A comprehensive evaluation of skin aging-related circular RNA expression profiles

The transcription factor TCF4 regulates the miR-494-3p/THBS1 axis in the fibrosis of pathologic scars

BACKGROUND

The fibrosis of pathologic scar (PS) is formed by the excessive deposition of extracellular matrix, resulting in an abnormal scar. Recent clinical tests have indicated that the regulation of PS fibroblast cells (PSF cells) proliferation can serve as an intervention measure for PS. Our work aimed to elucidate the specific mechanism of action of TCF4 on the progression of PS fibrosis.

METHODS

Our study used qRT-PCR and Western blot to search for the expression of key proteins in PS clinical samples and cells. Transwell, CCK-8, and wound scratch assays were employed to analyze the proliferation and migration of PSF cells. CHIP, dual-luciferase reporter experiments, and bio-informatics analysis were used to analyze the interactions between molecules.

RESULTS

The analysis of PS clinical samples confirmed a positive correlation between TCF4 and miR-494-3p. This regulatory mechanism was related to the progression of PS. We verified that the overexpression of miR-494-3p or the knockdown of THBS1 both suppressed the proliferation and migration of PSF cells. Furthermore, we also confirmed the binding relationships between TCF4, miR-494-3p, and THBS1. Simultaneously, we verified the existence of the TCF4/miR-494-3p/THBS1 regulatory network in PS. This regulatory process affects the development of PS fibrosis.

CONCLUSION

Our study results indicate that TCF4, miR-494-3p, and THBS1 are abnormally expressed in PS. TCF4 increases the proliferation and migration ability of PSF cells through the miR-494-3p/THBS1 signaling pathway, which promotes the fibrosis of PS.

Circular RNAs as multifaceted molecular regulators of vital activity and potential biomarkers of aging

Aging presents a significant challenge to health and social care systems due to the increasing proportion of the elderly population. The identification of reliable biomarkers to assess the progression of aging remains an unresolved question. Circular RNAs (circRNAs) are single-stranded covalently closed RNAs. They have been found to regulate various biological processes. CircRNAs are present in human biological fluids, are relatively stable, and accumulate with age, making them promising as biomarkers of aging. Current information on the expression of circRNAs in aging was analyzed using scientific databases. In this review, we have identified key stages in the study of circRNAs during aging and summarized the current understanding of their biogenesis. By focusing on the role of circRNAs in processes that contribute to aging - such as genomic stability, metabolism, cell death, and signaling pathways - we hypothesize that circRNAs may drive the aging process through their age-related accumulation and resultant deregulation. Examples of age-related differential expression of circRNAs in various species, including humans, are provided. This review highlights the importance of finding novel epigenetic biomarkers of aging, beyond the already identified molecules (circFOXO3, circRNA100783, circPVT1), and highlights circRNAs as a potential therapeutic target for the treatment of age-associated diseases.

Recent advances in exosomal non-coding RNA-based therapeutic approaches for photoaging

BACKGROUND

Photoaging is a degenerative biological process that affects the quality of life. It is caused by environmental factors including ultraviolet radiation (UVR), deep skin burns, smoking, active oxygen, chemical substances, and trauma. Among them, UVR plays a vital role in the aging process.

AIM

With the continuous development of modern medicine, clinical researchers have investigated novel approaches to treat aging. In particular, mesenchymal stem cells (MSCs), non-coding RNAs are involved in various physiological processes have broad clinical application as they have the advantages of convenient samples, abundant sources, and avoidable ethical issues.

METHODS

This article reviews research progress on five types of stem cell, exosomes, non-coding RNA in the context of photoaging treatment: adipose-derived stem cell, human umbilical cord MSCs, epidermal progenitor cells, keratinocyte stem cells, and hair follicle stem cells (HFSCs). It also includes stem cell related exosomes and their non-coding RNA research.

RESULTS

The results have clinical guiding significance for prevention and control of the onset and development of photoaging. It is found that stem cells secrete cytokines, cell growth factors, non-coding RNA, exosomes and proteins to repair aging skin tissues and achieve skin rejuvenation. In particular, stem cell exosomes and non-coding RNA are found to have significant research potential, as they possess the benefits of their source cells without the disadvantages which include immune rejection and granuloma formation.

