Cargando…

Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma

The distinction between Keratoacanthoma (KA) and Cutaneous Squamous Cell Carcinoma (cSCC) is critical yet usually challenging to discriminate clinically and histopathologically. One approach to differentiate KA from cSCC is through assessing the immunohistochemical staining patterns of the three ind...

Descripción completa

Detalles Bibliográficos
Autores principales: Fan, Xinyun, Niu, Xueli, Wu, Ze, Yao, Lu, Chen, Shirui, Wan, Wenyu, Huang, Bo, Qi, Rui-Qun, Zhang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427316/
https://www.ncbi.nlm.nih.gov/pubmed/36051475
http://dx.doi.org/10.1155/2022/3168503
_version_ 1784778872735137792
author Fan, Xinyun
Niu, Xueli
Wu, Ze
Yao, Lu
Chen, Shirui
Wan, Wenyu
Huang, Bo
Qi, Rui-Qun
Zhang, Tao
author_facet Fan, Xinyun
Niu, Xueli
Wu, Ze
Yao, Lu
Chen, Shirui
Wan, Wenyu
Huang, Bo
Qi, Rui-Qun
Zhang, Tao
author_sort Fan, Xinyun
collection PubMed
description The distinction between Keratoacanthoma (KA) and Cutaneous Squamous Cell Carcinoma (cSCC) is critical yet usually challenging to discriminate clinically and histopathologically. One approach to differentiate KA from cSCC is through assessing the immunohistochemical staining patterns of the three indicators, β-catenin, C-Myc, and CyclinD1, which are critical molecules that play important roles in the Wnt/β-catenin signaling pathway. Ki-67, as a proliferation biomarker for human tumor cells, was also assessed as an additional potential marker for differentiating KA from cSCC. In this report, these four indicators were analyzed in 42 KA and 30 cSCC cases with the use of the computer automated image analysis system. Computer automated image analysis is a time-based and cost-effective method of determining IHC staining in KA and cSCC samples. We found that C-Myc staining was predominantly localized in the nuclei of basal cells within KA patients, whereas cSCC staining was predominantly localized in the nuclei of diffuse cells. This C-Myc staining pattern has a sensitivity of 78.6% and a specificity of 66.7% for identifying KA. Moreover, positive rates of distinct expression patterns of C-Myc and Ki-67 may also serve as a means to clinically distinguish KA from cSCC. Taken together, our results suggest that these markers, in particular C-Myc, may be useful in differentiating KA from cSCC.
format Online
Article
Text
id pubmed-9427316
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-94273162022-08-31 Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma Fan, Xinyun Niu, Xueli Wu, Ze Yao, Lu Chen, Shirui Wan, Wenyu Huang, Bo Qi, Rui-Qun Zhang, Tao Biomed Res Int Research Article The distinction between Keratoacanthoma (KA) and Cutaneous Squamous Cell Carcinoma (cSCC) is critical yet usually challenging to discriminate clinically and histopathologically. One approach to differentiate KA from cSCC is through assessing the immunohistochemical staining patterns of the three indicators, β-catenin, C-Myc, and CyclinD1, which are critical molecules that play important roles in the Wnt/β-catenin signaling pathway. Ki-67, as a proliferation biomarker for human tumor cells, was also assessed as an additional potential marker for differentiating KA from cSCC. In this report, these four indicators were analyzed in 42 KA and 30 cSCC cases with the use of the computer automated image analysis system. Computer automated image analysis is a time-based and cost-effective method of determining IHC staining in KA and cSCC samples. We found that C-Myc staining was predominantly localized in the nuclei of basal cells within KA patients, whereas cSCC staining was predominantly localized in the nuclei of diffuse cells. This C-Myc staining pattern has a sensitivity of 78.6% and a specificity of 66.7% for identifying KA. Moreover, positive rates of distinct expression patterns of C-Myc and Ki-67 may also serve as a means to clinically distinguish KA from cSCC. Taken together, our results suggest that these markers, in particular C-Myc, may be useful in differentiating KA from cSCC. Hindawi 2022-08-23 /pmc/articles/PMC9427316/ /pubmed/36051475 http://dx.doi.org/10.1155/2022/3168503 Text en Copyright © 2022 Xinyun Fan et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fan, Xinyun
Niu, Xueli
Wu, Ze
Yao, Lu
Chen, Shirui
Wan, Wenyu
Huang, Bo
Qi, Rui-Qun
Zhang, Tao
Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title_full Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title_fullStr Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title_full_unstemmed Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title_short Computer Image Analysis Reveals C-Myc as a Potential Biomarker for Discriminating between Keratoacanthoma and Cutaneous Squamous Cell Carcinoma
title_sort computer image analysis reveals c-myc as a potential biomarker for discriminating between keratoacanthoma and cutaneous squamous cell carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9427316/
https://www.ncbi.nlm.nih.gov/pubmed/36051475
http://dx.doi.org/10.1155/2022/3168503
work_keys_str_mv AT fanxinyun computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT niuxueli computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT wuze computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT yaolu computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT chenshirui computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT wanwenyu computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT huangbo computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT qiruiqun computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma
AT zhangtao computerimageanalysisrevealscmycasapotentialbiomarkerfordiscriminatingbetweenkeratoacanthomaandcutaneoussquamouscellcarcinoma