Ultraviolet Filters: Dissecting Current Facts and Myths.

Skin cancer is a global and increasingly prevalent issue, causing significant individual and economic damage. UV filters in sunscreens play a major role in mitigating the risks that solar ultraviolet ra-diation poses to the human organism. While empirically effective, multiple adverse effects of these compounds are discussed in the media and in scientific research. UV filters are blamed for the dis-ruption of endocrine processes and vitamin D synthesis, damaging effects on the environment, induction of acne and neurotoxic and carcinogenic effects. Some of these allegations are based on scientific facts while others are simply arbitrary. This is especially dangerous considering the risks of exposing unprotected skin to the sun. In summary, UV filters approved by the respective governing bodies are safe for human use and their proven skin cancer-preventing properties make them in-dispensable for sensible sun protection habits. Nonetheless, compounds like octocrylene and ben-zophenone-3 that are linked to the harming of marine ecosystems could be omitted from skin care regimens in favor of the myriad of non-toxic UV filters.

Susceptibility of Melanoma Cells to Targeted Therapy Correlates with Protection by Blood Neutrophils.

Elevated levels of peripheral blood and tumor tissue neutrophils are associated with poorer clinical response and therapy resistance in melanoma. The underlying mechanism and the role of neutrophils in targeted therapy is still not fully understood. Serum samples of patients with advanced melanoma were collected and neutrophil-associated serum markers were measured and correlated with response to targeted therapy. Blood neutrophils from healthy donors and patients with advanced melanoma were isolated, and their phenotypes, as well as their in vitro functions, were compared. In vitro functional tests were conducted through nonadherent cocultures with melanoma cells. Protection of melanoma cell lines by neutrophils was assessed under MAPK inhibition. Blood neutrophils from advanced melanoma patients exhibited lower CD16 expression compared to healthy donors. In vitro, both healthy-donor- and patient-derived neutrophils prevented melanoma cell apoptosis upon dual MAPK inhibition. The effect depended on cell-cell contact and melanoma cell susceptibility to treatment. Interference with protease activity of neutrophils prevented melanoma cell protection during treatment in cocultures. The negative correlation between neutrophils and melanoma outcomes seems to be linked to a protumoral function of neutrophils. In vitro, neutrophils exert a direct protective effect on melanoma cells during dual MAPK inhibition. This study further hints at a crucial role of neutrophil-related protease activity in protection.

Preferences of physicians for treatment-related toxicity vs. recurrence in melanoma (GERMELATOX-A): the doctors' perspective.

INTRODUCTION: Adjuvant treatment with immune checkpoint inhibitors, such as PD1-antibodies (ICI) ± CTLA4-antibodies (cICI) or targeted therapy with BRAF/MEK inhibitors (TT), has shown a significant improvement in disease-free survival (DFS) for high-risk melanoma patients. However, due to specific side effects, the choice of treatment is often influenced by the risk of toxicity. Therefore, the role of physicians in treatment decisions of patients is crucial. This study investigated for the first time in a multicenter setting the attitudes and preferences of dermatooncologists in Germany and Switzerland regarding adjuvant treatment with (c)ICI and TT. METHODS: In the GERMELATOX-A study, 108 physicians (median age: 32 yrs, 67.6% female) from 11 skin cancer centers were surveyed to rate typical side effect scenarios of (c)ICI and TT treatments and then compared to patients' ratings evaluated in a previous analysis from the same centers. The scenarios described mild-to-moderate or severe toxicity and included melanoma relapse leading to death. The physicians were asked about the level of side effects they would tolerate in exchange for a reduction in melanoma relapse and an increase in survival at 5 years. RESULTS: The preferences of physicians and patients revealed significant differences regarding adjuvant melanoma treatment with (c)ICI and TT (p < 0.05). Compared to patients, physicians tend to value a melanoma relapse less severe, according to a visual analog scale. They were also less threatened by all scenarios of side effects during adjuvant treatment with (c)ICI or TT, compared to patients. Physicians required lower risk reductions for disease-free survival (DFS) and overall survival (OS) for both ICI and TT and their drug-related side effects to accept these treatments. In case of severe side effects, physicians required similar 5-year DFS rates for ICI and TT (60-65%), while patients needed a 15% improvement of 5-year DFS for ICI compared to TT (80%/65%). For survival, physicians expected an OS improvement of + 10% for all three treatment modalities, whereas patients required a higher increase: + 18-22% for ICI and + 15% for TT. CONCLUSION: Our study highlights the importance of understanding the patient's perspective and a potential difference to the doctor's view when making decisions about adjuvant melanoma treatment with (c)ICI and TT, especially as these treatments are increasingly being implemented in earlier stages.

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy.

BACKGROUND: Tumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline would lay the foundation for immunotherapy trials with the potential to enhance treatment, tremendously benefiting patients suffering from rare, understudied cancers. METHODS: We present an experimentally validated, data-driven computational pipeline that selects and ranks antigens in a multipronged approach. In addition to minimizing the risk of immune-related adverse events by selecting antigens based on their expression profile in tumor biopsies and healthy tissues, we incorporated a network analysis-derived antigen indispensability index based on computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model relying on peptide physicochemical characteristics. RESULTS: In a model study of uveal melanoma, Human Leukocyte Antigen (HLA) docking simulations and experimental quantification of the peptide-major histocompatibility complex binding affinities confirmed that our approach discriminates between high-binding and low-binding affinity peptides with a performance similar to that of established methodologies. Blinded validation experiments with autologous T-cells yielded peptide stimulation-induced interferon-γ secretion and cytotoxic activity despite high interdonor variability. Dissecting the score contribution of the tested antigens revealed that peptides with the potential to induce cytotoxicity but unsuitable due to potential tissue damage or instability of expression were properly discarded by the computational pipeline. CONCLUSIONS: In this study, we demonstrate the feasibility of the de novo computational selection of antigens with the capacity to induce an anti-tumor immune response and a predicted low risk of tissue damage. On translation to the clinic, our pipeline supports fast turn-around validation, for example, for adoptive T-cell transfer preparations, in both generalized and personalized antigen-directed immunotherapy settings.

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.

Federated Learning for Decentralized Artificial Intelligence in Melanoma Diagnostics.

Importance: The development of artificial intelligence (AI)-based melanoma classifiers typically calls for large, centralized datasets, requiring hospitals to give away their patient data, which raises serious privacy concerns. To address this concern, decentralized federated learning has been proposed, where classifier development is distributed across hospitals. Objective: To investigate whether a more privacy-preserving federated learning approach can achieve comparable diagnostic performance to a classical centralized (ie, single-model) and ensemble learning approach for AI-based melanoma diagnostics. Design, Setting, and Participants: This multicentric, single-arm diagnostic study developed a federated model for melanoma-nevus classification using histopathological whole-slide images prospectively acquired at 6 German university hospitals between April 2021 and February 2023 and benchmarked it using both a holdout and an external test dataset. Data analysis was performed from February to April 2023. Exposures: All whole-slide images were retrospectively analyzed by an AI-based classifier without influencing routine clinical care. Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUROC) served as the primary end point for evaluating the diagnostic performance. Secondary end points included balanced accuracy, sensitivity, and specificity. Results: The study included 1025 whole-slide images of clinically melanoma-suspicious skin lesions from 923 patients, consisting of 388 histopathologically confirmed invasive melanomas and 637 nevi. The median (range) age at diagnosis was 58 (18-95) years for the training set, 57 (18-93) years for the holdout test dataset, and 61 (18-95) years for the external test dataset; the median (range) Breslow thickness was 0.70 (0.10-34.00) mm, 0.70 (0.20-14.40) mm, and 0.80 (0.30-20.00) mm, respectively. The federated approach (0.8579; 95% CI, 0.7693-0.9299) performed significantly worse than the classical centralized approach (0.9024; 95% CI, 0.8379-0.9565) in terms of AUROC on a holdout test dataset (pairwise Wilcoxon signed-rank, P < .001) but performed significantly better (0.9126; 95% CI, 0.8810-0.9412) than the classical centralized approach (0.9045; 95% CI, 0.8701-0.9331) on an external test dataset (pairwise Wilcoxon signed-rank, P < .001). Notably, the federated approach performed significantly worse than the ensemble approach on both the holdout (0.8867; 95% CI, 0.8103-0.9481) and external test dataset (0.9227; 95% CI, 0.8941-0.9479). Conclusions and Relevance: The findings of this diagnostic study suggest that federated learning is a viable approach for the binary classification of invasive melanomas and nevi on a clinically representative distributed dataset. Federated learning can improve privacy protection in AI-based melanoma diagnostics while simultaneously promoting collaboration across institutions and countries. Moreover, it may have the potential to be extended to other image classification tasks in digital cancer histopathology and beyond.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma.

