Clinical implication of genome-wide profiling in diffuse large B-cell lymphoma and other subtypes of B-cell lymphoma

The differentiation of lymphoid cells is tightly regulated by transcription factors at various stages during their development. During the maturation processes, different genomic alterations or aberrations such as chromosomal translocation, mutation and deletions may occur that can eventually result in distinct biological and clinical tumors. The different differentiation stages create heterogeneity in lymphoid malignancies, which can complicate the diagnosis. The initial diagnostic scheme for lymphoid diseases was coined by Rappaport followed by Revised European and American Classification of Lymphoid Neoplasms (REAL) and World Health Organization (WHO) classifications. These classification methods were based on histological, immunophenotypic and cytogenetic markers and widely accepted by pathologists and oncologists worldwide. During last several decades, great progress has been made in understanding the etiology, pathogenesis and molecular biology of malignant lymphoma. However, detailed knowledge in the molecular mechanism of lymphomagenesis is largely unknown. New therapeutic protocols based on the new classification have been on clinical trials, but with little success. Therefore, it is imperative to understand the basic biology of the tumor at molecular level. One important approach will be to measure the activity of the tumor genome and this can partly be achieved by the measurement of whole cellular mRNA. One of the key technologies to perform a high-throughput analysis is DNA microarray technology. The genome-wide transcriptional measurement, also called gene expression profile (GEP) can accurately define the biological phenotype of the tumor. In this review, important discoveries made by genome-wide GEP in understanding the biology of lymphoma and additionally the diagnostic and prognostic value of microarrays are discussed.

Keywords
Classification, diffuse large B-cell lymphomas, gene expression profiling, prognosis, targeted therapy