PRRX1 silencing is required for metastatic outgrowth in melanoma and is an independent prognostic of reduced survival in patients.

Paired related homeobox 1 (PRRX1) is an inducer of epithelial-to-mesenchymal transition (EMT) in different types of cancer cells. We detected low PRRX1 expression in nevus but increased levels in primary human melanoma and cell lines carrying the BRAFV600E mutation. High expression of PRRX1 correlates with invasiveness and enrichment of genes belonging to the EMT programme. Conversely, we found that loss of PRRX1 in metastatic samples is an independent prognostic predictor of poor survival for melanoma patients. Here, we show that stable depletion of PRRX1 improves the growth of melanoma xenografts and increases the number of distant spontaneous metastases, compared to controls. We provide evidence that loss of PRRX1 counteracts the EMT phenotype, impairing the expression of other EMT-related transcription factors, causing dysregulation of the ERK and signal transducer and activator of transcription 3 (STAT3) signaling pathways, and abrogating the invasive and migratory properties of melanoma cells while triggering the up-regulation of proliferative/melanocytic genes and the expression of the neural-crest-like markers nerve growth factor receptor (NGFR; also known as neurotrophin receptor p75NTR) and neural cell adhesion molecule L1 (L1CAM). Overall, our results indicate that loss of PRRX1 triggers a switch in the invasive programme, and cells de-differentiate towards a neural crest stem cell (NCSC)-like phenotype that accounts for the metastatic aggressiveness.

Actinic keratosis: Current challenges and unanswered questions.

Actinic keratoses (AK) are common skin lesions associated with chronic exposure to sun. They are believed to be precursors of malignancy as they potentially may progress to invasive squamous cell carcinomas. The goal of current therapies is to reduce the number of AK and to prevent future cancer development. This review aims at providing an overview of the hallmarks of AK and skin field cancerization. We discuss epidemiology trends, risk factors and the state of the art and evidence of the current treatments. We review key figures of AK prevalence from different countries with regard to skin cancer risk and the associated economic burden of AK. We discuss the mutational status in AK lesions and the difficulties encountered by clinicians in evaluating AK visible and invisible lesions, referring to the concept of field cancerization. Based on a systematic literature review, we further evaluate the available treatment options. The presence of subclinical skin alterations in the periphery of visible AK lesions has gained a particular attention as those non-visible lesions are known to contain the same genetic changes as those found in the AK lesions themselves, prompting the concept of 'field cancerization'. Therefore, AK treatment guidelines now recognize the importance of treating the field in patients with AK. A recent systematic literature review and network meta-analysis showed that 5-FU interventions were associated with the best efficacy and a satisfactory acceptability profile compared with other field-directed therapies used in the treatment of AK. Although AK are considered quite common, they lack an accurate descriptive definition and conclusive epidemiologic data. Limited public awareness is a barrier to early and effective treatment, including prevention strategies. While different treatment options are available, there is still a limited understanding of long-term outcomes of treatment as measured by recurrence of cancer prevention.

Understanding the Dermoscopic Patterns of Basal Cell Carcinoma Using Line-Field Confocal Tomography.

Basal cell carcinoma (BCC) is the most frequent malignancy in the general population. To date, dermoscopy is considered a key tool for the diagnosis of BCC; nevertheless, line-field confocal optical coherence tomography (LC-OCT), a new non-invasive optical technique, has become increasingly important in clinical practice, allowing for in vivo imaging at cellular resolution. The present study aimed to investigate the possible correlation between the dermoscopic features of BCC and their LC-OCT counterparts. In total, 100 histopathologically confirmed BCC cases were collected at the Dermatologic Clinic of the University of Siena, Italy. Predefined dermoscopic and LC-OCT criteria were retrospectively evaluated, and their frequencies were calculated. The mean (SD) age of our cohort was 65.46 (13.36) years. Overall, BCC lesions were mainly located on the head (49%), and they were predominantly dermoscopically pigmented (59%). Interestingly, all dermoscopic features considered had a statistically significant agreement with the LC-OCT criteria (all p < 0.05). In conclusion, our results showed that dermoscopic patterns may be associated with LC-OCT findings, potentially increasing accuracy in BCC diagnosis. However, further studies are needed in this field.

Predictive and Prognostic Factors in Melanoma Central Nervous System Metastases-A Cohort Study.