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists' decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists' diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists' confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists' willingness to adopt such XAI systems, promoting future use in the clinic.

Evaluating deep learning-based melanoma classification using immunohistochemistry and routine histology: A three center study.

Pathologists routinely use immunohistochemical (IHC)-stained tissue slides against MelanA in addition to hematoxylin and eosin (H&E)-stained slides to improve their accuracy in diagnosing melanomas. The use of diagnostic Deep Learning (DL)-based support systems for automated examination of tissue morphology and cellular composition has been well studied in standard H&E-stained tissue slides. In contrast, there are few studies that analyze IHC slides using DL. Therefore, we investigated the separate and joint performance of ResNets trained on MelanA and corresponding H&E-stained slides. The MelanA classifier achieved an area under receiver operating characteristics curve (AUROC) of 0.82 and 0.74 on out of distribution (OOD)-datasets, similar to the H&E-based benchmark classification of 0.81 and 0.75, respectively. A combined classifier using MelanA and H&E achieved AUROCs of 0.85 and 0.81 on the OOD datasets. DL MelanA-based assistance systems show the same performance as the benchmark H&E classification and may be improved by multi stain classification to assist pathologists in their clinical routine.

Tumor cell-intrinsic PD-1 promotes Merkel cell carcinoma growth by activating downstream mTOR-mitochondrial ROS signaling.

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer. Inhibitors targeting the programmed cell death 1 (PD-1) immune checkpoint have improved MCC patient outcomes by boosting antitumor T cell immunity. Here, we identify PD-1 as a growth-promoting receptor intrinsic to MCC cells. In human MCC lines and clinical tumors, RT-PCR-based sequencing, immunoblotting, flow cytometry, and immunofluorescence analyses demonstrated PD-1 gene and protein expression by MCC cells. MCC-PD-1 ligation enhanced, and its inhibition or silencing suppressed, in vitro proliferation and in vivo tumor xenograft growth. Consistently, MCC-PD-1 binding to PD-L1 or PD-L2 induced, while antibody-mediated PD-1 blockade inhibited, protumorigenic mTOR signaling, mitochondrial (mt) respiration, and ROS generation. Last, pharmacologic inhibition of mTOR or mtROS reversed MCC-PD-1:PD-L1-dependent proliferation and synergized with PD-1 checkpoint blockade in suppressing tumorigenesis. Our results identify an MCC-PD-1-mTOR-mtROS axis as a tumor growth-accelerating mechanism, the blockade of which might contribute to clinical response in patients with MCC.

Identifying biomarkers and novel therapeutic targets in uveal melanoma.

Uveal melanoma (UM) is an orphan cancer despite being the most common eye tumor in adults. Patients often present to skin cancer centers for treatment of metastatic disease although there are significant genetic, biological, and clinical differences from cutaneous melanoma. The treatments most commonly used for metastatic UM are tebentafusp and combined immune checkpoint blockade, both of which yield low response rates and may be accompanied by high treatment costs and significant immune-related toxicities. Thus, it is of paramount importance to identify biomarkers and clinical profiles predictive of treatment response and to find novel therapeutic targets. The use of immune checkpoint blockade showed more favorable outcomes in patients with extrahepatic disease and normal levels of serum lactate dehydrogenase in a panel of retrospective studies, making its use more reasonable in this subgroup. To identify novel drug targets, we will analyze the expression and relevance of neural crest transcription factors in patient bio-specimens using next-generation nanopore sequencing. Computer algorithms and network-based analysis will facilitate the identification of druggable targets which will subsequently be validated in patient-derived short-term cell cultures. This approach will help to find novel and personalized treatments for UM.

