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Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel Bayesian hierarchical modeling approach, named rDriver can achieve enhanced prediction accuracy by identifying mutations that not only have high functional impact scores but also are associated with systemic variation in gene expression levels. In examining 3,080 tumor samples from 8 cancer types in The Cancer Genome Atlas, rDriver predicted 1,389 driver mutations. Compared with existing tools, rDriver identified more low frequency mutations associated with lineage specific functional properties, timing of occurrence and patient survival. Evaluation of rDriver predictions using engineered cell-line models resulted in a positive predictive value of 0.94 in PIK3CA genes. Our study highlights the importance of integrating multi-omic data in predicting cancer driver mutations and provides a statistically rigorous solution for cancer target discovery and development. [ABSTRACT FROM AUTHOR]

The complexity of genomic alterations in cancer has made it difficult to identify oncogenic drivers for the development of targeted therapies. The study by Berger et al. in this issue of Cancer Cell demonstrates that high-throughput functional profiling can uncover impactful mutations and oncogenic driver alleles. [ABSTRACT FROM AUTHOR]

Von Hippel-Landau (VHL) protein is a potent tumor suppressor regulating numerous pathways that drive cancer, but mutations in VHL are restricted to limited subsets of malignancies. Here we identified a novel mechanism for VHL suppression in tumors that do not have inactivating mutations. Using developmental processes to uncover new pathways contributing to tumorigenesis, we found that Daam2 promotes glioma formation. Protein expression screening identified an inverse correlation between Daam2 and VHL expression across a host of cancers, including glioma. These in silico insights guided corroborating functional studies, which revealed that Daam2 promotes tumorigenesis by suppressing VHL expression. Furthermore, biochemical analyses demonstrate that Daam2 associates with VHL and facilitates its ubiquitination and degradation. Together, these studies are the first to define an upstream mechanism regulating VHL suppression in cancer and describe the role of Daam2 in tumorigenesis. [ABSTRACT FROM AUTHOR]

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2, and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Nuclear genetic disorders causing mitochondrial DNA (mtDNA) depletion are clinically and genetically heterogeneous, and the molecular etiology remains undiagnosed in the majority of cases. Through whole-exome sequencing, we identified recessive nonsense and splicing mutations in FBXL4 segregating in three unrelated consanguineous kindreds in which affected children present with a fatal encephalopathy, lactic acidosis, and severe mtDNA depletion in muscle. We show that FBXL4 is an F-box protein that colocalizes with mitochondria and that loss-of-function and splice mutations in this protein result in a severe respiratory chain deficiency, loss of mitochondrial membrane potential, and a disturbance of the dynamic mitochondrial network and nucleoid distribution in fibroblasts from affected individuals. Expression of the wild-type FBXL4 transcript in cell lines from two subjects fully rescued the levels of mtDNA copy number, leading to a correction of the mitochondrial biochemical deficit. Together our data demonstrate that mutations in FBXL4 are disease causing and establish FBXL4 as a mitochondrial protein with a possible role in maintaining mtDNA integrity and stability. [ABSTRACT FROM AUTHOR]