An in silico analysis of microRNAs: mining the miRNAome

The role of miR-370 and miR-138 in the regulation of BMP2 suppressor gene expression in colorectal cancer: preliminary studies

PURPOSE

Colorectal cancer (CRC) is the fourth-most common cancer worldwide and the second most common cancer cause of death in the world. The components of the TGFβ-signalling pathway, which are often affected by miRNAs, are involved in the regulation of apoptosis and cell cycle. Therefore, in the current study, the expression of BMP2 gene in CRC tissues at different clinical stages compared to the non-tumour tissues has been assessed. Moreover, the plasma BMP2 protein concentration in the same group of CRC patients has been validated. Due to the constant necessity to conduct further research of the correlation between specific miRNAs and mRNAs in CRC, in silico analysis has been performed to select miRNAs that regulate BMP2 mRNA.

METHODS

The cDNA samples from tumor and non-tumor tissue were used in a qPCR reaction to determine the mRNA expression of the BMP2 gene and the expression of selected miRNAs. The concentration of BMP2 protein in plasma samples was also measured.

RESULTS

It was indicated that BMP2 was downregulated in CRC tissue. Moreover, miR-370 and miR-138 expression showed an upward trend. Decreased BMP2 with accompanied increasing miR-370 and miR-138 expression was relevant to the malignant clinicopathological features of CRC and consequently poor patient prognosis.

CONCLUSION

Our data suggest that miR-370 with its clear expression in plasma samples may be a potential diagnostic marker to determine the severity of the disease in patients at a later stage of colorectal cancer.

emiRIT: a text-mining-based resource for microRNA information

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information.

Database URL: https://research.bioinformatics.udel.edu/emirit/

Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation

Background

It is important but challenging to understand the interactions of multiple chronic conditions (MCC) and how they develop over time in patients and populations. Clinical data on MCC can now be represented using graphical models to study their interaction and identify the path toward the development of MCC. However, the current graphical models representing MCC are often complex and difficult to analyze. Therefore, it is necessary to develop improved methods for generating these models.

Objective

This study aimed to summarize the complex graphical models of MCC interactions to improve comprehension and aid analysis.

Methods

We examined the emergence of 5 chronic medical conditions (ie, traumatic brain injury [TBI], posttraumatic stress disorder [PTSD], depression [Depr], substance abuse [SuAb], and back pain [BaPa]) over 5 years among 257,633 veteran patients. We developed 3 algorithms that utilize the second eigenvalue of the graph Laplacian to summarize the complex graphical models of MCC by removing less significant edges. The first algorithm learns a sparse probabilistic graphical model of MCC interactions directly from the data. The second algorithm summarizes an existing probabilistic graphical model of MCC interactions when a supporting data set is available. The third algorithm, which is a variation of the second algorithm, summarizes the existing graphical model of MCC interactions with no supporting data. Finally, we examined the coappearance of the 100 most common terms in the literature of MCC to validate the performance of the proposed model.

Results

The proposed summarization algorithms demonstrate considerable performance in extracting major connections among MCC without reducing the predictive accuracy of the resulting graphical models. For the model learned directly from the data, the area under the curve (AUC) performance for predicting TBI, PTSD, BaPa, SuAb, and Depr, respectively, during the next 4 years is as follows—year 2: 79.91%, 84.04%, 78.83%, 82.50%, and 81.47%; year 3: 76.23%, 80.61%, 73.51%, 79.84%, and 77.13%; year 4: 72.38%, 78.22%, 72.96%, 77.92%, and 72.65%; and year 5: 69.51%, 76.15%, 73.04%, 76.72%, and 69.99%, respectively. This demonstrates an overall 12.07% increase in the cumulative sum of AUC in comparison with the classic multilevel temporal Bayesian network.

Conclusions

Using graph summarization can improve the interpretability and the predictive power of the complex graphical models of MCC.

Statistical principle-based approach for recognizing and normalizing microRNAs described in scientific literature

The detection of MicroRNA (miRNA) mentions in scientific literature facilitates researchers with the ability to find relevant and appropriate literature based on queries formulated using miRNA information. Considering most published biological studies elaborated on signal transduction pathways or genetic regulatory information in the form of figure captions, the extraction of miRNA from both the main content and figure captions of a manuscript is useful in aggregate analysis and comparative analysis of the studies published. In this study, we present a statistical principle-based miRNA recognition and normalization method to identify miRNAs and link them to the identifiers in the Rfam database. As one of the core components in the text mining pipeline of the database miRTarBase, the proposed method combined the advantages of previous works relying on pattern, dictionary and supervised learning and provided an integrated solution for the problem of miRNA identification. Furthermore, the knowledge learned from the training data was organized in a human-interpretable manner to understand the reason why the system considers a span of text as a miRNA mention, and the represented knowledge can be further complemented by domain experts. We studied the ambiguity level of miRNA nomenclature to connect the miRNA mentions to the Rfam database and evaluated the performance of our approach on two datasets: the BioCreative VI Bio-ID corpus and the miRNA interaction corpus by extending the later corpus with additional Rfam normalization information. Our study highlights and also proposes a better understanding of the challenges associated with miRNA identification and normalization in scientific literature and the research gap that needs to be further explored in prospective studies.

The TGFβ-signaling pathway and colorectal cancer: associations between dysregulated genes and miRNAs

Background

The TGFβ-signaling pathway plays an important role in the pathogenesis of colorectal cancer (CRC). Loss of function of several genes within this pathway, such as bone morphogenetic proteins (BMPs) have been seen as key events in CRC progression.

Methods

In this study we comprehensively evaluate differential gene expression (RNASeq) of 81 genes in the TGFβ-signaling pathway and evaluate how dysregulated genes are associated with miRNA expression (Agilent Human miRNA Microarray V19.0). We utilize paired carcinoma and normal tissue from 217 CRC cases. We evaluate the associations between differentially expressed genes and miRNAs and sex, age, disease stage, and survival months.

