SUMMARY We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations, and discovered putative tumor suppressor genes by determining homozygous deletions and loss-of-heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53 and DIS3 (particularly in non-hyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g. KRAS, NRAS and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of non-mutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88, CARD11, EZH2, and CREBBP. We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO, and TNFRSF14. Further, we show that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase-mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS, BRAF, and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.next-generation sequencing | human genetics | activation-induced deaminase D iffuse large B-cell lymphoma (DLBCL) is an aggressive nonHodgkin lymphoma that affects 30,000 new patients in the United States every year (1, 2). The standard of care for the treatment of most cases of DLBCL is the R-CHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) consisting of multiagent chemotherapy plus a therapeutic antibody directed against CD20, a marker of B lymphocytes. The 3-year event-free survival rate is approximately 60%, with the majority of the remaining 40% dying of their disease (3). To date, treatment strategies to improve outcome have largely included increased doses of standard agents in the context of autologous stem cell transplantation (4). Therefore, there is a great medical need to define the genetic abnormalities that are associated with DLBCL to define novel targets for therapy.Germinal centers (GCs) in lymphoid tissues are sites of clonal expansion and editing of the Ig receptor in B lymphocytes, and this GC reaction is a physiological component of the humoral immune response. Somatic hypermutation (SHM) is part of the GC reaction, and its dysregulation contributes to the accumulation of somatic mutations in oncogenes and tumor-suppressor genes in B lymphocytes.Traditionally, DLBCL has been classified by the morphology and immunophenotype of the malignant B-cells but more recently, molecular classifications have been reported. Specifically, gene expression-based classification o...

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

Cancer treatment generally involves drugs used in combinations. Most prior work has focused on identifying and understanding synergistic drug-drug interactions; however, understanding antagonistic interactions remains an important and understudied issue. To enrich for antagonism and reveal common features of these combinations, we screened all pairwise combinations of drugs characterized as activators regulated cell death. This network is strongly enriched for antagonism, particularly a form of antagonism that we call “single agent dominance”. Single agent dominance refers to antagonisms in which a two-drug combination phenocopies one of the two agents. Dominance results from differences in death onset time, with dominant drugs acting earlier than their suppressed counterparts. We explored mechanisms by which parthanatotic agents dominate apoptotic agents, finding dominance in this scenario caused by mutually exclusive and conflicting use of PARP1. Taken together, our study reveals death kinetics as a predictive feature of antagonism, due to inhibitory crosstalk between death pathways.