Type Of Skin Cancer Research Articles

Increased CD56 expression after photodynamic therapy indicates an increased natural killer cell count following early photodynamic therapy for cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) is the second most common type of skin cancer. Photodynamic therapy (PDT) is a promising therapeutic method for managing cSCC due to its proven ability to target specific areas over time and its low risk of side effects. PDT may cause tissue damage and vascular shutdown, and may regulate local immunological responses. The present study aimed to investigate and compare the early lymphocyte modifications before and after PDT for SCC. A total of 10 patients with SCC were identified by pathological investigation. Initially, all wounds were treated with 20% aminolevulinic acid (ALA)-PDT as the initial stage in the therapeutic procedure. The wounds were treated by exposing them to red LED light with a wavelength of 635 nm, an energy density of 100 J/cm2 and an intensity of 80 mW/cm2. The tumor tissue was surgically removed 24 h later, and another round of PDT therapy was administered. Immunohistochemistry for CD3 and CD56 was conducted on the wound tissue post-surgery. If the wound showed granulation, necrosis or secretion, debridement was added to the therapy. All patients were monitored for 0.6-1.0 year post-treatment. ALA-PDT combination surgery fully controlled the tumor tissue in all 10 patients. The immunohistochemical analysis of the wound tissues showed that the expression of CD56 increased, while the expression of CD3 was not different after photodynamic therapy. These results also indirectly indicated that the overall count of NK cells in the 10 patients increased, nevertheless, there was no alteration in the T lymphocyte count. In conclusion, the ALA-PDT combination surgical therapy for cSCC demonstrates favorable results. An increase in CD56 expression may be a mechanism for the effective treatment of cSCC with PDT.

Optimized attention-induced multihead convolutional neural network with efficientnetv2-fostered melanoma classification using dermoscopic images.

Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatologists in detection, yet the nuances between melanoma and non-melanoma conditions complicate diagnosis. Early identification of melanoma is vital for successful treatment, but manual diagnosis is time-consuming and requires a dermatologist with training. To overcome this issue, this article proposes an Optimized Attention-Induced Multihead Convolutional Neural Network with EfficientNetV2-fostered melanoma classification using dermoscopic images (AIMCNN-ENetV2-MC). The input pictures are extracted from the dermoscopic images dataset. Adaptive Distorted Gaussian Matched Filter (ADGMF) is used to remove the noise and maximize the superiority of skin dermoscopic images. These pre-processed images are fed to AIMCNN. The AIMCNN-ENetV2 classifies acral melanoma and benign nevus. Boosted Chimp Optimization Algorithm (BCOA) optimizes the AIMCNN-ENetV2 classifier for accurate classification. The proposed AIMCNN-ENetV2-MC is implemented using Python. The proposed approach attains an outstanding overall accuracy of 98.75%, less computation time of 98 s compared with the existing models.

Overcoming melanin interference in melanocyte photodynamic therapy with a pyrene-derived two-photon photosensitizer

Photodynamic therapy (PDT) is primarily applied in the treatment of skin diseases. However, conventional PDT is less effective for melanoma, a type of skin cancer that contains melanin pigment, due to melanin’s broad absorption spectrum in the ultraviolet–visible region. This reduces the effectiveness of traditional photosensitizers (PSs) in PDT. Here, we introduced pyrene based two-photon (TP) PSs that are easy to synthesize. Among the π-extended pyrene derivatives, we have confirmed the synergetic generation of reactive oxygen species (ROS) with asymmetric pyrene (Py3). We proposed a mechanism explaining the higher ROS generation efficiency of Py3 compared with that of the symmetric derivatives through theoretical calculations. Py3 effectively stains the plasma membrane of melanoma cells and demonstrates superior PDT efficacy compared with Chlorin e6. As the melanin content increases in melanoma cells, cell death significantly decreases under visible light excitation; notably, it is minimally affected by TP irradiation at 750 nm. In 3D multicellular tumor spheroids with a high melanin content, Py3 showed high PDT efficacy through TP irradiation, whereas under visible light irradiation, PDT efficacy decreased. In experiments involving the injection of Py3 into the tail of mice with B16F10 and 4 T1 tumor models, followed by TP-PDT, we observed significant inhibition of tumor growth and high biocompatibility. Our results indicate a promising TP-PDT method for treating melanomas.

