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.