LAYN Serves as a Prognostic Biomarker and Downregulates Tumor-Infiltrating CD8+ T Cell Function in Hepatocellular Carcinoma.

Background: Layilin (LAYN) represents a valuable prognostic biomarker across various tumor types, while also serving as an innovative indicator of dysfunctional or exhausted CD8+ T cells and exhibiting correlation with immune context. However, the immune function and prognostic significance of LAYN in hepatocellular carcinoma (HCC) remain unexplored. Therefore, our objective is to investigate the role of LAYN in CD8+ T cell exhaustion, clinical prognosis, and the tumor microenvironment within HCC. Methods: TIMER or GEPIA databases were used to analyze LAYN expression level and its correlation with immune infiltration in HCC. Bioinformatics analysis was conducted on TCGA and scRNA-seq cohorts. The evaluation of LAYN expression level in fresh specimens was performed through IF, IHC, and ELISA assays. Flow cytometry and mRNA-seq were employed to investigate co-expressed genes of LAYN, the LAYN+CD8+ T cell exhaustion signature and immune function. Cell proliferation ability and killing activity were assessed using CCK8 and CFSE/PI. Results: The expression level of LAYN in HCC tumors was significantly higher compared to peri-tumors. Patients with high levels of LAYN exhibited poorer OS. GO or KEGG analysis confirmed that LAYN was involved in immune response and was positively associated with CD8+ T cell immune infiltration levels. Furthermore, LAYN negatively regulated the immune function of CD8+ T cells, leading to dysfunctional phenotypes characterized by elevated levels of CD39, TIM3 and reduced levels of perforin, TNF-α, Ki-67. CFSE/PI assays demonstrated that LAYN+CD8+ T cells displayed decreased cytotoxic activity. Additionally, there was a positive correlation between LAYN and CD146 levels, which are involved in adhesion and localization processes of CD8+ T cells. Interestingly, blocking LAYN partially restored the exhaustion properties of CD8+ T cells. Conclusion: LAYN exhibits a strong correlation with immune infiltration in the TME and represents a novel biomarker for predicting clinical prognosis in HCC. Moreover, targeting LAYN may hold promise as an effective strategy for HCC immunotherapy.

A novel protein encoded by circFOXP1 enhances ferroptosis and inhibits tumor recurrence in intrahepatic cholangiocarcinoma.

CircRNAs participates in the development and occurrence of multiple tumor types. However, the specific effects and underlying mechanisms of circRNA in intrahepatic cholangiocarcinoma (ICC) progression and recurrence remain poorly understood. CircRNA sequencing was performed to screen circRNAs related to ICC recurrence after surgery using 53 ICC frozen tumor specimens. We found that compared with patients who experienced postsurgical recurrence, circFOXP1 had high expression in tumor tissues from patients with no postoperative recurrence. Functional experiments revealed that circFOXP1 inhibited ICC progression in vitro and in vivo. We then found that circFOXP1 inhibited ICC progression via encoding a novel protein, circFOXP1-231aa. Mechanistically, circFOXP1-231aa directly interacted with OTUD4, which regulates NCOA4 protein stability via deubiquitination modification, and thereby enhances ferroptosis of ICC cells. Examination of clinical ICC samples found positive correlations between circFOXP1 expression levels and levels of OTUD4 and NCOA4. These three factors are predictors of prognosis in patients with ICC. Collectively, we identified circFOXP1 encoded circFOXP1-231aa, which interacted with OTUD4 to suppress ubiquitination of NCOA4 and, thereby, promoted ferroptosis and inhibited ICC recurrence.

Tumor-associated macrophage-induced circMRCKα encodes a peptide to promote glycolysis and progression in hepatocellular carcinoma.

