A comprehensive analysis of ncRNA-mediated interactions reveals potential prognostic biomarkers in prostate adenocarcinoma

As one of common malignancies, prostate adenocarcinoma (PRAD) has been a growing health problem and a leading cause of cancer-related death. To obtain expression and functional relevant RNAs, we firstly screened candidate hub mRNAs and characterized their associations with cancer. Eight deregulated genes were identified and used to build a risk model (AUC was 0.972 at 10 years) that may be a specific biomarker for cancer prognosis. Then, relevant miRNAs and lncRNAs were screened, and the constructed primarily interaction networks showed the potential cross-talks among diverse RNAs. IsomiR landscapes were surveyed to understand the detailed isomiRs in relevant homologous miRNA loci, which largely enriched RNA interaction network due to diversities of sequence and expression. We finally characterized TK1, miR-222-3p and SNHG3 as crucial RNAs, and the abnormal expression patterns of them were correlated with poor survival outcomes. TK1 was found synthetic lethal interactions with other genes, implicating potential therapeutic target in precision medicine. LncRNA SNHG3 can sponge miR-222-3p to perturb RNA regulatory network and TK1 expression. These results demonstrate that TK1:miR-222-3p:SNHG3 axis may be a potential prognostic biomarker, which will contribute to further understanding cancer pathophysiology and providing potential therapeutic targets in precision medicine.

Critical Roles of Circular RNA in Tumor Metastasis via Acting as a Sponge of miRNA/isomiR

Circular RNAs (circRNAs), a class of new endogenous non-coding RNAs (ncRNAs), are closely related to the carcinogenic process and play a critical role in tumor metastasis. CircRNAs can lay the foundation for tumor metastasis via promoting tumor angiogenesis, make tumor cells gain the ability of migration and invasion by regulating epithelial-mesenchymal transition (EMT), interact with immune cells, cytokines, chemokines, and other non-cellular components in the tumor microenvironment, damage the normal immune function or escape the immunosuppressive network, and further promote cell survival and metastasis. Herein, based on the characteristics and biological functions of circRNA, we elaborated on the effect of circRNA via circRNA-associated competing endogenous RNA (ceRNA) network by acting as miRNA/isomiR sponges on tumor angiogenesis, cancer cell migration and invasion, and interaction with the tumor microenvironment (TME), then explored the potential interactions across different RNAs, and finally discussed the potential clinical value and application as a promising biomarker. These results provide a theoretical basis for the further application of metastasis-related circRNAs in cancer treatment. In summary, we briefly summarize the diverse roles of a circRNA-associated ceRNA network in cancer metastasis and the potential clinical application, especially the interaction of circRNA and miRNA/isomiR, which may complicate the RNA regulatory network and which will contribute to a novel insight into circRNA in the future.

Characterization of Cell Cycle-Related Competing Endogenous RNAs Using Robust Rank Aggregation as Prognostic Biomarker in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD), one of the most common pathological subtypes in lung cancer, has been of concern because it is the leading cause of cancer-related deaths. Due to its poor prognosis, to identify a prognostic biomarker, this study performed an integrative analysis to screen curial RNAs and discuss their cross-talks. The messenger RNA (mRNA) profiles were primarily screened using robust rank aggregation (RRA) through several datasets, and these deregulated genes showed important roles in multiple biological pathways, especially for cell cycle and oocyte meiosis. Then, 31 candidate genes were obtained via integrating 12 algorithms, and 16 hub genes (containing homologous genes) were further screened according to the potential prognostic values. These hub genes were used to search their regulators and biological-related microRNAs (miRNAs). In this way, 10 miRNAs were identified as candidate small RNAs associated with LUAD, and then miRNA-related long non-coding RNAs (lncRNAs) were further obtained. In-depth analysis showed that 4 hub mRNAs, 2 miRNAs, and 2 lncRNAs were potential crucial RNAs in the occurrence and development of cancer, and a competing endogenous RNA (ceRNA) network was then constructed. Finally, we identified CCNA2/MKI67/KIF11:miR-30a-5p:VPS9D1-AS1 axis-related cell cycle as a prognostic biomarker, which provided RNA cross-talks among mRNAs and non-coding RNAs (ncRNAs), especially at the multiple isomiR levels that further complicated the coding–non-coding RNA regulatory network. Our findings provide insight into complex cross-talks among diverse RNAs particularly involved in isomiRs, which will enrich our understanding of mRNA–ncRNA interactions in coding–non-coding RNA regulatory networks and their roles in tumorigenesis.

