Sensitive Detection of Viral Transcripts in Human Tumor Transcriptomes. Detection of Viral Transcripts in Human Tumors

We have developed a novel computational approach for detecting viral transcripts in human cancers applicable to a wide variety of viruses and tumors that takes the aforementioned confounding factors into account. We apply the approach to conducting the first systematic search for viruses in neuroblastoma, the most common cancer in infancy. The diverse clinical progression of this disease as well as related epidemiological and virological findings are highly suggestive of a pathogenic cofactor. However, a viral etiology of neuroblastoma is currently contested. We mapped 14 transcriptomes of neuroblastoma as well as several positive control transcriptomes to the human and all known viral genomes in order to detect both known and unknown viruses. Analysis of positive controls, comparisons with related methods, and statistical estimates demonstrate the high sensitivity of our approach. However, detailed analysis of putative vi- ral transcripts within neuroblastoma samples did not provide evidence for the existence of any known human viruses. Likewise, de-novo assembly and analysis of chimeric transcripts did not result in expression signatures associated with novel human pathogens. While confounding factors such as sample dilution or viral clearance in progressed tumors may mask viral cofactors in the data, in principle, this is rendered less likely by the high sensitivity of our approach and the number of biological replicates analyzed. Therefore, our results suggest that frequent viral cofactors of metastatic neuroblastoma are unlikely.