Identification of lncRNA-miRNA-mRNA Regulatory Network and Therapeutic Agents for Skin Aging by Bioinformatics Analysis

Skin aging is the most intuitive manifestation of aging. Skin aging inevitably leads to cosmetic and psychological problems, and even diseases. The present study aims to research the pathological and molecular mechanisms underlying skin aging and identify the therapeutic agents for reversing skin aging. Two available gene expression datasets (GSE55118 and GSE72264) for skin aging were downloaded from Gene Expression Omnibus, followed by bioinformatic analyses performed on the datasets. Firstly, 169 crucial mRNAs, 27 crucial miRNAs and 50 crucial lncRNAs closely related to skin aging were identified by weighted gene co-expression network analysis. Then, function Enrichment Analysis performed by Metascape database showed that skin aging involves a variety of biological functions, such as detection of stimulus, response to steroid hormone and water channel activity, regulation of muscle contraction. Next, ten hub genes including AQP4, TRPM8, TBR1, NTSR2, MPPED1, BARHL2, PAX9, CPN1, CES3, and CHGB were screened out by the protein-protein interaction analysis. Next, the "lncRNA-miRNA-mRNA" network and the "lncRNA-miRNA-hub mRNA" network were constructed to explore the competing endogenous RNAs mechanism of skin aging. Finally, ten significant potential small molecules mitigating skin aging were screened using CMAP platform, including tretinoin, pifithrin, selamectin, entinostat, bretazenil, syringic-acid, BRD-K96475865, emedastine, abacavir, and rotenone, and their reliability was verified by molecular docking experiments. The present study provided basis for revealing the molecular mechanism of skin aging and identified the potential candidate drugs for mitigating skin aging.

Forensic age estimation from human blood using age-related microRNAs and circular RNAs markers

Aging is a complicated process characterized by progressive and extensive changes in physiological homeostasis at the organismal, tissue, and cellular levels. In modern society, age estimation is essential in a large variety of legal rights and duties. Accumulating evidence suggests roles for microRNAs (miRNAs) and circular RNAs (circRNAs) in regulating numerous processes during aging. Here, we performed circRNA sequencing in two age groups and analyzed microarray data of 171 healthy subjects (17-104 years old) downloaded from Gene Expression Omnibus (GEO) and ArrayExpress databases with integrated bioinformatics methods. A total of 1,403 circular RNAs were differentially expressed between young and old groups, and 141 circular RNAs were expressed exclusively in elderly samples while 10 circular RNAs were expressed only in young subjects. Based on their expression pattern in these two groups, the circular RNAs were categorized into three classes: age-related expression between young and old, age-limited expression-young only, and age-limited expression-old only. Top five expressed circular RNAs among three classes and a total of 18 differentially expressed microRNAs screened from online databases were selected to validate using RT-qPCR tests. An independent set of 200 blood samples (20-80 years old) was used to develop age prediction models based on 15 age-related noncoding RNAs (11 microRNAs and 4 circular RNAs). Different machine learning algorithms for age prediction were applied, including regression tree, bagging, support vector regression (SVR), random forest regression (RFR), and XGBoost. Among them, random forest regression model performed best in both training set (mean absolute error = 3.68 years, r = 0.96) and testing set (MAE = 6.840 years, r = 0.77). Models using one single type of predictors, circular RNAs-only or microRNAs-only, result in bigger errors. Smaller prediction errors were shown in males than females when constructing models according to different-sex separately. Putative microRNA targets (430 genes) were enriched in the cellular senescence pathway and cell homeostasis and cell differentiation regulation, indirectly indicating that the microRNAs screened in our study were correlated with development and aging. This study demonstrates that the noncoding RNA aging clock has potential in predicting chronological age and will be an available biological marker in routine forensic investigation to predict the age of biological samples.

Research Techniques Made Simple: Studying Circular RNA in Skin Diseases

Circular RNAs (circRNAs) are a unique class of covalently closed, single-stranded RNAs. High-throughput sequencing has uncovered the abundance and complexity of circRNAs. Changes in levels of circRNAs correlate with diverse disease states, including many skin diseases. CircRNAs can function as microRNA inhibitors, protein interactors, or mRNAs. Although circRNAs do have unique topological features, they share many similarities, including primary sequence, with their linear orthologs, so carefully controlled experiments are required to detect and study them. Here, we summarize some protocols used in the identification, validation, and characterization of circRNAs. We also discuss ways to repress and overexpress specific circRNAs to assess potential unique functions for these molecules. These techniques may be useful in exploring how circRNAs contribute to skin disease.