Biology subjects

Van Arsdale, A.

Publications and source records attributed to Van Arsdale, A..

4 recordsLinked to original sources

bioRxiv2025

Complex HPV-human DNA structures revealed by large-scale DNA analyses in an HPV-cancer derived cell line

Most human papillomavirus (HPV)-associated cancers harbor viral DNA integrated into the human genome as extrachromosomal circles, intrachromosomal segments, or both. Distinguishing intrachromosomal from identical-sequence extrachromosomal DNA (ecDNA) by sequencing alone is challenging, and the architecture of large-scale HPV-human DNA structures remains incompletely understood. To address this, we applied complementary genomic tools, spanning single-nucleotide to megabase resolution, to the HPV16-positive oropharyngeal cancer-cell line UM-SCC-47. These revealed that an initial integration event formed a 23 kb extrachromosomal heterocatemer circle comprising 7.5 kb of HPV16 DNA and 16 kb of the human TP63 gene. Subsequent genomic rearrangements generated heterocatemer tandem arrays extending to 0.6 megabases, plus additional large-scale rearrangements involving the HPV-TP63 structures, as revealed by long-read DNA sequencing and optical genome mapping. Fluorescent in situ Hybridization (FISH) showed that the heterocatemers were intrachromosomally localized at chromosome 3 at the TP63 locus in 100% of the cells. Long-read RNA sequencing further showed that these intrachromosomal templates produced spliced, polyadenylated transcripts. A subset of cells also harbored HPV16 ecDNA derived from the intrachromosomal HPV-TP63 DNAs. These findings define previously unrecognized higher-order architecture of integrated HPV DNA and highlight the power of FISH for distinguishing intrachromosomal from extrachromosomal DNA structures. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/680684v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@f3d584org.highwire.dtl.DTLVardef@470811org.highwire.dtl.DTLVardef@162c88corg.highwire.dtl.DTLVardef@5c80dd_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Pathogenic Viruses, Genome Integrations, and Viral::Human Chimeric Transcripts Detected by VirusIntegrationFinder Across >30k Human Tumor and Normal Samples

Viruses are a leading cause of human morbidity and mortality. Certain viruses, including human papillomaviruses (HPVs), play a significant role in the etiology of cancer. Detection of viral DNA insertions in the human genome from next generation sequencing data defines viral associations with cancer and other diseases, identifies impacted organs and tissues, provides insights into disease mechanisms and has the potential to enhance clinical evaluations. In this study, we developed VirusIntegrationFinder (CTAT-VIF), a tool for surveying human genome insertions of various human viruses using both DNA and RNA sequencing data. We applied CTAT-VIF to analyze a dataset of over 30,000 tumor and normal samples, as well as more than 1,000 cancer cell lines. This effort resulted in the compilation of a catalog of over 30,0000 virus-human DNA or RNA junctions at more than 20,000 insertion loci and reassessed viral cancer-insertion hotspots across the human genome. Furthermore, we characterized the functional impacts of insertions with respect to human copy number alterations, effects on the expression of flanking human genes, and the identification of potentially oncogenic chimeric human and human/virus fusion transcripts at insertion loci. In addition to confirming known viral associations with specific tumor types, our study revealed both shared and virus-specific insertion hotspots in addition to variable functional impacts based on virus type. Besides some rare events of interest, we also found evidence for sequencing contamination, which underscores the need for vigilance when studying viral content or genome integrations.

cancer biology↗

bioRxiv2021

Targeted in silico characterization of fusion transcripts in tumor and normal tissues via FusionInspector

