Max-Planck-Institute for Informatics, Campus E1.4, Saarbrücken, Germany.
PLoS Comput Biol. 2013;9(10):e1003228. doi: 10.1371/journal.pcbi.1003228. Epub 2013 Oct 3.
In excess of 12% of human cancer incidents have a viral cofactor. Epidemiological studies of idiopathic human cancers indicate that additional tumor viruses remain to be discovered. Recent advances in sequencing technology have enabled systematic screenings of human tumor transcriptomes for viral transcripts. However, technical problems such as low abundances of viral transcripts in large volumes of sequencing data, viral sequence divergence, and homology between viral and human factors significantly confound identification of tumor viruses. We have developed a novel computational approach for detecting viral transcripts in human cancers that takes the aforementioned confounding factors into account and is applicable to a wide variety of viruses and tumors. 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 positive and negative controls to the human and all known viral genomes in order to detect both known and unknown viruses. Analysis of controls, comparisons with related methods, and statistical estimates demonstrate the high sensitivity of our approach. Detailed investigation of putative viral 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.
超过 12%的人类癌症与病毒因素有关。对特发性人类癌症的流行病学研究表明，还有其他肿瘤病毒有待发现。最近测序技术的进步使得能够对人类肿瘤转录组进行病毒转录本的系统筛选。然而，技术问题，如大量测序数据中病毒转录本的低丰度、病毒序列的差异以及病毒和人类因素之间的同源性，极大地干扰了肿瘤病毒的鉴定。我们开发了一种新的计算方法，用于检测人类癌症中的病毒转录本，该方法考虑了上述混杂因素，适用于广泛的病毒和肿瘤。我们应用该方法对神经母细胞瘤进行了首次系统搜索，神经母细胞瘤是婴儿最常见的癌症。这种疾病的不同临床进展以及相关的流行病学和病毒学发现高度提示存在致病的协同因素。然而，神经母细胞瘤的病毒病因目前存在争议。我们将 14 份神经母细胞瘤转录组以及阳性和阴性对照与人类和所有已知病毒基因组进行了映射，以检测已知和未知的病毒。对对照的分析、与相关方法的比较以及统计估计表明，我们的方法具有很高的灵敏度。对神经母细胞瘤样本中假定的病毒转录本的详细研究没有提供任何已知人类病毒存在的证据。同样，对嵌合转录本的从头组装和分析也没有导致与新的人类病原体相关的表达特征。虽然混杂因素，如样本稀释或进展性肿瘤中的病毒清除，可能会掩盖数据中的病毒协同因素，但我们的方法具有很高的灵敏度和分析的生物学重复次数，这在原则上降低了这种可能性。因此，我们的结果表明，转移性神经母细胞瘤的常见病毒协同因素不太可能存在。
