SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data

Bioinformatics analysis of a disease-specific lncRNA-miRNA-mRNA regulatory network in recurrent spontaneous abortion (RSA)

BACKGROUND

This study investigated the molecular mechanisms of long non-coding RNAs (lncRNAs) in RSA using the lncRNA-miRNA-mRNA regulatory network.

METHODS

The present study obtained expression datasets of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) from blood samples of individuals with unexplained recurrent spontaneous abortion (RSA) and healthy controls. Differentially expressed lncRNAs (DELs), mRNAs (DEMs), and miRNAs (DEmiRs) were identified. A regulatory network comprising lncRNA, miRNA, and mRNA was constructed, and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEM. Also, a protein-protein interaction (PPI) network was made and key genes were identified.

RESULTS

A total of 57 DELs, 212 DEmiRs, and 301 DEMs regarding RSA were identified. Later analysis revealed a lncRNA-miRNA-mRNA network comprising nine lncRNAs, 14 miRNAs, and 65 mRNAs. Then, the ceRNA network genes were subjected to functional enrichment and pathway analysis, which showed their association with various processes, such as cortisol and thyroid hormone synthesis and secretion, human cytomegalovirus infection, and parathyroid hormone synthesis. In addition, ten hub genes (ITGB3, GNAI2, GNAS, SRC, PLEC, CDC42, RHOA, RAC1, CTNND1, and FN1) were identified based on the PPI network results.

CONCLUSION

In summary, the outcomes of our study provided some data regarding the alteration genes involved in RSA pathogenic mechanism via the lncRNA-miRNA-mRNA network and reveal the possibility of identifying new lncRNAs and miRNAs as promising molecular biomarkers.

Post-prostatic-massage urine exosomes of men with chronic prostatitis/chronic pelvic pain syndrome carry prostate-cancer-typical microRNAs and activate proto-oncogenes

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) has a high prevalence of up to 15% and accounts for 90-95% of prostatitis diagnoses, and yet its etiopathogenesis and link to prostate cancer (PCa) are still unclear. Here, we investigated microRNAs in exosomes isolated from blood and post-prostatic-massage urine of CP/CPPS type IIIb patients and healthy men. THP-1 monocytes (human leukemia monocytic cell line) were treated with exosomes and subjected to mRNA arrays "Cancer Inflammation and Immunity Crosstalk" and "Transcription Factors." Using The Cancer Genome Atlas, the expression of CP/CPPS-associated microRNAs was analyzed in PCa and normal prostate tissue. In silico functional studies were carried out to explore the disease ontology of CP/CPPS. In CP/CPPS, urine exosomes exhibited significant upregulation of eight PCa-specific microRNAs (e.g., hsa-miR-501, hsa-miR-20a, and hsa-miR-106), whose target genes were significantly enriched for GO terms, hallmark gene sets, and pathways specific for carcinogenesis. In THP-1 monocytes, CP/CPPS-derived urine exosomes induced upregulation of PCa-associated proinflammatory genes (e.g., CCR2 and TLR2) and proto-oncogene transcription factors (e.g., MYB and JUNB). In contrast, CP/CPPS-derived blood exosomes exhibited molecular properties similar to those of healthy men. Thus, CP/CPPS exhibits molecular changes that constitute a risk for PCa and should be considered in the development of PCa biomarkers and cancer screening programs.

MiRNAs from serum-derived extracellular vesicles as biomarkers for uveal melanoma progression

Uveal melanoma (UM) is a rare type of malignancy that originates from melanocytes in the choroid, iris and the eye's ciliary body. Biomarkers for early detection and progression of UM, especially the molecular traits governing the development of metastasis, are still not available in clinical practice. One extensively studied components of liquid biopsies are extracellular vesicles. Due to their unique molecular cargo, they can contribute to early cancer development and at the same time carry markers for disease onset and progression. For characterisation of the miRNA profiles present in circulating serum-derived exosomes of patients with diagnosed primary and metastatic UM, we have analyzed the miRNA cargos using next-generation sequencing followed by RT-qPCR validation in a cohort of patients (control n = 20; primary n = 9; metastatic n = 11). Nine miRNAs differentiating these patient groups have been established. We show that hsa-miR-144-5p and hsa-miR-191-5p are the most promising biomarker candidates, allowing the categorization of patients into local and advanced UM. Additionally, the comparison of miRNA expression levels in exosomes derived from UM patients with those derived from healthy donors revealed that hsa-miR-191-5p, -223-3p, -483-5p, -203a has the potential to be used as an early marker for the presence of UM. This pilot study reveals that miRNAs extracted from circulating exosomes could be exploited as potential biomarkers in UM diagnosis and, more importantly, for indicating metastatic spread.

Integration of p16/HPV DNA Status with a 24-miRNA-Defined Molecular Phenotype Improves Clinically Relevant Stratification of Head and Neck Cancer Patients

Simple Summary

Human papillomavirus (HPV)-driven head and neck squamous cell carcinomas (HNSCC), regarded as a distinct clinical entity, are characterized by a considerably favourable prognosis after radio(chemo)therapy and a not yet fully understood distinct molecular pathogenesis. We aimed to develop a miRNA-signature that identifies HPV-associated HNSCC according to their specific molecular pathogenesis, and to characterise the transcriptome compared to HPV-negative HNSCC. We performed miRNA expression profiling of n = 229 HPV characterized HNSCC specimens of patients treated by adjuvant radio(chemo) therapy. Using lasso-regression, a 24-miRNA signature predicting HPV-status was built in a multicentre cohort and validated in a single-centre cohort. Its combination with p16/HPV DNA status improved clinically relevant risk stratification, allowed the identification of an HPV-associated patient subgroup with impaired overall survival, and might be considered for future clinical decision-making. miRNA-transcriptome integration identified HPV-specific signaling pathways.

Abstract

Human papillomavirus (HPV)-driven head and neck squamous cell carcinomas (HNSCC) generally have a more favourable prognosis. We hypothesized that HPV-associated HNSCC may be identified by an miRNA-signature according to their specific molecular pathogenesis, and be characterized by a unique transcriptome compared to HPV-negative HNSCC. We performed miRNA expression profiling of two p16/HPV DNA characterized HNSCC cohorts of patients treated by adjuvant radio(chemo)therapy (multicentre DKTK-ROG n = 128, single-centre LMU-KKG n = 101). A linear model predicting HPV status built in DKTK-ROG using lasso-regression was tested in LMU-KKG. LMU-KKG tumours (n = 30) were transcriptome profiled for differential gene expression and miRNA-integration. A 24-miRNA signature predicted HPV-status with 94.53% accuracy (AUC: 0.99) in DKTK-ROG, and 86.14% (AUC: 0.86) in LMU-KKG. The prognostic values of 24-miRNA- and p16/HPV DNA status were comparable. Combining p16/HPV DNA and 24-miRNA status allowed patient sub-stratification and identification of an HPV-associated patient subgroup with impaired overall survival. HPV-positive tumours showed downregulated MAPK, Estrogen, EGFR, TGFbeta, WNT signaling activity. miRNA-mRNA integration revealed HPV-specific signaling pathway regulation, including PD−L1 expression/PD−1 checkpoint pathway in cancer in HPV-associated HNSCC. Integration of clinically established p16/HPV DNA with 24-miRNA signature status improved clinically relevant risk stratification, which might be considered for future clinical decision-making with respect to treatment de-escalation in HPV-associated HNSCC.

