Dataset Information

Deep sequencing detects human papillomavirus (HPV) in cervical cancers negative for HPV by PCR.

ABSTRACT:

Background

Human papillomavirus (HPV) is a necessary cause of cervical cancer, although some invasive cervical cancers may test negative by HPV PCR. We previously requested all invasive cervical cancers in Sweden during 10 years and subjected them to PCR. We also optimised methods for deep sequencing of formalin-fixed paraffin-embedded samples.

Methods

Using Novaseq 6000, we simultaneously sequenced total DNA and cDNA from 392 HPV PCR-negative cervical cancers. Non-human reads were queried against all known HPVs. The complete database now contains PCR and/or deep sequencing data on 2850 invasive cervical cancers.

Results

HPV sequences were detected in 169/392 of HPV PCR-negative cervical cancers. Overall, 30 different HPV types were detected, but only 5 types were present in proportions above 3% of cancers. More than 92% of tumours were HPV-positive in PCR and/or sequencing (95% confidence interval: 91.1-93.1%). Exploring possible reasons for failure to previously detect HPV suggest that more sensitive type-specific PCRs for HPV 31, 33, 45 and 73 targeting retained regions of HPV would have detected most of these (117/392).

Conclusions

Unbiased deep sequencing provides comprehensive data on HPV types in cervical cancers and appears to be an important tool for quality assurance of HPV screening.

SUBMITTER: Arroyo Muhr LS

PROVIDER: S-EPMC7722749 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

Deep sequencing detects human papillomavirus (HPV) in cervical cancers negative for HPV by PCR.

Arroyo Mühr Laila Sara LS Lagheden Camilla C Lei Jiayao J Eklund Carina C Nordqvist Kleppe Sara S Sparén Pär P Sundström Karin K Dillner Joakim J

British journal of cancer 20201006 12

<h4>Background</h4>Human papillomavirus (HPV) is a necessary cause of cervical cancer, although some invasive cervical cancers may test negative by HPV PCR. We previously requested all invasive cervical cancers in Sweden during 10 years and subjected them to PCR. We also optimised methods for deep sequencing of formalin-fixed paraffin-embedded samples.<h4>Methods</h4>Using Novaseq 6000, we simultaneously sequenced total DNA and cDNA from 392 HPV PCR-negative cervical cancers. Non-human reads wer ...[more]

PMID: 33020595

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Project description:Human papillomaviruses (HPVs) are associated with nearly all cervical cancers (CCs), 20-30% of head and neck cancers (HNCs), and other cancers. Because HNCs also arise in HPV-negative patients, this type of cancer provides unique opportunities to define similarities and differences of HPV-positive versus HPV-negative cancers arising in the same tissue. Here, we describe genome-wide expression profiling of 84 HNCs, CCs and site-matched normal epithelial samples in which we used laser capture microdissection to enrich samples for tumor-derived versus normal epithelial cells. This analysis revealed that HPV+HNCs and CCs differed in their patterns of gene expression yet shared many changes compared to HPV-HNCs. Some of these shared changes were predicted, but many others were not. Notably, HPV+HNCs and CCs were found to be upregulated in their expression of a distinct and larger subset of cell cycle genes than observed in HPV-HNC. Moreover, HPV+ cancers over-expressed testis-specific genes that are normally expressed only in meiotic cells. Many, though not all, of the hallmark differences between HPV+HNC and HPV-HNC were a direct consequence of HPV and in particular the viral E6 and E7 oncogenes. This included a novel association of HPV oncogenes with testes specific gene expression. These findings in primary human tumors provide novel biomarkers for early detection of HPV+ and HPV- cancers, and emphasize the potential value of targeting E6 and E7 function, alone or combined with radiation and/or traditional chemotherapy, in the treatment of HPV+ cancers. Experiment Overall Design: All tissue samples were fresh frozen in liquid nitrogen and collected with patientsâ?? consent under approval of the Institutional Review Boards from all participating institutions. Each tissue sample was cryosectioned, and selected sections stained with hematoxylin/eosin, and reviewed to determine tumor content, pathological status, and freedom from necrosis and freezing artifacts. Epithelial cells from all normal samples and tumor cells from HNC or CC samples with less than 80% tumor were laser capture microdissected from adjacent sections using a PixCell II LCM system. For guidance, an adjacent section was briefly stained with hematoxylin to visualize tissue structure. Total RNA was extracted from sectioned and/or microdissected samples as follows: 1 ml of TRIzol (Invitrogen, Carlsbad, CA) was added to each tissue sample, homogenized by passing through a 20 gauge needle, and added to 0.2 ml chloroform. After centrifugation at 20,000 xg for 20 min at 4oC, RNA in the aqueous phase was precipitated with an equal volume of isopropanol for 30 min at 4oC, pelleted, and washed twice with cold 70% ethanol. Double strand (ds) cDNA was synthesized from this RNA using a SuperScript ds cDNA synthesis kit (Invitrogen) and T7 promoter-linked oligo (dT)24. Complementary RNA (cRNA) was synthesized from T7 promoter-linked ds cDNA using a MEGAscript high transcription kit (Ambion, Austin, TX). To obtain a sufficient cRNA for 2 microarray hybridizations, this amplification process was repeated. Second round cRNA was biotin labeled using a BioArray High Yield RNA Transcript Labeling Kit (Enzo Life Sciences, Farmingdale, NY) and stored at -80oC until hybridized. cRNA quality and quantity was determined by gel electrophoresis and UV spectrophotometry. Whole human gene expression was profiled using Affymetrix Human Genome U133 Plus 2.0 arrays.

Dataset Information

Deep sequencing detects human papillomavirus (HPV) in cervical cancers negative for HPV by PCR.

Background

Methods

Results

Conclusions

Publications

Deep sequencing detects human papillomavirus (HPV) in cervical cancers negative for HPV by PCR.

Similar Datasets

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