Identification of transcriptionally-active human papillomavirus integrants through nanopore sequencing reveals viable targets for gene therapy against cervical cancer.

Integration of the human papillomavirus (HPV) genome into the cellular genome is a key event that leads to constitutive expression of viral oncoprotein E6/E7 and drives the progression of cervical cancer. However, HPV integration patterns differ on a case-by-case basis among related malignancies. Next-generation sequencing technologies still face challenges for interrogating HPV integration sites. In this study, utilizing Nanopore long-read sequencing, we identified 452 and 108 potential integration sites from the cervical cancer cell lines (CaSki and HeLa) and five tissue samples, respectively. Based on long Nanopore chimeric reads, we were able to analyze the methylation status of the HPV long control region (LCR), which controls oncogene E6/E7 expression, and to identify transcriptionally-active integrants among the numerous integrants. As a proof of concept, we identified an active HPV integrant in between RUNX2 and CLIC5 on chromosome 6 in the CaSki cell line, which was supported by ATAC-seq, H3K27Ac ChIP-seq, and RNA-seq analysis. Knockout of the active HPV integrant, by the CRISPR/Cas9 system, dramatically crippled cell proliferation and induced cell senescence. In conclusion, identifying transcriptionally-active HPV integrants with Nanopore sequencing can provide viable targets for gene therapy against HPV-associated cancers.

SR proteins in cancer: function, regulation, and small inhibitor.

Alternative splicing of pre-mRNAs is a fundamental step in RNA processing required for gene expression in most metazoans. Serine and arginine-rich proteins (SR proteins) comprise a family of multifunctional proteins that contain an RNA recognition motif (RRM) and the ultra-conserved arginine/serine-rich (RS) domain, and play an important role in precise alternative splicing. Increasing research supports SR proteins as also functioning in other RNA-processing-related mechanisms, such as polyadenylation, degradation, and translation. In addition, SR proteins interact with N6-methyladenosine (m6A) regulators to modulate the methylation of ncRNA and mRNA. Dysregulation of SR proteins causes the disruption of cell differentiation and contributes to cancer progression. Here, we review the distinct biological characteristics of SR proteins and their known functional mechanisms during carcinogenesis. We also summarize the current inhibitors that directly target SR proteins and could ultimately turn SR proteins into actionable therapeutic targets in cancer therapy.

Splicing factor TRA2A contributes to esophageal cancer progression via a noncanonical role in lncRNA m6 A methylation.

Transformer 2 alpha homolog (TRA2A), a member of the serine/arginine-rich splicing factor family, has been shown to control mRNA splicing in development and cancers. However, it remains unclear whether TRA2A is involved in lncRNA regulation. In the present study, we found that TRA2A was upregulated and correlated with poor prognosis in esophageal cancer. Downregulation of TRA2A suppressed the tumor growth in xenograft nude mice. Epitranscriptomic microarray showed that depletion of TRA2A affected global lncRNA methylation similarly to the key m6 A methyltransferase, METTL3, by silencing. MeRIP-qPCR, RNA pull-down, CLIP analyses, and stability assays indicated that ablation of TRA2A reduced m6 A-modification of the oncogenic lncRNA MALAT1, thus inducing structural alterations and reduced stability. Furthermore, Co-IP experiments showed TRA2A directly interacted with METTL3 and RBMX, which also affected the writer KIAA1429 expression. Knockdown of TRA2A inhibited cell proliferation in a manner restored by RBMX/KIAA1429 overexpression. Clinically, MALAT1, RBMX, and KIAA1429 were prognostic factors of worse survival in ESCA patients. Structural similarity-based virtual screening in FDA-approved drugs repurposed nebivolol, a ß1 -adrenergic receptor antagonist, as a potent compound to suppress the proliferation of esophageal cancer cells. Cellular thermal shift and RIP assay indicated that nebivolol may compete with MALAT1 to bind TRA2A. In conclusion, our study revealed the noncanonical function of TRA2A, which coordinates with multiple methylation proteins to promote oncogenic MALAT1 during ESCA carcinogenesis.

Computational Drug Repurposing Based on a Recommendation System and Drug-Drug Functional Pathway Similarity.

