| Literature DB >> 35889167 |
Rodney Hull1, Rahaba Marima1, Mohammed Alaouna1,2, Demetra Demetriou1, Rui Manuel Reis1,3,4, Thulo Molefi1,5, Zodwa Dlamini1.
Abstract
About 15% of all human cancers have a viral etiology. Although progress has been made, understanding the viral oncogenesis and associated molecular mechanisms remain complex. The discovery of cellular miRNAs has led to major breakthroughs. Interestingly, viruses have also been discovered to encode their own miRNAs. These viral, small, non-coding miRNAs are also known as viral-miRNAs (v-miRNAs). Although the function of v-miRNAs largely remains to be elucidated, their role in tumorigenesis cannot be ignored. V-miRNAs have also been shown to exploit the cellular machinery to benefit viral replication and survival. Although the discovery of Hepatitis C virus (HCV), and its viral miRNAs, is a work in progress, the existence of HPV-, EBV-, HBV-, MCPyV- and KSHV-encoded miRNA has been documented. V-miRNAs have been shown to target host factors to advance tumorigenesis, evade and suppress the immune system, and deregulate both the cell cycle and the apoptotic machinery. Although the exact mechanisms of v-miRNAs-induced tumorigenesis are still unclear, v-miRNAs are active role-players in tumorigenesis, viral latency and cell transformation. Furthermore, v-miRNAs can function as posttranscriptional gene regulators of both viral and host genes. Thus, it has been proposed that v-miRNAs may serve as diagnostic biomarkers and therapeutic targets for cancers with a viral etiology. Although significant challenges exist in their clinical application, emerging reports demonstrate their potent role in precision medicine. This review will focus on the roles of HPV-, HCV-, EBV-, HBV-, MCPyV-, and KSHV-produced v-miRNAs in tumorigenesis, as effectors in immune evasion, as diagnostic biomarkers and as novel anti-cancer therapeutic targets. Finally, it will discuss the challenges and opportunities associated with v-miRNAs theranostics in precision oncology.Entities:
Keywords: Epstein–Barr virus (EBV); Hepatitis B virus (HBV); Hepatitis C virus (HCV); Kaposi’s sarcoma-associated herpesvirus (KSHV); Merkel Cell Polyomavirus (MCPyV); biomarkers; human papillomaviruses (HPV); precision oncology; theranostics; therapeutics; viral-miRNAs (v-miRNAs)
Year: 2022 PMID: 35889167 PMCID: PMC9321719 DOI: 10.3390/microorganisms10071448
Source DB: PubMed Journal: Microorganisms ISSN: 2076-2607
Figure 1Oncogenic viruses in precision oncology. (A) Summary of oncoviruses and their associated tumors. These oncoviruses include EBV, HPV, KSHV, HBV, HCB and MCPyV. Cancers associated with these viruses include Hodgkin’s lymphoma, cervical cancer, Kaposi sarcoma, liver cancer and Merkel cell carcinomas. (B) Representation of relative v-miRNA abundance. EBV v-miRNAs relative abundance is higher than the other v-miRNAs, followed by KSHV, HPV, HBV, and no HCV* v-miRNA has been confirmed to date [10].
Figure 2V-miRNAs’ mediated tumourigenesis. (A) Schematic representation of v-miRNA biogenesis. Simliar to cellular miRNAs, v-miRNAs are transcribed as primary v-miRNAs (pri-v-miRNAs) in the nucleus. Pri-v-miRNAs is then cleaved by Drosha into pre-v-miRNA. Exportin 5 exports the pre-v-miRNA to the cytoplasm. Mature v-miRNA is generated from pre-v-miRNA by Dicer cleavage. MiRNA is then loaded into the RISC complex to target mRNA, viral and cellular transcripts [11]. (B) Diagrammatic representation of v-miRNA mediated tumorigenesis. V-miRNAs play an important role in viral latency by targeting key tumour-suppressor genes such as p53 and PTEN, causing genomic instability, and favouring tumorigenic pathways such as cell growth, survival, proliferation and cell transformation, and immune evasion, while inhibiting anti-tumorigenic mechanisms such as cell cycle arrest and apoptosis [10].
Summary of known viral miRNAs with roles in oncogenesis.
