Transcriptome Analysis Identifies Piwi-Interacting RNAs as Prognostic Markers for Recurrence of Prostate Cancer

piR-823 tale as emerging cancer-hallmark molecular marker in different cancer types: a step-toward ncRNA-precision

PIWI-interacting RNAs (piRNAs) have received a lot of attention for their functions in cancer research. This class of short non-coding RNAs (ncRNA) has roles in genomic stability, chromatin remodeling, messenger RNA (mRNA) integrity, and genome structure. We summarized the mechanisms underlying the biogenesis and regulatory molecular functions of piRNAs. Among all piRNAs studied in cancer, this review offers a comprehensive analysis of the emerging roles of piR-823 in various types of cancer, including colorectal, gastric, liver, breast, and renal cancers, as well as multiple myeloma. piR-823 has emerged as a crucial modulator of various cancer hallmarks through regulating multiple pathways. In the current review, we analyzed several databases and conducted an extensive literature search to explore the influence of piR-823 in carcinogenesis in addition to describing the potential application of piR-823 as prognostic and diagnostic markers as well as the therapeutic potential toward ncRNA precision.

Identification of key genes associated with cancer stem cell characteristics in Wilms' tumor based on bioinformatics analysis

Background

Nephroblastoma, also known as Wilms' tumor (WT), remains one of the major causes of tumor-related deaths worldwide in children. Cancer stem cells (CSCs) are considered to be the main culprits in cancer resistance and disease recurrence, which are reported in multiple types of tumors. However, the research on CSCs in WT is limited. Therefore, our study aimed to identify the key genes related to CSCs in WT to provide new ideas for treating WT.

Methods

The RNA-seq and clinical data of WT samples were obtained from the University of California Santa Cruz (UCSC) Xena database, which included 120 WT and six para-cancerous tissues. The mRNA stemness index (mRNAsi) based on mRNA expression was calculated to evaluate tumor stem cell characteristics in WT patients. A Kaplan-Meier (KM) analysis was performed to explore the clinical characteristics of the mRNAsi in WT. A weighted gene co-expression network analysis (WGCNA) was used to identify the key modules and genes related to the mRNAsi. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed to explore the signaling pathways based on the key genes. The expression levels of the key genes were validated by the Gene Expression Omnibus (GEO) database. Further, the important upstream genes were identified by DisNor and gene co-expression analyses.

Results

The mRNAsi was significantly upregulated in WT (P=7.2e-05) and showed an upward trend in line with the pathological stage. Patients with lower mRNAsi scores had better overall survival (OS) than those with higher mRNAsi scores (P=0.0087). Eleven genes were defined as the key genes associated with the mRNAsi based on our WGCNA analysis [cor.MM (correlation. Module membership) >0.8 and cor.GS (correlation. Gene significance) >0.45] and were closely related to cell proliferation-related signaling pathways (P<0.05). Moreover, using protein interaction analysis, we identified ATM and CDKN1A as the key upstream regulatory genes of the 11 key genes.

Conclusions

Our study showed that the mRNAsi score was a potential prognostic factors in WT and identified the upstream genes ATM and CDKN1A and 11 genes closely related to the mRNAsi, which may provide new insights for CSC-targeted therapy in WT and improve clinical outcomes for WT patients.

Daphnia magna egg piRNA cluster expression profiles change as mothers age

BACKGROUND

PiRNAs prevent transposable elements wreaking havoc on the germline genome. Changes in piRNA expression over the lifetime of an individual may impact on ageing through continued suppression, or release, of transposable element expression. We identified piRNA producing clusters in the genome of Daphnia magna by a combination of bioinformatic methods, and then contrasted their expression between parthenogenetically produced eggs representing maternally-deposited germline piRNAs of young (having their 1st clutch) and old (having their 5th clutch) mothers. Results from eggs were compared to cluster expression in three generations of adults.

RESULTS

As for other arthropods, D. magna encodes long uni-directionally transcribed non-coding RNAs consisting of fragmented transposable elements which account for most piRNAs expressed. Egg tissues showed extensive differences between clutches from young mothers and those from old mothers, with 578 and 686 piRNA clusters upregulated, respectively. Most log fold-change differences for significant clusters were modest, however. When considering only highly expressed clusters, there was a bias towards 1st clutch eggs at 41 upregulated versus eight clusters in the eggs from older mothers. F0 generation differences between young and old mothers were fewer than eggs, as 179 clusters were up-regulated in young versus 170 old mothers. This dropped to 31 versus 22 piRNA clusters when comparing adults in the F1 generation, and no differences were detected in the F3 generation. Inter-generational losses of differential piRNA cluster were similar to that observed for D. magna micro-RNA expression.

