Evidence map›Paper›PMID 34036652›Full record

ArticleExperimental dermatology2021

Detection of viral gene expression in risk-stratified biopsies reveals no active HPV in cutaneous squamous cell carcinoma.

Amy R Vandiver, Brandon J Thomas, Mohammad Karimzada, Byron C Knowles, Giovanni A Botten, Roberto Spreafico, Jeremy N Rotman, Nima M Gharavi, Cameron Chesnut, Kevin Wesel and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Experimental dermatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 6 institutions in 1 country.

Amy R VandiverDepartment of Medicine, Division of Dermatology, University of California, Los Angeles, CA, USA.ORCID 0000-0003-2176-9161
Brandon J ThomasDavid Geffen School of Medicine, University of California at Los Angeles, CA, USA.
Mohammad KarimzadaDavid Geffen School of Medicine, University of California at Los Angeles, CA, USA.
Byron C KnowlesDepartment of Dermatology, University of California at San Francisco, CA, USA.
Giovanni A BottenInstitute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA, USA.
Roberto SpreaficoInstitute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA, USA.
Jeremy N RotmanDepartment of Computer Science, University of California, Los Angeles, CA, USA.
Nima M GharaviDepartment of Dermatology and Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Cameron ChesnutUniversity of Washington School of Medicine, Spokane, WAS, USA.
Kevin WeselDepartment of Computer Science, University of California, Los Angeles, CA, USA.
Serghei MangulDepartment of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
Teresa SorianoDepartment of Medicine, Division of Dermatology, University of California, Los Angeles, CA, USA.
Philip O ScumpiaDepartment of Medicine, Division of Dermatology, University of California, Los Angeles, CA, USA.
University of California, Los Angeles · USQB3 · USCedars-Sinai Medical Center · USUniversity of California, San Francisco · USUniversity of Southern California · USWashington State University Spokane · US

Funding

MULTIDISCIPLINARY TRAINING IN MICROBIAL PATHOGENESIST32AI007323 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Peter John Bradley · 1988 to 2026
$8.6M
Dermatology Scientist Training ProgramT32AR071307 · NIAMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MODLIN, ROBERT L · 2017 to 2021
$1.1M
Regulation of macrophage transcriptional networks by stress pathways in the skinK08AR066545 · NIAMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SCUMPIA, PHILIP · 2014 to 2018
$781k
NIAID NIH HHS T32 AI007323NIAMS NIH HHS K08 AR066545NIAMS NIH HHS T32 AR071307
6 · The paper itself

Abstract

backgroundHuman papillomavirus (HPV) infection is known to promote the development of mucosal squamous cell carcinoma (mSCC), including pathologically high-grade lesions, but its role in cutaneous squamous cell carcinoma (cuSCC) remains unclear, particularly in lesions that are considered high risk.

objectiveWe aimed to determine whether enhanced HPV transcriptional activity can be detected in high-risk cuSCC samples compared with low-grade SCC samples or normal skin.

methodsWe performed RNA sequencing of cuSCC across 23 risk-stratified skin lesions. A subset of samples was tested for the presence of HPV DNA. High-quality, non-human reads from each sample group were used for viral analysis using Microbiome Coverage Profiler.

resultsNone of the samples analysed had detectable expression of HPV RNA, while 64% of samples tested positive for HPV DNA. All samples were found to have expression of human endogenous retrovirus, and multiple samples showed expression of other viruses.

conclusionsViral and prophage gene expression can be monitored in cuSCC or normal skin biopsies, yet no sample in our study showed evidence of active HPV gene expression despite evidence of HPV genome presence. This suggests HPV transcription does not play a role in differentiating high-risk cuSCCs from low-risk cuSCCs or normal skin.

Indexed as

Gene ExpressionAgedBiopsyCarcinoma, Squamous CellDNA Probes, HPVFemaleHumansMalePapillomaviridaePapillomavirus InfectionsRisk AssessmentSkin NeoplasmsDNA Probes, HPVhigh-risk SCCHPVimmunosuppressionSCC

Identifiers

PMID34036652
PMCPMC9639216
OpenAlexW3165287692

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.