarker discovery. This article aims to give deep insights into the advantages and challenges of current computational approaches for biomarker detection, and to light up the future wisdom toward precision medicine and nation-wide healthcare.

Relevance function of microRNA-708 in the pathogenesis of cancer

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally responsible for regulating >70% of human genes. MicroRNA-708 (miR-708) is encoded in the intron 1 of the Odd Oz/ten-m homolog 4 (ODZ4) gene. Numerous researches have confirmed that the abnormal expressed miR-708 is involved in the regulation of multiple types of cancer. Notably, the expression level of miR-708 was higher in lung cancer, bladder cancer (BC) and colorectal cancer (CRC) cell lines while lower in hepatocellular carcinoma (HCC), prostate cancer (PC), gastric cancer (GC) and so on. This review provides a current view on the association between miR-708 and several cancers and focuses on the recent studies of miR-708 regulation, discussing its potential as an epigenetic biomarker and therapeutic target for these cancers. In particular, the regulated mechanisms and clinical application of miR-708 in these cancers are also discussed.

MiR-876-5p modulates head and neck squamous cell carcinoma metastasis and invasion by targeting vimentin

BACKGROUND

Local or distant metastasis remains the main course of death in head and neck squamous cell carcinoma (HNSCC) patients. MicroRNAs (miRNAs) have been implicated in metastasis of HNSCC, but the mechanisms of their action are mainly undocumented. Through public head and neck cancer miRNA expression datasets, we found that miR-876-5p was a novel potential tumor suppressor targeting HNSCC metastasis.

METHODS

Clinical significance and mechanism of miR-876-5P was systematically analyzed in HNSCC. Quantitative RT-PCR was used to evaluate miR-876-5p levels in HNSCC cell lines and in 20 pairs of HNSCC with associated regional nodal metastases and HNSCC without metastatic primary tumors. Scratch and invasion assays were evaluated to determine the role of miR-876-5p in the regulation of HNSCC cell migration and invasion, respectively. Western blotting was used to investigate the mechanism by which miR-876-5p suppresses HNSCC cell invasion and migration. Luciferase assays were performed to assess miR-876-5p binding to the vimentin gene. The animal model was used to support the in vitro experimental findings.

RESULTS

MiR-876-5p mimics inhibited HNSCC cell migration and invasion. Vimentin protein and mRNA levels were decreased in the miR-876-5p mimics group but increased in the miR-876-5p inhibitors group, which demonstrated that miR-876-5p inhibits vimentin expression in HNSCC cells. By directly targeting the vimentin 3'-UTR, we used dual-luciferase reporter assays to verify that vimentin is a functional downstream target of miR-876-5p. Importantly, increased vimentin expression promoted cell migration and invasion, and co-transfection with miR-876-5p mimics and vimentin restored cell aggressiveness to the original level. Moreover, miR-876-5p overexpression significantly downregulated vimentin expression level and inhibited the distal metastasis of HNSCC cells in vivo.

CONCLUSIONS

miR-876-5p, which functions as a tumor suppressor in HNSCC, inhibits metastasis by targeting vimentin and provides a novel therapeutic target for HNSCC treatment.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

Background

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases.

Methods

In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets.

Results

With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis.

Conclusions

Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1506-7) contains supplementary material, which is available to authorized users.

Clinically Significant Dysregulation of hsa-miR-30d-5p and hsa-let-7b Expression in Patients with Surgically Resected Non-Small Cell Lung Cancer

BACKGROUND

The cyclin E2 (CYCE2) is an important regulator in the progression and development of NSCLC, and its ectopic expression promoted the proliferation, invasion, and migration in several tumors, including Non-Small Cell Lung Cancer (NSCLC). However, the upregulation of CYCE2 in NSCLC cells suggested that it has a key role in tumorigenicity. In addition, the RAS family proteins as oncoproteins were activated in many major tumor types and its suitability as the therapeutic target in NSCLC was proposed. Considering the crucial role of microRNAs, it was hypothesized that altered expression of hsa-miR-30d-5p and hsa-let-7b might provide a reliable diagnostic tumor marker for diagnosis of NSCLC.

