Skin Cancer Research Articles

Reconstruction after Nasal Skin Cancer Resection: Nasal Obstruction and Associated Factors.

Background: Equal attention must be given to nasal aesthetics and function when reconstructing nasal defects after skin cancer resection. Little data exist on functional nasal outcomes following nasal reconstruction. Learning/Study Objective: Describe and analyze factors contributing to functional outcomes following nasal skin cancer defect reconstruction. Design Type: Retrospective review. Methods: Patients who underwent reconstruction of Mohs nasal defects were included. Reconstruction methods included primary closure, skin grafts, and local and interpolated flaps. Both subjective reports and physician-noted exam findings suggestive of nasal obstruction were noted. The obstructive domain of the Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS-O) was administered preoperatively and at follow-up intervals. Results: In total, 193 patients met the inclusion criteria. Female sex, medial or lateral ala primary defect subunit, and auricular cartilage use were associated with increased risk of postoperative nasal obstruction within the first year on multivariate analysis, while reconstruction with a skin/composite graft was associated with lower risk of obstruction. Average time from reconstructive surgery to first report of obstruction was 116 days, and time to reported resolution was 235 days. Conclusion: The incidence of nasal obstruction following nasal defect reconstruction is low. Female sex, ala involvement, and auricular cartilage may increase the risk of nasal obstruction postoperatively.

From toasted skin to tumors: a retrospective nationwide case-control analysis investigating the link between erythema ab igne and various skin cancers

From toasted skin to tumors: a retrospective nationwide case-control analysis investigating the link between erythema ab igne and various skin cancers

Australian Sunscreens: The Price of Protection for Skin of Colour With Pigmentary Disorders.

Australia experiences some of the highest ultraviolet radiation (UVR) levels globally, known for causing sunburn, skin cancers, photoageing and immunosuppression. While effects of UVA and UVB are well-studied, visible light (VL; 400-700 nm) is the driving force behind pigmentary disorders, especially in skin of colour (SOC) patients. Nearly 50% of Australians are affected, with significant impacts on appearance and psychological well-being. Tinted sunscreens containing iron oxides and pigmentary-grade titanium dioxide are the only effective options for blocking VL. However, Australia's stringent Therapeutic Goods Administration (TGA) regulations limit the availability of colour-matched tinted sunscreens, significantly impacting SOC patients. SOC patients may also underestimate their need for photoprotection, believing their skin provides sufficient natural protection. In dermatological practice, tailored sunscreen recommendations for darker skin tones may sometimes be overlooked. This review explores the barriers to effective treatment and the cost implications for SOC individuals suffering from pigmentary disorders in Australia. The goal is to guide both patients and dermatologists in making informed decisions on VL protection and skin tone matching.

Cutaneous leishmaniasis misdiagnosed as epithelial skin cancer

Cutaneous leishmaniasis, transmitted by sand flies of the genus Phlebotomus, is one of the most important traveler's dermatoses in Germany. In recent years, an increased incidence of the disease has been observed in travelers returning from endemic areas, including the Mediterranean region of Spain and Italy. In these regions, Leishmania infantum belonging to the Leishmania donovani complex is characteristically the most frequently detected pathogen. We herein report two cases of cutaneous leishmaniasis caused by Leishmania infantum with solitary or multilocular lesions, initially misdiagnosed as actinic keratosis and cutaneous squamous cell carcinoma.

Photocarcinogenesis of the skin: Current status and future trends.

Solar radiation is essential for life on Earth but is also a major contributor to skin carcinogenesis. Solar radiation, particularly ultraviolet (UV) B (280-320 nm) and UVA (320-400 nm), induces photocarcinogenesis via various pathways. UV light can directly cause DNA damage, resulting in genetic mutations if not repaired correctly. UV light can also induce photocarcinogenesis by generating reactive oxygen species, inducing immunosuppression and inflammation. Recently, visible light (400-760 nm) has been shown to contribute to photocarcinogenesis by activating oxidative pathways. In addition to the irradiation dose (fluence, J/m2), UVB irradiance (W/m2) is also considered a factor influencing photocarcinogenesis. In this review, we summarize the mechanisms of photocarcinogenesis and provide strategies to prevent skin cancer.

