Evidence map›Paper›PMID 37419445›Full record

ArticleThe Journal of investigative dermatology2023

Distinguishing Keratoacanthoma from Well-Differentiated Cutaneous Squamous Cell Carcinoma Using Single-Cell Spatial Pathology.

Jesse Veenstra, David Ozog, Ian Loveless, Indra Adrianto, Peter Dimitrion, Kalpana Subedi, Ben J Friedman, Li Zhou, Qing-Sheng Mi

Open access · greenAbstract read
In one paragraph

Article in The Journal of investigative dermatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

10 citing papers in PubMed, 13 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Jesse VeenstraDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA; Center for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA; Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
David OzogDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA; Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
Ian LovelessCenter for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA; Center for Bioinformatics, Department of Public Health Sciences, Henry Ford Health, Detroit, Michigan, USA; Department of Computational Mathematics, Science, and Engineering; Medical Imaging and Data Integration Lab; Michigan State University, East Lansing, Michigan, USA.
Indra AdriantoCenter for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA; Center for Bioinformatics, Department of Public Health Sciences, Henry Ford Health, Detroit, Michigan, USA; Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
Peter DimitrionCenter for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA.
Kalpana SubediDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA; Center for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA.
Ben J FriedmanDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA.
Li ZhouDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA; Center for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA; Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA.
Qing-Sheng MiDepartment of Dermatology, Henry Ford Health, Detroit, Michigan, USA; Center for Cutaneous Biology and Immunology, Henry Ford Health, Detroit, Michigan, USA; Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, Michigan, USA; Department of Internal Medicine, Henry Ford Health, Detroit, Michigan, USA. Electronic address: qmi1@hfhs.org.
Henry Ford Health System · USFord Motor Company (United States) · US

Funding

Genetic and Genomic Dissection of Psoriatic ArthritisR01AR063611 · NIAMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ELDER, JAMES TILFORD, GLADMAN, DAFNA D · 2012 to 2023
$6.2M
Using whole-exome sequencing to uncover key genetic variants related to Hidradenitis Suppurativa risk in African American and Hispanic population.R01AR078688 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIAO, WILSON, MI, QING-SHENG · 2021 to 2025
$4.1M
Roles of HDAC3 in Epidermal Langerhans Cell Ontogeny and FunctionR01AR069681 · NIAMS · HENRY FORD HEALTH SYSTEM · PI MI, QING-SHENG · 2016 to 2020
$1.7M
MicroRNAs regulate skin Langerhans cellsR01AR072046 · NIAMS · HENRY FORD HEALTH SYSTEM · PI ZHOU, LI · 2018 to 2022
$1.6M
Uncover the new subsets of epidermal Langerhans cellsR61AR076803 · NIAMS · HENRY FORD HEALTH SYSTEM · PI ADRIANTO, INDRA, MI, QING-SHENG · 2019 to 2020
$746k
Genetic risk of hidradenitis suppurativa in African AmericansR21AR079089 · NIAMS · HENRY FORD HEALTH SYSTEM · PI ADRIANTO, INDRA, MI, QING-SHENG · 2022 to 2023
$520k
Uncover the new subsets of epidermal Langerhans cellsR33AR076803 · NIAMS · HENRY FORD HEALTH SYSTEM · PI ADRIANTO, INDRA, MI, QING-SHENG · 2021 to 2021
$380k
Decoding TGF-beta signaling pathways in skin langerhans cellsR56AI165991 · NIAID · HENRY FORD HEALTH SYSTEM · PI MI, QING-SHENG, ZHOU, LI · 2022 to 2022
$376k
NIAID NIH HHS R56 AI165991NIAMS NIH HHS R01 AR063611NIAMS NIH HHS R01 AR069681NIAMS NIH HHS R01 AR072046NIAMS NIH HHS R01 AR078688NIAMS NIH HHS R21 AR079089NIAMS NIH HHS R33 AR076803NIAMS NIH HHS R61 AR076803
6 · The paper itself

Abstract

Keratoacanthoma (KA) is a common keratinocyte neoplasm that is regularly classified as a type of cutaneous squamous cell carcinoma (cSCC) despite demonstrating benign behavior. Differentiating KA from well-differentiated cSCC is difficult in many cases due to the substantial overlap of clinical and histological features. Currently, no reliable discriminating markers have been defined, and consequently, KAs are often treated similarly to cSCC, creating unnecessary surgical morbidity and healthcare costs. In this study, we used RNA sequencing to identify key differences in transcriptomes between KA and cSCC, which suggested divergent keratinocyte populations between each tumor. Imaging mass cytometry was then used to identify single-cell tissue characteristics, including cellular phenotype, frequency, topography, functional status, and interactions between KA and well-differentiated cSCC. We found that cSCC had significantly increased proportions of Ki67+ keratinocytes among tumor keratinocytes, which were dispersed significantly throughout non-basal keratinocyte communities. In cSCC, regulatory T-cells were more prevalent and held greater suppressive capacity. Furthermore, cSCC regulatory T-cells, tumor-associated macrophages, and fibroblasts had significant associations with Ki67

Indexed as

Carcinoma, Squamous CellKeratoacanthomaSkin NeoplasmsHumansKeratinocytesKi-67 AntigenKi-67 Antigen

Identifiers

PMID37419445
PMCPMC10840781
OpenAlexW4383198135

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.