An ultra-deep sequencing strategy to detect sub-clonal TP53 mutations in presentation chronic lymphocytic leukemia cases using multiple polymerases

Chronic lymphocytic leukaemia (CLL) is the most common clonal B-cell disorder characterized by clonal diversity, a relapsing and remitting course, and in its aggressive forms remains largely incurable. Current front-line regimes include agents such as fludarabine, which act primarily via the DNA damage response pathway. Key to this is the transcription factor p53. Mutations in the TP53 gene, altering p53 functionality, are associated with genetic instability, and are present in aggressive CLL. Furthermore, the emergence of clonal TP53 mutations in relapsed CLL, refractory to DNA-damaging therapy, suggests that accurate detection of sub-clonal TP53 mutations prior to and during treatment may be indicative of early relapse. In this study, we describe a novel deep sequencing workflow using multiple polymerases to generate sequencing libraries (MuPol-Seq), facilitating accurate detection of TP53 mutations at a frequency as low as 0.3%, in presentation CLL cases tested. As these mutations were mostly clustered within the regions of TP53 encoding DNA-binding domains, essential for DNA contact and structural architecture, they are likely to be of prognostic relevance in disease progression. The workflow described here has the potential to be implemented routinely to identify rare mutations across a range of diseases

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL