Long Non-coding RNAs in Gammaherpesvirus Infections: Their Roles in Tumorigenic Mechanisms

Cell-specific housekeeping role of lncRNAs in COVID-19-infected and recovered patients

A plethora of studies have demonstrated the roles of lncRNAs in modulating disease severity and outcomes during infection. However, the spatio-temporal expression of these lncRNAs is poorly understood. In this study, we used single-cell RNA-seq to understand the spatio-temporal expression dynamics of lncRNAs across healthy, SARS-CoV-2-infected, and recovered individuals and their functional role in modulating the disease and recovery. We identified 203 differentially expressed lncRNAs, including cell type-specific ones like MALAT1, NEAT1, ZFAS1, SNHG7, SNHG8, and SNHG25 modulating immune function in classical monocyte, NK T, proliferating NK, plasmablast, naive, and activated B/T cells. Interestingly, we found invariant lncRNAs (no significant change in expression across conditions) regulating essential housekeeping functions (for example, HOTAIR, NRAV, SNHG27, SNHG28, and UCA1) in infected and recovered individuals. Despite similar repeat element abundance, variant lncRNAs displayed higher Alu content, suggesting increased interactions with proximal and distal genes, crucial for immune response modulation. The comparable repeat abundance but distinct expression levels of variant and invariant lncRNAs highlight the significance of investigating the regulatory mechanisms of invariant lncRNAs. Overall, this study offers new insights into the spatio-temporal expression patterns and functional roles of lncRNAs in SARS-CoV-2-infected and recovered individuals while highlighting the importance of invariant lncRNAs in the disease context.

Bioinformatic identification of genomic instability-associated lncRNAs signatures for improving the clinical outcome of cervical cancer by a prognostic model

The research is executed to analyze the connection between genomic instability-associated long non-coding RNAs (lncRNAs) and the prognosis of cervical cancer patients. We set a prognostic model up and explored different risk groups' features. The clinical datasets and gene expression profiles of 307 patients have been downloaded from The Cancer Genome Atlas database. We established a prognostic model that combined somatic mutation profiles and lncRNA expression profiles in a tumor genome and identified 35 genomic instability-associated lncRNAs in cervical cancer as a case study. We then stratified patients into low-risk and high-risk groups and were further checked in multiple independent patient cohorts. Patients were separated into two sets: the testing set and the training set. The prognostic model was built using three genomic instability-associated lncRNAs (AC107464.2, MIR100HG, and AP001527.2). Patients in the training set were divided into the high-risk group with shorter overall survival and the low-risk group with longer overall survival (p < 0.001); in the meantime, similar comparable results were found in the testing set (p = 0.046), whole set (p < 0.001). There are also significant differences in patients with histological grades, FIGO stages, and different ages (p < 0.05). The prognostic model focused on genomic instability-associated lncRNAs could predict the prognosis of cervical cancer patients, paving the way for further research into the function and resource of lncRNAs, as well as a key approach to customizing individual care decision-making.

Role of Virus-Induced Host Cell Epigenetic Changes in Cancer

The tumor viruses human T-lymphotropic virus 1 (HTLV-1), hepatitis C virus (HCV), Merkel cell polyomavirus (MCPyV), high-risk human papillomaviruses (HR-HPVs), Epstein-Barr virus (EBV), Kaposi’s sarcoma-associated herpes virus (KSHV) and hepatitis B virus (HBV) account for approximately 15% of all human cancers. Although the oncoproteins of these tumor viruses display no sequence similarity to one another, they use the same mechanisms to convey cancer hallmarks on the infected cell. Perturbed gene expression is one of the underlying mechanisms to induce cancer hallmarks. Epigenetic processes, including DNA methylation, histone modification and chromatin remodeling, microRNA, long noncoding RNA, and circular RNA affect gene expression without introducing changes in the DNA sequence. Increasing evidence demonstrates that oncoviruses cause epigenetic modifications, which play a pivotal role in carcinogenesis. In this review, recent advances in the role of host cell epigenetic changes in virus-induced cancers are summarized.

Viral Manipulation of the Host Epigenome as a Driver of Virus-Induced Oncogenesis

Tumorigenesis due to viral infection accounts for a high fraction of the total global cancer burden (15–20%) of all human cancers. A comprehensive understanding of the mechanisms by which viral infection leads to tumor development is extremely important. One of the main mechanisms by which viruses induce host cell proliferation programs is through controlling the host’s epigenetic machinery. In this review, we dissect the epigenetic pathways through which oncogenic viruses can integrate their genome into host cell chromosomes and lead to tumor progression. In addition, we highlight the potential use of drugs based on histone modifiers in reducing the global impact of cancer development due to viral infection.