RESUMEN
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 low- or high-risk of recurrence and aggressiveness, but the underlying biology of how the individual subtypes arise remains largely unknown. Because 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 tumor microenvironment and in particular by cancer-associated fibroblasts (CAFs) and their secreted factors. OBJECTIVE: We aimed 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 applied laser-capture microdissection (LCM) followed by RNA sequencing. A cohort of 15 BCC samples from 5 different "pure" subtypes (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). We confirmed the results by immunohistochemistry. We validated our findings in two independent, public single-cell RNA sequencing (scRNAseq) datasets and by RNAscope. RESULTS: The stroma of the different BCC subtypes have distinct gene expression signatures. Nodular and micronodular seem to have the most similar signatures, while superficial and sclerosing the most different. By comparing low- and high-risk BCC subtypes, we observed that Collagen 10A1 (COL10A1) is overexpressed in the stroma of sclerosing/infiltrative and basosquamous but not micronodular high-risk subtypes. Those findings were confirmed by immunohistochemistry in a cohort of 89 different BCC and 13 healthy skin samples. Moreover, scRNAseq analysis of BCCs of two independent datasets showed that the COL10A1-expressing population of cells is associated with the stroma adjacent to invasive BCC and shows extracellular matrix remodeling features. CONCLUSION: 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 invasive BCC. This opens up new tailored treatment options as well as a new prognostic biomarker for BCC progression.
RESUMEN
We present an optimized dissociation protocol for preparing high-quality skin cell suspensions for in-depth single-cell RNA-sequencing (scRNA-seq) analysis of fresh and cultured human skin. Our protocol enabled the isolation of a consistently high number of highly viable skin cells from small freshly dissociated punch skin biopsies, which we use for scRNA-seq studies. We recapitulated not only the main cell populations of existing single-cell skin atlases, but also identified rare cell populations, such as mast cells. Furthermore, we effectively isolated highly viable single cells from ex vivo cultured skin biopsy fragments and generated a global single-cell map of the explanted human skin. The quality metrics of the generated scRNA-seq datasets were comparable between freshly dissociated and cultured skin. Overall, by enabling efficient cell isolation and comprehensive cell mapping, our skin dissociation-scRNA-seq workflow can greatly facilitate scRNA-seq discoveries across diverse human skin pathologies and ex vivo skin explant experimentations.
RESUMEN
Increasing incidence of antibiotic resistance in clinical and environmental settings calls for increased scalability in their surveillance. Current screening technologies are limited by the number of samples and genes that can easily be screened. We demonstrate here digital multiplex ligation assay (dMLA) as a low-cost targeted genomic detection workflow capable of highly-parallel screening of bacterial isolates for multiple target gene regions simultaneously. Here, dMLA is used for simultaneous detection of 1187 ß-lactamase-encoding genes, including extended spectrum ß-lactamase (ESBL) genes, in 74 bacterial isolates. We demonstrate dMLA as a light-weight and cost-efficient workflow which provides a highly scalable tool for antimicrobial resistance surveillance and is also adaptable to genetic screening applications beyond antibiotic resistance.
