Global Proteomic Profiling of Endemic Versus Sporadic Epstein-Barr Virus (EBV) Positive Burkitt Lymphoma (BL).
Authors: El-Mallawany Nader , Ayello Janet , Day Nancy , van de Ven Carmella , Conlon Kevin P , Fermin Damian , Basrur Venkatesha , Elenitoba-Johnson Kojo S.J. , Lim Megan S , Cairo Mitchell S. 
Published: October 2019

Abstract 4779

Background

EBV infection of normal B-cells is commonly associated with the pathogenesis of BL (Brady et al, Clin Path, 2007). Endemic BL (eBL) is characteristically positive (100%) for EBV, contrasting with sporadic BL (sBL), where approximately 30% of cases are positive for EBV. eBL vs. sBL have significantly different breakpoint regions within c-myc (Shiramizu/Magrath et al, Blood, 1991). Overexpression of c-myc is the sine quae non of BL. C-myc interactions with other genes/proteins is multilayered and complex (Basso/Della-Favera, Nat Gen, 2005). Apoptotic pathway disruption is propelled by EBV and is critically important in c-myc deregulation and subsequent lymphomagenesis that occurs in EBV+ eBL vs. sBL (Ruf et al, J Vir, 2000). Global analysis of proteins expressed in EBV+ eBL vs. sBL may provide insights into biologic, pathogenetic, and molecular differences between the two subtypes of lymphoma, and potentially identify targets for the development of therapeutic agents.

Objectives

To compare the proteomic expression profile and signal transduction pathways of EBV+ eBL vs. sBL.

Methods

Whole cell lysates obtained from the EBV+ eBL cell line Raji and the EBV+ sBL cell line NC37 were digested and labeled with iTRAQ” labeling reagents, following manufacturer's protocol. The peptides were resolved by 2D-LC technique (off-line Strong cation exchange followed by on-line reverse-phase liquid chromatography). Data-dependant High energy C-trap Dissociation MS/MS spectra were acquired using an Orbitrap XL Tandem Mass Spectrometer (ThermoFisher). The MS/MS data was searched using X!Tandem/TPP software suite against human IPI database (v3.50) appended with decoy (reverse) sequences. iTRAQ” ratios of proteins (ProteinProphet probability of >0.9) were normalized and differentially expressed proteins were determined through Mixture Modeling. Protein interactions were further analyzed using the GoMiner and Ingenuity pathway analysis tools.

Results

Over 400 proteins were identified as being differentially expressed by a ≥ 1.25 fold change between the two cell lines. We identified differentially expressed proteins in both cell lines that are involved in a wide array of cellular processes as exhibited in Figure 1. Cellular processes uniquely involved by proteins over-expressed in eBL included immune response, hematopoiesis, cell proliferation, heat shock, and B-cell activation, while those uniquely identified in sBL included cell division, response to virus, and NF-kB cascade proteins. Specific cell-regulatory pathways implicated by the differential protein profile expressions (with associated proteins in parentheses) included the p53 apoptosis pathway (PCNA, MSH6, C1QBP, MAP4, and BAX), the caspase network of apoptosis (HCLS1, ACIN1, and AIFM1), the tumor suppressor protein RB network (MCM7, PA2G4, and API5), general apoptotic pathways (HSP90 and PDCD4), B-cell differentiation and proliferation pathways (TPD52 and IKBKG), and the ubiquitin-proteasome pathway (UBE2J1, UBE2C, and UBE2S). Seven of these proteins are c-myc target genes. Ingenuity protein network analysis revealed nine proteins identified in the experiment with interactions connected through the p53, caspase, and tumor necrosis factor apoptosis pathways.

Conclusion

Proteomic profile analysis of EBV+ eBL and sBL revealed over and under-expression of multiple proteins that may be implicated in the multi-factorial nature of disease pathogenesis. This is the first MS-based direct proteomic comparison of eBL and sBL. Our results suggest that there are potentially different mechanisms driving cell proliferation and resistance to apoptosis in eBL versus sBL and that EBV infection may be involved in the processes that drive lymphomagenesis. Ultimately, identification of proteins unique to the distinct disease subtypes will serve to establish tumor markers that may enable development of new diagnostic, prognostic, and therapeutic strategies.

Disclosures:

No relevant conflicts of interest to declare.