Whole transcriptome analysis identifies differentially expressed mRNA, miRNA and lncRNA associated with male sterility in the silkworm, Bombyx mori.

Insect sterility technology is gradually being applied to the control of lepidoptera pests, and the target gene for male sterility is the core of this technology. JMS is a mutant silkworm that exhibits male sterility, and to elucidate its formation mechanism, this study conducted a full transcriptome analysis of the testes of JMS and its wild-type silkworms 48 h after pupation, identifying 205 DElncRNAs, 913 mRNAs, and 92 DEmiRNAs. The KEGG pathway enrichment analysis of the DEmRNAs revealed that they were involved in the biosynthesis of amino acids and ECM-receptor interactions. Combined with ceRNA regulatory network KEGG analysis suggests that pathways from amino acid biosynthesis to hydrolytic processes of protein synthesis may play a crucial role in the formation of JMS mutant variants. Our study deepens our understanding of the regulatory network of male sterility genes in silkworms; it also provides a new perspective for insect sterility technology.

Long non-coding RNA HOTTIP promotes renal cell carcinoma progression through the regulation of the miR-506 pathway.

HOXA transcript at the distal tip (HOTTIP), a lncRNA, induces cell proliferation and cancer progression. However, the expression and function of HOTTIP in renal cell carcinoma (RCC) were rarely reported. The role of the HOTTIP in RCC was explored in this study. HOTTIP expresses higher in RCC tissues than in normal tissues and indicates poor prognosis based on the TCGA database. The over- and low-expression HOTTIP cell line was established in this research to assess the oncogenic function of HOTTIP in RCC progression. Mechanistic analyses revealed that HOTTIP functioned as a competing endogenous RNA (ceRNA) for miR-506. RIP experiment and luciferase assay were performed to explore the mechanisms of the sponge between HOTTIP and miR-506. HOTTIP down-regulation attenuated cell proliferation, migration, and invasion, which could be rescued by miR-506 down-regulation. On the whole, this study revealed that the HOTTIP/miR-506 axis has a dominant impact on RCC progression and potentially provides a novel strategy for RCC diagnosis and therapy.

A black phosphorus nanosheet-based RNA delivery system for prostate cancer therapy by increasing the expression level of tumor suppressor gene PTEN via CeRNA mechanism.

BACKGROUND: Prostate cancer (PCa) has a high incidence in men worldwide, and almost all PCa patients progress to the androgen-independent stage which lacks effective treatment measures. PTENP1, a long non-coding RNA, has been shown to suppress tumor growth through the rescuing of PTEN expression via a competitive endogenous RNA (ceRNA) mechanism. However, PTENP1 was limited to be applied in the treatment of PCa for the reason of rapid enzymatic degradation, poor intracellular uptake, and excessively long base sequence to be synthesized. Considering the unique advantages of artificial nanomaterials in drug loading and transport, black phosphorus (BP) nanosheet was employed as a gene-drug carrier in this study. RESULTS: The sequence of PTENP1 was adopted as a template which was randomly divided into four segments with a length of about 1000 nucleotide bases to synthesize four different RNA fragments as gene drugs, and loaded onto polyethyleneimine (PEI)-modified BP nanosheets to construct BP-PEI@RNA delivery platforms. The RNAs could be effectively delivered into PC3 cells by BP-PEI nanosheets and elevating PTEN expression by competitive binding microRNAs (miRNAs) which target PTEN mRNA, ultimately exerting anti-tumor effects. CONCLUSIONS: Therefore, this study demonstrated that BP-PEI@RNAs is a promising gene therapeutic platform for PCa treatment.

Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis.