Evaluating the Efficacy and Safety of 4% 5-Fluorouracil Cream in Patients with Actinic Keratosis: An Expert Opinion.

Actinic keratosis is a lesion that develops in sun-exposed areas of the skin and is considered to be a precancerous condition or an early in situ squamous cell carcinoma. Treatment of actinic keratosis is important for reducing skin cancer risk, with treatment choice based on patient-, lesion- and treatment-related considerations. Of the topical treatments used for field-directed therapy, those containing 5-fluorouracil are among the most effective and widely prescribed. The most recently developed topical 5-fluorouracil preparation (Tolak®; Pierre Fabre, France) contains 4% 5-fluorouracil in an aqueous cream. This narrative review discusses data on 4% 5-fluorouracil cream to treat actinic keratosis, and provides the authors' expert opinion on issues associated with it use. The effect of the cream has been evaluated in phase 2 and 3 trials of adult patients with actinic keratosis on the face, ears or scalp. These trials included patients with severe baseline disease, defined by high lesion counts and large-size treatment fields, which possibly affected the proportion of patients who were able to achieve complete clearance. Other efficacy parameters (e.g. percentage change in lesion count, ≥ 75% clearance of lesions or clinically significant changes in validated severity scales) should also be assessed to fully evaluate 4% 5-fluorouracil treatment efficacy in these patients. Nevertheless, 4% 5-fluorouracil is associated with high efficacy, a low level of recurrence and a satisfactory safety profile.

S3 guideline "actinic keratosis and cutaneous squamous cell carcinoma" - update 2023, part 2: epidemiology and etiology, diagnostics, surgical and systemic treatment of cutaneous squamous cell carcinoma (cSCC), surveillance and prevention.

Actinic keratosis (AK) are common lesions in light-skinned individuals that can potentially progress to cutaneous squamous cell carcinoma (cSCC). Both conditions may be associated with significant morbidity and constitute a major disease burden, especially among the elderly. To establish an evidence-based framework for clinical decision making, the guideline "actinic keratosis and cutaneous squamous cell carcinoma" was updated and expanded by the topics cutaneous squamous cell carcinoma in situ (Bowen's disease) and actinic cheilitis. The guideline is aimed at dermatologists, general practitioners, ear nose and throat specialists, surgeons, oncologists, radiologists and radiation oncologists in hospitals and office-based settings, as well as other medical specialties, policy makers and insurance funds involved in the diagnosis and treatment of patients with AK and cSCC. A separate guideline exists for patients and their relatives. In this part, we will address aspects relating to epidemiology and etiology, diagnostics, surgical and systemic treatment of cutaneous squamous cell carcinoma (cSCC), surveillance and prevention.

Standardized Computer-Assisted Analysis of 5-hmC Immunoreactivity in Dysplastic Nevi and Superficial Spreading Melanomas.

