Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer

Interactions Between Genetics, Lifestyle, and Environmental Factors for Healthcare

The occurrence and progression of diseases are strongly associated with a combination of genetic, lifestyle, and environmental factors. Understanding the interplay between genetic and nongenetic components provides deep insights into disease pathogenesis and promotes personalized strategies for people healthcare. Recently, the paradigm of systems medicine, which integrates biomedical data and knowledge at multidimensional levels, is considered to be an optimal way for disease management and clinical decision-making in the era of precision medicine. In this chapter, epigenetic-mediated genetics-lifestyle-environment interactions within specific diseases and different ethnic groups are systematically discussed, and data sources, computational models, and translational platforms for systems medicine research are sequentially presented. Moreover, feasible suggestions on precision healthcare and healthy longevity are kindly proposed based on the comprehensive review of current studies.

Gene-microRNA network module analysis for ovarian cancer

Background

MicroRNAs (miRNAs) are involved in many biological processes by regulating post-transcriptional gene expression. The alterations of the regulatory pathways can cause different diseases including cancer. Although many works have been done to study the gene-miRNA regulatory network, the intertwined relationship is far from being fully understood. The objective of this study is to integrate both gene expression data and miRNA data so as to explore the complex relationships among them.

Methods

By integrating the networks consisting of gene coexpression, miRNA coexpression, gene-miRNA coexpression, and the known gene-miRNA interactions, we aim to find the most connected network modules so as to study their functions and properties. In this paper, we proposed an optimization model for identification of the modules in the integrated networks. This model tries to find both the modules in the gene-gene and miRNA-miRNA coexpression networks and the densely connected gene-miRNA subneworks. An approximation computational method was developed to solve the optimization problem.

Results

We applied the method to 556 human ovarian cancer samples with both gene expression data and miRNA expression data. The identified modules are significantly enriched by miRNA clusters, GO-BPs, and KEGG pathways. We compared our method with some existing methods and showed the better performance of our method. We also showed that the miRNAs and genes in our identified modules are associated with cancers, especially ovarian cancer.

Conclusions

This study provides strong support that the subnetworks consisting of genes and miRNAs with close interactions contribute the cancers. The proposed computational method can be applied to other studies that are related to different types of networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0357-1) contains supplementary material, which is available to authorized users.

Knowledge-Guided Bioinformatics Model for Identifying Autism Spectrum Disorder Diagnostic MicroRNA Biomarkers

Autism spectrum disorder (ASD) is a severe neurodevelopmental disease with a high incidence and effective biomarkers are urgently needed for its diagnosis. A few previous studies have reported the detection of miRNA biomarkers for autism diagnosis, especially those based on bioinformatics approaches. In this study, we developed a knowledge-guided bioinformatics model for identifying autism miRNA biomarkers. We downloaded gene expression microarray data from the GEO Database and extracted genes with expression levels that differed in ASD and the controls. We then constructed an autism-specific miRNA-mRNA network and inferred candidate autism biomarker miRNAs based on their regulatory modes and functions. We defined a novel parameter called the autism gene percentage as autism-specific knowledge to further facilitate the identification of autism-specific biomarker miRNAs. Finally, 11 miRNAs were screened as putative autism biomarkers, where eight miRNAs (72.7%) were significantly dysregulated in ASD samples according to previous reports. Functional enrichment results indicated that the targets of the identified miRNAs were enriched in autism-associated pathways, such as Wnt signaling (in KEGG and IPA), cell cycle (in KEGG), and glioblastoma multiforme signaling (in IPA), thereby supporting the predictive power of our model.

Biomarker MicroRNAs for Diagnosis, Prognosis and Treatment of Hepatocellular Carcinoma: A Functional Survey and Comparison

Hepatocellular Carcinoma (HCC) is one of the most common malignant tumors with high incidence and mortality rate. Precision and effective biomarkers are therefore urgently needed for the early diagnosis and prognostic estimation. MicroRNAs (miRNAs) are important regulators which play functions in various cellular processes and biological activities. Accumulating evidence indicated that the abnormal expression of miRNAs are closely associated with HCC initiation and progression. Recently, many biomarker miRNAs for HCC have been identified from blood or tissues samples, however, the universality and specificity on clinicopathological features of them are less investigated. In this review, we comprehensively surveyed and compared the diagnostic, prognostic, and therapeutic roles of HCC biomarker miRNAs in blood and tissues based on the cancer hallmarks, etiological factors as well as ethnic groups, which will be helpful to the understanding of the pathogenesis of biomarker miRNAs in HCC development and further provide accurate clinical decisions for HCC diagnosis and treatment.

Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach

Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis.

Prioritizing cancer-related microRNAs by integrating microRNA and mRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs regulating the expression of target genes, and they are involved in cancer initiation and progression. Even though many cancer-related miRNAs were identified, their functional impact may vary, depending on their effects on the regulation of other miRNAs and genes. In this study, we propose a novel method for the prioritization of candidate cancer-related miRNAs that may affect the expression of other miRNAs and genes across the entire biological network. For this, we propose three important features: the average expression of a miRNA in multiple cancer samples, the average of the absolute correlation values between the expression of a miRNA and expression of all genes, and the number of predicted miRNA target genes. These three features were integrated using order statistics. By applying the proposed approach to four cancer types, glioblastoma, ovarian cancer, prostate cancer, and breast cancer, we prioritized candidate cancer-related miRNAs and determined their functional roles in cancer-related pathways. The proposed approach can be used to identify miRNAs that play crucial roles in driving cancer development, and the elucidation of novel potential therapeutic targets for cancer treatment.

Screening key microRNAs for castration-resistant prostate cancer based on miRNA/mRNA functional synergistic network

High-throughput methods have been used to explore the mechanisms by which androgen-sensitive prostate cancer (ASPC) develops into castration-resistant prostate cancer (CRPC). However, it is difficult to interpret cryptic results by routine experimental methods. In this study, we performed systematic and integrative analysis to detect key miRNAs that contribute to CRPC development. From three DNA microarray datasets, we retrieved 11 outlier microRNAs (miRNAs) that had expression discrepancies between ASPC and CRPC using a specific algorithm. Two of the miRNAs (miR-125b and miR-124) have previously been shown to be related to CRPC. Seven out of the other nine miRNAs were confirmed by quantitative PCR (Q-PCR) analysis. MiR-210, miR-218, miR-346, miR-197, and miR-149 were found to be over-expressed, while miR-122, miR-145, and let-7b were under-expressed in CRPC cell lines. GO and KEGG pathway analyses revealed that miR-218, miR-197, miR-145, miR-122, and let-7b, along with their target genes, were found to be involved in the PI3K and AKT3 signaling network, which is known to contribute to CRPC development. We then chose five miRNAs to verify the accuracy of the analysis. The target genes of each miRNA were altered significantly upon transfection of specific miRNA mimics in the C4–2 CRPC cell line, which was consistent with our pathway analysis results. Finally, we hypothesized that miR-218, miR-145, miR-197, miR-149, miR-122, and let-7b may contribute to the development of CRPC through the influence of Ras, Rho proteins, and the SCF complex. Further investigation is needed to verify the functions of the identified novel pathways in CRPC development.

Dissecting the regulation rules of cancer-related miRNAs based on network analysis

miRNAs (microRNAs) are a set of endogenous and small non-coding RNAs which specifically induce degradation of target mRNAs or inhibit protein translation to control gene expression. Obviously, aberrant miRNA expression in human cells will lead to a serious of changes in protein-protein interaction network (PPIN), thus to activate or inactivate some pathways related to various diseases, especially carcinogenesis. In this study, we systematically constructed the miRNA-regulated co-expressed protein-protein interaction network (CePPIN) for 17 cancers firstly. We investigated the topological parameters and functional annotation for the proteins in CePPIN, especially for those miRNA targets. We found that targets regulated by more miRNAs tend to play a more important role in the forming process of cancers. We further elucidated the miRNA regulation rules in PPIN from a more systematical perspective. By GO and KEGG pathway analysis, miRNA targets are involved in various cellular processes mostly related to cell cycle, such as cell proliferation, growth, differentiation, etc. Through the Pfam classification, we found that miRNAs belonging to the same family tend to have targets from the same family which displays the synergistic function of these miRNAs. Finally, the case study on miR-519d and miR-21-regulated sub-network was performed to support our findings.

