Cutaneous Malignant Melanoma: A Review of Early Diagnosis and Management

Exosomes in melanoma: Future potential for clinical theranostics

Melanoma, an aggressive form of skin cancer, presents significant therapeutic challenges due to its resistance to conventional treatments and propensity for metastasis. Exosomes, nanoscale vesicles secreted by a wide variety of cells, have emerged as promising tools for developing novel melanoma therapies. Exosome-based therapeutic approaches offer several advantages, including inherent biocompatibility, low immunogenicity, and the ability to cross biological barriers. This review explores the therapeutic potential of exosomes in melanoma treatment, focusing on their multifaceted roles in modulating tumor cell behavior, enhancing anti-tumor immune responses, and serving as targeted drug delivery vehicles. We discuss various strategies employed to engineer exosomes for enhanced therapeutic efficacy, including loading them with chemotherapeutic agents, small interfering RNAs (siRNAs), microRNAs (miRNAs), and immunomodulatory molecules. Additionally, we highlight the potential of exosomes derived from diverse sources to enhance anti-cancer effects. Furthermore, we address the challenges and future directions in translating exosome-based therapies from bench to bedside, emphasizing the need for standardized isolation and manufacturing protocols, as well as rigorous preclinical and clinical evaluations to unlock the full therapeutic potential of exosomes in the fight against melanoma.

Using The Cancer Genome Atlas from cBioPortal to Develop Genomic Datasets for Machine Learning Assisted Cancer Treatment

Predicting the impact of genetic mutations is crucial for understanding diseases like cancer. Polymorphism Phenotyping (PolyPhen) and Sorting Intolerant From Tolerant (SIFT) are key tools for assessing how amino acid substitutions affect protein function and mutation pathogenicity. To our knowledge, no ready-to-use genomic dataset exists for prediction models to identify potentially harmful mutations, which could support research and clinical decisions. This study develops genomic and non-genomic datasets using The Cancer Genome Atlas (TCGA) from cBioPortal and applies machine learning models to predict PolyPhen and SIFT scores. We explore three classification models: Random Forest (RF), Extreme Gradient Boosting (XGBoost), and an ensemble RF-XGBoost model. Experimental results show that genomic data yields more accurate predictions than non-genomic data. The ensemble RF-XGBoost model performs best on genomic data, achieving average accuracies of 88.43% for PolyPhen and 95.13% for SIFT, highlighting the potential of artificial intelligence in genetic mutation analysis for disease treatment.

Towards an integrated imaging for melanoma diagnosis: A review of multispectral, hyperspectral, and thermal technologies with preliminary system development

The diagnosis of melanoma traditionally relies on visual inspection or on the use of the dermoscope, which do not have capabilities for early and precise detection. In this review, we aimed to explore other imaging technologies that can provide non-invasive and detailed information on skin lesions, such as multispectral, hyperspectral and thermal imaging. In this regard, the systems were evaluated in terms of hardware, performance and clinical applications. Since there is currently a very big interest in developing artificial intelligence (AI) applications in dermatology, the review also focuses on analysing studies that integrated this technology with newer imaging systems. To obtain clinical validation for such systems, there is an extensive need for publicly available datasets, as the current ones are limited. Expanding and obtaining new datasets is crucial in advancing research for a more accurate melanoma diagnosis. Taking into consideration the benefits that these imaging modalities can provide if they are combined with AI, we propose a prototype that can distinguish between melanoma and its precursor, the nevus, for which the set-up, components, imaging processing pipeline and classification techniques are described. The final system benefits of the advantages provided by near infrared, thermal and visible cameras, that allow a more in-depth characterizations of melanoma for a better understanding of its behaviour, an early detection improvement and diagnostic precision.

ATF3 regulates CDC42 transcription and influences cytoskeleton remodeling, thus inhibiting the proliferation, migration and invasion of malignant skin melanoma cells

Cutaneous malignant melanoma (CMM) is one of the most aggressive and lethal types of skin cancer. Cytoskeletal remodeling is a key factor in the progression of CMM. Previous research has shown that activating transcription factor 3 (ATF3) inhibits metastasis in bladder cancer by regulating actin cytoskeleton remodeling through gelsolin. However, whether ATF3 plays a similar role in cytoskeletal remodeling in CMM cells remains unknown. Various gene and protein expression analyses were performed using techniques such as reverse transcription quantitative PCR, western blot, immunofluorescent staining, and immunohistochemical staining. CMM viability, migration, and invasion were examined through cell counting kit-8 and transwell assays. The interactions between cell division cycle 42 (CDC42) and ATF3 were investigated using chromatin immunoprecipitation and dual-luciferase reporter assays. CDC42 was upregulated in CMM tissues and cells. Cytoskeletal remodeling of CMM cells, as well as CMM cell proliferation, migration, and invasion, were inhibited by CDC42 or ATF3. ATF3 targeted the CDC42 promoter region to regulate its transcriptional activity. ATF3 suppresses cytoskeletal remodeling in CMM cells, thereby inhibiting CMM progression and metastasis through CDC42. This research may provide a foundation for using ATF3 as a therapeutic target for CMM.

Robust ROI Detection in Whole Slide Images Guided by Pathologists' Viewing Patterns

Deep learning techniques offer improvements in computer-aided diagnosis systems. However, acquiring image domain annotations is challenging due to the knowledge and commitment required of expert pathologists. Pathologists often identify regions in whole slide images with diagnostic relevance rather than examining the entire slide, with a positive correlation between the time spent on these critical image regions and diagnostic accuracy. In this paper, a heatmap is generated to represent pathologists' viewing patterns during diagnosis and used to guide a deep learning architecture during training. The proposed system outperforms traditional approaches based on color and texture image characteristics, integrating pathologists' domain expertise to enhance region of interest detection without needing individual case annotations. Evaluating our best model, a U-Net model with a pre-trained ResNet-18 encoder, on a skin biopsy whole slide image dataset for melanoma diagnosis, shows its potential in detecting regions of interest, surpassing conventional methods with an increase of 20%, 11%, 22%, and 12% in precision, recall, F1-score, and Intersection over Union, respectively. In a clinical evaluation, three dermatopathologists agreed on the model's effectiveness in replicating pathologists' diagnostic viewing behavior and accurately identifying critical regions. Finally, our study demonstrates that incorporating heatmaps as supplementary signals can enhance the performance of computer-aided diagnosis systems. Without the availability of eye tracking data, identifying precise focus areas is challenging, but our approach shows promise in assisting pathologists in improving diagnostic accuracy and efficiency, streamlining annotation processes, and aiding the training of new pathologists.

Bilateral Choroidal Metastases from Primary Cutaneous Melanoma Following Nivolumab Discontinuation: A Case Report

PURPOSE

To present the case of a young patient with BRAF V600E-mutant cutaneous melanoma who developed bilateral choroidal metastases complicated by neovascular glaucoma (NVG) in both eyes following the interruption of nivolumab therapy.

METHODS

A 28-year-old female with primary cutaneous melanoma of the left hand underwent surgical resection and adjuvant nivolumab. Immunotherapy was discontinued due to immune-related acute interstitial nephritis. Three months after cessation, she presented with bilateral decreased vision, pain, and redness.

RESULTS

Ophthalmic examination and imaging revealed bilateral choroidal thickening with focal nodular lesions consistent with metastatic disease, along with uveitis and NVG in both eyes. This condition required topical anti-inflammatory treatment and cyclophotocoagulation for intraocular pressure (IOP) control. Nivolumab was reinitiated in combination with systemic corticosteroids to manage immune-related toxicity. At the 12-month follow-up, the patient retained visual function in one eye, with no signs of new metastatic lesions.

CONCLUSIONS

Bilateral choroidal metastases from cutaneous melanoma are rare and can be complicated by NVG. Interruption of immune checkpoint inhibitors (ICIs) like nivolumab may lead to metastatic recurrence. Prompt resumption of immunotherapy, coupled with appropriate ocular interventions, is crucial for controlling disease progression and preserving vision. Careful management of immune-related adverse effects (irAEs) is essential to prevent treatment discontinuation and subsequent disease relapse.

