Search

Background: Histopathological classification of basal cell carcinoma (BCC) has important prognostic and therapeutic implications, but reproducibility of BCC subtyping among dermatopathologists is poor. Objectives: To obtain a consensus paper on BCC classification and subtype definitions. Methods: A panel of 12 recognized dermatopathologists (G12) from nine European countries used a modified Delphi method and evaluated 100 BCC cases uploaded to a website. The strategy involved five steps: (I) agreement on definitions for WHO 2018 BCC subtypes; (II) classification of 100 BCCs using the agreed definitions; (III) discussion on the weak points of the WHO classification and proposal of a new classification with clinical insights; (IV) re‐evaluation of the 100 BCCs using the new classification; and (V) external independent evaluation by 10 experienced dermatopathologists (G10). Results: A simplified classification unifying infiltrating, sclerosing, and micronodular BCCs into a single "infiltrative BCC" subtype improved reproducibility and was practical from a clinical standpoint. Fleiss' κ values increased for all subtypes, and the level of agreement improved from fair to moderate for the nodular and the unified infiltrative BCC groups, respectively. The agreement for basosquamous cell carcinoma remained fair, but κ values increased from 0.276 to 0.342. The results were similar for the G10 group. Delphi consensus was not achieved for the concept of trichoblastic carcinoma. In histopathological reports of BCC displaying multiple subtypes, only the most aggressive subtype should be mentioned, except superficial BCC involving margins. Conclusions: The three BCC subtypes with infiltrative growth pattern, characteristically associated with higher risk of deep involvement (infiltrating, sclerosing, and micronodular), should be unified in a single group. The concise and encompassing term "infiltrative BCCs" can be used for these tumors. A binary classification of BCC into low‐risk and high‐risk subtypes on histopathological grounds alone is questionable; correlation with clinical factors is necessary to determine BCC risk and therapeutic approach. [ABSTRACT FROM AUTHOR]

Background: The umbilicus is a fibrous remnant located in the centre of the abdomen. Various entities may be encountered in this special anatomical location; however, little is known about their dermoscopic presentation. The aim of this study was to provide a comprehensive summary of existing evidence on dermoscopic features of umbilical lesions. Methods: Studies assessing dermoscopic images of umbilical lesions were included in this study. No age, ethnicity or skin phototype restrictions were applied. Papers assessing lesions outside of the umbilical area, lacking dermoscopic images and/or dermoscopic description and not related to the topic were excluded. Embase, Medline and Cochrane Library were searched from inception to the end of May 2023. The Joanna Briggs Institute critical appraisal tools were used to evaluate the risk of bias of the selected studies. The quality and the level of evidence of included studies were assessed according to the Oxford 2011 Levels of Evidence. Thirty-four studies reporting a total of 39 lesions met the inclusion criteria and were included in qualitative analysis. Results: A qualitative synthesis of the following entities was performed: melanoma, nevi, basal cell carcinoma, fibroepithelioma of Pinkus, Sister Mary Joseph nodule, mycosis fungoides, dermatofibroma, endometriosis, epidermal cyst, granuloma, intravascular papillary endothelial hyperplasia, lichen planus, omphalolith, seborrheic keratosis, and syringoma. Conclusions: Dermoscopy is a non-invasive technique that may be useful in the differential diagnosis of umbilical lesions. The main limitations of this study were lack of a high level of evidence in the studies and the lack of uniformity in applied dermoscopic terminology between included studies. [ABSTRACT FROM AUTHOR]

Non-melanoma skin cancers (NMSC) form the majority of skin cancers, with basal cell carcinoma (BCC) being the most common and cutaneous squamous cell carcinoma (cSCC) being second. Prolonged ultraviolet (UV) exposure, aging, male gender, and immunosuppression represent most of the causes of this category of diseases. BCCs and cSCCs both include different types of skin cancers, such as nodular or morpheaform BCC or flat cSCC. Locally advanced and metastatic NMSCs cannot be treated surgically; thus, systemic therapy (TKI and Immunotherapy) is needed. Interestingly, NMSCs are frequently linked to abnormal Hedgehog (HH) signaling which most systemic immunotherapies for these cancers are based upon. Of note, the first line therapies of BCC, sonidegib and vismodegib, are HH inhibitors. Programmed death receptor 1 antibody (PD-1) inhibitors such as cemiplimab, pembrolizumab, and nivolumab have been approved for the treatment of cSCC. Thus, this paper reviews the epidemiology, risk factors, clinical features, and treatment options for both BCC and cSCC. [ABSTRACT FROM AUTHOR]

A subset of patients with Lynch Syndrome demonstrates cutaneous manifestations of the disorder. Characterization of these Lynch-related skin lesions could help in early recognition of patients with Lynch Syndrome. A broad search of the literature on OVID Medline and Embase was carried out to capture papers reporting cutaneous manifestations in Lynch Syndrome patients. The results were uploaded into Mendeley reference management software. The PRISMA workflow was used in the literature selection process. In this systematic review, data were collected from 961 cases from 413 studies, including 380 molecularly confirmed Lynch Syndrome cases. The main skin lesions were: Sebaceous adenomas (43%), sebaceous carcinomas (27%), keratoacanthomas (16%), sebaceomas (13%), squamous cell carcinomas (23%), and basal cell carcinomas (10%). MSH2 variants were the most common underlying genotype (72%). Assessment of mismatch repair by immunohistochemistry, microsatellite instability analysis, or both were performed on 328 skin lesions from 220 (58%) molecularly confirmed cases. In those skin lesions, 95% of Immunohistochemistry and 90% of the microsatellite instability test results were concordant with the underlying genotype. Sebaceous skin lesions are well-recognised phenotypic features of Lynch Syndrome. Our results show that squamous and basal cell carcinomas are relatively common in patients with Lynch syndrome; however, available evidence cannot confirm that Lynch syndrome is causal. Immunohistochemistry and/or microsatellite instability testing of skin tumours in patients with a family history of Lynch Syndrome-associated cancers may be a useful approach in identifying patients requiring referral to Clinical Genetics and/or consideration of germline genetic testing for Lynch Syndrome. [ABSTRACT FROM AUTHOR]

The paper presents recommendations concerning the surveillance of patients after the treatment of squamous-cell carcinoma (SCC), basal-cell carcinoma (BCC) and Merkel-cell carcinoma (MCC) based on the current European and American recommendations. This overview discusses the methodology and detailed recommendations concerning the post-treatment surveillance, with special attention to the clinical examination, dermatoscopy, imaging diagnostics and patient education. The recommendations emphasise the significance of early monitoring for recurrences, and early detection of new skin cancers, adapted to individual risk factors in a patient and the characteristics of primary cancer. Also the significance of patient education, with regards to the protection against sun radiation and the role of skin self-examination are stressed. [ABSTRACT FROM AUTHOR]