Long Non-coding RNAs in Urologic Malignancies: Functional Roles and Clinical Translation

Early diagnosis and surveillance for metastasis and recurrences are critical issues of urologic cancer. Deregulation of long non-coding RNAs (lncRNAs) has been implicated in urologic malignancies and represents potential markers or therapeutic targets. However, the utility of lncRNA as biomarkers appears to be overstated due to heterogeneous or irreproducible results from different studies. Thus, a critical and cautious review on the biomarker potential of lncRNAs is needed. This review provides an update on new findings of lncRNA-based markers for urologic cancer. The diverse mechanisms and associated examples of lncRNAs involved during the carcinogenesis of prostate cancer, bladder cancer and renal cancer were discussed in a more balanced and critical manner, as were the suitability of lncRNAs as diagnostic or prognostics markers.

Let-7a inhibits tumor cell growth and metastasis by directly targeting RTKN in human colon cancer

Colorectal cancer (CRC) is the third most common cancer worldwide, with high morbidity. MicroRNAs (miRNAs) are endogenous small RNAs that play important roles in regulating multiple biological and pathologic processes. The differential expression of miRNAs in CRC was first reported in 2003. Accumulated evidence indicates that lethal-7a (let-7a, miRNA) generally functions as a tumor suppressor in several human cancers. However, the role of let-7a in human colon cancer remains unclear. The aim of this study was to investigate the biological functions of let-7a and its potential role in colon cancer. We first discovered that let-7a level was significantly decreased in colon cancer tissues and cell lines (HT-29, HCT-116, LoVo, SW480, and SW620). To explore the effects of let-7a on colon cancer, let-7a over-expressed HCT-116 and SW620 cells were constructed. Further studies demonstrated that over-expressed let-7a could remarkably inhibit HCT-116 and SW620 cell growth and metastasis by directly down-regulating Rhotekin (RTKN). When RTKN was reintroduced into let-7a mimic transfected HCT-116 or SW620 cells, the inhibition effects of let-7a on colon cancer cell growth and metastasis were markedly reversed. In conclusion, our research shows that let-7a can inhibit tumor cell growth and metastasis by directly targeting RTKN in human colon cancer.

MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model

Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and treatment selection. Here, we describe a novel bioinformatics model for the prediction of microRNA biomarkers for the diagnosis of paediatric AML based on computational functional analysis of the microRNA regulatory network substructure. microRNA-196b, microRNA-155 and microRNA-25 were identified as putative diagnostic biomarkers for pediatric AML. Further systematic analysis confirmed the association of the predicted microRNAs with the leukemogenesis of AML. In vitro q-PCR experiments showed that microRNA-155 is significantly overexpressed in children with AML and microRNA-196b is significantly overexpressed in subgroups M4–M5 of the French-American-British classification system. These results suggest that microRNA-155 is a potential diagnostic biomarker for all subgroups of paediatric AML, whereas microRNA-196b is specific for subgroups M4–M5.

Comparison of Prognostic MicroRNA Biomarkers in Blood and Tissues for Gastric Cancer

Gastric cancer (GC) still keeps up high mortality worldwide with poor prognosis. Efficient and non-invasive prognostic biomarkers are urgently needed. MicroRNAs are non-coding RNAs playing roles in post-transcriptional gene regulation, which contribute to various biological processes such as development, differentiation and carcinogenesis. MicroRNA expression profiles have been associated with the prognosis and outcome in GC. MicroRNA prognostic biomarkers have been identified from blood or tissues samples, but with different prognostic features. Understanding the various roles of microRNAs in different sample sources of GC will provide deep insights into GC progression. In this review, we highlight the distinct prognostic roles of microRNAs biomarkers in blood and tissue according to their relationships with prognostic parameters, survival rates and target pathways. This will be useful for non-invasive biomarker development and selection in prognosis of GC.

MicroRNA-125a-5p regulates cancer cell proliferation and migration through NAIF1 in prostate carcinoma

Background

We investigated the functional roles of microRNA-125a-5p in regulating human prostate carcinoma.

Methods

Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to evaluate the gene expression levels of miR-125a-5p in eight prostate cancer cell lines and nine biopsy specimens from patients with prostate cancer. miR-125a-5p was genetically knocked down in prostate cancer cell lines, DU145 and VCaP cells by lentiviral transduction. The effects of miR-125a-5p downregulation on prostate cancer cell proliferation and migration were evaluated by MTT assay and transwell assay, respectively. Direct regulation of miR-125a-5p on its downstream targets, NAIF1, and apoptotic gene caspase-3 were evaluated through dual-luciferase reporter assay, qRT-PCR, and Western blot, respectively. NAIF1 was then ectopically overexpressed in DU145 and VCaP cells to modulate prostate cancer cell proliferation and migration. Finally, the effects of miR-125a-5p downregulation or NAIF1 overexpression on the growth of in vivo prostate cancer xenograft were evaluated.

