An angiogenesis-associated gene-based signature predicting prognosis and immunotherapy efficacy of head and neck squamous cell carcinoma patients.

OBJECTIVES: To develop a model that can assist in the diagnosis and prediction of prognosis for head and neck squamous cell carcinoma (HNSCC). MATERIALS AND METHODS: Data from TCGA and GEO databases were used to generate normalized gene expression data. Consensus Cluster Plus was used for cluster analysis and the relationship between angiogenesis-associated gene (AAG) expression patterns, clinical characteristics and survival was examined. Support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) analyzes and multiple logistic regression analyzes were performed to determine the diagnostic model, and a prognostic nomogram was constructed using univariate and multivariate Cox regression analyses. ESTIMATE, XCELL, TIMER, QUANTISEQ, MCPCOUNTER, EPIC, CIBERSORT-ABS, CIBERSORT algorithms were used to assess the immune microenvironment of HNSCC patients. In addition, gene set enrichment analysis, treatment sensitivity analysis, and AAGs mutation studies were performed. Finally, we also performed immunohistochemistry (IHC) staining in the tissue samples. RESULTS: We classified HNSCC patients into subtypes based on differences in AAG expression from TCGA and GEO databases. There are differences in clinical features, TME, and immune-related gene expression between two subgroups. We constructed a HNSCC diagnostic model based on nine AAGs, which has good sensitivity and specificity. After further screening, we constructed a prognostic risk signature for HNSCC based on six AAGs. The constructed risk score had a good independent prognostic significance, and it was further constructed into a prognostic nomogram together with age and stage. Different prognostic risk groups have differences in immune microenvironment, drug sensitivity, gene enrichment and gene mutation. CONCLUSION: We have constructed a diagnostic and prognostic model for HNSCC based on AAG, which has good performance. The constructed prognostic risk score is closely related to tumor immune microenvironment and immunotherapy response.

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis.

BACKGROUND: Although periodontitis has previously been reported to be linked with multiple sclerosis (MS), but the molecular mechanisms and pathological interactions between the two remain unclear. This study aims to explore potential crosstalk genes and pathways between periodontitis and MS. METHODS: Periodontitis and MS data were obtained from the Gene Expression Omnibus (GEO) database. Shared genes were identified by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Then, enrichment analysis for the shared genes was carried out by multiple methods. The least absolute shrinkage and selection operator (LASSO) regression was used to obtain potential shared diagnostic genes. Furthermore, the expression profile of 28 immune cells in periodontitis and MS was examined using single-sample GSEA (ssGSEA). Finally, real-time quantitative fluorescent PCR (qRT-PCR) and immune histochemical staining were employed to validate Hub gene expressions in periodontitis and MS samples. RESULTS: FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ genes were the shared genes between periodontitis, and MS. GO analysis revealed that the shared genes exhibited the greatest enrichment in response to molecules of bacterial origin. LASSO analysis indicated that CFI, DDIT4L, and FAM46C were the most effective shared diagnostic biomarkers for periodontitis and MS, which were further validated by qPCR and immunohistochemical staining. ssGSEA analysis revealed that T and B cells significantly influence the development of MS and periodontitis. CONCLUSIONS: FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ were the most important crosstalk genes between periodontitis, and MS. Further studies found that CFI, DDIT4L, and FAM46C were potential biomarkers in periodontitis and MS.

Decoding the role of aberrant RNA alternative splicing in hepatocellular carcinoma: a comprehensive review.

During eukaryotic gene expression, alternative splicing of messenger RNA precursors is critical in increasing protein diversity and regulatory complexity. Multiple transcript isoforms could be produced by alternative splicing from a single gene; they could eventually be translated into protein isoforms with deleted, added, or altered domains or produce transcripts containing premature termination codons that could be targeted by nonsense-mediated mRNA decay. Alternative splicing can generate proteins with similar, different, or even opposite functions. Increasingly strong evidence indicates that abnormal RNA splicing is a prevalent and crucial occurrence in cellular differentiation, tissue advancement, and the development and progression of cancer. Aberrant alternative splicing could affect cancer cell activities such as growth, apoptosis, invasiveness, drug resistance, angiogenesis, and metabolism. This systematic review provides a comprehensive overview of the impact of abnormal RNA alternative splicing on the development and progression of hepatocellular carcinoma.

Decoding the role of long non-coding RNAs in periodontitis: A comprehensive review.

Periodontitis is an inflammatory disease characterized by the pathological loss of alveolar bone and the adjacent periodontal ligament. It is considered a disease that imposes a substantial health burden, with an incidence rate of 20-50%. The etiology of periodontitis is multifactorial, with genetic factors accounting for approximately half of severe cases. Studies have revealed that long non-coding RNAs (lncRNAs) play a pivotal role in periodontitis pathogenesis. Accumulating evidence suggests that lncRNAs have distinct regulatory mechanisms, enabling them to control numerous vital processes in periodontal cells, including osteogenic differentiation, inflammation, proliferation, apoptosis, and autophagy. In this review, we summarize the diverse roles of lncRNAs in the pathogenesis of periodontitis, shedding light on the underlying mechanisms of disease development. By highlighting the potential of lncRNAs as biomarkers and therapeutic targets, this review offers a new perspective on the diagnosis and treatment of periodontitis, paving the way for further investigation into the field of lncRNA-based therapeutics.