Protein profiling reveals potential isomiR-associated cross-talks among RNAs in cholangiocarcinoma

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Protein profiling identified crucial genes that were used to screen related ncRNAs.

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Both miRNAs and isomiRs were involved in coding-non-coding RNA regulatory network.

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IsomiR-associated ceRNA networks implied the complex interactions among RNAs.

Cholangiocarcinomas (CCAs) are tumors that arise from the cholangiocytes. Although some genes have been shown with important roles in pathological process, interactions or cross-talks among different RNAs are important to understand the detailed molecular mechanisms in cancer development, especially discussing cross-talks among isomiRs and other RNAs. Herein, to characterize crucial genes in CCA, the protein expression profile was performed to survey potential crucial mRNAs and related non-coding RNAs (ncRNAs) in mRNA-ncRNA network, mainly including miRNAs/isomiRs and lncRNAs. Deregulated mRNAs were firstly obtained if consistent expression patterns were found at protein and mRNA levels, and related miRNAs/isomiRs were screened according to regulatory relationships. Diverse isomiRs from a given miRNA locus also contributed to interactions between the small RNAs and target mRNAs, and miRNAs were further used to survey related lncRNAs to expand the interactions. Thus, several groups of RNAs were constructed as candidate competitive endogenous RNA (ceRNA) networks. Finally, we found that RAB11FIP1:miR-101-3p:MIR3142HG may be a potential ceRNA network, and the interactions among them may be more complex due to variety of isomiRs. Simultaneously, RAB11FIP1 and miR-194-5p were also detected other related lncRNAs (FBXL19-AS1, SNHG1 and PVT1) that may be crucial in coding-non-coding RNA regulatory network. Our results show that diverse isomiRs with sequence and expression heterogeneities contribute to ceRNA regulatory network that may have crucial roles in CCA, which will expand our understanding of interactions among diverse RNAs and their contributions in cancer development.

Hairpin sequence and structure is associated with features of isomiR biogenesis

MiRNA isoforms (isomiRs) are single stranded small RNAs originating from the same pri-miRNA hairpin as a result of cleavage by Drosha and Dicer enzymes. Variations at the 5'-end of a miRNA alter the seed region of the molecule, thus affecting the targetome of the miRNA. In this manuscript, we analysed the distribution of miRNA cleavage positions across 31 different cancers using miRNA sequencing data of TCGA project. As a result, we found that the processing positions are not tissue specific and that all miRNAs could be correctly classified as ones exhibiting homogeneous or heterogeneous cleavage at one of the four cleavage sites. In 42% of cases (42 out of 100 miRNAs), we observed imprecise 5'-end Dicer cleavage, while this fraction was only 14% for Drosha (14 out of 99). To the contrary, almost all cleavage sites of 3'-ends (either Drosha or Dicer) were heterogeneous. With the use of only four nucleotides surrounding a 5'-end Dicer cleavage position we built a model which allowed us to distinguish between homogeneous and heterogeneous cleavage with the reliable quality (ROC AUC = 0.68). Finally, we showed the possible applications of the study by the analysis of two 5'-end isoforms originating from the same exogeneous shRNA hairpin. It turned out that the less expressed shRNA variant was functionally active, which led to the increased off-targeting. Thus, the obtained results could be applied to the design of shRNAs whose processing will result in a single 5'-variant.