Results

Thirteen genes were significantly downregulated and 14 were significantly upregulated after considering fold change (FC) of > 1.50 or < 0.67 and multiple comparison adjustment. Bone morphogenetic protein genes BMP5, BMP6, and BMP2 and growth differentiation factor GDF7 were downregulated. BMP4, BMP7, INHBA (Inhibin beta A), TGFBR1, TGFB2, TGIF1, TGIF2, and TFDP1 were upregulated. In general, genes with the greatest dysregulation, such as BMP5 (FC 0.17, BMP6 (FC 0.25), BMP2 (FC 0.32), CDKN2B (FC 0.32), MYC (FC 3.70), BMP7 (FC 4.17), and INHBA (FC 9.34) showed dysregulation in the majority of the population (84.3, 77.4, 81.1, 80.2, 82.0, 51.2, and 75.1% respectively). Four genes, TGFBR2, ID4, ID1, and PITX2, were un-associated or slightly upregulated in microsatellite-stable (MSS) tumors while downregulated in microsatellite-unstable (MSI) tumors. Eight dysregulated genes were associated with miRNA differential expression. E2F5 and THBS1 were associated with one or two miRNAs; RBL1, TGFBR1, TGIF2, and INHBA were associated with seven or more miRNAs with multiple seed-region matches. Evaluation of the joint effects of mRNA:miRNA identified interactions that were stronger in more advanced disease stages and varied by survival months.

Conclusion

These data support an interaction between miRNAs and genes in the TGFβ-signaling pathway in association with CRC risk. These interactions are associated with unique clinical characteristics that may provide targets for further investigations.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1566-8) contains supplementary material, which is available to authorized users.

Gain-of-function miRNA signature by mutant p53 associates with poor cancer outcome

Missense mutation of p53 not only impairs its tumor suppression function, but also causes oncogenic gain of function (GOF). The molecular underpinning of mutant p53 (mutp53) GOF is not fully understood, especially for the potential roles of non-coding genes. Here we identify the microRNA expression profile (microRNAome) of mutp53 on Arg282 by controlled microarray experiments, and clarify the prognostic significance of mutp53-regulated miRNAs in cancers. A predominant repression effect on miRNA expression was found for mutant p53, with 183 significantly downregulated and only 12 upregulated miRNAs. Mutp53 and wild-type (wtp53) commonly upregulate let-7i, and other two miRNAs were upregulated by wtp53 but repressed by mutp53 (miR-610 and miR-3065–3p). Based the mutp53-regulated miRNA signature, a non-negative matrix factorization (NMF) model classified gastric cancer (GC) cases into subgroups with significantly different Disease-free survival (Kaplan-Meier test, P = 0.013). In contrast, the NMF model based on all miRNAs did not associate with cancer outcome. The mutp53 miRNA signature associated with the outcomes of breast cancer (P = 0.024) and hepatocellular cancer (P = 0.012). The miRPath analysis revealed that mutp53-suppressed miRNAs associate with Hippo, TGF-β and stem cell signaling pathways. Taken together, our results highlight a miRNA-mediated GOF mechanism of mutant p53 on Arg282, and suggest the prognostic potential of mutp53-associated miRNA signature.

Improving biocuration of microRNAs in diseases: a case study in idiopathic pulmonary fibrosis

MicroRNAs (miRNAs) are small and non-coding RNA molecules that inhibit gene expression posttranscriptionally. They play important roles in several biological processes, and in recent years there has been an interest in studying how they are related to the pathogenesis of diseases. Although there are already some databases that contain information for miRNAs and their relation with illnesses, their curation represents a significant challenge due to the amount of information that is being generated every day. In particular, respiratory diseases are poorly documented in databases, despite the fact that they are of increasing concern regarding morbidity, mortality and economic impacts. In this work, we present the results that we obtained in the BioCreative Interactive Track (IAT), using a semiautomatic approach for improving biocuration of miRNAs related to diseases. Our procedures will be useful to complement databases that contain this type of information. We adapted the OntoGene text mining pipeline and the ODIN curation system in a full-text corpus of scientific publications concerning one specific respiratory disease: idiopathic pulmonary fibrosis, the most common and aggressive of the idiopathic interstitial cases of pneumonia. We curated 823 miRNA text snippets and found a total of 246 miRNAs related to this disease based on our semiautomatic approach with the system OntoGene/ODIN. The biocuration throughput improved by a factor of 12 compared with traditional manual biocuration. A significant advantage of our semiautomatic pipeline is that it can be applied to obtain the miRNAs of all the respiratory diseases and offers the possibility to be used for other illnesses.

Database URL

http://odin.ccg.unam.mx/ODIN/bc2015-miRNA/.

Identifying factors associated with the direction and significance of microRNA tumor-normal expression differences in colorectal cancer

Background

microRNAs are small non-protein-coding RNA molecules that regulate gene expression, and have a potential epigenetic role in disease progression and survival of colorectal cancer. In terms of tumor-normal expression differences, many microRNAs exhibit evidence of being up-regulated in some subjects but down-regulated in others, or are dysregulated only for a subset of the population. We present and implement an approach to identify factors (lifestyle, tumor molecular phenotype, and survival-related) that are associated with the direction and/or significance of these microRNAs’ tumor-normal expression differences in colorectal cancer.

Methods

Using expression data for 1394 microRNAs and 1836 colorectal cancer subjects (each with both tumor and normal samples), we perform a dip test to identify microRNAs with multimodal distributions of tumor-normal expression differences. For proximal, distal, and rectal tumor sites separately, these microRNAs are tested for tumor-normal differential expression using a signed rank test, both overall and within levels of each lifestyle, tumor molecular phenotype, and survival-related factor. Appropriate adjustments are made to control the overall FDR.