CONCLUSIONS

Little overlap in differentially expressed clusters was found between adults containing mixed somatic and germline (ovary) tissues and germ-line representing eggs. A cluster encompassing a Tudor domain containing gene important in the piRNA pathway was upregulated in the eggs from old mothers. We hypothesise that regulation of this gene could form part of a feedback loop that reduces piRNA pathway activity explaining the reduced number of highly-expressed clusters in eggs from old mothers.

piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers

piRNAs (PIWI-interacting RNAs) are small non-coding RNAs capable of regulation of transposon and gene expression. piRNAs utilise multiple mechanisms to affect gene expression, which makes them potentially more powerful regulators than microRNAs. The mechanisms by which piRNAs regulate transposon and gene expression include DNA methylation, histone modifications, and mRNA degradation. Genitourinary cancers (GC) are a large group of neoplasms that differ by their incidence, clinical course, biology, and prognosis for patients. Regardless of the GC type, metastatic disease remains a key therapeutic challenge, largely affecting patients’ survival rates. Recent studies indicate that piRNAs could serve as potentially useful biomarkers allowing for early cancer detection and therapeutic interventions at the stage of non-advanced tumour, improving patient’s outcomes. Furthermore, studies in prostate cancer show that piRNAs contribute to cancer progression by affecting key oncogenic pathways such as PI3K/AKT. Here, we discuss recent findings on biogenesis, mechanisms of action and the role of piRNAs and the associated PIWI proteins in GC. We also present tools that may be useful for studies on the functioning of piRNAs in cancers.

piRNAQuest V.2: an updated resource for searching through the piRNAome of multiple species

PIWI interacting RNAs (piRNAs) have emerged as important gene regulators in recent times. Since the release of our first version of piRNAQuest in 2014, lots of novel piRNAs have been annotated in different species other than human, mouse and rat. Such new developments in piRNA research have led us to develop an updated database piRNAQuest V.2. It consists of 92,77,689 piRNA entries for 25 new species of different phylum along with human, mouse and rat. Besides providing primary piRNA features which include their genomic location, with further information on piRNAs overlapping with repeat elements, pseudogenes and syntenic regions, etc., the novel features of this version includes (i) density based cluster prediction, (ii) piRNA expression profile across various healthy and disease systems and (iii) piRNA target prediction. The concept of density-based piRNA cluster identification is robust as it does not consider parametric distribution in its model. The piRNA expression profile for 21 disease systems including cancer have been hosted in addition to 32 tissue specific piRNA expression profile for various species. Further, the piRNA target prediction section includes both predicted and curated piRNA targets within eight disease systems and developmental stages of mouse testis. Further, users can visualize the piRNA-target duplex structure and the ping-pong signature pattern for all the ping-pong piRNA partners in different species. Overall, piRNAQuest V.2 is an updated user-friendly database which will serve as a useful resource to survey, search and retrieve information on piRNAs for multiple species. This freely accessible database is available at http://dibresources.jcbose.ac.in/zhumur/pirnaquest2.

Candidate l-methionine target piRNA regulatory networks analysis response to cocaine-conditioned place preference in mice

BACKGROUND

Methionine has been proven to inhibit addictive behaviors of cocaine dependence. However, the mechanism of methionine response to cocaine CPP is unknown. Recent evidence highlights piRNAs to regulate genes via a miRNA-like mechanism. Here, next-generation sequencing is used to study mechanism on methionine response to drug-induced behaviors though piRNA.

METHODS

l-methionine treatment cocaine CPP animal model was used to do non-coding RNA sequencing. There were four groups to sequence: saline+saline (SS), MET+saline (MS), MET+cocaine (MC), and cocaine+saline. Combining mRNA sequencing data, the network and regulation of piRNA were analyzed with their corresponding mRNA and miRNA.