LncRNA Gm26917 regulates inflammatory response in macrophages by enhancing Annexin A1 ubiquitination in LPS-induced acute liver injury.

Long noncoding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides that have little or no coding potential. LncRNAs function as key regulators in diverse physiological and pathological processes. However, the roles of lncRNAs in lipopolysaccharide (LPS)-induced acute liver injury (ALI) are still elusive. In this study, we report the roles of lncRNA Gm26917 induced by LPS in modulating liver inflammation. As key components of the innate immune system, macrophages play critical roles in the initiation, progression and resolution of ALI. Our studies demonstrated that Gm26917 localized in the cytoplasm of hepatic macrophages and globally regulated the expression of inflammatory genes and the differentiation of macrophages. In vivo study showed that lentivirus-mediated gene silencing of Gm26917 attenuated liver inflammation and protected mice from LPS-induced ALI. Furthermore, mechanistic study showed that the 3'-truncation of Gm26917 interacted with the N-terminus of Annexin A1, a negative regulator of the NF-κB signaling pathway. We also found that Gm26917 knockdown suppressed NF-κB activity by decreasing the ubiquitination of Annexin A1 and its interaction with NEMO. In addition, expression of Gm26917 in inflammatory macrophages was regulated by the transcription factor forkhead box M1 (FOXM1). LPS treatment dramatically increased the binding of FOXM1 to the promoter region of Gm26917 in macrophages. In summary, our findings suggest that lncRNA Gm26917 silencing protects against LPS-induced liver injury by regulating the TLR4/NF-κB signaling pathway in macrophages.

An Alternatively Spliced Variant of METTL3 Mediates Tumor Suppression in Hepatocellular Carcinoma.

Many post-transcriptional mRNA processing steps play crucial roles in tumorigenesis and the progression of cancers, such as N6-methyladenosine (m6A) modification and alternative splicing. Upregulation of methyltransferase-like 3 (METTL3), the catalytic core of the m6A methyltransferase complex, increases m6A levels and results in significant effects on the progression of hepatocellular carcinoma (HCC). However, alternative splicing of METTL3 has not been fully investigated, and the functions of its splice variants remain unclear. Here, we analyzed both our and online transcriptomic data, obtaining 13 splice variants of METTL3 in addition to canonical full-length METTL3-A in HCC cell lines and tissues. Validated by RT-qPCR and Western blotting, we found that METTL3-D, one of the splice variants expressing a truncated METTL3 protein, exhibits higher levels than METTL3-A in normal human livers but lower levels than METTL3-A in HCC tumor tissues and cell lines. Further functional assays demonstrated that METTL3-D expression decreased cellular m6A modification, inhibited the proliferation, migration, and invasion of HCC cells, and was negatively associated with the malignancy of patient tumors, exhibiting functions opposite to those of full-length METTL3-A. This study demonstrates that the METTL3-D splice variant is a tumor suppressor that could potentially be used as a target for HCC therapy.

CXCL13/CXCR5 are potential biomarkers for diagnosis and prognosis for breast cancer.

PURPOSE: Breast cancer is known as the second frequent cancer in the world, even as the most common cancer among women. This study aimed to explore the correlation of CXCL13/CXCR5 expression with clinical characteristics in breast cancer and evaluate their potential to be used as biomarkers in diagnosis and prognosis of this disease. METHODS: A total of 133 female patients diagnosed with breast cancer were collected. The expression of CXCL13 and CXCR5 mRNA was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical staining. RESULTS: The expression of CXCL13 and CXCR5 was significantly higher in breast cancer tissue than in normal breast tissues, with a high correlation coefficient of 0.9973. Positive cell numbers and positive expression rates of CXCL13 and CXCR5 in cancer breast tissue were much higher than those in normal breast tissue, and raised with increase of cancer stage. The high expression of CXCL13 and CXCR5 in breast cancer tissue was notably associated with lymph node metastasis, distant metastasis, disease stage, but not with age, Her-2 status, histological type or tumor size. Immunohistochemistry analysis showed that the positive expression of CXCL13 and CXCR5 was related with cancer stage, Also, positive expression of CXCL13 was correlated with positive expression of CXCR5. Patient age, Her-2 status, tumor size, histological type, and lymph node metastasis were independent factors for the 5-year survival rate of breast cancer patients, whereas the 5-year survival was correlated with distant metastasis and expression of CXCL13 and CXCR5. CONCLUSIONS: These results suggested that CXCL13 and CXCR5 expressions could act as potential biomarkers for breast cancer diagnosis and prognosis.