Dermatology: Practical and Conceptual Review | Dermatol Pract Concept. 2024;14(2):e2024047 1 Identifying SCC Lesions Capable of Spontaneous Regression by Using Immunohistochemistry: A Systematic Review and Meta-Analysis Maryam Hedayati1, Behzad Garousi2, Zahrasadat Rezaei2, Yasaman Nazerian3, Younes Yassaghi3, Arian Tavasol4, Dorsa Bahrami Zanjanbar5, Sanaz Sharifpour6, Amir Golestani7, Mansoor Bolideei8, Farajolah Maleki9 1 Zhejiang University School of Medicine, Hangzhou, China 2 Department of Pathology, Karolinska Institute, Stockholm, Sweden 3 School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran 4 Student Research Committee, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran 5 Pharmaceutical Science Research Center, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran 6 Islamic Azad University Tehran Medical Branch, Tehran, Iran 7 Students Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran 8 The Center for Biomedical Research, Ministry of Education and Ministry of Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan, China 9 Non-Communicable Diseases Research Center, Ilam University of Medical Sciences, Ilam, Iran Key words: keratoacanthoma (KA), squamous cell carcinoma (SCC), immunohistochemistry, CD10, COX-2, elastic fibers, lesions capable of spontaneous regression Citation: Hedayati M, Garousi B, Rezaei Z, et al. Identifying SCC Lesions Capable of Spontaneous Regression by Using Immunohistochemistry: A Systematic Review and Meta-Analysis Study. Dermatol Pract Concept. 2024;14(2):e2024047. DOI: https://doi.org/10.5826/dpc.1402a47 Accepted: November 1, 2023; Published: April 2024 Copyright: ©2024 Hedayati et al. This is an open-access article distributed under the terms of the Creative Commons Attribution- NonCommercial License (BY-NC-4.0), https://creativecommons.org/licenses/by-nc/4.0/, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original authors and source are credited. Funding: None. Competing Interests: None. Authorship: All authors have contributed significantly to this publication. Behzad Garousi, Zahrasadat Rezaei contributed equally to this work. Corresponding Author: Mansoor Bolideei, The Center for Biomedical Research, Ministry of Education and Ministry of Health, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan 430030, China. E-mail: bolaydaei@gmail.com Introduction: Keratoacanthoma (KA) and squamous cell carcinoma (SCC) are two cutaneous con- ditions 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 spon- taneous regression. ABSTRACT 2 Review | Dermatol Pract Concept. 2024;14(2):e2024047 Introduction Cutaneous squamous cell carcinoma is the second most com- mon non-melanoma malignant tumor of the skin, following basal cell carcinoma (BCC), and is also the leading cause of death related to non-melanoma skin cancer. The incidence rate of cutaneous SCC is rising continuously, primarily be- cause of population aging and an increased screening rate [1, 2]. It is characterized by the uncontrolled proliferation of atypical keratinocytes within the epidermis, which should be excised. Apart from population aging, other risk factors are mainly genetic factors, male sex, smoking, immunosup- pression, and ultraviolet irradiation, primarily due to sun ex- posure [3, 4]. Early diagnosis of such lesions is crucial. The diagnosis is based on the appearance, location (sun- exposed), and the patient’s medical history. More importantly, the phy- sician’s suspicion would lead to more evaluation and eventu- ally to reaching the diagnosis [5]. The gold standard for SCC diagnosis is still to obtain a skin biopsy and histopathologic evaluation[6]. Keratoacanthoma (KA), on the other hand, is considered a premalignant lesion with the potential capacity for trans- formation into SCC and is, therefore, a precursor of SCC. However, meta-analysis studies have pointed out a 12% probability of the transformation of KA into SCC [7]. In- deed, KA is a spontaneously regressing type of SCC [8]. If not transformed into SCC, KA would regress spontaneously within weeks [9]. Similar to SCC, the gold standard method of diagnosis of lesions capable of spontaneous regression is tissue biopsy and histological findings [7]. It should be mentioned that some studies consider KA, which are lesions capable of spontaneous regression, as a sub- branch of SCC [10, 11], and other studies do not consider