Simple Summary: Skin cancers are common and sometimes difficult to diagnose malignancies that occur worldwide. Most skin cancers are diagnosed by visual assessment of patient samples obtained through biopsy. However, due to the lack of well-defined malignancy features, the diagnosis and classification of skin cancer lesions remain difficult in some cases. To overcome this issue, researchers have attempted to use molecular information such as genes and proteins and imaging data to improve skin cancer diagnosis and classification. Therefore, this paper reviews the recent advancements in large-scale molecular profiling approaches and appraises their limitations and potential for reliable and reproducible classification and stratification of skin cancers. Skin cancers are common and heterogenous malignancies affecting up to two in three Australians before age 70. Despite recent developments in diagnosis and therapeutic strategies, the mortality rate and costs associated with managing patients with skin cancers remain high. The lack of well-defined clinical and histopathological features makes their diagnosis and classification difficult in some cases and the prognostication difficult in most skin cancers. Recent advancements in large-scale "omics" studies, including genomics, transcriptomics, proteomics, metabolomics and imaging-omics, have provided invaluable information about the molecular and visual landscape of skin cancers. On many occasions, it has refined tumor classification and has improved prognostication and therapeutic stratification, leading to improved patient outcomes. Therefore, this paper reviews the recent advancements in omics approaches and appraises their limitations and potential for better classification and stratification of skin cancers. [ABSTRACT FROM AUTHOR]

Background and Objective. Skin cancer is the most common cancer worldwide. One of the most common non-melanoma tumors is basal cell carcinoma (BCC), which accounts for 75% of all skin cancers. There are many benign lesions that can be confused with these types of cancers, leading to unnecessary biopsies. In this paper, a new method to identify the different BCC dermoscopic patterns present in a skin lesion is presented. In addition, this information is applied to classify skin lesions into BCC and non-BCC. Methods. The proposed method combines the information provided by the original dermoscopic image, introduced in a convolutional neural network (CNN), with deep and handcrafted features extracted from color and texture analysis of the image. This color analysis is performed by transforming the image into a uniform color space and into a color appearance model. To demonstrate the validity of the method, a comparison between the classification obtained employing exclusively a CNN with the original image as input and the classification with additional color and texture features is presented. Furthermore, an exhaustive comparison of classification employing different color and texture measures derived from different color spaces is presented. Results. Results show that the classifier with additional color and texture features outperforms a CNN whose input is only the original image. Another important achievement is that a new color cooccurrence matrix, proposed in this paper, improves the results obtained with other texture measures. Finally, sensitivity of 0.99, specificity of 0.94 and accuracy of 0.97 are achieved when lesions are classified into BCC or non-BCC. Conclusions. To the best of our knowledge, this is the first time that a methodology to detect all the possible patterns that can be present in a BCC lesion is proposed. This detection leads to a clinically explainable classification into BCC and non-BCC lesions. In this sense, the classification of the proposed tool is based on the detection of the dermoscopic features that dermatologists employ for their diagnosis. [ABSTRACT FROM AUTHOR]

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound. Using diffuse reflectance spectroscopy, the coefficients of melanin pigmentation, erythema, hemoglobin content, and the slope coefficient of diffuse reflectance spectroscopy in the wavelength range 650–800 nm were determined. Statistical texture analysis of optical coherence tomography images was used to calculate first- and second-order statistical parameters. The analysis of ultrasound images assessed the shape of the tumor according to parameters such as area, perimeter, roundness and other characteristics. Based on the calculated parameters, a machine learning algorithm was developed to differentiate the various clinical forms of basal cell carcinoma. The proposed algorithm for classifying various forms of basal cell carcinoma and benign neoplasms provided a sensitivity of 70.6 ± 17.3%, specificity of 95.9 ± 2.5%, precision of 72.6 ± 14.2%, F1 score of 71.5 ± 15.6% and mean intersection over union of 57.6 ± 20.1%. Moreover, for differentiating basal cell carcinoma and benign neoplasms without taking into account the clinical form, the method achieved a sensitivity of 89.1 ± 8.0%, specificity of 95.1 ± 0.7%, F1 score of 89.3 ± 3.4% and mean intersection over union of 82.6 ± 10.8%. [ABSTRACT FROM AUTHOR]

Among various types of skin diseases, skin cancer is the deadliest form of the disease. This paper classifies seven types of skin diseases: Actinic keratosis and intraepithelial carcinoma, Basal cell carcinoma, Benign keratosis, Dermatofibroma, Melanoma, Melanocytic type, and Vascular lesions. The primary objective of this paper is to evaluate the performance of these deep learning networks on skin lesion images. The lesion classification is implemented through transfer learning on fourteen deep learning networks: AlexNet, GoogleNet, ResNet50, VGG16, VGG19, ResNet101, InceptionV3, InceptionResNetV2, SqueezeNet, DenseNet201, ResNet18, MobileNetV2, ShuffleNet and NasNetMobile. The dataset used for these experiments are from ISIC 2018 of about 10,154 images. The results show that DenseNet201 performs best with 0.825 accuracy and improves skin lesion classification under multiple diseases. The proposed work shows the various parameters, including the accuracy of all fourteen deep learning networks, which helped build an efficient automated classification model for multiple skin lesions. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of basal cell carcinoma (BCC) is based on clinical and dermoscopical features. In uncertain cases, innovative imaging techniques, such as reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), have been used. The main limitation of these techniques is the inability to study deep margins. HFUS (high‐frequency ultrasound) and the most recent UHFUS (ultra‐high‐frequency ultrasound) have been used in various applications in dermatology, but they are not yet routinely used in the diagnosis of BCC. A key point in clinical practice is to find an imaging technique that can help to reduce post‐surgical recurrences with a careful presurgical assessment of the lesional margins. This technique should show high sensitivity, specificity, reproducibility and simplicity of execution. This concept is very important for the optimal management of patients who are often elderly and have many comorbidities. The aim of the paper is to analyse the characteristics of current imaging techniques and the studies in the literature on this topic. Materials and methods: The authors independently searched the MEDLINE, PubMed, Embase, Scopus, ScienceDirect and Cochrane Library databases for studies looking for non‐invasive imaging techniques for the presurgical margin assessment of BCC. Results: Preoperative study of the BCC subtype can help to obtain a complete excision with free margins. Different non‐invasive imaging techniques have been studied for in vivo evaluation of tumour margins, comparing the histologic evaluation with a radical surgery. The possibility to study the lateral and deep margins would allow a reduction of recurrences and sparing of healthy tissue. Conclusion: HFUS and UHFUS represent the most promising, non‐invasive techniques for the pre‐operative study of BCC facilitating the characterization of vascularization, deep lateral margins and high‐risk subtypes, although they are limited by insufficient literature unlike RCM and OCT. [ABSTRACT FROM AUTHOR]