The tumor-associated macrophages (TAMs) play multifaceted roles in the progression of hepatocellular carcinoma (HCC). However, the involvement of circular RNAs in the interplay between TAMs and HCC remains unclear. Based on Transwell co-culturing and circular RNA sequencing, this study revealed that TAMs enhanced tumor glycolysis and progression by upregulating circMRCKα in HCC cells. Patients with HCC who exhibited elevated circMRCKα levels presented significantly reduced overall survival and greater cumulative recurrence. Notably, we identified a novel functional peptide of 227 amino acids named circMRCKα-227aa, encoded by circMRCKα. Mechanistically, circMRCKα-227aa bound to USP22 and enhanced its protein level to obstruct HIF-1α degradation via the ubiquitin-proteasome pathway, thereby augmenting HCC glycolysis and progression. In clinical HCC samples, a positive correlation was observed between the expression of circMRCKα and the number of infiltrating CD68+ TAMs and expression of USP22. Furthermore, circMRCKα emerged as an independent prognostic risk factor both individually and in conjunction with CD68+ TAMs and USP22. This study illustrated that circMRCKα-227aa, a novel TAM-induced peptide, promotes tumor glycolysis and progression via USP22 binding and HIF-1α upregulation, suggesting that circMRCKα and TAMs could be combined as therapeutic targets in HCC.

Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods.

Background: The human body has more than 600 kinds of skeletal muscles, which accounts for about 40% of the whole weight. Most skeletal muscles can make bones move, and their strength and endurance directly affect their performance during exercise. Methods: To determine the effects of exercise and time on human skeletal muscle, we downloaded the microarray expression profile of GSE1832 and analyzed it to select differentially expressed genes (DEGs). Then, a protein-protein interaction (PPI) network was established, and the hub genes were identified. Afterwards, DEGs were applied to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Finally, with the help of Gene Set Enrichment Analysis (GSEA), the gene sets in the 7 samples were enriched in the KEGG pathway. Results: Through a series of bioinformatics analyses, we obtained a total of 271 DEGs. After that, four hub genes were determined through the PPI network, namely, EP300, STAT1, CDKN1A, and RAC2. In addition, we got that these DEGs were enriched in GO, such as regulation of cell population proliferation, cellular water homeostasis, and so on, and in KEGG, namely, hepatitis B, Epstein-Barr virus infection, small cell lung cancer, pathways in cancer, and others. Finally, the gene set in the samples obtained by GSEA was enriched in the cell cycle, chemokine signaling pathway, DNA replication, cytokine receptor interaction, ECM receptor interaction, and focal adhesion in KEGG. Conclusion: The findings obtained in this study will provide new clues for elucidating the mechanism of exercise and time on human skeletal muscles.

Bioinformatics Analysis of Exercise-Related Biomarkers in Diabetes.

Background: Exercise is a regular behavioral activity that not only helps to lose weight but also reduces the risk of cardiovascular and cerebrovascular diseases. Diabetes is a common disease that plagues human health. It is shown that regular exercise can improve the insulin sensitivity of diabetic patients and have an important function in adjuvant therapy. Methods: We downloaded the GSE101931 dataset from the Gene Expression Omnibus (GEO) database, 10 samples were obtained from the GSE101931 dataset, including 5 before exercise and 5 postexercise samples, and GEO2R was used to screen the differentially expressed genes (DEGs) exhibited by a heat map. Then, the enrichment analysis of DEGs in Gene Ontology (GO) function was analyzed by Metascape, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of DEGs was also analyzed by gene set enrichment analysis (GSEA). Next, the protein-protein interaction (PPI) network maps were drawn, and the hub genes were identified through Metascape. Finally, the expressions of the hub genes in the dataset were analyzed. Results: Totally, 116 upregulated DEGs and 1017 downregulated DEGs were identified from these data. These DEGs were mainly enriched in the platelet-derived growth factor receptor signaling pathway and mRNA processing. Then, the GSEA analysis showed that 6 KEGG pathways were associated with postexercise prediabetic samples, namely, ABC transporters, focal adhesion, MAPK signaling pathway, prion diseases, melanogenesis, and gap junction. Afterward, three hub genes (HSPA8, STIP1, and HSPH1) were highly expressed after exercise through the box plot analysis. Conclusion: A myriad of research results confirms that there is a certain connection between exercise and diabetes, which provides a favorable basis for emerging exercise into the treatment of diabetic patients.