Results

We identify hundreds of microRNAs whose direction and/or significance of tumor-normal differential expression is associated with one or more lifestyle, tumor molecular phenotype, or survival-related factors.

Conclusions

The results of this study demonstrate the benefit to colorectal cancer researchers to consider multiple subject-level factors when studying dysregulation of microRNAs, whose tumor-related changes in expression can be associated with multiple factors. Our results will serve as a publicly-available resource to provide clarifying information about various factors associated with the direction and significance of tumor-normal differential expression of microRNAs in colorectal cancer.

Electronic supplementary material

The online version of this article (10.1186/s12885-017-3690-x) contains supplementary material, which is available to authorized users.

The MicroRNA Interaction Network of Lipid Diseases

Background: Dyslipidemia is one of the major forms of lipid disorder, characterized by increased triglycerides (TGs), increased low-density lipoprotein-cholesterol (LDL-C), and decreased high-density lipoprotein-cholesterol (HDL-C) levels in blood. Recently, MicroRNAs (miRNAs) have been reported to involve in various biological processes; their potential usage being a biomarkers and in diagnosis of various diseases. Computational approaches including text mining have been used recently to analyze abstracts from the public databases to observe the relationships/associations between the biological molecules, miRNAs, and disease phenotypes. Materials and Methods: In the present study, significance of text mined extracted pair associations (miRNA-lipid disease) were estimated by one-sided Fisher's exact test. The top 20 significant miRNA-disease associations were visualized on Cytoscape. The CyTargetLinker plug-in tool on Cytoscape was used to extend the network and predicts new miRNA target genes. The Biological Networks Gene Ontology (BiNGO) plug-in tool on Cytoscape was used to retrieve gene ontology (GO) annotations for the targeted genes. Results: We retrieved 227 miRNA-lipid disease associations including 148 miRNAs. The top 20 significant miRNAs analysis on CyTargetLinker provides defined, predicted and validated gene targets, further targeted genes analyzed by BiNGO showed targeted genes were significantly associated with lipid, cholesterol, apolipoprotein, and fatty acids GO terms. Conclusion: We are the first to provide a reliable miRNA-lipid disease association network based on text mining. This could help future experimental studies that aim to validate predicted gene targets.

Infrequently expressed miRNAs influence survival after diagnosis with colorectal cancer

Half of miRNAs expressed in colorectal tissue are expressed < 50% of the population. Many infrequently expressed miRNAs have low levels of expression. We hypothesize that less frequently expressed miRNAs, when expressed at higher levels, influence both disease stage and survival after diagnosis with colorectal cancer (CRC); low levels of expression may be background noise.

We examine 304 infrequently expressed miRNAs in 1893 population-based cases of CRC with paired carcinoma and normal mucosa miRNA profiles. We evaluate miRNAs with disease stage and survival after adjusting for age, study center, sex, MSI status, and AJCC stage. These miRNAs were further evaluated with RNA-Seq data to identify miRNA::mRNA associations that may provide insight into the functionality of miRNAs.

Eleven miRNAs were associated with advanced disease stage among colon cancer patients (Q value = 0.10). Eight infrequently expressed miRNAs influenced survival if highly expressed in overall CRC. Of these, five increased likelihood of dying if they were highly expressed, i.e. miR-124-3p, miR-143-5p, miR-145-3p, miR31-5p, and miR-99b-5p, while three were associated with better survival if highly expressed, i.e. miR-362-5p, miR-374a-5p, and miR-590-5p. Thirteen miRNAs infrequently expressed in colon-specific carcinoma tissue were associated with CRC survival if highly expressed. Evaluation of miRNAs::mRNA associations showed that mRNA expression influenced by infrequently expressed miRNA contributed to networks and pathways shown to influence disease progression and prognosis.

Our large study enabled us to examine the implications of infrequently expressed miRNAs after removal of background noise. These results require replication in other studies. Confirmation of our findings in other studies could lead to important markers for prognosis.

Infrequently expressed miRNAs in colorectal cancer tissue and tumor molecular phenotype

We have previously shown that commonly expressed miRNAs influenced tumor molecular phenotype in colorectal cancer. We hypothesize that infrequently expressed miRNAs, when showing higher levels of expression, help to define tumor molecular phenotype. In this study, we examine 304 miRNAs expressed in at least 30 individuals, but in <50% of the population and with a mean level of expression above 1.0 relative florescent unit. We examine associations in 1893 individuals who have the tumor molecular phenotype data as well as miRNA expression levels for both carcinoma and normal colorectal tissue. We compare miRNAs uniquely associated with tumor molecular phenotype to the RNAseq data to identify genes associated with these miRNAs. This information is used to further identify unique pathways associated with tumor molecular phenotypes of TP53-mutated, KRAS-mutated, CpG island methylator phenotype and microsatellite instability tumors. Thirty-seven miRNAs were uniquely associated with TP53-mutated tumors; 30 of these miRNAs had higher level of expression in TP53-mutated tumors, while seven had lower levels of expression. Of the 34 miRNAs associated with CpG island methylator phenotype-high tumors, 16 were more likely to have a CpG island methylator phenotype-high tumor and 19 were less likely to be CpG island methylator phenotype-high. For microsatellite instability, 13 of the 22 infrequently expressed miRNAs were significantly less likely to be expressed in microsatellite unstable tumors. KRAS-mutated tumors were not associated with any miRNAs after adjustment for multiple comparisons. Of the dysregulated miRNAs, 17 were more likely to be TP53-mutated tumors while simultaneously being less likely to be CpG island methylator phenotype-high and/or microsatellite instability tumors. Genes regulated by these miRNAs were involved in numerous functions and pathways that influence cancer risk and progression. In summary, some infrequently expressed miRNAs, when expressed at higher levels, appear to have significant biological meaning in terms of tumor molecular phenotype and gene expression profiles.

