Beyerlein, Peter

Abstract Background Advances in next-generation DNA sequencing technologies are now enabling detailed characterization of sequence variations in cancer genomes. With whole-genome sequencing, variations in coding and non-coding sequences can be discovered. But the cost associated with it is currently limiting its general use in research. Whole-exome sequencing is used to characterize sequence variations in coding regions, but the cost associated with capture reagents and biases in capture rate limit its full use in research. Additional limitations include uncertainty in assigning the functional significance of the mutations when these mutations are observed in the non-coding region or in genes that are not expressed in cancer tissue. Results We investigated the feasibility of uncovering mutations from expressed genes using RNA sequencing datasets with a method called Variant Detection in RNA(VaDiR) that integrates 3 variant callers, namely: SNPiR, RVBoost, and MuTect2. The combination of all 3 methods, which we called Tier 1 variants, produced the highest precision with true positive mutations from RNA-seq that could be validated at the DNA level. We also found that the integration of Tier 1 variants with those called by MuTect2 and SNPiR produced the highest recall with acceptable precision. Finally, we observed a higher rate of mutation discovery in genes that are expressed at higher levels. Conclusions Our method, VaDiR, provides a possibility of uncovering mutations from RNA sequencing datasets that could be useful in further functional analysis. In addition, our approach allows orthogonal validation of DNA-based mutation discovery by providing complementary sequence variation analysis from paired RNA/DNA sequencing datasets.

ObjectiveMutations in Charcot–Marie–Tooth disease (CMT) genes are the cause of rare familial forms of polyneuropathy. Whether allelic variability in CMT genes is also associated with common forms of polyneuropathy—considered “acquired” in medical parlance—is unknown. Chemotherapy‐induced peripheral neuropathy (CIPN) occurs commonly in cancer patients and is individually unpredictable. We used CIPN as a clinical model to investigate the association of non‐CMT polyneuropathy with CMT genes.MethodsA total of 269 neurologically asymptomatic cancer patients were enrolled in the clinical trial Alliance N08C1 to receive the neurotoxic drug paclitaxel, while undergoing prospective assessments for polyneuropathy. Forty‐nine CMT genes were analyzed by targeted massively parallel sequencing of genomic DNA from patient blood.ResultsA total of 119 (of 269) patients were identified from the 2 ends of the polyneuropathy phenotype distribution: patients that were most and least susceptible to paclitaxel polyneuropathy. The CMT gene PRX was found to be deleteriously mutated in patients who were susceptible to CIPN but not in controls (p = 8 × 10−3). Genetic variation in another CMT gene, ARHGEF10, was highly significantly associated with CIPN (p = 5 × 10−4). Three nonsynonymous recurrent single nucleotide variants contributed to the ARHGEF10 signal: rs9657362, rs2294039, and rs17683288. Of these, rs9657362 had the strongest effect (odds ratio = 4.8, p = 4 × 10−4).InterpretationThe results reveal an association of CMT gene allelic variability with susceptibility to CIPN. The findings raise the possibility that other acquired polyneuropathies may also be codetermined by genetic etiological factors, of which some may be related to genes already known to cause the phenotypically related Mendelian disorders of CMT. Ann Neurol 2014;76:727–737