Deficiency of adenosine deaminase-2 (DADA2) is an autosomal recessive autoinflammatory disease with an extremely variable disease presentation. This paper provides a comprehensive overview of the Dutch DADA2 cohort. We performed a retrospective cohort study in 29 ADA2-deficient patients from 23 families with a median age at inclusion of 26 years. All patients had biallelic pathogenic variants in the ADA2 gene. The most common clinical findings included cutaneous involvement (79.3%), (hepato)splenomegaly (70.8%) and recurrent infections (58.6%). Stroke was observed in 41.4% of the patients. The main laboratory abnormalities were hypogammaglobulinemia and various cytopenias. Patients presented most often with a mixed phenotype involving vasculopathy, immunodeficiency and hematologic manifestations (62.1%). In this cohort, malignancies were reported in eight patients (27.6%), of whom five presented with a hematologic malignancy and two with a basal cell carcinoma. Four patients developed hemophagocytic lymphohistiocytosis (HLH) or an HLH-like episode, of whom three passed away during or shortly after the occurrence of HLH. TNF-inhibitors (TNFi) were effective in treating vasculopathy-associated symptoms and preventing stroke, but were hardly effective in the treatment of hematologic manifestations. Three patients underwent hematopoietic cell transplantation and two of them are doing well with complete resolution of DADA2-related symptoms. The overall mortality in this cohort was 17.2%. In conclusion, this cohort describes the clinical, genetic and laboratory findings of 29 Dutch DADA2 patients. We describe the occurrence of HLH as a life-threatening disease complication and report a relatively high incidence of malignancies and mortality. [ABSTRACT FROM AUTHOR]

In this paper, a novel 8-shaped resonator coupled to metal–insulator–metal waveguides is used for designing plasmonic filters and sensors. The resonator supports two resonance modes, which result in peaks in the transmission spectrum of the structure. A Q-factor of 247.4 which can reach up to 270 at the wavelength of 1187.5 nm is observed. By placing vertical and horizontal metal blades in the resonator, two tunable single-mode plasmonic filters are obtained at the first and second resonance modes, respectively. The effect of structural parameters on the transmission spectrum is investigated using the finite-difference time-domain (FDTD) method. Based on the obtained results, the proposed plasmonic structure can be used for biosensing applications such as the detection of basal cancer cells with a sensitivity of 1200 nm/RIU. It is of great significance that both the sensitivity and Q-factor values for the proposed structure are higher than most recent sensors reported in the literature. Therefore, the proposed structure is a potentially promising candidate for filtering and sensing applications. [ABSTRACT FROM AUTHOR]

Although melanoma accounts for only 5.3% of skin cancer, it results in >75% of skin-cancer-related deaths. To avoid disfiguring surgeries on the head and neck associated with surgical excision, there is a clear unmet need for other strategies to selectively remove cutaneous melanoma lesions. Mohs surgery is the current treatment for cutaneous melanoma lesions and squamous and basal cell carcinoma. While Mohs surgery is an effective way to remove melanomas in situ, normal tissue is also excised to achieve histologically negative margins. This paper describes a novel combination therapy of nonthermal plasma (NTP) which emits a multitude of reactive oxygen species (ROS) and the injection of a pharmaceutical agent. We have shown that the effects of NTP are augmented by the DNA-damaging prodrug, tirapazamine (TPZ), which becomes a free radical only in conditions of hypoxemia, which is often enhanced in the tumor microenvironment. In this study, we demonstrate the efficacy of the combination therapy through experiments with B16-F10 and 1205 Lu metastatic melanoma cells both in vitro and in vivo. We also show the safety parameters of the therapy with no significant effects of the therapy when applied to porcine skin. We show the need for the intratumor delivery of TPZ in combination with the surface treatment of NTP and present a model of a medical device to deliver this combination therapy. The importance of functional gap junctions is indicated as a mechanism to promote the therapeutic effect. Collectively, the data support a novel therapeutic combination to treat melanoma and the development of a medical device to deliver the treatment in situ. [ABSTRACT FROM AUTHOR]

Many patient-reported outcome measures (PROMs) have been used to study quality of life (QOL) in the skin cancer population. Advanced melanoma and non-melanoma skin cancer (NMSC) may be associated with increased morbidity, mortality, and treatment side effects; however, it is unclear which PROM is valid and appropriate to use in these populations for both clinical and research purposes. We aimed to identify the PROMs that have been used to measure QOL in advanced skin cancer patients and determine which of these PROMs have been validated to assess QOL outcomes in this population. A PubMed and EMBASE search was conducted from its inception to March 2021 according to PRISMA guidelines with a comprehensive list of search terms under three main topics: (1) PROM; (2) advanced skin cancer; and (3) staging and interventions. We included articles utilizing a PROM measuring QOL and having a patient population with advanced skin cancer defined as melanoma stage > T1a or non-melanoma AJCC stage T3 or greater. Advanced skin cancer patients were also defined as those with metastasis or requiring adjuvant therapy (systemic chemotherapy, radiation, and immunotherapy). Studies were excluded according to the following criteria: mix of low-risk and advanced skin cancer patients in the study population without stratification into low-risk and advanced groups, stage T1a melanoma or mix of stages without stratification, low-risk NMSC, no PROM (i.e., study specific questionnaires), non-English publication, review article or protocol paper, conference abstract, or populations including non-skin cancers. A total of 1,998 articles were identified. 82 met our inclusion criteria resulting in 22 PROMs: five generic health-related (QWB-SA, AQoL-8D, EQ-5D, SF-36, and PRISM), six general cancer (EORTC QLQ-C30, EORTC QLQ-C36, LASA, IOC, Rotterdam Symptom Checklist, and FACT-G), nine disease-focused or specialized (EORTC QLQ-H&N35, EORTC QLQ-MEL38, EORTC QLQ-BR23, Facial Disability Index, FACT-H&N, FACT-BRM, FACT-B, FACT-M, and scqolit), and two general dermatology (Skindex-16 and DLQI) PROMs. All PROMs have been generally validated except for EORTC QLQ-MEL38. Only two PROMs have been validated in the advanced melanoma population: FACT-M and EORTC QLQ-C36. No PROMS have been validated in the advanced NMSC population. The PROMs that were validated in the advanced melanoma population do not include QOL issues unique to advanced skin tumors such as odor, bleeding, itching, wound care burden, and public embarrassment. Breast cancer and head and neck cancer instruments were adapted but not validated for use in the advanced skin cancer population due to the lack of an adequate instrument for this population. This study highlights the need for PROM instrument validation or creation specifically geared toward the advanced skin cancer population. Future studies should aim to develop and validate a PROM to assess QOL in this population. [ABSTRACT FROM AUTHOR]