these two diseases as separate from each other [12]. Although the features of these 2 types of lesions are alike in some as- pects, the outcomes diverge. Hence, it is imperative to discrim- inate between these lesions. Nevertheless, a solid criterion is lacking for this manner [9]. A number of studies have assessed the role of diverse cellular and nuclear markers in the differen- tiation between these two lesions. Some of these markers have been evaluated in several studies, while other markers have been determined in single studies. In this study, we intended to analyze the effectiveness of these markers in identifying le- sions capable of spontaneous regression like KA and SCC. 2. Methods The present systematic review and meta-analysis was per- formed based on the PRISMA statement. 2.1 Search Strategy and Screening To determine  research studies that assessed Immunohisto- chemistry (IHC) biomarkers participating in differentiating between SCC and lesions capable of spontaneous regres- sion, a literature search was conducted  using 'MEDLINE via PubMed and Google Scholar database up to 15 June 2022. The following keywords were used in the search: “ker- atoacanthomas,” “KA,” “lesions capable of spontaneous regression,” “squamous cell carcinoma,” “SCC,” “differenti- ation,” “diagnoses,” “biomarkers,” and “IHC.” The authors screened the titles, abstracts, and full texts of selected articles to choose the relevant articles. 2.2 Inclusion and Exclusion Criteria The inclusion criteria based on the full text were: (1) as- sessing the IHC biomarkers in differentiating between SCC and lesions capable of spontaneous regression; (2) analyzing the IHC biomarkers on subtypes of skin cancers that must contain lesions capable of spontaneous regression and SCC. The exclusion criteria were: (1) publications not in English; (2) non-IHC methods; (3) analysis of other subtypes of skin cancers without containing both SCC and lesions capable of spontaneous regression. Methods: MEDLINE via PubMed and Google Scholar database were used to identify relevant liter- ature 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. Review | Dermatol Pract Concept. 2024;14(2):e2024047 3 2.3 Data Extraction Two authors reviewed all the suitable publications. Ex- tracted data were organized into an Excel spreadsheet. The following data were collected from each study: first author’s name, publication year, journal, biomarker(s), sample size (total and individual SCC and lesions capable of sponta- neous regression), IHC staining positivity of lesions capable of spontaneous regression samples, and the significance of statistical analyses (obtained P value). 2.4 Statistical Analysis R software was used to conduct statistical analyses to com- pare the odds ratio (OR) with 95% CI of SCC and lesions capable of spontaneous regression. Pooled ORs with 95% CI and I2 test for heterogeneity were calculated for the bio- markers investigated in at least 2 publications. The con- sistency of studies was evaluated by the I2 heterogeneity test, which is interpreted as follows: 0% represents no in- consistency, and 100% represents total heterogeneity. The significance of heterogeneity was considered if the P value was <0.1. 3. Results 3.1 Relevant Studies and Flowchart Among 64 relevant manuscripts, 33 were excluded based on the inclusion and exclusion criteria. Thirty-one relevant publications from 1989 to 2021 were reviewed, and data were extracted for analysis (Table 1). Overall, 43 biomark- ers were studied, of which 14/43 were assessed in at least two studies, and 23/43 were investigated once. This selec- tion is shown in Figure 1. The OR and 95% CI of these biomarkers were evaluated. Finally, seven significantly ef- fective biomarkers that could differentiate between SCC and lesions capable of spontaneous regression were selected and are discussed. 3.2 Meta-analysis The individual and pooled OR and P values of 24 single [13- 26] and 13 repeated [14, 18-20, 23-25, 27-41] biomarkers are listed in Table 2 and Table 3. The odds of lesions ca- pable of spontaneous regression IHC staining of a specific biomarker, compared with SCC, represent the OR. Calcu- lated infinite OR was excluded due to insensible analysis. However, in order to include studies with zero calculated OR, Peto’s  method was used. These selected biomarkers’ capability to differentiate between SCC and lesions capable of spontaneous regression was demonstrated by statistically significant OR with 95% CI. AT1R was the single IHC bio- marker, and CD-10, COX-2, elastic fibers, IMP-3, and P53 were repeated IHC biomarkers. 