Abstract
Currently, distinguishing between benign and malignant lymphoid proliferations is based on a combination of clinical characteristics, cyto/histomorphology, immunophenotype and the identification of well-defined chromosomal aberrations. However, such diagnoses remain challenging in 10-15% of cases of lymphoproliferative disorders, and clonality assessments are often required to confirm diagnostic suspicions. In recent years, the development of new techniques for clonality detection has allowed researchers to better characterize, classify and monitor hematological neoplasms. In the past, clonality was primarily studied by performing Southern blotting analyses to characterize rearrangements in segments of the IG and TCR genes. Currently, the most commonly used method in the clinical molecular diagnostic laboratory is polymerase chain reaction (PCR), which is an extremely sensitive technique for detecting nucleic acids. This technique is rapid, accurate, specific, and sensitive, and it can be used to analyze small biopsies as well as formalin-fixed paraffin-embedded samples. These advantages make PCR-based approaches the current gold standard for IG/TCR clonality testing. Since the completion of the first human genome sequence, there has been a rapid development of technologies to facilitate high-throughput sequencing of DNA. These techniques have been applied to the deep characterization and classification of various diseases, patient stratification, and the monitoring of minimal residual disease. Furthermore, these novel approaches have the potential to significantly improve the sensitivity and cost of clonality assays and post-treatment monitoring of B- and T-cell malignancies. However, more studies will be required to demonstrate the utility, sensitivity, and benefits of these methods in order to warrant their adoption into clinical practice. In this review, recent developments in clonality testing are examined with an emphasis on highly sensitive systems for improving diagnostic workups and minimal residual disease assessments.