Applying network approaches to identify genes and circular RNAs that drive Kaposi’s sarcoma-associated herpesvirus’s lytic replication and pathogenesis

Kaposi’s Sarcoma-associated herpesvirus (KSHV) is an oncogenic herpesvirus that exhibits a characteristic bi-phasic life cycle, existing in a suppressed latent cycle or an actively replicating lytic replication program. One aspect of gene expression regulation crucial in controlling this is the post-transcriptional level. Circular RNAs (circRNA) are covalently closed loops of RNA whose primary function is believed to be by acting at this level, as miRNA sponges, whereby they modulate the abundance of cognate miRNAs and downstream target mRNAs. Given the extensiveness of miRNA targeting networks, circRNAs represent efficient targets of viral dysregulation as they sit at the top of hierarchical networks of such interactions, termed competing endogenous RNA (ceRNA) networks. Initial studies have highlighted the involvement of circRNA miRNA sponges in KSHV’s life cycle and pathogenesis, but remains to be elucidated and their functional characterisation is limited. To this end, the first half of this study aimed to construct and analyse a circRNA ceRNA network of differentially expressed circRNAs, miRNAs and mRNAs to characterise the involvement and purpose of dysregulation of this level of regulation. This revealed several cellular circRNAs, primarily circBAGE3, circLRCH3, circSH3PXD2A and circSMG1P1 as highly influential in the network, while the network may be targeted to promote RNA synthesis and gene expression to drive lytic replication. Such a finding reresents a novel mechanism by which KSHV modulates cellular non-coding RNA-based regulatory systems to promote the progression of its life cycle. Viral-host interplay is believed to underpin much of KSHV’s pathogenesis and to contribute to Kaposi Sarcoma (KS), the cancer it is named after. However, little is known about the individual determinants for the development of KS, primarily the influence of host factors. Recent developments in transcriptomics applied to KS lesion tissue has enabled many of these determinants to begin being elucidated, but in-depth analysis is lacking. Thus, in the second half of this study, we modelled and analysed the transcriptome of KS lesions by weighted gene co-expression network analysis (WGCNA). Module partitioning revealed a positive association between latent and some lytic genes and lesion development, while hub gene analysis suggested importance of the Ras/ERK/ETS1 axis and structural maintenance of chromosomes (SMC) proteins to this process. Differential gene co-expression analysis revealed two key factors, SIMC1 and LRRK2, as possible determinants in the transformation of healthy tissue. Such analyses help to identify and characterise novel candidate determinants that drive the oncogenesis of KSHV.