3.3 Cluster of Differentiation 10 The cluster of differentiation (CD) 10 is a cell surface ectoen- zyme marker used for the diagnosis and differentiation of cancers [42]. There is a correlation between tumor cell prolif- eration and the number of CD10+ dermal tumor- associated macrophages (TAM) and epidermal Langerhans cells (LC) in the development of epidermal tumors. Indeed, these compo- nents are important cellular elements of the tumor microen- vironment. It has been reported that the number of LCs in SCC and malignant melanoma is lower than in normal skin. It is assumed that the induction of CD10+ stromal cells may be associated with the infiltration of TAMs and loss of LCs. Therefore, CD10+ stromal cell induction, increased TAMs, and decreased LCs are related to each other, and these 3 items correlate with the rate of tumor proliferation [27]. Two similar studies were evaluated to determine whether CD-10 can serve as a differentiating biomarker for SCC and lesions capable of spontaneous regression [27, 34]. Together, these two studies had 60 samples, of which only four samples of lesions capable of spontaneous regression were positive for CD-10 IHC staining compared with all positive SCC sam- ples (33 samples). The pooled OR was calculated at 0.006 (95% CI: 0.001–0.057) for lesions capable of spontaneous regression compared to SCC, meaning that the tendency of SCC lesions to have positive IHC staining for CD-10 was 166.7 times higher in comparison with lesions capable of spontaneous regression. There was also no statistically sig- nificant heterogeneity between studies (I2=0%). 3.4 Cyclooxygenase 2 Cyclooxygenase 2 (COX2) is a key enzyme that produces prostaglandins involved in  the inflammatory process [43]. A total of two studies were reviewed for this biomarker [23, 29]. The pooled OR of these studies (lesions capable of spontaneous regression compared with SCC) was calculated at 0.089 (95% CI: 0.029–0.269). These two studies did not have heterogeneity since I2=17.1%. For this reason, the OR of COX-2 IHC staining for SCC compared with lesions ca- pable of spontaneous regression was 11.2. 3.5 Elastic Fiber Elastic fibers are extracellular components that exist in many tissues, such as the skin, and are important for the skin’s physiological processes [44]. Data extracted from two studies [30, 45] were assessed for this biomarker, revealing a calculated pooled OR of 6.69 (95% CI: 2.928–15.281) for lesions capable of spontaneous regression compared with SCC. Of 118 total samples, 47 were positive for lesions ca- pable of spontaneous regression, while 15 were positive for SCC. The calculated I2 was 0%, meaning that the studies were consistent with one another. 4 Review | Dermatol Pract Concept. 2024;14(2):e2024047 Table 1. Characteristics of included studies. Author Year Total sample size Mean Age (KA) Mean Age (SCC) Biomarkers Stephenson et al. [24] 1992 88 P53/nm23 Urano et al. [33] 1992 27 P53 Kerschmann et al. [35] 1994 50 P53 Watanabe et al. [77] 2015 40 P53/ Ki-67/ CD-34/ CD-105 Cain et al. [36] 1995 24 P53/ PCNA Sakiz et al.[20] 2009 29 P53/P63 Vasiljevic et al. [14] 2009 89 P53/ Ki-67/ P16/ Bcl-xL/ Bcl-x/ CD-3/ CD-20/ CD68/ NFκB/ IκBα/ STAT3/ pRb/ P21/ Survivin/ BAK/ FLK-1/ Cyld/ TRAP-1/ Caspase-3 Batinac et al. [37] 2006 120 68.5 76.3 P53/ Ki-67/BAK/ Bcl-2/ Ribeiro et al. [18] 2008 108 P53/PCNA/Bcl-2/MIB-1 /Caspase-3 Khodaeiani et al. [38] 2013 18 p53/ ki-67/ Bedir et al. [25] 2016 70 71 74 p53/ki-67/p16/p21/p27 Putti et al. [23] 2004 41 P53/COX-2/Telomerase Leblebici et al. [84] 2017 51 63.7 74.6 Ki-67/ Cytokeratin-17 Takahara et al. [27] 2009 30 Ki-67/CD-10/CD-68 /CD-1a Soddu et al. [32] 2013 67 69.5 76.1 IMP-3 Kanzaki et al. [31] 2016 23 61.7 78.4 IMP3 Hua et al. [29] 2015 55 COX-2 Markey et al. [19] 1990 15 B2M/ MHC II Graham et al. [39] 1987 91 62.4 69.7 B2M Jordan et al. [45] 1991 100 66.2 74 Elastic Fiber Philips et al. [30] 1993 18 Elastic Fiber/ PCNA Kaabipour et al. [40] 2006 48 66.3 74.5 P16 Tan et al. [26] 2009 55 Bcl-x Tanikawa et al. [41] 1992 12 P21 Cabibi et al. [17] 2016 30 62 74 HSP60/ CD-1a Gambichler et al. [22] 2017 47 PD-L1 Krunic et al. [15] 1998 