**2.2. Information concerning the tumor genome into the routine clinical management is useful for better treatment strategy selection, delivering "the right treatment to the right patient at the right time"**

The best efficacy would be achieved if treatment is directed toward specific genetic lesions within malignant cells, which have a key role in the pathogenesis of the respective disease, while minimizing damage to normal, healthy cells [11]. Unfortunately, several limitations still restrict the widespread application of this personalized approach, such as (1) various technological and methodological diagnostic problems; (2) insufficient level of our knowledge about the molecular mechanisms involved in the pathogenesis of different malignancies and the prognostic significance of individual molecular abnormalities; and (3) relatively low number of available targeted therapeutic agents approved for clinical use. Therefore, in practical terms, the personalized approach in hemato-oncology comprises а personalized risk stratification: refinement of clinical prognostic models for a better risk stratification and identification of biologic subtypes within pathologically similar diseases; identification of patients suitable for targeted treatment and "response-adapted" changes in therapy in individual patients [12].

In several hematological malignancies, such as acute leukemias, MDS, chronic lymphocytic leukemia (CLL), and so on, cytogenetics remains the most important disease-related prognostic factor for predicting remission rate, relapse, and overall survival (OS) [13–15]. In addition, recent genetic studies identified a large number of mutations in most of the hematological malignancies that point to novel pathways involved in the pathogenesis of the respective disease, and some of these molecular abnormalities have allowed substantial improvements in clinical decision making. As a result, the current prognostic models based on genetic abnormalities are nowadays subject to change as new cytogenetic and mutational findings are revealed, contributing to refine better and better these approaches.

Multiple myeloma (MM) is an incurable malignancy characterized by the clonal proliferation of neoplastic plasma cells in the bone marrow that produce monoclonal protein that can be detected in the serum or urine. MM is a highly heterogeneous disease composed of multiple molecularly defined subtypes, each with varying clinico-pathological features and disease outcomes. Cytogenetically, there are two main subtypes: (1) hyperdiploid myeloma—characterized by trisomies of certain odd-numbered chromosomes and generally associated with a better survival; and (2) nonhyperdiploid myeloma—characterized by translocations of the immunoglobulin heavy chain alleles at chromosome 14q32 with various partner chromosomes, the most important of which are 4, 6, 11, 16, and 20. Several abnormalities have been reported to be associated with poor prognosis, such as t(4;14)(p16;q32)/IGH-MMSET, t(14;16)(p32;q23)/

IGG-MAF, t(14;20)(q32;q11)/IGG-MAFB, del(17p), and gains of 1q, despite that the adverse effect of t(4,14) can be partially abrogated by bortezomib-based treatment [16]. Technological development provides various opportunities to evaluate the tumor genome. In this regard, Sridurga Mithraprabhu and Andrew Spencer provide a comprehensive chapter on the possible role of liquid biopsies in multiple myeloma as an innovative methodology for diagnostics and disease monitoring, implementing the analysis of circulating cell-free nucleic acids (CFNAs) and circulating tumor cells (CTCs) as representative of the underlying mutational profile of a cancer as well as of extracellular RNA (exRNA) that can be utilized as a prognostic biomarker. The authors discuss the potential of these noninvasive, repeatable biomarkers to provide additional information as an adjunct to bone marrow biopsies and conventional disease variables in multiple myeloma.