Novel Potential Small Molecule-MiRNA-Cancer Associations Prediction Model Based on Fingerprint, Sequence, and Clinical Symptoms

As an important biomarker in organisms, miRNA is closely related to various small molecules and diseases. Research on small molecule-miRNA-cancer associations is helpful for the development of cancer treatment drugs and the discovery of pathogenesis. It is very urgent to develop theoretical methods for identifying potential small molecular-miRNA-cancer associations, because experimental approaches are usually time-consuming, laborious, and expensive. To overcome this problem, we developed a new computational method, in which features derived from structure, sequence, and symptoms were utilized to characterize small molecule, miRNA, and cancer, respectively. A feature vector was construct to characterize small molecule-miRNA-cancer association by concatenating these features, and a random forest algorithm was utilized to construct a model for recognizing potential association. Based on the 5-fold cross-validation and benchmark data set, the model achieved an accuracy of 93.20 ± 0.52%, a precision of 93.22 ± 0.51%, a recall of 93.20 ± 0.53%, and an F1-measure of 93.20 ± 0.52%. The areas under the receiver operating characteristic curve and precision recall curve were 0.9873 and 0.9870. The real prediction ability and application performance of the developed method have also been further evaluated and verified through an independent data set test and case study. Some potential small molecules and miRNAs related to cancer have been identified and are worthy of further experimental research. It is anticipated that our model could be regarded as a useful high-throughput virtual screening tool for drug research and development. All source codes can be downloaded from https://github.com/LeeKamlong/Multi-class-SMMCA.

Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer

Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases.

For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

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Protocols for ancestry associations with TCGA molecular data

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Protocols for ancestry associations with oncogenic pathways

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Statistical and power analysis for determining significant associations

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Key considerations of potential confounding factors

Overview of host miRNA properties and their association with epigenetics, long non-coding RNAs, and Xeno-infectious factors

MicroRNA-derived structures play impressive roles in various biological processes. So dysregulation of miRNAs can lead to different human diseases. Recent studies have extended our comprehension of the control of miRNA function and features. Here, we overview some remarkable miRNA properties that have potential implications for the miRNA functions, including different variants of a miRNA called isomiRs, miRNA arm selection/arm switching, and the effect of these factors on miRNA target selection. Besides, we review some aspects of miRNA interactions such as the interaction between epigenetics and miRNA (different miRNAs and their related processing enzymes are epigenetically regulated by multiple DNA methylation enzymes. moreover, DNA methylation could be controlled by diverse mechanisms related to miRNAs), direct and indirect crosstalk between miRNA and lnc (Long Non-Coding) RNAs as a further approach to conduct intercellular regulation called "competing endogenous RNA" (ceRNA) that is involved in the pathogenesis of different diseases, and the interaction of miRNA activities and some Xeno-infectious (virus/bacteria/parasite) factors, which result in modulation of the pathogenesis of infections. This review provides some related studies to a better understanding of miRNA involvement mechanisms and overcoming the complexity of related diseases that may be applicable and useful to prognostic, diagnostic, therapeutic purposes and personalized medicine in the future.

Seq-SymRF: a random forest model predicts potential miRNA-disease associations based on information of sequences and clinical symptoms

Increasing evidence indicates that miRNAs play a vital role in biological processes and are closely related to various human diseases. Research on miRNA-disease associations is helpful not only for disease prevention, diagnosis and treatment, but also for new drug identification and lead compound discovery. A novel sequence- and symptom-based random forest algorithm model (Seq-SymRF) was developed to identify potential associations between miRNA and disease. Features derived from sequence information and clinical symptoms were utilized to characterize miRNA and disease, respectively. Moreover, the clustering method by calculating the Euclidean distance was adopted to construct reliable negative samples. Based on the fivefold cross-validation, Seq-SymRF achieved the accuracy of 98.00%, specificity of 99.43%, sensitivity of 96.58%, precision of 99.40% and Matthews correlation coefficient of 0.9604, respectively. The areas under the receiver operating characteristic curve and precision recall curve were 0.9967 and 0.9975, respectively. Additionally, case studies were implemented with leukemia, breast neoplasms and hsa-mir-21. Most of the top-25 predicted disease-related miRNAs (19/25 for leukemia; 20/25 for breast neoplasms) and 15 of top-25 predicted miRNA-related diseases were verified by literature and dbDEMC database. It is anticipated that Seq-SymRF could be regarded as a powerful high-throughput virtual screening tool for drug research and development. All source codes can be downloaded from https://github.com/LeeKamlong/Seq-SymRF.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2–10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA–mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.