36 Dsg1 and Dsg2 Takeda et al. [13] 2001 72 AT1R Jia et al. [16] 2021 45 63 63.6 HSP-105 Tran et al. [21] 2000 55 OSM Gouda et al. [28] 2014 35 P53/ Ki-67/CD10 3.6 Insulin-like Growth Factor 2 mRNA-binding Protein The insulin-like growth factor 2 (IGF-2) mRNA-binding protein (IMP) is a protein family that binds to IGF-2 mRNA and regulates its transcription [46]. Previous studies evaluat- ing IMP-3 as a biomarker for differentiating between SCC and lesions capable of spontaneous regression were con- ducted by Soddu et al. and by Kanzaki et al. [31, 32]. In the former study, 9/34 were positive for lesions capable of spontaneous regression compared to 19/33 for SCC. In the latter study, all eight samples of lesions capable of sponta- neous regression were negative, while 10/15 of SCC samples were positive for IHC staining of IMP-3. The pooled OR of these two studies was 0.145 (95% CI: 0.021–1.001), which is defined as a 6.9 times greater tendency of SCC lesions for IMP-3- positive staining compared with lesions capable of Review | Dermatol Pract Concept. 2024;14(2):e2024047 5 Figure 1. Prisma flow diagram illustrating the selection of articles. Table 2. Results of 13 biomarkers with repeated studies. Biomarkers Pooled OR (KA/SCC) 95% CI I2 P value of pooled OR (calculated) CD10 0.006 0.001 – 0.057 0% <0.0001 COX-2 0.089 0.029 – 0.269 17.1% <0.0001 Elastic Fiber 6.689 2.928 – 15.281 0% <0.0001 P53 0.371 0.188 – 0.733 55.9% 0.004 IMP-3 0.145 0.021 – 1.001 44.5% 0.05 Ki-67 OR=0.143 0.026 – 0.774 - 0.024 B2M 18.13 0.251 – 1309.386 77.6% 0.184 PCNA 2.032 0.902 – 4.579 0% 0.087 P16 1.176 0.483 – 2.866 - - P21 OR=1.75 0.512 – 5.978 - 0.372 BAK 4.90 0.252 – 95.68 59.9% 0.294 BCL-2 OR=0.689 0.323 – 1.472 - 0.337 Caspase 3 2.562 0.032 – 206.1 97.1% 0.674 spontaneous regression. Although the calculated I2 test was 44.5%, this heterogeneity was not statistically significant. 3.7 P53 P53 is a tumor suppressant transcription factor that, upon activation, causes downstream events that suppress cell cy- cle and proliferation [47]. For a careful assessment of the capability of P53 for the differentiation of SCC and lesions capable of spontaneous regression, a total of 12 studies were reviewed [14, 18, 20, 23, 25, 33-38, 48]. There were 730 samples (lesions capable of spontaneous regression=354, SCC=376) with a calculated pooled OR (lesions capable of spontaneous regression compared with SCC) of 0.371 (95% CI: 0.188–0.733). The I2 percentage of heterogeneity was 55.9%, which was statistically significant. Individual and pooled ORs are shown in Figure 2. 3.8 Angiotensin II Receptor Type 1 Angiotensin II receptor type 1 (AT1R) is one of the two types of angiotensin II receptors, which, after activation, is respon- sible for the homeostasis of blood pressure and body elec- trolytes, alongside other effects. Among the other effects of 6 Review | Dermatol Pract Concept. 2024;14(2):e2024047 Table 3. Results of 24 biomarkers with single study. Biomarker OR (KA/SCC) 95% CI Obtained P value from studies Calculated P value of OR AT1R 0.026 0.006 – 0.107 - <0.0001 CD-20 Infinite - N/S - CD-3 Infinite - N/S - CD-68 0.981 0.309 – 3.109 N/S 0.974 Cyld Infinite - N/S - Dsg 1 & 2 10.714 0.559 – 205.382 - 0.116 FLK-1 Infinite - N/S - HSP-105 0.733 0.138 – 3.88 - 0.716 HSP-60 8.81 0.385 – 201.383 <0.05 0.173 IκBα 0.264 0.014 – 5.078 N/S 0.377 MHC-II 1.2 0.121 – 11.865 - 0.876 MIB-1 0.074 0.004 – 1.348 <0.05 0.079 NF-κB Infinite - N/S - OSM 3.529 0.947 – 13.153 0.001 0.06 P63 Infinite - - - PD-L1 1.357 0.387 – 4.759 - 0.633 STAT-3 0.49 0.023 – 10.571 N/S 0.649 Survivin Infinite - N/S - TRAP-1 0.708 0.137 – 3.666 N/S 0.681 Telomerase 0.448 0.017 – 11.659 0.001 0.629 nm-23 Infinite - 0.189 - P-27 Infinite - 0.744 - pRb Infinite - N/S - Bcl-xl 1.029 0.29 – 3.642 <0.001 0.965 AT1R activation are cell growth and migration [49]. In the study by Takeda et al. [13], AT1R was evaluated in 72 sam- ples (22 lesions capable of spontaneous regression samples compared with 50 SCC samples): 5/22 samples of lesions ca- pable of spontaneous regression were positive on AT1R IHC staining, while 46/50 SCC samples had the same result (cal- culated P<0.0001). The calculated OR (lesions capable of spontaneous regression in comparison with SCC) was 0.026 (95% CI: 0.006–0.107), meaning that the SCC lesions were 38.4 times more likely to express AT1R than lesions capable of spontaneous regression. 