The Profile of MicroRNA Expression and Potential Role in the Regulation of Drug-Resistant Genes in Doxorubicin and Topotecan Resistant Ovarian Cancer Cell Lines

Epithelial ovarian cancer has the highest mortality among all gynecological malignancies. The main reasons for high mortality are late diagnosis and development of resistance to chemotherapy. Resistance to chemotherapeutic drugs can result from altered expression of drug-resistance genes regulated by miRNA. The main goal of our study was to detect differences in miRNA expression levels in two doxorubicin (DOX)- and two topotecan (TOP)-resistant variants of the A2780 drug-sensitive ovarian cancer cell line by miRNA microarray. The next aim was to recognize miRNAs as factors responsible for the regulation of drug-resistance genes. We observed altered expression of 28 miRNA that may be related to drug resistance. The upregulation of miR-125b-5p and miR-935 and downregulation of miR-218-5p was observed in both DOX-resistant cell lines. In both TOP-resistant cell lines, we noted the overexpression of miR-99a-5p, miR-100-5p, miR-125b-5p, and miR-125b-2-3p and decreased expression of miR-551b-3p, miR-551b-5p, and miR-383-5p. Analysis of the targets suggested that expression of important drug-resistant genes such as the collagen type I alpha 2 chain (COL1A2), protein Tyrosine Phosphatase Receptor Type K (PTPRK), receptor tyrosine kinase—EPHA7, Roundabout Guidance Receptor 2 (ROBO2), myristoylated alanine-rich C-kinase substrate (MARCK), and the ATP-binding cassette subfamily G member 2 (ABCG2) can be regulated by miRNA.

The Profile of MicroRNA Expression and Potential Role in the Regulation of Drug-Resistant Genes in Cisplatin- and Paclitaxel-Resistant Ovarian Cancer Cell Lines

Ovarian cancer is the most lethal gynecological malignancy. The high mortality results from late diagnosis and the development of drug resistance. Drug resistance results from changes in the expression of different drug-resistance genes that may be regulated miRNA. The main aim of our study was to detect changes in miRNA expression levels in two cisplatin (CIS) and two paclitaxel (PAC)—resistant variants of the A2780 drug-sensitive ovarian cancer cell line—by miRNA microarray. The next goal was to identify miRNAs responsible for the regulation of drug-resistance genes. We observed changes in the expression of 46 miRNA that may be related to drug resistance. The overexpression of miR-125b-5p, miR-99a-5p, miR-296-3p, and miR-887-3p and downregulation of miR-218-5p, miR-221-3p, and miR-222-3p was observed in both CIS-resistant cell lines. In both PAC-resistant cell lines, we observed the upregulation of miR-221-3p, miR-222-3p, and miR-4485, and decreased expression of miR-551b-3p, miR-551b-5p, and miR-218-5p. Analysis of targets suggest that expression of important drug-resistant genes like protein Tyrosine Phosphatase Receptor Type K (PTPRK), receptor tyrosine kinase—EPHA7, Semaphorin 3A (SEMA3A), or the ATP-binding cassette subfamily B member 1 gene (ABCB1) can be regulated by miRNA.

Coordinated regulation of gene expression and microRNA changes in adipose tissue and circulating extracellular vesicles in response to pioglitazone treatment in humans with type 2 diabetes

Pioglitazone, a PPARγ agonist, is used to treat type 2 diabetes (T2D). PPARγ is highly expressed in adipose tissue (AT), however the effects of pioglitazone to improve insulin sensitivity are also evident in other tissues and PPARγ agonism has been shown to alter cancer derived extracellular vesicle (EV)-miRNAs. We hypothesized that pioglitazone modifies the cargo of circulating AT-derived EVs to alter interorgan crosstalk in people with diabetes. We tested our hypothesis in a 3-month trial in which 24 subjects with T2D were randomized to treatment with either pioglitazone 45 mg/day or placebo (NCT00656864). Levels of 42 adipocyte-derived EV-miRNAs were measured in plasma EVs using low density TaqMan arrays. Levels of differentially expressed EV-miRNAs and their most relevant target genes were also measure in adipose tissue from the same participants, using individual TaqMan assays. Levels of 5 miRNAs (i.e., miR-7-5p, miR-20a-5p, miR-92a-3p, miR-195-5p, and miR-374b-5p) were significantly downregulated in EVs in response to pioglitazone treatment relative to placebo. The opposite occurred for miR-195-5p in subcutaneous AT. Changes in miRNA expression in EVs and AT correlated with changes in suppression of lipolysis and improved insulin sensitivity, among others. DICER was downregulated and exosomal miRNA sorting-related genes YBX1 and hnRNPA2B1 displayed a downregulation trend in AT. Furthermore, analysis of EV-miRNA targeted genes identified a network of transcripts that changed in a coordinated manner in AT. Collectively, our results suggest that some beneficial pharmacologic effects of pioglitazone are mediated by adipose-specific miRNA regulation and exosomal/EV trafficking.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, identifier NCT00656864.

A Preliminary Study on the Pathogenesis of Colorectal Cancer by Constructing a Hsa-circRNA-0067835-miRNA-mRNA Regulatory Network

Background

Increasing evidence shows that circular RNAs (circRNAs) play a key role in the development of colorectal cancer (CRC). An interesting candidate RNA in this context is hsa-circRNA-0067835 (circIFT80), but its network of actions is still unclear.

Methods

Big data mining technology was used to explore the downstream microRNAs (miRNA) and messenger RNAs (mRNA) of the circIFT80 network. A regulatory network, comprising circIFT80 and its corresponding miRNAs and mRNAs, was derived to preliminarily explore the potential mechanism of circIFT80 in CRC. Finally, the proposed regulatory network was experimentally verified at the cellular level.

