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Nuclear Factor kappa B is central to Marek's disease herpesvirus induced neoplastic transformation of CD30 expressing lymphocytes in-vivo.

Kumar S, Kunec D, Buza JJ, Chiang HI, Zhou H, Subramaniam S, Pendarvis K, Cheng HH, Burgess SC - BMC Syst Biol (2012)

Bottom Line: The exact mechanism of neoplastic transformation from CD30(lo) expressing phenotype to CD30(hi) expressing neoplastic phenotype is unknown.Here, using microarray, proteomics and Systems Biology modeling; we compare the global gene expression of CD30(lo) and CD30(hi) cells to identify key pathways of neoplastic transformation.We propose and test a specific mechanism of neoplastic transformation, and genetic resistance, involving the MDV oncogene Meq, host gene products of the Nuclear Factor Kappa B (NF-κB) family and CD30; we also identify a novel Meq protein interactome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathobiology and Population Medicine, Mississippi State University, MS 39762, USA. skumar@cvm.msstate.edu

ABSTRACT

Background: Marek's Disease (MD) is a hyperproliferative, lymphomatous, neoplastic disease of chickens caused by the oncogenic Gallid herpesvirus type 2 (GaHV-2; MDV). Like several human lymphomas the neoplastic MD lymphoma cells overexpress the CD30 antigen (CD30(hi)) and are in minority, while the non-neoplastic cells (CD30(lo)) form the majority of population. MD is a unique natural in-vivo model of human CD30(hi) lymphomas with both natural CD30(hi) lymphomagenesis and spontaneous regression. The exact mechanism of neoplastic transformation from CD30(lo) expressing phenotype to CD30(hi) expressing neoplastic phenotype is unknown. Here, using microarray, proteomics and Systems Biology modeling; we compare the global gene expression of CD30(lo) and CD30(hi) cells to identify key pathways of neoplastic transformation. We propose and test a specific mechanism of neoplastic transformation, and genetic resistance, involving the MDV oncogene Meq, host gene products of the Nuclear Factor Kappa B (NF-κB) family and CD30; we also identify a novel Meq protein interactome.

Results: Our results show that a) CD30(lo) lymphocytes are pre-neoplastic precursors and not merely reactive lymphocytes; b) multiple transformation mechanisms exist and are potentially controlled by Meq; c) Meq can drive a feed-forward cycle that induces CD30 transcription, increases CD30 signaling which activates NF-κB, and, in turn, increases Meq transcription; d) Meq transcriptional repression or activation of the CD30 promoter generally correlates with polymorphisms in the CD30 promoter distinguishing MD-lymphoma resistant and susceptible chicken genotypes e) MDV oncoprotein Meq interacts with proteins involved in physiological processes central to lymphomagenesis.

Conclusions: In the context of the MD lymphoma microenvironment (and potentially in other CD30(hi) lymphomas as well), our results show that the neoplastic transformation is a continuum and the non-neoplastic cells are actually pre-neoplastic precursor cells and not merely immune bystanders. We also show that NF-κB is a central player in MDV induced neoplastic transformation of CD30-expressing lymphocytes in vivo. Our results provide insights into molecular mechanisms of neoplastic transformation in MD specifically and also herpesvirus induced lymphoma in general.

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Meq interactome showing previously published and novel interactions identified by ChIP experiments and GO based modeling of Meq interacting proteins. Meq interactome based on combined data from proteins identified by chromatin immunoprecipitation (ChIP) experiments (see Methods) and published literature. Differential expression is shown for proteins identified by ChIP. (A). Meq interactome converted to a GO functional network showing the physiological processes that Meq directly affects are consistent with neoplasia. Circle size represents effect size based on numbers of proteins associated with that GO annotation (B).
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Figure 6: Meq interactome showing previously published and novel interactions identified by ChIP experiments and GO based modeling of Meq interacting proteins. Meq interactome based on combined data from proteins identified by chromatin immunoprecipitation (ChIP) experiments (see Methods) and published literature. Differential expression is shown for proteins identified by ChIP. (A). Meq interactome converted to a GO functional network showing the physiological processes that Meq directly affects are consistent with neoplasia. Circle size represents effect size based on numbers of proteins associated with that GO annotation (B).

Mentions: Meq’s functions are modulated by its interacting partners. Here we wanted to identify which proteins were involved with Meq in the context of DNA binding and so we used chromatin immunoprecipitaion (ChIP) using anti-Meq antibodies (rather than traditional immuneprecipitation), followed by 2D LC-MSMS. We used MSB-1 MDCC cells as a model for tumor cells. We identified 31 proteins (PRIDE Accession # 14847–14852, Additional file1). We used these 31 proteins and included previously identified interacting proteins (RB1, TP53, CTBP, HSP70, JUN, FOS, CDK2, CCND1), to produce theoretical Meq interactome model. From these, and using binding proteins from literature, we produced a Meq interactome model (Figure6A). Using GO BP annotations for all the proteins that we modeled in the network, we next generated a GO BP-based functional interaction network (Figure6B). This model suggests how Meq could interact with proteins associated with BPs critical to tumor formation such as cell growth, development, apoptosis, stress, immunity, transcription, cell adhesion, energy metabolism, protein metabolism and transport.