RET Inhibitor SPP86 Triggers Apoptosis and Activates the DNA Damage Response Through the Suppression of Autophagy and the PI3K/AKT Signaling Pathway in Melanoma Cells

Background

Melanoma is a highly lethal form of skin cancer, and effective treatment remains a significant challenge. SPP86 is a novel potential therapeutic drug. Nonetheless, the specific influence of SPP86 on autophagy, particularly its mechanisms in the context of DNA damage and apoptosis in human melanoma cells, remains inadequately understood. Thus, this study aims to explore the effects of SPP86 on autophagy and to elucidate its association with cell proliferation, apoptosis, and DNA damage in melanoma cells.

Methods

This study assessed the anti-tumor effects of SPP86 on cell viability, colony formation, apoptosis, and DNA damage in two melanoma cell lines, A375 and A2058. Concurrently, the underlying mechanisms, including the PI3K/AKT signaling pathway and autophagy modulation, were also elucidated.

Results

The study demonstrated that SPP86 exerts anti-tumor effects in melanoma cells through multiple mechanisms: it induces apoptosis, causes DNA damage, inhibits cell proliferation, and suppresses the PI3K/AKT signaling pathway. Importantly, the inhibition of autophagy appears to be a critical component of SPP86' s mode of action, with the modulation of autophagic processes influencing the cytotoxicity against melanoma cells.

Conclusion

These promising findings suggest that SPP86 is a potential drug candidate for the treatment of melanoma, warranting further research and development.

Combination of gold nanoparticles with near-infrared light as an alternative approach for melanoma management

Melanoma is the most aggressive type of skin cancer and recently approved drugs are often associated with resistance and significant adverse effects. Therefore, the design of more effective and safe options remains imperative. Photothermal therapy (PTT) using gold nanoparticles (AuNPs) presents a promising and innovative approach. In this work, the efficacy of combining a previously optimized formulation of AuNPs coated with a mixture of hyaluronic and oleic acids (HAOA-AuNPs) with near-infrared (NIR) laser irradiation in melanoma cell lines was explored. Coated and uncoated AuNPs formulations were characterized in physicochemical, morphological and elemental terms. Next, the cellular uptake efficiency as well as antiproliferative activity of the combination of each formulation with laser irradiation was evaluated. Subsequently, HAOA-AuNPs were selected to assess the underlying mechanism of combined therapy by cell cycle and Annexin V/PI assays. An in vivo syngeneic murine melanoma model was also conducted. In vitro studies demonstrated that 24 h after incubation and in the absence of laser, HAOA-AuNPs did not exhibit cytotoxic effects on the melanoma cell lines tested, similar to the laser alone. On the contrary, the combination therapy resulted in a large reduction in cell viability. Furthermore, it has been shown to promote S-phase cell cycle arrest and increase in the percentage of late apoptotic cells. Finally, the in vivo proof-of-concept showed that the intratumoral administration of HAOA-AuNPs followed by three laser irradiations impaired tumor progression. Collectively, AuNP-based PTT holds significant potential to improve treatment efficacy and safety, offering a versatile and potent tool against cancer.

Evaluation of skin cancer screening in Germany - a Microsimulation

BACKGROUND

Comprehensive skin cancer screening was introduced in Germany in 2008. It is unclear whether subsequently observed changes in the epidemiology of malignant melanoma (MM), squamous cell carcinoma (SCC) and basal cell carcinoma (BCC) are due to the screening. Simulation models are used to compare different screening scenarios with each other and with observed incidence and mortality trends.

METHODS

A microsimulation model for MM, SCC, and BCC was programmed and validated separately by sex on skin cancer-specific mortality data. In addition to the currently practiced screening (biennial offer, annual participation probability 15%), triennial screening, screening with increased participation, e.g., via invitation, and no screening were simulated. Incidence, mortality, costs, and life-years gained were simulated for 30 years from the start of screening.

RESULTS

Compared with no screening, mortality is reduced by 13.8% in the simulation with current conditions. This effect occurs in the first years after screening starts before reaching a stable level. More screening allows for further increases in incidence, life-years gained, and costs and decreases in mortality. Comparing simulated and observed effects shows little agreement.

CONCLUSIONS

The model is useful for comparing screening scenarios to identify potential optimization opportunities in SCS. Additional, especially risk-adapted, screening scenarios should be investigated.

Liquid biopsy in cancer management: Integrating diagnostics and clinical applications

Liquid biopsy is an innovative, minimally invasive diagnostic tool revolutionizing cancer management by enabling the detection and analysis of cancer-related biomarkers from bodily fluids such as blood, urine, or cerebrospinal fluid. Unlike traditional tissue biopsies, which require invasive procedures, liquid biopsy offers a more accessible and repeatable method for tracking cancer progression, detecting early-stage cancers, and monitoring therapeutic responses. The technology primarily focuses on analyzing circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and other cancer-derived genetic materials. These biomarkers provide critical information on tumor heterogeneity, mutation profiles, and potential drug resistance. In clinical practice, liquid biopsy has demonstrated its utility in identifying actionable mutations, guiding personalized treatment strategies, and assessing minimal residual disease (MRD). While liquid biopsy holds immense promise, challenges related to its sensitivity, specificity, and standardization remain. Efforts to optimize pre-analytical and analytical processes, along with the establishment of robust regulatory frameworks, are crucial for its widespread clinical adoption. This abstract highlights the transformative potential of liquid biopsy in cancer diagnosis, prognosis, and treatment monitoring, emphasizing its role in advancing personalized oncology. Further research, clinical trials, and regulatory harmonization will be vital in realizing its full potential in precision cancer care.

An innovative cellular medicine approach via the utilization of novel nanotechnology-based biomechatronic platforms as a label-free biomarker for early melanoma diagnosis

Innovative cellular medicine (ICM) is an exponentially emerging field with a promising approach to combating complex and ubiquitous life-threatening diseases such as multiple sclerosis (MS), arthritis, Parkinson's disease, Alzheimer's, heart disease, and cancer. Together with the advancement of nanotechnology and bio-mechatronics, ICM revolutionizes cellular therapy in understanding the essence and nature of the disease initiated at a single-cell level. This paper focuses on the intricate nature of cancer that requires multi-disciplinary efforts to characterize it well in order to achieve the objectives of modern world contemporary medicine in the early detection of the disease at a cellular level and potentially arrest its proliferation mechanism. This justifies the multidisciplinary research backgrounds of the authors of this paper in advancing cellular medicine by bridging the gap between experimental biology and the engineering field. Thus, in pursuing this approach, two novel miniaturized and highly versatile biomechatronic platforms with dedicated operating software and microelectronics are designed, modeled, nanofabricated, and tested in numerous in vitro experiments to investigate a hypothesis and arrive at a proven theorem in carcinogenesis by interrelating cellular contractile force, membrane potential, and cellular morphology for early detection and characterization of melanoma cancer cells. The novelties that flourished within this work are manifested in sixfold: (1) developing a mathematical model that utilizes a Heaviside step function, as well as a pin-force model to compute the contractile force of a living cell, (2) deriving an expression of cell-membrane potential based on Laplace and Fourier Transform and their Inverse Transform functions by encountering Warburg diffusion impedance factor, (3) nano-fabricating novel biomechatronic platforms with associated microelectronics and customized software that extract cellular physics and mechanics, (4) developing a label-free biomarker, (5) arrive at a proved theorem in developing a mathematical expression in relating cancer cell mechanobiology to its biophysics in connection to the stage of the disease, and (6) to the first time in literature, and to the best of the authors' knowledge, discriminating different stages and morphology of cancer cell melanoma based on their cell-membrane potentials, and associated contractile forces that could introduce a new venue of cellular therapeutic modalities, preclinical early cancer diagnosis, and a novel approach in immunotherapy drug development. The proposed innovative technology-based versatile bio-mechatronic platforms shall be extended for future studies, investigating the role of electrochemical signaling of the nervous system in cancer formation that will significantly impact modern oncology by pursuing a targeted immunotherapy approach. This work also provides a robust platform for immunotherapy practitioners in extending the study of cellular biophysics in stalling neural-cancer interactions, of which the FDA-approved chimeric antigen receptor (CAR)-T cell therapies can be enhanced (genetically engineered) in a lab by improving its receptors to capture cancer antigens. This work amplifies the importance of studying neurotransmitters and electrochemical signaling molecules in shaping the immune T-cell function and its effectiveness in arresting cancer proliferation rate (mechanobiology mechanism).

