Computing MicroRNA-Gene Interaction Networks in Pan-cancer Using MiRDriver

DNA copy number aberrated regions in cancer are known to harbor cancer driver genes and the short non-coding RNA molecules, i.e., microRNAs. In this study, we integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach. We studied 7,294 patient samples associated with eighteen different cancer types from The Cancer Genome Atlas (TCGA) database and identified several cancer-specific microRNA-gene interactions enriched in experimentally validated microRNA-target databases. We highlighted several oncogenic and tumor suppressor microRNAs and genes that were common in several cancer types. Our method substantially outperformed the five state-of-art methods in selecting significantly known microRNA-gene interactions in multiple cancer types. Several microRNAs and genes were found to be associated with tumor survival and progression. Selected target genes were found to be significantly enriched in cancer-related pathways, cancer Hallmark and Gene Ontology (GO) terms. Furthermore, subtype-specific potential gene signatures were discovered in multiple cancer types.

A Network Biology Approach to Understanding the Tissue-Specific Roles of Non-Coding RNAs in Arthritis

Discovery of non-coding RNAs continues to provide new insights into some of the key molecular drivers of musculoskeletal diseases. Among these, microRNAs have received widespread attention for their roles in osteoarthritis and rheumatoid arthritis. With evidence to suggest that long non-coding RNAs and circular RNAs function as competing endogenous RNAs to sponge microRNAs, the net effect on gene expression in specific disease contexts can be elusive. Studies to date have focused on elucidating individual long non-coding-microRNA-gene target axes and circular RNA-microRNA-gene target axes, with a paucity of data integrating experimentally validated effects of non-coding RNAs. To address this gap, we curated recent studies reporting non-coding RNA axes in chondrocytes from human osteoarthritis and in fibroblast-like synoviocytes from human rheumatoid arthritis. Using an integrative computational biology approach, we then combined the findings into cell- and disease-specific networks for in-depth interpretation. We highlight some challenges to data integration, including non-existent naming conventions and out-of-date databases for non-coding RNAs, and some successes exemplified by the International Molecular Exchange Consortium for protein interactions. In this perspective article, we suggest that data integration is a useful in silico approach for creating non-coding RNA networks in arthritis and prioritizing interactions for further in vitro and in vivo experimentation in translational research.

An Overview of C19MC Cluster Subgroup 3 and Cancer

: The primate-specific microRNA gene cluster on chromosome 19 (C19MC) is composed of 56 mature microRNAs (miRNAs), which are divided into three subgroups according to the sequence similarity. This cluster is principally expressed in the placenta but not in other tissues. C19MC is involved in the regulation of proliferation, migration, and invasion of trophoblastic cells, which are important for the development of the placenta. There is a growing number of studies that have found an altered expression of some miRNAs of the C19MC cluster in cancer, suggesting that these could play an important role in the development of this disease. Therefore, in this work, we provided an overview of the C19MC cluster’s role in cancer through a systematic review of published articles. In particular, we focused on miRNAs of subgroup 3. These studies suggest that miRNAs such as miR-512-3p, miR-512-5p, miR-516a-5p, miR-516b-5p, and miR-498-5p could play a pivotal role in the development of therapies for cancer. Future studies are necessary to elucidate the molecular processes and pathways regulated by subgroup 3 miRNAs.

Two microRNA regulatory circuits set start and end times for dendritic arborization of a nociceptive neuron

Choreographic dendritic arborization takes place within a defined time frame, but the timing mechanism is currently not known. Here, we report that a precisely timed lin-4-lin-14 regulatory circuit triggers an initial dendritic growth activity whereas a precisely timed let-7-lin-41 regulatory circuit signals a subsequent developmental decline in dendritic growth ability, hence restricting dendritic arborization within a defined time frame. Loss-of-function mutations in the lin-4 microRNA gene cause limited dendritic outgrowth whereas loss-of-function mutations in its direct target, the lin-14 transcription factor gene, cause precocious and excessive outgrowth. In contrast, loss-of-function mutations in the let-7 microRNA gene prevent a developmental decline in dendritic growth ability whereas loss-of-function mutations in its direct target, the lin-41 tripartite motif protein gene, cause further decline. lin-4 and let-7 regulatory circuits are expressed at the right place and the right time to set start and end times for PVD dendritic arborization. Replacing the endogenous lin-4 promoter at the lin-4 locus with a late-onset let-7 promoter delays PVD dendrite arborization whereas replacing the endogenous let-7 promoter at the let-7 locus with an early-onset lin-4 promoter causes precocious decline in dendritic growth ability in PVD neurons. We further find that lin-28 acts upstream of let-7 in regulating developmental decline in dendritic growth ability. Our results indicate that the lin-4-lin-14 and the lin-28-let-7-lin-41 regulatory circuits control the timing of PVD dendrite arborization through antagonistic regulation of the DMA-1 receptor level on PVD dendrites.