BACKGROUND: Circular RNAs (circRNAs) have been shown to play critical roles in the initiation and progression of chronic glomerulonephritis (CGN), while their role from mesangial cells in contributing to the pathogenesis of CGN is rarely understood. Our study aims to explore the potential functions of mesangial cell-derived circRNAs using RNA sequencing (RNA-seq) and bioinformatics analysis. METHODS: Mouse mesangial cells (MMCs) were stimulated by lipopolysaccharide (LPS) to establish an in vitro model of CGN. Pro-inflammatory cytokines and cell cycle stages were detected by Enzyme-linked immunosorbent assay (ELISA) and Flow Cytometry experiment, respectively. Subsequently, differentially expressed circRNAs (DE-circRNAs) were identified by RNA-seq. GEO microarrays were used to identify differentially expressed mRNAs (DE-mRNAs) between CGN and healthy populations. Weighted co-expression network analysis (WGCNA) was utilized to explore clinically significant modules of CGN. CircRNA-associated CeRNA networks were constructed by bioinformatics analysis. The hub mRNAs from CeRNA network were identified using LASSO algorithms. Furthermore, utilizing protein-protein interaction (PPI), gene ontology (GO), pathway enrichment (KEGG), and GSEA analyses to explore the potential biological function of target genes from CeRNA network. In addition, we investigated the relationships between immune cells and hub mRNAs from CeRNA network using CIBERSORT. RESULTS: The expression of pro-inflammatory cytokines IL-1ß, IL-6, and TNF-α was drastically increased in LPS-induced MMCs. The number of cells decreased significantly in the G1 phase but increased significantly in the S/G2 phase. A total of 6 DE-mRNAs were determined by RNA-seq, including 4 up-regulated circRNAs and 2 down-regulated circRNAs. WGCNA analysis identified 1747 DE-mRNAs of the turquoise module from CGN people in the GEO database. Then, the CeRNA networks, including 6 circRNAs, 38 miRNAs, and 80 mRNAs, were successfully constructed. The results of GO and KEGG analyses revealed that the target mRNAs were mainly enriched in immune, infection, and inflammation-related pathways. Furthermore, three hub mRNAs (BOC, MLST8, and HMGCS2) from the CeRNA network were screened using LASSO algorithms. GSEA analysis revealed that hub mRNAs were implicated in a great deal of immune system responses and inflammatory pathways, including IL-5 production, MAPK signaling pathway, and JAK-STAT signaling pathway. Moreover, according to an evaluation of immune infiltration, hub mRNAs have statistical correlations with neutrophils, plasma cells, monocytes, and follicular helper T cells. CONCLUSIONS: Our findings provide fundamental and novel insights for further investigations into the role of mesangial cell-derived circRNAs in CGN pathogenesis.

Identifying autophagy-related mRNAs and potential ceRNA networks in meniscus degeneration based on RNA sequencing and experimental validation.

Purpose: The intimate connection between long noncoding RNA (lncRNA) and autophagy has been established in cartilage degeneration. However, their roles in meniscal degeneration remain ambiguous. This study aimed to identify the key autophagy-related lncRNA and its associated regulatory network in meniscal degeneration in the context of osteoarthritis (OA). Methods: RNA sequencing was performed to identify differentially expressed lncRNAs (DELs) and mRNAs (DEMs), which were then conducted to enrichment analyses using the DAVID database and Metascape. Autophagy-related DEMs were identified by combining DEMs with data from the Human Autophagy Database. Three databases were used to predict miRNA, and the DIANA LncBase Predicted database was utilized to predict miRNA-lncRNA interactions. Based on these predictions, comprehensive competitive endogenous RNA (ceRNA) network were constructed. The expression levels of the classical autophagy markers and autophagy-related ceRNA network were validated. Additionally, Gene Set Enrichment Analysis (GSEA) was performed using autophagy-related DEMs. Results: 310 DELs and 320 DEMs were identified, with five upregulated and one downregulated autophagy-related DEMs. Through reverse prediction of miRNA, paired miRNA-lncRNA interactions, and verification using RT-qPCR, two lncRNAs (PCAT19, CLIP1-AS1), two miRNA (has-miR-3680-3p and has-miR-4795-3p) and two mRNAs (BAG3 and HSP90AB1) were included in the constructed ceRNA regulatory networks. GSEA indicated that the increased expression of autophagy-related mRNAs inhibited glycosaminoglycan biosynthesis in the degenerative meniscus. Conclusion: This study presented the first construction of regulatory ceRNA network involving autophagy-related lncRNA-miRNA-mRNA interactions in OA meniscus. These findings offered valuable insights into the mechanisms underlying meniscal degeneration and provided potential targets for therapeutic intervention.

Effect of ZIC2 on immune infiltration and ceRNA axis regulation in lung adenocarcinoma via bioinformatics and experimental studies.