A comprehensive review of PRAME and BAP1 in melanoma: Genomic instability and immunotherapy targets

In a thorough review of the literature, the complex roles of PRAME (preferentially expressed Antigen of Melanoma) and BAP1 (BRCA1-associated protein 1) have been investigated in uveal melanoma (UM) and cutaneous melanoma. High PRAME expression in UM is associated with poor outcomes and correlated with extraocular extension and chromosome 8q alterations. BAP1 mutations in the UM indicate genomic instability and a poor prognosis. Combining PRAME and BAP1 immunohistochemical staining facilitates effective risk stratification. Mechanistically, both genes are associated with genomic instability, making them promising targets for cancer immunotherapy. Hypomethylation of PRAME, specifically in its promoter regions, is critical for UM progression and contributes to epigenetic reprogramming. Additionally, miR-211 regulation is crucial in melanoma and has therapeutic potential. The way PRAME changes signaling pathways provides clues about the cause of cancer due to genomic instability related to modifications in DNA repair. Inhibition of poly(ADP-ribose) polymerase-1 (PARP-1) and PARP-2 in cells expressing PRAME could lead to potential therapeutic applications. Pathway enrichment analysis underscores the significance of PRAME and BAP1 in melanoma pathogenesis.

The spike-and-slab quantile LASSO for robust variable selection in cancer genomics studies

Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy-tailed distributions in the complex traits. In the past decade, robust variable selection methods have emerged as powerful alternatives to the nonrobust ones to identify important genes associated with heterogeneous disease traits and build superior predictive models. In this study, to keep the remarkable features of the quantile LASSO and fully Bayesian regularized quantile regression while overcoming their disadvantage in the analysis of high-dimensional genomics data, we propose the spike-and-slab quantile LASSO through a fully Bayesian spike-and-slab formulation under the robust likelihood by adopting the asymmetric Laplace distribution (ALD). The proposed robust method has inherited the prominent properties of selective shrinkage and self-adaptivity to the sparsity pattern from the spike-and-slab LASSO (Roc̆ková and George, J Am Stat Associat, 2018, 113(521): 431-444). Furthermore, the spike-and-slab quantile LASSO has a computational advantage to locate the posterior modes via soft-thresholding rule guided Expectation-Maximization (EM) steps in the coordinate descent framework, a phenomenon rarely observed for robust regularization with nondifferentiable loss functions. We have conducted comprehensive simulation studies with a variety of heavy-tailed errors in both homogeneous and heterogeneous model settings to demonstrate the superiority of the spike-and-slab quantile LASSO over its competing methods. The advantage of the proposed method has been further demonstrated in case studies of the lung adenocarcinomas (LUAD) and skin cutaneous melanoma (SKCM) data from The Cancer Genome Atlas (TCGA).

cGAS/STING in skin melanoma: from molecular mechanisms to therapeutics

Melanoma, recognized as the most aggressive type of skin cancer, has experienced a notable increase in cases, especially within populations with fair skin. This highly aggressive cancer is largely driven by UV radiation exposure, resulting in the uncontrolled growth and malignant transformation of melanocytes. The cGAS-STING pathway, an immune signaling mechanism responsible for detecting double-stranded DNA in the cytoplasm, is essential for mediating the immune response against melanoma. This pathway serves a dual purpose: it enhances antitumor immunity by activating immune cells, but it can also promote tumor growth when chronically activated by creating an immunosuppressive environment. This review comprehensively examines the multifaceted implication of the cGAS-STING pathway in melanoma pathogenesis and treatment. We explore its molecular mechanisms, including epigenetic regulation, interaction with signaling pathways such as AR signaling, and modulation by various cellular effectors like TG2 and activin-A. The therapeutic potential of modulating the cGAS-STING pathway is highlighted, with promising results from STING agonists, combination therapies with immune checkpoint inhibitors, and novel drug delivery systems, including nanoparticles and synthetic drugs. Our findings underscore the importance of the cGAS-STING pathway in melanoma, presenting it as a critical target for enhancing anti-tumor immunity. By leveraging this pathway, future therapeutic strategies can potentially convert 'cold' tumors into 'hot' tumors, making them more susceptible to immune responses.

52Mn-labelled Beta-cyclodextrin for Melanoma Imaging: A Proof-of-concept Preclinical Study

BACKGROUND/AIM

As prostaglandin E2 (PGE2) and its receptors (EP2) are over-expressed on tumor cells and microenvironment, radiolabeled cyclodextrins targeting such biomolecules are valuable vector candidates in molecular cancer diagnostics. Using experimental melanoma models, we evaluated the in vivo imaging behavior of novel Manganese-52-labeled (52Mn) randomly methylated beta-cyclodextrin ([52Mn]Mn-DOTAGA-RAMEB) and compared it with the following well-established tumor-specific probes: melanocortin-1 receptor (MC1-R)-affine [68Ga]Ga-DOTA-NAPamide and PGE2 selective [68Ga]Ga-DOTAGA-RAMEB cyclodextrin.

MATERIALS AND METHODS

Post-injection of [68Ga]Ga-DOTA-NAPamide, [68Ga]Ga-DOTAGA-RAMEB, and [52Mn]Mn-DOTAGA-RAMEB into MC1-R positive B16F10 melanoma-bearing mice, tumor radio-pharmaceutical uptake was quantified in vivo and ex vivo using preclinical positron emission tomography (PET) and high-performance gamma counter.

RESULTS

Although all tracers performed well in tumor identification, the highest standardized uptake values were detected in the [68Ga]Ga-DOTA-NAPamide scans. Corresponding to the ex vivo data, meaningful [52Mn]Mn-DOTAGA-RAMEB accumulation 1 h post-injection confirmed the tumor-targeting potential of the tracer. Temporal changes in PGE2/EP2 expression of the neoplasms may explain the significant differences observed between the tumor uptake of the two cyclodextrin probes and that of the 52Mn-labelled compound measured 1 h, 4 h, and 3 days post-injection (p≤0.01, p≤0.05).

CONCLUSION

Although further pharmacokinetical optimization may be required, 52Mn-labelled cyclodextrin holds potential in melanoma diagnostics and the PET-based longitudinal assessment of tumor-associated PGE2/EP2 expression.

Exploring resistance to immune checkpoint inhibitors and targeted therapies in melanoma

Melanoma is the most aggressive form of skin cancer, characterized by a poor prognosis, and its incidence has risen rapidly over the past 30 years. Recent therapies, notably immunotherapy and targeted therapy, have significantly improved the outcome of patients with metastatic melanoma. Previously dismal five-year survival rates of below 5% have shifted to over 50% of patients surviving the five-year mark, marking a significant shift in the landscape of melanoma treatment and survival. Unfortunately, about 50% of patients either do not respond to therapy or experience early or late relapses following an initial response. The underlying mechanisms for primary and secondary resistance to targeted therapies or immunotherapy and relapse patterns remain not fully identified. However, several molecular pathways and genetic factors have been associated with melanoma resistance to these treatments. Understanding these mechanisms paves the way for creating novel treatments that can address resistance and ultimately enhance patient outcomes in melanoma. This review explores the mechanisms behind immunotherapy and targeted therapy resistance in melanoma patients. Additionally, it describes the treatment strategies to overcome resistance, which have improved patients' outcomes in clinical trials and practice.

Identification and validation of matrix metalloproteinase hub genes as potential biomarkers for Skin Cutaneous Melanoma

Objectives

The role of matrix metalloproteinases (MMPs) in Skin Cutaneous Melanoma (SKCM) development and progression is unclear so far. This comprehensive study delved into the intricate role of MMPs in SKCM development and progression.

Methods

RT-qPCR, bisulfite sequencing, and WES analyzed MMP gene expression, promoter methylation, and mutations in SKCM cell lines. TCGA datasets validated findings. DrugBank and molecular docking identified potential regulatory drugs, and cell line experiments confirmed the role of key MMP genes in tumorigenesis.