RESULTS

Analysis of the piRNAome reveals that piRNAs inversely regulated their target mRNA genes. KEGG analysis of DE-piRNA target mRNA genes were enriched in Morphine addiction, GABAergic synapse and Cholinergic synapse pathway. Furthermore, four significantly differential expressed genes Cacna2d3, Epha6, Nedd4l, and Vav2 were identified and regulated by piRNAs in the process of l-methionine inhibits cocaine CPP. Thereinto, Vav2 was regulated by multiple DE piRNAs by sharing the common sequence: GTCTCTCCAGCCACCTT. Meanwhile, it was found that piRNA positively regulates miRNA and three genes Bcl3, Il20ra, and Insrr were identified and regulated by piRNA through miRNA.

CONCLUSION

The results showed that piRNA negatively regulated target mRNA genes and positively regulated target miRNA genes. Genes located in substance dependence, signal transduction and also nervous functions pathways were identified. When taken together, these data may explain the roles of l-methionine in counteracting the effects of cocaine CPP via piRNAs.

PIWI‑interacting RNA in cancer: Molecular mechanisms and possible clinical implications (Review)

PIWI‑interacting RNA is a class of non‑coding small RNA that is ~30 nt long and is primarily found in mammalian germ cells from mice and humans. In cooperation with the members of PIWI protein family, this macromolecule participates in germ cell development, inhibits DNA self‑-replication and maintains genomic stability. Increasing evidence has demonstrated that PIWI‑interacting RNA (piRNAs) are abnormally expressed in various human cancers, such as liver cancer, stomach cancer, colorectal cancer, osteosarcoma, breast cancer, lung cancer, prostate cancer, etc. piRNAs abnormal expression is also associated with the occurrence and development of human cancers, such as liver cancer, stomach cancer, colorectal cancer, etc. Despite their unclear molecular mechanisms, piRNAs may act as oncogenes or tumor suppressors by interacting with multiple cancer‑related signal pathways including STAT3/Bcl‑xl or coding genes, such as heat shock transcription factor‑1. Hence, piRNAs may be potential markers and targets and provide new opportunities for cancer diagnosis, treatment or prognosis monitoring. The current review mainly aims to highlight the latest research progress made in the biological functions and regulation of piRNAs in mammals, their involvement in various cancer forms and their potential clinical applications.

Computational Methods and Online Resources for Identification of piRNA-Related Molecules

piRNAs are a class of small non-coding RNA molecules, which interact with the PIWI family and have many important and diverse biological functions. The present review is aimed to provide guidelines and contribute to piRNA research. We focused on the four types of identification models on piRNA-related molecules, including piRNA, piRNA cluster, piRNA target, and disease-related piRNA. We evaluated the types of tools for the identification of piRNAs based on five aspects: datasets, features, classifiers, performance, and usability. We found the precision of 2lpiRNApred was the highest in datasets of model organisms, piRNN had a better performance of datasets of non-model organisms, and 2L-piRNA had the fastest recognition speed of all tools. In addition, we presented an overview of piRNA databases. The databases were divided into six categories: basic annotation, comprehensive annotation, isoform, cluster, target, and disease. We found that piRNA data of non-model organisms, piRNA target data, and piRNA-disease-associated data should be strengthened. Our review might assist researchers in selecting appropriate tools or datasets for their studies, reveal potential problems and shed light on future bioinformatics studies.

Non-Coding RNAs Set a New Phenotypic Frontier in Prostate Cancer Metastasis and Resistance

Prostate cancer (PCa) mortality remains a significant public health problem, as advanced disease has poor survivability due to the development of resistance in response to both standard and novel therapeutic interventions. Therapeutic resistance is a multifaceted problem involving the interplay of a number of biological mechanisms including genetic, signaling, and phenotypic alterations, compounded by the contributions of a tumor microenvironment that supports tumor growth, invasiveness, and metastasis. The androgen receptor (AR) is a primary regulator of prostate cell growth, response and maintenance, and the target of most standard PCa therapies designed to inhibit AR from interacting with androgens, its native ligands. As such, AR remains the main driver of therapeutic response in patients with metastatic castration-resistant prostate cancer (mCRPC). While androgen deprivation therapy (ADT), in combination with microtubule-targeting taxane chemotherapy, offers survival benefits in patients with mCRPC, therapeutic resistance invariably develops, leading to lethal disease. Understanding the mechanisms underlying resistance is critical to improving therapeutic outcomes and also to the development of biomarker signatures of predictive value. The interconversions between epithelial-to-mesenchymal transition (EMT) and mesenchymal-to-epithelial transition (MET) navigate the prostate tumor therapeutic response, and provide a novel targeting platform in overcoming therapeutic resistance. Both microRNA (miRNA)- and long non-coding RNA (lncRNA)-mediated mechanisms have been associated with epigenetic changes in prostate cancer. This review discusses the current evidence-based knowledge of the role of the phenotypic transitions and novel molecular determinants (non-coding RNAs) as contributors to the emergence of therapeutic resistance and metastasis and their integrated predictive value in prostate cancer progression to advanced disease.