OBJECTIVE: This study aimed to conlude the effect and mechanism of ZIC2 on immune infiltration in lung adenocarcinoma (LUAD). METHODS: Expression of ZIC2 in several kinds of normal tissues of TCGA data was analyzed and its correlation with the baseline characteristic of LUAD patients were analyzed. The immune infiltration analysis of LUAD patients was performed by CIBERSORT algorithm. The correlation analysis between ZIC2 and immune cell composition was performed. Additionally, the potential upstream regulatory mechanisms of ZIC2 were predicted to identify the possible miRNAs and lncRNAs that regulated ZIC2 in LUAD. In vitro and in vivo experiments were also conducted to confirm the potential effect of ZIC2 on cell proliferation and invasion ability of LUAD cells. RESULTS: ZIC2 expression was decreased in various normal tissues, but increased in multiple tumors, including LUAD, and correlated with the prognosis of LUAD patients. Enrichement by GO and KEGG suggested the possible association of ZIC2 with cell cycle and p53 signal pathway. ZIC2 expression was significantly correlated with T cells CD4 memory resting, Macrophages M1, and plasma cells, indicating that dysregulated ZIC2 expression in LUAD may directly influence immune infiltration. ZIC2 might be regulated by several different lncRNA-mediated ceRNA mechanisms. In vitro experiments validated the promotive effect of ZIC2 on cell viability and invasion ability of LUAD cells. In vivo experiments validated ZIC2 can accelerate tumor growth in nude mouse. CONCLUSION: ZIC2 regulated by different lncRNA-mediated ceRNA mechanisms may play a critical regulatory role in LUAD through mediating the composition of immune cells in tumor microenvironment.

[Retracted] LINC00665 functions as a competitive endogenous RNA to regulate AGTR1 expression by sponging miR­34a­5p in glioma.

Following the publication of the above paper, it was drawn to the Editor's attention by a concerned reader that the 'Control' data panel shown for the EdU assay experiment in Fig. 6D on p. 1209 was strikingly similar to a data panel featured in Fig. 7 that had already been submitted to the journal Cancer Management and Research by different authors at different research institutes [Chen T­J, Gao F, Yang T, Li H, Li Y, Ren H and Chen M­W: Knockdown of linc­POU3F3 suppresses the proliferation, apoptosis, and migration resistance of colorectal cancer. Cancer Manag Res 12: 4379­4390, 2020]. Owing to the fact that contentious data in the above article had already been submitted for publication prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 45: 1202­1212, 2021; DOI: 10.3892/or.2021.7949].

Whole transcriptome analysis revealed the regulatory network and related pathways of non-coding RNA regulating ovarian atrophy in broody hens.

Poultry broodiness can cause ovarian atresia, which has a detrimental impact on egg production. Non-coding RNAs (ncRNAs) have become one of the most talked-about topics in life sciences because of the increasing evidence of their novel biological roles in regulatory systems. However, the molecular mechanisms of ncRNAs functions and processes in chicken ovarian development remain largely unknown. Whole-transcriptome RNA sequencing of the ovaries of broodiness and laying chickens was thus performed to identify the ncRNA regulatory mechanisms associated with ovarian atresia in chickens. Subsequent analysis revealed that the ovaries of laying chickens and those with broodiness had 40 differentially expressed MicroRNA (miRNAs) (15 up-regulated and 25 down-regulated), 379 differentially expressed Long Noncoding RNA (lncRNAs) (213 up-regulated and 166 down-regulated), and 129 differentially expressed circular RNA (circRNAs) (63 up-regulated and 66 down-regulated). The competing endogenous RNAs (ceRNA) network analysis further revealed the involvement of ECM-receptor interaction, AGE-RAGE signaling pathway, focal adhesion, cytokine-cytokine receptor interaction, inflammatory mediator regulation of TRP channels, renin secretion, gap junction, insulin secretion, serotonergic synapse, and IL-17 signaling pathways in broodiness. Upon further analysis, it became evident that THBS1 and MYLK are significant candidate genes implicated in the regulation of broodiness. The expression of these genes is linked to miR-155-x, miR-211-z, miR-1682-z, gga-miR-155, and gga-miR-1682, as well as to the competitive binding of novel_circ_014674 and MSTRG.3306.4. The findings of this study reveal the existence of a regulatory link between non-coding RNAs and their competing mRNAs, which provide a better comprehension of the ncRNA function and processes in chicken ovarian development.