Results

Our findings unveiled significant up-regulation of MMP9, MMP12, MMP14, and MMP16, coupled with hypomethylation of their promoters in SKCM cell lines, implicating their involvement in disease progression. Mutational analysis highlighted a low frequency of mutations in these genes, indicating less involvement of mutations in the expression regulatory mechanisms. Prognostic assessments showcased a significant correlation between elevated expression of these genes and poor overall survival (OS) in SKCM patients. Additionally, functional experiments involving gene silencing revealed a potential impact on cellular proliferation, further emphasizing the significance of MMP9, MMP12, MMP14, and MMP16 in SKCM pathobiology.

Conclusion

This study identifies Estradiol and Calcitriol as potential drugs for modulating MMP expression in SKCM, highlighting MMP9, MMP12, MMP14, and MMP16 as key diagnostic and prognostic biomarkers.

Programmable Release of Chemotherapeutics from Ferrocene-Based Injectable Hydrogels Slows Melanoma Growth

Hydrogel-based injectable drug delivery systems provide temporally and spatially controlled drug release with reduced adverse effects on healthy tissues. Therefore, they represent a promising therapeutic option for unresectable solid tumor entities. In this study, a peptide-starPEG/hyaluronic acid-based physical hydrogel is modified with ferrocene to provide a programmable drug release orchestrated by matrix-drug interaction and local reactive oxygen species (ROS). The injectable ROS-responsive hydrogel (hiROSponse) exhibits adequate biocompatibility and biodegradability, which are important for clinical applications. HiROSponse is loaded with the two cytostatic drugs (hiROSponsedox/ptx) doxorubicin (dox) and paclitaxel (ptx). Dox is a hydrophilic compound and its release is mainly controlled by Fickian diffusion, while the hydrophobic interactions between ptx and ferrocene can control its release and thus be regulated by the oxidation of ferrocene to the more hydrophilic state of ferrocenium. In a syngeneic malignant melanoma-bearing mouse model, hiROSponsedox/ptx slows tumor growth without causing adverse side effects and doubles the relative survival probability. Programmable release is further demonstrated in a tumor model with a low physiological ROS level, where dox release, low dose local irradiation, and the resulting ROS-triggered ptx release lead to tumor growth inhibition and increased survival.

Peroxisome proliferator-activated receptors: Key regulators of tumor progression and growth

One of the main causes of death on the globe is cancer. Peroxisome-proliferator-activated receptors (PPARs) are nuclear hormone receptors, including PPARα, PPARδ and PPARγ, which are important in regulating cancer cell proliferation, survival, apoptosis, and tumor growth. Activation of PPARs by endogenous or synthetic compounds regulates tumor progression in various tissues. Although each PPAR isotype suppresses or promotes tumor development depending on the specific tissues or ligands, the mechanism is still unclear. PPARs are receiving interest as possible therapeutic targets for a number of disorders. Numerous clinical studies are being conducted on PPARs as possible therapeutic targets for cancer. Therefore, this review will focus on the existing and future uses of PPARs agonists and antagonists in treating malignancies. PubMed, Science Direct, and Scopus databases were searched regarding the effect of PPARs on various types of cancers until the end of May 2023. The results of the review articles showed the therapeutic influence of PPARs on a wide range of cancer on in vitro, in vivo and clinical studies. However, further experimental and clinical studies are needed to be conducted on the influence of PPARs on various cancers.

Topically Applied Therapies for the Treatment of Skin Disease: Past, Present, and Future

The purpose of this review is to summarize essential biological, pharmaceutical, and clinical aspects in the field of topically applied medicines that may help scientists when trying to develop new topical medicines. After a brief history of topical drug delivery, a review of the structure and function of the skin and routes of drug absorption and their limitations is provided. The most prevalent diseases and current topical treatment approaches are then detailed, the organization of which reflects the key disease categories of autoimmune and inflammatory diseases, microbial infections, skin cancers, and genetic skin diseases. The complexity of topical product development through to large-scale manufacturing along with recommended risk mitigation approaches are then highlighted. As such topical treatments are applied externally, patient preferences along with the challenges they invoke are then described, and finally the future of this field of drug delivery is discussed, with an emphasis on areas that are more likely to yield significant improvements over the topical medicines in current use or would expand the range of medicines and diseases treatable by this route of administration. SIGNIFICANCE STATEMENT: This review of the key aspects of the skin and its associated diseases and current treatments along with the intricacies of topical formulation development should be helpful in making judicious decisions about the development of new or improved topical medicines. These aspects include the choices of the active ingredients, formulations, the target patient population's preferences, limitations, and the future with regard to new skin diseases and topical medicine approaches.

General practitioners' perspectives on statutory skin cancer screening-A questionnaire-based cross-sectional survey in Germany

BACKGROUND

In Germany, skin cancer screening (SCS) is available free of charge every two years to all those with statutory health insurance over the age of 35. General Practitioners (GP) can carry out the screening if they have completed an 8-hour training course. GPs play a crucial role in the implementation of SCS and act as gatekeepers between initial patient contact and referral to dermatologists.

OBJECTIVE

To record how comprehensively GPs carry out SCS in terms of patient information and body examination, as well as to explore GPs opinions on the feasibility of SCS.

METHODS

A cross-sectional survey was conducted. A questionnaire was sent to GPs with permission to perform SCS in two regions of Germany (Bavaria and Saxony) between August and September 2021. Data were analyzed using descriptive analysis. Subgroup analysis was performed according to regions (federal state, location of physician´s office), professional experience (experience in years, number of monthly screenings, age) and gender. Open questions were evaluated using qualitative content analysis.

RESULTS

In the survey, 204 GPs responded. Genitalia (40.7%, 83/203), anal fold (62.3%, 127/204) and oral mucosa (66.7%, 136/204) were the least examined body regions during screening. Information on risks (false-positive findings: 18.6%, 38/203; false-negative findings: 13.2%, 27/203; overdiagnosis: 7.8%, 16/203) and benefits (48.0%, 98/202) were not always provided. GPs who performed screenings more frequently were more likely to provide information about the benefits of SCS (p<0.001; >10 vs. <5 screenings per month). Opinions were provided on uncertainties, knowledge requirements, structural and organizational requirements of SCS, SCS training and evaluation. The organization and remuneration of the SCS programme was seen as a barrier to implementation. GPs expressed uncertainties especially in unclear findings and in dermatoscopy.

CONCLUSION

Uncertainties in the implementation of the SCS should be addressed by offering refresher courses. Good networking between GPs and dermatologists is essential to improve SCS quality.

Exploring the therapeutic modalities of targeted treatment approach for skin carcinoma: cutting-edge strategies and key insights

INTRODUCTION

Skin carcinoma, including malignant melanoma, basal, squamous, and Merkel cell carcinoma, present significant healthcare challenges. Conventional treatments like surgery and chemotherapy suffer from limitations like non-specificity, toxicity, and adverse effects. The upcoming treatments are dominated by nano-sized delivery systems, which improve treatment outcomes while minimizing side effects. Moving ahead, targeted nanoparticles allow localized delivery of drugs at tumor site, ensuring minimal damage to surrounding tissues.

AREAS COVERED

This review explores various targeting strategies for specific types of skin cancers. The strategies discussed include nanocarrier-mediated targeted delivery with multiple types of ligands like aptamers, antibodies, peptides, and vitamins and their advantages in skin cancer. Upcoming cutting-edge technologies such as smart delivery systems, microneedle-assisted delivery and three-dimensional printed scaffolds have also been discussed in detail. The findings in this review are summarized from databases like PubMed, Scopus, Web of Science, ClinicalTrials.gov, NIH, and articles published between 2005 and 2024 that discuss targeted therapy for skin cancer.

EXPERT OPINION

Specific cancer-targeting strategies promise personalized treatments, improving response rates and reducing need for intensive therapies. The review highlights various challenges, their solution, and economic aspects in this dynamic field. It further emphasizes the potential for specialized strategies to revolutionize skin cancer treatment.

Assessment of educational services by Patient Target Group participating in the National Skin Cancer Prevention Programme (OPPNS) based on the example of the Wielkopolska region

Background

Skin melanoma is one of the three main types of skin cancer along with basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), and develops from melanocytes. 2019 saw the beginning of the National Skin Cancer Prevention Programme (OPPNS) in Poland. One of the tasks performed was a health promotion campaign for patients. To effectively educate the public, the project was preceded by a survey assessing knowledge on skin cancer prevention methods. Then, the survey was repeated to evaluate the effectiveness of the awareness raising campaign.