The co-regulatory networks of tumor suppressor genes, oncogenes, and miRNAs in colorectal cancer

Tumor suppressor genes (TSGs) and oncogenes (OG) are involved in carcinogenesis. MiRNAs also contribute to cellular pathways leading to cancer. We use data from 217 colorectal cancer (CRC) cases to evaluate differences in TSGs and OGs expression between paired CRC and normal mucosa and evaluate how TSGs and OGs are associated with miRNAs. Gene expression data from RNA-Seq and miRNA expression data from Agilent Human miRNA Microarray V19.0 were used. We focus on genes most strongly associated with CRC (fold change (FC) of ≥1.5 or ≤0.67) that were statistically significant after adjustment for multiple comparisons. Of the 74 TSGs evaluated, 22 were associated with carcinoma/normal mucosa differential expression. Ten TSGs were up-regulated (FAM123B, RB1, TP53, RUNX1, MSH2, BRCA1, BRCA2, SOX9, NPM1, and RNF43); six TSGs were down-regulated (PAX5, IZKF1, GATA3, PRDM1, TET2, and CYLD); four were associated with MSI tumors (MLH1, PTCH1, and CEBPA down-regulated and MSH6 up-regulated); and two were associated with MSS tumors (PHF6 and ASXL1 up-regulated). Thirteen of these TSGs were associated with 44 miRNAs. Twenty-seven of the 59 OGs evaluated were dysregulated: 14 down-regulated (KLF4, BCL2, SSETBP1, FGFR2, TSHR, MPL, KIT, PDGFRA, GNA11, GATA2, FGFR3, AR, CSF1R, and JAK3), seven up-regulated (DNMT1, EZH2, PTPN11, SKP2, CCND1, MET, and MYC); three down-regulated for MSI (FLT3, CARD11, and ALK); two up-regulated for MSI (IDH2 and HRAS); and one up-regulated with MSS tumors (CTNNB1). These findings suggest possible co-regulatory function between TSGs, OGs, and miRNAs, involving both direct and indirect associations that operate through feedback and feedforward loops.

Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma

Endemic Burkitt lymphoma (eBL) is an aggressive B cell lymphoma and is associated with Epstein-Barr virus (EBV) and Plasmodium falciparum malaria co-infections. Central to BL oncogenesis is the over-expression of the MYC proto-oncogene which is caused by a translocation of an Ig enhancer in approximation to the myc gene. While whole genome/transcriptome sequencing methods have been used to define driver mutations and transcriptional dysregulation, microRNA (miRNA) dysregulation and differential expression has yet to be fully characterized. We hypothesized that both human and EBV miRNAs contribute to eBL clinical presentation, disease progression, and poor outcomes. Using sensitive and precise deep sequencing, we identified miRNAs from 17 Kenyan eBL patient tumor samples and delineated the complement of both host and EBV miRNAs. One human miRNA, hsa-miR-10a-5p was found to be differentially expressed (DE), being down-regulated in jaw tumors relative to abdominal and in non-survivors compared to survivors. We also examined EBV miRNAs, which made up 2.7% of the miRNA composition in the eBL samples. However, we did not find any significant associations regarding initial patient outcome or anatomical presentation. Gene ontology analysis and pathway enrichment of previously validated targets of miR-10a-5p suggest that it can promote tumor cell survival as well as aid in evasion of apoptosis. To examine miR-10a-5p regulatory effect on gene expression in eBL, we performed a pairwise correlation coefficient analysis on the expression levels of all its validated targets. We found a significant enrichment of correlated target genes consistent with miR-10a-5p impacting expression. The functions of genes and their correlation fit with multiple target genes impacting tumor resilience. The observed downregulation of miR-10a and associated genes suggests a role for miRNA in eBL patient outcomes and has potential as a predictive biomarker that warrants further investigation.

Extracting microRNA-gene relations from biomedical literature using distant supervision

Many biomedical relation extraction approaches are based on supervised machine learning, requiring an annotated corpus. Distant supervision aims at training a classifier by combining a knowledge base with a corpus, reducing the amount of manual effort necessary. This is particularly useful for biomedicine because many databases and ontologies have been made available for many biological processes, while the availability of annotated corpora is still limited. We studied the extraction of microRNA-gene relations from text. MicroRNA regulation is an important biological process due to its close association with human diseases. The proposed method, IBRel, is based on distantly supervised multi-instance learning. We evaluated IBRel on three datasets, and the results were compared with a co-occurrence approach as well as a supervised machine learning algorithm. While supervised learning outperformed on two of those datasets, IBRel obtained an F-score 28.3 percentage points higher on the dataset for which there was no training set developed specifically. To demonstrate the applicability of IBRel, we used it to extract 27 miRNA-gene relations from recently published papers about cystic fibrosis. Our results demonstrate that our method can be successfully used to extract relations from literature about a biological process without an annotated corpus. The source code and data used in this study are available at https://github.com/AndreLamurias/IBRel.