4. Discussion Mentioned above is that the gold standard for the diagnosis of both SCC and lesions capable of spontaneous regression is biopsy sampling and histopathological evaluation, and that all of the evaluated lesion samples in the studies that we reviewed for IHC staining of various biomarkers had been previously diagnosed for SCC or as lesions capable of spon- taneous regression. Therefore, it is worth mentioning that IHC staining of these diverse biomarkers is beneficial where a net diagnosis between these two lesions, with the capabil- ity of spontaneous regression, is complex and challenging [9, 50]. More importantly, it should be considered that this diversity in biomarkers indicates that the diagnosis based on one biomarker is insensible. Hence, a combination of these biomarkers should be utilized to differentiate between SCC and lesions capable of spontaneous regression. For this reason, we investigated a variety of biomarkers assessed in different studies to identify the most significant and useful biomarkers for this differentiation. Of all 43 biomarkers, af- ter statistical analyses of the extracted data, six biomarkers had significantly more probability of distinguishing between the two entities. Five out of six biomarkers were assessed in two or more studies, including CD-10, COX-2, elastic fibers, IMP-3, and P53. The other biomarker, AT1R, was evaluated in only one study. Other biomarkers that were investigated repeatedly were Ki-67, B2M, PCNA, P16, P21, BAK, Bcl- 2, Caspase-3, and CD-1a. Repeated biomarkers are highly important since they give us information across the studies, and their analysis results are more reliable. For a complete Review | Dermatol Pract Concept. 2024;14(2):e2024047 7 Figure 2. Forest plot for P53. evaluation, the consistency of these studies was assessed by statistical analysis. The reviewed studies for CD10 had a similar trend of OR for comparison of SCC and lesions capable of sponta- neous regression. Therefore, the results of the statistical sig- nificance of this biomarker for differentiation are reliable. CD10 is expressed in the epithelial cells of various tissues and has been widely used in diagnosing different skin can- cers, including SCC, BCC, and melanoma [51]. The overex- pression of CD10 in skin cancer cells promotes rapid tumor progression and proliferation, leading to a higher grade and a larger tumor size [52-54]. Following the analysis for CD10, the pooled OR was cal- culated at 0.006 (95% CI: 0.001–0.057) for lesions capable of spontaneous regression compared to SCC. For this reason, CD10 can distinguish between SCC and lesions capable of spontaneous regression, since SCC lesions are 166.7 times more likely to be positive for the IHC of this biomarker. Therefore, SCC lesions are biologically more progressive, with a higher proliferation rate, than lesions capable of spontaneous regression [55]. All reviewed studies had the same OR calculation equal to 0.006. Although the num- ber of studies was limited, the combined total sample size of these studies was acceptable. Furthermore, there was no significant heterogeneity between studies, as I2 = 0%. Taken together, CD10 can be used as an applicable biomarker to differentiate between these lesions. Another biomarker is COX-2, which is expressed in skin lesions and through the production of prostaglandins[56]; it is involved in the initiation, invasion, and angiogenesis of tu- mors and also participates in the suppression of the immune system [57, 58]. UV exposure can induce COX-2 expres- sion, leading to skin malignancies [59, 60]. COX-2 has been demonstrated to be effective in the differentiation between benign and malignant skin lesions [59, 61]. Two studies were reviewed to assess the capability of COX-2 to differentiate between SCC and lesions capable of spontaneous regression. These studies were consistent since the calculated I2=17.1 % was not significant. More- over, the trend of OR of these studies was similar. In this study, we demonstrate that COX-2 IHC positivity was 11.2 times more positive for SCC compared to lesions capable of spontaneous regression since the calculated pooled OR was 0.089 (95% CI: 0.029–0.269). According to these results, we can conclude that SCC has a more progressive and inva- sive behavior compared to lesions capable of spontaneous regression. Taken together, with a considerable sample size, we can indicate COX-2 as an acceptable biomarker for the differentiation between SCC and lesions capable of sponta- neous regression. 