Construction and Analysis of a ceRNA Network Reveals Potential Prognostic Markers in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide and is derived from an accumulation of genetic and epigenetic changes. This study explored potential prognostic markers in CRC via the construction and in-depth analysis of a competing endogenous RNA (ceRNA) network, which was generated through a three-step process. First, we screened candidate hub genes in CRC as the primary gene markers to survey their related regulatory non-coding RNAs, miRNAs. Second, the interacting miRNAs were used to search for associated lncRNAs. Thus, candidate RNAs were first constructed into ceRNA networks based on close associations with miRNAs. Further analysis at the isomiR level was also performed for each miRNA locus to understand the detailed expression patterns of the multiple variants. Finally, RNAs were performed an in-depth analysis of expression correlations, which contributed to further screening and validation of potential RNAs with close correlations to each other. Using this approach, nine hub genes, 13 related miRNAs, and 29 candidate lncRNAs were collected and used to construct the ceRNA network. Further in-depth analysis identified the MFAP5-miR-200b-3p-AC005154.6 axis as a potential prognostic marker in CRC. MFAP5 and miR-200b-3p have previously been reported to play important roles in tumorigenesis. These RNAs showed potential prognostic values, and the combination of them may have more sensitivity than using them alone. In conclusion, MFAP5, miR-200b-3p, and AC005154.6 may have potential prognostic value in CRC and may provide a prognostic reference for this patient population.

Identification of the miRNAome of early mesoderm progenitor cells and cardiomyocytes derived from human pluripotent stem cells

MicroRNAs are small non-coding RNAs involved in post-transcriptional regulation of gene expression related to many cellular functions. We performed a small-RNAseq analysis of cardiac differentiation from pluripotent stem cells. Our analyses identified some new aspects about microRNA expression in this differentiation process. First, we described a dynamic expression profile of microRNAs where some of them are clustered according to their expression level. Second, we described the extensive network of isomiRs and ADAR modifications. Third, we identified the microRNAs families and clusters involved in the establishment of cardiac lineage and define the mirRNAome based on these groups. Finally, we were able to determine a more accurate miRNAome associated with cardiomyocytes by comparing the expressed microRNAs with other mature cells. MicroRNAs exert their effect in a complex and interconnected way, making necessary a global analysis to better understand their role. Our data expands the knowledge of microRNAs and their implications in cardiomyogenesis.

Profiling and Bioinformatic Analyses Indicate Differential circRNA and miRNA/isomiR Expression and Interactions

As a novel class of noncoding RNAs, circular RNAs (circRNAs) have been reported to play a role in various biological processes. Some circRNAs may serve as microRNA (miRNA) sponges, regulating transcription or splicing. Herein, we investigated the expression profiles and interactions of miRNAs/isomiRs and circRNAs in male patients with esophageal cancer. We found that some miRNA genes generated two deregulated miRNA products (miR-#-5p and miR-#-3p), and these products were consistently abnormally expressed. Some circRNAs were predicted to be miRNA sponges for specific miRNAs. Some of these typically showed opposing expression patterns in cancer tissues: one upregulated and the other downregulated. Although fewer miRNAs were predicted to interact with circRNAs, the number of predicted interactions would be substantially increased if detailed isomiRs were involved. High sequence similarity across multiple isomiRs suggested that they might interact with circRNAs, similar to the interaction of homologous miRNAs with circRNAs. At the isomiR level, due to the characteristics of the sequences and expression patterns involved, the cross-talk between different ncRNAs is complicated despite simplification of the isomiRs involved through clustering. We expect that our results may provide methods for further study of the cross-talk among ncRNAs and elucidate their biological roles in human diseases.