Plasmablastic lymphoma (PBL) is a highly aggressive lymphoma of pre-terminally differentiated B-cells which is often associated with HIV/AIDS immunodeficiency and represents one of the two B-NHL diagnoses that have significantly increased in incidence in South Africa over the past few years. This tumor has well documented morphological and immunophenotypic features but the specific mutational signature associated with HIV-associated PBL is unknown. This project aims to identify cancer driver genes by integrating diverse genomic data to interrogate a panel of 20 PBL and matched normal tissues for the presence of somatic point mutations, copy number alterations and genes fusion. Genomic data from this cohort will be integrated to assess the most likely driver genes using MutComfocal, and representative significant lesions will be validated in the same cases by FISH and Sanger sequencing analysis. The prevalence of genetic lesions at the top 30 candidate target genes will be assessed in a screening panel of 100 HIV associated PBL cases by targeted resequencing in the Illumina MiSeq instrument and FISH analysis. These data will then be contrasted to the genetic landscape of HIV negative DLBCL, by using exome sequencing and SNP array data generated by our team in previous studies. The results of the proposed studies are expected to further our knowledge about the molecular pathogenesis of PBL and have the potential to uncover novel molecular targets/pathways that are disrupted by genetic lesions in this disease and may be exploited as biomarkers for improved diagnostic, prognostic and/or therapeutic management of this aggressive disease. PUBLIC HEALTH RELEVANCE: Plasmablastic lymphoma (PBL) is a highly aggressive lymphoma of pre-terminally differentiated B-cells which is often associated with HIV/AIDS immunodeficiency and represents one of the two B-NHL diagnoses that have significantly increased in incidence in South Africa over the past few years. This tumor has well documented morphological and immunophenotypic features but the specific mutational signature associated with HIV-associated PBL is unknown. The proposed project aims to integrate high throughput data generated from whole exome and RNA deep sequencing in order to identify the landscape of genetic aberrations in HIV positive PBLs.