Introduction: Gorlin- Goltz syndrome is an inherited autosomal dominant disorder. This shows a high level of penetrance and variable expressiveness. Early diagnosis of this syndrome is important for counseling of patients to prevent harmful exposure to Ultra-Violet and ionizing radiations that increase the risk of developing Basal Cell Carcinoma. Presentation of Case: A 18 years old male patient came with chief complaint of swelling in lower front region of jaw. Clinical examination done. Orthopantomograph revealed multiple multi-locular, well-defined radiolucency with sclerotic border located in maxilla and mandible. Relevant investigations were done including chest X-ray, Computed Tomography scan and Histopathological examination revealed presence of Gorlin- goltz syndrome. Discussion: The Gorlin-Goltz syndrome is manifested by multiple defects involving the skin, nervous system, eyes, endocrine system, and bones. The presence of two major and one minor or one major and three minor criteria are necessary to establish diagnosis. The present reported case of Gorlin-Goltz syndrome fulfilled 3 major and 1 minor criteria. Conclusion: In the treatment of recurrent Odontogenic Keratocyst, associated with Gorlin- goltz syndrome, the overlying surface epithelium should be excised along with the cystic lining to prevent recurrence. This paper focus on the importance of oral and maxillofacial health professionals in the early diagnosis of Gorlin-Goltz syndrome and in a multidisciplinary approach to provide a better prognosis to the patient. [ABSTRACT FROM AUTHOR]

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Goltz-Gorlin syndrome, also known as focal dermal hypoplasia or nevoid basal cell carcinoma syndrome, is a rare multisystemic disease caused by autosomal dominant mutations in the PORCN gene. The characterizing features are keratocystic odontogenic tumors in the jaw, multiple basal cell carcinomas, calcification of the falx cerebri, palmar or plantar pits, and skeletal abnormalities. This paper reports the case of a 3-yearold girl with Goltz-Gorlin syndrome, showing progressively increasing tonsillar hypertrophy with obstructive effect on the oropharynx. The lymphatic tissue was remarkably papillomatous in aspect. Pathologic examination after tonsillectomy showed hyperplastic, morphologically normal tonsillar tissue, without arguments for papilloma, active inflammation, or malignancy. This paper highlights the rare manifestations of ENT pathologies in GGS which demand attention early on and long-term follow-up. [ABSTRACT FROM AUTHOR]

Basal Cell Carcinoma (BCC) is the most frequent skin cancer and its increasing incidence is producing a high overload in dermatology services. In this sense, it is convenient to aid physicians in detecting it soon. Thus, in this paper, we propose a tool for the detection of BCC to provide a prioritization in the teledermatology consultation. Firstly, we analyze if a previous segmentation of the lesion improves the ulterior classification of the lesion. Secondly, we analyze three deep neural networks and ensemble architectures to distinguish between BCC and nevus, and BCC and other skin lesions. The best segmentation results are obtained with a SegNet deep neural network. A 98% accuracy for distinguishing BCC from nevus and a 95% accuracy classifying BCC vs. all lesions have been obtained. The proposed algorithm outperforms the winner of the challenge ISIC 2019 in almost all the metrics. Finally, we can conclude that when deep neural networks are used to classify, a previous segmentation of the lesion does not improve the classification results. Likewise, the ensemble of different neural network configurations improves the classification performance compared with individual neural network classifiers. Regarding the segmentation step, supervised deep learning-based methods outperform unsupervised ones. [ABSTRACT FROM AUTHOR]

Skin cancer is one of the most common cancers, and its early detection can have a huge impact on its outcomes. Deep learning, especially convolutional neural networks, performs well in processing massive amounts of data, especially image data in classifying skin cancer. In this paper, convolutional neural networks are mainly used to diagnose and classify 7 types of skin lesions, including melanoma, basal cell carcinoma, melanocytic nevus, actinic keratosis, intraepithelial carcinoma, benign keratinoid lesions, dermatofibroma, and vascular lesions. First, the characteristics of skin lesion images are analyzed, using image processing technology and sampling technology to preprocess skin lesion images. Then the training parameters of imageNet network are adjusted through the idea of transfer learning on InceptionV3, ResNet50, DenseNet201, and other networks to perform training classification. Furthermore, different convolutional neural network models are built for classification. In order to validate the classification performance of various convolutional neural network models, this paper adopts ISIC 2017 HAM10000 dataset for experiments. The experimental results show that proper preprocessing is necessary when applying CNN for image classification. In classifying the 224*224 skin lesion images, the classical deep convolutional network with DenseNet201 achieved a remarkable performance classification accuracy of 99.12% for training and 86.91% for testing. [ABSTRACT FROM AUTHOR]

Treatment with Hedgehog Inhibitors in Gorlin‐Goltz syndrome (GGS) yields favourable objective clinical responses, yet secondary resistance and class‐related toxicity restrict treatment duration. This study aims to review current data on GGS patients undergoing vismodegib therapy, focusing on treatment duration, clinical outcomes and schedule modifications. A systematic search of the PubMed database was conducted for English articles from 1993 to 2023, identifying 31 papers suitable for inclusion. A total of 351 patients, with a mean age of 52 years, were analysed. The average treatment duration was 9.3 months for patients who discontinued treatment, and 25.1 months for those who continued vismodegib at the time this study was published. Vismodegib achieved a complete response rate of 44%. Treatment interruption predominantly occurred due to side effects (69.1%) and secondary resistance (9.1%). The use of alternative regimens, although not compromising efficacy, may enhance treatment compliance. Further investigations are warranted to ascertain the optimal treatment regimen and timeline for GGS patients. Schedule modifications offer promise in ameliorating side effects and facilitating long‐term treatment. [ABSTRACT FROM AUTHOR]

The article discusses the challenges and potential benefits of Mohs micrographic surgery (MMS) in India for the treatment of certain types of skin cancer. While MMS is gaining popularity as an effective treatment option, there are obstacles to its widespread adoption, including limited access to specialized centers, cost considerations for patients, and the need for continued training and education among healthcare professionals. The article suggests that as awareness increases and infrastructure improves, MMS is likely to become more widely available and accepted as a standard of care for appropriate cases of skin cancer in India. [Extracted from the article]