Championing Diversity in Mohs and Cutaneous Oncology: Reducing Disparities in Skin Cancer Care for Patients of Color.

Skin cancer is the most common type of cancer affecting people in America. Skin cancer grows in patients from many diverse racial and ethnic backgrounds. Research shows that there are significant disparities that exist in the diagnosis and treatment of skin cancer for patients of color. Patients of color have lower incidence but higher rates of mortality for certain types of skin cancers. This article expounds on the role of diversity in Mohs surgery and cutaneous oncology to improve medical outcomes and address these health care disparities. By training an oncology workforce that has increased representation and improved cultural competence, the health care system can collaborate to achieve health equity in the treatment of skin cancer. Through both collaboration and advocacy, the oncology field can create an inclusive health care system that prioritizes the needs of all patients.

A Review on Skin Melanoma Classification using different ML and DL Models

This review explores the classification of skin melanoma utilizing various machine learning (ML) and deep learning (DL) models, highlighting the advancements and comparative performance of these methodologies. Skin melanoma, a serious type of skin cancer, demands early and accurate diagnosis for effective treatment. The review covers a range of ML techniques such as support vector machines, decision trees, and ensemble methods, alongside \DL approaches including convolutional neural networks and recurrent neural networks. Emphasis is placed on the models' accuracy, computational efficiency, and the datasets used for training and validation. The review underscores the potential of DL models to outperform traditional ML methods due to their ability to automatically extract and learn intricate features from large datasets, thus offering promising prospects for enhanced diagnostic precision in melanoma classification.

SKIN CANCER DETECTION USING CNN

The skin is the main component of a human body and serves to cover all of the body's muscles, bones, and other structures. Many people these days are afflicted with skin cancer. Skin cancer that is most deadly is called malignant melanoma. Melanoma is the most dangerous kind of cancer. It is a massive malignant tumour on the skin, and its spread is growing daily. If melanoma is discovered early on, treatment is straightforward. Melanoma diagnosis involves both automated and clinical procedures. Early detection of malignant melanoma has significant potential with image-based computer aided diagnosis methods. Automatically identifying the type of skin cancer from the pictures can help with a speedier diagnosis and improved accuracy.

The Burden of Multiple Basal Cell Carcinomas: A Population-wide Study.

Basal cell carcinoma (BCC) is a common skin cancer type and affected individuals are known to be at risk of developing multiple consecutive tumours. Research into BCC multiplicity has, thus far, been challenging, due to a lack of national registration. This registry-based cohort study aimed to analyse the occurrence of multiple BCCs in Sweden, and risk factors for subsequent primary BCCs. Data regarding all histopathologically verified, primary BCC tumours in Sweden from 2004 to 2017 was extracted from the Swedish BCC Registry. Risk of developing a subsequent BCC in relation to person-related factors was estimated with Cox regression analysis. Cumulative risk of BCC development after 1 or 3 earlier BCCs was estimated. In total, 39.9% of individuals with a registered BCC had at least 2 registered tumours. The risk of developing a subsequent BCC increased significantly in males, older age, and with residence in southern Sweden. The cumulative 5-year risk of developing an additional BCC after first diagnosis was approximately 30% in males and 27% in females and increased after multiple previous BCCs. This study showed the cumulative risk of a subsequent BCC to increase with a history of multiple BCCs, indicating the need for clinical surveillance in these individuals.

A retrospective analysis of drugs associated with the development of cutaneous squamous cell carcinoma reported by patients on the FDA’s adverse events reporting system