Drug repurposing identifies new clinical indications for existing drugs. It can be used to overcome common problems associated with cancers, such as heterogeneity and resistance to established therapies, by rapidly adapting known drugs for new treatment. In this study, we utilized a recommendation system learning model to prioritize candidate cancer drugs. We designed a drug-drug pathway functional similarity by integrating multiple genetic and epigenetic alterations such as gene expression, copy number variation (CNV), and DNA methylation. When compared with other similarities, such as SMILES chemical structures and drug targets based on the protein-protein interaction network, our approach provided better interpretable models capturing drug response mechanisms. Furthermore, our approach can achieve comparable accuracy when evaluated with other learning models based on large public datasets (CCLE and GDSC). A case study about the Erlotinib and OSI-906 (Linsitinib) indicated that they have a synergistic effect to reduce the growth rate of tumors, which is an alternative targeted therapy option for patients. Taken together, our computational method characterized drug response from the viewpoint of a multi-omics pathway and systematically predicted candidate cancer drugs with similar therapeutic effects.

Challenge-comet assay, a functional and genomic biomarker for precision risk assessment and disease prevention among exposed workers.

Advancements in genomic technologies have ushered application of innovative changes into biomedical sciences and clinical medicine. Consequently, these changes have created enormous opportunities to implement precision population/occupational disease prevention and target-specific disease intervention (or personalized medicine). To capture the opportunities, however, it is necessary is to develop novel, especially genomic-based, biomarkers which can provide precise and individualized health risk assessment. In this review, development of the Challenge-comet assay is used as an example to demonstrate how assays need to be validated for its sensitivity, specificity, and functional and quantitative features, and how assays can be used to provide individualized health risk assessment for precision prevention and intervention. Other examples of genomic-based novel biomarkers will also be discussed. Furthermore, no biomarkers can be used alone therefore their integrated usage with other biomarkers and with personal data bases will be discussed.

OmicsARules: a R package for integration of multi-omics datasets via association rules mining.

BACKGROUND: The improvements of high throughput technologies have produced large amounts of multi-omics experiments datasets. Initial analysis of these data has revealed many concurrent gene alterations within single dataset or/and among multiple omics datasets. Although powerful bioinformatics pipelines have been developed to store, manipulate and analyze these data, few explicitly find and assess the recurrent co-occurring aberrations across multiple regulation levels. RESULTS: Here, we introduced a novel R-package (called OmicsARules) to identify the concerted changes among genes under association rules mining framework. OmicsARules embedded a new rule-interestingness measure, Lamda3, to evaluate the associated pattern and prioritize the most biologically meaningful gene associations. As demonstrated with DNA methlylation and RNA-seq datasets from breast invasive carcinoma (BRCA), esophageal carcinoma (ESCA) and lung adenocarcinoma (LUAD), Lamda3 achieved better biological significance over other rule-ranking measures. Furthermore, OmicsARules can illustrate the mechanistic connections between methlylation and transcription, based on combined omics dataset. OmicsARules is available as a free and open-source R package. CONCLUSIONS: OmicsARules searches for concurrent patterns among frequently altered genes, thus provides a new dimension for exploring single or multiple omics data across sequencing platforms.

Histone methyltransferase NSD2 mediates the survival and invasion of triple-negative breast cancer cells via stimulating ADAM9-EGFR-AKT signaling.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with a poor prognosis due to the lack of an effective targeted therapy. Histone lysine methyltransferases (KMTs) have emerged as attractive drug targets for cancer therapy. However, the function of the majority of KMTs in TNBC has remained largely unknown. In the current study, we found that KMT nuclear receptor binding SET domain protein 2 (NSD2) is overexpressed in TNBC tumors and that its overexpression is associated with poor survival of TNBC patients. NSD2 regulates TNBC cell survival and invasion and is required for tumorigenesis and tumor growth. Mechanistically, NSD2 directly controls the expression of EGFR and ADAM9, a member of the ADAM (a disintegrin and metalloproteinase) family that mediates the release of growth factors, such as HB-EGF. Through its methylase activity, NSD2 overexpression stimulates EGFR-AKT signaling and promotes TNBC cell resistance to the EGFR inhibitor gefitinib. Together, our results identify NSD2 as a major epigenetic regulator in TNBC and provide a rationale for targeting NSD2 alone or in combination with EGFR inhibitors as a targeted therapy for TNBC.