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| Immune evasion, cell cycle regulation | SP3, XRCC4, PKNOX1, JAK2, FOXP1 | HPV16-miR-H2 | [ |
| HPV16-miR-H2 | |||
| HPV16-miR-H1 | |||
| HPV6-miR-H1 | |||
| BCL11A, TCEA1, CHD7, ITGAM, RAG1, TEF1 | HPV16-miR-H3 | [ | |
| HPV16-miR-H5 | |||
| HPV16-miR-H6 | |||
| HPV38-miR-H1 | |||
| HPV35-miR-H1 | |||
| HPV68-miR-H1 | |||
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| Proliferation | PPM1A, PTEN | HBV-mir-3 | [ |
| Pro-tumorigenic | TRIM35 | HBV-mir-2 | [ |
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| Immune evasion | SP100 | MCV-miR-M1-5p | [ |
| Viral proliferation | RUNX1 | MCV-miR-M1-3p | [ |
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| Immune evasion | IPO7 | ebv-BART3-3p | [ |
| LMP1 | ebv-BART5-5p | [ | |
| RIG-1 | ebv-BART6-3p | [ | |
| MICB | ebv-BART2-5p | [ | |
| TAP | ebv-BART17-5p | [ | |
| LMP2A | ebv-BART22 | [ | |
| IL-12 | ebv-BART1-5p | [ | |
| IL1Receptor1 | ebv-BHRF1-2 | [ | |
| CXCL-11/I-TAC | ebv-BHRF1-3 | [ | |
| ebv-BART1-3p | [ | ||
| RNF38 | ebv-BART8 | [ | |
| Angiogenesis | PHLPP1 | ebv-BART15 | [ |
| Anti-apoptosis | TOM22 | ebv-BART16 | [ |
| PRDM1/Blimp1 | ebv-BHRF1-2 | [ | |
| Bid | ebv-BART4-5p | [ | |
| PUMA | ebv-BART5-5p | [ | |
| P53 | ebv-BHRF1-1 | [ | |
| BAD | ebv-BART20-5p | [ | |
| Tumorigenic | Catalytic subunit of AMP-activated protein kinase (AMPKα1) | ebv-BART1-5p | [ |
| LMP1 | ebv-BART16 | [ | |
| PRDM1/BLIMP1 | ebv-BHRF1-2 | [ | |
| ABI2 | ebv-BART13-3p | [ | |
| Pro-metastatic | E-Cadherin | ebv-BART9 | [ |
| BTRC | ebv-BART10-3p | [ | |
| NDRG1 | ebv-BART22 | [ | |
| Proliferative | RIG1 | ebv-BART6-3p | [ |
| FOXP1 | ebv-BART11 | [ | |
| MAP3K5, | ebv-BART22 | [ | |
| Viral latency | DICER | ebv-BART6-5p | [ |
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| Proliferation and metastasis | SOCS6 | kshv-miR-K12-1-5p | [ |
| Anti-Apoptotic | CASP3 | kshv-miR-K12-1 | [ |
| kshv-miR-K12-3 | |||
| kshv-miR-K12-4 | |||
| kshv-mir-K3 | [ | ||
| CASP7 | kshv-mir-K3 | [ | |
| Cell migration and invasion | RK2/CXCR2/AKT | kshv-miR-K12-3 | [ |
| Viral latency | Rbl2 | kshv-miR-K12-5 | [ |
| Kshv-miR-K12-4-5p | [ | ||
| Immune evasion | MYD88 | kshv-mir-K12-5 | [ |
| IRAK1, | kshv-mir-K12-9 | ||
| C/EBP_ | Kshv-mir-K12-3 | [ | |
| kshv-mir-K12-7 | |||
| MICB | kshv-miR-K12-7 | [ | |
| IKKε | kshv-miR-K12-11 | [ | |
| TWEAK | kshv-miR-K12-10a | [ | |
| C/EBPβ p20 (LIP) | kshv-miR-K12-3 | [ | |
| Tumorigenesis | TGFBR2 | kshv-miR-K12-10b | [ |
| CASTOR1 | Kshv-miR-K4-5p, | [ | |
| Kshv-miR-K1-5p, | |||
| Regulation of lytic induction | RTA | kshv-miR-K5 | [ |
| miR-K7-5p | |||
| kshv-miR-K9-5p, | |||
| kshv-miR-K3 | |||
| kshv-miR-K4 | |||
| Differentiation of infected cells | C/EBPβ; | kshv-miR-K12-11 | [ |
| MAF | kshv-miR-K12-6 | [ | |
Abbreviations: Abelson interactor 2 (ABI2); Bcl2-associated agonist of cell death (BAD); B-cell lymphoma/leukemia 11A (BCL11A); BH3-interacting domain death agonist (BID); Cytosolic arginine sensor for mTORC1 subunit 1 (CASTOR1); chromodomain helicase DNA binding protein 7 (CHD7); Forkhead box protein P1 (FOXP1); Integrin alpha M (ITGAM); Importin-7 (IPO7); Janus kinase 2 (JAK2); Latent membrane protein (LMP1); Musculoaponeurotic fibrosarcoma oncogene homolog (MAF); MHC class I polypeptide-related sequence B (MICB); N-myc downstream regulated gene 1 (NDRG1); PH domain and leucine rich repeat protein phosphatase 1 (PHLPP1); PBX/Knotted 1 Homeobox 1(PKNOX1); Protein phosphatase 1A (PPM1A); PR domain zinc finger protein 1, or B lymphocyte-induced maturation protein-1 (PRDM!/HLIMP1); Phosphatase and tensin homolog (PTEN); p53 upregulated modulator of apoptosis (PUMA); Recombination activating gene 1 (RAG1); retinoblastoma (Rb)-like protein 2 (Rbl2); retinoic acid-inducible gene I (RIG1); RING finger protein 38 (RNF38); Runt-related transcription factor 1 (RUNX1); suppressor of cytokine signalling 6 (SOCS6); SP3 transcription factor (SP3); Transcription Elongation Factor A1(TCEA1); translation elongation factor 1alpha (TEF1); Translocase of outer membrane 22 (Tom22); Tripartite Motif Containing 35(TRIM35); X-ray repair cross-complementing protein 4 (XRCC4).
Figure 3V-miRNA biomarkers in precision oncology. (A) v-miRNA can be profiled in an infected population. Various infections may lead to a range of disease outcomes. These may include people with no symptoms (dark blue), mild symptoms (orange) and severe symptoms (light blue). Unique v-miRNA signatures may be used to discriminate between these groups. This figure shows changes in the transcription of various hypothetical miRNAs, demonstrating how the changes in the miRNA profiles can be used to classify patients. (B) This will also improve cancer management and patient outcome through personalized medicine.