Cutaneous squamous cell carcinoma (cSCC) is the second most common type of skin cancer arising from squamous cells of the epidermis. Most cases of cSCC have a good prognosis if detected and treated early; however, certain cases can be aggressive. The primary risk factor for cSCC is prolonged ultraviolet radiation from sun exposure, leading to DNA mutations. Other risk factors have also been observed, including adverse reactions to medications, particularly immunosuppressants. A query of the Food and Drug Administration Adverse Events Reporting System (FAERS) was done, and all reported events of cSCC as adverse events to medication were recorded along with demographic data of patients affected. A total of 4,792 cases of cSCC as an adverse event to medication were reported between 1997 and 2023. Lenalidomide, a chemotherapeutic drug, had the most cases of cSCC as an adverse event. Nine of the top 10 drugs associated with cSCC had immunosuppressive characteristics. While males had higher odds of cSCC associated with corticosteroids and calcineurin inhibitors, females had higher odds of cSCC related to monoclonal antibodies. Geriatric patients accounted for the majority of cSCC cases at 59.7%. Drawing on data from the FAERS database, there’s been a consistent increase in cSCC cases as a side-effect to certain medications, with most having immunosuppressive characteristics. Since there is a lack of up-to-date literature overviewing the most implicated medications for cSCC, we aimed to illustrate this better, as well as patient demographics, to better guide clinicians when prescribing these medications.

SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma

Melanoma, arising from the malignant transformation of melanocytes, stands as the most lethal type of skin cancer. While significant strides have been made in targeted therapy and immunotherapy, substantially enhancing therapeutic efficacy, the prognosis for melanoma patients remains unoptimistic. SIRT7, a nuclear-localized deacetylase, plays a pivotal role in maintaining cellular homeostasis and adapting to external stressors in melanoma, with its activity closely tied to intracellular nicotinamide adenine dinucleotide (NAD+). However, its involvement in adaptive resistance to targeted therapy remains unclear. Herein, we unveil that up-regulated SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma. Initially, we observed a significant increase of SIRT7 expression in publicly available datasets following targeted therapy within a short duration. In consistent, we found elevated SIRT7 expression in melanoma cells subjected to BRAF or MEK inhibitors in vitro. The up-regulation of SIRT7 expression was also confirmed in xenograft tumors in mice after targeted therapy in vivo. Furthermore, we proved that SIRT7 deficiency led to decreased cell viability upon prolonged exposure to BRAF or MEK inhibitors, accompanied by an increase in cell apoptosis. Mechanistically, SIRT7 deficiency restrained the upregulation of genes associated with mitochondrial biogenesis and intracellular ATP levels in response to targeted therapy treatment in melanoma cells. Ultimately, we proved that SIRT7 deficieny could sensitize BRAF-mutant melanoma cells to MAPK inhibition targeted therapy in vivo. In conclusion, our findings underscore the role of SIRT7 in fostering adaptive resistance to targeted therapy through the facilitation of mitochondrial biogenesis. Targeting SIRT7 emerges as a promising strategy to overcome MAPK inhibitor adaptive resistance in melanoma.

The influence of viscosity of hydrogels on the spreading and migration of cells in 3D bioprinted skin cancer models.

Various in vitro three-dimensional (3D) tissue culture models of human and diseased skin exist. Nevertheless, there is still room for the development and improvement of 3D bioprinted skin cancer models. The need for reproducible bioprinting methods, cell samples, biomaterial inks, and bioinks is becoming increasingly important. The influence of the viscosity of hydrogels on the spreading and migration of most types of cancer cells is well studied. There are however limited studies on the influence of viscosity on the spreading and migration of cells in 3D bioprinted skin cancer models. In this review, we will outline the importance of studying the various types of skin cancers by using 3D cell culture models. We will provide an overview of the advantages and disadvantages of the various 3D bioprinting technologies. We will emphasize how the viscosity of hydrogels relates to the spreading and migration of cancer cells. Lastly, we will give an overview of the specific studies on cell migration and spreading in 3D bioprinted skin cancer models.