Illuminating the pathogenic role of SARS-CoV-2: Insights into competing endogenous RNAs (ceRNAs) regulatory networks.

The appearance of SARS-CoV-2 in 2019 triggered a significant economic and health crisis worldwide, with heterogeneous molecular mechanisms that contribute to its development are not yet fully understood. Although substantial progress has been made in elucidating the mechanisms behind SARS-CoV-2 infection and therapy, it continues to rank among the top three global causes of mortality due to infectious illnesses. Non-coding RNAs (ncRNAs), being integral components across nearly all biological processes, demonstrate effective importance in viral pathogenesis. Regarding viral infections, ncRNAs have demonstrated their ability to modulate host reactions, viral replication, and host-pathogen interactions. However, the complex interactions of different types of ncRNAs in the progression of COVID-19 remains understudied. In recent years, a novel mechanism of post-transcriptional gene regulation known as "competing endogenous RNA (ceRNA)" has been proposed. Long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and viral ncRNAs function as ceRNAs, influencing the expression of associated genes by sequestering shared microRNAs. Recent research on SARS-CoV-2 has revealed that disruptions in specific ceRNA regulatory networks (ceRNETs) contribute to the abnormal expression of key infection-related genes and the establishment of distinctive infection characteristics. These findings present new opportunities to delve deeper into the underlying mechanisms of SARS-CoV-2 pathogenesis, offering potential biomarkers and therapeutic targets. This progress paves the way for a more comprehensive understanding of ceRNETs, shedding light on the intricate mechanisms involved. Further exploration of these mechanisms holds promise for enhancing our ability to prevent viral infections and develop effective antiviral treatments.

Identification of Potential lncRNA-miRNA-mRNA Regulatory Network Contributing to Arrhythmogenic Right Ventricular Cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) can lead to sudden cardiac death and life-threatening heart failure. Due to its high fatality rate and limited therapies, the pathogenesis and diagnosis biomarker of ARVC needs to be explored urgently. This study aimed to explore the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network in ARVC. The mRNA and lncRNA expression datasets obtained from the Gene Expression Omnibus (GEO) database were used to analyze differentially expressed mRNA (DEM) and lncRNA (DElnc) between ARVC and non-failing controls. Differentially expressed miRNAs (DEmiRs) were obtained from the previous profiling work. Using starBase to predict targets of DEmiRs and intersecting with DEM and DElnc, a ceRNA network of lncRNA-miRNA-mRNA was constructed. The DEM and DElnc were validated by real-time quantitative PCR in human heart tissue. Protein-protein interaction network and weighted gene co-expression network analyses were used to identify hub genes. A logistic regression model for ARVC diagnostic prediction was established with the hub genes and their ceRNA pairs in the network. A total of 448 DEMs (282 upregulated and 166 downregulated) were identified, mainly enriched in extracellular matrix and fibrosis-related GO terms and KEGG pathways, such as extracellular matrix organization and collagen fibril organization. Four mRNAs and two lncRNAs, including COL1A1, COL5A1, FBN1, BGN, XIST, and LINC00173 identified through the ceRNA network, were validated by real-time quantitative PCR in human heart tissue and used to construct a logistic regression model. Good ARVC diagnostic prediction performance for the model was shown in both the training set and the validation set. The potential lncRNA-miRNA-mRNA regulatory network and logistic regression model established in our study may provide promising diagnostic methods for ARVC.

Exploring Ferroptosis-Associated Gene Signatures as Diagnostic and Therapeutic Targets for Sepsis-Induced Cardiomyopathy.

