VECTOR: An Integrated Correlation Network Database for the Identification of CeRNA Axes in Uveal Melanoma

Comprehensive investigation of differentially expressed ncRNAs, mRNAs, and their ceRNA networks in the regulation of shell color formation in clam, Cyclina sinensis

Noncoding RNAs (ncRNAs) have gained significant attention in recent years due to their crucial roles in various biological processes. However, our understanding of the expression and functions of ncRNAs in Cyclina sinensis, an economically important marine bivalve, remains limited. This study aimed to address this knowledge gap by systematically identifying ncRNAs in the mantles of C. sinensis with purple and white shells. Through our analysis, we identified a differential expression of 1244 mRNAs, 196 lncRNAs, 49 circRNAs, and 23 miRNAs between purple- and white-shell clams. Functional enrichment analysis revealed the involvement of these differentially expressed ncRNAs in biomineralization and pigmentation processes. To gain further insights into the regulatory mechanisms underlying shell color formation, we established competitive endogenous RNA (ceRNA) networks. These networks allowed us to identify targeted differentially expressed miRNAs (DEMis) and genes associated with shell color formation. Based on the ceRNA networks, we obtained an up-down-up lncRNA-miRNA-mRNA network consisting of 13 upregulated lncRNAs and a circRNA-miRNA-mRNA network comprising three upregulated circRNAs (novel_circ_0004787, novel_circ_0001165, novel_circ_0000245). Through these networks, we identified and selected an upregulated novel gene (evm.TU.Hic_asm_7.988) and a downregulated sponge miRNA (hru-miR-1985) as potential contributors to shell color regulation. In summary, the present investigation offers a comprehensive analysis of ncRNA catalogs expressed in the clam mantle of C. sinensis. The findings enhance our comprehension of the molecular mechanisms governing shell coloration and offer new perspectives for selective breeding of C. sinensis in the future.

Uncovering the ceRNA Network Related to the Prognosis of Stomach Adenocarcinoma Among 898 Patient Samples

Stomach adenocarcinoma (STAD) patients are often associated with significantly high mortality rates and poor prognoses worldwide. Among STAD patients, competing endogenous RNAs (ceRNAs) play key roles in regulating one another at the post-transcriptional stage by competing for shared miRNAs. In this study, we aimed to elucidate the roles of lncRNAs in the ceRNA network of STAD, uncovering the molecular biomarkers for target therapy and prognosis. Specifically, a multitude of differentially expressed lncRNAs, miRNAs, and mRNAs (i.e., 898 samples in total) was collected and processed from TCGA. Cytoplasmic lncRNAs were kept for evaluating overall survival (OS) time and constructing the ceRNA network. Differentially expressed mRNAs in the ceRNA network were also investigated for functional and pathological insights. Interestingly, we identified one ceRNA network including 13 lncRNAs, 25 miRNAs, and 9 mRNAs. Among them, 13 RNAs were found related to the patient survival time; their individual risk score can be adopted for prognosis inference. Finally, we constructed a comprehensive ceRNA regulatory network for STAD and developed our own risk-scoring system that can predict the OS time of STAD patients by taking into account the above.

RNA-RNA competitive interactions: a molecular civil war ruling cell physiology and diseases

The idea that proteins are the main determining factors in the functioning of cells and organisms, and their dysfunctions are the first cause of pathologies, has been predominant in biology and biomedicine until recently. This protein-centered view was too simplistic and failed to explain the physiological and pathological complexity of the cell. About 80% of the human genome is dynamically and pervasively transcribed, mostly as non-protein-coding RNAs (ncRNAs), which competitively interact with each other and with coding RNAs generating a complex RNA network regulating RNA processing, stability, and translation and, accordingly, fine-tuning the gene expression of the cells. Qualitative and quantitative dysregulations of RNA-RNA interaction networks are strongly involved in the onset and progression of many pathologies, including cancers and degenerative diseases. This review will summarize the RNA species involved in the competitive endogenous RNA network, their mechanisms of action, and involvement in pathological phenotypes. Moreover, it will give an overview of the most advanced experimental and computational methods to dissect and rebuild RNA networks.

lncRNA NORAD, soluble ICAM1 and their correlations may be related to the regulation of the tumor immune microenvironment in laryngeal squamous cell carcinoma (LSCC)