Materials and methods

both studies were conducted based on an author-developed survey. A representative sample size was determined based on the calculator available at www.cem.pl/pl/analizy/wielkość-proby. In addition, each participant filled in a knowledge upgrade declaration. The analysis employed basic statistical data, such as absolute numbers and structural indicators.

Results and Conclusions

Knowledge upgrade score of 9.16 (out of 10) was declared by 99.7% of the respondents. As many as 99.0% of them declared an intent to change their lifestyle to a healthier one. Thus, the education provided to the Programme participants was confirmed to have raised their awareness of skin cancer prevention and self-examination methods.

Cuproptosis in cancers: Function and implications from bench to bedside

Copper, an indispensable micronutrient, is implicated in numerous vital biological processes and is essential for all physiological activities. Recently, the discovery of a novel type of copper-dependent cell death, known as cuproptosis, has shed light on its role in cancer development. Extensive research is currently underway to unravel the mechanisms underlying cuproptosis and its correlation with various cancer types. In this review, we summarize the findings regarding the roles and mechanisms of cuproptosis in various cancer types, including colorectal cancer, lung cancer, gastric cancer, breast cancer, liver cancer and cutaneous melanoma. Furthermore, the effects of copper-related agents such as copper chelators and copper ionophores on cell proliferation, apoptosis, angiogenesis, tumor immunity, and chemotherapy resistance have been explored in cancer preclinical and clinical trials. These insights provide promising avenues for the development of prospective anticancer drugs aimed at inducing cuproptosis.

A Rare Presentation of Malignant Melanoma of the Face: A Case Report

Melanoma is a malignant neoplasm of melanoblasts, which are the precursors of the melanocytes arising from the neural crest cells. Melanomas can occur at various sites like the skin, eyes, upper esophagus, and meninges due to the migration of neural crest cells. Usually, the prognostic factors are decided based on the Breslow index. This case report describes a 61-year-old female who presented with the complaint of pinkish irregular swelling over the left side of her face for six months. The patient had a surgical resection, and the condition was determined to be invasive melanoma following confirmation by magnetic resonance imaging (MRI) and histological examination. Through our case report, we aim to shed light on the existing protocol for managing malignant melanoma while also exploring new aspects of presentation and multidisciplinary action.

Regression of metastatic malignant melanoma with dupilumab: A case report

Excoriated pruritus can be an intolerable symptom in patients with cancer where Type 2 inflammation and its associated cytokines IL-4 and IL-13 play major roles in the pruritus. Dupilumab, an antibody blocking IL-4 and IL-13, is approved for treating moderate to severe atopic dermatitis (AD) where itching is a significant symptom. We present a case report of intractable malignancy-associated AD and pruritus with eosinophilia in a patient with stage IV malignant melanoma who was treated with dupilumab. Biweekly treatment with dupilumab led to an immediate improvement in itching and resolution of the AD, which subsided after a few doses and without significant adverse effects. Routine radiologic monitoring of the malignant melanoma showed concomitant resolution of secondary nodules in the lung, liver, and pleura. It was concluded that dupilumab may be a safe and effective treatment for intractable malignancy-associated AD with pruritus and may have potential for moderating metastatic malignant melanoma.

Iris Pigmented Lesions and Risk of Cutaneous Melanoma: Case-Control Study in Lithuania

The global incidence of cutaneous melanoma (CM) is rising, necessitating early detection and identification of risk factors across different populations. A case-control study with 180 patients with primary diagnosed CM and 182 healthy controls was conducted. Participants underwent ophthalmic and skin examinations, where the identification and counting of common melanocytic nevi (CMN) and atypical melanocytic nevi (AMN) was performed. During ophthalmic examination, high-resolution slit lamp iris images were taken. Images were categorized according to iris periphery, collaret, and freckles. There was no difference in iris periphery and collaret color between groups. However, blue/grey iris periphery and blue collaret with or without freckles were the most common patterns. The presence of pigmented iris lesions and 2-5 mm and ≥5 mm in diameter CMNs was strongly associated with CM risk. The evidence from this study indicates that blue or grey periphery and blue collaret iris pattern with iris freckles are 2.74 times higher in the CM group than controls. Further research is needed to explore iris patterns' association with CM risk in diverse populations.

Identification of novel biomarkers in the early diagnosis of malignant melanoma by untargeted liquid chromatography coupled to high-resolution mass spectrometry-based metabolomics: a pilot study

BACKGROUND

Malignant melanoma (MM) is a highly aggressive form of skin cancer whose incidence continues to rise worldwide. If diagnosed at an early stage, it has an excellent prognosis, but mortality increases significantly at advanced stages after distant spread. Unfortunately, early detection of aggressive melanoma remains a challenge.

OBJECTIVES

To identify novel blood-circulating biomarkers that may be useful in the diagnosis of MM to guide patient counselling and appropriate disease management.

METHODS

In this study, 105 serum samples from 26 healthy patients and 79 with MM were analysed using an untargeted approach by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) to compare the metabolomic profiles of both conditions. Resulting data were subjected to both univariate and multivariate statistical analysis to select robust biomarkers. The classification model obtained from this analysis was further validated with an independent cohort of 12 patients with stage I MM.

RESULTS

We successfully identified several lipidic metabolites differentially expressed in patients with stage I MM vs. healthy controls. Three of these metabolites were used to develop a classification model, which exhibited exceptional precision (0.92) and accuracy (0.94) when validated on an independent sample.

CONCLUSIONS

These results demonstrate that metabolomics using LC-HRMS is a powerful tool to identify and quantify metabolites in bodily fluids that could serve as potential early diagnostic markers for MM.

An efficient multi-class classification of skin cancer using optimized vision transformer

Skin cancer is a pervasive and deadly disease, prompting a surge in research efforts towards utilizing computer-based techniques to analyze skin lesion images to identify malignancies. This paper introduces an optimized vision transformer approach for effectively classifying skin tumors. The methodology begins with a pre-processing step aimed at preserving color constancy, eliminating hair artifacts, and reducing image noise. Here, a combination of techniques such as piecewise linear bottom hat filtering, adaptive median filtering, Gaussian filtering, and an enhanced gradient intensity method is used for pre-processing. Afterwards, the segmentation phase is initiated using the self-sparse watershed algorithm on the pre-processed image. Subsequently, the segmented image is passed through a feature extraction stage where the hybrid Walsh-Hadamard Karhunen-Loeve expansion technique is employed. The final step involves the application of an improved vision transformer for skin cancer classification. The entire methodology is implemented using the Python programming language, and the International Skin Imaging Collaboration (ISIC) 2019 database is utilized for experimentation. The experimental results demonstrate remarkable performance with the different performance metrics is accuracy 99.81%, precision 96.65%, sensitivity 98.21%, F-measure 97.42%, specificity 99.88%, recall 98.21%, Jaccard coefficient 98.54%, and Mathew's correlation coefficient (MCC) 98.89%. The proposed methodology outperforms the existing methodology.

Circulating miRNAs as biomarkers for the diagnosis in patients with melanoma: systematic review and meta-analysis

Objective: Melanoma is the most aggressive and deadly form of skin cancer, especially at later stages. There is currently no excellent diagnostic test established for the diagnosis of melanoma; however, circulating microRNAs (miRNAs) have shown some promise. We seek to conduct a systematic review and meta-analysis to establish the clinical utility of circulating miRNAs in diagnosing melanoma. Methods: PubMed, Wiley, and Web of Science were searched for studies that determined miRNA sensitivity and specificity in patients with melanoma. The included studies were assessed in Stata, and the sensitivity, specificity, summary receiver operating characteristic (SROC), positive likelihood ratio, negative likelihood ratio, and the area under the SROC curve (AUC) were calculated. Results: 9 studies with 898 melanoma patients were included in the meta-analysis. The circulating miRNAs showed high diagnostic accuracy with a sensitivity of 0.89 (p < 0.001), specificity of 0.85 (p < 0.001), diagnostic odds ratio of 45, and an area under the curve of 0.93. Conclusion: Circulating miRNAs have shown a high diagnostic power in detecting melanoma.