BACKGROUND: Sepsis-induced cardiomyopathy (SICM) is a severe complication of sepsis associated with high mortality rates. Despite its significance, the molecular mechanisms underlying SICM remain poorly understood, particularly the role of ferroptosis - a form of iron-dependent programmed cell death. METHODOLOGY: This study analyzed the GSE79962 dataset from the Gene Expression Omnibus, containing cardiac gene expression profiles from SICM patients and controls. A list of ferroptosis-related genes (FRGs) was retrieved from the FerrDb. We used the limma package in R for differential expression analysis, setting an adjusted P-value cutoff of <0.05 and a log2-fold change threshold of ±1 to identify differentially expressed ferroptosis-related genes (DE-FRGs). We applied machine learning algorithms for biomarker identification, including least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine with recursive feature elimination (SVM-RFE), implemented via the glmnet and e1071 packages in R, respectively. Gene set enrichment analysis (GSEA) was conducted using the GSEA package to investigate the biological pathways related to key DE-FRGs. RESULTS: After differential expression analysis, we identified 145 DE-FRGs. Functional enrichment analyses underscored the involvement of these genes in critical biological processes and pathways, such as lipid metabolism and insulin resistance. Machine learning approaches pinpointed five key DE-FRGs (NCOA4, GABARAPL1, GJA1, CISD1, CP), with strong predictive potential for SICM. Further analyses, including the construction of a ceRNA network, revealed intricate post-transcriptional regulatory mechanisms that may influence the expression of these key genes. CONCLUSIONS: Our findings highlight the central role of ferroptosis in SICM and identify potential biomarkers and therapeutic targets that could help refine diagnostic and treatment strategies. This study advances our understanding of the molecular underpinnings of SICM and sets the stage for future research aimed at mitigating this severe sepsis complication.

CircRNA hsa_circ_0069,399 as a potential clinical prognostic marker in laryngeal squamous cell carcinoma.

Objective: Circular RNAs (circRNAs) significantly influence the invasion, metastasis, gene expression, proliferation, and apoptosis of tumor cells. However, the roles of circRNAs in laryngeal squamous cell carcinoma (LSCC) remain largely unexplored. This study aims to examine circRNA expression patterns in LSCC and adjacent non-tumorous tissues, with the goal of uncovering potential biomarkers for LSCC. Methods: Tissue samples were collected from both the tumor and adjacent normal tissues of ten patients who had undergone surgical resection. The profiling of circRNAs was conducted through transcriptomic sequencing and analytical bioinformatics approaches. A ternary regulatory network based on the competitive endogenous RNA (ceRNA) hypothesis was established, linking target circRNAs to clinical immunohistochemical parameters for comparison. Verification of target circRNAs in LSCC tissues was performed using quantitative real-time PCR (RT-qPCR), whereas target mRNAs were analyzed through immunohistochemistry. Results: A total of 126 significantly different circRNAs were identified, including 40 up-regulated genes and 86 down-regulated genes. Furthermore, 92 circRNA-miRNA-mRNA regulatory relationship axes related to clinical immunohistochemical indicators were found based on 5 candidate circRNAs. Interestingly, all axes related to the target genes MKI67 and TP53 were found to compete with the same circRNA: hsa_circ_0069,399. Further verification confirmed that the hsa_circ_0069,399 expression was overtly upregulated in tumor tissues from LSCC patients, which was consistent with the sequencing results. Conclusion: hsa_circ_0069,399 could be a potential prognostic marker for LSCC.

Comprehensive analysis of ceRNA network and immune cell infiltration pattern of autophagy related genes in IgA nephropathy.

INTRODUCTION: IgA nephropathy (IgAN) is a prevalent worldwide glomerular disease with a complex pathophysiology that has significant economic implications. Despite the lack of successful research, this study aims to discover the potential competing endogenous RNA (ceRNA) network of autophagy-associated genes in IgAN and examine their correlation with immune cell infiltration. METHODS: Autophagy-related hub genes were discovered by assessing the GSE116626 dataset and constructing a protein-protein interaction network. Nephroseq v5 analysis engine was used to analyze correlations between hub genes and proteinuria, glomerular filtration rate (GFR) and serum creatinine levels. Then, a ceRNA network construction and the CIBERSORT tool for immune cell infiltration analysis were also performed. Additionally, the differentially expressed autophagy-related genes (DEARGs) were used to predict potential targeted medications for IgAN. RESULTS: 1396 differentially expressed genes (DEGs) were identified in IgAN along with 25 autophagy-related differentially expressed messenger RNAs (DEmRNAs). Enrichment analysis revealed significant involvement of autophagy and apoptosis in biological processes. Next, we evaluated the top hub nodes based on their highest degrees. The ability of IgAN discrimination was confirmed in the GSE35487 and GSE37460 datasets by validating the five hub genes: SIRT1, FOS, CCL2, CDKN1A and MYC. In the Nephroseq v5 analysis engine, the clinical correlation of the five hub genes was confirmed. Furthermore, the ceRNA network identified 18 circular RNAs and 2 microRNAs associated with hub autophagy-related genes in IgAN. Our investigation identified hsa-miR-32-3p and hsa-let-7i-5p as having elevated expression levels and substantial diagnostic value. Finally, four distinctively infiltrated immune cells were found to be associated with the hub autophagy-related genes, and 67 drugs were identified as potential therapeutic options for IgAN. CONCLUSION: This study sheds light on a novel ceRNA regulatory network mechanism associated with autophagy in IgAN development.