INTRODUCTION The relationship between tobacco smoking and cutaneous photodamage or malignancies is still unclear. In addition to smoking, both ultraviolet radiation and immunosuppression have an impact on carcinogenesis. The purpose was to study the association of smoking with cutaneous photoaging, actinic keratosis (AK), skin cancers, and pigment cell nevi in adult subjects at risk of any type of skin cancer. METHODS In this cross-sectional study at Kuopio University Hospital, Finland, between May 2017 and October 2020, 488 subjects (aged 21-79 years, 246 males and 242 females, 94 with immunosuppression) were examined for a variety of skin lesions, photoaging severity, nevi, tobacco pack-years (TPY), as well as for possible confounding factors. RESULTS In logistic regression analyses, no marked association was found between TPY and total skin photoaging, facial photoaging, AK, or nevi, especially when other confounding factors, such as age, were considered. In addition, TPY was not associated with melanoma, basal cell carcinoma, or any type of skin cancer. However, ever smokers produced an elevated crude odds ratio (OR=1.99; 95% CI: 1.02-3.88, p=0.043) for squamous cell carcinoma (SCC) compared to non-smokers. In further analysis, TPY of ≤10 produced an elevated multivariable adjusted odds ratio (AOR=4.90; 95% CI: 1.31-18.26, p=0.018) for SCC, but TPY >10 did not (AOR=1.14; 95% CI: 0.22-6.05, p=0.876). CONCLUSIONS Smoking was associated, though not dose-dependently, with an increased likelihood of SCC, but it was not associated with basal cell carcinoma or melanoma. However, the impact of smoking on cutaneous photoaging severity, AK, and nevi, appears to be weak. [ABSTRACT FROM AUTHOR]

Human cancer is the most hazardous sicknesses existing which is principally brought about by hereditary flimsiness of numerous atomic changes. Among the numerous kinds of disease, skin cancer is quite possibly the most widely recognized sorts of malignancy. There are three kinds of skin malignant growth, to be specific, Basal Cell Carcinoma (BCC), Squamous Cell Carcinoma (SCC)and Melanoma, melanoma is the sort of skin cancer which is perilous. The skin cancer detection technology is extensively isolated into four fundamental parts beginning from gathering dermoscopic image data set, dermoscopic image database, image pre-processing which includes hair removal, noise removal, sharpening, resize, contrast stretching of the given skin image, segmentation in which gave for segmenting the zone of interest from the given image. Various methods can be utilized for segmentation. Some regularly utilized division calculations are k-means, thresholding histogram and so on, feature extraction from the portioned picture and grouping of the picture from the feature set separated from sectioned picture. Various classification algorithms are used for this, among which the utilization of machine learning and deep learning-based algorithm are used to improve results for classification. The most frequently utilized classification. algorithms are 'support vector machine', 'feedforward artificial neural network', 'deep convolutional neural network'. This paper provides the two types of skin cancer - Basal Cell Carcinoma and Melanoma and equally threatening (skin) diseases such as Actinic keratosis, Cherry nevus, Dermatofibroma and Melanocytic nevus, and classify them into six different classes using the 'support vector machine (SVM) classifier'. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma of the prostate (BCCP) is a rare tumor with a total incidence of 140 cases to date. However, BCCP with squamous metaplasia has not been reported as of date. In this paper, we report the first case of BCCP with squamous metaplasia. The patient was hospitalized for progressive dyspareunia and had been treated for recurrent urinary retention four times in 5 years. Rectal examination showed that the prostate was medium in texture with no palpable nodules. The levels of total prostate specific antigen (tPSA), free prostate specific antigen (fPSA), and fPSA/tPSA (f/t) ratio were 1.29 ng/mL, 0.4 ng/mL, and 0.31, respectively. Ultrasound of the urinary tract showed that the prostate gland was 51 mm*40 mm*38 mm in size. We performed transurethral resection of the prostate. Histopathology confirmed the diagnosis of basal cell carcinoma with focal squamous differentiation, and immunohistochemical staining was positive for P63 and 34bE12. A laparoscopic radical prostatectomy was performed 45 days after the first surgery and the postoperative pathology showed a small amount of residual tumor with negative margins and no involvement of the seminal vesicles and vas deferens. The patient was followed up for 50 months and was doing well by the end of our study. We describe the clinical symptoms, pathological features, treatment, and prognosis of patients with BCCP with squamous metaplasia. The relevant published literature is also briefly reviewed. [ABSTRACT FROM AUTHOR]

Facial tissue loss is acquired as a result of congenital anomalies or acquisitional misshapen like tumoral lesions or accidents. These defects result in functional problems, esthetic concerns, and also psychosocial troubles and could be repaired by plastic surgery or reconstructed using facial prostheses. Conventional tissue-supported auricular prostheses meet lots of challenges due to dependence on tissue undercut or adhesive for retention. Implant-retained auricular prostheses lessen the complications related to adhesive-retained prostheses and alleviate the need for invasive plastic surgery. Implant-retained auricular prostheses provide patients with secure retention and avoid prosthesis disengagement caused by movable surrounding soft tissue. The impact of prostheses with secured retention and satisfactory esthetics on the self-confidence of patients with facial defects is promising. This paper aimed to describe the surgical and prosthetic workflow of a patient with acquired ear deformity due to basal cell carcinoma (BCC) which was rehabilitated with implant retained auricular prosthesis. [ABSTRACT FROM AUTHOR]

Non-melanoma skin cancer (NMSC) is one of the most frequent types of malignancy in the human body with an increasing incidence. Short, non-coding RNA molecules called microRNAs (miRNAs) can control post-transcriptional gene expression and they have a significant role in several physiological cellular processes and pathologies, including cancer. Depending on the functions of the genes, miRNAs may function as oncogenes or tumor suppressors. The aim of this paper was to describe the role of miRNA-34a and miRNA-221 in head and neck NMSC. Thirty-eight NMSC match paired (tumor and adjacent) tissue samples were evaluated by qRT-PCR. Total RNA was extracted and isolated from tissue samples using the phenol-chloroform (Trireagent) method according to the manufacturer's protocol. The concentration of RNA was measured by a NanoDrop-1000 spectrophotometer. The expression level of each miRNA was calculated by threshold cycle. For all statistical tests, the 0.05 significance level was used and two-tailed p values. All analyses were conducted in an R environment for statistical computing and graphics. We found the miRNA-221 being overexpressed in squamous cell carcinoma (SCC) (p < 0.05), basal cell carcinoma (BCC) and basosquamous cell carcinoma (BSC) compared with adjacent normal tissue. Additionally, the levels of miRNA-221 were two times higher (p < 0.05) in cases where the excision of the tumor was done with positive margins (R1), which means that we are the first to highlight the potential role of miRNA-221 in the microscopical local invasion. Mi-RNA-34a expression was altered in the malignant tissue compared with the adjacent normal one both in BCC and SCC but not statistically significantly. In conclusion, NMSC are challenging because of their increasing incidence and rapidly evolving development and discovering their molecular mechanisms of action lead us to understand tumorigenesis and evolution, while also contributing to the implementation of novel therapeutic keys. [ABSTRACT FROM AUTHOR]