Single nucleotide polymorphisms within MicroRNAs, MicroRNA targets, and MicroRNA biogenesis genes and their impact on colorectal cancer survival

We have shown that single nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes, miRNA target genes, and miRNA biogenesis genes minimally contribute to colon cancer risk. It is possible that these SNPs alter survival. We analyzed 565 SNPs in or adjacent to microRNAs, target genes, or biogenesis genes, using 1,115 cases and 1,173 controls; 837 cases had survival information. We tested SNPs for associations with colorectal cancer (CRC) survival using a Cox proportional hazard model adjusting for age, study center, gender, AJCC disease stage, and MSI tumor status. Multiple comparison adjustments were made using the step-down Bonferroni correction. SNPs associated with survival (P_raw  < 0.05) also were assessed with messenger RNA (mRNA). Seven of the 565 SNPs analyzed were associated significantly with CRC survival after adjustment for multiple comparisons. Six of these increased risk of dying, and one, rs12140 (ADAMTS1) decreased risk of dying from CRC (HRR = 0.44, 95% CI (0.24, 0.83; P_Holm  = 0.011). Six SNPs altered colon cancer risk and five were associated with altered mRNA expression across genotypes. One SNP, rs2059691 (PRKRA), was associated with increased mRNA expression and worse survival, and one SNP, rs6598964 (LIN28A), decreased risk of developing colon cancer [OR = 0.77 95% CI (0.61, 0.98)] and increased risk of dying from CRC (HRR = 2.26 95% CI (1.52, 3.36). P_Holm  = 0.003). The few SNPs associated with CRC survival, colon cancer risk, or with mRNA expression, resided in genes that influence metastasis and angiogenesis. © 2017 Wiley Periodicals, Inc.

Diet and lifestyle factors associated with miRNA expression in colorectal tissue

MicroRNAs (miRNAs) are small non-protein-coding RNA molecules that regulate gene expression. Diet and lifestyle factors have been hypothesized to be involved in the regulation of miRNA expression. In this study it was hypothesized that diet and lifestyle factors are associated with miRNA expression. Data from 1,447 cases of colorectal cancer to evaluate 34 diet and lifestyle variables using miRNA expression in normal colorectal mucosa as well as for differential expression between paired carcinoma and normal tissue were used. miRNA data were obtained using an Agilent platform. Multiple comparisons were adjusted for using the false discovery rate q-value. There were 250 miRNAs differentially expressed between carcinoma and normal colonic tissue by level of carbohydrate intake and 198 miRNAs differentially expressed by the level of sucrose intake. Of these miRNAs, 166 miRNAs were differentially expressed for both carbohydrate intake and sucrose intake. Ninety-nine miRNAs were differentially expressed by the level of whole grain intake in normal colonic mucosa. Level of oxidative balance score was associated with 137 differentially expressed miRNAs between carcinoma and paired normal rectal mucosa. Additionally, 135 miRNAs were differentially expressed in colon tissue based on recent NSAID use. Other dietary factors, body mass index, waist and hip circumference, and long-term physical activity levels did not alter miRNA expression after adjustment for multiple comparisons. These results suggest that diet and lifestyle factors regulate miRNA level. They provide additional support for the influence of carbohydrate, sucrose, whole grains, NSAIDs, and oxidative balance score on colorectal cancer risk.

Colorectal tumor molecular phenotype and miRNA: expression profiles and prognosis

MiRNAs regulate gene expression by post-transcriptionally suppressing mRNA translation or by causing mRNA degradation. It has been proposed that unique miRNAs influence specific tumor molecular phenotype. In this paper, we test the hypotheses that miRNA expression differs by tumor molecular phenotype and that those differences may influence prognosis. Data come from population-based studies of colorectal cancer conducted in Utah and the Northern California Kaiser Permanente Medical Care Program. A total of 1893 carcinoma samples were run on the Agilent Human miRNA Microarray V19.0 containing 2006 miRNAs. We assessed differences in miRNA expression between TP53-mutated and non-mutated, KRAS-mutated and non-mutated, BRAF-mutated and non-mutated, CpG island methylator phenotype (CIMP) high and CIMP low, and microsatellite instability (MSI) and microsatellite stable (MSS) colon and rectal tumors. Using a Cox proportional hazard model we evaluated if those miRNAs differentially expressed by tumor phenotype influenced survival after adjusting for age, sex, and AJCC stage. There were 22 differentially expressed miRNAs for TP53-mutated colon tumors and 5 for TP53-mutated rectal tumors with a fold change of >1.49 (or <0.67). Additionally, 13 miRNAS were differentially expressed for KRAS-mutated rectal tumors, 8 differentially expressed miRNAs for colon CIMP high tumors, and 2 differentially expressed miRNAs for BRAF-mutated colon tumors. The majority of differentially expressed miRNAS were observed between MSI and MSS tumors (94 differentially expressed miRNAs for colon; 41 differentially expressed miRNAs for rectal tumors). Of these miRNAs differentially expressed between MSI and MSS tumors, the majority were downregulated. Ten of the differentially expressed miRNAs were associated with survival; after adjustment for MSI status, five miRNAS, miR-196b-5p, miR-31-5p, miR-99b-5p, miR-636, and miR-192-3p, were significantly associated with survival. In summary, it appears that the majority of miRNAs that are differentially expressed by tumor molecular phenotype are MSI tumors. However, these miRNAs appear to have minimal effect on prognosis.

Impact of polymorphisms in microRNA biogenesis genes on colon cancer risk and microRNA expression levels: a population-based, case-control study

Background

MicroRNAs (miRNAs) have been implicated in the incidence and progression of cancer. It has been proposed that single nucleotide polymorphisms (SNPs) influence cancer risk due to their position within genes involved in miRNA synthesis and regulation.

Methods

Genes directly and indirectly involved in miRNA biogenesis were identified from the literature. We then identified SNPs within these regions. Using genome-wide association study data we evaluated associations between biogenesis-related SNPs with colon cancer risk and their corresponding mRNA expression in normal colonic mucosa and carcinoma and difference in expression between the two tissues. SNPs that were associated with either altered colon cancer risk or with mRNA expression were evaluated for associations with altered miRNA expression.