Circular RNAs: Biogenesis, Mechanism, and Function in Human Cancers.

CircRNAs are a class of noncoding RNA species with a circular configuration that is formed by either typical spliceosome-mediated or lariat-type splicing. The expression of circRNAs is usually abnormal in many cancers. Several circRNAs have been demonstrated to play important roles in carcinogenesis. In this review, we will first provide an introduction of circRNAs biogenesis, especially the regulation of circRNA by RNA-binding proteins, then we will focus on the recent findings of circRNA molecular mechanisms and functions in cancer development. Finally, some open questions are also discussed.

circRNA expression analysis in lung adenocarcinoma: comparison of paired fresh frozen and formalin-fixed paraffin-embedded specimens.

Circular RNA (circRNAs) is a novel class of endogenous non-coding RNAs which is widely involved in carcinogenesis. Archived formalin-fixed paraffin-embedded (FFPE) specimens represent valuable resources for cancer research. Currently there is a lack of systematic analysis on the feasibility of circRNAs expression analysis using FFPE samples. Here, we reported the first comparison study of circRNA expression from paired fresh frozen and FFPE specimens of lung adenocarcinoma. circRNAs expression of paired lung adenocarcinoma and adjacent normal samples, starting from either fresh frozen or FFPE materials, were analyzed via a high-throughput circRNA microarray. Hierarchical clustering was performed on samples. qRT-PCR was used to confirm the differentially expressed circRNAs. The circRNA regulation networks were built by bioinformatics tools for several candidate circRNAs. Our results demonstrated that there was a good correlation in circRNAs expression analysis utilizing fresh frozen or FFPE tissues. Tumors and adjacent normal tissues can be clustered correctly by the differentially expressed circRNAs in fresh frozen or FFPE groups. Furthermore, three differentially expressed circRNAs, hsa_circRNA_100421, hsa_circRNA_104329 and hsa_circRNA_101969 were verified by qRT-PCR assay. Bioinformatics analysis was also applied to predict the circRNA-miRNA-protein coding gene interaction network for each of above circRNAs. To the best of our knowledge, this is the first report demonstrating that the circRNAs microarray analysis, starting from FFPE specimens, is comparable with that based on fresh frozen samples. Therefore FFPE specimen represents a good substitute for fresh frozen tissue, especially when fresh frozen specimen is limited.

RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence.

RNA-protein interactions (RPIs) have critical roles in numerous fundamental biological processes, such as post-transcriptional gene regulation, viral assembly, cellular defence and protein synthesis. As the number of available RNA-protein binding experimental data has increased rapidly due to high-throughput sequencing methods, it is now possible to measure and understand RNA-protein interactions by computational methods. In this study, we integrate a sequence-based derived kernel with regularized least squares to perform prediction. The derived kernel exploits the contextual information around an amino acid or a nucleic acid as well as the repetitive conserved motif information. We propose a novel machine learning method, called RPiRLS to predict the interaction between any RNA and protein of known sequences. For the RPiRLS classifier, each protein sequence comprises up to 20 diverse amino acids but for the RPiRLS-7G classifier, each protein sequence is represented by using 7-letter reduced alphabets based on their physiochemical properties. We evaluated both methods on a number of benchmark data sets and compared their performances with two newly developed and state-of-the-art methods, RPI-Pred and IPMiner. On the non-redundant benchmark test sets extracted from the PRIDB, the RPiRLS method outperformed RPI-Pred and IPMiner in terms of accuracy, specificity and sensitivity. Further, RPiRLS achieved an accuracy of 92% on the prediction of lncRNA-protein interactions. The proposed method can also be extended to construct RNA-protein interaction networks. The RPiRLS web server is freely available at http://bmc.med.stu.edu.cn/RPiRLS.

RAID: a comprehensive resource for human RNA-associated (RNA-RNA/RNA-protein) interaction.

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA-RNA/RNA-protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA-RNA interactions and 1619 RNA-protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA-RNA/RNA-protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA-RNA/RNA-protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network.