METHOD

Real-time RT-PCR approach could evaluate the expression alteration of hsa-miR-30d-5p and hsa-let-7b and it was related to the surgically resected tissue of 24 lung cancer patients and 10 non-cancerous patients. The miRNAs expression was associated with clinicopathological features of the patients.

RESULTS

Hsa-miR-30d showed a significant downregulation (p=0.0382) in resected tissue of NSCLC patients compared with control group. Its expression level could differentiate different stages of malignancies from each other. The ROC curve analysis gave it an AUC=0.73 (p=0.037) which was a good score as a reliable biomarker. In contrast, hsa-let-7b was significantly overexpressed in tumor samples (p=0.03). Interestingly, our findings revealed a significant association of hsa-let-7b in adenocarcinoma tumors, compared to Squamous Cell Carcinomas (SCC) (p<0.05). Also, analysis of ROC curve of hsa-let-7b (AUC=0.74, p-value=0.042) suggests that it could be as a suitable biomarker for NSCLC.

CONCLUSION

Together, these results suggest a possible tumor suppressor role for hsa-miR-30d in lung tumor progression and initiation. Moreover, upregulation of hsa-let-7b was associated with the tumor type.

Tissue microRNAs as predictive markers for gastric cancer patients undergoing palliative chemotherapy

MicroRNAs have the potential to become valuable predictive markers for gastric cancer. Samples of biopsy tissue, routinely taken from gastric cancer patients undergoing palliative chemotherapy, constitute suitable material for microRNA profiling with the aim of predicting the effect of chemotherapy. Our study group consisted of 54 patients, all of whom underwent palliative chemotherapy based on 5-fluorouracil (5-FU) or 5-FU in combination with platinum derivatives between 2000 and 2013. The expression of 29 selected microRNAs and genes BRCA1, ERCC1, RRM1 and TS, in gastric cancer tissue macrodissected from FFPE tissue samples, was measured by quantitative RT-PCR. The relationship between gene expression levels and time to progression (TTP) and overall survival (OS) was analysed. From the set of the 29 microRNAs of interest, we found high expression of miR-150, miR-342-3p, miR-181b, miR-221, miR-224 and low levels of miR-520h relate to shorter TTP. High levels of miR-150, miR-192, miR-224, miR-375 and miR-342-3p related to shorter OS. In routinely available FFPE tissue samples, we found 6 miRNAs with a relation to TTP, which may serve as predictors of the effectiveness of palliative treatment in gastric cancer patients. These miRNAs could also help in deciding whether to indicate palliative chemotherapy.

Dysregulation of non-coding RNAs in gastric cancer

Gastric cancer (GC) is one of the most common cancers in the world and a significant threat to the health of patients, especially those from China and Japan. The prognosis for patients with late stage GC receiving the standard of care treatment, including surgery, chemotherapy and radiotherapy, remains poor. Developing novel treatment strategies, identifying new molecules for targeted therapy, and devising screening techniques to detect this cancer in its early stages are needed for GC patients. The discovery of non-coding RNAs (ncRNAs), primarily microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), helped to elucidate the mechanisms of tumorigenesis, diagnosis and treatment of GC. Recently, significant research has been conducted on non-coding RNAs and how the regulatory dysfunction of these RNAs impacts the tumorigenesis of GC. In this study, we review papers published in the last five years concerning the dysregulation of non-coding RNAs, especially miRNAs and lncRNAs, in GC. We summarize instances of aberrant expression of the ncRNAs in GC and their effect on survival-related events, including cell cycle regulation, AKT signaling, apoptosis and drug resistance. Additionally, we evaluate how ncRNA dysregulation affects the metastatic process, including the epithelial-mesenchymal transition, stem cells, transcription factor activity, and oncogene and tumor suppressor expression. Lastly, we determine how ncRNAs affect angiogenesis in the microenvironment of GC. We further discuss the use of ncRNAs as potential biomarkers for use in clinical screening, early diagnosis and prognosis of GC. At present, no ideal ncRNAs have been identified as targets for the treatment of GC.