Results

A total of 6 miRNAs were screened, of which hsa-miR-197-3p, hsa-miR-370-3p and hsa-miR-377-5p may be the most potential downstream miRNAs of hsa-circRNA-0067835 in CRC. A total of 74 up-regulated genes with opposite miRNA expression were selected for subsequent verification. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases revealed that the target genes occurred more frequently in cancer-related pathways. In addition, protein-protein interaction (PPI) analysis of the target genes revealed a set of involved genes from which the hubTop 10 genes were selected for further analysis. Moreover, circRNA-miRNA-hubTop 10 mRNA networks were constructed. According to this analysis, circIFT80 simultaneously regulates hsa-miR-197-3p, hsa-miR-370-3p, and hsa-miR-377-5p, among which hsa-miR-370-3p seems to be associated with further genes that may be relevant to CRC development. Therefore, the proposed circIFT80/hsa-miR-370-3p/WNT7B, SLC1A5, RCBTB1 and COL6A6 signal axes were subjected to experimental verification. It could be shown that circIFT80 was up-regulated in CRC tissues. The circIFT80 was able to inhibit apoptosis and promote proliferation, migration and invasion. Moreover, circIFT80 inhibited the expression of hsa-miR-370-3p and promoted the expression of COL6A6, RCBTB1, SLC1A5 and WNT7B in CRC cell lines. Dual luciferase reporter assays further validated that circIFT80 is able to bind to hsa-miR-370-3p which in turn targets WNT7B.

Conclusion

The circIFT80 may play a role in carcinogenesis through the new circIFT80/hsa-miR-370-3p/WNT7B signal axis. These findings may provide potential biomarkers and therapeutic targets for the treatment of CRC.

TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis

Motivation

The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)–mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA–mRNA datasets.

Results

We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA–mRNA interactions influencing signaling pathways of interest. miRNA–mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction.

Availability and implementation

TimiRGeN is available for download on Bioconductor (https://bioconductor.org/packages/TimiRGeN) and requires R v4.0.2 or newer and BiocManager v3.12 or newer.

Supplementary information

Supplementary data are available at Bioinformatics online.

STATegra: Multi-Omics Data Integration - A Conceptual Scheme With a Bioinformatics Pipeline

Technologies for profiling samples using different omics platforms have been at the forefront since the human genome project. Large-scale multi-omics data hold the promise of deciphering different regulatory layers. Yet, while there is a myriad of bioinformatics tools, each multi-omics analysis appears to start from scratch with an arbitrary decision over which tools to use and how to combine them. Therefore, it is an unmet need to conceptualize how to integrate such data and implement and validate pipelines in different cases. We have designed a conceptual framework (STATegra), aiming it to be as generic as possible for multi-omics analysis, combining available multi-omic anlaysis tools (machine learning component analysis, non-parametric data combination, and a multi-omics exploratory analysis) in a step-wise manner. While in several studies, we have previously combined those integrative tools, here, we provide a systematic description of the STATegra framework and its validation using two The Cancer Genome Atlas (TCGA) case studies. For both, the Glioblastoma and the Skin Cutaneous Melanoma (SKCM) cases, we demonstrate an enhanced capacity of the framework (and beyond the individual tools) to identify features and pathways compared to single-omics analysis. Such an integrative multi-omics analysis framework for identifying features and components facilitates the discovery of new biology. Finally, we provide several options for applying the STATegra framework when parametric assumptions are fulfilled and for the case when not all the samples are profiled for all omics. The STATegra framework is built using several tools, which are being integrated step-by-step as OpenSource in the STATegRa Bioconductor package.

Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

Circulating microRNA: The Potential Novel Diagnostic Biomarkers to Predict Drug Resistance in Temporal Lobe Epilepsy, a Pilot Study

MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as new potential epigenetic biomarkers. Here, we evaluate the efficacy of six circulating miRNA previously described in the literature as biomarkers for the diagnosis of temporal lobe epilepsy (TLE) and/or as predictive biomarkers to antiepileptic drug response. We measured the differences in serum miRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays in a cohort of 27 patients (14 women and 13 men; mean ± SD age: 43.65 ± 17.07) with TLE compared to 20 healthy controls (HC) matched for sex, age and ethnicity (11 women and 9 men; mean ± SD age: 47.5 ± 9.1). Additionally, patients were classified according to whether they had drug-responsive (n = 17) or drug-resistant (n = 10) TLE. We have investigated any correlations between miRNAs and several electroclinical parameters. Three miRNAs (miR-142, miR-146a, miR-223) were significantly upregulated in patients (expressed as average expression ± SD). In detail, miR-142 expression was 0.40 ± 0.29 vs. 0.16 ± 0.10 in TLE patients compared to HC (t-test, p < 0.01), miR-146a expression was 0.15 ± 0.11 vs. 0.07 ± 0.04 (t-test, p < 0.05), and miR-223 expression was 6.21 ± 3.65 vs. 1.23 ± 0.84 (t-test, p < 0.001). Moreover, results obtained from a logistic regression model showed the good performance of miR-142 and miR-223 in distinguishing drug-sensitive vs. drug-resistant TLE. The results of this pilot study give evidence that miRNAs are suitable targets in TLE and offer the rationale for further confirmation studies in larger epilepsy cohorts.

Prioritization of potential drug targets and antigenic vaccine candidates against Klebsiella aerogenes using the computational subtractive proteome-driven approach

Klebsiella aerogenes is a multidrug-resistant Gram-negative bacterium that causes nosocomial infections. The organism showed resistance to most of the conventional antibiotics available. Because of the high resistance of the species, the treatment of K. aerogenes is difficult. These species are resistant to third-generation cephalosporins due to the production of chromosomal beta-lactams with cephalosporin activity. The lack of better treatment and the development of therapeutic resistance in hospitals hinders better/new broad-spectrum-based treatment against this pathogen. This study identifies potential drug targets/vaccine candidates through a computational subtractive proteome-driven approach. This method is used to predict proteins that are not homologous to humans and human symbiotic intestinal flora. The resultant proteome of K. aerogenes was further searched for proteins, which are essential, virulent, and determinants of antibiotic/drug resistance. Subsequently, their druggability properties were also studied. The data set was reduced based on its presence in the pathogen-specific metabolic pathways. The subtractive proteome analysis predicted 13 proteins as potential drug targets for K. aerogenes. Furthermore, these target proteins were annotated based on their spectrum of activity, cellular localization, and antigenicity properties, which ensured that they are potent candidates for broad-spectrum antibiotic and vaccine design. The results open up new opportunities for designing and manufacturing powerful antigenic vaccines against K. aerogenes and the detection and release of new and active drugs against K. aerogenes without altering the gut microbiome.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42485-021-00068-9.