MicroRNA-192 targeting retinoblastoma 1 inhibits cell proliferation and induces cell apoptosis in lung cancer cells.

microRNAs play an important roles in cell growth, differentiation, proliferation and apoptosis. They can function either as tumor suppressors or oncogenes. We found that the overexpression of miR-192 inhibited cell proliferation in A549, H460 and 95D cells, and inhibited tumorigenesis in a nude mouse model. Both caspase-7 and the PARP protein were activated by the overexpression of miR-192, thus suggesting that miR-192 induces cell apoptosis through the caspase pathway. Further studies showed that retinoblastoma 1 (RB1) is a direct target of miR-192. Over-expression of miR-192 decreased RB1 mRNA and protein levels and repressed RB1-3'-UTR reporter activity. Knockdown of RB1 using siRNA resulted in a similar cell morphology as that observed for overexpression of miR-192. Additionally, RB1-siRNA treatment inhibited cell proliferation and induced cell apoptosis in lung cancer cells. Analysis of miRNA expression in clinical samples showed that miR-192 is significantly downregulated in lung cancer tissues compared to adjacent non-cancerous lung tissues. In conclusion, our results demonstrate that miR-192 is a tumor suppressor that can target the RB1 gene to inhibit cell proliferation and induce cell apoptosis in lung cancer cells. Furthermore, miR-192 was expressed at low levels in lung cancer samples, indicating that it might be a promising therapeutic target for lung cancer treatment.

fRNC: Uncovering the dynamic and condition-specific RBP-ncRNA circuits from multi-omics data.

The RNA binding protein (RBP) and non-coding RNA (ncRNA) interacting networks are increasingly recognized as the main mechanism in gene regulation, and are tightly associated with cellular malfunction and disease. Here, we present fRNC, a systems biology tool to uncover the dynamic spectrum of RBP-ncRNA circuits (RNC) by integrating transcriptomics, interactomics and proteomics data. fRNC constructs the RBP-ncRNA network derived from CLIP-seq or PARE experiments. Given scoring on nodes and edges according to differential analysis of expression data, it finds an RNC containing global maximum significant RBPs and ncRNAs. Alternatively, it can also capture the locally maximum scoring RNC according to user-defined starting nodes with the greedy search. When compared with existing tools, fRNC can detect more accurate and robust sub-network with scalability. As shown in the cases of esophageal carcinoma, breast cancer and Alzheimer's disease, fRNC enables users to analyze the collective behaviors between RBP and the interacting ncRNAs, and reveal novel insights into the disease-associated processes. The fRNC R package is available at https://github.com/BioinformaticsSTU/fRNC.

CRIT: Identifying RNA-binding protein regulator in circRNA life cycle via non-negative matrix factorization.

Circular RNAs (circRNAs) are endogenous non-coding RNAs that regulate gene expression and participate in carcinogenesis. However, the RNA-binding proteins (RBPs) involved in circRNAs biogenesis and modulation remain largely unclear. We developed the circRNA regulator identification tool (CRIT), a non-negative matrix-factorization-based pipeline to identify regulating RBPs in cancers. CRIT uncovered 73 novel regulators across thousands of samples by effectively leveraging genomics data and functional annotations. We demonstrated that known RBPs involved in circRNA control are significantly enriched in these predictions. Analysis of circRNA-RBP interactions using two large cross-linking immunoprecipitation (CLIP) databases, we validated the consistency between CRIT prediction and the CLIP experiments. Furthermore, newly discovered RBPs are functionally connected with authentic circRNA regulators by various biological associations, such as physical interaction, similar binding motifs, common transcription factor modulation, and co-expression. When analyzing RNA sequencing (RNA-seq) datasets after short hairpin RNA (shRNA)/small interfering RNA (siRNA) knockdown, we found several novel RBPs that can affect global circRNA expression, which strengthens their role in the circRNA life cycle. The above evidence provided independent confirmation that CRIT is a useful tool to capture RBPs in circRNA processing. Finally, we show that authentic regulators are more likely the core splicing proteins and peripheral factors and usually harbor more alterations in the vast majority of cancers.

Chromatin-modifying drugs induce miRNA-153 expression to suppress Irs-2 in glioblastoma cell lines.

