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Transcriptional perturbations caused by tumor virus proteins

ABSTRACT: Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer. We profiled the transcriptome of human cells expressing tumor virus proteins, in order to trace pathways through which viral proteins could alter cellular states.

ORGANISM(S): Homo sapiens

PROVIDER: GSE38467 | GEO | 2012/07/20

SECONDARY ACCESSION(S): PRJNA167934

REPOSITORIES: GEO

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Project description:Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. These complementary approaches together result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer. We profiled the transcriptome of human cells expressing tumor virus proteins, in order to trace pathways through which viral proteins could alter cellular states. To examine transcriptome network perturbations directly in human cells, we generated expression constructs fusing each viral ORF (open reading frame) to a tandem epitope tag and introduced each construct into IMR-90 normal human diploid fibroblasts. Total RNA was isolated from IMR-90 cells expressing viORFs and gene expression was assayed on Human Gene 1.0 ST arrays.

Project description:This mathematical model of the role of the innate immune responses generated by macrophages in the context of anti-tumour oncolytic viral therapies is described in the publication: Nada Almuallem, Dumitru Trucu, Raluca Eftimie. "Oncolytic viral therapies and the delicate balance between virus-macrophage-tumour interactions: A mathematical approach". Mathematical Biosciences and Engineering, 2021, 18(1): 764-799. doi: 10.3934/mbe.2021041 Comment: This model is represented by Equations 2.1a-f of the publication manuscript. Abstract: The success of oncolytic virotherapies depends on the tumour microenvironment, which contains a large number of infiltrating immune cells. In this theoretical study, we derive an ODE model to investigate the interactions between breast cancer tumour cells, an oncolytic virus (Vesicular Stomatitis Virus), and tumour-infiltrating macrophages with different phenotypes which can impact the dynamics of oncolytic viruses. The complexity of the model requires a combined analytical-numerical approach to understand the transient and asymptotic dynamics of this model. We use this model to propose new biological hypotheses regarding the impact on tumour elimination/relapse/persistence of: (i) different macrophage polarisation/re-polarisation rates; (ii) different infection rates of macrophages and tumour cells with the oncolytic virus; (iii) different viral burst sizes for macrophages and tumour cells. We show that increasing the rate at which the oncolytic virus infects the tumour cells can delay tumour relapse and even eliminate tumour. Increasing the rate at which the oncolytic virus particles infect the macrophages can trigger transitions between steady-state dynamics and oscillatory dynamics, but it does not lead to tumour elimination unless the tumour infection rate is also very large. Moreover, we confirm numerically that a large tumour-induced M1→M2 polarisation leads to fast tumour growth and fast relapse (if the tumour was reduced before by a strong anti-tumour immune and viral response). The increase in viral-induced M2→M1 re-polarisation reduces temporarily the tumour size, but does not lead to tumour elimination. Finally, we show numerically that the tumour size is more sensitive to the production of viruses by the infected macrophages.

Project description:Smallpox is a highly communicable, often fatal diseae. There is currently no licensed treatment for smallpox and vaccinia virus (VV) is currently used for immunization. While immunization with VV can provide good protection against exposure to the smallpox virus, the current vaccine is far from optimal. Complications occur in 1/1,000-1/10,000 vaccinees, with at least one death per million vaccinees. We have constructed recombinant VV strains which are less pathogenic, yet provide a protective immune response. These viruses contain various mutations in the E3L which is known to block the host antiviral response. Identifying the host genes involved in producing a strong protective immunological response to these attenuated viruses would not only increase our understanding of the proteins and pathways involved in effective smallpox vaccination, but aid in the development of alternative vaccine strains which enhance these specific immune responses. We will determine gene expression patterns in HeLa cells at various times following infection with wtVV and several VV constructs containing mutations in the E3L gene. The VV E3L gene product blocks the host antiviral response by sequestering viral danger signals, including double-stranded RNA and Z-DNA. VV constructs containing mutations in E3L which allow host cell recognition of either of these danger signals leads to a decrease in viral pathogensis. In this project we will dissect the cellular inflammatory response to infection with wtVV in comparison to VV containing mutations in the E3L gene. By understanding why certain strains of VV are non-pathogenic, yet highly immunogenic, it is possible to gain a better understanding on the mechanisms of poxvirus pathogenesis and the host response. We will examine three times points following infection with VV: 2 HPI, 6 HPI and 9 HPI. These times points represent keys points in the virus replication cycle. Several VV constructs will be used which contain mutations in the E3L gene. These constructs alter the ability of E3L to sequester double-stranded RNA and/or Z-DNA and therefore have a direct effect on viral pathogenesis. Fourteen constructs will be used including: mock, wtVV, VVdelE3L, VVE3Ldel83N, VVE3Ldel37N, VVE3Ldel26C, VVE3Ldel7C, VVE3L Y48A, VVE3L P63A, VVE3L K167T, VV-ATV, VV-ADAR/E3L, VVdelK3L, VVdelK3L-E3Ldel37N. Cells will be infected at an MOI of 5 to allow infection of all cells. At each time point, cells will be harvested by scraping. RNA will be isolated using a Trizol RNA extraction protocol (Invitrogen) followed by RNA purification using the RNeasy cleanup kit available from Qiagen.

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Transcriptional perturbations caused by tumor virus proteins

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