BACKGROUND: Melanoma is the cancer with the highest risk of dissemination to the central nervous system (CNS), one of the leading causes of mortality from this cancer. OBJECTIVE: To identify patients at higher risk of developing CNS metastases and to evaluate associated prognostic factors. METHODS: A cohort study (1998-2023) assessed patients who developed CNS melanoma metastases. Multivariate logistic regression was used to identify predictive factors at melanoma diagnosis for CNS metastasis. Cox regression analysis evaluated the CNS-independent metastasis-related variables impacting survival. RESULTS: Out of 4718 patients, 380 (8.05%) developed CNS metastases. Multivariate logistic regression showed that a higher Breslow index, mitotic rate ≥ 1 mm2, ulceration, and microscopic satellitosis were significant risk factors for CNS metastasis development. Higher patient age and the location of the primary tumor in the upper or lower extremities were protective factors. In survival analysis, post-CNS metastasis, symptomatic disease, prior non-CNS metastases, CNS debut with multiple metastases, elevated LDH levels, and leptomeningeal involvement correlated with poorer survival. CONCLUSION: Predictive factors in the primary tumor independently associated with brain metastases include microscopic satellitosis, ulceration, higher Breslow index, and trunk location. Prognostic factors for lower survival in CNS disease include symptomatic disease, multiple CNS metastases, and previous metastases from different sites.

BCN20000: Dermoscopic Lesions in the Wild.

Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial intelligence model training. Furthermore, a ninth out-of-distribution (OOD) class is also present on the test set, comprised of lesions which could not be distinctively classified as any of the others. By providing a comprehensive collection of varied images, BCN20000 helps bridge the gap between the training data for machine learning models and the day-to-day practice of medical practitioners. Additionally, we present a set of baseline classifiers based on state-of-the-art neural networks, which can be extended by other researchers for further experimentation.

Prognostic Value of the Neutrophil-to-lymphocyte Ratio, Platelet-to- lymphocyte Ratio and Monocyte-to-lymphocyte Ratio in Melanoma Patients: A Cohort Study.

The prognostic value of the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio in patients with melanoma has yielded controversial results in the literature. A retrospective single-centre cohort study was conducted from 1998 to 2020, including patients diagnosed with invasive melanoma. A total of 2,721 patients were included in the study. The median follow-up was 8.23 years (IQR 4.41-13.25). The median baseline neutrophil- lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio values increased significantly (p < 0.001) with the increasing American Joint Committee on Cancer stage. The optimal cut-off values for neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio were determined as 2.1, 184 and 0.2, respectively. In the multivariate analysis, high levels of neutrophil-lymphocyte ratio (≥ 2.1), platelet-lymphocyte ratio (≥ 184) and monocyte-lymphocyte ratio (≥ 0.2) were independently associated with significantly shorter melanoma-specific survival (neutrophil-lymphocyte ratio: HR 1.30, 95% CI 1.06-1.60, p = 0.013; platelet-lymphocyte ratio: HR 1.37, 95% CI 1.06-1.76, p = 0.014; monocyte- lymphocyte ratio: HR 1.29, 95% CI 1.05-1.58, p = 0.015) and overall survival (neutrophil-lymphocyte ratio: HR 1.39, 95% CI 1.19-1.64, p < 0.001; platelet- lymphocyte ratio: HR 1.44, 95% CI 1.19-1.74, p < 0.001; monocyte-lymphocyte ratio: HR 1.42, 95% CI 1.21-1.66, p < 0.001). High levels of neutrophil- lymphocyte ratio and monocyte-lymphocyte ratio were also associated with poor relapse-free survival, while platelet-lymphocyte ratio was not. In conclusion, baseline neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio were identified as independent predictors for the prognosis of melanoma.

A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification.

