![]() Next-generation sequencing (NGS) data was analyzed to comprehensively provide genome-wide information on structural, mutational, and copy number (CN) drivers, which can provide a global view of association with outcome. As part of the Myeloma Genome Project (MGP), we have established the largest repository of uniformly called molecular data associated with clinical outcomes in NDMM, providing adequate power to identify the variables associated with very high-risk groups. While a number of mutational markers have been identified as being associated with prognosis, there has been no comprehensive approach to integrate such markers into risk stratification approaches because of small study size, use of focused disease panels, and lack of follow-up, all of which can confound interpretation of the results. Thus, although high-risk groups can be identified, the definition of these groups and the specificity for very poor outcome varies, confounding effective clinical decision making and the design of risk-adjusted trials.ĭNA drivers of biological activity are key determinants of cancer behavior, are robust, and easily measured in the clinical laboratory. The high-risk group in the R-ISS classification comprised 10% and had a median PFS of 29 months and 5-year OS of 40%. The revised ISS (R-ISS) is the most recent risk stratification approach and incorporates the genetic markers t(4 14) and del17p, but not 1q gain or mutational data from TP53 as the data were not available. For example, the high-risk group identified by the ISS is 33.6% with a median overall survival (OS) of 29 months, while the International Myeloma Working Group (IMWG) identified a high-risk group of 20% with a 4-year progression free survival (PFS) of 12% and OS of 35%. Current approaches rely upon cytogenetic and clinical biomarkers to define high-risk, including the International Staging System (ISS) group III, the presence of adverse translocations, and 17p deletion (del17p) however, non-uniform application and interpretation of these variables have resulted in the description of different high-risk groups with varying outcomes. Multiple definitions of high-risk have evolved over time, but today no definition is uniformly accepted or implemented in clinical practice. Patients with high-risk disease are associated with a poor prognosis, but identifying these patients at diagnosis remain a challenge. ![]() We have made consistent therapeutic progress for patients with newly diagnosed multiple myeloma (NDMM) over the last two decades however, not all patients, especially high-risk patients, have uniformly derived the benefit. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches. ![]() A high-risk subgroup was defined by recursive partitioning using either a) bi-allelic TP53 inactivation or b) amplification (≥4 copies) of CKS1B (1q21) on the background of International Staging System III, comprising 6.1% of the population (median PFS = 15.4 months OS = 20.7 months) that was validated in an independent dataset. Integrating DNA drivers and clinical data into a Cox model using 784 patients with ISS, age, PFS, OS, and genomic data, the model has a cumlative R 2 of 34.3% for PFS and 46.5% for OS. Whole-genome and exome data from 1273 NDMM patients identified genetic factors that contribute significantly to progression free survival (PFS) and overall survival (OS) (cumulative R 2 = 18.4% and 25.2%, respectively). In a genome-wide analysis of the largest set of molecular and clinical data established to date from NDMM, as part of the Myeloma Genome Project, we have defined DNA drivers of aggressive clinical behavior. Inclusion of molecular features into risk stratification could resolve the current challenges. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. ![]() Leukemia volume 33, pages 159–170 ( 2019) Cite this article Multiple myeloma gammopathies A high-risk, Double-Hit, group of newly diagnosed myeloma identified by genomic analysis
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |