No abstract

We have refined our understanding of genetic events in myeloma and identified clinically relevant mutations that may be used to better stratify patients at presentation.

Here we report the sequence of the region that determines rapid allograft rejection in chickens, the chicken major histocompatibility complex (MHC). This 92-kilobase region of the B locus contains only 19 genes, making the chicken MHC roughly 20-fold smaller than the human MHC. Virtually all the genes have counterparts in the human MHC, defining a minimal essential set of MHC genes conserved over 200 million years of divergence between birds and mammals. They are organized differently, with the class III region genes located outside the class II and class I region genes. The absence of proteasome genes is unexpected and might explain unusual peptide-binding specificities of chicken class I molecules. The presence of putative natural killer receptor gene(s) is unprecedented and might explain the importance of the B locus in the response to the herpes virus responsible for Marek's diseases. The small size and simplicity of the chicken MHC allows co-evolution of genes as haplotypes over considerable periods of time, and makes it possible to study the striking MHC-determined pathogen-specific disease resistance at the molecular level.

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1273 newly diagnosed patients with MM, we identified 63 driver genes, some of which are novel, including ,, ,, and Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more driver gene abnormalities are associated with worse outcomes, as are identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in, , and; t(11;14) with mutations in and; t(14;16) with mutations in ,, , and; and hyperdiploidy with gain 11q, mutations in , and rearrangements. These associations indicate that the genomic landscape of myeloma is predetermined by the primary events upon which further dependencies are built, giving rise to a nonrandom accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens.

Patients with newly diagnosed multiple myeloma (NDMM) with high-risk disease are in need of new treatment strategies to improve the outcomes. Multiple clinical, cytogenetic, or gene expression features have been used to identify high-risk patients, each of which has significant weaknesses. Inclusion of molecular features into risk stratification could resolve the current challenges. 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. 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 = 18.4% and 25.2%, respectively). 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 of 34.3% for PFS and 46.5% for OS. 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. Double-Hit patients have a dire prognosis despite modern therapies and should be considered for novel therapeutic approaches.

To obtain a comprehensive genomic profile of presenting multiple myeloma cases we performed high-resolution single nucleotide polymorphism mapping array analysis in 114 samples alongside 258 samples analyzed by U133 Plus 2.0 expression array (Affymetrix). We examined DNA copy number alterations and loss of heterozygosity (LOH) to define the spectrum of minimally deleted regions in which relevant genes of interest can be found. The most frequent deletions are located at 1p (30%), 6q (33%), 8p (25%), 12p (15%), 13q (59%), 14q (39%), 16q (35%), 17p (7%), 20 (12%), and 22 (18%). In addition, copy number-neutral LOH, or uniparental disomy, was also prevalent on 1q (8%), 16q (9%), and X (20%), and was associated with regions of gain and loss. Based on fluorescence in situ hybridization and expression quartile analysis, genes of prognostic importance were found to be located at 1p (FAF1, CDKN2C), 1q (ANP32E), and 17p (TP53). In addition, we identified common homozygously deleted genes that have functions relevant to myeloma biology. Taken together, these analyses indicate that the crucial pathways in myeloma pathogenesis include the nuclear factor-B pathway, apoptosis, cell-cycle regulation, Wnt signaling, and histone modifications. This study was registered at http://isrctn.org as ISRCTN68454111. (Blood. 2010;116(15): e56-e65)

The association of genetic lesions detected by FISH with survival was analyzed in 1069 patients with newly presenting myeloma treated in the Medical Research Council (MRC) Myeloma IX trial, with the aim of identifying patients associated with the worst prognosis. A comprehensive FISH panel was performed, and the lesions associated with short PFS and OS in multivariate analysis were +1q21, del(17p13) and an adverse IGH translocation group incorporating t(4;14), t(14;16) and t(14;20). These lesions frequently co-segregated, and there was an association between the accumulation of these adverse FISH lesions and a progressive impairment of survival. This observation was used to define a series of risk groups based on number of adverse lesions. Taking this approach we defined a favorable risk group by the absence of adverse genetic lesions, an intermediate group with 1 adverse lesion and a high risk group defined by the co-segregation of >1 adverse lesion. This genetic grouping was independent of the ISS and so was integrated with the ISS to identify an ultra-high risk group defined by ISS II or III and >1 adverse lesion. This group constituted 13.8 % of patients and was associated with a median OS of 19.4 months.

In multiple myeloma malignant plasma cells expand within the bone marrow. Since this site is well-perfused, a rapid dissemination of “fitter” clones may be anticipated. However, an imbalanced distribution of multiple myeloma is frequently observed in medical imaging. Here, we perform multi-region sequencing, including iliac crest and radiology-guided focal lesion specimens from 51 patients to gain insight into the spatial clonal architecture. We demonstrate spatial genomic heterogeneity in more than 75% of patients, including inactivation of CDKN2C and TP53, and mutations affecting mitogen-activated protein kinase genes. We show that the extent of spatial heterogeneity is positively associated with the size of biopsied focal lesions consistent with regional outgrowth of advanced clones. The results support a model for multiple myeloma progression with clonal sweeps in the early phase and regional evolution in advanced disease. We suggest that multi-region investigations are critical to understanding intra-patient heterogeneity and the evolutionary processes in multiple myeloma.