MotivationGene fusions play a key role as driver oncogenes in tumors, and their reliable discovery and detection are important for cancer research, diagnostics, prognostics and guiding personalized therapy. While discovering gene fusions from genome sequencing can be laborious and costly, the resulting "fusion transcripts" can be recovered from RNA-seq data of tumor and normal samples. However, alleged and putative fusion transcripts can also arise from multiple sources other than chromosomal rearrangements, including cis- or trans-splicing events, experimental artifacts during RNA-seq or computational errors of transcriptome reconstruction methods. Understanding how to discern, interpret, categorize, and verify predicted fusion transcripts is essential for consideration in clinical settings and prioritization for further research. SummaryHere, we present FusionInspector for in silico characterization and interpretation of candidate fusion transcripts from RNA-seq and exploration of their sequence and expression characteristics. We applied FusionInspector to thousands of tumor and normal transcriptomes, and identified statistical and experimental features enriched among biologically impactful fusions. Through clustering and machine learning, we identified large collections of fusions potentially relevant to tumor and normal biological processes. We show that biologically relevant fusions are enriched for relatively high expression of the fusion transcript, imbalanced fusion allelic ratios, and canonical splicing patterns, and are deficient in sequence microhomologies detected between partner genes. We demonstrate that FusionInspector accurately validates fusion transcripts in silico, and helps identify and characterize numerous understudied fusions in tumor and normal tissues samples. FusionInspector is freely available as open source for screening, characterization, and visualization of candidate fusions via RNA-seq, and helps with transparent explanation and interpretation of machine learning predictions and their experimental sources. HighlightsO_LIFusionInspector software for supervised analysis of candidate fusion transcripts C_LIO_LIClustering of recurrent fusion transcripts resolves biologically relevant fusions C_LIO_LIIdentification of distinguishing characteristics of known and novel fusion transcripts in tumor and normal tissues C_LI

bioinformatics↗

bioRxiv2019

Insertional oncogenesis by HPV70 revealed by multiple genomic analyses in a clinically HPV-negative cervical cancer

Cervical carcinogenesis, the second leading cause of cancer death in women worldwide, is caused by multiple types of human papillomaviruses (HPVs). To investigate a possible role for HPV in a cervical carcinoma that was HPV-negative by PCR testing, we performed HPV DNA hybridization capture plus massively parallel sequencing. This detected a subgenomic, URR- E6-E7-E1 segment of HPV70 DNA, a type not generally associated with cervical cancer, inserted in an intron of the B-cell lymphoma/leukemia 11B (BCL11B) gene in the human genome. Long range DNA sequencing confirmed the virus and flanking BCL11B DNA structures including both insertion junctions. Global transcriptomic analysis detected multiple, alternatively spliced, HPV70-BCL11B, fusion transcripts with fused open reading frames. The insertion and fusion transcripts were present in an intraepithelial precursor phase of tumorigenesis. These results suggest oncogenicity of HPV70, identify novel BCL11B variants with potential oncogenic implications, and underscore the advantages of thorough genomic analyses to elucidate insights into HPV-associated tumorigenesis.\n\nStatement of SignificanceMultiple HPV types have been defined as high risk for cancer causation. However, genomic analyses applied here detected a non-high risk HPV in a carcinoma that was HPV negative, and elucidated virally-associated tumorigenic genetic events. This stresses the importance of thorough genomic analyses for elucidating genetic processes in HPV-associated tumorigenesis.\n\nAuthor SummaryCervical cancer is the second leading cause of cancer death in women worldwide. Most cervical cancers are caused by one of 15 high risk types of human papilloma viruses (HPVs), although hundreds of types of HPVs exist. We used a series of contemporary genomics analyses to examine a cervical cancer that was clinically determined to be HPV-negative. These detected DNA of HPV70, an HPV type not considered to be high risk, in the tumor. Approximately half of the HPV70 DNA genome was present including the viral E6 and E7 oncogenes. Moreover, the viral DNA was inserted into the BCL11B gene in the human genome. BCL11B is known to be mutated in certain human cancers. The HPV70 DNA interacted with the human BCL11B gene to produce altered forms of RNA encoding unusual, truncated forms of the BCL11B protein. These results strongly implicate HPV70 as being oncogenic, suggest that this tumor was caused by a combination of viral oncogenes plus the virally-activated human BCL11B gene, demonstrate novel truncated BCL11B variants with oncogenic implications, and underscore the advantages of thorough genomic analyses to elucidate HPV tumorigenesis insights

cancer biology↗