Lymphomas are a group of hematological malignancies that are derived from lymphocytes and occur predominantly in lymph nodes or other lymphoid structures. More than 50 different types of lymphoma were described in the 2008 World Health Organization Classification of Tumors of the Hematopoietic and Lymphoid Tissues.1 Lymphomas are heterogeneous at the clinical, morphological, and molecular level, and have overlapping features. Mechanistic studies have shown that lymphomas are driven or affected by abnormal genetic alterations, disordered epigenetic regulation, aberrant pathway activation, and complex tumor–microenvironment interactions.2, 3, 4 Hence, the diagnosis and classification of different lymphomas and related entities can be challenging. In addition, the molecular heterogeneity underlying lymphoma aggressiveness and progression leads to patients who are treated similarly having variable outcomes.5, 6, 7 Although biomarkers, especially protein markers detected mainly by immunohistochemistry and flow cytometry, have been used widely and have contributed greatly to diagnosis, classification, and prognostication of lymphomas, novel clinically applicable, reliable, and reproducible biomarkers for lymphoma diagnosis and prognosis are still needed for better supervision of clinical trials.
01-08-2016 | Lymphoma | Article
Diagnostic and predictive biomarkers for lymphoma diagnosis and treatment in the era of precision medicine
Abstract
Lymphomas are a group of hematological malignancies derived from lymphocytes. Lymphomas are clinically and biologically heterogeneous and have overlapping diagnostic features. With the advance of new technologies and the application of efficient and feasible detection platforms, an unprecedented number of novel biomarkers have been discovered or are under investigation at the genetic, epigenetic, and protein level as well as the tumor microenvironment. These biomarkers have enabled new clinical and pathological insights into the mechanisms underlying lymphomagenesis and also have facilitated improvements in the diagnostic workup, sub-classification, outcome stratification, and personalized therapy for lymphoma patients. However, integrating these biomarkers into clinical practice effectively and precisely in daily practice is challenging. More in-depth studies are required to further validate these novel biomarkers and to assess other parameters that can affect the reproducibility of these biomarkers such as the selection of detection methods, biological reagents, interpretation of data, and cost efficiency. Despite these challenges, there are many reasons to be optimistic that novel biomarkers will facilitate better algorithms and strategies as we enter a new era of precision medicine to better refine diagnosis, prognostication, and rational treatment design for patients with lymphomas.
Mod Pathol 2016; 29: 1118–1142. doi:10.1038/modpathol.2016.92