8 Review | Dermatol Pract Concept. 2024;14(2):e2024047 20, 23, 25, 28, 35-38, 48, 77, 78], two were excluded due to the calculation of OR since the results were calculated as infinite. Of the remaining ten studies, the trend of OR was towards lesions capable of spontaneous regression, while for other studies, this trend was towards SCC. The calculated OR of that single study was 2.67. Considering the weight of the study (11.93%) compared with other studies, this calcu- lated OR could be ignored. The pooled OR comparing the IHC positivity of lesions capable of spontaneous regression and SCC for P53 was 0.371, and it was statistically signif- icant. In other words, SCC would express P53 3.69 times more than lesions capable of spontaneous regression. The reviewed studies were inconsistent since I2= 55.9%, which was statistically significant. However, this heterogeneity of the studies could be considered moderate. This indicates that P53 could distinguish between SCC and lesions capable of spontaneous regression when used as a biomarker, but care should be taken so that it is not assessed without other biomarkers. Although the activation of AT1R has homeostatic effects, studies suggest its role and expression in different types of malignancies [79]. Also, a number of studies have investi- gated its expression on cancerous cells, revealing AT1R’s role in tumor genesis [80]. Consistent with this implication, sev- eral treatment approaches were utilized for the management of a number of malignancies, and the results were promising [81, 82]. Moreover, IHC staining of this receptor was eval- uated in previous studies for skin lesions, which suggests a high probability of its differentiation capability between skin lesions [83]. AT1R was investigated in one study, by Takeda et al. [13]. SCC significantly expressed AT1R compared with lesions capable of spontaneous regression, with OR (lesions capable of spontaneous regression compared with SCC) of 0.026 (95% CI: 0.006–0.107). Ki-67, aside from the biomarkers discussed above, had a significant OR in our analyses as well. This biomarker was investigated in six studies [14, 25, 34, 37, 38, 84], five of which were excluded during the analyses due to infinite calculated ORs, which were insensible. The OR of the re- maining study was 0.143, indicating a probability of IHC positivity for Ki-6 comparing lesions capable of spontaneous regression with SCC, which was significant. However, when we assessed the excluded studies, all SCC and lesions capa- ble of spontaneous regression samples for each study were entirely positive. This implies that Ki-67 may not be an ac- ceptable biomarker for the differentiation between SCC and lesions capable of spontaneous regression. Some of the evaluated biomarkers had a high calculated OR compared with other biomarkers, although they were not statistically significant. These biomarkers were B2M, BAK, Dsg1 &2, HSP60, and MIB-1, and their calculated ORs were 18.1, 4.9, 10.7, 8.81, and 0.074, respectively. Elastic fibers are components of dermal connective tissue that maintain the elasticity of the skin. They have consider- able distinguishing capabilities between malignancies. Loss of these fibers more often occurs in malignant tumors than in benign lesions [62-64]. The calculated pooled OR, com- paring lesions capable of spontaneous regression with SCC, was 6.69 (95% CI: 2.928–5.281) with I2=0%. Considering the total sample size of these studies, which was 118, and no significant heterogeneity, the results are reliable. The ten- dency of OR for these two studies was consistent (6.167 and 13.333), confirming the reliability of the results. The other biomarker is IMP-3. The members of the IMP family are IMP-1, IMP-2, and IMP-3, which bind to the tran- script of IGF-2 mRNA [65]. Particularly, the overexpression of IMP-3 has been detected in several malignant cancers [65- 70]. Also, the role of this protein has been investigated as a biomarker to differentiate between benign and malignant le- sions, including melanoma [71] and SCC [72]. Furthermore, IMP-3 increases the migration of the malignant cells and leads to the invasiveness of the tumor [73]. For this reason, as