Искусственный интеллект как инструмент популяционного скрининга опухолей кожи

BCC/SCC and melanoma are the most common types of skin cancer. Low public awareness, unavailability of local professional dermatological expertise, and ineffective screening programs prevent early detection critical for successful treatment. Aim. Evaluate capabilities of AI-powered mobile application for population screening. Materials and methods. We proposed a free mobile application for regular skin self-examination based on AI analysis of photos taken using a smartphone enriched with demographic data and risk factors. Our model provides a binary output (malignant/benign), encouraging people to see dermatologists for an in-depth examination if a risk of a malignant skin tumor is detected. Results. We received and processed 500,000+ images of skin neoplasms taken by 290,000 users from 86 regions of the Russian Federation from 01.2021 to 12.2022. The images were accompanied by demographic data and responses to a questionnaire on cancer risk factors. 5,957 cases of BCC/SCC and 7,622 cases of melanoma were detected. Analysis of the campaign results revealed a significantly higher prevalence of malignant skin tumors per 100,000 population. Our results exposed a much younger average age of skin cancer patients in both men and women populations compared to official statistics, with a difference of 15 years. Conclusion. The AI-based mobile application proved to be a feasible vehicle for skin cancer mass screening campaigns requiring no significant investment from the public health authorities. The proposed tool provides an efficient way to increase public awareness about skin cancer and associated risk factors as well as encourages people to seek dermatologists’ help in case of skin cancer risk.

Common skin cancers and their association with other non-cutaneous primary malignancies: a review of the literature.

It has long been recognized that a history of skin cancer puts one at risk for additional primary skin cancers. However, more variable data exists for the risk of developing a non-cutaneous primary cancer following a diagnosis of skin cancer. The data are most variable for Basal Cell Carcinoma (BCC), the most common and least aggressive type of skin cancer. While early studies imply that BCC does not impart a larger risk of other primary non-cutaneous cancers, more recent studies with larger populations suggest otherwise. The cancers most significantly associated with BCC are lip, oropharyngeal, and salivary gland cancer. There is also burgeoning evidence to suggest a link between BCC and prostate, breast, and colorectal cancer, but more data are needed to draw a concrete conclusion. Squamous Cell Carcinoma (SCC), the second most common type of skin cancer, has a slightly more defined risk to other non-cutaneous primary malignancies. There is a notable link between SCC and non-Hodgkin's lymphoma (NHL), possibly due to immunosuppression. There is also an increased risk of other cancers derived from squamous epithelium following SCC, including oropharyngeal, lip, and salivary gland cancer. Some studies also suggest an increased risk of respiratory tract cancer following SCC, possibly due to shared risk factors. Melanoma, a more severe type of skin cancer, shows a well-defined risk of additional primary non-cutaneous malignancies. The most significant of these risks include NHL, thyroid cancer, prostate cancer, and breast cancer along with a host of other cancers. Each of these three main skin cancer types has a profile of genetic mutations that have also been linked to non-cutaneous malignancies. In this review, we discuss a selection of these genes to highlight the complex interplay between different tumorigenesis processes.

Photodynamic therapy in the treatment of non-melanoma skin cancer: A literature review

Objective: The following study aims to analyze the mechanism of action, efficacy, safety and recent trends in the use of photodynamic therapy (PDT) as a therapeutic approach in the treatment of non-melanoma skin cancer. In addition, it seeks to provide a comprehensive overview of the current state of knowledge on the subject, highlighting its use and availability in the Brazilian scenario. Methods: The research was carried out using a literature review based on data published in Periódicos CAPES, Biblioteca Virtual de Saúde (BVS) and UpToDate. Results: PDT is a technique that has already been consolidated globally and has several advantages in the treatment of non-melanoma skin cancer, as well as actinic keratoses, even in comprehensive cases. PDT is considered a non-invasive, fast, safe method, with few side effects, providing rapid recovery and being well tolerated by patients. It has a significant cure rate and excellent aesthetic results, differing from other treatments often cited for their disadvantages, such as undesirable scars. Conclusion: It is crucial to further explore the benefits of PDT, considering its application in different subtypes of non-melanoma skin cancer and optimizing protocols to expand its clinical application. As a promising innovation, the technology has the prospect of contributing to improving the quality of life of patients affected by this specific type of skin cancer.

Incidence Rates and Time Trends of Skin Cancer in Golestan Province, Northeastern Iran, 2005-2018.