NRASQ61K melanoma tumor formation is reduced by p38-MAPK14 activation in zebrafish models and NRAS-mutated human melanoma cells

Oncogenic BRAF and NRAS mutations drive human melanoma initiation. We used transgenic zebrafish to model NRAS-mutant melanoma, and the rapid tumor onset allowed us to study candidate tumor suppressors. We identified P38α-MAPK14 as a potential tumor suppressor in The Cancer Genome Atlas melanoma cohort of NRAS-mutant melanomas, and overexpression significantly increased the time to tumor onset in transgenic zebrafish with NRAS-driven melanoma. Pharmacological activation of P38α-MAPK14 using anisomycin reduced in vitro viability of melanoma cultures, which we confirmed by stable overexpression of p38α. We observed that the viability of MEK inhibitor resistant melanoma cells could be reduced by combined treatment of anisomycin and MEK inhibition. Our study demonstrates that activating the p38α-MAPK14 pathway in the presence of oncogenic NRAS abrogates melanoma in vitro and in vivo. SIGNIFICANCE: The significance of our study is in the accountability of NRAS mutations in melanoma. We demonstrate here that activation of p38α-MAPK14 pathway can abrogate NRAS-mutant melanoma which is contrary to the previously published role of p38α-MAPK14 pathway in BRAF mutant melanoma. These results implicate that BRAF and NRAS-mutant melanoma may not be identical biologically. We also demonstrate the translational benefit of our study by using a small molecule compound-anisomycin (already in use for other diseases in clinical trials) to activate p38α-MAPK14 pathway.

H19, a Long Non-coding RNA, Mediates Transcription Factors and Target Genes through Interference of MicroRNAs in Pan-Cancer

Long non-coding RNAs (lncRNAs) have recently been found to be important in gene regulation. lncRNA H19 has been reported to play an oncogenic role in many human cancers. Its specific regulatory role is still elusive. In this study, we developed a novel analytic approach by integrating the synergistic regulation among lncRNAs (e.g., H19), transcription factors (TFs), target genes, and microRNAs (miRNAs) and then applied it to the pan-cancer expression datasets from The Cancer Genome Atlas (TCGA). Using linear regression models, we identified 88 H19-TF-gene co-regulatory triplets, in which 93% of the TF-gene pairs were related to cancer, indicating that our approach was effective to identify disease-related lncRNA-TF-gene co-regulation mechanisms. lncRNAs can function as miRNA sponges. Our further experiments found that H19 might regulate SP1-TGFBR2 through let-7b and miR-200b, ETS1-TGFBR2 through miR-29a and miR-200b, and STAT3-KLF11 through miR-17 in breast cancer cell lines. Our work suggests that miRNA-mediated lncRNA-TF-gene co-regulation is complicated yet important in cancer.

A protein interaction map identifies existing drugs targeting SARS-CoV-2

BACKGROUND

Severe acute respiratory syndrome coronavirus (SARS-CoV-2), an emerging Betacoronavirus, is the causative agent of COVID-19. Angiotensin converting enzyme 2 (ACE2), being the main cell receptor of SARS-CoV-2, plays a role in the entry of the virus into the cell. Currently, there are neither specific antiviral drugs for the treatment or preventive drugs such as vaccines.

METHODS

We proposed a bioinformatics analysis to test in silico existing drugs as a fast way to identify an efficient therapy. We performed a differential expression analysis in order to identify differentially expressed genes in COVID-19 patients correlated with ACE-2 and we explored their direct relations with a network approach integrating also drug-gene interactions. The drugs with a central role in the network were also investigated with a molecular docking analysis.

RESULTS

We found 825 differentially expressed genes correlated with ACE2. The protein-protein interactions among differentially expressed genes identified a network of 474 genes and 1130 interactions.

CONCLUSIONS

The integration of drug-gene interactions in the network and molecular docking analysis allows us to obtain several drugs with antiviral activity that, alone or in combination with other treatment options, could be considered as therapeutic approaches against COVID-19.

(Differential) Co-Expression Analysis of Gene Expression: A Survey of Best Practices

Analysis of gene expression data is widely used in transcriptomic studies to understand functions of molecules inside a cell and interactions among molecules. Differential co-expression analysis studies diseases and phenotypic variations by finding modules of genes whose co-expression patterns vary across conditions. We review the best practices in gene expression data analysis in terms of analysis of (differential) co-expression, co-expression network, differential networking, and differential connectivity considering both microarray and RNA-seq data along with comparisons. We highlight hurdles in RNA-seq data analysis using methods developed for microarrays. We include discussion of necessary tools for gene expression analysis throughout the paper. In addition, we shed light on scRNA-seq data analysis by including preprocessing and scRNA-seq in co-expression analysis along with useful tools specific to scRNA-seq. To get insights, biological interpretation and functional profiling is included. Finally, we provide guidelines for the analyst, along with research issues and challenges which should be addressed.

The Significance of MicroRNAs Expression in Regulation of Extracellular Matrix and Other Drug Resistant Genes in Drug Resistant Ovarian Cancer Cell Lines

Ovarian cancer rates the highest mortality among all gynecological malignancies. The main reason for high mortality is the development of drug resistance. It can be related to increased expression of drug transporters and increased expression of extracellular matrix (ECM) proteins. Our foremost aim was to exhibit alterations in the miRNA expression levels in cisplatin (CIS), paclitaxel (PAC), doxorubicin (DOX), and topotecan (TOP)-resistant variants of the W1 sensitive ovarian cancer cell line-using miRNA microarray. The second goal was to identify miRNAs responsible for the regulation of drug-resistant genes. According to our observation, alterations in the expression of 40 miRNAs were present. We could observe that, in at least one drug-resistant cell line, the expression of 21 miRNAs was upregulated and that of 19 miRNAs was downregulated. We identified target genes for 22 miRNAs. Target analysis showed that miRNA regulates key genes responsible for drug resistance. Among others, we observed regulation of the ATP-binding cassette subfamily B member 1 gene (ABCB1) in the paclitaxel-resistant cell line by miR-363 and regulation of the collagen type III alpha 1 chain gene (COL3A1) in the topotekan-resistant cell line by miR-29a.

In Silico Discovery of Candidate Drugs against Covid-19

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide.

