An insight into the roles of piRNAs and PIWI proteins in the diagnosis and pathogenesis of oral, esophageal, and gastric cancer

iPiDA-SWGCN: Identification of piRNA-disease associations based on Supplementarily Weighted Graph Convolutional Network

Accurately identifying potential piRNA-disease associations is of great importance in uncovering the pathogenesis of diseases. Recently, several machine-learning-based methods have been proposed for piRNA-disease association detection. However, they are suffering from the high sparsity of piRNA-disease association network and the Boolean representation of piRNA-disease associations ignoring the confidence coefficients. In this study, we propose a supplementarily weighted strategy to solve these disadvantages. Combined with Graph Convolutional Networks (GCNs), a novel predictor called iPiDA-SWGCN is proposed for piRNA-disease association prediction. There are three main contributions of iPiDA-SWGCN: (i) Potential piRNA-disease associations are preliminarily supplemented in the sparse piRNA-disease network by integrating various basic predictors to enrich network structure information. (ii) The original Boolean piRNA-disease associations are assigned with different relevance confidence to learn node representations from neighbour nodes in varying degrees. (iii) The experimental results show that iPiDA-SWGCN achieves the best performance compared with the other state-of-the-art methods, and can predict new piRNA-disease associations.

The epigenetic regulatory mechanism of PIWI/piRNAs in human cancers

PIWI proteins have a strong correlation with PIWI-interacting RNAs (piRNAs), which are significant in development and reproduction of organisms. Recently, emerging evidences have indicated that apart from the reproductive function, PIWI/piRNAs with abnormal expression, also involve greatly in varieties of human cancers. Moreover, human PIWI proteins are usually expressed only in germ cells and hardly in somatic cells, so the abnormal expression of PIWI proteins in different types of cancer offer a promising opportunity for precision medicine. In this review, we discussed current researches about the biogenesis of piRNA, its epigenetic regulatory mechanisms in human cancers, such as N6-methyladenosine (m⁶A) methylation, histone modifications, DNA methylation and RNA interference, providing novel insights into the markers for clinical diagnosis, treatment and prognosis in human cancers.

Trypanosoma cruzi dysregulates expression profile of piRNAs in primary human cardiac fibroblasts during early infection phase

Trypanosoma cruzi, the etiological agent of Chagas Disease, causes severe morbidity, mortality, and economic burden worldwide. Though originally endemic to Central and South America, globalization has led to increased parasite presence in most industrialized countries. About 40% of infected individuals will develop cardiovascular, neurological, and/or gastrointestinal pathologies. Accumulating evidence suggests that the parasite induces alterations in host gene expression profiles in order to facilitate infection and pathogenesis. The role of regulatory gene expression machinery during T. cruzi infection, particularly small noncoding RNAs, has yet to be elucidated. In this study, we aim to evaluate dysregulation of a class of sncRNAs called piRNAs during early phase of T. cruzi infection in primary human cardiac fibroblasts by RNA-Seq. We subsequently performed in silico analysis to predict piRNA-mRNA interactions. We validated the expression of these selected piRNAs and their targets during early parasite infection phase by stem loop qPCR and qPCR, respectively. We found about 26,496,863 clean reads (92.72%) which mapped to the human reference genome. During parasite challenge, 441 unique piRNAs were differentially expressed. Of these differentially expressed piRNAs, 29 were known and 412 were novel. In silico analysis showed several of these piRNAs were computationally predicted to target and potentially regulate expression of genes including SMAD2, EGR1, ICAM1, CX3CL1, and CXCR2, which have been implicated in parasite infection, pathogenesis, and various cardiomyopathies. Further evaluation of the function of these individual piRNAs in gene regulation and expression will enhance our understanding of early molecular mechanisms contributing to infection and pathogenesis. Our findings here suggest that piRNAs play important roles in infectious disease pathogenesis and can serve as potential biomarkers and therapeutic targets.