Results

Eleven SNPs were associated (P < 0.05) with colon cancer risk, and two of these variants remained significant after correction for multiple comparisons (P_Holm < 0.05): rs1967327 (PRKRA) (OR_dom = 0.78, 95 % CI 0.66–0.92) and rs4548444 (MAPKAP2) (OR_rec = 1.67, 95 % CI 1.12–2.48). Of these two SNPs, rs4548444 (MAPKAP2), was associated with significantly altered miRNA expression levels in normal colonic mucosa, with nine miRNAs upregulated among individuals homozygous rare (GG) for rs4548444. One SNP associated with cancer prior to adjustment for multiple comparisons, rs11089328 (DGCR8), was associated with altered levels of hsa-miR-645 in differential tissue under the dominant model. Three SNPs, rs2740349 (GEMIN4) in carcinoma tissue, and rs235768 (BMP2) and rs2059691 (PRKRA) in normal mucosa, were significantly associated with altered mRNA expression levels across genotypes after multiple comparison adjustment. Rs2740349 (GEMIN4) and rs235768 (BMP2) were significantly associated with the upregulation of six and nine individual miRNAs in normal colonic mucosa, respectively.

Conclusion

Our data suggest that few of the SNPs in biogenesis genes we evaluated alter levels of mRNA transcription or colon cancer risk. As only one SNP both alters colon cancer risk and miRNA expression it is likely that SNPs influencing cancer do not do so through miRNAs. Because the significant SNPs were associated with downregulated mRNAs and upregulated miRNAs, and because each SNP was associated with unique miRNAs, it is possible that other mechanisms influence mature miRNA levels.

MicroRNA profiles in colorectal carcinomas, adenomas and normal colonic mucosa: variations in miRNA expression and disease progression

Roughly 27% of miRNAs are commonly expressed in colonic tissue; of these, over 86% are dysregulated between carcinoma and normal tissue when applying a false discovery rate of 0.05. MiRNA expression from normal to adenoma to carcinoma varied by miRNA and its frequency of expression in the population.

MiRNAs are small, non-protein-coding RNA molecules that regulate gene expression either by post-transcriptionally suppressing mRNA translation or by mRNA degradation. We examine differentially expressed miRNAs in colorectal carcinomas, adenomas and normal colonic mucosa. Data come from population-based studies of colorectal cancer conducted in Utah and the Kaiser Permanente Medical Care Program. A total of 1893 carcinoma/normal-paired samples and 290 adenoma tissue samples were run on the Agilent Human miRNA Microarray V19.0 which contained 2006 miRNAs. We tested for significant differences in miRNA expression between paired carcinoma/adenoma/normal colonic tissue samples. Fewer than 600 miRNAs were expressed in >80% of people for colonic tissue; of these 86.5% were statistically differentially expressed between carcinoma and normal colonic mucosa using a false discovery rate of 0.05. Roughly half of these differentially expressed miRNAs showed a progression in levels of expression from normal to adenoma to carcinoma tissue. Other miRNAs appeared to be altered at the normal to adenoma stage, while others were only altered at the adenoma to carcinoma stage or only at the normal to carcinoma stage. Evaluation of the Agilent platform showed a high degree of repeatability (r = 0.98) and reasonable agreement with the NanoString platform. Our data suggest that miRNAs are highly dysregulated in colorectal tissue among individuals with colorectal cancer; the pattern of disruption varies by miRNA as tissue progresses from normal to adenoma to carcinoma.

SNP Regulation of microRNA Expression and Subsequent Colon Cancer Risk

Introduction

MicroRNAs (miRNAs) regulate messenger RNAs (mRNAs) and as such have been implicated in a variety of diseases, including cancer. MiRNAs regulate mRNAs through binding of the miRNA 5’ seed sequence (~7–8 nucleotides) to the mRNA 3’ UTRs; polymorphisms in these regions have the potential to alter miRNA-mRNA target associations. SNPs in miRNA genes as well as miRNA-target genes have been proposed to influence cancer risk through altered miRNA expression levels.

Methods

MiRNA-SNPs and miRNA-target gene-SNPs were identified through the literature. We used SNPs from Genome-Wide Association Study (GWAS) data that were matched to individuals with miRNA expression data generated from an Agilent platform for colon tumor and non-tumor paired tissues. These samples were used to evaluate 327 miRNA-SNP pairs for associations between SNPs and miRNA expression levels as well as for SNP associations with colon cancer.

Results

Twenty-two miRNAs expressed in non-tumor tissue were significantly different by genotype and 21 SNPs were associated with altered tumor/non-tumor differential miRNA expression across genotypes. Two miRNAs were associated with SNP genotype for both non-tumor and tumor/non-tumor differential expression. Of the 41 miRNAs significantly associated with SNPs all but seven were significantly differentially expressed in colon tumor tissue. Two of the 41 SNPs significantly associated with miRNA expression levels were associated with colon cancer risk: rs8176318 (BRCA1), OR_AA 1.31 95% CI 1.01, 1.78, and rs8905 (PRKAR1A), OR_GG 2.31 95% CI 1.11, 4.77.

Conclusion

Of the 327 SNPs identified in the literature as being important because of their potential regulation of miRNA expression levels, 12.5% had statistically significantly associations with miRNA expression. However, only two of these SNPs were significantly associated with colon cancer.

Effectiveness and Usability of Bioinformatics Tools to Analyze Pathways Associated with miRNA Expression

MiRNAs are small, nonprotein-coding RNA molecules involved in gene regulation. While bioinformatics help guide miRNA research, it is less clear how they perform when studying biological pathways. We used 13 criteria to evaluate effectiveness and usability of existing bioinformatics tools. We evaluated the performance of six bioinformatics tools with a cluster of 12 differentially expressed miRNAs in colorectal tumors and three additional sets of 12 miRNAs that are not part of a known cluster. MiRPath performed the best of all the tools in linking miRNAs, with 92% of all miRNAs linked as well as the highest based on our established criteria followed by Ingenuity (58% linked). Other tools, including Empirical Gene Ontology, miRó, miRMaid, and PhenomiR, were limited by their lack of available tutorials, lack of flexibility and interpretability, and/or difficulty using the tool. In summary, we observed a lack of standardization across bioinformatic tools and a general lack of specificity in terms of pathways identified between groups of miRNAs. Hopefully, this evaluation will help guide the development of new tools.