Challenges of deciphering gastric cancer heterogeneity

Gastric cancer is in decline in most developed countries; however, it still accounts for a notable fraction of global mortality and morbidity related to cancer. High-throughput methods are rapidly changing our view and understanding of the molecular basis of gastric carcinogenesis. Today, it is widely accepted that the molecular complexity and heterogeneity, both inter- and intra-tumour, of gastric adenocarcinomas present significant obstacles in elucidating specific biomarkers for early detection of the disease. Although genome-wide sequencing and gene expression studies have revealed the intricate nature of the molecular changes that occur in tumour landscapes, the collected data and results are complex and sometimes contradictory. Several aberrant molecules have already been tested in clinical trials, although their diagnostic and prognostic utilities have not been confirmed thus far. The gold standard for the detection of sporadic gastric cancer is still the gastric endoscopy, which is considered invasive. In addition, genome-wide association studies have confirmed that genetic variations are important contributors to increased cancer risk and could participate in the initiation of malignant transformation. This hypothesis could in part explain the late onset of sporadic gastric cancers. The elaborate interplay of polymorphic low penetrance genes and lifestyle and environmental risk factors requires additional research to decipher their relative impacts on tumorigenesis. The purpose of this article is to present details of the molecular heterogeneity of sporadic gastric cancers at the DNA, RNA, and proteome levels and to discuss issues relevant to the translation of basic research data to clinically valuable tools. The focus of this work is the identification of relevant molecular changes that could be detected non-invasively.

May Circulating microRNAs be Gastric Cancer Diagnostic Biomarkers?

Gastric cancer (GC) is the third leading cause of cancer-related deaths. More than 80% of the diagnosis was made at the advanced stages of the disease, highlighting the urgent demand for novel biomarkers that can be used for early detection. Recently, a number of studies suggest that circulating microRNAs (miRNAs) could be potential biomarkers for GC diagnosis. Cancer-related circulating miRNAs, as well as tissue miRNAs, provide a hopeful prospect of detecting GC at early stages, and the prospective participation of miRNAs in biomarker development will enhance the sensitivity and specificity of diagnostic tests for GC. As miRNAs in blood are stable, their potential value as diagnostic biomarkers in GC has been explored over the past few years. However, due to the inconsistent or sometimes conflicting reports, large-scale prospective studies are needed to validate their potential applicability in GC diagnosis. This review summarizes the current development about potential miRNA biomarkers for GC diagnosis and the obstacles hindering their clinical usage.

Clinical Diagnostic Implications of Body Fluid MiRNA in Oral Squamous Cell Carcinoma: A Meta-Analysis

Oral cancer, predominantly oral squamous cell carcinoma (OSCC), is one of the most leading causes of cancers worldwide. Due to a low 5-year survival rate, highly effective methods for the early detection of OSCC are totally needed. MicroRNAs (miRNAs), as promising biomarkers, can bring insights into tumorigenesis of oral cancers. However, studies on the accuracy of miRNAs detection in OSCC have inconsistent conclusions, leading us to conduct this meta-analysis. The aim of this study was to systematically review the articles investigating the diagnostic value of miRNAs in OSCC. The PubMed, Embase, Chinese National Knowledge Infrastructure (CNKI), Web of Science were searched (updated to June 11th, 2015) to identify all articles evaluating the diagnostic yield of miRNAs for OSCC. The pooled sensitivity, specificity, and other diagnostic parameters were used to assess the performance of miRNAs assays on OSCC detection. Statistical analysis was conducted by employing the R software. The present meta-analysis comprised 23 studies from 10 articles, including 598 OSCC patients and 320 healthy individuals, available for analysis. The summary receiver operator characteristic (SROC) curve was plotted. Meanwhile, the pooled diagnostic parameters and the area under curve (AUC) were calculated based on all included studies. The pooled diagnostic parameters calculated from all 23 studies were as follows: pooled sensitivity of 0.759 (95% CI: 0.701-0.809), pooled specificity of 0.773 (95% CI: 0.713-0.823) and AUC of 0.832, which indicates a relatively high diagnostic accuracy of miRNAs in differentiating OSCC patients from healthy controls. Meanwhile, In addition, subgroup analyses were conducted to access the heterogeneity between studies, which is based on specimen (serum/plasma/blood/saliva/ tissue) and ethnicity (Asian/Caucasian). In summary, our meta-analysis suggests that miRNAs might be used in noninvasive screening tests for OSCC, which needs further large-scale studies to be validated.