Reconstruction of lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveals functional lncRNAs in skin cutaneous melanoma

Long noncoding RNA MALAT1 in dermatologic disorders: a comprehensive review

Dermatologic disorders, affecting the integumentary system, involve diverse molecular mechanisms such as cell proliferation, apoptosis, inflammation and immune responses. Long noncoding RNAs, particularly Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1), are crucial regulators of gene expression. MALAT1 influences inflammatory responses, immune cell function and signaling pathways, impacting various physiological and pathological processes, including dermatologic disorders. Dysregulation of MALAT1 is observed in skin conditions like psoriasis, atopic dermatitis and systemic lupus erythematosus. However, its precise role remains unclear. This review consolidates knowledge on MALAT1's impact on skin biology and pathology, emphasizing its potential diagnostic and therapeutic implications in dermatologic conditions.

Non-coding RNAs as skin disease biomarkers, molecular signatures, and therapeutic targets

Non-coding RNAs (ncRNAs) are emerging as biomarkers, molecular signatures, and therapeutic tools and targets for diseases. In this review, we focus specifically on skin diseases to highlight how two classes of ncRNAs-microRNAs and long noncoding RNAs-are being used to diagnose medical conditions of unclear etiology, improve our ability to guide treatment response, and predict disease prognosis. Furthermore, we explore how ncRNAs are being used as both as drug targets and associated therapies have unique benefits, risks, and challenges to development, but offer a distinctive promise for improving patient care and outcomes.

The interaction of mast cells with membranes from lung cancer cells induces the release of extracellular vesicles with a unique miRNA signature

Mast cells (MCs) are immune cells that play roles in both normal and abnormal processes. They have been linked to tumor progression in several types of cancer, including non-small cell lung cancer (NSCLC). However, the exact role of MCs in NSCLC is still unclear. Some studies have shown that the presence of a large number of MCs is associated with poor prognosis, while others have suggested that MCs have protective effects. To better understand the role of MCs in NSCLC, we aimed to identify the initial mechanisms underlying the communication between MCs and lung cancer cells. Here, we recapitulated cell-to-cell contact by exposing MCs to membranes derived from lung cancer cells and confirming their activation, as evidenced by increased phosphorylation of the ERK and AKT kinases. Profiling of the microRNAs that were selectively enriched in the extracellular vesicles (EVs) released by the lung cancer-activated MCs revealed that they contained significantly increased amounts of miR-100-5p and miR-125b, two protumorigenic miRNAs. We explored the pathways regulated by these miRNAs via enrichment analysis using the KEGG database, demonstrating that these two miRNAs regulate p53 signaling, cancer pathways, and pathways associated with apoptosis and the cell cycle.

Unlocking the predictive potential of long non-coding RNAs: a machine learning approach for precise cancer patient prognosis

The intricate web of cancer biology is governed by the active participation of long non-coding RNAs (lncRNAs), playing crucial roles in cancer cells' proliferation, migration, and drug resistance. Pioneering research driven by machine learning algorithms has unveiled the profound ability of specific combinations of lncRNAs to predict the prognosis of cancer patients. These findings highlight the transformative potential of lncRNAs as powerful therapeutic targets and prognostic markers. In this comprehensive review, we meticulously examined the landscape of lncRNAs in predicting the prognosis of the top five cancers and other malignancies, aiming to provide a compelling reference for future research endeavours. Leveraging the power of machine learning techniques, we explored the predictive capabilities of diverse lncRNA combinations, revealing their unprecedented potential to accurately determine patient outcomes.

LINC00943 regulates miR-1252-5p/YWHAH axis to promote tumor proliferation and metastasis in lung adenocarcinoma

Lung cancer is the most common malignant tumor worldwide. In recent years, the incidence of lung adenocarcinoma (LAD) has increased significantly, with an unfavorable 5-year survival rate. Long non-coding RNAs (lncRNAs) have been shown to play a significant role in the emergence, growth, and metastasis of tumors. However, the functional role and mechanism of LINC00943 in LAD progression have not yet been investigated. Aberrant expressions of LINC00943, miR-1252-5p, and YWHAH were determined by RT-qPCR and Western blot analyses. The binding relationship between miR-1252-5p and LINC00943 or YWHAH was examined by Pearson's correlation analysis, RNA pull-down, and dual-luciferase reporter assays. MTT assay was conducted to measure cell viability and colony formation assay was performed to evaluate cell proliferation potential. Transwell assay was used to investigate cell migration and invasion and flow cytometry was applied to evaluate cell apoptosis. We found that LINC00943 was highly expressed in LAD tissue samples and cell lines and was a reliable biomarker with high sensitivity, and specificity (P < 0.0001; AUC: 0.8966) for LAD detection. LINC00943 was mainly localized in the cytoplasm. In vitro, LINC00943 promoted LAD cell proliferation, migration, and invasion; however, silencing LINC00943 inhibited LAD tumor metastasis. Mechanistically, LINC00943 was competitively bound with miR-1252-5p to enhance YWHAH expression. Moreover, LINC00943 silencing sponged miR-1252-5p to inhibit YWHAH, thereby retraining LAD cell malignant behaviors. In summary, LINC00943 facilitates LAD cell malignancy through sponging miR-1252-5p to upregulate YWHAH. LINC00943 is a novel lncRNA that serves as an oncogene and might be used as a prognostic biomarker for LAD.