LMTK2 as Potential Biomarker for Stratification between Clinically Insignificant and Clinically Significant Prostate Cancer

A set of prostate tumors tend to grow slowly and do not require active treatment. Therefore, stratification between patients with clinically significant and clinically insignificant prostate cancer (PC) remains a vital issue to avoid overtreatment. Fast development of genetic technologies accelerated development of next-generation molecular tools for reliable PC diagnosis. The aim of this study is to evaluate the diagnostic value of molecular biomarkers (CRISP3, LMTK2, and MSMB) for separation of PC cases from benign prostatic changes and more specifically for identification of clinically significant PC from all pool of PC cases in patients with rising PSA levels. Patients (n = 200) who had rising PSA (PSA II) after negative transrectal systematic prostate biopsy due to elevated PSA (PSA I) were eligible to the study. In addition to PSA concentration, PSA density was calculated for each patient. Gene expression level was measured in peripheral blood samples of cases applying RT-PCR, while MSMB (−57 C/T) polymorphism was identified by pyrosequencing. LMTK2 and MSMB significantly differentiated control group from both BPD and PC groups. MSMB expression tended to increase from the major alleles of the CC genotype to the minor alleles of the TT genotype. PSA density was the only clinical characteristic that significantly differentiated clinically significant PC from clinically insignificant PC. Therefore, LMTK2 expression and PSA density were significantly distinguished between clinically significant PC and clinically insignificant PC. PSA density rather than PSA can differentiate PC from the benign prostate disease and, in combination with LMTK2, assist in stratification between clinically insignificant and clinically significant PC.

Cargo small non-coding RNAs of extracellular vesicles isolated from uterine fluid associate with endometrial receptivity and implantation success

OBJECTIVE

To optimize a method of isolating extracellular vesicles (EVs) from uterine fluid and to characterize small non-coding RNAs (sncRNAs) from the EVs, with the goal of identifying novel receptivity-associated biomarkers.

DESIGN

Longitudinal study comparing sncRNA expression profiles from endometrial EVs.

SETTING

University-affiliated, hospital-based fertility clinic.

PATIENT(S)

Healthy volunteers with no history of infertility (Group A) and women receiving controlled ovarian stimulation (COS)-in vitro fertilization treatment (Group B).

INTERVENTIONS(S)

In Group A, EVs were isolated from uterine fluid obtained on luteinizing hormone (LH)+2 and LH+7 in one natural menstrual cycle. In Group B, EVs were isolated from uterine fluid obtained on human chorionic gonadotropin (hCG)+2 and hCG+7 in one COS cycle. RNAs extracted from EVs were profiled using next-generation sequencing.

MAIN OUTCOME MEASURE(S)

Differential EV-sncRNAs between LH+2 and LH+7 (Group A), between hCG+2 and hCG+7 (Group B), and between pregnant and nonpregnant in vitro fertilization cycles (Group B).

RESULT(S)

Ultracentrifugation was validated as the most efficient method to isolate EVs from uterine fluid. We identified 12 endometrial EV-sncRNAs (11 microRNAs and 1 piwi-interacting RNA) as receptivity-associated transcripts conserved in both natural and COS cycles. These sncRNAs were associated strongly with biological functions related to immune response, extracellular matrix, and cell junction. Within COS cycles, we also identified a group of EV-sncRNAs that exhibited differential expression in patients who conceived versus those who did not, with hsa-miR-362-3p most robustly overexpressed in the nonpregnant patients.

CONCLUSION(S)

This study is the first to profile comprehensively sncRNAs in endometrial EVs from uterine fluid and identify sncRNA biomarkers of endometrial receptivity and implantation success.