Advances in Classical Hodgkin Lymphoma Biology: New Prognostic Factors and Outcome Prediction Using Gene Expression Signatures

March 27, 2012

Beatriz Sánchez-Espiridión, Juan F. García and Margarita Sánchez-Beato (2012).

Advances in Classical Hodgkin Lymphoma Biology: New Prognostic Factors and Outcome Prediction Using Gene Expression Signatures, Hodgkin's Lymphoma, Dr. Nima Rezaei (Ed.), ISBN: 978-953-51-0402-5, InTech

Introduction

Transcriptional analysis of cancer is a powerful and increasingly useful tool in biomedical research. Many studies are revealing transcriptional patterns using gene expression profiling (GEP) analyses, increasing our knowledge of cancer pathogenesis, identifying signatures related to prognosis and revealing the variation in responses to therapy.

Gene-expression signatures have been identified for the most common types of non- Hodgkin lymphomas. These studies have demonstrated the ability of these technologies to identify pathogenic mechanisms, new molecular targets and biological processes involved in lymphomagenesis (Margalit, Somech et al. 2005). Thus, in the last decade molecular subtypes of diffuse large B-cell, namely germinal center B-cell and activated B-cell-like types, have been identified, each of which has their particular prognostic and therapeutic implications. Likewise, GEP studies have identified relevant molecular characteristics in follicular lymphomas (Alizadeh, Eisen et al. 2000; Alizadeh, Ross et al. 2001), primary mediastinal large B-cell lymphomas (Rosenwald, Wright et al. 2003), Burkitt lymphomas (Dave, Fu et al. 2006; Hummel, Bentink et al. 2006) or mantle cell lymphomas (Rosenwald, Wright et al. 2003). Specific therapeutic targets are likely to emerge from these insights into the molecular pathogenesis of the different lymphomas.

Regarding Hodgkin lymphoma (HL), GEP has provided vital clues and new insights into its pathogenesis (Devilard, Bertucci et al. 2002). More recently, GEP has also identified specific gene patterns related to tumor aggressivity and/or sensitivity to therapy (Sanchez-Aguilera, Montalban et al. 2006; Chetaille, Bertucci et al. 2009; Steidl, Lee et al. 2010).

DNA microarray assays require well-preserved RNA, which is usually extracted from frozen tissue, so this technology is not adequate for clinical applications. However, new strategies for translating this information into clinical practice are currently being investigated, through the identification of smaller gene signatures and validation of them
for clinical practice using simple, robust, and conventional assays such as quantitative real time PCR (qRT-PCR) (Sanchez-Espiridion, Sanchez-Aguilera et al. 2009; Sanchez-Espiridion, Montalban et al. 2010).

In this chapter we review recent advances in the understanding of HL biology, new data and improvements in the clinical management of patients in the future, from the application of high-throughput molecular analyses, including gene and microRNA (miRNA) expression, immunohistochemistry and others.