Detection of DNA viruses in prostate cancer

Comparative Study Analysis of Epstein-Barr Virus Infection: Tissue Versus Blood Samples in Patients With Prostatic Adenocarcinoma and Its Correlation With Clinicopathological Parameters

Prostate cancer (PCa) is the most frequently diagnosed cancer and a leading cause of cancer-related mortality in men. The diagnosis and treatment of PCa carry considerable medical, psychological, and economic implications. Among the risk factors contributing to cancer, viral infections, notably Epstein-Barr virus (EBV), play a significant role. It is recognized as an oncogenic virus associated with various lymphomas, nasopharyngeal carcinomas, and breast cancer cases but its role in PCa remains unclear. This study aims to contrast the prevalence of EBV in blood and tissue samples of PCa patients and assess its correlation with tumor clinicopathological criteria. In this prospective study, 50 fresh biopsies and 50 blood samples were collected from patients with a confirmed diagnosis of PCa. EBV DNA was detected using polymerase chain reaction (PCR). A statistical analysis was then conducted to examine the correlation between EBV prevalence and PCa clinicopathological characteristics. EBV DNA was detected in 38% of PCa blood samples and 64% of PCa tissue samples, with a higher prevalence in tissue samples (p = 0.009). The statistical analysis revealed a significant correlation between EBV infection and pathological Gleason score (p = 0.041) in PCa tissue, as well as pathological T-stage (p = 0.02) in PCa blood. The results show that patients with PCa have higher levels of EBV in their tissues than in their blood, suggesting that EBV may play an important role in the etiology of PCa. This paves the way for further research into the function of EBV as a potential biomarker in the development and progression of prostate carcinoma in order to combat oncogenic viruses.

Human papillomavirus and prostate cancer: systematic review and meta-analysis

The involvement of human papillomavirus (HPV) in the prostate carcinogenesis is a controversial issue. The presented meta-analysis was carried out to systematize the currently available research results regarding this question. The meta-analysis includes case-control studies from 1991 to 2022, which were collected from publicly available bibliometric databases. The meta-analysis was performed using Meta-Essentials_1.5 software. We used Begg's and Egger's methods to assess publication bias. Cochran's Q test was used to assess heterogeneity and the I2 index was employed for calculating the variation in the pooled estimations. The analysis was based on data from 27 case-control studies, which in total yielded 1607 tumour tissue samples of prostate and 1515 control samples (317 samples of normal tissue, 1198 samples of benign prostatic hyperplasia (BPH)). According to the data obtained, there was high risk of prostate cancer by HPV infection in both cases. HPV was found in prostate cancer in 25.8% of cases, while in normal tissue samples the virus was detected in 9.2% of cases and in 17.4% with BPH as a control. In particular, more studies on the association of HPV and prostate cancer are needed to prove the role of HPV in the development of prostate cancer. In addition to the controversial question of whether HPV infection is associated with prostate cancer risk, it is worth considering whether the samples used as a control have an impact on the results. The impact of HPV in prostate tumour tissue samples on outcome should also be investigated.

Merkel Cell Polyomavirus (MCPyV) and Cancers: Emergency Bell or False Alarm?

Merkel cell polyomavirus (MCPyV), the sole member of Polyomavirus associated with oncogenesis in humans, is the major causative factor of Merkel cell carcinoma (MCC), a rare, neuroendocrine neoplasia of the skin. Many aspects of MCPyV biology and oncogenic mechanisms remain poorly understood. However, it has been established that oncogenic transformation is the outcome of the integration of the viral genome into the host DNA. The high prevalence of MCPyV in the population, along with the detection of the virus in various human tissue samples and the strong association of MCPyV with the emergence of MCC, have prompted researchers to further investigate the role of MCPyV in malignancies other than MCC. MCPyV DNA has been detected in several different non-MCC tumour tissues but with significantly lower prevalence, viral load and protein expression. Moreover, the two hallmarks of MCPyV MCC have rarely been investigated and the studies have produced generally inconsistent results. Therefore, the outcomes of the studies are inadequate and unable to clearly demonstrate a direct correlation between cellular transformation and MCPyV. This review aims to present a comprehensive recapitulation of the available literature regarding the association of MCPyV with oncogenesis (MCC and non-MCC tumours).

