VirusSeq: software to identify viruses and their integration sites using next-generation sequencing of human cancer tissue

Chen, Yunxin; Yao, Hui; Thompson, Erika J.; Tannir, Nizar M.; Weinstein, John N.; Su, Xiaoping

doi:10.1093/bioinformatics/bts665

Cited by 152 publications

(159 citation statements)

References 11 publications

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“…HPV status detected by our method correlated with perfect sensitivity and specificity with known clinicopathologic variables and with established methods for HPV detection (colorimetric in situ hybridization and/or p16 ink4a expression) (28). For this HNSCC data set, the sensitivity for HPV16 detection was 100%, with 95% confidence intervals (CI) of 67.6 to 100%, and specificity for HPV16 detection was 100%, with 95% CI of 90.4 to 100%, as reported previously (39).…”

Section: Resultssupporting

confidence: 80%

“…After confirming the accuracy of our tool (39) in malignancies that are known to be associated with DNA viruses, we turned our attention to screening all remaining TCGA tumors on which RNA-Seq data were available. Our analysis showed no evidence of transcribed viral elements in any of the following neoplasms: acute myeloid leukemia, breast carcinoma (ductal and lobular), colonic and rectal adenocarcinoma, lung adenocarcinoma, prostate adenocarcinoma, cutaneous melanoma, ovarian serous cystadenocarcinoma, papillary renal cell carcinoma, thyroid carcinoma, lowergrade glioma, and glioblastoma multiforme.…”

Section: Resultsmentioning

confidence: 99%

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Landscape of DNA Virus Associations across Human Malignant Cancers: Analysis of 3,775 Cases Using RNA-Seq

Khoury¹,

Tannir

Williams³

et al. 2013

J Virol

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198

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Elucidation of tumor-DNA virus associations in many cancer types has enhanced our knowledge of fundamental oncogenesis mechanisms and provided a basis for cancer prevention initiatives. RNA-Seq is a novel tool to comprehensively assess such associations. We interrogated RNA-Seq data from 3,775 malignant neoplasms in The Cancer Genome Atlas database for the presence of viral sequences. Viral integration sites were also detected in expressed transcripts using a novel approach. The detection capacity of RNA-Seq was compared to available clinical laboratory data. Human papillomavirus (HPV) transcripts were detected using RNA-Seq analysis in head-and-neck squamous cell carcinoma, uterine endometrioid carcinoma, and squamous cell carcinoma of the lung. Detection of HPV by RNA-Seq correlated with detection by in situ hybridization and immunohistochemistry in squamous cell carcinoma tumors of the head and neck. Hepatitis B virus and Epstein-Barr virus (EBV) were detected using RNA-Seq in hepatocellular carcinoma and gastric carcinoma tumors, respectively. Integration sites of viral genes and oncogenes were detected in cancers harboring HPV or hepatitis B virus but not in EBV-positive gastric carcinoma. Integration sites of expressed viral transcripts frequently involved known coding areas of the host genome. No DNA virus transcripts were detected in acute myeloid leukemia, cutaneous melanoma, low-and high-grade gliomas of the brain, and adenocarcinomas of the breast, colon and rectum, lung, prostate, ovary, kidney, and thyroid. In conclusion, this study provides a large-scale overview of the landscape of DNA viruses in human malignant cancers. While further validation is necessary for specific cancer types, our findings highlight the utility of RNA-Seq in detecting tumor-associated DNA viruses and identifying viral integration sites that may unravel novel mechanisms of cancer pathogenesis.

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Section: Resultssupporting

confidence: 80%

Section: Resultsmentioning

confidence: 99%

Landscape of DNA Virus Associations across Human Malignant Cancers: Analysis of 3,775 Cases Using RNA-Seq

Khoury¹,

Tannir

Williams³

et al. 2013

J Virol

Self Cite

198

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“…Several groups have developed and discussed virus detection methods based on subtraction of nonhuman sequences from human samples (3)(4)(5). For example, VirusSeq (5) uses RNAseq as input, and performs two filtrations to distinguish viral and non-viral sequences: the minimum number of reads aligned to a viral sequence (set at 1000 reads) and the coverage of the aligned reads (threshold of 30X).…”

Section: Discussionmentioning

confidence: 99%

“…Researchers have developed some computational tools for the discovery and identification of viruses in NGS data from human tissues (3)(4)(5), including viral integration sites (6)(7)(8)(9)(10). However, all previous studies used subtractive analyses.…”

Section: Introductionmentioning

confidence: 99%

“…used a subtractive approach to detect viruses (4); they considered the reads which were not mapped to the human genome after filtrations to be "candidate nonhuman pathogen-derived reads." Another set of researchers used a subtractive approach with thresholds for coverage and minimum number of reads, which were mapped to virus genomes in their defined virus database (5). They used two different filtrations: (I) the number of mapped reads to any virus (>1000) and (II) the minimum coverage of reads (30X).…”

Section: Introductionmentioning

confidence: 99%

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VirTect: a computational method for detecting virus species from RNA-Seq and its application in head and neck squamous cell carcinoma

Khan

Chen

et al. 2018

Preprint

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Next generation sequencing (NGS) provides an opportunity to detect viral species from RNAseq data on human tissues, but existing computational approaches do not perform optimally on clinical samples. We developed a bioinformatics method called VirTect for detecting viruses in neoplastic human tissues using RNA-seq data. Here, we used VirTect to analyze RNA-seq data from 363 HNSCC (head and neck squamous cell carcinoma) patients and identified 22 HPV-induced HNSCCs. These predictions were validated by manual review of pathology reports on histopathologic specimens. Our results suggest that HPV-induced HNSCC involves unique mechanisms of carcinogenesis, so understanding these molecular mechanisms will have a significant impact on therapeutic approaches and outcomes. In summary, VirTect can be an effective solution for the detection of viruses with NGS data, and can facilitate the clinicopathologic characterization of various types of cancers with broad applications for oncology.

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Finding Pathogenic Nucleic Acid Sequences in Next Generation Sequencing Data

Parfenov

Seidman

2015

CP Human Genetics

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Viruses and bacteria are established as one of the main causes of human diseases from hepatitis to cancer. Recently, the presence of such pathogens has been extensively studied using human whole genome and transcriptome sequencing data. However, detecting and studying pathogens via next generation sequencing data is a challenging task in terms of time and computational resources. In this protocol we give instructions for a simple and quick method to find pathogenic DNA or RNA and detect possible integration of the pathogen genome into the host genome.

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VirusSeq: software to identify viruses and their integration sites using next-generation sequencing of human cancer tissue

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 152 publications

References 11 publications

Landscape of DNA Virus Associations across Human Malignant Cancers: Analysis of 3,775 Cases Using RNA-Seq

Landscape of DNA Virus Associations across Human Malignant Cancers: Analysis of 3,775 Cases Using RNA-Seq

VirTect: a computational method for detecting virus species from RNA-Seq and its application in head and neck squamous cell carcinoma

Finding Pathogenic Nucleic Acid Sequences in Next Generation Sequencing Data

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