Non-small cell lung cancer (NSCLC) is the most common form of cancer, resulting in cancer-related deaths worldwide. Exosomes, a subclass of extracellular vesicles, are produced and secreted from various types of cells, including cancer cells. Cancer-derived exosomes can deliver nucleic acids, proteins, and lipids to provide a favorable microenvironment that supports tumor growth through enhancing cell proliferation and metastasis. Our results showed that miR-224-5p was upregulated in NSCLC patient tissues and cell lines, with a tumor-promoting phenotype. Meanwhile, exosome-derived miR-224-5p induced cell proliferation and metastasis in NSCLC and human lung cells. Moreover, we characterized the androgen receptor (AR) as a direct target of miR-224-5p. Tumor xenograft assay experiments revealed that overexpression of miR-224-5p drove NSCLC tumor growth via the suppression of AR and the mediation of epithelial-mesenchymal transition (EMT). Collectively, our results suggest that miR-224-5p-enriched exosomes promote tumorigenesis by directly targeting AR in NSCLC, which may provide novel potential therapeutic and preventive targets for NSCLC.

These results indicate that enhanced proliferation and defective AICD of CD4+ T cells influence the T cell-mediated inflammatory reaction in childhood asthma and that increased IL-4, FLIPL and Bcl-2 expression and decreased Fas expression jointly participate in these changes in cell proliferation and apoptosis.ression and decreased Fas expression jointly participate in these changes in cell proliferation and apoptosis.

Nuclear factor κB (NF-κB) acts as a nuclear factor that is composed of five main subunits. It is a pluripotent and crucial dimer transcription factor that has a close relationship with many serious illnesses, especially its influences on cell proliferation, inflammation, and cancer initiation and progression. NF-κB acts as part of the signaling pathway and determines its effect on the expression of several other genes, such as epidermal growth factor receptor (EGFR), p53, signal transducer and activator of transcription 3 (STAT3), and non-coding RNA (ncRNA). Continuous activation of the NF-κB signaling pathway has been seen in many cancer types. While the NF-κB signaling pathway is tightly regulated in physiological settings, quite frequently it is constitutively activated in cancer, and the molecular biology mechanism underlying the deregulated activation of NF-κB signaling remains unclear. In this review, we discuss the regulatory role and possible clinical significance of ncRNA (microRNA [miRNA] and long non-coding RNA [lncRNA]) in NF-κB signaling in cancer, including in the conversion of inflammation to carcinogenesis. Non-coding RNA plays an essential and complex role in the NF-κB signaling pathway. NF-κB activation can also induce the ncRNA status. Targeting NF-κB signaling by ncRNA is becoming a promising strategy of drug development and cancer treatment.

Background Diabetic wounds are refractory and very difficult to heal. We aimed to use miRNA to identify novel and specific molecular markers for diabetes mellitus (DM) diagnosis and treatment. Methods The expression level of miR‐296‐5p was determined in tissue samples of 12 DM patients. The effect of miR‐296‐5p on proliferation of β‐cells was examined using Cell Counting Kit‐8 (CCK‐8) and colony formation assay. The effect of miR‐296‐5p on cell cycle progression was analysed using flow cytometry. The target gene was verified using luciferase reporter assay. A rat diabetes model was used to assess the effect of miR‐296‐5p in vivo. Results Overexpression of miR‐296‐5p suppressed cell proliferation, arrested cell cycle progression, and increased the healing rate of diabetic wounds both in vivo and in vitro. TargetScan analysis results showed that miR‐296‐5p is a direct regulator of SGLT2. Conclusions miR‐296‐5p can increase the healing rate of diabetic wounds and may be an effective molecular tool in DM diagnosis and therapy.