Differential Microbial Signature Associated With Benign Prostatic Hyperplasia and Prostate Cancer

Apart from other risk factors, chronic inflammation is also associated with the onset of Prostate Cancer (PCa), wherein pathogen infection and tissue microbiome dysbiosis are known to play a major role in both inflammatory response and cancer development. However, except for a few studies, the link between microbes and PCa remained poorly understood. To explore the potential microbiome signature associated with PCa in Indian patients, we investigated differential compositions of commensal bacteria among patients with benign prostatic hyperplasia (BPH) and PCa using 16S rRNA amplicon sequencing followed by qPCR analyses using two distinct primer sets. Using two independent cohorts, we show that Prevotella copri, Cupriavidus campinensis, and Propionibacterium acnes represent the three most abundant bacteria in diseased prostate lesions. LEfSe analyses identified that while Cupriavidus taiwanensis and Methylobacterium organophilum are distinctly elevated in PCa samples, Kocuria palustris and Cellvibrio mixtus are significantly enriched in BPH samples. Furthermore, we identify that a number of human tumor viruses, including Epstein-Barr virus (EBV) and hepatitis B virus (HBV), along with two high-risk human papillomaviruses - HPV-16 and HPV-18, are significantly associated with the PCa development and strongly correlated with PCa bacterial signature. The study may thus offer to develop a framework for exploiting this microbial signature for early diagnosis and prognosis of PCa development.

The role of viruses in adenocarcinoma development

Cancer is a leading public health issue that accounts for million deaths around the world every year. Human cancers contain over 100 types, which are categorized into different groups. Adenocarcinoma is one of those categories of cancer that begins from the glans and involves various tissues such as lung, esophagus, pancreas, prostate and colorectal. A range of risk factors has been identified for the development and progression of adenocarcinomas. One of these risk factors are viruses that serves special mechanisms to affect important host cell factors and tumorigenic pathways, contributing in development and promotion of adenocarcinomas. Here, we summarized the main viruses and their mechanisms implicated in the course of various adenocarcinomas development.

The Human Microbiome in Relation to Cancer Risk: A Systematic Review of Epidemiologic Studies

The microbiome has been hypothesized to play a role in cancer development. Because of the diversity of published data, an overview of available epidemiologic evidence linking the microbiome with cancer is now needed. We conducted a systematic review using a tailored search strategy in Medline and EMBASE databases to identify and summarize the current epidemiologic literature on the relationship between the microbiome and different cancer outcomes published until December 2019. We identified 124 eligible articles. The large diversity of parameters used to describe microbial composition made it impossible to harmonize the different studies in a way that would allow meta-analysis, therefore only a qualitative description of results could be performed. Fifty studies reported differences in the gut microbiome between patients with colorectal cancer and various control groups. The most consistent findings were for Fusobacterium, Porphyromonas, and Peptostreptococcus being significantly enriched in fecal and mucosal samples from patients with colorectal cancer. For the oral microbiome, significantly increased and decreased abundance was reported for Fusobacterium and Streptococcus, respectively, in patients with oral cancer compared with controls. Overall, although there was a large amount of evidence for some of these alterations, most require validation in high-quality, preferably prospective, epidemiologic studies.

Prostate carcinogenesis: inflammatory storms

Prostate cancer is a major cause of cancer morbidity and mortality. Intra-prostatic inflammation is a risk factor for prostate carcinogenesis, with diet, chemical injury and an altered microbiome being causally implicated. Intra-prostatic inflammatory cell recruitment and expansion can ultimately promote DNA double-strand breaks and androgen receptor activation in prostate epithelial cells. The activation of the senescence-associated secretory phenotype fuels further 'inflammatory storms', with free radicals leading to further DNA damage. This drives the overexpression of DNA repair and tumour suppressor genes, rendering these genes susceptible to mutagenic insults, with carcinogenesis accelerated by germline DNA repair gene defects. We provide updates on recent advances in elucidating prostate carcinogenesis and explore novel therapeutic and prevention strategies harnessing these discoveries.