Long non-coding RNAs and melanoma: From diagnosis to therapy

Although extremely rare, malignant melanoma is the deadliest type of skin malignancy with the inherent capability to invade other organs and metastasize to distant tissues. In 2021, it was estimated that approximately 106,110 patients may have received the diagnosis of melanoma, with a mortality rate of 7180. Surgery remains the common choice for treatment in patients with melanoma. Despite many advances in the treatment of melanoma, some patients, such as those who have received cytotoxic chemotherapeutic and immunotherapic agents, a significant number of patients may show inadequate treatment response following initiating these treatments. Non-coding RNAs, including lncRNAs, have become recently popular and attracted the attention of many researchers to make new insights into the pathogenesis of many diseases, particularly malignancies. LncRNAs have been thoroughly investigated in multiple cancers such as melanoma and have been shown to play a major role in regulating various physiological and pathological cellular processes. Considering their core regulatory function, these non-coding RNAs may be appropriate candidates for melanoma patients' diagnosis, prognosis, and treatment. In this review, we will cover all the current literature available for lncRNAs in melanoma and will discuss their potential benefits as diagnostic and/or prognostic markers or potent therapeutic targets in the treatment of melanoma patients.

Graphene oxide accelerates diabetic wound repair by inhibiting apoptosis of Ad-MSCs via Linc00324/miR-7977/STK4 pathway

Many studies have shown that graphene oxide (GO) promotes proliferation and differentiation of a variety of stem cells. However, its effect on adipose-derived mesenchymal stem cell (Ad-MSCs) apoptosis is still unclear. Apoptosis is a significant factor affecting stem cell-based treatment of diabetic wounds. Therefore, we explored the effect of GO on Ad-MSC apoptosis and diabetic wound healing. In this study, qRT-PCR was used to detect Ad-MSC expression of LncRNAs, miRNAs, and mRNAs under high-glucose environment. RNA immunoprecipitation (RIP), RNA pull-down, and luciferase assays were used to detect interactions of specific lncRNAs, miRNAs, and mRNAs. The effects of GO on Ad-MSC apoptosis were explored by flow cytometry, TUNEL assay, and Western blot. A diabetic wound model was used to explore the function of Linc00324 on Ad-MSC reparative properties in vivo. As a result, GO inhibited high glucose-induced apoptosis in Ad-MSCs, and Linc00324 contributed to the anti-apoptotic effect of GO. RIP and RNA pull-down confirmed that Linc00324 directly interacted with miR-7977, functioning as a miRNA sponge to regulate expression of the miR-7977 target gene STK4 (MST1) and downstream signaling pathways. In addition, GO reduced the apoptosis of Ad-MSCs in wounds and promoted wound healing. Taken together, these findings suggest GO may be a superior auxiliary material for Ad-MSCs to facilitate diabetic wound healing via the Linc00324/miR-7977/STK4 pathway.

Integration of lncRNAs, Protein-Coding Genes and Pathology Images for Detecting Metastatic Melanoma

Melanoma is a lethal skin disease that develops from moles. This study aimed to integrate multimodal data to predict metastatic melanoma, which is highly aggressive and difficult to treat. The proposed EnsembleSKCM method evaluated the prediction performances of long noncoding RNAs (lncRNAs), protein-coding messenger genes (mRNAs) and pathology images (images) for metastatic melanoma. Feature selection was used to screen for metastatic biomarkers in the lncRNA and mRNA datasets. The integrated EnsembleSKCM model was built based on the weighted results of the lncRNA-, mRNA- and image-based models. EnsembleSKCM achieved 0.9444 in the prediction accuracy of metastatic melanoma and outperformed the single-modal prediction models based on the lncRNA, mRNA and image data. The experimental data suggest the importance of integrating the complementary information from the three data modalities. WGCNA was used to analyze the relationship of molecular-level features and image features, and the results show connections between them. Another cohort was used to validate our prediction.