Hypoxia-Induced Adaptations of miRNomes and Proteomes in Melanoma Cells and Their Secreted Extracellular Vesicles

Reduced levels of intratumoural oxygen are associated with hypoxia-induced pro-oncogenic events such as invasion, metabolic reprogramming, epithelial–mesenchymal transition, metastasis and resistance to therapy, all favouring cancer progression. Small extracellular vesicles (EV) shuttle various cargos (proteins, miRNAs, DNA and others). Tumour-derived EVs can be taken up by neighbouring or distant cells in the tumour microenvironment, thus facilitating intercellular communication. The quantity of extracellular vesicle secretion and their composition can vary with changing microenvironmental conditions and disease states. Here, we investigated in melanoma cells the influence of hypoxia on the content and number of secreted EVs. Whole miRNome and proteome profiling revealed distinct expression patterns in normoxic or hypoxic growth conditions. Apart from the well-known miR-210, we identified miR-1290 as a novel hypoxia-associated microRNA, which was highly abundant in hypoxic EVs. On the other hand, miR-23a-5p and -23b-5p were consistently downregulated in hypoxic conditions, while the protein levels of the miR-23a/b-5p-predicted target IPO11 were concomitantly upregulated. Furthermore, hypoxic melanoma EVs exhibit a signature consisting of six proteins (AKR7A2, DDX39B, EIF3C, FARSA, PRMT5, VARS), which were significantly associated with a poor prognosis for melanoma patients, indicating that proteins and/or miRNAs secreted by cancer cells may be exploited as biomarkers.

Poor clinical outcome in metastatic melanoma is associated with a microRNA-modulated immunosuppressive tumor microenvironment

Background

Interaction between malignant cells and immune cells that reside within the tumor microenvironment (TME) modulate different aspects of tumor development and progression. Recent works showed the importance of miRNA-containing extracellular vesicles in this crosstalk.

Methods

Interested in understanding the interplay between melanoma and immune-related TME cells, we characterized the TCGA’s metastatic melanoma samples according to their tumor microenvironment profiles, HLA-I neoepitopes, transcriptome profile and classified them into three groups. Moreover, we combined our results with melanoma single-cell gene expression and public miRNA data to better characterize the regulatory network of circulating miRNAs and their targets related to immune evasion and microenvironment response.

Results

The group associated with a worse prognosis showed phenotypic characteristics that favor immune evasion, including a strong signature of suppressor cells and less stable neoantigen:HLA-I complexes. Conversely, the group with better prognosis was marked by enrichment in lymphocyte and MHC signatures. By analyzing publicly available melanoma single-cell RNA and microvesicle microRNAs sequencing data we identified circulating microRNAs potentially involved in the crosstalk between tumor and TME cells. Candidate miRNA/target gene pairs with previously reported roles in tumor progression and immune escape mechanisms were further investigated and demonstrated to impact patient’s overall survival not only in melanoma but across different tumor types.

Conclusion

Our results underscore the impact of tumor-microenvironment interactions on disease outcomes and reveal potential non-invasive biomarkers of prognosis and treatment response.

Zika virus targets the human thymic epithelium

Previous work showed that the thymus can be infected by RNA viruses as HIV and HTLV-1. We thus hypothesized that the thymus might also be infected by the Zika virus (ZIKV). Herein we provide compelling evidence that ZIKV targets human thymic epithelial cells (TEC) in vivo and in vitro. ZIKV-infection enhances keratinization of TEC, with a decrease in proliferation and increase in cell death. Moreover, ZIKV modulates a high amount of coding RNAs with upregulation of genes related to cell adhesion and migration, as well as non-coding genes including miRNAs, circRNAs and lncRNAs. Moreover, we observed enhanced attachment of lymphoblastic T-cells to infected TEC, as well as virus transfer to those cells. Lastly, alterations in thymuses from babies congenitally infected were seen, with the presence of viral envelope protein in TEC. Taken together, our data reveals that the thymus, particularly the thymic epithelium, is a target for the ZIKV with changes in the expression of molecules that are relevant for interactions with developing thymocytes.

Theranostic application of miR-429 in HER2+ breast cancer

Human epidermal growth factor receptor 2 (HER2) is overexpressed/amplified in one third of breast cancers (BCs), and is associated with the poorer prognosis and the higher metastatic potential in BC. Emerging evidences highlight the role of microRNAs (miRNAs) in the regulation of several cellular processes, including BC.

Methods: Here we identified, by in silico approach, a group of three miRNAs with central biological role (high degree centrality) in HER2+ BC. We validated their dysregulation in HER2+ BC and we analysed their functional role by in vitro approaches on selected cell lines and by in vivo experiments in an animal model.

Results: We found that their expression is dysregulated in both HER2+ BC cell lines and human samples. Focusing our study on the only upregulated miRNA, miR-429, we discovered that it acts as an oncogene and its upregulation is required for HER2+ cell proliferation. It controls the metastatic potential of HER2+ BC subtype by regulating migration and invasion of the cell.

Conclusions: In HER2+ BC oncogenic miR-429 is able to regulate HIF1α pathway by directly targeting VHL mRNA, a molecule important for the degradation of HIF1α. The overexpression of miR-429, observed in HER2+ BC, causes increased proliferation and migration of the BC cells. More important, silencing miR-429 succeeds in delaying tumor growth, thus miR-429 could be proposed as a therapeutic probe in HER2+ BC tumors.

miRNA Genetic Variants Alter Their Secondary Structure and Expression in Patients With RASopathies Syndromes

RASopathies are a group of rare genetic diseases caused by germline mutations in genes involved in the RAS–mitogen-activated protein kinase (RAS-MAPK) pathway. Whole-exome sequencing (WES) is a powerful approach for identifying new variants in coding and noncoding DNA sequences, including miRNAs. miRNAs are fine-tuning negative regulators of gene expression. The presence of variants in miRNAs could lead to malfunctions of regulation, resulting in diseases. Here, we identified 41 variants in mature miRNAs through WES analysis in five patients with previous clinical diagnosis of RASopathies syndromes. The pathways, biological processes, and diseases that were over-represented among the target genes of the mature miRNAs harboring variants included the RAS, MAPK, RAP1, and PIK3-Akt signaling pathways, neuronal differentiation, neurogenesis and nervous system development, congenital cardiac defects (hypertrophic cardiomyopathy, dilated cardiomyopathy, and arrhythmogenic right ventricular cardiomyopathy), and the phenotypes and syndromes of RASopathies (Noonan syndrome, Legius syndrome, Costello syndrome, Cafe au lait spots multiple, subaortic stenosis, pulmonary valve stenosis, and LEOPARD syndrome). Furthermore, eight selected variants in nine mature miRNAs (hsa-miR-1304, hsa-miR-146a, hsa-miR-196a2, hsa-miR-499a/hsa-miR-499b, hsa-miR-449b, hsa-miR-548l, hsa-miR-575, and hsa-miR-593) may have caused alterations in the secondary structures of miRNA precursor. Selected miRNAs containing variants such as hsa-miR-146a-3p, hsa-miR-196a-3p, hsa-miR-548l, hsa-miR-449b-5p, hsa-miR-575, and hsa-miR499a-3p could regulate classical genes associated with Rasopathies and RAS-MAPK pathways, contributing to modify the expression pattern of miRNAs in patients. RT-qPCR expression analysis revealed four differentially expressed miRNAs that were downregulated: miRNA-146a-3p in P1, P2, P3, P4, and P5, miR-1304-3p in P2, P3, P4, and P5, miR-196a2-3p in P3, and miR-499b-5p in P1. miR-499a-3p was upregulated in P1, P3, and P5. These results indicate that miRNAs show different expression patterns when these variants are present in patients. Therefore, this study characterized the role of miRNAs harboring variants related to RASopathies for the first time and indicated the possible implications of these variants for phenotypes of RASopathies such as congenital cardiac defects and cardio-cerebrovascular diseases. The expression and existence of miRNA variants may be used in the study of biomarkers of the RASopathies.