Aggregation-induced signal amplification strategy based on peptide self-assembly for ultrasensitive electrochemical detection of melanoma biomarker

The detection of melanoma circulating biomarker in liquid biopsies is current under evaluation for being potentially utilized for earlier cancer diagnosis and its metastasis. Herein, we developed a non-invasive electrochemical approach for ultrasensitive detection of the S100B, serving as a potential promising blood circulating biomarker of melanoma, based on an aggregation-induced signal amplification (AISA) strategy via in-situ peptide self-assembly. The fundamental principle of this assay is that the designed amphiphilic peptides (C16-Pep-Fc), fulfilling multiple functions, feature both a recognition region for specific binding to S100B and an aggregation (self-assembly) region for the formation of peptide nanomicelles under mild conditions. The C16 tails were encapsulated within the hydrophobic core of the aggregates, while the relatively hydrophilic recognition fragment Pep and Fc tag were exposed on the outer surface for subsequent recognition of S100B and signal output. AISA provided remarkable accumulation of electroactive Fc moieties that enabled ultrasensitive S100B detection of as low as 0.02 nM, which was 10-fold lower than un-amplified approach and better than previously reported assays. As a proof-of-concept study, further experiments also highlighted the good reproducibility and stability of AISA and demonstrated its usability when applied to simulated serum samples. Hence, this work not only presented a valuable assay tool for ultrasensitive detecting protein biomarker, but also advocated for the utilization of aggregation-induced signal amplification in electrochemical biosensing system, given its considerable potential for future practical applications.

A Narrative Review of Current Knowledge on Cutaneous Melanoma

Cutaneous melanoma is a public health problem. Efforts to reduce its incidence have failed, as it continues to increase. In recent years, many risk factors have been identified. Numerous diagnostic systems exist that greatly assist in early clinical diagnosis. The histopathological aspect illustrates the grim nature of these cancers. Currently, pathogenic pathways and the tumor microclimate are key to the development of therapeutic methods. Revolutionary therapies like targeted therapy and immune checkpoint inhibitors are starting to replace traditional therapeutic methods. Targeted therapy aims at a specific molecule in the pathogenic chain to block it, stopping cell growth and dissemination. The main function of immune checkpoint inhibitors is to boost cellular immunity in order to combat cancer cells. Unfortunately, these therapies have different rates of effectiveness and side effects, and cannot be applied to all patients. These shortcomings are the basis of increased incidence and mortality rates. This study covers all stages of the evolutionary sequence of melanoma. With all these data in front of us, we see the need for new research efforts directed at therapies that will bring greater benefits in terms of patient survival and prognosis, with fewer adverse effects.

Emerging role of microRNAs as regulators of protein kinase C substrate MARCKS and MARCKSL1 in cancer

MicroRNAs (miRNAs) have emerged as pivotal regulators of gene expression, playing essential roles in diverse cellular processes, including the development and progression of cancer. Among the numerous proteins influenced by miRNAs, the MARCKS/MARCKSL1 protein, a key regulator of cellular cytoskeletal dynamics and membrane-cytosol communication, has garnered significant attention due to its multifaceted involvement in various cancer-related processes, including cell migration, invasion, metastasis, and drug resistance. Motivated by the encouraging early clinical success of peptides targeting MARCKS in several pathological conditions, this review article delves into the intricate interplay between miRNAs and the MARCKS protein in cancer. Herein, we have highlighted the latest findings on specific miRNAs that modulate MARCKS/MARCKSL1 expression, providing a comprehensive overview of their roles in different cancer types. We have underscored the need for in-depth investigations into the therapeutic feasibility of targeting the miRNA-MARCKS axis in cancer, taking cues from the successes witnessed in related fields. Unlocking the full potential of miRNA-mediated MARCKS regulation could pave the way for innovative and effective therapeutic interventions against various cancer types.

Optimizing Skin Cancer Survival Prediction with Ensemble Techniques

The advancement in cancer research using high throughput technology and artificial intelligence (AI) is gaining momentum to improve disease diagnosis and targeted therapy. However, the complex and imbalanced data with high dimensionality pose significant challenges for computational approaches and multi-omics data analysis. This study focuses on predicting skin cancer and analyzing overall survival probability. We employ the Kaplan-Meier estimator and Cox proportional hazards regression model, utilizing high-throughput machine learning (ML)-based ensemble methods. Our proposed ML-based ensemble techniques are applied to a publicly available dataset from the ICGC Data Portal, specifically targeting skin cutaneous melanoma cancers (SKCM). We used eight baseline classifiers, namely, random forest (RF), decision tree (DT), gradient boosting (GB), AdaBoost, Gaussian naïve Bayes (GNB), extra tree (ET), logistic regression (LR), and light gradient boosting machine (Light GBM or LGBM). The study evaluated the performance of the proposed ensemble methods and survival analysis on SKCM. The proposed methods demonstrated promising results, outperforming other algorithms and models in terms of accuracy compared to traditional methods. Specifically, the RF classifier exhibited outstanding precision results. Additionally, four different ensemble methods (stacking, bagging, boosting, and voting) were created and trained to achieve optimal results. The performance was evaluated and interpreted using accuracy, precision, recall, F1 score, confusion matrix, and ROC curves, where the voting method achieved a promising accuracy of 99%. On the other hand, the RF classifier achieved an outstanding accuracy of 99%, which exhibits the best performance. We compared our proposed study with the existing state-of-the-art techniques and found significant improvements in several key aspects. Our approach not only demonstrated superior performance in terms of accuracy but also showcased remarkable efficiency. Thus, this research work contributes to diagnosing SKCM with high accuracy.

Identification and targeting of cancer-associated fibroblast signature genes for prognosis and therapy in Cutaneous melanoma

BACKGROUND

Cancer-associated fibroblasts (CAFs) play pivotal roles in tumor invasion and metastasis. However, studies on CAF biomarkers in Cutaneous Melanoma (CM) are still scarce. This study aimed to explore the potential CAF biomarkers in CM, propose the potential therapeutic targets, and provide new insights for targeted therapy of CAFs in CM.

METHODS

We utilized weighted gene co-expression network analysis to identify CAF signature genes in CM, and conducted comprehensive bioinformatics analysis on the CAF risk score established by these genes. Moreover, single-cell sequencing analysis, spatial transcriptome analysis, and cell experiments were utilized for verifying the expression and distribution pattern of signature genes. Furthermore, molecular docking was employed to screen potential target drugs.

RESULTS

FBLN1 and COL5A1, two crucial CAF signature genes, were screened to establish the CAF risk score. Subsequently, a comprehensive bioinformatic analysis of the CAF risk score revealed that high-risk score group was significantly enriched in pathways associated with tumor progression. Besides, CAF risk score was significantly negatively correlated with clinical prognosis, immunotherapy response, and tumor mutational burden in CM patients. In addition, FBLN1 and COL5A1 were further identified as CAF-specific biomarkers in CM by multi-omics analysis and experimental validation. Eventually, based on these two targets, Mifepristone and Dexamethasone were screened as potential anti-CAFs drugs.

CONCLUSION

The findings indicated that FBLN1 and COL5A1 were the CAF signature genes in CM, which were associated with the progression, treatment, and prognosis of CM. The comprehensive exploration of CAF signature genes is expected to provide new insight for clinical CM therapy.

Exploring the Complex and Multifaceted Interplay between Melanoma Cells and the Tumor Microenvironment

Malignant melanoma is a very aggressive skin cancer, characterized by a heterogeneous nature and high metastatic potential. The incidence of melanoma is continuously increasing worldwide, and it is one of the most common cancers in young adults. In the past twenty years, our understanding of melanoma biology has increased profoundly, and disease management for patients with disseminated disease has improved due to the emergence of immunotherapy and targeted therapy. However, a significant fraction of patients relapse or do not respond adequately to treatment. This can partly be explained by the complex signaling between the tumor and its microenvironment, giving rise to melanoma phenotypes with different patterns of disease progression. This review focuses on the key aspects and complex relationship between pathogenesis, genetic abnormalities, tumor microenvironment, cellular plasticity, and metabolic reprogramming in melanoma. By acquiring a deeper understanding of the multifaceted features of melanomagenesis, we can reach a point of more individualized and patient-centered disease management and reduced costs of ineffective treatments.