Effective and safe surgery for keratinocyte skin cancer in the elderly over 80 years of age: a single-institution retrospective study of 345 patients over one year

Objectives As life expectancy rises and the population continues to age, physicians will be faced with an increasing number of elderly patients with keratinocyte cancer (KC). This study aims to better characterize KC surgery in patients over 80 years of age, with a particular focus on the incidence of postoperative complications. Methods A retrospective study was conducted on all patients aged 80 years and older who underwent surgery for KC at the University Hospital of Zurich in 2022. Data were collected from operative and postoperative notes within six months after surgery. Results A total of 565 tumors were removed from 345 patients, consisting mainly of basal cell carcinoma (46.5%) and squamous cell carcinoma (45.8%), including 24.2% clinically large tumors (>2 cm in diameter). A total of 26 complications were recorded, resulting in an overall complication rate of4.6%. Only one patient with a hematoma required surgical revision under local anaesthesia. Four cases of hemorrhage were solved by bed side ligations under local anaesthesia. Of the 26 recorded complications, 15 (58%) concerned wound dehiscence, requiring no further measures. The use of novel oral anticoagulants, lower extremity location, surgical specimen size >2 cm2, and flap repair were found to be independent risk factors associated with a statistically higher incidence of complications. Conclusions This study demonstrated that dermatologic surgery adapted to the geriatric population is relatively safe and effective, even for larger KC of several centimeters in diameter.

Modulating Polyphenol Activity with Metal Ions: Insights into Dermatological Applications

Background: The skin represents the first barrier of defense, and its integrity is crucial for overall health. Skin wounds present a considerable risk seeing how their progression is rapid and sometimes they are caused by comorbidities like diabetes and venous diseases. Nutraceutical combinations like the ones between polyphenols and metal ions present considerable applications thanks to their increased bioavailability and their ability to modulate intrinsic molecular pathways. Methods: The research findings presented in this paper are based on a systematic review of the current literature with an emphasis on nanotechnology and regenerative medicine strategies that incorporate polyphenols and metallic nanoparticles (NPs). The key studies which described the action mechanisms, efficacy, and safety of these hybrid formulations were reviewed. Results: Nanocomposites of polyphenol and metal promote healing by activating signaling pathways such as PI3K/Akt and ERK1/2, which in turn improve fibroblast migration and proliferation. Nanoparticles of silver and copper have antibacterial, angiogenesis-promoting, inflammation-modulating capabilities. With their ability to induce apoptosis and restrict cell growth, these composites have the potential to cure skin malignancies in addition to facilitating wound healing. Conclusions: Nanocomposites of polyphenols and metals provide hope for the treatment of cancer and chronic wounds. Their antimicrobial capabilities, capacity to modulate inflammatory responses, and enhancement of fibroblast activity all point to their medicinal potential. Furthermore, these composites have the ability to decrease inflammation associated with tumors while simultaneously inducing cell death in cancer cells. Clarifying their mechanisms, guaranteeing stability, and enhancing effective delivery techniques for clinical usage should be the focus of future studies.

Gut microbiome features associate with immune checkpoint inhibitor response in individuals with non-melanoma skin cancers: an exploratory study.

Immune checkpoint inhibitor (ICI) therapy has yielded revolutionary outcomes among some individuals with skin cancer, but a large percentage of individuals do not benefit from these treatments. The gut microbiota is hypothesized to impact ICI therapy outcomes. However, data on ICI therapy, gut microbiota, and non-melanoma skin cancers are limited. To examine the association of gut microbiota structure and function with non-melanoma skin cancer ICI outcomes, we performed 16S rRNA V1-V2 gene amplicon sequencing of 68 fecal samples collected longitudinally from individuals with basal cell carcinoma (n = 5), Merkel cell carcinoma (n = 5), or cutaneous squamous cell carcinoma (CSCC, n = 11), followed by tumor-dependent differential analyses of bacterial composition and fecal sample analysis by untargeted metabolomics. Across all tumor types, we identified 10 differential bacterial genera between responders (R) or non-responders (NR) to ICI therapy. Among individuals with CSCC, we identified 10 genera and 20 species that differentiated between R and NR and yielded 8 pathways enriched in NR and 12 pathways enriched in R by predicted functional pathway analyses. Untargeted fecal metabolomics to examine putative gut microbiota metabolites associated with CSCC ICI R/NR identified nine KEGG pathways associated with ICI efficacy. In summary, this exploratory study suggests gut microbiota features that are associated with ICI efficacy in individuals with non-melanoma skin cancers and highlights the need for larger studies to validate the results.IMPORTANCEPrior studies examining associations between ICI efficacy and the gut microbiome have focused primarily on individuals with melanoma, for whom ICI therapy was first approved. Meanwhile, data regarding microbiome features associated with ICI responses in individuals with non-melanoma skin cancers (NMSCs) have remained limited. This initial fecal microbiota examination of individuals with NMSCs suggests that larger-scale studies to extend and validate our findings may yield predictive or prognostic biomarkers for individuals with NMSC receiving ICI with potential to provide insight to complementary, effective therapeutic interventions through microbiota modification.