Profiling of tRNA Halves and YRNA Fragments in Serum and Tissue From Oral Squamous Cell Carcinoma Patients Identify Key Role of 5' tRNA-Val-CAC-2-1 Half

Oral squamous cell carcinoma (OSCC) is the most common type of head and neck cancer and, as indicated by The Oral Cancer Foundation, kills at an alarming rate of roughly one person per hour. With this study, we aimed at better understanding disease mechanisms and identifying minimally invasive disease biomarkers by profiling novel small non-coding RNAs (specifically, tRNA halves and YRNA fragments) in both serum and tumor tissue from humans. Small RNA-Sequencing identified multiple 5' tRNA halves and 5' YRNA fragments that displayed significant differential expression levels in circulation and/or tumor tissue, as compared to control counterparts. In addition, by implementing a modification of weighted gene coexpression network analysis, we identified an upregulated genetic module comprised of 5' tRNA halves and miRNAs (miRNAs were described in previous study using the same samples) with significant association with the cancer trait. By consequently implementing miRNA-overtargeting network analysis, the biological function of the module (and by "guilt by association," the function of the 5' tRNA-Val-CAC-2-1 half) was found to involve the transcriptional targeting of specific genes involved in the negative regulation of the G1/S transition of the mitotic cell cycle. These findings suggest that 5' tRNA-Val-CAC-2-1 half (reduced in serum of OSCC patients and elevated in the tumor tissue) could potentially serve as an OSCC circulating biomarker and/or target for novel anticancer therapies. To our knowledge, this is the first time that the specific molecular function of a 5'-tRNA half is specifically pinpointed in OSCC.

The Role of MicroRNAs in Early Chondrogenesis of Human Induced Pluripotent Stem Cells (hiPSCs)

Human induced pluripotent stem cells (hiPSCs) play an important role in research regarding regenerative medicine. Particularly, chondrocytes differentiated from hiPSCs seems to be a promising solution for patients suffering from osteoarthritis. We decided to perform chondrogenesis in a three-week monolayer culture. Based on transcriptome analysis, hiPSC-derived chondrocytes (ChiPS) demonstrate the gene expression profile of cells from early chondrogenesis. Chondrogenic progenitors obtained by our group are characterized by significantly high expression of Hox genes, strongly upregulated during limb formation and morphogenesis. There are scanty literature data concerning the role of microRNAs in early chondrogenesis, especially in chondrogenic differentiation of hiPSCs. The main aim of this study was to investigate the microRNA expression profile and to select microRNAs (miRNAs) taking part in early chondrogenesis. Our findings allowed for selection crucial miRNAs engaged in both diminishing pluripotency state and chondrogenic process (inter alia hsa-miR-525-5p, hsa-miR-520c-3p, hsa-miR-628-3p, hsa-miR-196b-star, hsa-miR-629-star, hsa-miR-517b, has-miR-187). These miRNAs regulate early chondrogenic genes such as: HOXD10, HOXA11, RARB, SEMA3C. These results were confirmed by RT-qPCR analysis. This work contributes to a better understanding of the role of miRNAs directly involved in chondrogenic differentiation of hiPSCs. These data may result in the establishment of a more efficient protocol of obtaining chondrocyte-like cells from hiPSCs.

Portrait of Tissue-Specific Coexpression Networks of Noncoding RNAs (miRNA and lncRNA) and mRNAs in Normal Tissues

Genes that encode proteins playing a role in more than one biological process are frequently dependent on their tissue context, and human diseases result from the altered interplay of tissue- and cell-specific processes. In this work, we performed a computational approach that identifies tissue-specific co-expression networks by integrating miRNAs, long-non-coding RNAs, and mRNAs in more than eight thousands of human samples from thirty normal tissue types. Our analysis (1) shows that long-non coding RNAs and miRNAs have a high specificity, (2) confirms several known tissue-specific RNAs, and (3) identifies new tissue-specific co-expressed RNAs that are currently still not described in the literature. Some of these RNAs interact with known tissue-specific RNAs or are crucial in key cancer functions, suggesting that they are implicated in tissue specification or cell differentiation.

Extracting predictors for lung adenocarcinoma based on Granger causality test and stepwise character selection

Background

Lung adenocarcinoma is the most common type of lung cancer, with high mortality worldwide. Its occurrence and development were thoroughly studied by high-throughput expression microarray, which produced abundant data on gene expression, DNA methylation, and miRNA quantification. However, the hub genes, which can be served as bio-markers for discriminating cancer and healthy individuals, are not well screened.

Result

Here we present a new method for extracting gene predictors, aiming to obtain the least predictors without losing the efficiency. We firstly analyzed three different expression microarrays and constructed multi-interaction network, since the individual expression dataset is not enough for describing biological behaviors dynamically and systematically. Then, we transformed the undirected interaction network to directed network by employing Granger causality test, followed by the predictors screened with the use of the stepwise character selection algorithm. Six predictors, including TOP2A, GRK5, SIRT7, MCM7, EGFR, and COL1A2, were ultimately identified. All the predictors are the cancer-related, and the number is very small fascinating diagnosis. Finally, the validation of this approach was verified by robustness analyses applied to six independent datasets; the precision is up to 95.3% ∼ 100%.

Conclusion

Although there are complicated differences between cancer and normal cells in gene functions, cancer cells could be differentiated in case that a group of special genes expresses abnormally. Here we presented a new, robust, and effective method for extracting gene predictors. We identified as low as 6 genes which can be taken as predictors for diagnosing lung adenocarcinoma.

