A Pan-Cancer Landscape of HOX-Related lncRNAs and Their Association With Prognosis and Tumor Microenvironment

Development and validation of a combined cuproptosis and immunogenic cell death prognostic model for diffuse large B-cell lymphoma

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide with a high degree of heterogeneity. Cuproptosis and immunogenic cell death (ICD) have been considered to be vital for tumor progression. However, current understanding of cuproptosis and immunogenic cell death in DLBCL is still very limited. We aim to explore a prognostic model combining cuproptosis and immunogenic cell death in DLBCL.

METHODS

Pearson's correlation analysis was utilized to acquire lncRNAs associated with cuproptosis and immunogenic cell death. Prognostic biomarker identification and model construction involved the use of univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox regression. We assessed the predictive capability of the risk model by conducting Kaplan-Meier analysis and time-dependent ROC analysis. The analysis and comparison of immune infiltration and drug sensitivity were conducted in this study. Moreover, RT-qPCR was employed to validate the expression of lncRNAs associated with cuproptosis and immunogenic cell death in DLBCL cell lines.

RESULTS

We identified 4 prognosis-related lncRNAs (ANKRD10-IT1, HOXB-AS1, LINC00520 and LINC01165) that were correlated with cuproptosis and immunogenic cell death. The model was verified to have a good and independent predictive ability in the prognostic prediction of DLBCL patients. Moreover, significant difference was observed in immune infiltration and drug sensitivity between high- and low-risk groups.

CONCLUSION

Our discoveries could enhance the comprehension of the role of cuproptosis and ICD in DLBCL, potentially offering novel viewpoints and knowledge for personalized and precise treatment of DLBCL individuals.

Long Non-Coding RNAs as Epigenetic Regulators of Immune Checkpoints in Cancer Immunity

In recent years, cancer treatment has undergone significant changes, predominantly in the shift towards immunotherapeutic strategies using immune checkpoint inhibitors. Despite the clinical efficacy of many of these inhibitors, the overall response rate remains modest, and immunotherapies for many cancers have proved ineffective, highlighting the importance of knowing the tumor microenvironment and heterogeneity of each malignancy in patients. Long non-coding RNAs (lncRNAs) have attracted increasing attention for their ability to control various biological processes by targeting different molecular pathways. Some lncRNAs have a regulatory role in immune checkpoints, suggesting they might be utilized as a target for immune checkpoint treatment. The focus of this review is to describe relevant lncRNAs and their targets and functions to understand key regulatory mechanisms that may contribute in regulating immune checkpoints. We also provide the state of the art on super-enhancers lncRNAs (selncRNAs) and circular RNAs (circRNAs), which have recently been reported as modulators of immune checkpoint molecules within the framework of human cancer. Other feasible mechanisms of interaction between lncRNAs and immune checkpoints are also reported, along with the use of miRNAs and circRNAs, in generating new tumor immune microenvironments, which can further help avoid tumor evasion.

Non-coding RNAs and glioma: Focus on cancer stem cells

Glioblastoma and gliomas can have a wide range of histopathologic subtypes. These heterogeneous histologic phenotypes originate from tumor cells with the distinct functions of tumorigenesis and self-renewal, called glioma stem cells (GSCs). GSCs are characterized based on multi-layered epigenetic mechanisms, which control the expression of many genes. This epigenetic regulatory mechanism is often based on functional non-coding RNAs (ncRNAs). ncRNAs have become increasingly important in the pathogenesis of human cancer and work as oncogenes or tumor suppressors to regulate carcinogenesis and progression. These RNAs by being involved in chromatin remodeling and modification, transcriptional regulation, and alternative splicing of pre-mRNA, as well as mRNA stability and protein translation, play a key role in tumor development and progression. Numerous studies have been performed to try to understand the dysregulation pattern of these ncRNAs in tumors and cancer stem cells (CSCs), which show robust differentiation and self-regeneration capacity. This review provides recent findings on the role of ncRNAs in glioma development and progression, particularly their effects on CSCs, thus accelerating the clinical implementation of ncRNAs as promising tumor biomarkers and therapeutic targets.

Integrated Analysis of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma

Tumor mutation burdens (TMBs) act as an indicator of immunotherapeutic responsiveness in various tumors. However, the relationship between TMBs and immune cell infiltrates in hepatocellular carcinoma (HCC) is still obscure. The present study aimed to explore the potential diagnostic markers of TMBs for HCC and analyze the role of immune cell infiltration in this pathology. We used OA datasets from The Cancer Genome Atlas database. First, the “maftools” package was used to screen the highest mutation frequency in all samples. R software was used to identify differentially expressed genes (DEGs) according to mutation frequency and perform functional correlation analysis. Then, the gene ontology (GO) enrichment analysis was performed with “clusterProfiler”, “enrichplot”, and “ggplot2” packages. Finally, the correlations between diagnostic markers and infiltrating immune cells were analyzed, and CIBERSORT was used to evaluate the infiltration of immune cells in HCC tissues. As a result, we identified a total of 359 DEGs in this study. These DEGs may affect HCC prognosis by regulating fatty acid metabolism, hypoxia, and the P53 pathway. The top 15 genes were selected as the hub genes through PPI network analysis. SRSF1, SNRPA1, and SRSF3 showed strong similarities in biological effects, NCBP2 was demonstrated as a diagnostic marker of HCC, and high NCBP2 expression was significantly correlated with poor over survival (OS) in HCC. In addition, NCBP2 expression was correlated with the infiltration of B cells (r = 0.364, p = 3.30 × 10⁻¹²), CD8⁺ T cells (r = 0.295, p = 2.71 × 10⁻⁸), CD4⁺ T cells, (r = 0.484, p = 1.37 × 10⁻²¹), macrophages (r = 0.551, p = 1.97 × 10⁻²⁸), neutrophils (r = 0.457, p = 3.26 × 10⁻¹⁹), and dendritic cells (r = 0.453, p = 1.97 × 10⁻¹⁸). Immune cell infiltration analysis revealed that the degree of central memory T-cell (Tcm) infiltration may be correlated with the HCC process. In conclusion, NCBP2 can be used as diagnostic markers of HCC, and immune cell infiltration plays an important role in the occurrence and progression of HCC.