Text Mining on Big and Complex Biomedical Literature

Driven by the rapidly advancing techniques and increasing interests in biology and medicine, about 2,000 to 4,000 references are added daily to MEDLINE, the US national biomedical bibliographic database. Even for a specific research topic, extracting useful and comprehensive information out of the huge literature data pool is challenging. Text mining techniques become extremely useful when dealing with the abundant biomedical information and they have been applied to various areas in the realm of biomedical research. Instead of providing a brief overview of all text mining techniques and every major biomedical text mining application, this chapter explores in-depth the microRNA profiling area and related text mining tools. As an illustrative example, one rule-based text mining system developed by the authors is discussed in detail. This chapter also includes the discussion of the challenges and potential research areas in biomedical text mining.

PRMT5 is required for human embryonic stem cell proliferation but not pluripotency

Human pluripotent stem cells (PSCs) are critical in vitro tools for understanding mechanisms that regulate lineage differentiation in the human embryo as well as a potentially unlimited supply of stem cells for regenerative medicine. Pluripotent human and mouse embryonic stem cells (ESCs) derived from the inner cell mass of blastocysts share a similar transcription factor network to maintain pluripotency and self-renewal, yet there are considerable molecular differences reflecting the diverse environments in which mouse and human ESCs are derived. In the current study we evaluated the role of Protein arginine methyltransferase 5 (PRMT5) in human ESC (hESC) self-renewal and pluripotency given its critical role in safeguarding mouse ESC pluripotency. Unlike the mouse, we discovered that PRMT5 has no role in hESC pluripotency. Using microarray analysis we discovered that a significant depletion in PRMT5 RNA and protein from hESCs changed the expression of only 78 genes, with the majority being repressed. Functionally, we discovered that depletion of PRMT5 had no effect on expression of OCT4, NANOG or SOX2, and did not prevent teratoma formation. Instead, we show that PRMT5 functions in hESCs to regulate proliferation in the self-renewing state by regulating the fraction of cells in Gap 1 (G1) of the cell cycle and increasing expression of the G1 cell cycle inhibitor P57. Taken together our data unveils a distinct role for PRMT5 in hESCs and identifies P57 as new target.

Detecting miRNA Mentions and Relations in Biomedical Literature

INTRODUCTION

MicroRNAs (miRNAs) have demonstrated their potential as post-transcriptional gene expression regulators, participating in a wide spectrum of regulatory events such as apoptosis, differentiation, and stress response. Apart from the role of miRNAs in normal physiology, their dysregulation is implicated in a vast array of diseases. Dissection of miRNA-related associations are valuable for contemplating their mechanism in diseases, leading to the discovery of novel miRNAs for disease prognosis, diagnosis, and therapy.

MOTIVATION

Apart from databases and prediction tools, miRNA-related information is largely available as unstructured text. Manual retrieval of these associations can be labor-intensive due to steadily growing number of publications. Additionally, most of the published miRNA entity recognition methods are keyword based, further subjected to manual inspection for retrieval of relations. Despite the fact that several databases host miRNA-associations derived from text, lower sensitivity and lack of published details for miRNA entity recognition and associated relations identification has motivated the need for developing comprehensive methods that are freely available for the scientific community. Additionally, the lack of a standard corpus for miRNA-relations has caused difficulty in evaluating the available systems. We propose methods to automatically extract mentions of miRNAs, species, genes/proteins, disease, and relations from scientific literature. Our generated corpora, along with dictionaries, and miRNA regular expression are freely available for academic purposes. To our knowledge, these resources are the most comprehensive developed so far.

RESULTS

The identification of specific miRNA mentions reaches a recall of 0.94 and precision of 0.93.  Extraction of miRNA-disease and miRNA-gene relations lead to an F 1 score of up to 0.76. A comparison of the information extracted by our approach to the databases miR2Disease and miRSel for the extraction of Alzheimer's disease related relations shows the capability of our proposed methods in identifying correct relations with improved sensitivity. The published resources and described methods can help the researchers for maximal retrieval of miRNA-relations and generation of miRNA-regulatory networks.

AVAILABILITY

The training and test corpora, annotation guidelines, developed dictionaries, and supplementary files are available at http://www.scai.fraunhofer.de/mirna-corpora.html.

Detecting miRNA Mentions and Relations in Biomedical Literature

INTRODUCTION

MicroRNAs (miRNAs) have demonstrated their potential as post-transcriptional gene expression regulators, participating in a wide spectrum of regulatory events such as apoptosis, differentiation, and stress response. Apart from the role of miRNAs in normal physiology, their dysregulation is implicated in a vast array of diseases. Dissection of miRNA-related associations are valuable for contemplating their mechanism in diseases, leading to the discovery of novel miRNAs for disease prognosis, diagnosis, and therapy.

MOTIVATION

Apart from databases and prediction tools, miRNA-related information is largely available as unstructured text. Manual retrieval of these associations can be labor-intensive due to steadily growing number of publications. Despite the fact that several databases host miRNA-associations derived from text, lower sensitivity has motivated the need for an improvised framework. Additionally, the lack of a standard corpus for miRNA-relations has caused difficulty in evaluating the available systems. We propose methods to automatically extract mentions of miRNAs, species, genes/proteins, disease, and relations from scientific literature. Our generated corpora, along with dictionaries, and miRNA regular expression are freely available for academic purposes. To our knowledge, these resources are the most comprehensive developed so far.

