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

Biomed Res Int. 2022 Aug 23:2022:3168503. doi: 10.1155/2022/3168503. eCollection 2022.

Abstract

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.

MeSH terms

  • Carcinoma, Squamous Cell* / pathology
  • Computers
  • Humans
  • Keratoacanthoma* / diagnosis
  • Keratoacanthoma* / metabolism
  • Keratoacanthoma* / pathology
  • Ki-67 Antigen
  • Skin Neoplasms* / pathology

Substances

  • Ki-67 Antigen