Given the significant occurrence of skin cancer in the Middle East and the existing research gap concerning its incidence and trends, this research aimed to study the epidemiology and trend changes of skin cancer in the Golestan province, Northeastern Iran. The Golestan Population-based Cancer Registry's (GPCR's) data bank was utilized to gather information on confirmed skin cancer cases in the province during 2005-2018. We used Poisson regression analysis for comparing incidence rates between groups. P values less than 0.05 were considered statistically significant. Of 1690 patients (mean age: 62.05±15.83 years), most were male (60.1%) and resided in urban areas (61.5%). The age-standardized rate (ASR) of non-melanoma and melanoma skin cancer was 8.49 and 0.56 per 100000 persons-year, respectively. A notably higher ASR for non-melanoma skin cancer (NMSC) was observed in men (ASR: 10.60; 95% CI: 9.91-11.29) (P<0.01) and urban residents (ASR: 10.19; 95% CI: 9.52-10.82) (P<0.01). There was no significant difference in the ASR of melanoma skin cancer based on gender (P=0.24) and place of residence (P=0.48). The incidence trend of melanoma (estimated annual percent change [EAPC]: -3.28; 95% CI: -18.54 to 14.83) and NMSC (EAPC: 0.39; 95% CI: -3.99 to 4.97) did not differ significantly. During the 14-year study period, the ASR of both types of skin cancer exhibited a consistent pattern, except for NMSC, which showed higher rates among men and urban residents. This should be taken into consideration when formulating preventive and control strategies in the study area.

The risk of skin cancer in women who carry BRCA1 or BRCA2 mutations

BackgroundIt has not been clearly established if skin cancer or melanoma are manifestations of BRCA1 or BRCA2 mutation carrier status. Estimating the risk of skin cancer is an important step towards developing screening recommendations.MethodsWe report the findings of a prospective cohort study of 6,207 women from North America who carry BRCA1 or BRCA2 mutations. Women were followed from the date of baseline questionnaire to the diagnosis of skin cancer, to age 80 years, death from any cause, or the date of last follow-up.ResultsDuring the mean follow-up period of eight years, 3.7% of women with a BRCA1 mutation (133 of 3,623) and 3.8% of women with a BRCA2 mutation (99 of 2,584) reported a diagnosis of skin cancer (including both keratinocyte carcinomas and melanoma). The cumulative risk of all types of skin cancer from age 20 to 80 years was 14.1% for BRCA1 carriers and 10.7% for BRCA2 carriers. The cumulative risk of melanoma was 2.5% for BRCA1 carriers and 2.3% for BRCA2 carriers, compared to 1.5% for women in the general population in the United States. The strongest risk factor for skin cancer was a prior diagnosis of skin cancer.ConclusionThe risk of non-melanoma skin cancer in women who carry a mutation in BRCA1 or BRCA2 is similar to that of non-carrier women. The risk of melanoma appears to be slightly elevated. We suggest that a referral to a dermatologist or primary care provider for BRCA mutation carriers for annual skin examination and counselling regarding limiting UV exposure, the use of sunscreen and recognizing the early signs of melanoma might be warranted, but further studies are necessary.

Scalp Spinal Cell Carcinoma Managed with Resection and Ying Yang Flap

The second most frequent type of non-melanoma skin cancer is cutaneous squamous cell carcinoma (cSCC). We present the case of a squamous cell carcinoma of the scalp with surgical management and the importance of the Ying-yang flap. Ying-Yang flaps" are employed when there is stress on the incision, especially on the scalp and lower extremities.

A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography

Objective. Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising. Approach. In this work, we propose a novel approach to rapid and non-invasive skin cancer diagnosis that leverages the technologies of difference-based electrical impedance tomography (EIT) and graphene electronic tattoos (GETs). Main results. We demonstrate the feasibility of this first-of-its-kind system using both computational numerical and experimental skin phantom models. We considered variations in skin cancer lesion impedance, size, shape, and position relative to the electrodes and evaluated the impact of using individual and multi-electrode GET (mGET) arrays. The results demonstrate that this approach has the potential to differentiate based on lesion impedance, size, and position, but additional techniques are needed to determine shape. Significance. In this way, the system proposed in this work, which combines both EIT and GET technology, exhibits potential as an entirely non-invasive and rapid approach to skin cancer diagnosis.

Enhancing Skin Cancer Classification using Efficient Net B0-B7 through Convolutional Neural Networks and Transfer Learning with Patient-Specific Data.

