Role of the long non-coding RNA LINC00052 in tumors

Accurate Identification of Spatial Domain by Incorporating Global Spatial Proximity and Local Expression Proximity

Accurate identification of spatial domains is essential in the analysis of spatial transcriptomics data in order to elucidate tissue microenvironments and biological functions. However, existing methods only perform domain segmentation based on local or global spatial relationships between spots, resulting in an underutilization of spatial information. To this end, we propose SECE, a deep learning-based method that captures both local and global relationships among spots and aggregates their information using expression similarity and spatial similarity. We benchmarked SECE against eight state-of-the-art methods on six real spatial transcriptomics datasets spanning four different platforms. SECE consistently outperformed other methods in spatial domain identification accuracy. Moreover, SECE produced spatial embeddings that exhibited clearer patterns in low-dimensional visualizations and facilitated a more accurate trajectory inference.

Comparative Transcriptome Profiles of Human HaCaT Cells in Response to Gynostemma pentaphyllum Extracts Obtained Using Three Independent Methods by RNA Sequencing

Gynostemma pentaphyllum (GP) is widely used in herbal medicine. In this study, we developed a method for the large-scale production of GP cells using plant tissue culture techniques combined with bioreactors. Six metabolites (uridine, adenosine, guanosine, tyrosine, phenylalanine, and tryptophan) were identified in GP extracts. Transcriptome analyses of HaCaT cells treated with GP extracts using three independent methods were conducted. Most differentially expressed genes (DEGs) from the GP-all condition (combination of three GP extracts) showed similar gene expression on treatment with the three individual GP extracts. The most significantly upregulated gene was LTBP1. Additionally, 125 and 51 genes were upregulated and downregulated, respectively, in response to the GP extracts. The upregulated genes were associated with the response to growth factors and heart development. Some of these genes encode components of elastic fibers and the extracellular matrix and are associated with many cancers. Genes related to folate biosynthesis and vitamin D metabolism were also upregulated. In contrast, many downregulated genes were associated with cell adhesion. Moreover, many DEGs were targeted to the synaptic and neuronal projections. Our study has revealed the functional mechanisms of GP extracts' anti-aging and photoprotective effects on the skin using RNA sequencing.

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Head and neck squamous cell carcinoma (HNSCC) is characterized by an immunosuppression environment and necessitates the development of new immunotherapy response predictors. The study aimed to build a prognosis-related competing endogenous RNA (ceRNA) network based on immune-related genes (IRGs) and analyze its immunological signatures. Differentially expressed IRGs were identified by bioinformatics analysis with Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ImmPort databases. Finally, via upstream prognosis-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) prediction and co-expression analysis, we built an immune-related ceRNA network (LINC00052/hsa-miR-148a-3p/PLAU) related to HNSCC patient prognosis. CIBERSORT analysis demonstrated that there were substantial differences in 11 infiltrating immune cells in HNSCC, and PLAU was closely correlated with 10 type cells, including T cells CD8+ (R =  - 0.329), T cells follicular helper (R = - 0.342) and macrophage M0 (R = 0.278). Methylation and Tumor Immune Dysfunction and Exclusion (TIDE) analyses revealed that PLAU upregulation was most likely caused by hypomethylation and that high PLAU expression may be associated with tumor immune evasion in HNSCC, respectively.

Hsa_circ_NOTCH3 regulates ZNF146 through sponge adsorption of miR-875-5p to promote tumorigenesis of hepatocellular carcinoma

Background

To explore the specific mechanism of circular RNA (circRNA) in the occurrence and development of hepatocellular carcinoma (HCC), and provide new ideas for its diagnosis and treatment.

Methods

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was for evaluating the expression of circ_NOTCH3 in liver cancer tissues and matched normal tissues and related cell lines. After overexpression or co-expression of circ_NOTCH3 or microRNA (miRNA) in cells, the changes in cell function were analyzed. Bioinformatics analysis and dual luciferase report analysis were utilized to predict and verify the binding site between circ_NOTCH3 and miRNA. Western blotting was applied to detect gene expression alterations. Additionally, in vivo tumor growth was also utilized to further assess the influence of knocking-down circ_NOTCH3 on the progression of HCC.

Results

It was confirmed circ_NOTCH3 was highly expressed in HCC specimens and cells. The proliferation, migration, invasion, and oxaliplatin-resistance potential of HCC could be restrained by silencing circ_NOTCH3 or by ectopic expression of miR-875-5p in vitro. In terms of mechanism, circ_NOTCH3 directly binds to miR-875-5p, regulating its activity by targeting the 3'-UTR of ZNF146. Overexpression of circ_NOTCH3 evidently overturned the diminishing influence of miR-875-5p mimics on HCC cells.

Conclusions

As an oncogene, circ_NOTCH3 can trigger the proliferation, invasion, migration, and oxaliplatin resistance of HCC cells through the miR-875-5p/ZNF146 axis, and may be a promising target for the treatment of HCC.