Adenoid cystic carcinomas (ACCs) are among the most enigmatic of human malignancies. These aggressive salivary cancers frequently recur and metastasize despite definitive treatment, with no known effective chemotherapy regimen. Here, we determined the ACC mutational landscape and report the exome or whole genome sequences of 60 ACC tumor/normal pairs. These analyses revealed a low exonic somatic mutation rate (0.31 non-silent events/megabase) and wide mutational diversity. Interestingly, mutations selectively involved chromatin state regulators, such as SMARCA2, CREBBP, and KDM6A, suggesting aberrant epigenetic regulation in ACC oncogenesis. Mutations in genes central to DNA damage and protein kinase A signaling also implicate these processes. We observed MYB-NFIB translocations and somatic mutations in MYB-associated genes, solidifying these aberrations as critical events. Lastly, we identified recurrent mutations in the FGF/IGF/PI3K pathway that may potentially offer new avenues for therapy (30%). Collectively, our observations establish a molecular foundation for understanding and exploring new treatments for ACC.
Aberrant Wnt signaling can drive cancer development. In many cancer types, the genetic basis of Wnt pathway activation remains incompletely understood. Here, we report recurrent somatic mutations of the Drosophila tumor suppressor-related gene FAT1 in glioblastoma (20.5%), colorectal cancer (7.7%), and head and neck cancer (6.7%). FAT1 encodes a cadherin-like protein, which we found is able to potently suppress cancer cell growth in vitro and in vivo, by normally binding β-catenin and antagonizing its nuclear localization. Inactivation of FAT1 via mutation therefore promotes Wnt signaling and tumorigenesis, and impacts patient survival. Together, these data strongly point to FAT1 as a tumor suppressor gene driving loss of chromosome 4q35, a prevalent region of deletion in cancer. Loss of FAT1 function is a frequent event during oncogenesis. These findings unify two outstanding questions in cancer biology: the basis of Wnt activation in non-colorectal tumors, and the identity of a 4q35 tumor suppressor.
Paired-end sequencing is a common approach for identifying structural variation (SV) in genomes. Discrepancies between the observed and expected alignments indicate potential SVs. Most SV detection algorithms use only one of the possible signals and ignore reads with multiple alignments. This results in reduced sensitivity to detect SVs, especially in repetitive regions. We introduce GASVPro, an algorithm combining both paired read and read depth signals into a probabilistic model that can analyze multiple alignments of reads. GASVPro outperforms existing methods with a 50 to 90% improvement in specificity on deletions and a 50% improvement on inversions. GASVPro is available at http://compbio.cs.brown.edu/software.
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