MicroRNAs (miRNAs) are noncoding RNAs that regulate gene expression by inhibiting translation or by promoting mRNA degradation. Previously, we established that microRNA-153 (miR-153) induces apoptosis by downregulating B-cell lymphoma 2 (Bcl-2) and myeloid cell leukemia sequence 1 (Mcl-1) protein expression levels in glioblastoma cell line DBTRG-05MG. In our study, we show that ectopic expression of miR-153 also inhibits the protein kinase B (PKB/Akt) pathway via reducing the protein level of insulin receptor substrate-2 (Irs-2). Moreover, simultaneous treatment with the chromatin-modifying drugs 4-phenylbutyric acid and 5-aza-2'-deoxycytidine induces miR-153 expression to suppress Irs-2, Bcl-2 and Mcl-1 expressions, thus downregulating the survival but upregulating the apoptotic pathways, implying that tumor suppressor miR-153 is a dual life and death regulator.

Revisiting the Relationship Between Alzheimer's Disease and Cancer With a circRNA Perspective.

BACKGROUND: Increasing evidence indicates an association between the incidence of Alzheimer's disease (AD) and cancer development. Despite advances being made by comparisons from epidemiological studies, common pathways and molecular mechanisms, little is known about the identities of the circular RNAs (circRNAs) involved in the development and progression of these two pathologies and their possible correlations. The aim of this study was to explore the circRNA relationship between AD and cancer. MATERIALS AND METHODS: In this investigation, circRNAs that were significantly dysregulated in AD or associated with AD diagnosis, clinical dementia severity, and neuropathological severity, were examined in a large panel of 28 cancer types. On the basis of shared abnormal circRNAs in AD and cancers, we constructed a circRNA-micro RNA (miRNA)-messenger RNA (mRNA) network by leveraging experimentally identified miRNA-circRNA and miRNA-mRNA interactions from crosslinking-immunoprecipitation sequencing data. RESULTS: An inverse correlation of expression pattern was found in acute myeloid leukemia, juvenile myelomonocytic leukemia, renal cell carcinoma, and myelofibrosis. CircRNAs associated with AD diagnosis and clinical severity demonstrated negative correlation in more cancer types. Notably, differentially expressed candidate circRNAs in temporal lobe epilepsy were not associated with any cancers. Gene Ontology and KEGG pathway analysis suggested the circRNA-regulated genes are significantly associated with interleukin-12-mediated signaling and viral response. CircPICALM, circRTN4 and circMAN2A1 are the hub nodes in the circRNA-miRNA-target network. CONCLUSION: Our results indicated the relevance of inflammation signaling as a common pathogenesis shared by cancer and AD and provided novel insight for therapeutics targeting circRNAs.

Characterizing the tumor RBP-ncRNA circuits by integrating transcriptomics, interactomics and clinical data.

The interactions among non-coding RNA (ncRNA) and RNA binding protein (RBP) are increasingly recognized as one of basic mechanisms in gene regulation, and play a crucial role in cancer progressions. However, the current understanding of this regulation network, especially its dynamic spectrum according to the differentially expressed nodes (i.e. ncRNAs and RBP) is limited. Utilizing transcriptomics and interactomics resources, dysregulated RBP-ncRNA circuits (RNCs) are systematically dissected across 14 tumor types. We found these aberrant RNCs are robust and enriched with cancer-associated ncRNAs, RBPs and drug targets. Notably, the nodes in altered RNCs can jointly predict the clinical outcome while the individual node can't, underscoring RNCs can serve as prognostic biomarkers. We identified 30 pan-cancer RNCs dysregulated at least in six tumor types. Pan-cancer RNC analysis can reveal novel mechanism of action (MOA) and repurpose for existing drugs. Importantly, our experiments elucidated the novel role of hsa-miR-224-5p, a member of the pan-cancer RNC hsa-miR-224-5p_MAGI2-AS3_MBNL2, in EMT program. Our analysis highlights the potential utilities of RNCs in elucidating ncRNA function in cancer, associating with clinical outcomes and discovering novel drug targets or MOA.

TRA2A Binds With LncRNA MALAT1 To Promote Esophageal Cancer Progression By Regulating EZH2/ß-catenin Pathway.