Introduction: Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with 'untrained' or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign. Another limitation often raised is the lack of clinical context (e.g., medical history) used as input for the AI decision process. The increasing use of Total Body Photography (TBP) in clinical examinations presents new opportunities for AI to perform holistic analysis of the whole patient, rather than a single lesion. Currently there is a lack of existing literature or standards for image annotation of TBP, or on preserving patient privacy during the machine learning process. Methods: This protocol describes the methods for the acquisition of patient data, including TBP, medical history, and genetic risk factors, to create a comprehensive dataset for machine learning. 500 patients of various risk profiles will be recruited from two clinical sites (Australia and Spain), to undergo temporal total body imaging, complete surveys on sun behaviors and medical history, and provide a DNA sample. This patient-level metadata is applied to image datasets using DICOM labels. Anonymization and masking methods are applied to preserve patient privacy. A two-step annotation process is followed to label skin images for lesion detection and classification using deep learning models. Skin phenotype characteristics are extracted from images, including innate and facultative skin color, nevi distribution, and UV damage. Several algorithms will be developed relating to skin lesion detection, segmentation and classification, 3D mapping, change detection, and risk profiling. Simultaneously, explainable AI (XAI) methods will be incorporated to foster clinician and patient trust. Additionally, a publicly released dataset of anonymized annotated TBP images will be released for an international challenge to advance the development of new algorithms using this type of data. Conclusion: The anticipated results from this protocol are validated AI-based tools to provide holistic risk assessment for individual lesions, and risk stratification of patients to assist clinicians in monitoring for skin cancer.

European consensus-based interdisciplinary guideline for diagnosis, treatment and prevention of actinic keratoses, epithelial UV-induced dysplasia and field cancerization on behalf of European Association of Dermato-Oncology, European Dermatology Forum, European Academy of Dermatology and Venereology and Union of Medical Specialists (Union Européenne des Médecins Spécialistes).

A collaboration of multidisciplinary experts from the European Association of Dermato-Oncology, the European Dermatology Forum, the European Academy of Dermatology and Venereology, and the European Union of Medical Specialists was formed to develop European recommendations on AK diagnosis and treatment, based on current literature and expert consensus. This guideline addresses the epidemiology, diagnostics, risk stratification and treatments in immunocompetent as well as immunosuppressed patients. Actinic keratoses (AK) are potential precursors of cutaneous squamous cell carcinoma (cSCC) and display typical histopathologic and immunohistochemical features of this malignancy in an early stage. They can develop into cSSC in situ and become invasive in a low percentage of cases. AK is the most frequent neoplasia in white populations, frequently occurring within a cancerous field induced by ultraviolet radiation. Since it cannot be predicted, which lesion will progress to cSCC and when treatment is usually recommended. The diagnosis of AK and field cancerization is made by clinical examination. Dermatoscopy, confocal microscopy, optical coherence tomography or line-field confocal-OCT can help in the differential diagnosis of AK and other skin neoplasms. A biopsy is indicated in clinically and/or dermatoscopically suspicious and/or treatment-refractory lesions. The choice of treatment depends on patients' and lesion characteristics. For single non-hyperkeratotic lesions, the treatment can be started upon patient's request with destructive treatments or topical treatments. For multiple lesions, field cancerization treatment is advised with topical treatments and photodynamic therapy. Preventive measures such as sun protection, self-examination and repeated field cancerization treatments of previously affected skin areas in high-risk patients are advised.

Dermatoscopic patterns of cutaneous metastases: A multicentre cross-sectional study of the International Dermoscopy Society.

BACKGROUND: The detection of cutaneous metastases (CMs) from various primary tumours represents a diagnostic challenge. OBJECTIVES: Our aim was to evaluate the general characteristics and dermatoscopic features of CMs from different primary tumours. METHODS: Retrospective, multicentre, descriptive, cross-sectional study of biopsy-proven CMs. RESULTS: We included 583 patients (247 females, median age: 64 years, 25%-75% percentiles: 54-74 years) with 632 CMs, of which 52.2% (n = 330) were local, and 26.7% (n = 169) were distant. The most common primary tumours were melanomas (n = 474) and breast cancer (n = 59). Most non-melanoma CMs were non-pigmented (n = 151, 95.6%). Of 169 distant metastases, 54 (32.0%) appeared on the head and neck region. On dermatoscopy, pigmented melanoma metastases were frequently structureless blue (63.6%, n = 201), while amelanotic metastases were typified by linear serpentine vessels and a white structureless pattern. No significant difference was found between amelanotic melanoma metastases and CMs of other primary tumours. CONCLUSIONS: The head and neck area is a common site for distant CMs. Our study confirms that most pigmented melanoma metastasis are structureless blue on dermatoscopy and may mimic blue nevi. Amelanotic metastases are typified by linear serpentine vessels and a white structureless pattern, regardless of the primary tumour.

A Narrative Review: Opportunities and Challenges in Artificial Intelligence Skin Image Analyses Using Total Body Photography.