Tweety homolog 3 promotes colorectal cancer progression through mutual regulation of histone deacetylase 7.

Colorectal cancer (CRC) is one of the leading cancers worldwide, with metastasis being a major cause of high mortality rates among patients. In this study, dysregulated gene Tweety homolog 3 (TTYH3) was identified by Gene Expression Omnibus database. Public databases were used to predict potential competing endogenous RNAs (ceRNAs) for TTYH3. Quantitative real-time polymerase chain reaction, western blot, and immunohistochemistry were utilized to analyze TTYH3 and histone deacetylase 7 (HDAC7) levels. Luciferase assays confirmed miR-1271-5p directly targeting the 3' untranslated regions of TTYH3 and HDAC7. In vitro experiments such as transwell and human umbilical vein endothelial cell tube formation, as well as in vivo mouse models, were conducted to assess the biological functions of TTYH3 and HDAC7. We discovered that upregulation of TTYH3 in CRC promotes cell migration by affecting the Epithelial-mesenchymal transition pathway, which was independent of its ion channel activity. Mechanistically, TTYH3 and HDAC7 functioned as ceRNAs, reciprocally regulating each other's expression. TTYH3 competes for binding miR-1271-5p, increasing HDAC7 expression, facilitating CRC metastasis and angiogenesis. This study reveals the critical role of TTYH3 in promoting CRC metastasis through ceRNA crosstalk, offering new insights into potential therapeutic targets for clinical intervention.

Identification and evaluation of a six-lncRNA prognostic signature for multiple myeloma.

PURPOSE: Multiple myeloma (MM) is the second most common hematologic malignancy, and there is no cure for this disease. This study aimed to explore the prognostic value of long noncoding RNAs (lncRNAs) in MM and to reveal related immune and chemotherapy resistance mechanisms. METHODS: In this study, lncRNA profiles from the Multiple Myeloma Research Foundation (MMRF) and Gene Expression Omnibus (GEO) databases were analyzed to identify lncRNAs linked to MM patient survival. A risk assessment model stratified patients into high- and low-risk groups, and survival was evaluated. Additionally, a triple-ceRNA (lncRNA-miRNA-mRNA) network was constructed, and functional analysis was performed. The research also involved immune function analysis and chemotherapy drug sensitivity assessment using oncoPredict and the GDSC dataset. RESULTS: We identified 422 lncRNAs significantly associated with overall survival in MM patients and ultimately focused on the 6 with the highest prognostic value. These lncRNAs were used to develop a risk score formula that stratified patients into high- and low-risk groups. Kaplan-Meier analysis revealed shorter survival in high-risk patients. We integrated this lncRNA signature with clinical parameters to construct a nomogram for predicting MM prognosis. Additionally, a triple-ceRNA network was constructed to reveal potential miRNA targets, coding genes related to these lncRNAs and significantly enriched pathways. Immune checkpoint gene expression and immune cell composition were also analyzed in relation to the lncRNA risk score. Finally, using the oncoPredict tool, we observed that high-risk patients exhibited decreased sensitivity to key MM chemotherapeutics, suggesting that lncRNA profiles are linked to chemotherapy resistance.

Osteosarcoma in a ceRNET perspective.