5-Hydroxymethylcytosine (5-hmC) is an important intermediate of DNA demethylation. Hypomethylation of DNA is frequent in cancer, resulting in deregulation of 5-hmC levels in melanoma. However, the interpretation of the intensity and distribution of 5-hmC immunoreactivity is not very standardized, which makes its interpretation difficult. In this study, 5-hmC-stained histological slides of superficial spreading melanomas (SSM) and dysplastic compound nevi (DN) were digitized and analyzed using the digital pathology and image platform QuPath. Receiver operating characteristic/area under the curve (ROCAUC) and t-tests were performed. A p-value of <0.05 was used for statistical significance, and a ROCAUC score of >0.8 was considered a "good" result. In total, 92 5-hmC-stained specimens were analyzed, including 42 SSM (45.7%) and 50 DN (54.3%). The mean of 5-hmC-positive cells/mm2 for the epidermis and dermo-epidermal junction and the entire lesion differed significantly between DN and SSM (p = 0.002 and p = 0.006, respectively) and showed a trend towards higher immunoreactivity in the dermal component (p = 0.069). The ROCAUC of 5-hmC-positive cells of the epidermis and dermo-epidermal junction was 0.79, for the dermis 0.74, and for the entire lesion 0.76. These results show that the assessment of the epidermal with junctional expression of 5-hmC is slightly superior to dermal immunoreactivity in distinguishing between DN and SSM.

COMBI-r: A Prospective, Non-Interventional Study of Dabrafenib Plus Trametinib in Unselected Patients with Unresectable or Metastatic BRAF V600-Mutant Melanoma.

Combined BRAF/MEK-inhibition constitutes a relevant treatment option for BRAF-mutated advanced melanoma. The prospective, non-interventional COMBI-r study assessed the effectiveness and tolerability of the BRAF-inhibitor dabrafenib combined with the MEK-inhibitor trametinib in patients with advanced melanoma under routine clinical conditions. Progression-free survival (PFS) was the primary objective, and secondary objectives included overall survival (OS), disease control rate, duration of therapy, and the frequency and severity of adverse events. This study enrolled 472 patients at 55 German sites. The median PFS was 8.3 months (95%CI 7.1-9.3) and the median OS was 18.3 months (14.9-21.3), both tending to be longer in pre-treated patients. In the 147 patients with CNS metastases, PFS was similar in those requiring corticosteroids (probably representing symptomatic patients, 5.6 months (3.9-7.2)) compared with those not requiring corticosteroids (5.9 months (4.8-6.9)); however, OS was shorter in patients with brain metastases who received corticosteroids (7.8 (6.3-11.6)) compared to those who did not (11.9 months (9.6-19.5)). The integrated subjective assessment of tumor growth dynamics proved helpful to predict outcome: investigators' upfront categorization correlated well with time-to-event outcomes. Taken together, COMBI-r mirrored PFS outcomes from other prospective, observational studies and confirmed efficacy and safety findings from the pivotal phase III COMBI-d/-v and COMBI-mb trials.

Threshold Optimization for Tumor Markers S100b and MIA in Uveal Melanoma - A Single Center Analysis.

BACKGROUND/AIM: Uveal melanoma (UM) is the most common malignant tumor of the eye in adults. Metastases develop in 50% of the patients, predominantly in the liver. In UM, the cut-off concentrations of the blood-based tumor markers S100b and MIA are inconclusive. PATIENTS AND METHODS: In this retrospective monocenter study, we statistically evaluated 1,878 S100b and 1,768 MIA measurements in 244 patients with UM from 2011-2020. Threshold optimization was performed using receiver operating characteristic (ROC) curves. RESULTS: A total of 171 patients with non-metastatic UM (nmUM) and 73 patients with metastatic UM (mUM) showed no differences in sex, age at diagnosis or the affected eye. In mUM, 80% of the patients developed metastases to the liver at a median of 46 months after initial diagnosis. The sensitivity and specificity of S100b was 16.10% and 94.52%, and that of MIA was 31.86% and 81.42%, respectively. ROC curves revealed poor values for the area under the curve of 0.57 for S100b and 0.55 for MIA. The optimal cut-off concentration to detect metastases was 0.14 µg/l for S100b and 17.4 ng/ml for MIA. With at least one tumor marker elevated, optimized sensitivity was 20.40% and specificity 96.76%. CONCLUSION: Current thresholds for S100b and MIA in UM are not able to detect early metastatic disease and require additional diagnostics to clarify false positive results. Threshold optimization considering both S100b and MIA results in a better diagnostic validity with an acceptable specificity and a poor sensitivity. Highly sensitive blood-based and imaging methods to detect metastases early in UM are urgently needed.