Artificial intelligence (AI) algorithms for skin lesion classification have reported accuracy at par with and even outperformance of expert dermatologists in experimental settings. However, the majority of algorithms do not represent real-world clinical approach where skin phenotype and clinical background information are considered. We review the current state of AI for skin lesion classification and present opportunities and challenges when applied to total body photography (TBP). AI in TBP analysis presents opportunities for intrapatient assessment of skin phenotype and holistic risk assessment by incorporating patient-level metadata, although challenges exist for protecting patient privacy in algorithm development and improving explainable AI methods.

Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy.

Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments.

Validation of epidermal AMBRA1 and loricrin (AMBLor) as a prognostic biomarker for nonulcerated American Joint Committee on Cancer stage I/II cutaneous melanoma.

BACKGROUND: Combined expression of the autophagy-regulatory protein AMBRA1 (activating molecule in Beclin1-regulated autophagy) and the terminal differentiation marker loricrin in the peritumoral epidermis of stage I melanomas can identify tumour subsets at low risk of -metastasis. OBJECTIVES: To validate the combined expression of peritumoral AMBRA1 and loricrin (AMBLor) as a prognostic biomarker able to identify both stage I and II melanomas at low risk of tumour recurrence. METHODS: Automated immunohistochemistry was used to analyse peritumoral AMBRA1 and loricrin expression in geographically distinct discovery (n = 540) and validation (n = 300) cohorts of nonulcerated American Joint Committee on Cancer (AJCC) stage I and II melanomas. AMBLor status was correlated with clinical outcomes in the discovery and validation cohorts separately and combined. RESULTS: Analysis of AMBLor in the discovery cohort revealed a recurrence-free survival (RFS) rate of 95.5% in the AMBLor low-risk group vs. 81.7% in the AMBLor at-risk group (multivariate log-rank, P < 0.001) and a negative predictive value (NPV) of 96.0%. In the validation cohort, AMBLor analysis revealed a RFS rate of 97.6% in the AMBLor low-risk group vs. 78.3% in the at-risk group (multivariate log-rank, P < 0.001) and a NPV of 97.6%. In a multivariate model considering AMBLor, Breslow thickness, age and sex, analysis of the combined discovery and validation cohorts showed that the estimated effect of AMBLor was statistically significant, with a hazard ratio of 3.469 (95% confidence interval 1.403-8.580, P = 0.007) and an overall NPV of 96.5%. CONCLUSIONS: These data provide further evidence validating AMBLor as a prognostic biomarker to identify nonulcerated AJCC stage I and II melanoma tumours at low risk of disease recurrence.

Artificial Intelligence in Skin Cancer Diagnosis: A Reality Check.

The field of skin cancer detection offers a compelling use case for the application of artificial intelligence (AI) within the realm of image-based diagnostic medicine. Through the analysis of large datasets, AI algorithms have the capacity to classify clinical or dermoscopic images with remarkable accuracy. Although these AI-based applications can operate both autonomously and under human supervision, the best results are achieved through a collaborative approach that leverages the expertise of both AI and human experts. However, it is important to note that most studies focus on assessing the diagnostic accuracy of AI in artificial settings rather than in real-world scenarios. Consequently, the practical utility of AI-assisted diagnosis in a clinical environment is still largely unknown. Furthermore, there exists a knowledge gap concerning the optimal use cases and deployment settings for these AI systems as well as the practical challenges that may arise from widespread implementation. This review explores the advantages and limitations of AI in a variety of real-world contexts, with a specific focus on its value to consumers, general practitioners, and dermatologists.

Position statement of the EADV Artificial Intelligence (AI) Task Force on AI-assisted smartphone apps and web-based services for skin disease.

BACKGROUND: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer. OBJECTIVE: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI-assisted smartphone applications (apps) and web-based services for skin diseases with emphasis on skin cancer detection. METHODS: An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance. RESULTS: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non-medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web-based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users. CONCLUSIONS: The utilisation of AI-assisted smartphone apps and web-based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice.

Sphingolipid paracrine signaling impairs keratinocyte adhesion to promote melanoma invasion.

Melanoma is the deadliest form of skin cancer due to its propensity to metastasize. It arises from melanocytes, which are attached to keratinocytes within the basal epidermis. Here, we hypothesize that, in addition to melanocyte-intrinsic modifications, dysregulation of keratinocyte functions could initiate early-stage melanoma cell invasion. We identified the lysolipid sphingosine 1-phosphate (S1P) as a tumor paracrine signal from melanoma cells that modifies the keratinocyte transcriptome and reduces their adhesive properties, leading to tumor invasion. Mechanistically, tumor cell-derived S1P reduced E-cadherin expression in keratinocytes via S1P receptor dependent Snail and Slug activation. All of these effects were blocked by S1P2/3 antagonists. Importantly, we showed that epidermal E-cadherin expression was inversely correlated with the expression of the S1P-producing enzyme in neighboring tumors and the Breslow thickness in patients with early-stage melanoma. These findings support the notion that E-cadherin loss in the epidermis initiates the metastatic cascade in melanoma.