Osteosarcoma (OS) is the most prevalent and fatal type of bone tumor. It is characterized by great heterogeneity of genomic aberrations, mutated genes, and cell types contribution, making therapy and patients management particularly challenging. A unifying picture of molecular mechanisms underlying the disease could help to transform those challenges into opportunities.This review deeply explores the occurrence in OS of large-scale RNA regulatory networks, denominated "competing endogenous RNA network" (ceRNET), wherein different RNA biotypes, such as long non-coding RNAs, circular RNAs and mRNAs can functionally interact each other by competitively binding to shared microRNAs. Here, we discuss how the unbalancing of any network component can derail the entire circuit, driving OS onset and progression by impacting on cell proliferation, migration, invasion, tumor growth and metastasis, and even chemotherapeutic resistance, as distilled from many studies. Intriguingly, the aberrant expression of the networks components in OS cells can be triggered also by the surroundings, through cytokines and vesicles, with their bioactive cargo of proteins and non-coding RNAs, highlighting the relevance of tumor microenvironment. A comprehensive picture of RNA regulatory networks underlying OS could pave the way for the development of innovative RNA-targeted and RNA-based therapies and new diagnostic tools, also in the perspective of precision oncology.

Gene Profiling of Circular RNAs in Keloid-prone Individuals and ceRNA Network Construction During Wound Healing.

Epigenetic alterations of non-coding RNA (ncRNA) are pivotal in the continuous activation and differentiation of fibroblasts in keloid. However, the epigenetic mechanism of circRNA in keloid is still not clear yet. In this study, we aimed to investigate the interplay among differentially expressed circRNAs, miRNAs, and mRNAs during wound healing in keloid-prone individuals, construct a competing endogenous RNA (ceRNA) network, and gain an in-depth insight into the pathophysiological mechanisms underlying keloid development. Utilizing bioinformatic methods, we analyzed the expression profiles from the GSE113621 database. We identified 29 differentially expressed circRNAs (DEcircRNAs) in keloid-prone individuals during wound healing, from which we constructed 14 ceRNA networks. Subsequently, we validated the expression of predicted DEcircRNAs in keloid tissues and elucidated the ceRNA network involving circ_064002 and fibronectin-1 (FN1) through competing miR-30a/b-5p. Knocking down circ_064002 led to down-regulation of FN1 expression and various cellular functions in keloid-derived fibroblasts (KFs), including cell viability, migration, invasion, and repair capacity. Our study introduces a novel approach to explore the presence of DEcircRNAs and the ceRNA regulatory network during wound healing in keloid-prone individuals through in-depth mining of GEO data and also proves the epigenetic regulatory mechanism of circ_064002 in KFs. LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Analysis of key circRNA events in the AOP framework of TCS acting on zebrafish based on the data-driven.

Triclosan (TCS) is a broad-spectrum antibiotic widely used in various personal care products. Research has found that exposure to TCS can cause toxic effects on organisms including neurotoxicity, cardiotoxicity, disorders of lipid metabolism, and abnormal vascular development, and the corresponding toxic mechanisms are gradually delving into the level of abnormal expression of miRNA regulating gene expression. Although the downstream mechanism of TCS targeting miRNA abnormal expression to induce toxicity is gradually improving, its upstream mechanism is still in a fog. Starting from the abnormal expression data of circRNA in zebrafish larvae induced by TCS, this study conducted a hierarchical analysis of the expression levels of all circRNAs, differential circRNAs, and trend circRNAs, and identified 29 key circRNA events regulating miRNA abnormal expression. In combination with GO and KEGG, the effects of TCS exposure were analyzed from the function and signaling pathway of the corresponding circRNA host gene. Furthermore, based on existing literature evidence about the biological toxicity induced by TCS targeting miRNA as data support, a competing endogenous RNAs (ceRNA) network characterizing the regulatory relationship between circRNA and miRNA was constructed and optimized. Finally, a comprehensive Adverse Outcome Pathway (AOP) framework of multiple levels of events including circRNA, miRNA, mRNA, pathway, and toxicity endpoints was established to systematically elucidate the toxic mechanism of TCS. Moreover, the rationality of the AOP framework was verified from the expression level of miRNA and adverse outcomes such as neurotoxicity, cardiotoxicity, oxidative stress, and inflammatory response by knockdown of circRNA48. This paper not only provides the key circRNA events for exploring the upstream mechanism of miRNA regulating gene expression but also provides an AOP framework for comprehensively demonstrating the toxicity mechanism of TCS on zebrafish, which is a theoretical basis for subsequent hazard assessment and prevention and control of TCS.