Results

miR-125a-5p was upregulated in prostate cancer cell lines and human prostate carcinomas. Lentivirus induced miR-125a-5p downregulation in DU145 and VCaP cells inhibited prostate cancer cell proliferation or migration. NAIF1 was the direct target of miR-125a-5p, as both gene and protein expression levels of NAIF1, as well as caspase-3 were upregulated by miR-125a-5p. Forced overexpression of NAIF1 had similar antitumor effects as miR-125a-5p downregulation on prostate cancer cell proliferation and migration. In vivo prostate xenograft assay confirmed the tumor-suppressive effect of miR-125a-5p downregulation or NAIF1 overexpression.

Conclusion

miR-125a-5p regulates prostate cancer cell proliferation and migration through NAIF1.

Genome-wide analysis of microRNA and mRNA expression signatures in cancer

Cancer is an extremely diverse and complex disease that results from various genetic and epigenetic changes such as DNA copy-number variations, mutations, and aberrant mRNA and/or protein expression caused by abnormal transcriptional regulation. The expression profiles of certain microRNAs (miRNAs) and messenger RNAs (mRNAs) are closely related to cancer progression stages. In the past few decades, DNA microarray and next-generation sequencing techniques have been widely applied to identify miRNA and mRNA signatures for cancers on a genome-wide scale and have provided meaningful insights into cancer diagnosis, prognosis and personalized medicine. In this review, we summarize the progress in genome-wide analysis of miRNAs and mRNAs as cancer biomarkers, highlighting their diagnostic and prognostic roles.

MicroRNAs in Salivary Exosome as Potential Biomarkers of Aging

The aim of this study was to examine whether salivary exosomal miRNAs could be identified as aging biomarkers. Fifteen young healthy volunteers (median age, 21.0 years) and 13 old individuals (median age, 66.0 years) were recruited. Unstimulated whole saliva was collected, salivary exosomes were isolated, and total RNA was extracted. In a microarray, 242 miRNAs were commonly detected in these two mixed samples. Based on the cut-off values of 2- or 0.5-fold changes (FC) and regulatory power for aging process, six candidate miRNAs (miR-24-3p, miR-371a-5p, miR-3175, miR-3162-5p, miR-671-5p, and miR-4667-5p) were selected. After comparing each total RNA obtained by the 15 young and 13 old individuals to validate the FC values using quantitative real-time PCR, miR-24-3p was identified as a novel candidate aging biomarker. This pilot study suggested that salivary exosomal miRNAs could be identified as candidate aging biomarkers. To confirm whether miR-24-3p in salivary exosomes are suitable biomarkers of aging, further validation research is required.

Integrated analysis of miRNA, gene, and pathway regulatory networks in hepatic cancer stem cells

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. HCC has a poor prognosis associated with tumor recurrence and drug resistance, which has been attributed to the existence of hepatic cancer stem cells (HCSCs). However, the characteristics and regulatory mechanisms of HCSCs remain unclear. We therefore established a novel system to enrich HCSCs and we demonstrate that these HCSCs exhibit cancer stem cell properties.

METHODS

We used miRNA and mRNA high-throughput sequencing data sets to determine molecular signatures and regulatory mechanisms in HCSCs. Paired miRNA and gene deep sequencing data in HCSCs versus HCC cells were used to identify candidate biomarkers of HCSCs. Using network analysis, we studied the relationship between miRNA and gene biomarkers, and KEGG pathway enrichment analysis was performed to study the function of candidate biomarkers.

RESULTS

We identified 9 up- and 9 down-regulated miRNAs and 115 up- and 402 down-regulated genes in HCSCs compared with HCC cells. A miRNA-gene network was constructed using 651 miRNA-gene interactions (between 7 up-regulated miRNAs and 274 down-regulated genes), and 103 miRNA-gene interactions (between 9 down-regulated miRNAs and 62 up-regulated genes). Pathway enrichment analysis identified five tumor invasion- and metastasis-related pathways and MAPK signaling associated with HCSCs. We further discovered two novel pathways that likely play a role in the regulation of HCSCs.