The RNA binding protein TRA2A, a member of the transformer 2 homolog family, plays a crucial role in the alternative splicing of pre-mRNA. However, it remains unclear whether TRA2A is involved in non-coding RNA regulation and, if so, what are the functional consequences. By analyzing expression profiling data, we found that TRA2A is highly expressed in esophageal cancer and is associated with disease-free survival and overall survival time. Subsequent gain- and loss-of-function studies demonstrated that TRA2A promotes proliferation and migration of esophageal squamous cell carcinoma and adenocarcinoma cells. RNA immunoprecipitation and RNA pull-down assay indicated that TRA2A can directly bind specific sites on MALAT1 in cells. In addition, ectopic expression or depletion of TRA2A leads to MALAT expression changes accordingly, thus modulates EZH2/ß-catenin pathway. Together, these findings elucidated that TRA2A triggers carcinogenesis via MALAT1 mediated EZH2/ß-catenin axis in esophageal cancer cells.

circ-NOL10 regulated by MTDH/CASC3 inhibits breast cancer progression and metastasis via multiple miRNAs and PDCD4.

Circular RNAs (circRNAs) play important roles in carcinogenesis. Here, we investigated the mechanisms and clinical significance of circ-NOL10, a highly repressed circRNA in breast cancer. Subsequently, we also identified RNA-binding proteins (RBPs) that regulate circ-NOL10. Bioinformatics analysis was utilized to predict regulatory RBPs as well as circ-NOL10 downstream microRNAs (miRNAs) and mRNA targets. RNA immunoprecipitation, luciferase assay, fluorescence in situ hybridization, cell proliferation, wound healing, Matrigel invasion, cell apoptosis assays, and a xenograft model were used to investigate the function and mechanisms of circ-NOL10 in vitro and in vivo. The clinical value of circ-NOL10 was evaluated in a large cohort of breast cancer by quantitative real-time PCR. Circ-NOL10 is downregulated in breast cancer and associated with aggressive characteristics and shorter survival time. Upregulation of circ-NOL10 promotes apoptosis, decreases proliferation, and inhibits invasion and migration. Furthermore, circ-NOL10 binds multiple miRNAs to alleviate carcinogenesis by regulating PDCD4. CASC3 and metadherin (MTDH) can bind directly to circ-NOL10 with characterized motifs. Accordingly, ectopic expression or depletion of CASC3 or MTDH leads to circ-NOL10 expression changes, suggesting that these two RBPs modulate circ-NOL10 in cancer cells. circ-NOL10 is a novel biomarker for diagnosis and prognosis in breast cancer. These results highlight the importance of therapeutic targeting of the RBP-noncoding RNA (ncRNA) regulation network.

Whole Genome Assembly of Human Papillomavirus by Nanopore Long-Read Sequencing.

Human papillomavirus (HPV) is a causal agent for most cervical cancers. The physical status of the HPV genome in these cancers could be episomal, integrated, or both. HPV integration could serve as a biomarker for clinical diagnosis, treatment, and prognosis. Although whole-genome sequencing by next-generation sequencing (NGS) technologies, such as the Illumina sequencing platform, have been used for detecting integrated HPV genome in cervical cancer, it faces challenges of analyzing long repeats and translocated sequences. In contrast, Oxford nanopore sequencing technology can generate ultra-long reads, which could be a very useful tool for determining HPV genome sequence and its physical status in cervical cancer. As a proof of concept, in this study, we completed whole genome sequencing from a cervical cancer tissue and a CaSki cell line with Oxford Nanopore Technologies. From the cervical cancer tissue, a 7,894 bp-long HPV35 genomic sequence was assembled from 678 reads at 97-fold coverage of HPV genome, sharing 99.96% identity with the HPV sequence obtained by Sanger sequencing. A 7904 bp-long HPV16 genomic sequence was assembled from data generated from the CaSki cell line at 3857-fold coverage, sharing 99.99% identity with the reference genome (NCBI: U89348). Intriguingly, long reads generated by nanopore sequencing directly revealed chimeric cellular-viral sequences and concatemeric genomic sequences, leading to the discovery of 448 unique integration breakpoints in the CaSki cell line and 60 breakpoints in the cervical cancer sample. Taken together, nanopore sequencing is a unique tool to identify HPV sequences and would shed light on the physical status of HPV genome in its associated cancers.