Microbiome signatures in prostate cancer

We have established a microbiome signature for prostate cancer using an array-based metagenomic and capture-sequencing approach. A diverse microbiome signature (viral, bacterial, fungal and parasitic) was observed in the prostate cancer samples compared with benign prostate hyperplasia controls. Hierarchical clustering analysis identified three distinct prostate cancer-specific microbiome signatures. The three signatures correlated with different grades, stages and scores of the cancer. Thus, microbiome signature analysis potentially provides clinical diagnosis and outcome predictions. The array data were validated by PCR and targeted next-generation sequencing (NGS). Specific NGS data suggested that certain viral genomic sequences were inserted into the host somatic chromosomes of the prostate cancer samples. A randomly selected group of these was validated by direct PCR and sequencing. In addition, PCR validation of Helicobacter showed that Helicobacter cagA sequences integrated within specific chromosomes of prostate tumor cells. The viral and Helicobacter integrations are predicted to affect the expression of several cellular genes associated with oncogenic processes.

Screening for chronic prostatitis pathogens using high-throughput next-generation sequencing

BACKGROUND

The pathogens responsible for chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS; NIH category III) are not currently known. the present study utilized high-throughput next-generation sequencing to screen for potential pathogens associated with NIH category III CP (CP III).

METHODS

This study included 33 patients with CP III and 30 healthy men, from which one sample each of urethral secretions and expressed prostatic secretion (EPS) was collected. High-throughput next-generation sequencing was performed to detect the sequence variations and the relative abundance of the bacterial 16S ribosomal variable region and fungal internal transcribed spacer region in all samples. Bioinformatics software and databases were used for data analysis, and differences with P < .05 were considered statistically significant.

RESULTS

Unweighted pair group method with arithmetic mean (UPGMA) cluster analysis, principal component analysis (PCA), and Spearman's rank correlation showed that the microbial compositions of the urethral secretions and EPS collected from the same subject were essentially the same.

CONCLUSIONS

No potential pathogens were identified in diagnosed patients with CP III. The EPS may be free from bacteria before and after infection. Changes in the urinary tract microbiome may disrupt the microecological balance of the urinary system, thereby leading to CP III. Conversely, the true pathogens of CP III may not be prokaryotic or eukaryotic microorganisms, Future research may involve the evaluation of noncellular microbes.

From Ancient to Emerging Infections: The Odyssey of Viruses in the Male Genital Tract

The male genital tract (MGT) is the target of a number of viral infections that can have deleterious consequences at the individual, offspring, and population levels. These consequences include infertility, cancers of male organs, transmission to the embryo/fetal development abnormalities, and sexual dissemination of major viral pathogens such as human immunodeficiency virus (HIV) and hepatitis B virus. Lately, two emerging viruses, Zika and Ebola, have additionally revealed that the human MGT can constitute a reservoir for viruses cleared from peripheral circulation by the immune system, leading to their sexual transmission by cured men. This represents a concern for future epidemics and further underlines the need for a better understanding of the interplay between viruses and the MGT. We review here how viruses, from ancient viruses that integrated the germline during evolution through old viruses (e.g., papillomaviruses originating from Neanderthals) and more modern sexually transmitted infections (e.g., simian zoonotic HIV) to emerging viruses (e.g., Ebola and Zika) take advantage of genital tract colonization for horizontal dissemination, viral persistence, vertical transmission, and endogenization. The MGT immune responses to viruses and the impact of these infections are discussed. We summarize the latest data regarding the sources of viruses in semen and the complex role of this body fluid in sexual transmission. Finally, we introduce key animal findings that are relevant for our understanding of viral infection and persistence in the human MGT and suggest future research directions.

Merkel cell polyomavirus and non-Merkel cell carcinomas: guilty or circumstantial evidence?

Merkel cell polyomavirus (MCPyV) is the major causative factor of the rare but aggressive cancer, Merkel cell carcinoma (MCC). Two characteristics of MCPyV-positive MCCs are integration of the viral genome and expression of a truncated version of one of its oncogenic proteins, namely large T antigen. The strong association of MCPyV with MCC development has incited researchers to further investigate a possible role of this virus in other cancers. However, many of the examples displaying the presence of the virus in the various non-MCC cancers are not able to clearly demonstrate a direct connection between cellular transformation and the presence of the virus. The prevalence of the virus is significantly lower in non-MCC cancers compared to MCCs, with a lower level of viral load and sparse viral protein expression. Moreover, the state of the viral genome, and whether a truncated large T antigen is expressed, has rarely been investigated. Nonetheless, considering the strong oncogenic potential of MCPyV proteins in MCC, the plausible contribution of MCPyV to transformation and cancer growth in non-MCC tumors cannot be ruled out. Furthermore, the absence of MCPyV in cancers does not exclude a hit-and-run mechanism, or the oncoproteins of MCPyV may potentiate the neoplastic process mediated by co-infecting oncoviruses such as high-risk human papillomaviruses and Epstein-Barr virus. The current review is focusing on the available data describing the presence of MCPyV in non-MCC tumors, with an aim to provide a comprehensive overview of the corresponding literature and to discuss the potential contribution of MCPyV to non-MCC cancer in light of this.