CONCLUSIONS

We identified a molecular expression signature and pathway regulatory mechanisms in HCSCs with potential diagnostic and therapeutic value.

Effects of microRNA-221/222 on cell proliferation and apoptosis in prostate cancer cells

OBJECTIVE

To investigate the role of miR-221/222 in cell proliferation and apoptosis in human prostate cancer cells, and examine the effects of miR-221/222 on caspase-10 expression.

METHODS

Prostate cancer cells were transfected with miR-221/222 mimics or inhibitors. Cell proliferation was assessed by MTT assay. The expression levels of miR-221/222 were detected with quantitative real-time PCR. Apoptosis was induced with TNF-α/CHX treatment, and evaluated by Hoechst 33342 staining, propidium iodide (PI) flow cytometric analysis, caspase-3 activity measurement, and Western blot analysis. Luciferase activity assay, quantitative real-time PCR, and Western blot were performed to evaluate the effects of miR-221/222 on caspase-10 expression.

RESULTS

Our results showed that miR-221/222 could promote the proliferation of prostate cancer cells, including LNCaP and PC3 cells. After transfection and apoptosis induction, Hoechst 33342 staining and PI flow cytometric assay showed that apoptosis was dramatically decreased in prostate cancer cells treated with miR-221/222 mimics. Moreover, caspase-3 activity was dramatically decreased, and the cleaved forms of caspase-3 were reduced, in the miR-221/222 mimic-treated group. On the contrary, miR-221/222 knockdown sensitized the prostate cancer cells to TNF-α/CHX-induced apoptosis. In addition, a negative correlation was observed between the expressions of miR-221/222 and caspase-10 in prostate cancer cells. miR-221/222 could repress the expression of caspase-10, which was confirmed by the luciferase reporter assay.

CONCLUSION

miR-221/222 promote cell proliferation and repress apoptosis, through suppressing caspase-10, in prostate cancer cells. Our results provide promising evidence for the miRNA-based therapeutic strategy of prostate cancers.

Epigenetic modifications in prostate cancer

Prostate cancer is the most common cancer in men and the second leading cause of cancer deaths in men in France. Apart from the genetic alterations in prostate cancer, epigenetics modifications are involved in the development and progression of this disease. Epigenetic events are the main cause in gene regulation and the three most epigenetic mechanisms studied include DNA methylation, histone modifications and microRNA expression. In this review, we summarized epigenetic mechanisms in prostate cancer. Epigenetic drugs that inhibit DNA methylation, histone methylation and histone acetylation might be able to reactivate silenced gene expression in prostate cancer. However, further understanding of interactions of these enzymes and their effects on transcription regulation in prostate cancer is needed and has become a priority in biomedical research. In this study, we summed up epigenetic changes with emphasis on pharmacologic epigenetic target agents.

Discovery and characterization of long intergenic non-coding RNAs (lincRNA) module biomarkers in prostate cancer: an integrative analysis of RNA-Seq data

Background

Prostate cancer (PCa) is a leading cause of cancer-related death of men worldwide. There is an urgent need to develop novel biomarkers for PCa prognosis and diagnosis in the post prostate-specific antigen era. Long intergenic noncoding RNAs (lincRNAs) play essential roles in many physiological processes and can serve as alternative biomarkers for prostate cancer, but there has been no systematic investigation of lincRNAs in PCa yet.

Results

Nine lincRNA co-expression modules were identified from PCa RNA-Seq data. The association between the principle component of each module and the PCa phenotype was examined by calculating the Pearson's correlation coefficients. Three modules (M1, M3, and M5) were found associated with PCa. Two modules (M3 and M5) were significantly enriched with lincRNAs, and one of them, M3, may be used as a lincRNA module-biomarker for PCa diagnosis. This module includes seven essential lincRNAs: TCONS_l2_00001418, TCONS_l2_00008237, TCONS_l2_00011130, TCONS_l2_00013175, TCONS_l2_00022611, TCONS_l2_00022670 and linc-PXN-1. The clustering analysis and microRNA enrichment analysis further confirmed our findings.

Conclusion

The correlation between lincRNAs and protein-coding genes is helpful for further exploration of functional mechanisms of lincRNAs in PCa. This study provides some important insights into the roles of lincRNAs in PCa and suggests a few lincRNAs as candidate biomarkers for PCa diagnosis and prognosis.