Hsa-let-7c-5p, hsa-miR-130b-3p, and hsa-miR-142-3p as Novel miRNA Biomarkers for Melanoma Progression

This study aimed to screen miRNA biomarkers for melanoma progression. Raw melanoma data were downloaded from the Gene Expression Omnibus (GSE34460, GSE35579, GSE18509, and GSE24996) and the Cancer Genome Atlas (TCGA). Then, all differentially expressed miRNAs (DEmiRNAs) between benign vs. primary, metastatic vs. benign, and metastatic vs. primary groups were obtained in the GSE34460 and GSE35579 datasets, and the miRNAs related to disease progression were further screened. Then, the miRNA-gene network was constructed, followed by enrichment, survival, and cluster analyses. Differentially expressed genes (DEGs), tumor-infiltrating immune cells, and tumor mutation burden (TMB) between subtypes were analyzed. miRNAs were verified in the GSE18509 and GSE24996 datasets. A total of 132 and 209 DEmiRNAs were obtained in the GSE34460 and GSE35579 datasets, respectively, and 27 DEmiRNAs related to disease progression were screened. hsa-miR-106b-5p, hsa-miR-27b-3p, and hsa-miR-141-3p had a higher degree and were regulated by numerous genes in the miRNA-gene network. Moreover, four miRNAs were associated with prognosis: hsa-let-7c-5p, hsa-miR-130b-3p, hsa-miR-142-3p, and hsa-miR-509-3p. Furthermore, the bidirectional hierarchical clustering of 27 miRNAs was classified into three subtypes, and TMB and four types of immune cells, including activated dendritic cells, naïve CD4 T cells, M1 macrophages, and plasma cells, showed significant differences among the three subtypes. The expression levels of most miRNAs in the GSE18509 and GSE24996 datasets were consistent with those in the training dataset. These miRNAs, including hsa-let-7c-5p, hsa-miR-130b-3p, and hsa-miR-142-3p, and activated dendritic cells, naïve CD4 T cells, M1 macrophages, and plasma cells may play vital roles in the pathogenesis of melanoma.

LncRNA HCG18 facilitates melanoma progression by modulating miR-324-5p/CDK16 axis

OBJECTIVE

LncRNA HCG18 has been reported to act as a tumor promoter in gastric cancer, hepatocellular carcinoma and nasopharyngeal carcinoma. However, the role of HCG18 in melanoma is still not clear. In this study, we detected the expression and molecular function of HCG18 in melanoma.

METHODS

The expression of HCG18 in melanoma cell lines and 50 pairs of melanoma and corresponding non-cancer tissues was detected by RT-qPCR. The relationship between HCG18 and clinicopathology was analyzed. We used HCG18 overexpressing melanoma cell lines A375 and M14, and si-HCG18 to knock down HCG18 expression. CCK-8, clone formation, Transwell assay and FCM were used to explore the effect of HCG18 knockdown on cell proliferation, migration, invasion and apoptosis in melanoma cells. Bioinformatics software was used to predict the downstream miRNA regulated by HCG18, and the downstream target genes regulated by miR-324-5p. Dual-luciferase reporter assay and RNA pull-down assay were used to verify whether miR-324-5p was related to the predicted sequence of HCG18.

RESULTS

HCG18 was highly expressed in melanoma tissues and cells. Besides, we found that HCG18 was closely correlated with thickness, TNM stage and metastasis. Functional experiments discovered that HCG18 knockdown restrained cell proliferation, migration and invasion, while promoted cell apoptosis in melanoma cells. HCG18 was confirmed to be a sponge of miR-324-5p, and CDK16 might be a downstream gene of miR-324-5p. HCG18 was found to reverse the effect of miR-324-5p by upregulating CDK16 expression in melanoma cell proliferation, apoptosis, migration and invasion in vitro.

CONCLUSION

This study indicated that HCG18 played an essential role in the pathogenesis of melanoma and suggested that HCG18 might be a potential target for the treatment and diagnosis of melanoma.

The Functional Role of Long Non-Coding RNAs in Melanoma

Melanoma is the most lethal skin cancer, with increasing incidence worldwide. The molecular events that drive melanoma development and progression have been extensively studied, resulting in significant improvements in diagnostics and therapeutic approaches. However, a high drug resistance to targeted therapies and adverse effects of immunotherapies are still a major challenge in melanoma treatment. Therefore, the elucidation of molecular mechanisms of melanomagenesis and cancer response to treatment is of great importance. Recently, many studies have revealed the close association of long noncoding RNAs (lncRNAs) with the development of many cancers, including melanoma. These RNA molecules are able to regulate a plethora of crucial cellular processes including proliferation, differentiation, migration, invasion and apoptosis through diverse mechanisms, and even slight dysregulation of their expression may lead to tumorigenesis. lncRNAs are able to bind to protein complexes, DNA and RNAs, affecting their stability, activity, and localization. They can also regulate gene expression in the nucleus. Several functions of lncRNAs are context-dependent. This review summarizes current knowledge regarding the involvement of lncRNAs in melanoma. Their possible role as prognostic markers of melanoma response to treatment and in resistance to therapy is also discussed.

