Potential miRNA-gene interactions determining progression of various ATLL cancer subtypes after infection by HTLV-1 oncovirus

MicroRNAs Associated with IgLON Cell Adhesion Molecule Expression

The IgLON family of cell adhesion molecules consists of five members (LSAMP, OPCML, neurotrimin, NEGR1, and IgLON5) discovered as supporters of neuronal development, axon growth and guidance, and synapse formation and maintenance. Tumour suppression properties have recently been emerging based on antiproliferative effects through the modulation of oncogenic pathways. Available evidence endorses a role for non-coding RNAs or microRNAs as relevant controllers of IgLON molecule expression that can impact their critical physiological and pathological roles. Current findings support a function for long non-coding RNAs and microRNAs in the modulation of LSAMP expression in cell senescence, cancer biogenesis, addiction, and pulmonary hypertension. For OPCML, data point to a role for several microRNAs in the control of tumorigenesis. MicroRNAs were detected in neurotrimin-mediated functions in cancer biogenesis and in Schwann cell responses to peripheral nerve injury. For NEGR1, studies have mainly investigated microRNA involvement in neuronal responses to ischaemic injury, although data also exist about tumorigenesis and endothelial cell dysfunction. For IgLON5, information is only available about microRNA involved in myocardial infarction. In conclusion, despite much information being still missing and further research needed, the emerging picture favours a model in which non-coding RNAs exert a crucial role in modulating IgLON expression, ultimately affecting their important physiological functions.

Viral oncogenes, viruses, and cancer: a third-generation sequencing perspective on viral integration into the human genome

The link between viruses and cancer has intrigued scientists for decades. Certain viruses have been shown to be vital in the development of various cancers by integrating viral DNA into the host genome and activating viral oncogenes. These viruses include the Human Papillomavirus (HPV), Hepatitis B and C Viruses (HBV and HCV), Epstein-Barr Virus (EBV), and Human T-Cell Leukemia Virus (HTLV-1), which are all linked to the development of a myriad of human cancers. Third-generation sequencing technologies have revolutionized our ability to study viral integration events at unprecedented resolution in recent years. They offer long sequencing capabilities along with the ability to map viral integration sites, assess host gene expression, and track clonal evolution in cancer cells. Recently, researchers have been exploring the application of Oxford Nanopore Technologies (ONT) nanopore sequencing and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) sequencing in cancer research. As viral integration is crucial to the development of cancer via viruses, third-generation sequencing would provide a novel approach to studying the relationship interlinking viral oncogenes, viruses, and cancer. This review article explores the molecular mechanisms underlying viral oncogenesis, the role of viruses in cancer development, and the impact of third-generation sequencing on our understanding of viral integration into the human genome.

Gene biomarkers and classifiers for various subtypes of HTLV-1-caused ATLL cancer identified by a combination of differential gene co‑expression and support vector machine algorithms

Adult T-cell leukemia/lymphoma (ATLL) is pathogen-caused cancer that is progressed after the infection by human T-cell leukemia virus type 1. Four significant subtypes comprising acute, lymphoma, chronic, and smoldering have been identified for this cancer. However, there are no trustworthy prognostic biomarkers for these subtypes. We utilized a combination of two powerful network-based and machine-learning algorithms including differential co-expressed genes (DiffCoEx) and support vector machine-recursive feature elimination with cross-validation (SVM-RFECV) methods to categorize disparate ATLL subtypes from asymptomatic carriers (ACs). The results disclosed the significant involvement of CBX6, CNKSR1, and MAX in chronic, MYH10 and P2RY1 in acute, C22orf46 and HNRNPA0 in smoldering subtypes. These genes also can classify each ATLL subtype from AC carriers. The integration of the results of two powerful algorithms led to the identification of reliable gene classifiers and biomarkers for diverse ATLL subtypes.