it is likely that IMP-3 can differentiate between SCC and lesions capable of spontaneous regression, it was evaluated in this manner. In our study, two studies were reviewed for the assessment of IMP-3 IHC staining. These studies were not significantly heterogeneous; however, the calculated I2 was 44.5%, which is high compared to other biomarkers. Therefore, the results should be considered more cautiously. The pooled OR was 0.145 (95% CI: 0.021–1.001), with individual ORs equal to 0.265 and 0.031. This means that SCC lesions’ biological be- havior is more invasive than that of lesions capable of spon- taneous regression. Although this pooled OR was considered statistically significant, IMP-3 was 3.9 times more likely to be positive for SCC in the Soddu et al. study [32], while in the Kanzaki et al. study [31], it was 32.2 times more likely to be positive for SCC. This suggests the diversity between the results of these two studies. In other words, IMP-3 should be taken into consideration for the differentiation between SCC and lesions capable of spontaneous regression, but more cautiously and in addition to other biomarkers. P53 protein is one of the most studied tumor suppressant proteins recognized to date. It is capable of regressing and inhibiting tumors, and the development of many tumors may occur with the mutation of the P53 gene [47]. As discussed in other studies, skin cells with previously mutated P53 genes can develop skin lesions after exposure to the sun [74]. It would seem that P53 is a good biomarker for differentiating between malignant tumors and other lesions, especially in the skin, as other studies have investigated in the past and recently [75, 76]. The highest number of studies in our study were re- viewed for this biomarker. Among these 12 studies [14, 18, Review | Dermatol Pract Concept. 2024;14(2):e2024047 9 4. Kim JYS, Kozlow JH, Mittal B, Moyer J, Olenecki T, Rodgers P. Guidelines of care for the management of cutaneous squamous cell carcinoma. J Am Acad Dermatol. 2018;78(3):560-578. doi:10.1016/j.jaad.2017.10.007 5. Combalia A, Carrera C. Squamous cell carcinoma: an update on diagnosis and treatment. Dermatology Practical & Conceptual. 2020;10(3). doi: 10.5826/dpc.1003a66 6. Hu C, Liu X, Wang P, et al. Dermoscopy and ultrosound mon- itoring actinic keratosis with cutaneous squamous cell car- cinoma: A case report and literature review. 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Pathology-Research and Practice. 2008;204(2):97-104. doi:10.1016/j.prp.2007.10.005 Therefore, these biomarkers could be potentially evaluated in future studies for this purpose. The limitation of our study may be the high number of investigated biomarkers among the small number of studies for each biomarker. Also, there was heterogeneity in the type of reference standard of the studies we reviewed; because the reference standard of the studies was different from one an- other, and since the number of our studies was not enough, we could not group the studies that were similar in terms of the standard reference into a subgroup or exclude some of them. Therefore, heterogeneity may be seen in the results that was explained above; for future studies, it is therefore suggested to consider studies that have a similar standard reference (such as hematoxylin). In addition, the range of the marker’s cutoff for positivity or negativity was also the same as above. Of course, it should be mentioned that the cutoff of our studies was almost the same, and there were no statistically significant differences. 5. Conclusion In summary, the results of our study show that a number of biomarkers, including CD10, COX-2, and elastic fibers, have a high capability of differentiating between SCC lesions and lesions with the capability of spontaneous regression, such as KA, in cases with a difficult diagnosis. IMP-3, P53, and AT1R could also be utilized in this manner; however, more investigation is required. The presence of these biomarkers was investigated through IHC staining and can be used in the clinical approach to SCC and KA lesions. Acknowledgments: No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this article. The authors declare that they have no conflict of interest. Ethical Approval: This review article is exempt from ethical approval. References 1. 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