NORAD, non-coding RNA activated by DNA damage, is a Long non-coding RNA (lncRNA) transcript that modulates genome stability and has been reported to be dysregulated in different cancers. Although it has been reported to be upregulated in tumor cells mostly for solid organ cancers, it has also been reported to be downregulated in some cancers. Although the pathophysiological mechanism is not fully understood, a negative correlation between NORAD and intercellular cell adhesion molecule-1 (ICAM-1) has been shown in experimental models, but this situation has not been evaluated in terms of cancer. We aimed to evaluate the potential roles of these two biomarker candidates together and separately in the clinicopathological axis in Laryngeal squamous cell carcinoma (LSCC) in a case-control study setting. The interactions of NORAD and ICAM1 at the RNA level were evaluated interactively by the RIblast program. sICAM1 (soluble intercellular cell adhesion molecule-1) levels were determined by ELISA in one hundred and five individuals (forty-four LSCC, sixty-one control) and lncRNA NORAD expression in eighty-eight tissues (forty-four LSCC tumors, forty-four tumor-free surrounding tissues) was determined by Real-time PCR. While the energy treesholud was - 16 kcal/mol between NORAD and ICAM1, the total energy was 176.33 kcal/mol, and 9 base pair pairings from 4 critical points were detected. NORAD expression level was found to be higher in tumor surrounding tissue compared to tumor tissue, and sICAM1 was higher in the control group compared to LSCC (p = 0.004; p = 0.02). NORAD discreminte tumor surrounding tissue from tumor (AUC: 0.674; optimal sensitivity:87.50%; optimal specificity 54.55%; cut-off point as >1.58 fold change; P = 0.034). The sICAM1 level was found to be higher in the control (494,814 ± 93.64 ng/L) than LSCC (432.95 ± 93.64 ng/L) (p = 0.02). sICAM1 discreminte control group from LSCC (AUC: 0.624; optimal sensitivity 68,85%; optimal specificity 61,36%; cut-off point ≤115,0 ng/L; (p = 0.033). A very strong negative correlation was found between NORAD expression and patients' sICAM1 levels (r = -.967; n = 44; p = 0.033). sICAM1 levels were found to be 1.63 times higher in NORAD downregulated subjects compared to upregulated ones (p = 0.031). NORAD was 3.63 times higher in those with alcohol use, and sICAM 1 was 5.77 times higher in those without distant organ metastasis (p = 0.043; 0.004). The increased NORAD expression in the tumor microenvironment in LSCC, the activation of T cells via TCR signaling, and the decrease of sICAM in the control group in correlation with NORAD suggests that ICAM1 may be needed as a membrane protein in the tumor microenvironment. NORAD and ICAM1 may be functionally related to tumor microenvironment and immune control in LSCC.

Genetics and RNA Regulation of Uveal Melanoma

Uveal melanoma (UM) is the most common intraocular malignant tumor and the most frequent melanoma not affecting the skin. While the rate of UM occurrence is relatively low, about 50% of patients develop metastasis, primarily to the liver, with lethal outcome despite medical treatment. Notwithstanding that UM etiopathogenesis is still under investigation, a set of known mutations and chromosomal aberrations are associated with its pathogenesis and have a relevant prognostic value. The most frequently mutated genes are BAP1, EIF1AX, GNA11, GNAQ, and SF3B1, with mutually exclusive mutations occurring in GNAQ and GNA11, and almost mutually exclusive ones in BAP1 and SF3B1, and BAP1 and EIF1AX. Among chromosomal aberrations, monosomy of chromosome 3 is the most frequent, followed by gain of chromosome 8q, and full or partial loss of chromosomes 1 and 6. In addition, epigenetic mechanisms regulated by non-coding RNAs (ncRNA), namely microRNAs and long non-coding RNAs, have also been investigated. Several papers investigating the role of ncRNAs in UM have reported that their dysregulated expression affects cancer-related processes in both in vitro and in vivo models. This review will summarize current findings about genetic mutations, chromosomal aberrations, and ncRNA dysregulation establishing UM biology.

Genetics and Genomics of Melanoma: Current Progress and Future Directions

Melanoma is a form of skin cancer that develops in the skin's pigment cells, known as melanocytes, and can spread via blood and the lymphatic system to nearby tissues or distant organs in the body [...].

Identification of a functional circRNA-miRNA-mRNA regulatory network in infantile hemangioma by bioinformatics analysis