Topical Photodynamic Therapy in a Medical Centre: The Scottish Dermatology Experience.

Topical photodynamic therapy (PDT) is widely used in dermatology for treating superficial non-melanoma skin cancer (NMSC) and dysplasia. This study aims to assess real-world outcomes of PDT in a Scottish dermatology service. We retrospectively reviewed patients with superficial NMSC and dysplasia who underwent conventional and daylight PDT at the Photobiology Unit, Dundee, Scotland. A total of 705 patients with 2108 NMSC and precancerous skin lesions underwent conventional PDT. Clearance at 12 months was achieved in 53.4% of actinic keratoses (AK), 71.3% of Bowenoid AK, 86.4% of Bowen's disease (BD), 89.0% of superficial basal cell carcinoma (BCC), and 89.7% of nodular BCC. On multivariate analysis, small lesion size and thin histological tumour thickness of superficial BCC were features, which were associated with likelihood of achieving clearance after PDT. Female sex, head/neck sites, larger lesion size, strong pre-treatment fluorescence intensity, fluorescence specificity, prominent treatment-induced erythema and an urticarial reaction were associated with moderate to severe pain during PDT. Daylight PDT for 77 AK patients (158 treatments) showed excellent or good outcomes in 63.3% of lesions. Higher visible light exposure is correlated with better treatment outcomes. In real-life settings, whilst the PDT response rates of BD and selected BCC are high and consistent with clinical trial outcomes, the efficacy rates for AK appear lower than expected. This emphasizes the need for realistic expectations in chronic disease management. Through review over a prolonged period, factors associated with PDT tolerability and outcomes were identified, allowing predictive utilisation for optimizing patient-centred PDT regimens.

Training State-of-the-Art Deep Learning Algorithms with Visible and Extended Near-Infrared Multispectral Images of Skin Lesions for the Improvement of Skin Cancer Diagnosis

An estimated 60,000 people die annually from skin cancer, predominantly melanoma. The diagnosis of skin lesions primarily relies on visual inspection, but around half of lesions pose diagnostic challenges, often necessitating a biopsy. Non-invasive detection methods like Computer-Aided Diagnosis (CAD) using Deep Learning (DL) are becoming more prominent. This study focuses on the use of multispectral (MS) imaging to improve skin lesion classification of DL models. We trained two convolutional neural networks (CNNs)—a simple CNN with six two-dimensional (2D) convolutional layers and a custom VGG-16 model with three-dimensional (3D) convolutional layers—using a dataset of MS images. The dataset included spectral cubes from 327 nevi, 112 melanomas, and 70 basal cell carcinomas (BCCs). We compared the performance of the CNNs trained with full spectral cubes versus using only three spectral bands closest to RGB wavelengths. The custom VGG-16 model achieved a classification accuracy of 71% with full spectral cubes and 45% with RGB-simulated images. The simple CNN achieved an accuracy of 83% with full spectral cubes and 36% with RGB-simulated images, demonstrating the added value of spectral information. These results confirm that MS imaging provides complementary information beyond traditional RGB images, contributing to improved classification performance. Although the dataset size remains a limitation, the findings indicate that MS imaging has significant potential for enhancing skin lesion diagnosis, paving the way for further advancements as larger datasets become available.

Building Better Deep Learning Models Through Dataset Fusion: A Case Study in Skin Cancer Classification with Hyperdatasets

Background/Objectives: This work brings to light the importance of forming large training datasets with diverse images generated and proposes an image dataset merging application, namely, the Data Merger App, to streamline the management and synthesis of large-scale datasets. The Data Merger can recognize common classes across various datasets and provides tools to combine and organize them in a well-structured and easily accessible way. Methods: A case study is then presented, leveraging four different Convolutional Neural Network (CNN) models, VGG16, ResNet50, MobileNetV3-small, and DenseNet-161, and a Visual Transformer (ViT), to benchmark their performance to classify skin cancer images, when trained on single datasets and on enhanced hyperdatasets generated by the Data Merger App. Results: Extended experimental results indicated that enhanced hyperdatasets are efficient and able to improve the accuracies of classification models, whether the models are trained from scratch or by using Transfer Learning. Moreover, the ViT model was reported for higher classification accuracies compared to CNNs on datasets with a limited number of classes, reporting 91.87% accuracy for 9 classes, as well as in the case of enhanced hyperdatasets with multiple numbers of classes, reporting accuracy of 58% for 32 classes. Conclusions: In essence, this work demonstrates the great significance of data combination, as well as the utility value of the developed prototype web application as a critical tool for researchers and data scientists, enabling them to easily handle complex datasets, combine datasets into larger diverse versions, to further enhance the generalization ability of models and improve the quality and impact of their work.