piRNAs may regulate expression of candidate genes of esophageal adenocarcinoma

Elucidation of ways to regulate the expression of candidate cancer genes will contribute to the development of methods for cancer diagnosis and therapy. The aim of the present study was to show the role of piRNAs as efficient regulators of mRNA translation of esophageal adenocarcinoma (EAC) candidate genes. We used bioinformatic methods to study the interaction characteristics of up to 200 thousand piRNAs with mRNAs of 38 candidate EAC genes. The piRNAs capable of binding to mRNA of AR, BTG3, CD55, ERBB3, FKBP5, FOXP1, LEP, SEPP1, SMAD4, and TP53 genes with high free energy by the formation of hydrogen bonds between canonical (G-C, A-U) and noncanonical (G-U, A-C) piRNA and mRNA nucleotide pairs were revealed. The organization of piRNA binding sites (BSs) in the mRNA of candidate genes was found to overlap nucleotide sequences to form clusters. Clusters of piRNA BSs were detected in the 5'-untranslated region, coding domain sequence, and 3'-untranslated region of mRNA. Due to the formation of piRNA binding site clusters, compaction of BSs occurs and competition between piRNAs for binding to mRNA of candidate EAC genes occurs. Associations of piRNA and candidate genes were selected for use as markers for the diagnosis of EAC.

iPiDA-GCN: Identification of piRNA-disease associations based on Graph Convolutional Network

Motivation

Piwi-interacting RNAs (piRNAs) play a critical role in the progression of various diseases. Accurately identifying the associations between piRNAs and diseases is important for diagnosing and prognosticating diseases. Although some computational methods have been proposed to detect piRNA-disease associations, it is challenging for these methods to effectively capture nonlinear and complex relationships between piRNAs and diseases because of the limited training data and insufficient association representation.

Results

With the growth of piRNA-disease association data, it is possible to design a more complex machine learning method to solve this problem. In this study, we propose a computational method called iPiDA-GCN for piRNA-disease association identification based on graph convolutional networks (GCNs). The iPiDA-GCN predictor constructs the graphs based on piRNA sequence information, disease semantic information and known piRNA-disease associations. Two GCNs (Asso-GCN and Sim-GCN) are used to extract the features of both piRNAs and diseases by capturing the association patterns from piRNA-disease interaction network and two similarity networks. GCNs can capture complex network structure information from these networks, and learn discriminative features. Finally, the full connection networks and inner production are utilized as the output module to predict piRNA-disease association scores. Experimental results demonstrate that iPiDA-GCN achieves better performance than the other state-of-the-art methods, benefitted from the discriminative features extracted by Asso-GCN and Sim-GCN. The iPiDA-GCN predictor is able to detect new piRNA-disease associations to reveal the potential pathogenesis at the RNA level. The data and source code are available at http://bliulab.net/iPiDA-GCN/.

In Silico Study of piRNA Interactions with the SARS-CoV-2 Genome

A prolonged pandemic with numerous human casualties requires a rapid search for means to control the various strains of SARS-CoV-2. Since only part of the human population is affected by coronaviruses, there are probably endogenous compounds preventing the spread of these viral pathogens. It has been shown that piRNA (PIWI-interacting RNAs) interact with the mRNA of human genes and can block protein synthesis at the stage of translation. Estimated the effects of piRNA on SARS-CoV-2 genomic RNA (gRNA) in silico. A cluster of 13 piRNA binding sites (BS) in the SARS-CoV-2 gRNA region encoding the oligopeptide was identified. The second cluster of BSs 39 piRNAs also encodes the oligopeptide. The third cluster of 24 piRNA BS encodes the oligopeptide. Twelve piRNAs were identified that strongly interact with the gRNA. Based on the identified functionally important endogenous piRNAs, synthetic piRNAs (spiRNAs) are proposed that will suppress the multiplication of the coronavirus even more strongly. These spiRNAs and selected endogenous piRNAs have little effect on human 17494 protein-coding genes, indicating a low probability of side effects. The piRNA and spiRNA selection methodology created for the control of SARS-CoV-2 (NC_045512.2) can be used to control all strains of SARS-CoV-2.

Impact of Non-Coding RNAs on Chemotherapeutic Resistance in Oral Cancer

Drug resistance in oral cancer is one of the major problems in oral cancer therapy because therapeutic failure directly results in tumor recurrence and eventually in metastasis. Accumulating evidence has demonstrated the involvement of non-coding RNAs (ncRNAs), such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in processes related to the development of drug resistance. A number of studies have shown that ncRNAs modulate gene expression at the transcriptional or translational level and regulate biological processes, such as epithelial-to-mesenchymal transition, apoptosis, DNA repair and drug efflux, which are tightly associated with drug resistance acquisition in many types of cancer. Interestingly, these ncRNAs are commonly detected in extracellular vesicles (EVs) and are known to be delivered into surrounding cells. This intercellular communication via EVs is currently considered to be important for acquired drug resistance. Here, we review the recent advances in the study of drug resistance in oral cancer by mainly focusing on the function of ncRNAs, since an increasing number of studies have suggested that ncRNAs could be therapeutic targets as well as biomarkers for cancer diagnosis.