MicroRNAs in melanocyte and melanoma biology

The importance of microRNAs as key molecular components of cellular processes is now being recognized. Recent reports have shown that microRNAs regulate processes as diverse as protein expression and nuclear functions inside cells and are able to signal extracellularly, delivered via exosomes, to influence cell fate at a distance. The versatility of microRNAs as molecular tools inspires the design of novel strategies to control gene expression, protein stability, DNA repair and chromatin accessibility that may prove very useful for therapeutic approaches due to the extensive manageability of these small molecules. However, we still lack a comprehensive understanding of the microRNA network and its interactions with the other layers of regulatory elements in cellular and extracellular functions. This knowledge may be necessary before we exploit microRNA versatility in therapeutic settings. To identify rules of interactions between microRNAs and other regulatory systems, we begin by reviewing microRNA activities in a single cell type: the melanocyte, from development to disease.

Key regulators in prostate cancer identified by co-expression module analysis

Background

Prostate cancer (PrCa) is the most commonly diagnosed cancer in men in the world. Despite the fact that a large number of its genes have been investigated, its etiology remains poorly understood. Furthermore, most PrCa candidate genes have not been rigorously replicated, and the methods by which they biologically function in PrCa remain largely unknown.

Results

Aiming to identify key players in the complex prostate cancer system, we reconstructed PrCa co-expressed modules within functional gene sets defined by the Gene Ontology (GO) annotation (biological process, GO_BP). We primarily identified 118 GO_BP terms that were well-preserved between two independent gene expression datasets and a consequent 55 conserved co-expression modules within them. Five modules were then found to be significantly enriched with PrCa candidate genes collected from expression Quantitative Trait Loci (eQTL), somatic copy number alteration (SCNA), somatic mutation data, or prognostic analyses. Specifically, two transcription factors (TFs) (NFAT and SP1) and three microRNAs (hsa-miR-19a, hsa-miR-15a, and hsa-miR-200b) regulating these five candidate modules were found to be critical to the development of PrCa.

Conclusions

Collectively, our results indicated that genes with similar functions may play important roles in disease through co-expression, and modules with different functions could be regulated by similar genetic components, such as TFs and microRNAs, in a synergistic manner.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1015) contains supplementary material, which is available to authorized users.

Identification of microRNAs as potential biomarker for gastric cancer by system biological analysis

Gastric cancers (GC) have the high morbidity and mortality rates worldwide and there is a need to identify sufficiently sensitive biomarkers for GC. MicroRNAs (miRNAs) could be promising potential biomarkers for GC diagnosis. We employed a systematic and integrative bioinformatics framework to identify GC-related microRNAs from the public microRNA and mRNA expression dataset generated by RNA-seq technology. The performance of the 17 candidate miRNAs was evaluated by hierarchal clustering, ROC analysis, and literature mining. Fourteen have been found to be associated with GC and three microRNAs (miR-211, let-7b, and miR-708) were for the first time reported to associate with GC and may be used for diagnostic biomarkers for GC.

Identification of microRNA as sepsis biomarker based on miRNAs regulatory network analysis

Sepsis is regarded as arising from an unusual systemic response to infection but the physiopathology of sepsis remains elusive. At present, sepsis is still a fatal condition with delayed diagnosis and a poor outcome. Many biomarkers have been reported in clinical application for patients with sepsis, and claimed to improve the diagnosis and treatment. Because of the difficulty in the interpreting of clinical features of sepsis, some biomarkers do not show high sensitivity and specificity. MicroRNAs (miRNAs) are small noncoding RNAs which pair the sites in mRNAs to regulate gene expression in eukaryotes. They play a key role in inflammatory response, and have been validated to be potential sepsis biomarker recently. In the present work, we apply a miRNA regulatory network based method to identify novel microRNA biomarkers associated with the early diagnosis of sepsis. By analyzing the miRNA expression profiles and the miRNA regulatory network, we obtained novel miRNAs associated with sepsis. Pathways analysis, disease ontology analysis, and protein-protein interaction network (PIN) analysis, as well as ROC curve, were exploited to testify the reliability of the predicted miRNAs. We finally identified 8 novel miRNAs which have the potential to be sepsis biomarkers.