Eyelid tumors are tumors that occur in the eye and its appendages, affecting vision and appearance, causing blindness and disability, and some having a high lethality rate. Pathological images of eyelid tumors are characterized by large pixels, multiple scales, and similar features. Solving the problem of difficult and time-consuming fine-grained classification of pathological images is important to improve the efficiency and quality of pathological diagnosis. The morphology of Basal Cell Carcinoma (BCC), Meibomian Gland Carcinoma (MGC), and Cutaneous Melanoma (CM) in eyelid tumors are very similar, and it is easy to be misdiagnosed among each category. In addition, the diseased area, which is decisive for the diagnosis of the disease, usually occupies only a relatively minor portion of the entire pathology section, and screening the area of interest is a tedious and time-consuming task. In this paper, deep learning techniques to investigate the pathological images of eyelid tumors. Inspired by the knowledge distillation process, we propose the Multiscale-Attention-Crop-ResNet (MAC-ResNet) network model to achieve the automatic classification of three malignant tumors and the automatic localization of whole slide imaging (WSI) lesion regions using U-Net. The final accuracy rates of the three classification problems of eyelid tumors on MAC-ResNet were 96.8%, 94.6%, and 90.8%, respectively. [ABSTRACT FROM AUTHOR]

Kidney transplant recipients (KTR) have a higher risk of developing malignancies compared to the general population, due to the immunosuppressive regimens which can promote the oncogenesis process. The incidence of de novo non-melanoma skin cancer (NMSC) in KTR is greater than in the general population. Basal cell carcinoma (BCC) represents one of the most frequent malignancies in KTR. Sonidegib is a Hedgehog signaling pathway inhibitor approved for the treatment of locally advanced basal-cell carcinoma (LABCC) that following surgery or radiation therapy, or is given to those candidates who are not eligible to surgery or radiation therapy. This paper reports the case of a kidney transplant patient, who developed severe acute kidney injury (AKI) due to rhabdomyolysis (RML) induced by sonidegib therapy which required renal replacement therapy (RRT). [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) is the most common malignancy worldwide. Surgical removal is considered the gold standard treatment. However, large defects following excisional surgery can pose a significant challenge for reconstruction, especially in cases where primary closure is not possible. In these cases, skin flaps may be used. Most traditional skin flaps are limited by design to take advantage of only one region of relative skin excess. This paper reports a case of a large forehead defect following BCC excision that was successfully reconstructed by a modified Hplasty involving a U-plasty and rotation-advancement flap. Maintenance of aesthetics without impaired function is the aim of closure defects with combined flaps. [ABSTRACT FROM AUTHOR]

In recent years, one of the deadliest malignancies is skin cancer. If it is not detected and treated in a timely manner, it is expected to spread to other body parts. An accurate automated system for skin lesion recognition is essential for early detection to save human lives. Although there are many other forms of skin cancer, basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma are the three most prevalent. With early identification and appropriate treatment, these three kinds of skin cancer can be successfully treated by using deep learning techniques. One of the main benefits of using deep learning for skin cancer detection is its ability to accurately classify images with subtle differences. In this paper, Image pre-processing is employed at an initial diagnosis for removing the artifacts present in the raw dataset and further Convolutional Neural Network (CNN) is employed to improve classification and detection of skin cancer with improved accuracy. For analyzing enormous volumes of data, R-CNN algorithms are proved to be incredibly effective in terms of accuracy of 84.32%. Due to its precision, effectiveness, objectivity, and accessibility, R-CNN algorithm have proven to be very helpful in the identification and categorization of skin cancer. [ABSTRACT FROM AUTHOR]

Introduction: Research in mice showed that vitamin D receptor deficiency was correlated with an increased rate of non-melanoma skin cancer. Therapeutic supplemental vitamin D has also been reported to reduce cell growth in both melanoma and non-melanoma skin cancer. This paper aims to describe the existing research studies that discuss the potential and role of vitamin D in the management of skin cancer. Methods: Articles were searched from three databases (PubMed, ScienceDirect, Scopus) and manual search. 18 articles were included. These were further divided into in vivo and in vitro studies. The literature search was based on the following Patients, Intervention, Control, and Outcome (PICO) criteria: Patients with any types of skin cancer; Vitamin D and their derivates as the intervention; placebo or standard regimen as control, and survival rate or response rate as primary outcome. Results: From the three databases, we obtained 802 studies. Prior to screening of the literature obtained, several studies were excluded. In the eligibility assessment, seven studies were excluded due to their outcomes being not eligible for analysis, and two studies were excluded due to inaccessible full texts. The remaining 18 studies were included. Five studies had a clinical research design (randomized controlled trial or interventional study), which use vitamin D3 as vitamin D derivatives and the results showed that the administration of vitamin D3 reduces the proliferation of skin cancer cells. Similar results were also reported in studies with pre-clinical research designs, either in vivo or in vitro, where six were in vivo studies and nine studies were in vitro studies. Conclusion: Our literature review revealed that that vitamin D derivatives, such as 1,25(OH)2D3 or 20(OH)D3 can effectively reduce the proliferation of skin cancer cells by contributing in the inhibition of cell growth and development, highlighting vitamin D's role as good prognostic factor. [ABSTRACT FROM AUTHOR]

Today, basal cancer cells is one of the most frequent diseases on the planet, which is global concern for human health. In order to maximize the success of treatment, early detection is a vital prerequisite. So, a rapid and sensitive detection of cancerous basal cells is a necessary topic. In this paper, a photodetector based on SPR nanostructure consisting prism (N-FK51A), silver (Ag), hybrid organic–inorganic halide perovskites (MAPbX3 ≡ CH3NH3PbY3, with M = CH3, A = NH3 and Y = Br), and graphene layers is suggested theoretically for the detection of cancerous basal cells. It is demonstrated that the proposed photodetector with perovskite has a superior efficiency than the conventional without perovskite. Silver, perovskite, and graphene layers of suggested SPR nanostructure have been optimized to achieve the highest efficiency. The highest reached sensitivity is 298.5 deg/RIU with the optimal thicknesses of Ag (60 nm), MAPbBr3 (3 nm), and the optimal number of graphene layers is equal to three layers. This sensitivity is ultra-high value compared to latest work that utilizes SPR configuration. As a result, the proposed SPR photodetector nominates as a strong candidate for use in several areas of biosensing applications. [ABSTRACT FROM AUTHOR]

Nestin is a protein belonging to class VI intermediate filaments, which is involved in organogenesis, cellular metabolism and cytoskeletal organisation. Originally found to be expressed in neuroepithelial stem cells, nestin is also expressed in other tissues. It plays an important role in the carcinogenesis and angiogenesis. Its increased expression in melanoma is associated with an aggressive course of the disease and poor prognosis. Research findings for nonmelanocytic skin neoplasms are inconclusive. The aim of this paper was to systematize knowledge on the role of nestin in cancerogenesis. The authors focused in particular on the expression of nestin in skin malignancies, as well as on the potential role of nestin in the pathogenesis, prognosis and treatment of cutaneous neoplasms. [ABSTRACT FROM AUTHOR]