Designing a Restriction Enzyme-free Method to Construct a MicroRNA Precursor gene for microRNA Cloning

Common cloning strategies depend on the enzymatic digestion of the insert. In addition, the enzymatic digestion of PCR product ends by restriction enzymes is of low efficiency. These limitations are related to the need for enzymatic digestion to produce sticky ends in the insert sequence. Hence, in the present study, we aimed to present a new generation of pre-microRNA cloning method without using restriction enzymes for constructing pre-microRNA gene. In this strategy, by engineering an expression vector's sequence and designing two intelligent primer sets for two consecutive PCR reactions, the pre-microRNA sequence with appropriate restriction sites related to the expression vector was produced, without restriction enzymes. The recombinant expression vector was transfected into HEK293 cells, and microRNA-21 expression was assayed in these cells by real-time PCR, confirming the high efficacy of the presented cloning method. The present method can be an inexpensive and reliable method for microRNA precursor cloning by providing a high-performance protocol.

Alterations in MicroRNA gene expression profile in liver transplant patients with hepatocellular carcinoma

Background Hepatocellular carcinoma (HCC) can lead to liver failure which renders to liver transplant. miRNAs might be detected as biomarkers in subclinical stage of several hepatobiliary disorders like HCC. Therefore, in the present study, alterations in miRNAs as biomarkers were detected in LT patients with HCC. Methods Fourteen tissue samples composed of 5 rejected and 9 non-rejected ones were used for studying the miRNAs expression pattern using LNA-array probe assay and the result was evaluated by in house SYBR Green Real-time PCR protocols on 30 other tissue samples composed of 10 rejected and 20 non-rejected ones for the selected miRNAs. All samples were collected from liver transplanted patients with HCC. Results The study results revealed that in rejected patients compared to non-rejected ones, hsa-miR-3158-5p, -4449, -4511, and -4633-5p were up-regulated and hsa-miR-122-3p, -194-5p, 548as-3p, and -4284 were down-regulated. ROC curve analysis also confirmed that miR194-5p and -548as-3p in up-regulated and also, miR-3158-5p, -4449 in down-regulated microRNAs are significantly important molecules in rejection. Conclusion Finally, the tissue levels of specific miRNAs (especially hsa-miR-3158-5p, -4449, -194-5p and -548as-3p) significantly correlated with the development of HCC, which can be present as biomarkers after further completing studies.

TSCCA: A tensor sparse CCA method for detecting microRNA-gene patterns from multiple cancers

Existing studies have demonstrated that dysregulation of microRNAs (miRNAs or miRs) is involved in the initiation and progression of cancer. Many efforts have been devoted to identify microRNAs as potential biomarkers for cancer diagnosis, prognosis and therapeutic targets. With the rapid development of miRNA sequencing technology, a vast amount of miRNA expression data for multiple cancers has been collected. These invaluable data repositories provide new paradigms to explore the relationship between miRNAs and cancer. Thus, there is an urgent need to explore the complex cancer-related miRNA-gene patterns by integrating multi-omics data in a pan-cancer paradigm. In this study, we present a tensor sparse canonical correlation analysis (TSCCA) method for identifying cancer-related miRNA-gene modules across multiple cancers. TSCCA is able to overcome the drawbacks of existing solutions and capture both the cancer-shared and specific miRNA-gene co-expressed modules with better biological interpretations. We comprehensively evaluate the performance of TSCCA using a set of simulated data and matched miRNA/gene expression data across 33 cancer types from the TCGA database. We uncover several dysfunctional miRNA-gene modules with important biological functions and statistical significance. These modules can advance our understanding of miRNA regulatory mechanisms of cancer and provide insights into miRNA-based treatments for cancer.

Simultaneous learning of individual microRNA-gene interactions and regulatory comodules

Background MicroRNAs (miRNAs) function in post-transcriptional regulation of gene expression by binding to target messenger RNAs (mRNAs). Because of the key part that miRNAs play, understanding the correct regulatory role of miRNAs in diverse patho-physiological conditions is of great interest. Although it is known that miRNAs act combinatorially to regulate genes, precise identification of miRNA-gene interactions and their specific functional roles in regulatory comodules remains a challenge. We developed Theia, an effective method for simultaneously predicting miRNA-gene interactions and regulatory comodules, which group functionally related miRNAs and genes via non-negative matrix factorization (NMF). Results We apply Theia to RNA sequencing data from breast invasive carcinoma samples and demonstrate its effectiveness in discovering biologically significant regulatory comodules that are significantly enriched in spatial miRNA clusters, biological pathways, and various cancers. Conclusions Theia is a theoretically rigorous optimization algorithm that simultaneously predicts the strength and direction (i.e., up-regulation or down-regulation) of the effect of modules of miRNAs on a gene. We posit that if Theia is capable of recovering known clusters of genes and miRNA, then the clusters found by our method not previously identified by literature are also likely to have biological significance. We believe that these novel regulatory comodules found by our method will be a springboard for further research into the specific functional roles of these new functional ensembles of miRNAs and genes,especially those related to diseases like breast cancer.