Learning how to detect: A deep reinforcement learning method for whole-slide melanoma histopathology images

Cutaneous melanoma represents one of the most life-threatening malignancies. Histopathological image analysis serves as a vital tool for early melanoma detection. Deep neural network (DNN) models are frequently employed to aid pathologists in enhancing the efficiency and accuracy of diagnoses. However, due to the paucity of well-annotated, high-resolution, whole-slide histopathology image (WSI) datasets, WSIs are typically fragmented into numerous patches during the model training and testing stages. This process disregards the inherent interconnectedness among patches, potentially impeding the models' performance. Additionally, the presence of excess, non-contributing patches extends processing times and introduces substantial computational burdens. To mitigate these issues, we draw inspiration from the clinical decision-making processes of dermatopathologists to propose an innovative, weakly supervised deep reinforcement learning framework, titled Fast medical decision-making in melanoma histopathology images (FastMDP-RL). This framework expedites model inference by reducing the number of irrelevant patches identified within WSIs. FastMDP-RL integrates two DNN-based agents: the search agent (SeAgent) and the decision agent (DeAgent). The SeAgent initiates actions, steered by the image features observed in the current viewing field at various magnifications. Simultaneously, the DeAgent provides labeling probabilities for each patch. We utilize multi-instance learning (MIL) to construct a teacher-guided model (MILTG), serving a dual purpose: rewarding the SeAgent and guiding the DeAgent. Our evaluations were conducted using two melanoma datasets: the publicly accessible TCIA-CM dataset and the proprietary MELSC dataset. Our experimental findings affirm FastMDP-RL's ability to expedite inference and accurately predict WSIs, even in the absence of pixel-level annotations. Moreover, our research investigates the WSI-based interactive environment, encompassing the design of agents, state and reward functions, and feature extractors suitable for melanoma tissue images. This investigation offers valuable insights and references for researchers engaged in related studies. The code is available at: https://github.com/titizheng/FastMDP-RL.

TP53 and its Regulatory Genes as Prognosis of Cutaneous Melanoma

The present study was the first comprehensive investigation of genetic mutation and expression levels of the p53 signaling genes in cutaneous melanoma through various genetic databases providing large datasets. The mutational landscape of p53 and its signaling genes was higher than expected, with TP53 followed by CDKN2A being the most mutated gene in cutaneous melanoma. Furthermore, the expression analysis showed that TP53, MDM2, CDKN2A, and TP53BP1 were overexpressed, while MDM4 and CDKN2B were under-expressed in cutaneous melanoma. Overall, TCGA data revealed that among all the other p53 signaling proteins, CDKN2A was significantly higher in both sun and non-sun-exposed healthy tissues than in melanoma. Likewise, MDM4 and TP53BP1 expressions were markedly greater in non-sun-exposed healthy tissues compared to other groups. However, CDKN2B expression was higher in the sun-exposed healthy tissues than in other tissues. In addition, various genes were expressed significantly differently among males and females. In addition, CDKN2A was highly expressed in the SK-MEL-30 skin cancer cell line, whereas, Immune cell type expression analysis revealed that the MDM4 was highly expressed in naïve B-cells. Furthermore, all six genes were significantly overexpressed in extraordinarily overweight or obese tumor tissues compared to healthy tissues. MDM2 expression and tumor stage were closely related. There were differences in gene expression across patient age groups and positive nodal status. TP53 showed a positive correlation with B cells, MDM2 with CD8+T cells, macrophages and neutrophils, and MDM4 with neutrophils. CDKN2A/B had a non-significant correlation with all six types of immune cells. However, TP53BP1 was positively correlated with all five types of immune cells except B cells. Only TP53, MDM2, and CDKN2A had a role in cutaneous melanoma-specific tumor immunity. All TP53 and its regulating genes may be predictive for prognosis. The results of the present study need to be validated through future screening, in vivo, and in vitro studies.

Structural Characterization and Anticancer Activity of a New Anthraquinone from Senna velutina (Fabaceae)

In this study, a novel compound was isolated, identified, and its chemical structure was determined from the extract of the roots of Senna velutina. In addition, we sought to evaluate the anticancer potential of this molecule against melanoma and leukemic cell lines and identify the pathways of cell death involved. To this end, a novel anthraquinone was isolated from the barks of the roots of S. velutina, analyzed by HPLC-DAD, and its molecular structure was determined by nuclear magnetic resonance (NMR). Subsequently, their cytotoxic activity was evaluated by the (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) method against non-cancerous, melanoma, and leukemic cells. The migration of melanoma cells was evaluated by the scratch assay. The apoptosis process, caspase-3 activation, analysis of mitochondrial membrane potential, and measurement of ROS were evaluated by flow cytometry technique. In addition, the pharmacological cell death inhibitors NEC-1, RIP-1, BAPTA, Z-VAD, and Z-DEVD were used to confirm the related cell death mechanisms. With the results, it was possible to elucidate the novel compound characterized as 2'-OH-Torosaol I. In normal cells, the compound showed no cytotoxicity in PBMC but reduced the cell viability of all melanoma and leukemic cell lines evaluated. 2'-OH-Torosaol I inhibited chemotaxis of B16F10-Nex2, SK-Mel-19, SK-Mel-28 and SK-Mel-103. The cytotoxicity of the compound was induced by apoptosis via the intrinsic pathway with reduced mitochondrial membrane potential, increased levels of reactive oxygen species, and activation of caspase-3. In addition, the inhibitors demonstrated the involvement of necroptosis and Ca²⁺ in the death process and confirmed caspase-dependent apoptosis death as one of the main programmed cell death pathways induced by 2'-OH-Torosaol I. Taken together, the data characterize the novel anthraquinone 2'-OH-Torosaol I, demonstrating its anticancer activity and potential application in cancer therapy.

Biological role and diagnostic utility of ribosomal protein L23a pseudogene 53 in cutaneous melanoma

Background

Skin melanoma is one of the deadliest types of skin cancer and develops from melanocytes. The genetic aberrations in protein-coding genes are well characterized, but little is known about changes in non-coding RNAs (ncRNAs) such as pseudogenes. Ribosomal protein pseudogenes (RPPs) have been described as the largest group of pseudogenes which are dispersed in the human genome.

Materials and methids

We looked deeply at the role of one of them, ribosomal protein L23a pseudogene 53 (RPL23AP53), and its potential diagnostic use. The expression level of RPL23AP53 was profiled in melanoma cell lines using real time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and analyzed based on the Cancer Genome Atlas (TCGA) data depending on BRAF status and clinicopathological parameters. Cellular phenotype, which was associated with RPL23AP53 levels, was described based on the REACTOME pathway browser, Gene Set Enrichment Analysis (GSEA) analysis as well as Immune and ESTIMATE Scores.

Results

We indicted in vitro changes in RPL23AP53 level depending on a cell line, and based on in silico analysis of TCGA samples demonstrated significant differences in RPL23AP53 expression between primary and metastatic melanoma, as well as correlation between RPL23AP53 and overall survival. No differences depending on BRAF status were observed. RPL23AP53 is associated with several signaling pathways and cellular processes.

Conclusions

This study showed that patients with higher expression of RPL23AP53 displayed changed infiltration of lymphocytes, macrophages, and neutrophils compared to groups with lower expression of RPL23AP53. RPL23AP53 pseudogene is differently expressed in melanoma compared with normal tissue and its expression is associated with cellular proliferation. Thus, it may be considered as an indicator of patients' survival and a marker for the immune profile assessment.

Transformer-Based Approach to Melanoma Detection

Melanoma is a malignant cancer type which develops when DNA damage occurs (mainly due to environmental factors such as ultraviolet rays). Often, melanoma results in intense and aggressive cell growth that, if not caught in time, can bring one toward death. Thus, early identification at the initial stage is fundamental to stopping the spread of cancer. In this paper, a ViT-based architecture able to classify melanoma versus non-cancerous lesions is presented. The proposed predictive model is trained and tested on public skin cancer data from the ISIC challenge, and the obtained results are highly promising. Different classifier configurations are considered and analyzed in order to find the most discriminating one. The best one reached an accuracy of 0.948, sensitivity of 0.928, specificity of 0.967, and AUROC of 0.948.