RESULTS

The identification of specific miRNA mentions reaches a recall of 0.94 and precision of 0.93.  Extraction of miRNA-disease and miRNA-gene relations lead to an F 1 score of up to 0.76. A comparison of the information extracted by our approach to the databases miR2Disease and miRSel for the extraction of Alzheimer's disease related relations shows the capability of our proposed methods in identifying correct relations with improved sensitivity. The published resources and described methods can help the researchers for maximal retrieval of miRNA-relations and generation of miRNA-regulatory networks.

AVAILABILITY

The training and test corpora, annotation guidelines, developed dictionaries, and supplementary files are available at http://www.scai.fraunhofer.de/mirna-corpora.html.

Detecting miRNA Mentions and Relations in Biomedical Literature

Introduction: MicroRNAs (miRNAs) have demonstrated their potential as post-transcriptional gene expression regulators, participating in a wide spectrum of regulatory events such as apoptosis, differentiation, and stress response. Apart from the role of miRNAs in normal physiology, their dysregulation is implicated in a vast array of diseases. Dissection of miRNA-related associations are valuable for contemplating their mechanism in diseases, leading to the discovery of novel miRNAs for disease prognosis, diagnosis, and therapy. Motivation: Apart from databases and prediction tools, miRNA-related information is largely available as unstructured text. Manual retrieval of these associations can be labor-intensive due to steadily growing number of publications. Additionally, most of the published miRNA entity recognition methods are keyword based, further subjected to manual inspection for retrieval of relations. Despite the fact that several databases host miRNA-associations derived from text, lower sensitivity and lack of published details for miRNA entity recognition and associated relations identification has motivated the need for developing comprehensive methods that are freely available for the scientific community. Additionally, the lack of a standard corpus for miRNA-relations has caused difficulty in evaluating the available systems. We propose methods to automatically extract mentions of miRNAs, species, genes/proteins, disease, and relations from scientific literature. Our generated corpora, along with dictionaries, and miRNA regular expression are freely available for academic purposes. To our knowledge, these resources are the most comprehensive developed so far. Results: The identification of specific miRNA mentions reaches a recall of 0.94 and precision of 0.93.  Extraction of miRNA-disease and miRNA-gene relations lead to an F 1 score of up to 0.76. A comparison of the information extracted by our approach to the databases miR2Disease and miRSel for the extraction of Alzheimer's disease related relations shows the capability of our proposed methods in identifying correct relations with improved sensitivity. The published resources and described methods can help the researchers for maximal retrieval of miRNA-relations and generation of miRNA-regulatory networks. Availability: The training and test corpora, annotation guidelines, developed dictionaries, and supplementary files are available at http://www.scai.fraunhofer.de/mirna-corpora.html.

Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs

Background

Transcription factors (TFs) have long been known to be principally activators of transcription in eukaryotes and prokaryotes. The growing awareness of the ubiquity of microRNAs (miRNAs) as suppressive regulators in eukaryotes, suggests the possibility of a mutual, preferential, self-regulatory connectivity between miRNAs and TFs. Here we investigate the connectivity from TFs and miRNAs to other genes and each other using text mining, TF promoter binding site and 6 different miRNA binding site prediction methods.

Results

In the first approach text mining of PubMed abstracts reveal statistically significant associations between miRNAs and both TFs and signal transduction gene classes. Secondly, prediction of miRNA targets in human and mouse 3’UTRs show enrichment only for TFs but not consistently across prediction methods for signal transduction or other gene classes. Furthermore, a random sample of 986 TarBase entries was scored for experimental evidence by manual inspection of the original papers, and enrichment for TFs was observed to increase with score. Low-scoring TarBase entries, where experimental evidence is anticorrelated miRNA:mRNA expression with predicted miRNA targets, appear not to select for real miRNA targets to any degree. Our manually validated text-mining results also suggests that miRNAs may be activated by more TFs than other classes of genes, as 7% of miRNA:TF co-occurrences in the literature were TFs activating miRNAs. This was confirmed when thirdly, we found enrichment for predicted, conserved TF binding sites in miRNA and TF genes compared to other gene classes.

Conclusions

We see enrichment of connections between miRNAs and TFs using several independent methods, suggestive of a network of mutual activating and suppressive regulation. We have also built regulatory networks (containing 2- and 3-loop motifs) for mouse and human using predicted miRNA and TF binding sites and we have developed a web server to search and display these loops, available for the community at http://rth.dk/resources/tfmirloop.

Dynamic changes in the microRNA expression profile reveal multiple regulatory mechanisms in the spinal nerve ligation model of neuropathic pain

Neuropathic pain resulting from nerve lesions or dysfunction represents one of the most challenging neurological diseases to treat. A better understanding of the molecular mechanisms responsible for causing these maladaptive responses can help develop novel therapeutic strategies and biomarkers for neuropathic pain. We performed a miRNA expression profiling study of dorsal root ganglion (DRG) tissue from rats four weeks post spinal nerve ligation (SNL), a model of neuropathic pain. TaqMan low density arrays identified 63 miRNAs whose level of expression was significantly altered following SNL surgery. Of these, 59 were downregulated and the ipsilateral L4 DRG, not the injured L5 DRG, showed the most significant downregulation suggesting that miRNA changes in the uninjured afferents may underlie the development and maintenance of neuropathic pain. TargetScan was used to predict mRNA targets for these miRNAs and it was found that the transcripts with multiple predicted target sites belong to neurologically important pathways. By employing different bioinformatic approaches we identified neurite remodeling as a significantly regulated biological pathway, and some of these predictions were confirmed by siRNA knockdown for genes that regulate neurite growth in differentiated Neuro2A cells. In vitro validation for predicted target sites in the 3′-UTR of voltage-gated sodium channel Scn11a, alpha 2/delta1 subunit of voltage-dependent Ca-channel, and purinergic receptor P2rx ligand-gated ion channel 4 using luciferase reporter assays showed that identified miRNAs modulated gene expression significantly. Our results suggest the potential for miRNAs to play a direct role in neuropathic pain.