In silico perturbation of drug targets in pan-cancer analysis combining multiple networks and pathways

The knowledge of cancer cell response to conventional therapies is crucial in order to choose the correct therapy of patients affected by cancer. The major problem is generally attributed to the lack of specific biological processes able to predict the therapy efficacy. Here, we optimized a computational method for the analysis of gene networks able to detect and quantify the effects of a drug in a pan-cancer study. Overall, our method, using several network topological measures has identified a cancer gene network with a key role in biological processes. The gene network, able to classify with a good performance cancer vs normal samples, was modulated in silico to evaluate the effects of new or approved drugs. This computational model could offer an interesting hint to decipher molecular mechanisms contributing to resistance or inefficacy of drugs.

Predicting and understanding the response to short-term intensive insulin therapy in people with early type 2 diabetes

OBJECTIVE

Short-term intensive insulin therapy (IIT) early in the course of type 2 diabetes acutely improves beta-cell function with long-lasting effects on glycemic control. However, conventional measures cannot determine which patients are better suited for IIT, and little is known about the molecular mechanisms determining response. Therefore, this study aimed to develop a model that could accurately predict the response to IIT and provide insight into molecular mechanisms driving such response in humans.

METHODS

Twenty-four patients with early type 2 diabetes were assessed at baseline and four weeks after IIT, consisting of basal detemir and premeal insulin aspart. Twelve individuals had a beneficial beta-cell response to IIT (responders) and 12 did not (nonresponders). Beta-cell function was assessed by multiple methods, including Insulin Secretion-Sensitivity Index-2. MicroRNAs (miRNAs) were profiled in plasma samples before and after IIT. The response to IIT was modeled using a machine learning algorithm and potential miRNA-mediated regulatory mechanisms assessed by differential expression, correlation, and functional network analyses (FNA).

RESULTS

Baseline levels of circulating miR-145-5p, miR-29c-3p, and HbA1c accurately (91.7%) predicted the response to IIT (OR = 121 [95% CI: 6.7, 2188.3]). Mechanistically, a previously described regulatory loop between miR-145-5p and miR-483-3p/5p, which controls TP53-mediated apoptosis, appears to also occur in our study population of humans with early type 2 diabetes. In addition, significant (fold change > 2, P < 0.05) longitudinal changes due to IIT in the circulating levels of miR-138-5p, miR-192-5p, miR-195-5p, miR-320b, and let-7a-5p further characterized the responder group and significantly correlated (|r| > 0.4, P < 0.05) with the changes in measures of beta-cell function and insulin sensitivity. FNA identified a network of coordinately/cooperatively regulated miRNA-targeted genes that potentially drives the IIT response through negative regulation of apoptotic processes that underlie beta cell dysfunction and concomitant positive regulation of proliferation.

CONCLUSIONS

Responses to IIT in people with early type 2 diabetes are associated with characteristic miRNA signatures. This study represents a first step to identify potential responders to IIT (a current limitation in the field) and provides important insight into the pathophysiologic determinants of the reversibility of beta-cell dysfunction. ClinicalTrial.gov identifier: NCT01270789.

Construction and Analysis of miRNA Regulatory Networks

This chapter is devoted to illustrate the usage of state-of-the-art methodologies for miRNA regulatory network construction and analysis. Advantages in understanding the role of miRNAs in regulating gene expression are increasing the possibility of developing targeted therapies and drugs. This new possibility can be exploited by gaining new knowledge through analyzing interactions between a specific miRNA and a targeted gene.

Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade

The recent successes of immunotherapy have shifted the paradigm in cancer treatment, but because only a percentage of patients are responsive to immunotherapy, it is imperative to identify factors impacting outcome. Obesity is reaching pandemic proportions and is a major risk factor for certain malignancies, but the impact of obesity on immune responses, in general and in cancer immunotherapy, is poorly understood. Here, we demonstrate, across multiple species and tumor models, that obesity results in increased immune aging, tumor progression and PD-1-mediated T cell dysfunction which is driven, at least in part, by leptin. However, obesity is also associated with increased efficacy of PD-1/PD-L1 blockade in both tumor-bearing mice and clinical cancer patients. These findings advance our understanding of obesity-induced immune dysfunction and its consequences in cancer and highlight obesity as a biomarker for some cancer immunotherapies. These data indicate a paradoxical impact of obesity on cancer. There is heightened immune dysfunction and tumor progression but also greater anti-tumor efficacy and survival after checkpoint blockade which directly targets some of the pathways activated in obesity.

Identification of putative non-host essential genes and novel drug targets against Acinetobacter baumannii by in silico comparative genome analysis

Acinetobacter baumannii, the gram-negative bacteria emerged as an extremely critical pathogen causing nosocomial and different kinds of infections. A. baumannii exhibit resistivity towards various classes of antibiotics that shows that there is a dire need to search more drug targets by exploiting the full genome of the bacteria. In doing so, a strategy is made with the combination of computational biology, pathogen informatics and cheminformatics. Comparative genomics analysis, modeling and docking studies have been performed for the prediction of non-host essential genes and novel drug candidates against A. baumannii. Among 37 unique and 82 common metabolic pathways, 92 genes were predicted as non-host genes. Similarly, using homology search between A. baumannii genome and essential genes of different bacteria, 293 genes were predicted as essential genes of A. baumannii. Among these predicted non-host and essential genes, 86 genes were predicted as non-host essential genes which could serve as potential novel drug and vaccine targets. Additional drug-target like physicochemical properties were estimated such as the molecular weight, subcellular localization and druggability potential. On the structural part, the crystal structures of all the non-host essential genes of A. baumannii were found except the three genes. Out of these three, a homology model of Undecaprenyl-diphosphatase was built using a PDB template by MODELLER [version 9.18]. The quality of the model was assessed by the ProSA and RAMPAGE. The built model was subjected as a receptor for the molecular docking with Adenosine diphosphate (ADP) as a ligand. The molecular docking was performed by AutoDock4 and the best conformation with lowest binding energy (-4.39 kcal/mol) was obtained. The LigPlot was used to identify the close interactions between the ligand the receptor's residues. This study will further aid for the selection of putative inhibitors against a novel drug target identified against A. baumannii and hence could lead to the better therapeutics.

Arena-Idb: a platform to build human non-coding RNA interaction networks

BACKGROUND

High throughput technologies have provided the scientific community an unprecedented opportunity for large-scale analysis of genomes. Non-coding RNAs (ncRNAs), for a long time believed to be non-functional, are emerging as one of the most important and large family of gene regulators and key elements for genome maintenance. Functional studies have been able to assign to ncRNAs a wide spectrum of functions in primary biological processes, and for this reason they are assuming a growing importance as a potential new family of cancer therapeutic targets. Nevertheless, the number of functionally characterized ncRNAs is still too poor if compared to the number of new discovered ncRNAs. Thus platforms able to merge information from available resources addressing data integration issues are necessary and still insufficient to elucidate ncRNAs biological roles.