The role of histological subtypes in the survival of patients diagnosed with cutaneous or mucosal melanoma in the United States of America

BACKGROUND

Literature presents limited information on histological subtypes and their association with other factors influencing the survival of melanoma patients. To explore the risk of death due to melanoma associated with histological subtypes, this retrospective study used the Surveillance, Epidemiology, and End Results program (SEER) data from 1998 to 2019.

METHODS

A total of 27,532 patients consisting of 15,527 males and 12,005 females. The Hypertabastic Accelerated Failure Time model was used to analyze the impact of histology on the survival of patients with cutaneous or mucosal melanoma.

RESULTS

The median survival time (MST) for cutaneous patients was 149 months, whereas those diagnosed with mucosal melanoma was 34 months. Nodular melanoma had a hazard ratio of 3.40 [95% CI: (2.94, 3.94)] compared to lentigo maligna melanoma. Across all histological subtypes, females had a longer MST, when compared to males. The hazard ratio (HR) of distant to localized melanoma was 9.56 [95% CI: (7.58, 12.07)].

CONCLUSIONS

Knowledge of patients' histological subtypes and their hazard assessment would enable clinicians and healthcare providers to perform personalized treatment, resulting in a lower risk of complication and higher survivability of melanoma patients. Significant factors were stage of the disease, age, histology, sex, and income. Focus should be placed on high-risk populations with severe and aggressive histological subtypes. Programs that emphasize preventive measures such as awareness, education, and early screening could reduce risk.

Melanin Stacking Differences in Pigmented and Non-Pigmented Melanomas: Quantitative Differentiation between Pigmented and Non-Pigmented Melanomas Based on Light-Scattering Properties

Cutaneous melanoma is a cancer with metastatic potential characterized by varying amounts of pigment-producing melanocytes, and it is one of the most aggressive and fatal forms of skin malignancy, with several hundreds of thousands of cases each year. Early detection and therapy can lead to decreased morbidity and decreased cost of therapy. In the clinic, this often translates to annual skin screenings, especially for high-risk patients, and generous use of the ABCDE (asymmetry, border irregularity, color, diameter, evolving) criteria. We have used a new technique termed vibrational optical coherence tomography (VOCT) to non-invasively differentiate between pigmented and non-pigmented melanomas in a pilot study. The VOCT results reported in this study indicate that both pigmented and non-pigmented melanomas have similar characteristics, including new 80, 130, and 250 Hz peaks. Pigmented melanomas have larger 80 Hz peaks and smaller 250 Hz peaks than non-pigmented cancers. The 80 and 250 Hz peaks can be used to quantitative characterize differences between different melanomas. In addition, infrared light penetration depths indicated that melanin in pigmented melanomas has higher packing densities than in non-pigmented lesions. Using machine learning techniques, the sensitivity and specificity of differentiating skin cancers from normal skin are shown to range from about 78% to over 90% in this pilot study. It is proposed that using AI on both lesion histopathology and mechanovibrational peak heights may provide even higher specificity and sensitivity for differentiating the metastatic potential of different melanocytic lesions.

Phenolic Compounds Contribution to Portuguese Propolis Anti-Melanoma Activity

Melanoma is the deadliest type of skin cancer, with about 61,000 deaths annually worldwide. Late diagnosis increases mortality rates due to melanoma’s capacity to metastasise rapidly and patients’ resistance to the available conventional therapies. Consequently, the interest in natural products as a strategy for drug discovery has been emerging. Propolis, a natural product produced by bees, has several biological properties, including anticancer effects. Propolis from Gerês is one of the most studied Portuguese propolis. Our group has previously demonstrated that an ethanol extract of Gerês propolis collected in 2018 (G18.EE) and its fractions (n-hexane, ethyl acetate, and n-butanol) decrease melanoma cell viability. Out of all the fractions, G18.EE-n-BuOH showed the highest potential as a melanoma pharmacological therapy. Thus, in this work, G18.EE-n-BuOH was fractioned into 17 subfractions whose effect was evaluated in A375 BRAF-mutated melanoma cells. The subfractions with the highest cytotoxic activity were analysed by UPLC-DAD-ESI/MSn in an attempt to understand which phenolic compounds could account for the anti-melanoma activity. The compounds identified are typical of the Gerês propolis, and some of them have already been linked with antitumor effectiveness. These results reaffirm that propolis compounds can be a source of new drugs and the isolation of compounds could allow its use in traditional medicine.

PRIMARY MULTIPLE MALIGNANT SKIN TUMORS: MELANOMA AND BASAL CELL CARCINOMA

The incidence of skin melanoma in the world is growing every year. Despite advances in diagnostics, the identification of the primary focus of melanoma in some cases is still difficult. The natural course sometimes manifests only with the appearance of melanoma metastases, which can mimic other diseases. Patient S., 52 years old, was admitted to the FCBRN of FMBA of Russia with complaints on periodic systemic dizziness, headaches of a pressing nature, episodes of speech impairment over the past three months. According to the brain MRI-scan results, a volumetric formation of the left frontal lobe was revealed. Upon examination, two non-pigmented lesions were found on the skin of the scalp and forehead. Due to the presence of focal neurological symptoms, it was decided to remove the brain tumor using neurophysiological monitoring and the scalp skin lesion, with histological verification. Morphological diagnosis of the removed brain tumor was a metastasis of amelanotic epithelioid melanoma. The skin lesion was basal cell carcinoma. Thus, the patient had primarily multiple malignant tumors: metastatic melanoma and basal cell carcinoma. The primary focus of melanoma could not be identified by available noninvasive research methods. The patient was referred to an oncologist to decide on the tactics of further examination and treatment. To date, the patient has been treated according to the scheme sh0876 1 line 1 course of pembrolizumab 400mg IV, cycle 42 days.

Photography as the Sole Means of Proof: Medical Liability in Dermatology

Malignant melanoma is a cutaneous malignancy resulting from the uncontrolled proliferation of melanocytes and poses a challenge diagnostically because neoplastic lesions can mimic benign lesions, which are much more common in the population. Doctors, when they suspect the presence of melanoma, arrange for its removal and the performance of a histological examination to ascertain its diagnosis; in cases where the dermatoscopic examination is indicative of benignity, however, after the lesion is removed, histological examination is not always performed, a very dangerous occurrence and a harbinger of further medico-legal problems. The authors present a court litigation case of an “alleged” failure to diagnose malignant melanoma in a patient who died of brain metastases from melanoma in the absence of a certain location of the primary tumor: the physician who had removed a benign lesion a few months earlier was sued, and only thanks to the presence of photographic documentation was the health care provider able to prove his extraneousness. The aim of this paper is to formulate a proposal for a dermatological protocol to be followed in cases of excisions of benign skin lesions with a twofold purpose: on the one hand, to be able to prove, in a judicial context, the right action on the part of the sanitarians; on the other hand, to avoid the rise of so-called “defensive medicine”.

(De)troubling transparency: artificial intelligence (AI) for clinical applications

Artificial intelligence (AI) and machine learning (ML) techniques occupy a prominent role in medical research in terms of the innovation and development of new technologies. However, while many perceive AI as a technology of promise and hope-one that is allowing for more early and accurate diagnosis-the acceptance of AI and ML technologies in hospitals remains low. A major reason for this is the lack of transparency associated with these technologies, in particular epistemic transparency, which results in AI disturbing or troubling established knowledge practices in clinical contexts. In this article, we describe the development process of one AI application for a clinical setting. We show how epistemic transparency is negotiated and co-produced in close collaboration between AI developers and clinicians and biomedical scientists, forming the context in which AI is accepted as an epistemic operator. Drawing on qualitative research with collaborative researchers developing an AI technology for the early diagnosis of a rare respiratory disease (pulmonary hypertension/PH), this paper examines how including clinicians and clinical scientists in the collaborative practices of AI developers de-troubles transparency. Our research shows how de-troubling transparency occurs in three dimensions of AI development relating to PH: querying of data sets, building software and training the model The close collaboration results in an AI application that is at once social and technological: it integrates and inscribes into the technology the knowledge processes of the different participants in its development. We suggest that it is a misnomer to call these applications 'artificial' intelligence, and that they would be better developed and implemented if they were reframed as forms of sociotechnical intelligence.