With the explosion of advanced Information and Recognition model, primarily the Deep Learning (DL) and Transfer Learning (TL) models, all aspects of recent research have been influenced. The Biomedical image analysis has also been considerably subjective by recent technology involvements, carrying about a pattern shift towards 'automation' and 'error free diagnosis' classification methods with markedly improved accurate diagnosis productivity and cost effectiveness. This paper proposes an automated deep learning model to diagnose the skin disease at early stage by using Dermoscopy images. The complete proposed framework is achieved by evaluating the four pre-trained transfer learning CNN models such as DenseNet121, ResNet50, VGG16 and ResNet18 for classification accuracy on skin dataset images. Also, some pre-processing steps are followed to enhance the accuracy; in addition with various simulation parameters like epochs, batch size and optimizers are studied to find the best model. Analysis is performed with two different batch sizes i.e. 16 and 32 and two different optimizers i.e. Adam and SGD optimizers. The best accuracy is obtained on proposed ResNet50 and ResNet18 model on batch size 32 and SGD optimizer. The best value of accuracy on ResNet50 and ResNet18 model is 90% followed by second best accuracy of 89% on DenseNet121 model. ResNet50 and ResNet18 have obtained sensitivity as 97% and 94% for Melanocytic Nevi disease whereas DenseNet121 model has obtained 94% sensitivity in case of Basal Cell Carcinoma disease. This model can be used for early diagnosis of skin disease and can also act as second opinion tool for dermatologists. [ABSTRACT FROM AUTHOR]

One of the most interesting topics in bio-optics is measuring the refractive index of tissues. Accordingly, two novel optical biosensor configurations for cancer cell detections have been proposed in this paper. These structures are composed of one-dimensional photonic crystal (PC) lattices coupled to two metal–insulator–metal (MIM) plasmonic waveguides. Also, the tapering method is used to improve the matching between the MIM plasmonic waveguides and PC structure in the second proposed topology. The PC lattices at the central part of the structures generate photonic bandgaps (PBGs) with sharp edges in the transmission spectra of the biosensors. These sharp edges are suitable candidates for sensing applications. On the other hand, the long distance between two PBG edges causes that when the low PBG edge is used for sensing mechanism, it does not have an overlapping with the high PBG edge by changing the refractive index of the analyte. Therefore, the proposed biosensors can be used for a wide wavelength range. The maximum obtained sensitivities and FOM values of the designed biosensors are equal to 718.6, 714.3 nm/RIU, and 156.217, 60.1 RIU−1, respectively. The metal and insulator materials which are used in the designed structures are silver, air, and GaAs, respectively. The finite-difference time-domain (FDTD) method is used for the numerical investigation of the proposed structures. Furthermore, the initial structure of the proposed biosensors is analyzed using the transmission line method to verify the FDTD simulations. The attractive and simple topologies of the proposed biosensors and their high sensitivities make them suitable candidates for biosensing applications. [ABSTRACT FROM AUTHOR]

Matthew Alexander I Royal Victoria Infirmary, Newcastle upon Tyne, UK i "The Topol Review" discusses how technology and other developments may be leveraged by clinical staff of the future to improve patient care. This methodology is the first to define TTC in a consultation, identify the metric and measure a difference between TTC in paper-based and EPR-based clinical encounters. Clinicians reduced their TTC to increase NVABN data entry in the EPR. [Extracted from the article]

Nonmelanoma skin cancers (NMSCs) are the most common malignancies worldwide. Millions of new cases every year present challenge to healthcare systems. Recent years brought numerous new data concerning high dose rate (HDR) brachytherapy (BT) as treatment option for NMSCs. International guidelines do not recognize BT as a method of choice given lack of randomized trials, however many prospective and retrospective studies show promising results. Aim of the study was to present the efficacy of HDR BT, with analysis of its safety and adverse effects based on review of the English published medical full‐text papers. Literature review of 13 articles published between 1999 and 2021 was performed. Pubmed and Google Scholar databases were searched on October 2021 using keywords: ([Basal cell carcinoma] OR [squamous cell carcinoma] OR [non‐melanoma skin cancer]) AND (HDR brachytherapy). Fourteen full‐text English articles with follow up over 1 year and study group over 50 patients were included into analysis. In analyzed material, 2403 patients received HDR BT. Local control varied between 71% and 99%.Dominant reported cosmetic effect was good or very good. Results were cross‐referenced with recent meta‐analyses comparing BT to surgical excision, Mohs microsurgery and external beam radiotherapy. Radiodermitis is the main adverse effect of radiation treatment during and after radiotherapy. HDR BT emerges as potentially noninferior treatment method providing very good reported cosmetic outcomes. [ABSTRACT FROM AUTHOR]

The application of artificial intelligence (AI) algorithms in medicine could support diagnostic and prognostic analyses and decision making. In the field of dermatopathology, there have been various papers that have trained algorithms for the recognition of different types of skin lesions, such as basal cell carcinoma (BCC), seborrheic keratosis (SK) and dermal nevus. Furthermore, the difficulty in diagnosing particular melanocytic lesions, such as Spitz nevi and melanoma, considering the grade of interobserver variability among dermatopathologists, has led to an objective difficulty in training machine learning (ML) algorithms to a totally reliable, reportable and repeatable level. In this work we tried to train a fast random forest (FRF) algorithm, typically used for the classification of clusters of pixels in images, to highlight anomalous areas classified as melanoma "defects" following the Allen–Spitz criteria. The adopted image vision diagnostic protocol was structured in the following steps: image acquisition by selecting the best zoom level of the microscope; preliminary selection of an image with a good resolution; preliminary identification of macro-areas of defect in each preselected image; identification of a class of a defect in the selected macro-area; training of the supervised machine learning FRF algorithm by selecting the micro-defect in the macro-area; execution of the FRF algorithm to find an image vision performance indicator; and analysis of the output images by enhancing lesion defects. The precision achieved by the FRF algorithm proved to be appropriate with a discordance of 17% with respect to the dermatopathologist, allowing this type of supervised algorithm to be nominated as a help to the dermatopathologist in the challenging diagnosis of malignant melanoma. [ABSTRACT FROM AUTHOR]