Comparison of Tissue-Engineered Dermis with Micronized Adipose Tissue and Artificial Dermis for Facial Reconstruction Following Skin Cancer Resection

Our group has previously demonstrated that tissue-engineered dermis containing cultured fibroblasts or adipose-derived stromal vascular fraction cells is superior to artificial dermis in terms of scar quality for covering facial defects. However, using these cells for clinical applications requires Food and Drug Administration approval and involves complex procedures for cell culture or isolation. This retrospective study aimed to compare effects of tissue-engineered dermis containing micronized adipose tissue (MAT) and artificial dermis for facial reconstruction. Tissue-engineered dermis consisting of MAT seeded on artificial dermis was applied in 30 cases, while artificial dermis without MAT was grafted in 35 cases. Healing time and severities of scar contraction, color mismatch, and landmark distortion at one year after healing were evaluated. Wounds in the tissue-engineered dermis group re-epithelialized in 30.0 ± 4.3 days compared to 34.3 ± 5.4 days in the artificial dermis group (p < 0.05). The average dE2000 score in color mismatch analysis was 4.9 ± 1.7 in the tissue-engineered dermis group and 5.1 ± 1.7 in the artificial dermis group (p = 0.57). The extent of scar contraction was 16.2 ± 12.3% in the tissue-engineered dermis group and 23.2 ± 12.8% in the artificial dermis group (p < 0.05). The average severity grade of landmark distortion was 0.20 ± 0.50 in the tissue-engineered dermis group and 0.50 ± 0.71 in the artificial dermis group (p < 0.05). These findings indicate that tissue-engineered dermis grafts containing MAT are superior to artificial dermis grafts for facial reconstruction in terms of healing time, scar contraction, and landmark distortion severity. However, there was no significant difference in color mismatch between the two groups.

Survival and risk factors for metastatic colorectal cancer patients with a history of prior malignancy

Given concerns about treatment, there is uncertainty surrounding the effect of prior malignancy on the survival of individuals with metastatic colorectal cancer. This study sought to evaluate how prior malignancy impacts the survival of patients with metastatic colorectal cancer (mCRC). Patients diagnosed with stage IV mCRC (per the American Joint Committee on Cancer [AJCC] 6th edition) between 2004 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Those without a prior history of malignancy were assigned to the control group, whereas those with a prior history of malignancy were assigned to the research group. Propensity score matching (PSM) was utilized to ensure that the baseline characteristics were balanced. The Kaplan‒Meier method was used for survival analysis, as were the multivariate Cox proportional hazard model and multivariate competing risk model. The PSM analysis included 54365 eligible patients with mCRC. Among them, 4,845 (8.9%) had a history of prior malignancy. A history of prior malignancy was associated with a greater cancer-specific survival rate (adjusted hazard ratio (AHR) ) = 0.49; 95% CI [0.47–0.51]). Subgroup analyses revealed that a prior diagnosis of a skin tumour (AHR = 1.37; 95% CI [1.11–1.69]) and a history of prior malignancy of more than five years (AHR = 1.39; 95% CI [1.23–1.57]) had adverse effects on the clinical outcomes of patients with mCRC. Our findings suggest that patients with a prior malignancy diagnosis may experience prolonged survival. Subgroup analysis indicated that a malignancy diagnosed more than 5 years ago may adversely impact the clinical outcomes of patients with mCRC. Therefore, we advocate for active standardized treatment for these patients and propose expanding the range of prior malignancies included in clinical trials based on publication timelines, primary tumour locations, and genetic testing results. The objective is to facilitate timely and proactive treatment for patients following the disclosure of results, thereby instilling confidence in the management of mCRC.