Skin cancer diagnosis challenges dermatologists due to its complex visual variations across diagnostic categories. Convolutional neural networks (CNNs), specifically the Efficient Net B0-B7 series, have shown superiority in multiclass skin cancer classification. This study addresses the limitations of visual examination by presenting a tailored preprocessing pipeline designed for Efficient Net models. Leveraging transfer learning with pre-trained ImageNet weights, the research aims to enhance diagnostic accuracy in an imbalanced multiclass classification context. The study develops a specialized image preprocessing pipeline involving image scaling, dataset augmentation, and artifact removal tailored to the nuances of Efficient Net models. Using the Efficient Net B0-B7 dataset, transfer learning fine-tunes CNNs with pre-trained ImageNet weights. Rigorous evaluation employs key metrics like Precision, Recall, Accuracy, F1 Score, and Confusion Matrices to assess the impact of transfer learning and fine-tuning on each Efficient Net variant's performance in classifying diverse skin cancer categories. The research showcases the effectiveness of the tailored preprocessing pipeline for Efficient Net models. Transfer learning and fine-tuning significantly enhance the models' ability to discern diverse skin cancer categories. The evaluation of eight Efficient Net models (B0-B7) for skin cancer classification reveals distinct performance patterns across various cancer classes. While the majority class, Benign Kertosis, achieves high accuracy (>87%), challenges arise in accurately classifying Eczema classes. Melanoma, despite its minority representation (2.42% of images), attains an average accuracy of 80.51% across all models. However, suboptimal performance is observed in predicting warts molluscum (90.7%) and psoriasis (84.2%) instances, highlighting the need for targeted improvements in accurately identifying specific skin cancer types. The study on skin cancer classification utilizes EfficientNets B0-B7 with transfer learning from ImageNet weights. The pinnacle performance is observed with EfficientNet-B7, achieving a groundbreaking top-1 accuracy of 84.4% and top-5 accuracy of 97.1%. Remarkably efficient, it is 8.4 times smaller than the leading CNN. Detailed per-class classification exactitudes through Confusion Matrices affirm its proficiency, signaling the potential of EfficientNets for precise dermatological image analysis.

Melanoma Detection using Deep Learning Algorithms

Abstract: Melanoma is a type of skin cancer that arises from pigment-producing cells called melanocytes. These cells are responsible for the production of melanin, the pigment that gives skin, hair and eyes their color. Melanoma is considered more dangerous than other types of cancer because it can spread (metastasize) to other parts of the body. Key features of melanoma include the formation of abnormal or cancerous cells in the skin pigment. The main cause of melanoma is exposure to ultraviolet (UV) radiation from the sun or tanning beds. Most malignant tumours can be treated if diagnosed early. Therefore, early diagnosis of skin cancer is important to save the lives of patients. With today's technology, skin cancer can be diagnosed early and treated effectively. The traditional method of detecting melanoma relies on eye exams where dermatologists review biopsy results, which is time-consuming. These facilities are less available in rural areas where doctors are often available but dermatologists are not. This study was designed to develop a system that uses deep learning techniques to identify melanoma.

Boronophenylalanine‐Containing Polydopamine Nanoparticles for Enhanced Combined Boron Neutron Capture Therapy and Photothermal Therapy for Melanoma Treatment

AbstractMelanoma, the most aggressive skin cancer type, is challenging to treat due to its high metastatic potential and low response to conventional therapies. Innovative approaches, including combination therapies, are crucial for enhancing treatment efficacy while minimizing side effects. It is developed boronophenylalanine‐containing polydopaine (B‐PDA) nanoparticles by encapsulating boronophenylalanine in polydopamine through nitrogen‐boronate coordination, targeting both boron neutron capture therapy (BNCT) and photothermal therapy (PTT). With stability and biocompatibility under physiological conditions, these nanoparticles utilize the phenylalanine residues in BPA to target the overexpressed neutral amino acid transporter 1 (LAT1) in melanoma cells, resulting in enhanced cell‐specific targeting. B‐PDA nanoparticles demonstrated significant photothermal effects under external stimulation, inducing localized heating and triggering heterogeneous tumor cell death, thereby enhancing sensitivity to BNCT. Combining BNCT and PTT, the B‐PDA nanoparticles offer a promising strategy for melanoma treatment.