Line-Field Confocal Optical Coherence Tomography for the Diagnosis of Skin Carcinomas: Real-Life Data over Three Years.

Line-field confocal optical coherence tomography (LC-OCT) can help the clinical diagnosis of skin diseases. The present study aimed to evaluate the sensitivity, specificity, and diagnostic accuracy of LC-OCT for the diagnosis of the most frequent non-melanoma skin cancers (NMSCs), i.e., basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). Comparing LC-OCT diagnostic performances with those of dermoscopy, histopathological examination was used as a gold standard. For every study endpoint, the diagnostic ability of LC-OCT revealed superiority over the dermoscopic examination. In particular, a significant increase in specificity was observed. Sensitivity, specificity, and diagnostic accuracy of dermoscopy and LC-OCT for the diagnosis of malignancy were, respectively, 0.97 (CI 0.94-0.99), 0.43 (CI 0.36-0.51), and 0.77 (CI 0.72-0.81) for dermoscopy and 0.99 (CI 0.97-1.00), 0.90 (CI 0.84-0.94), and 0.96 (CI 0.93-0.97) for LC-OCT. The positive predictive value (PPV) resulted in 0.74 (CI 0.69-0.78) for dermoscopy and 0.94 (CI 0.91-0.97) for LC-OCT, and the negative predictive value (NPV) was 0.89 (CI 0.81-0.95) for dermoscopy and 0.98 (CI 0.95-1.00) for LC-OCT. Finally, our real-life study showed a potentially important role of LC-OCT in the non-invasive diagnosis of NMSCs, especially BCC. The real-time imaging technique could spare unnecessary biopsies with an increased sensitivity, a much higher specificity, and better accuracy than clinical assessment with dermoscopy alone.

European consensus-based interdisciplinary guideline for invasive cutaneous squamous cell carcinoma: Part 2. Treatment-Update 2023.

In order to update recommendations on treatment, supportive care, education, and follow-up of patients with invasive cutaneous squamous cell carcinoma (cSCC), a multidisciplinary panel of experts from the European Association of Dermato-Oncology (EADO), the European Dermatology Forum (EDF), the European Society for Radiotherapy and Oncology (ESTRO), the European Union of Medical Specialists (UEMS), the European Academy of Dermatology and Venereology (EADV), and the European Organisation of Research and Treatment of Cancer (EORTC) was formed. Recommendations were based on an evidence-based literature review, guidelines, and expert consensus. Treatment recommendations are presented for common primary cSCC (low risk, high risk), locally advanced cSCC, regional metastatic cSCC (operable or inoperable), and distant metastatic cSCC. For common primary cSCC, the first-line treatment is surgical excision with postoperative margin assessment or micrographically controlled surgery. Achieving clear surgical margins is the most important treatment consideration for patients with cSCCs amenable to surgery. Regarding adjuvant radiotherapy for patients with high-risk localised cSCC with clear surgical margins, current evidence has not shown significant benefit for those with at least one high-risk factor. Radiotherapy should be considered as the primary treatment for non-surgical candidates/tumours. For cSCC with cytologically or histologically confirmed regional nodal metastasis, lymph node dissection is recommended. For patients with metastatic or locally advanced cSCC who are not candidates for curative surgery or radiotherapy, anti-PD-1 agents are the first-line systemic treatment, with cemiplimab being the first approved systemic agent for advanced cSCC by the Food and Drugs Administration/European Medicines Agency. Second-line systemic treatments for advanced cSCC, include epidermal growth factor receptor inhibitors (cetuximab) combined with chemotherapy or radiotherapy. Multidisciplinary board decisions are mandatory for all patients with advanced cSCC, considering the risks of toxicity, the age and frailty of patients, and co-morbidities, including immunosuppression. Patients should be engaged in informed, shared decision-making on management and be provided with the best supportive care to improve symptom management and quality of life. The frequency of follow-up visits and investigations for subsequent new cSCC depends on underlying risk characteristics.