Epstein-Barr and BK virus in cancerous and noncancerous prostate tissue

Aim: We conducted a case–control study to examine the presence of BK virus (BKV) and Epstein barr virus (EBV) genome in prostate specimens of benign prostatic hyperplasia (BPH) and prostate cancer (PCa) in Iran. Materials & methods: 64 paraffin-embedded PCa specimens were included as case subjects and 57 paraffin-embedded BPH specimens as control. DNA extraction was carried out by phenol–chloroform technique and PCR for detection of BKV and EBV. Results: 90 (73%) out of 121 specimens were collected by prostatectomy and 31 (27%) by transurethral resection of the prostate. BKV was not detected in any of the samples and one positive EBV was reported. Conclusion: These findings provide further evidence against a causative role of BKV and EBV in the development of PCa.

ViraMiner: Deep learning on raw DNA sequences for identifying viral genomes in human samples

Despite its clinical importance, detection of highly divergent or yet unknown viruses is a major challenge. When human samples are sequenced, conventional alignments classify many assembled contigs as "unknown" since many of the sequences are not similar to known genomes. In this work, we developed ViraMiner, a deep learning-based method to identify viruses in various human biospecimens. ViraMiner contains two branches of Convolutional Neural Networks designed to detect both patterns and pattern-frequencies on raw metagenomics contigs. The training dataset included sequences obtained from 19 metagenomic experiments which were analyzed and labeled by BLAST. The model achieves significantly improved accuracy compared to other machine learning methods for viral genome classification. Using 300 bp contigs ViraMiner achieves 0.923 area under the ROC curve. To our knowledge, this is the first machine learning methodology that can detect the presence of viral sequences among raw metagenomic contigs from diverse human samples. We suggest that the proposed model captures different types of information of genome composition, and can be used as a recommendation system to further investigate sequences labeled as "unknown" by conventional alignment methods. Exploring these highly-divergent viruses, in turn, can enhance our knowledge of infectious causes of diseases.

ViraPipe: scalable parallel pipeline for viral metagenome analysis from next generation sequencing reads

Motivation

Next Generation Sequencing (NGS) technology enables identification of microbial genomes from massive amount of human microbiomes more rapidly and cheaper than ever before. However, the traditional sequential genome analysis algorithms, tools, and platforms are inefficient for performing large-scale metagenomic studies on ever-growing sample data volumes. Currently, there is an urgent need for scalable analysis pipelines that enable harnessing all the power of parallel computation in computing clusters and in cloud computing environments. We propose ViraPipe, a scalable metagenome analysis pipeline that is able to analyze thousands of human microbiomes in parallel in tolerable time. The pipeline is tuned for analyzing viral metagenomes and the software is applicable for other metagenomic analyses as well. ViraPipe integrates parallel BWA-MEM read aligner, MegaHit De novo assembler, and BLAST and HMMER3 sequence search tools. We show the scalability of ViraPipe by running experiments on mining virus related genomes from NGS datasets in a distributed Spark computing cluster.

Results

ViraPipe analyses 768 human samples in 210 minutes on a Spark computing cluster comprising 23 nodes and 1288 cores in total. The speedup of ViraPipe executed on 23 nodes was 11x compared to the sequential analysis pipeline executed on a single node. The whole process includes parallel decompression, read interleaving, BWA-MEM read alignment, filtering and normalizing of non-human reads, De novo contigs assembling, and searching of sequences with BLAST and HMMER3 tools.

Contact

ilari.maarala@aalto.fi.

Availability and implementation

https://github.com/NGSeq/ViraPipe.

Machine Learning for detection of viral sequences in human metagenomic datasets

BACKGROUND

Detection of highly divergent or yet unknown viruses from metagenomics sequencing datasets is a major bioinformatics challenge. When human samples are sequenced, a large proportion of assembled contigs are classified as "unknown", as conventional methods find no similarity to known sequences. We wished to explore whether machine learning algorithms using Relative Synonymous Codon Usage frequency (RSCU) could improve the detection of viral sequences in metagenomic sequencing data.

