The cover image is based on the Research Article Near-infrared radiation causes sebaceous gland enlargement along with an ROS-dependent augmentation of epidermal growth factor receptor expression in hamsters by Shiho Tanaka et al., https://doi.org/10.1111/exd.14878.
Melanoma is a melanocyte-derived malignant cancer and is known for its early metastasis and high mortality rates. It is a highly cutaneous tumour disease that could be related to the abnormal immune microenvironment, and the identification of reliable diagnostic and prognostic markers is crucial for improving patient outcomes. In the search for biomarkers, various types of RNAs have been discovered and recognized as reliable prognostic markers. Among these, small nucleolar RNAs (snoRNAs) have emerged as a promising avenue for studying early diagnosis and prognostic markers in tumours due to their widespread presence in tissues, tumour specificity and stability. In our study, we analysed snoRNAs data from melanoma samples in the TCGA-SKCM cohort and developed a prognostic model comprising 12 snoRNAs (SNORD9, SNORA31, SNORD14E, SNORA14A, SNORA5A, SNORD83A, SNORA75, AL096855, AC007684, SNORD14A, SNORA65 and AC004839). This model exhibited unique prognostic accuracy and demonstrated a significant correlation with the immune infiltration tumour microenvironment. Additionally, analysis of the GSE213145 dataset, which explored the sensitivity and resistance of immune checkpoint inhibitors, further supported the potential of snoRNAs as prognostic markers for immunotherapy. Overall, our study contributes reliable prognostic and immune-related biomarkers for melanoma patients. These findings can offer valuable insights for the future discovery of novel melanoma treatment strategies and hold promise for improving clinical outcomes in melanoma patients.
Atypical pigmented facial lesions (aPFLs)—including lentigo maligna (LM) and lentigo maligna melanoma (LMM), solar lentigo (SL), pigmented actinic keratosis (PAK), atypical nevi (AN), seborrheic keratosis (SK) and lichen planus-like keratosis (LPLK)—can exhibit clinical and dermoscopic overlapping features. We aimed to investigate if and how 14 dermoscopic features suggestive for the aforementioned aPFLs vary according to six facial sites among 1197 aPFLs cases (excised to rule out malignancy) along with lesion and patients' metadata. According to distribution and association analysis, aPFLs on the forehead of a male patient aged > 69 years displaying the obliterated follicular openings pattern, appear to be more at risk of malignancy. Of converse, aPFLs of the orbital/cheek/nose area with evident and regular follicular openings with diameter < 10 mm in a female aged below 68 are probably benign. The obliterated follicular openings, keratin plugs, evident and regular follicular openings and target-like pattern features differed significantly among six facial areas in all aPFLs cases. Lesion of the nose may show both features suggestive of malignancy and benignity (e.g. many SL and PAK may display target-like pattern and some LM/LMM cases display keratin plugs and evident and follicular openings), making these features less specific.
The skin is the largest organ in the human body, and histologically consists of the epidermis, dermis and subcutaneous tissue. Humans maintain a cooperative symbiotic relationship with their skin microbiota, a complex community of bacteria, fungi and viruses that live on the surface of the skin, and which act as a barrier to protect the body from the inside and outside. The skin is a ‘habitat’ and vast ‘ecosystem’ inhabited by countless microbes; as such, relationships have been forged through millions of years of coevolution. It is not surprising then that microbes are key participants in shaping and maintaining essential physiological processes. In addition to maintaining barrier function, the unique symbiotic microbiota that colonizes the skin increases the immune response and provides protection against pathogenic microbes. This review examines our current understanding of skin microbes in shaping and enhancing the skin barrier, as well as skin microbiome–host interactions and their roles in skin diseases, such as atopic dermatitis (AD). We also report on the current status of AD therapeutic drugs that target the skin microbiome, related research on current therapeutic strategies, and the limitations and future considerations of skin microbiome research. In particular, as a future strategy, we discuss the need for a skin-on-a-chip-based microphysiological system research model amenable to biomimetic in vitro studies and human skin equivalent models, including skin appendages.