Background: Lung cancer is one of the most malignant cancers threatening human health. The miR-17-92 gene cluster is a highly conserved oncogene cluster encoding 6 miRNAs: miR-17, miR-18a, miR-19a, miR-19b-1, miR-20a and miR-92a. This study explored whether these miRNAs can be used as diagnostic markers for non-small-cell lung cancer (NSCLC). Methods: Serum samples were collected from healthy subjects (n = 23) and NSCLC patients at various stages (n = 74). Serum RNA was extracted by the TRIzol-glycogen method, and cDNA libraries were constructed by reverse transcription. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression levels of the 6 miRNAs. Results: The expression levels of the 6 miRNAs varied in different stages of NSCLC. Thus, 2 receiver operating characteristic (ROC) curves, that is, normal subjects and stage I-III patients and normal subjects and stage IV patients, of each miRNA were established to determine the interval of normal DCt values. The 2 areas under the curve (AUCs) of each miRNA were investigated (miR-17: 0.8097 and 1.000; miR-18a: 0.7388 and 0.9907; miR-19a/19b: 0.8451 and 0.5104; miR-20a: 0.8975 and 1.000; miR-92a: 0.8097 and 0.8342). In addition, a high positive correlation was discovered between miR-17 and miR-20a expression. Combining these 2 miRNAs can improve the screening effect of NSCLC. Conclusion: The miR-17-92 gene cluster can likely serve as a diagnostic marker in NSCLC.

tRNA-derived small RNAs (tRFs), a kind of noncoding RNAs, are generated from transfer RNAs. tRFs have some types according to their source and sizes.They play important roles in cell life and carcinogenesis. In this paper, we review the biogenesis and biological properties. We also focus on current progress of tRFs and some tsRNAs such as tRF-Leu-CAG, which have been studied or will be further investigated in tumorgenesis and diagnostic biomarkers in the clinic.

Diabetes mellitus (DM) is a growing health problem. As a common complication of DM, diabetic foot ulcer (DFU) results in delayed wound healing and is a leading cause of nontraumatic amputation. miR-199a-5p, a short noncoding RNA, had abnormal expression in DFU wound tissues. The expression of miR-199a-5p was significantly increased in DFU wound tissues, skin tissues of diabetic rats, and high glucose-induced cells. Vascular endothelial growth factor A (VEGFA) and Rho-associated kinase 1 (ROCK1) are directly targets of miR-199a-5p. Inhibiting the expression of miR-199a-5p alleviated the inhibition of VEGFA and ROCK1, thereby rescued impaired proliferation and migration of HG-induced cells, and restored the normal function of the cells to some extent. In diabetic rats, inhibition of miR-199a-5p significantly increased the expression of VEGFA and ROCK1, significantly promoted wound healing, and rescued impaired wound healing. miR-199a-5p and its targets showed therapeutic effect on diabetic wounds.

AbstractEmerging evidence suggests that PIWI-interacting RNAs (piRNAs) are one of the most influential small non-coding RNAs (ncRNAs) that regulate RNA silencing. piRNA and PIWI proteins have been confirmed for disease diagnosis and treatment as novel biomarkers due to its abnormal expression in various cancers. However, the current research is not strong enough to further clarify the functions of piRNA in cancer and its underlying mechanism. Therefore, how to provide large-scale and serious piRNA candidates for biological research has grown up to be a pressing issue. The main motivation of this work is tantamount to fill the gap in research on large-scale prediction of disease-related piRNAs. In this study, a novel computational model based on the structural perturbation method is proposed, called SPRDA. In detail, the duplex network is constructed based on the piRNA similarity network and disease similarity network extracted from piRNA sequence information, Gaussian interaction profile kernel similarity information and gene-disease association information. The structural perturbation method is then used to predict the potential associations on the duplex network, which is more predictive than other network structures in terms of structural consistency. In the five-fold cross-validation, SPRDA shows high performance on the benchmark dataset piRDisease, with an AUC of 0.9529. Furthermore, the predictive performance of SPRDA for 10 diseases shows the robustness of the proposed method. Overall, the proposed approach can provide unique insights into the pathogenesis of the disease and will advance the field of oncology diagnosis and treatment.