RESULTS

We trained Random Forest and Artificial Neural Network using metagenomic sequences taxonomically classified into virus and non-virus classes. The algorithms achieved accuracies well beyond chance level, with area under ROC curve 0.79. Two codons (TCG and CGC) were found to have a particularly strong discriminative capacity.

CONCLUSION

RSCU-based machine learning techniques applied to metagenomic sequencing data can help identify a large number of putative viral sequences and provide an addition to conventional methods for taxonomic classification.

Tumour virology in the era of high-throughput genomics

With the advent of massively parallel sequencing, oncogenic viruses in tumours can now be detected in an unbiased and comprehensive manner. Additionally, new viruses or strains can be discovered based on sequence similarity with known viruses. Using this approach, the causative agent for Merkel cell carcinoma was identified. Subsequent studies using data from large collections of tumours have confirmed models built during decades of hypothesis-driven and low-throughput research, and a more detailed and comprehensive description of virus-tumour associations have emerged. Notably, large cohorts and high sequencing depth, in combination with newly developed bioinformatical techniques, have made it possible to rule out several suggested virus-tumour associations with a high degree of confidence. In this review we discuss possibilities, limitations and insights gained from using massively parallel sequencing to characterize tumours with viral content, with emphasis on detection of viral sequences and genomic integration events.This article is part of the themed issue 'Human oncogenic viruses'.

vhfRNAi: a web-platform for analysis of host genes involved in viral infections discovered by genome wide RNAi screens

Knockdown of host genes using high-throughput genome-wide RNA interference screens has identified numerous host factors that affect viral infections, which would be helpful in understanding host-virus interactions. We have developed a vhfRNAi web resource based on genome-wide RNAi experiments for viruses. It contains experimental details of 12 249 entries (host factors + restriction factors) for 18 viruses. Simultaneously, this resource encompasses analysis of overlapping genes, genome wide association studies, gene ontology (GO), pathogen interacting proteins, interaction networks and pathway enrichment. Using overlap analysis, it was found that Influenza A virus shared overlapping host genes with the majority of viruses including Hepatitis C virus and Dengue virus 2. In the genome wide association studies analysis, 429 diseases/traits were mapped, of which obesity-related traits were the most common. GO analysis revealed that the major categories belonged to metabolic processes, molecule transport, signal transduction, proteolysis, etc. In the pathogen interacting protein analysis, protein interaction data from different resources can be explored for further understanding of host-virus biology. By pathway enrichment analysis, a total of 8955 genes were mapped on 303 pathways with most of the hits coming from metabolic pathways. We have found 491 genes that are not essential for the host but essential for the virus and can be targeted to inhibit the virus. These may be explored as potential candidates for drug targets. The resource is freely accessible at and will be useful in understanding host-virus biology as well as identification of targets for the development of antiviral therapeutics.

Metagenomics for the study of viruses in urban sewage as a tool for public health surveillance

The application of next-generation sequencing (NGS) techniques for the identification of viruses present in urban sewage has not been fully explored. This is partially due to a lack of reliable and sensitive protocols for studying viral diversity and to the highly complex analysis required for NGS data processing. One important step towards this goal is finding methods that can efficiently concentrate viruses from sewage samples. Here the application of a virus concentration method based on skimmed milk organic flocculation (SMF) using 10L of sewage collected in different seasons enabled the detection of many viruses. However, some viruses, such as human adenoviruses, could not always be detected using metagenomics, even when quantitative PCR (qPCR) assessments were positive. A targeted metagenomic assay for adenoviruses was conducted and 59.41% of the obtained reads were assigned to murine adenoviruses. However, up to 20 different human adenoviruses (HAdV) were detected by this targeted assay being the most abundant HAdV-41 (29.24%) and HAdV-51 (1.63%). To improve metagenomics' sensitivity, two different protocols for virus concentration were comparatively analysed: an ultracentrifugation protocol and a lower-volume SMF protocol. The sewage virome contained 41 viral families, including pathogenic viral species from families Caliciviridae, Adenoviridae, Astroviridae, Picornaviridae, Polyomaviridae, Papillomaviridae and Hepeviridae. The contribution of urine to sewage metavirome seems to be restricted to a few specific DNA viral families, including the polyomavirus and papillomavirus species. In experimental infections with sewage in a rhesus macaque model, infective human hepatitis E and JC polyomavirus were identified. Urban raw sewage consists of the excreta of thousands of inhabitants; therefore, it is a representative sample for epidemiological surveillance purposes. The knowledge of the metavirome is of significance to public health, highlighting the presence of viral strains that are circulating within a population while acting as a complex matrix for viral discovery.