Gene Instability-Related lncRNA Prognostic Model of Melanoma Patients via Machine Learning Strategy

Background

Melanoma is a common tumor characterized by a high mortality rate in its late stage. After metastasis, current treatment methods are relatively ineffective. Many studies have shown that long noncoding RNA (lncRNA) may participate in gene mutation and genomic instability in cancer.

Methods

We downloaded transcriptome data, mutation data, and clinical follow-up data of melanoma patients from The Cancer Genome Atlas. We divided samples into groups according to the number of somatic cell mutations and then performed a differential analysis to screen out the differentially expressed genes. We then divided samples into genomic unstable and genomic stable groups. We compared lncRNA expression profiles in these groups and constructed a protein-coding genes network coexpressed with selected lncRNA to analyze the pathways enriched by these genes. Two machine learning methods, least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to conduct the lncRNA-related prognostic model. Afterward, we performed survival analysis, risk correlation analysis, independent prognostic analysis, and clinical subgroup model validation. Finally, through wound healing assay and transwell assay, the function of AATBC was verified by A375 cell lines.

Results

We screened 61 prognostic-related lncRNAs and constructed an lncRNA-mRNA coexpression network based on these lncRNAs. Seven lncRNAs were selected as common characteristic factors based on the two machine learning methods. The model formula was as follows: risk score = 0.085∗AATBC + 0.190∗ AC026689.1−0.117∗AC083799.1 + 0.036∗ AC091544.6−0.039∗ LINC01287−0.291∗ SPRY4.AS1 + 0.056∗ ZNF667.AS1. The seven lncRNAs in this formula are key candidates. Cell experiments have verified that knocking down AATBC in A375 cell lines can reduce the proliferation and invasion ability of melanoma cells.

Conclusion

The lncRNA we identified provides a new way to study lncRNA's role in the genomic instability of melanoma. Our findings may provide essential candidate biomarkers for the diagnosis and treatment of melanoma.

LINC00943 knockdown exerts neuroprotective effects in Parkinson's disease through regulates CXCL12 expression by sponging miR-7-5p

BACKGROUND

Parkinson's disease (PD) is a common neurodegenerative movement disorder, but the pathogenesis is still unclear. Long non-coding RNAs (lncRNAs) have been reported to play a prominent role in PD.

OBJECTIVE

This study is designed to explore the role and mechanism of long intergenic non-coding RNA 00943 (LINC00943) in the N-methyl-4-phenylpyridine (MPP⁺)-inducted PD model.

METHODS

LINC00943, microRNA-7-5p (miR-7-5p), and the chemokine (C-X-C motif) ligand 12 (CXCL12, also referred to as SDF-1) level were examined by real-time quantitative polymerase chain reaction (RT-qPCR). Cell viability and apoptosis were analyzed by 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2-H-tetrazolium bromide (MTT), and flow cytometry assays, severally. Protein levels of interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and CXCL12 were assessed by western blot assay. The ROS generation and SOD activity were detected by the corresponding kits. The binding relationship between miR-7-5p and LINC00943 or CXCL12 was predicted by Starbase and then verified by a dual-luciferase reporter and RNA Immunoprecipitation (RIP) assays.

RESULTS

LINC00943 and CXCL12 were increased, and miR-7-5p was decreased in MPP⁺-inducted SK-N-SH cells. LINC00943 silencing promoted cell viability, and repressed apoptosis and the inflammatory response in MPP⁺-treated SK-N-SH cells. The mechanical analysis discovered that LINC00943 acted as a sponge of miR-7-5p to regulate CXCL12 expression.

CONCLUSIONS

LINC00943 knockdown could attenuate MPP⁺-triggered neuron injury by regulating the miR-7-5p/CXCL12 axis, hinting at a promising therapeutic target for PD treatment.

Comprehensive Review on the Clinical Relevance of Long Non-Coding RNAs in Cutaneous Melanoma

Cutaneous melanoma is considered a rare tumor, although it is one of the most common cancers in young adults and its incidence has risen in the last decades. Targeted therapy, with BRAF and MEK inhibitors, and immunotherapy revolutionized the treatment of metastatic melanoma but there is still a considerable percentage of patients with primary or acquired resistance to these therapies. Recently, oncology researchers directed their attention at the role of long non-coding RNAs (lncRNAs) in different types of cancers, including melanoma. lncRNAs are RNA transcripts, initially considered "junk sequences", that have been proven to have a crucial role in the fine regulation of physiological and pathological processes of different tissues. Furthermore, they are more expressed in tumors than protein-coding genes, constituting perfect candidates either as biomarkers (diagnostic, prognostic, predictive) or as therapeutic targets. In this work, we reviewed all the literature available for lncRNA in melanoma, elucidating all the potential roles in this tumor.