Multi-Skin disease classification using hybrid deep learning model

Among the many cancers that people face today, skin cancer is among the deadliest and most dangerous. As a result, improving patients’ chances of survival requires skin cancer to be identified and classified early. Therefore, it is critical to assist radiologists in detecting skin cancer through the development of Computer Aided Diagnosis (CAD) techniques. The diagnostic procedure currently makes heavy use of Deep Learning (DL) techniques for disease identification. In addition, skin lesion extraction and improved classification performance are achieved through Region Growing (RG) based segmentation. At the outset of this study, noise is reduced using an Adaptive Wiener Filter (AWF), and hair is removed using a Maximum Gradient Intensity (MGI). Then, the best RG, which is the result of integrating RG with the Modified Honey Badger Optimiser (MHBO), does the segmentation. Finally, several forms of skin cancer are classified using the DL model MobileSkinNetV2. The experiments were conducted on the ISIC dataset and the results show that the accuracy and precision were improved to 99.01% and 98.6%, respectively. In comparison to existing models, the experimental results show that the proposed model performs competitively, which is great news for dermatologists treating cancer.

DeepMelaNet: Advancing Melanoma Stage Classification in Skin Cancer Diagnosis

Melanoma skin cancer is a global public health threat due to its increasing rates and the possibility of severe outcomes if not adequately addressed. Melanoma is caused by ultraviolet radiation and, among its two stages, malignant is more dangerous than benign. The diagnosis of melanoma is typically based on visual inspection and manual methods carried out by experienced physicians. However, this method is usually slow and has a high probability of error. Deep-learning-based models can offer better and low-cost treatments for people with melanoma. This study aimed to develop a deep-learning model to classify melanoma skin cancer in its early stages. This study presents a modified deep-learning model, named DeepMelaNet, to correctly classify skin cancer images as benign or malignant. The proposed classifier achieved an accuracy of 93.40%, a precision of 98%, a recall of 94%, and an F1 score of 93% on a dataset of 10,000 melanoma skin cancer images, offering a practical solution that can help healthcare professionals in early skin cancer prediction.

CD44-targeted hyaluronic acid coated imiquimod lipid nanocapsules foster the efficacy against skin cancer: Attempt to conquer unfavorable side effects.

This study was executed to mitigate imiquimod (IMQ)-side effects and promote its anticancer potential against skin cancer via encapsulation in hyaluronic acid-coated lipid nanocapsules (HA-LNCs) for targeted topical delivery. The LNCs were prepared using the phase inversion technique. Optimized LNCs formulation was gained following 22 factorial design experiment to adjust the IMQ and CTAB concentrations. The two variables were found to significantly influence the dependent responses. The encapsulation efficiency of IMQ exceeded 97%. HA coating provided a sustained release of IMQ from LNCs, with 63.81±2.45% of IMQ released after 24h. Moreover, the ex-vivo human skin permeation study showed that 7.9-fold more IMQ was localized in all skin layers than that permeated. In vitro anticancer activity indicated that IMQ-HA-LNCs had higher cytotoxicity (IC50=22.39μg/mL) compared to free IMQ (IC50=97.94μg/mL). Further, in vivo studies revealed that encapsulation of IMQ in HA-LNCs enhanced its immunostimulatory potential and promoted its anti-tumor activity in competing skin cancer even in low doses compared to the untreated group and group treated with a brand product with no topical or systemic toxicity. The present study suggested that HA-LNCs with their mixed polymeric/lipophilic nature epitomize a promising strategy for safe topical delivery of poorly water-soluble candidates.

Inflammation-reducing thermosensitive hydrogel with photothermal conversion for skin cancer therapy.

Photothermal therapy (PTT) has widely been utilized for postoperative treatment of skin cancer, while high temperature, usually >50°C, would induce damage to healthy tissue and increased wound inflammation. Herein, we developed an "all in one" hydrogel to enhance mild PTT for postoperative skin cancer treatment while circumventing photothermo-induced inflammation by loading quercetin (Que)-coated tannin‑iron (TA-Fe) nanoparticles with poly (N-acrylylglycine) amine (PNAGA) hydrogel (Que@TA-Fe@PNAGA). Exposure to near-infrared light, Que.@TA-Fe@PNAGA occurred a mild temperature increase (∼47°C), which induces local mild PTT and disrupts the hydrogen bonds within the hydrogel, triggering a gel-to-sol phase transition and the release of Que.@TA-Fe nanoparticles. These released nanoparticles inhibit the expression of heat shock proteins in tumor cells by producing reactive oxygen species and enter inflammatory cells to release TA and Que. via acid hydrolysis, reducing tumor necrosis factor-α expression by 66.6% and promoting M1-to-M2 macrophage conversion. Based on this integrated functionality, Que.@TA-Fe@PNAGA hydrogel achieves over 99.4% tumor inhibition rate, effectively avoids photothermo-induced damage in normal tissue and inflammation, and thus represents a new approach for postoperative photothermal therapy in skin cancer treatment.