Severe cutaneous adverse drug reactions, including Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN), are challenging to be early diagnosed and evaluate their prognoses. This investigation aimed to analyse the expression profiles of SJS/TEN in peripheral blood mononuclear cells (PBMC) and assess the correlation between circular RNA (circRNA) and disease severity. Sixteen SJS/TEN patients and sixteen controls were enrolled and serum samples of both groups were obtained. CircRNA expression profiles in three SJS/TEN patients and three controls were detected by RNA sequencing and bioinformatic analyses were then performed. The differentially expressed circRNAs were verified by quantitative polymerase chain reaction (qPCR). Then, analysing the correlation of circRNAs with the toxic epidermal necrolysis-specific severity of illness score (SCORTEN) and the epidermal detachment area. A total of 134 circRNAs were differentially expressed in the PBMCs of SJS/TEN individuals, according to our results. The qPCR showed that three circRNAs (hsa_circ_0000711, hsa_circ_0083619 and hsa_circ_0005615) were down-regulated, and one circRNA (hsa_circ_0003028) was up-regulated, which were compatible with the sequencing findings. The concentration of hsa_circ_0083619 was closely associated with the SCORTEN scale (r = −0.581, p = 0.037) and the epidermal detachment area (r = −0.576, p = 0.039). The circRNA-miRNA-mRNA prediction network was used to construct the hsa_circ_0083619/miR-18a-5p/BCL2L10 axis. The hsa_circ_0083619 could serve as a disease severity indicator for SJS/TEN. Through bioinformatics analysis, we speculated that hsa_circ_0083619/miR-18a-5p/BCL2L10 axis might play a role in SJS/TEN pathogenesis.
Psoriasis is a frequent chronic, recurrent and immune-mediated inflammatory skin disease, whose pathogenesis remains unclear at present. The role of antiviral protein in the pathogenesis of psoriasis is the focus of current research. Interferon stimulated gene 15 (ISG15) is an important antiviral protein. In this study, the expression of ISG15 saw a significant increase through the immunohistochemical detection of imiquimod (IMQ)-induced mice. In the psoriasis cell model, a remarkable increase also occurred in the expression of ISG15. In this study, it was found that the cell cycle was blocked in G1/S conversion, and a reduction took place in the proliferation of keratinocytes and the expression of a cell cycle-related protein—cyclin D1 after the knockout of ISG15 in the psoriasis cell model. After that, messenger ribonucleic acid (mRNA) sequencing and Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) analysis indicated its close association with the hypoxia inducible factor-1α (HIF-1α) signalling pathway. Western blot showed a decrease in the expression of HIF-1α and vascular endothelial growth factor C (VEGFC) after the knockout of the ISG15 gene. The rescue experiment verified that ISG15 promotes the proliferation of keratinocytes by regulating the HIF-1α signalling pathway. It was concluded that psoriasis cells and mouse models witnessed the increased expression of ISG15. In psoriasis, knocking out ISG15 inhibits the proliferation of keratinocytes and blocks the cell cycle. Besides, ISG15 promotes the proliferation of keratinocytes through the HIF-1α signalling pathway.
Artificial intelligence (AI) is a field of computer science that involves the development of programs designed to replicate human cognitive processes and the analysis of complex data. In dermatology, which is predominantly a visual-based diagnostic field, AI has become increasingly important in improving professional processes, particularly in the diagnosis of psoriasis. In this review, we summarized current AI applications in psoriasis: (i) diagnosis, including identification, classification, lesion segmentation, lesion severity and area scoring; (ii) treatment, including prediction treatment efficiency and prediction candidate drugs; (iii) management, including e-health and preventive medicine. Key challenges and future aspects of AI in psoriasis were also discussed, in hope of providing potential directions for future studies.