Silencing the expression of lncRNA SNHG15 may be a novel therapeutic approach in human breast cancer through regulating miR-345-5p

Tumor-targeted delivery of SNHG15 siRNA using a ZIF-8 nanoplatform: Towards a more effective prostate cancer therapy

Small interfering RNAs (siRNAs) can be used as a powerful tool in gene therapy to downregulate the expression of specific disease related genes. Some properties however, such as instability, and low penetration into cells can limit their efficacy, and thus reduce their therapeutic potential. Metal-organic frameworks (MOFs) such as zeolitic imidazolate framework-8 (ZIF-8), which consist of organic bridging ligands and metal cations (Zn), have a very high binding affinity with nucleic acids including siRNAs. In this study, we designed a PEGylated ZIF-8 platform that was equipped with epithelial cell adhesion molecule (EpCAM) aptamer for the targeted delivery of siRNA molecules, in order to knockdown SNHG15 in both a prostate cancer (PC) cell line, and a human PC xenograft mouse model. SNHG15 is a long noncoding RNA, with oncogenic roles in different cancers including PC. The results indicated that the depletion of SNHG15 by Apt-PEG-siRNA@ZIF-8 nanoplatfrom inhibited cell proliferation and colony formation, and increased apoptosis in PC cells. This nanoparticle facilitated the release of siRNAs into the tumor environment in vivo, and subsequently reduced the tumor growth, with no side effects observed in vital organs. We have therefore developed a novel siRNA nano-delivery system for targeted prostate cancer treatment; however further studies are required before it can be tested in clinical trials.

Predicting lncRNA-disease associations based on heterogeneous graph convolutional generative adversarial network

There is a growing body of evidence indicating the crucial roles that long non-coding RNAs (lncRNAs) play in the development and progression of various diseases, including cancers, cardiovascular diseases, and neurological disorders. However, accurately predicting potential lncRNA-disease associations remains a challenge, as existing methods have limitations in extracting heterogeneous association information and handling sparse and unbalanced data. To address these issues, we propose a novel computational method, called HGC-GAN, which combines heterogeneous graph convolutional neural networks (GCN) and generative adversarial networks (GAN) to predict potential lncRNA-disease associations. Specifically, we construct a lncRNA-miRNA-disease heterogeneous network by integrating multiple association data and sequence information. The GCN-based generator is then employed to aggregate neighbor information of nodes and obtain node embeddings, which are used to predict lncRNA-disease associations. Meanwhile, the GAN-based discriminator is trained to distinguish between real and fake lncRNA-disease associations generated by the generator, enabling the generator to improve its ability to generate accurate lncRNA-disease associations gradually. Our experimental results demonstrate that HGC-GAN performs better in predicting potential lncRNA-disease associations, with AUC and AUPR values of 0.9591 and 0.9606, respectively, under 10-fold cross-validation. Moreover, our case study further confirms the effectiveness of HGC-GAN in predicting potential lncRNA-disease associations, even for novel lncRNAs without any known lncRNA-disease associations. Overall, our proposed method HGC-GAN provides a promising approach to predict potential lncRNA-disease associations and may have important implications for disease diagnosis, treatment, and drug development.

SnoRNA and lncSNHG: Advances of nucleolar small RNA host gene transcripts in anti-tumor immunity

The small nucleolar RNA host genes (SNHGs) are a group of genes that can be transcript into long non-coding RNA SNHG (lncSNHG) and further processed into small nucleolar RNAs (snoRNAs). Although lncSNHGs and snoRNAs are well established to play pivotal roles in tumorigenesis, how lncSNHGs and snoRNAs regulate the immune cell behavior and function to mediate anti-tumor immunity remains further illustrated. Certain immune cell types carry out distinct roles to participate in each step of tumorigenesis. It is particularly important to understand how lncSNHGs and snoRNAs regulate the immune cell function to manipulate anti-tumor immunity. Here, we discuss the expression, mechanism of action, and potential clinical relevance of lncSNHGs and snoRNAs in regulating different types of immune cells that are closely related to anti-tumor immunity. By uncovering the changes and roles of lncSNHGs and snoRNAs in different immune cells, we aim to provide a better understanding of how the transcripts of SNHGs participate in tumorigenesis from an immune perspective.