Deep learning for skin melanoma classification using dermoscopic images in different color spaces

Skin cancer begins in the skin cells. The damage to the skin cells can cause genetic mutations that lead to uncontrolled growth and the formation of tumors. It is estimated that millions of people are diagnosed with skin cancer of different kinds each year. The earlier a skin cancer is diagnosed, the better the patient's prognosis and the lower their chance of complications. In this work, an efficient deep learning classification (EDLCS) to classify dermoscopic images is developed. The importance of color in the diagnosis of skin melanoma has caused color analysis to attract considerable attention from researchers of image-based skin melanoma analysis. Three different color spaces such as red-green-blue (RGB), hue-saturation-lightness (HIS) and LAB are investigated in this study. The obtained dermoscopic images are in RGB color space. The RGB dermoscopic images are first converted into HSV and LAB spaces to investigate the HSV and LAB color spaces for melanoma classification. Then, the color space converted image is fed to the proposed EDLCS to evaluate their performances. Results show that the proposed EDLCS provides 99.58% accuracy while using the LAB color model to classify preprocessed images while other models provide 99.17%.

Antitumoral effectiveness and safety of intravenous versus subcutaneous administration of immunomodulatory peptide GK-1 in a murine breast cancer model.

GK-1 is a safe and effective molecule with high antimetastatic activity against murine breast and skin cancer. GK-1 treatment enhances cytotoxic response of CD8+ lymphocytes against the tumor and modifies the oxidative stress in the tumor. This study was designed to compare the antitumor efficacy of GK-1 by subcutaneous (SC) versus intravenous (IV) route of administration in the 4T1 mouse mammary carcinoma model and to extend its innocuity in heart and kidney, key tissues for observing damage induced by anticancer drugs and immunotherapy. BALB/c female mice were injected orthotopically with 1000 4T1 cells. When palpable primary tumors of about 1mm3 were detected, GK-1 (5mg/kg) was administered IV or SC weekly for 21days. Tumor growth and mouse weight were monitored weekly. The primary tumor weight and volume, the number of lung metastases, and programmed cell death protein 1 (PD-1) expression were recorded after 28days of starting treatment. Kidney, heart, spleen, serum, and blood samples from naïve mice were obtained to evaluate the safety of GK-1 administration by measuring the degree of damage to these tissues with specific cytotoxic markers. Subcutaneous or intravenous administration of GK-1 significantly increased the lifespan of mice and significantly reduced the primary tumor weight and volume and the number of lungs macrometastases. GK-1 reduced the expression of PD-1 in tumor-infiltrating lymphocytes in mice regardless of the route of immunization used, which is especially encouraging. No evidence of damage to kidney or heart tissues was detected in the tumor-free mice. This study supports that subcutaneous GK-1 administered, has an efficacy non-inferior to intravenous administration, well-tolerated with a similar safety profile and therefore offers a less invasive valid treatment alternative.

A human skin-on-a-chip platform for microneedling-driven skin cancer treatment.

Skin-on-a-chip models provide physiologically relevant platforms for studying diseases and drug evaluation, replicating the native skin structures and functions more accurately than traditional 2D or simple 3D cultures. However, challenges remain in creating models suitable for microneedling applications and monitoring, as well as developing skin cancer models for analysis and targeted therapy. Here, we developed a human skin/skin cancer-on-a-chip platform within a microfluidic device using bioprinting/bioengineering techniques. The fabricated skin models include vascular, dermal, and epidermal layers, demonstrating increased functionalities and maturation of dermal (Collagen I & Fibronectin for 7 days) as well as epidermal (Filaggrin & Keratin 10, 14, and 19at the air-liquid interface (ALI) for 21 days) layers. Histological analysis confirmed the formation of a differentiated epidermis and ridges at the dermal-epidermal junction in our model, closely resembling native skin tissue. Melanoma cells were embedded approximately 400μm beneath the epidermis to simulate tumor invasion into the dermis. The platform was further used to test doxorubicin (DOX)-loaded gelatin methacryloyl (GelMA) microneedles (MNs) for localized transdermal drug delivery targeting melanoma. The DOX-loaded MNs penetrated uniformly to a depth of approximately 600μm, effectively reaching the melanoma cells. Drug delivery via MNs demonstrated significantly higher efficiency than diffusion through media flow, confirming the practicality and robustness of the proposed model for future therapeutic applications.