Extension of the viral ecology in humans using viral profile hidden Markov models

When human samples are sequenced, many assembled contigs are "unknown", as conventional alignments find no similarity to known sequences. Hidden Markov models (HMM) exploit the positions of specific nucleotides in protein-encoding codons in various microbes. The algorithm HMMER3 implements HMM using a reference set of sequences encoding viral proteins, "vFam". We used HMMER3 analysis of "unknown" human sample-derived sequences and identified 510 contigs distantly related to viruses (Anelloviridae (n = 1), Baculoviridae (n = 34), Circoviridae (n = 35), Caulimoviridae (n = 3), Closteroviridae (n = 5), Geminiviridae (n = 21), Herpesviridae (n = 10), Iridoviridae (n = 12), Marseillevirus (n = 26), Mimiviridae (n = 80), Phycodnaviridae (n = 165), Poxviridae (n = 23), Retroviridae (n = 6) and 89 contigs related to described viruses not yet assigned to any taxonomic family). In summary, we find that analysis using the HMMER3 algorithm and the "vFam" database greatly extended the detection of viruses in biospecimens from humans.

Utility of high-throughput DNA sequencing in the study of the human papillomaviruses

The Papillomaviridae family is probably the most diverse group of viruses that affect vertebrates. The study of the relationship between infection by certain types of human papillomavirus (HPV) and the development of neoplastic epithelial lesions is of particular interest because of the high prevalence of HPV-related carcinomas in populations of developing countries. To understand the mechanisms of infection and their association with different clinical manifestations, molecular tools play an important role in the description of new types of HPV, the characterization of effector properties of the viral factors, the specific diagnosis and monitoring of HPV types, and the alteration patterns at genetic level in the host. Technological advances in the field of DNA sequencing have led to the development of different next-generation sequencing systems, allowing obtaining a large amount of data and broadening the applications to study viral diseases. In this review, we summarize the main approaches and their perspectives where the use of massively parallel sequencing has been proved as a useful tool in the research of the HPV infection.

Giant Viruses of Amoebae: A Journey Through Innovative Research and Paradigm Changes

Giant viruses of amoebae were discovered serendipitously in 2003; they are visible via optical microscopy, making them bona fide microbes. Their lifestyle, structure, and genomes break the mold of classical viruses. Giant viruses of amoebae are complex microorganisms. Their genomes harbor between 444 and 2,544 genes, including many that are unique to viruses, and encode translation components; their virions contain >100 proteins as well as mRNAs. Mimiviruses have a specific mobilome, including virophages, provirophages, and transpovirons, and can resist virophages through a system known as MIMIVIRE (mimivirus virophage resistance element). Giant viruses of amoebae bring upheaval to the definition of viruses and tend to separate the current virosphere into two categories: very simple viruses and viruses with complexity similar to that of other microbes. This new paradigm is propitious for enhanced detection and characterization of giant viruses of amoebae, and a particular focus on their role in humans is warranted.

Viruses in case series of tumors: Consistent presence in different cancers in the same subject

Studies investigating presence of viruses in cancer often analyze case series of cancers, resulting in detection of many viruses that are not etiologically linked to the tumors where they are found. The incidence of virus-associated cancers is greatly increased in immunocompromised individuals. Non-melanoma skin cancer (NMSC) is also greatly increased and a variety of viruses have been detected in NMSC. As immunosuppressed patients often develop multiple independent NMSCs, we reasoned that viruses consistently present in independent tumors might be more likely to be involved in tumorigenesis. We sequenced 8 different NMSCs from 1 patient in comparison to 8 different NMSCs from 8 different patients. Among the latter, 12 different virus sequences were detected, but none in more than 1 tumor each. In contrast, the patient with multiple NMSCs had human papillomavirus type 15 and type 38 present in 6 out of 8 NMSCs.