Pushing and loss of elastic fibers are highly specific for melanoma and rare in melanocytic nevi

Identifying SCC Lesions Capable of Spontaneous Regression by Using Immunohistochemistry: A Systematic Review and Meta-Analysis

INTRODUCTION

Keratoacanthoma (KA) and squamous cell carcinoma (SCC) are two cutaneous conditions with morphological resemblance, which can complicate the diagnosis in some cases. Using immunohistochemistry staining of biomarkers could be beneficial in resolving this obstacle.

OBJECTIVES

We investigated a variety of biomarkers assessed in different studies in order to find the most important and helpful biomarkers for differentiation between SCC and lesions capable of spontaneous regression.

METHODS

MEDLINE via PubMed and Google Scholar database were used to identify relevant literature up to 15 June 2022. The aim of our analyses was to determine the capability of biomarkers to distinguish between SCC and lesions capable of spontaneous regression using calculated individual and pooled odds ratios (OR) and 95% confidence intervals (CI) and I2 tests.

RESULTS

Six potential biomarkers were CD10 with pooled OR= 0.006 (95% CI: 0.001-0.057) and I2=0%; COX-2 with pooled OR=0.089 (95% CI: 0.029-0.269) and I2=17.1%; elastic fibers with pooled OR= 6.69 (95% CI: 2.928-15.281) and I2=0%; IMP-3 with pooled OR=0.145 (95% CI: 0.021-1.001) and I2=44.5%; P53 with pooled OR=0.371 (95% CI: 0.188-0.733) and I2=55.9%; AT1R with OR=0.026 (95% CI: 0.006-0.107).

CONCLUSIONS

We suggest the utilization of the following IHC biomarkers for discrimination between lesions with spontaneous regression such as KA and SCC: CD10, COX-2, and elastic fibers.

Assessment of Elastic Fibers in Tumor Stroma as a New Method to Predict 6-Year Outcomes for Gastric Cancer Patients

Purpose: This study aimed to determine whether detecting elastic fibers in tumor stroma (EFTS) could be used as a new method for predicting the prognosis of gastric cancer (GC) patients.

Materials and Methods: EFTS expression was determined by histochemistry in 160 GC patients who underwent gastrectomy. Based on the staining results, the patients were divided into three groups according to their EFTS expression level: low (n = 57), moderate (n = 50), and high (n = 53). The clinicopathological data and 6-year survival data were analyzed among different EFTS groups.

Results: The expression of EFTS was closely related to lymphovascular invasion (P = 0.010), blood transfusion in operation (P < 0.001), recurrence rate (P < 0.001), and motility (P < 0.001). High expression of EFTS was also correlated with recurrence-free survival (RFS) and overall survival (OS) in GC patients by Kaplan–Meier curve (P < 0.001 for RFS and P < 0.001 for OS).

Conclusions: Multivariate analysis showed that EFTS was an independent prognostic factor for RFS and OS. In conclusion, detecting EFTS to predict the prognosis of GC patients is effective and highly feasible.