RESULTS

In this paper, we describe a platform called Arena-Idb for the retrieval of comprehensive and non-redundant annotated ncRNAs interactions. Arena-Idb provides a framework for network reconstruction of ncRNA heterogeneous interactions (i.e., with other type of molecules) and relationships with human diseases which guide the integration of data, extracted from different sources, via mapping of entities and minimization of ambiguity.

CONCLUSIONS

Arena-Idb provides a schema and a visualization system to integrate ncRNA interactions that assists in discovering ncRNA functions through the extraction of heterogeneous interaction networks. The Arena-Idb is available at http://arenaidb.ba.itb.cnr.it.

miRmapper: A Tool for Interpretation of miRNA⁻mRNA Interaction Networks

It is estimated that 30% of all genes in the mammalian cells are regulated by microRNA (miRNAs). The most relevant miRNAs in a cellular context are not necessarily those with the greatest change in expression levels between healthy and diseased tissue. Differentially expressed (DE) miRNAs that modulate a large number of messenger RNA (mRNA) transcripts ultimately have a greater influence in determining phenotypic outcomes and are more important in a global biological context than miRNAs that modulate just a few mRNA transcripts. Here, we describe the development of a tool, “miRmapper”, which identifies the most dominant miRNAs in a miRNA–mRNA network and recognizes similarities between miRNAs based on commonly regulated mRNAs. Using a list of miRNA–target gene interactions and a list of DE transcripts, miRmapper provides several outputs: (1) an adjacency matrix that is used to calculate miRNA similarity utilizing the Jaccard distance; (2) a dendrogram and (3) an identity heatmap displaying miRNA clusters based on their effect on mRNA expression; (4) a miRNA impact table and (5) a barplot that provides a visual illustration of this impact. We tested this tool using nonmetastatic and metastatic bladder cancer cell lines and demonstrated that the most relevant miRNAs in a cellular context are not necessarily those with the greatest fold change. Additionally, by exploiting the Jaccard distance, we unraveled novel cooperative interactions between miRNAs from independent families in regulating common target mRNAs; i.e., five of the top 10 miRNAs act in synergy.

Potential Role of miRNAs as Theranostic Biomarkers of Epilepsy

Epilepsy includes a group of disorders of the brain characterized by an enduring predisposition to generate epileptic seizures. Although familial epilepsy has a genetic component and heritability, the etiology of the majority of non-familial epilepsies has no known associated genetic mutations. In epilepsy, recent epigenetic profiles have highlighted a possible role of microRNAs in its pathophysiology. In particular, molecular profiling identifies a significant number of microRNAs (miRNAs) altered in epileptic hippocampus of both animal models and human tissues. In this review, analyzing molecular profiles of different animal models of epilepsy, we identified a group of 20 miRNAs commonly altered in different epilepsy-animal models. As emerging evidences highlighted the poor overlap between signatures of animal model tissues and human samples, we focused our analysis on miRNAs, circulating in human biofluids, with a principal role in epilepsy hallmarks, and we identified a group of 8 diagnostic circulating miRNAs. We discussed the functional role of these 8 miRNAs in the epilepsy hallmarks. A few of them have also been proposed as therapeutic molecules for epilepsy treatment, revealing a great potential for miRNAs as theranostic molecules in epilepsy.

Identifying Genes Whose Mutant Transcripts Cause Dominant Disease Traits by Potential Gain-of-Function Alleles

Premature termination codon (PTC)-bearing transcripts are often degraded by nonsense-mediated decay (NMD) resulting in loss-of-function (LoF) alleles. However, not all PTCs result in LoF mutations, i.e., some such transcripts escape NMD and are translated to truncated peptide products that result in disease due to gain-of-function (GoF) effects. Since the location of the PTC is a major factor determining transcript fate, we hypothesized that depletion of protein-truncating variants (PTVs) within the gene region predicted to escape NMD in control databases could provide a rank for genic susceptibility for disease through GoF versus LoF. We developed an NMD escape intolerance score to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study (ARIC) and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database. This analysis revealed 1,996 genes significantly depleted for PTVs that are predicted to escape from NMD, i.e., PTVesc; further studies provided evidence that revealed a subset as candidate genes underlying Mendelian phenotypes. Importantly, these genes have characteristically low pLI scores, which can cause them to be overlooked as candidates for dominant diseases. Collectively, we demonstrate that this NMD escape intolerance score is an effective and efficient tool for gene discovery in Mendelian diseases due to production of truncated or altered proteins. More importantly, we provide a complementary analytical tool to aid identification of genes associated with dominant traits through a mechanism distinct from LoF.

In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC.

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis

BACKGROUND

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network.

RESULTS

We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study.

CONCLUSIONS

Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Microarray-Based MicroRNA Expression Data Analysis with Bioconductor

MicroRNAs (miRNAs) are small, noncoding RNAs that are able to regulate the expression of targeted mRNAs. Thousands of miRNAs have been identified; however, only a few of them have been functionally annotated. Microarray-based expression analysis represents a cost-effective way to identify candidate miRNAs that correlate with specific biological pathways, and to detect disease-associated molecular signatures. Generally, microarray-based miRNA data analysis contains four major steps: (1) quality control and normalization, (2) differential expression analysis, (3) target gene prediction, and (4) functional annotation. For each step, a large couple of software tools or packages have been developed. In this chapter, we present a standard analysis pipeline for miRNA microarray data, assembled by packages mainly developed with R and hosted in Bioconductor project.

Novel Biomarkers for Prostate Cancer Detection and Prognosis

Prostate cancer (PCa) remains as one of the most controversial issues in health care because of the dilemmas related to screening using Prostate Specific Antigen (PSA). A high number of false positive biopsies and an elevated rate of overdiagnosis are the main problems associated with PSA. New PCa biomarkers have been recently proposed to increase the predictive value of PSA. The published results showed that PCA3 score, Prostate Health Index and 4Kscore can reduce the number of unnecessary biopsies, outperforming better than PSA and the percentage of free PSA. Furthermore, 4Kscore provides with high accuracy an individual risk for high-grade PCa. High values of PHI are also associated with tumor aggressiveness. In contrast, the relationship of PCA3 score with aggressiveness remains controversial, with studies showing opposite conclusions. Finally, the development of molecular biology has opened the study of genes, among them TMPRSS2:ERG fusion gene and miRNAs, in PCa detection and prognosis.