Comprehensive analysis of the expression profiles of mRNA, lncRNA, circRNA, and miRNA in primary hair follicles of coarse sheep fetal skin.

BACKGROUND: The Qinghai Tibetan sheep, a local breed renowned for its long hair, has experienced significant deterioration in wool characteristics due to the absence of systematic breeding practices. Therefore, it is imperative to investigate the molecular mechanisms underlying follicle development in order to genetically enhance wool-related traits and safeguard the sustainable utilization of valuable germplasm resources. However, our understanding of the regulatory roles played by coding and non-coding RNAs in hair follicle development remains largely elusive. RESULTS: A total of 20,874 mRNAs, 25,831 circRNAs, 4087 lncRNAs, and 794 miRNAs were annotated. Among them, we identified 58 DE lncRNAs, 325 DE circRNAs, 924 DE mRNAs, and 228 DE miRNAs during the development of medullary primary hair follicle development. GO and KEGG functional enrichment analyses revealed that the JAK-STAT, TGF-ß, Hedgehog, PPAR, cGMP-PKG signaling pathway play crucial roles in regulating fibroblast and epithelial development during skin and hair follicle induction. Furthermore, the interactive network analysis additionally identified several crucial mRNA, circRNA, and lncRNA molecules associated with the process of primary hair follicle development. Ultimately, by investigating DEmir's role in the ceRNA regulatory network mechanism, we identified 113 circRNA-miRNA pairs and 14 miRNA-mRNA pairs, including IGF2BP1-miR-23-x-novel-circ-01998-MSTRG.7111.3, DPT-miR-370-y-novel-circ-005802-MSTRG.14857.1 and TSPEAR-oar-miR-370-3p-novel-circ-005802- MSTRG.10527.1. CONCLUSIONS: Our study offers novel insights into the distinct expression patterns of various transcription types during hair follicle morphogenesis, establishing a solid foundation for unraveling the molecular mechanisms that drive hair development and providing a scientific basis for selectively breeding desirable wool-related traits in this specific breed.

Identification of potential biomarkers for sepsis based on neutrophil extracellular trap-related genes.

Sepsis is a highly lethal disease that poses a serious threat to human health. Increasing evidence indicates that neutrophil extracellular traps (NETs) are key factors in the pathological progression of sepsis. This study aims to screen potential biomarkers for sepsis and delve into their regulatory function in the pathogenesis. We downloaded 6 microarray datasets from the Gene Expression Omnibus (GEO) database, with 4 as the training sets and 2 as the validation sets. NETs-related genes (NRGs) were obtained from relevant literature. Differential expression analysis was performed on four training sets separately. We intersected differentially expressed genes (DEGs) from the four training sets and NRGs, finally resulting in 19 NETs-related sepsis genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) unearthed that NETs-related sepsis genes were majorly abundant in functions and pathways such as defense response to bacterium and Neutrophil extracellular trap formation. Using the PPI network, the MCC algorithm, and the MCODE algorithm in the CytoHubba plugin, 7 sepsis hub genes (ELANE, TLR4, MPO, PADI4, CTSG, MMP9, S100A12) were identified. ROC curve for each Hub gene in the training and validation sets were plotted, which revealed that the Area Under Curve (AUC) values are all greater than 0.6, indicating good classification ability. A total of 349 miRNAs targeting Hub genes were predicted in the mirDIP database, and 620 lncRNAs targeting miRNAs were predicted in the ENCORI database. The ceRNA regulatory network was constructed using Cytoscape software. Finally, we employed the cMAP database to predict small molecular complexes as potentially effective drugs for the treatment of sepsis, such as chloroquine, harpagoside, and PD-123319. In conclusion, this project successfully identified 7 core genes, which may serve as promising candidates for novel sepsis biomarkers. Meanwhile, we constructed a related ceRNA network and predicted potential targeted drugs, providing potential therapeutic targets and treatment strategies for sepsis patients.