Nuclear Factor kappa B is central to Marek's disease herpesvirus induced neoplastic transformation of CD30 expressing lymphocytes in-vivo.

Kumar S, Kunec D, Buza JJ, Chiang HI, Zhou H, Subramaniam S, Pendarvis K, Cheng HH, Burgess SC - BMC Syst Biol (2012)

Meq interactome showing previously published and novel interactions identified by ChIP experiments and GO based modeling of Meq interacting proteins. Meq interactome based on combined data from proteins identified by chromatin immunoprecipitation (ChIP) experiments (see Methods) and published literature. Differential expression is shown for proteins identified by ChIP. (A). Meq interactome converted to a GO functional network showing the physiological processes that Meq directly affects are consistent with neoplasia. Circle size represents effect size based on numbers of proteins associated with that GO annotation (B).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472249&req=5

Figure 6: Meq interactome showing previously published and novel interactions identified by ChIP experiments and GO based modeling of Meq interacting proteins. Meq interactome based on combined data from proteins identified by chromatin immunoprecipitation (ChIP) experiments (see Methods) and published literature. Differential expression is shown for proteins identified by ChIP. (A). Meq interactome converted to a GO functional network showing the physiological processes that Meq directly affects are consistent with neoplasia. Circle size represents effect size based on numbers of proteins associated with that GO annotation (B).
Mentions: Meq’s functions are modulated by its interacting partners. Here we wanted to identify which proteins were involved with Meq in the context of DNA binding and so we used chromatin immunoprecipitaion (ChIP) using anti-Meq antibodies (rather than traditional immuneprecipitation), followed by 2D LC-MSMS. We used MSB-1 MDCC cells as a model for tumor cells. We identified 31 proteins (PRIDE Accession # 14847–14852, Additional file1). We used these 31 proteins and included previously identified interacting proteins (RB1, TP53, CTBP, HSP70, JUN, FOS, CDK2, CCND1), to produce theoretical Meq interactome model. From these, and using binding proteins from literature, we produced a Meq interactome model (Figure6A). Using GO BP annotations for all the proteins that we modeled in the network, we next generated a GO BP-based functional interaction network (Figure6B). This model suggests how Meq could interact with proteins associated with BPs critical to tumor formation such as cell growth, development, apoptosis, stress, immunity, transcription, cell adhesion, energy metabolism, protein metabolism and transport.

Bottom Line: The exact mechanism of neoplastic transformation from CD30(lo) expressing phenotype to CD30(hi) expressing neoplastic phenotype is unknown.Here, using microarray, proteomics and Systems Biology modeling; we compare the global gene expression of CD30(lo) and CD30(hi) cells to identify key pathways of neoplastic transformation.We propose and test a specific mechanism of neoplastic transformation, and genetic resistance, involving the MDV oncogene Meq, host gene products of the Nuclear Factor Kappa B (NF-κB) family and CD30; we also identify a novel Meq protein interactome.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Pathobiology and Population Medicine, Mississippi State University, MS 39762, USA. skumar@cvm.msstate.edu

ABSTRACT

Background: Marek's Disease (MD) is a hyperproliferative, lymphomatous, neoplastic disease of chickens caused by the oncogenic Gallid herpesvirus type 2 (GaHV-2; MDV). Like several human lymphomas the neoplastic MD lymphoma cells overexpress the CD30 antigen (CD30(hi)) and are in minority, while the non-neoplastic cells (CD30(lo)) form the majority of population. MD is a unique natural in-vivo model of human CD30(hi) lymphomas with both natural CD30(hi) lymphomagenesis and spontaneous regression. The exact mechanism of neoplastic transformation from CD30(lo) expressing phenotype to CD30(hi) expressing neoplastic phenotype is unknown. Here, using microarray, proteomics and Systems Biology modeling; we compare the global gene expression of CD30(lo) and CD30(hi) cells to identify key pathways of neoplastic transformation. We propose and test a specific mechanism of neoplastic transformation, and genetic resistance, involving the MDV oncogene Meq, host gene products of the Nuclear Factor Kappa B (NF-κB) family and CD30; we also identify a novel Meq protein interactome.

Results: Our results show that a) CD30(lo) lymphocytes are pre-neoplastic precursors and not merely reactive lymphocytes; b) multiple transformation mechanisms exist and are potentially controlled by Meq; c) Meq can drive a feed-forward cycle that induces CD30 transcription, increases CD30 signaling which activates NF-κB, and, in turn, increases Meq transcription; d) Meq transcriptional repression or activation of the CD30 promoter generally correlates with polymorphisms in the CD30 promoter distinguishing MD-lymphoma resistant and susceptible chicken genotypes e) MDV oncoprotein Meq interacts with proteins involved in physiological processes central to lymphomagenesis.

Conclusions: In the context of the MD lymphoma microenvironment (and potentially in other CD30(hi) lymphomas as well), our results show that the neoplastic transformation is a continuum and the non-neoplastic cells are actually pre-neoplastic precursor cells and not merely immune bystanders. We also show that NF-κB is a central player in MDV induced neoplastic transformation of CD30-expressing lymphocytes in vivo. Our results provide insights into molecular mechanisms of neoplastic transformation in MD specifically and also herpesvirus induced lymphoma in general.

Show MeSH
Related in: MedlinePlus