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Background: Basal cell carcinoma (BCC) is the most frequently diagnosed skin cancer and the most common malignancy in humans. Different morphological subtypes of BCC are associated with a low or high risk of recurrence and aggressiveness, but the underlying biology of how the individual subtypes arise remains largely unknown. As the majority of BCCs appear to arise from mutations in the same pathway, we hypothesized that BCC development, growth and invasive potential is also influenced by the tumour microenvironment and, in particular, by cancer-associated fibroblasts (CAFs) and the factors they secrete., Objectives: To characterize the stroma of the different BCC subtypes with a focus on CAF populations., Methods: To investigate the stromal features of the different BCC subtypes, we used laser capture microdissection (LCM) followed by RNA sequencing (RNA-Seq). Fifteen BCC samples from five different 'pure' subtypes (i.e. superficial, nodular, micronodular, sclerosing and basosquamous; n = 3 each) were selected and included in the analysis. Healthy skin was used as a control (n = 6). The results were confirmed by immunohistochemistry (IHC). We validated our findings in two independent public single-cell RNA-Seq (scRNA-Seq) datasets and by RNAscope., Results: The stroma of the different BCC subtypes were found to have distinct gene expression signatures. Nodular and micronodular appeared to have the most similar signatures, while superficial and sclerosing the most different. By comparing low- and high-risk BCC subtypes, we found that COL10A1 is overexpressed in the stroma of sclerosing/infiltrative and basosquamous but not in micronodular high-risk subtypes. Those findings were confirmed by IHC in 93 different BCC and 13 healthy skin samples. Moreover, scRNA-Seq analysis of BCCs from two independent datasets found that the COL10A1-expressing population of cells is associated with the stroma adjacent to infiltrative BCC and shows extracellular matrix remodelling features., Conclusions: We identified COL10A1 as a marker of high-risk BCC, in particular of the sclerosing/infiltrative and basosquamous subtypes. We demonstrated at the single-cell level that COL10A1 is expressed by a specific CAF population associated with the stroma of infiltrative BCC. This opens up new, tailored treatment options, and suggests COL10A1 as a new prognostic biomarker for BCC progression., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Association of Dermatologists.)

The skin is the most affected organ by cancer. The incidence rates of skin cancer are steadily increasing, both for melanoma and non-melanoma skin cancers (squamous cell carcinoma, basal cell carcinoma). Over 90 % of the death cases from skin cancers attribute to melanoma. Survival from melanoma is strongly related to tumour thickness. Therefore early detection is the most important step to improve prognosis. In the last years a number of new non invasive techniques for the early diagnosis of melanoma have been developed which are superior to the naked eye examination. In this overview article we present some non-invasive diagnostic techniques like total body photography, digital dermoscopy and confocal microscopy which in addition to dermoscopy assist the dermatologist in differentiating nevi from early melanomas.Non-melanoma skin cancer can be prevented by accurate sun protection. Early squamous cell carcinomas and basal cell carcinomas can be treated either invasively or non-invasively with excellent prognosis.

Background: Semitranslucency, defined as a smooth, jelly-like area with varied, near-skin-tone color, can indicate a diagnosis of basal cell carcinoma (BCC) with high specificity. This study sought to analyze potential areas of semitranslucency with histogram-derived texture and color measures to discriminate BCC from non-semitranslucent areas in non-BCC skin lesions., Methods: For 210 dermoscopy images, the areas of semitranslucency in 42 BCCs and comparable areas of smoothness and color in 168 non-BCCs were selected manually. Six color measures and six texture measures were applied to the semitranslucent areas of the BCC and the comparable areas in the non-BCC images., Results: Receiver operating characteristic (ROC) curve analysis showed that the texture measures alone provided greater separation of BCC from non-BCC than the color measures alone. Statistical analysis showed that the four most important measures of semitranslucency are three histogram measures: contrast, smoothness, and entropy, and one color measure: blue chromaticity. Smoothness is the single most important measure. The combined 12 measures achieved a diagnostic accuracy of 95.05% based on area under the ROC curve., Conclusion: Texture and color analysis measures, especially smoothness, may afford automatic detection of BCC images with semitranslucency.