Several circRNA have been reported to serve critical roles in various biological processes of human body. The present study aimed to build a circRNA-based competing endogenous RNA (ceRNA) network and explore the regulatory mechanisms of circRNA in infantile hemangiomas (IH). Differentially expressed circRNA, miRNA, and mRNA were downloaded from the gene expression synthesis (GEO) microarray database (GSE98795, GSE69136, and GSE127487). Cancer-specific circRNA database (CSCD), miRDB and Targetscan were employed to predict the targets of RNA. A total of 855 DEcircRNAs, 69 differentially expressed miRNAs (DEmiRNAs), and 3233 differentially expressed mRNAs (DEmRNAs) appeared as genes that were aberrantly expressed in IH. The circRNA-miRNA-mRNA network was constructed based on 108 circRNAs, 7 miRNAs, 274 mRNAs in IH. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated hypoxia-inducible factors (HIF)-1 signaling pathway and Notch signaling pathway were significantly enriched in IH with being constructed a ceRNA regulatory network. Furthermore, protein-protein interaction (PPI) network and Cytoscape showed the top 10 hub genes that regulate angiogenesis, namely FBXW7, CBLB, HECW2, FBXO32, FBXL7, KLHL5, EP300, MAPK1, MEF2C, and PLCG1. Our findings provide a deeper understanding the circRNA-related ceRNA regulatory mechanism in IH. This study further perfected the circRNA-miRNA-mRNA regulatory network related to IH and explored the potential function of mRNA in this network. It provides more understanding for the circRNA-related ceRNA regulation mechanism in the pathogenesis of IH.

Do Extracellular RNAs Provide Insight into Uveal Melanoma Biology?

Simple Summary

The study of RNAs in the extracellular environment in physiological and pathological conditions has become a growing field of research with intriguing applications in diagnostics and prognostics. Such extracellular RNAs are passively or actively released by all cells into biological fluids to spread biological signals to other cells. The perturbation of such RNA-based cell-to-cell communications in cancer can be easily identified by molecular analysis of liquid biopsies, even if source cells secreting RNAs are often elusive. In uveal melanoma (UM), extracellular RNAs can be assayed in serum, plasma, and vitreous and aqueous humor. In this review, we explore the possibility that extracellular RNA alterations in UM could partially match with RNA dysregulations observed in tumor tissues and provide information to better understand UM biology.

Abstract

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults, showing a high mortality due to metastasis. Although it is considered a rare disease, a growing number of papers have reported altered levels of RNAs (i.e., coding and non-coding RNAs) in cancerous tissues and biological fluids from UM patients. The presence of circulating RNAs, whose dysregulation is associated with UM, paved the way to the possibility of exploiting it for diagnostic and prognostic purposes. However, the biological meaning and the origin of such RNAs in blood and ocular fluids of UM patients remain unexplored. In this review, we report the state of the art of circulating RNAs in UM and debate whether the amount and types of RNAs measured in bodily fluids mirror the RNA alterations from source cancer cells. Based on literature data, extracellular RNAs in UM patients do not represent, with rare exceptions, a snapshot of RNA dysregulations occurring in cancerous tissues, but rather the complex and heterogeneous outcome of a systemic dysfunction, including immune system activity, that modifies the mechanisms of RNA delivery from several cell types.

LGFC-CNN: Prediction of lncRNA-Protein Interactions by Using Multiple Types of Features through Deep Learning

Long noncoding RNA (lncRNA) plays a crucial role in many critical biological processes and participates in complex human diseases through interaction with proteins. Considering that identifying lncRNA–protein interactions through experimental methods is expensive and time-consuming, we propose a novel method based on deep learning that combines raw sequence composition features, hand-designed features and structure features, called LGFC-CNN, to predict lncRNA–protein interactions. The two sequence preprocessing methods and CNN modules (GloCNN and LocCNN) are utilized to extract the raw sequence global and local features. Meanwhile, we select hand-designed features by comparing the predictive effect of different lncRNA and protein features combinations. Furthermore, we obtain the structure features and unifying the dimensions through Fourier transform. In the end, the four types of features are integrated to comprehensively predict the lncRNA–protein interactions. Compared with other state-of-the-art methods on three lncRNA–protein interaction datasets, LGFC-CNN achieves the best performance with an accuracy of 94.14%, on RPI21850; an accuracy of 92.94%, on RPI7317; and an accuracy of 98.19% on RPI1847. The results show that our LGFC-CNN can effectively predict the lncRNA–protein interactions by combining raw sequence composition features, hand-designed features and structure features.

The Role of LncRNAs in Uveal Melanoma

Uveal melanoma (UM) is an intraocular cancer tumor with high metastatic risk. It is considered a rare disease, but 90% of affected patients die within 15 years. Non-coding elements (ncRNAs) such as long non-coding RNAs (lncRNAs) have a crucial role in cellular homeostasis maintenance, taking part in many critical cellular pathways. Their deregulation, therefore, contributes to the induction of cancer and neurodegenerative and metabolic diseases. In cancer, lncRNAs are implicated in apoptosis evasion, proliferation, invasion, drug resistance, and other roles because they affect tumor suppressor genes and oncogenes. For these reasons, lncRNAs are promising targets in personalized medicine and can be used as biomarkers for diseases including UM.