Simple Summary: It is widely known that long-term treatment with immunosuppressive drugs represents a risk factor for the onset of malignancies, including multiple basal cell carcinomas. However, multiple basal carcinomas are ao found in the general population, and even in the absence of specific predisposing genetic mutations. This paper aims, through the retrospective evaluation of all patients diagnosed and surgically treated for basal cell carcinomas during 5 years at our Dermatological Division, to identify the characteristics of these subjects and any possible risk factors, useful for outlining specific surveillance programs. In our experience, multiple carcinomas were identified in over 24% of the subjects analyzed, with several lesions removed, ranging from 2 to 11, confirming the relevance of this phenomenon. Background: The onset of multiple BCCs is a relatively common condition, not only among patients undergoing chronic treatment with immunosuppressant drugs, but also in the general population, although specific risk factors for immunocompetent patients have not been identified. A putative role of somatic mutations in the hedgehog pathway should be considered. Methods: This study is a retrospective observation of all patients diagnosed and surgically treated for BCCs during 5 years at our Dermatological Division. For these patients, we evaluated clinical and histopathological characteristics and data about possible risk factors for BCC. Results: Five-hundred and six patients affected by multiple BCCs, accounting for the 24.2% of the entire sample, have been identified. In these patients, the total number of BCCs was 1516, ranging from 2 to 11. Subjects affected by multiple BCCs were more frequently males, with an older age at diagnosis; multiple BCCs developed mainly on the trunk and were often represented by a nodular histotype. The multivariate analysis highlighted that male gender, older age, nodular BCC, or face involvement at the first diagnosis are risk factors for the development of multiple BCCs. Conclusions: The frequency of multiple BCCs even among the non-immunocompromised population underlines the need to subject patients to a close surveillance program, to allow early diagnosis and treatment of additional cancers. [ABSTRACT FROM AUTHOR]

Skin Cancer classification has been one of the most challenging problems for dermatologists; it is a tremendously tedious process to detect the kind of lesion/cancer form it is for just the human eye. Deep learning has become popular due to its potential to learn complex traits from the huge dataset. A prominent deep learning model for image categorization is the convolutional neural network (CNN). Many researchers have been conducted on the efficiency of CNN's use to classify skin cancer forms. In this paper, the efficiency of VGG bottleneck features and transfer learning have been used on 3 kinds of skin cancers namely, (a) squamous cell carcinoma, (b) basal cell carcinoma and (c) melanoma. The proposed model comprises of VGG-16 NET and Transfer Learning with 2 fullyconnected layers. The proposed model is experimented on 1077 dermoscopy images in total (MSK-1, UDA -1, UDA- 2, HAM10000). The experimental analysis proves that the proposed model achieves higher values for accuracy, specificity and sensitivity. [ABSTRACT FROM AUTHOR]

Background: Non-melanoma skin cancer (NMSC) stands as an umbrella term for common cutaneous malignancies, including basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), together with rarer cutaneous cancers, such as Merkel cell carcinoma (MCC) and other forms of adnexal cancers. The majority of NMSCs can be successfully treated with surgery or radiotherapy, but advanced and metastatic stages may require systemic approaches such as immunotherapy with immune checkpoint inhibitors (ICIs). Summary: Since immunotherapy is not effective in all patients and can potentially lead to severe adverse effects, an important clinical question is how to properly identify those who could be suitable candidates for this therapeutic choice. In this paper, we review the potential features and biomarkers used to predict the outcome of ICIs therapy for NMSCs. Moreover, we analyze the role of immunotherapy in special populations, such as the elderly, immunocompromised patients, organ transplant recipients, and subjects suffering from autoimmune conditions. Key messages: Many clinical, serum, histopathological, and genetic features have been investigated as potential predictors of response in NMSCs treated with ICIs. Although this field of research is very promising, definitive, cost-effective, and reproducible biomarkers are still lacking and further efforts are needed to validate the suggested predictors in larger cohorts. [ABSTRACT FROM AUTHOR]

Keywords: basal; carcinoma; cell; collision; keratosis; neoplasm; seborrheic; skin; trichoblastoma; tumor EN basal carcinoma cell collision keratosis neoplasm seborrheic skin trichoblastoma tumor e242 e243 2 03/17/23 20230401 NES 230401 We read with interest the excellent correspondence describing the first reported case of a collision tumor of melanotrichoblastoma and seborrheic keratosis by Mizuta et al.[1] We recently published an extensive review of collision tumors associated with BCC; in our paper, we suggested the descriptive term "multiple skin neoplasms at one site" (MUSK IN A NEST) to replace "collision tumors." In addition, we proposed a new terminology and classification for these unique neoplasms.[2] Cutaneous collision tumors are multiple skin neoplasms at one site. [Extracted from the article]

BCC (basal cell carcinoma) and SCC (squamous cell carcinoma) account for the vast majority of cases of non-melanoma skin cancer (NMSC). The gold standard for the diagnosis remains biopsy, which, however, is an invasive and time-consuming procedure. In this study, we employed spatially offset Raman spectroscopy (SORS), a non-invasive approach, allowing the assessment of deeper skin tissue levels and collection of Raman photons with a bias towards the different layers of epidermis, where the non-melanoma cancers are initially formed and expand. Ex vivo Raman measurements were acquired from 22 skin biopsies using conventional back-scattering and a defocused modality (with and without a spatial offset). The spectral data were assessed against corresponding histopathological data to determine potential prognostic factors for lesion detection. The results revealed a positive correlation of protein and lipid content with the SCC and BCC types, respectively. By further correlating with patient data, multiple factor analysis (MFA) demonstrated a strong clustering of variables based on sex and age in all modalities. Specifically for the defocused modality (zero and 2 mm offset), further clustering occurred based on pathology. This study demonstrates the utility of the SORS technology in NMSC diagnosis prior to histopathological examination on the same tissue. [ABSTRACT FROM AUTHOR]

The main task of creating new digital images of different skin diseases is to increase the resolution of the specific textures and colors of each skin disease. In this paper, the performance of generative adversarial networks has been optimized to generate multicolor and histological color digital images of a variety of skin diseases (melanoma, birthmarks, and basal cell carcinomas). Two architectures for generative adversarial networks were built using two models: the first is a model for generating new images of dermatology through training processes, and the second is a discrimination model whose main task is to identify the generated digital images as either real or fake. The gray wolf swarm algorithm and the whale swarm algorithm were relied on to generate values that improve the performance of GANs and insert them into the generator instead of random values, which in turn worked to reduce the loss values for the generated images. Loss values were adopted as a measure of optimizations for each epoch, and the fastest access time to actual digital images for each skin disease was adopted. Before the optimization operations, 50% accurate images of skin diseases were obtained; after the optimization operations, 98% accurate images of skin diseases were obtained. [ABSTRACT FROM AUTHOR]

Fibroepithelioma of Pinkus (FeP) is an uncommon variant of basal cell carcinoma (BCC) that usually presents as a solitary, well-demarcated tumor or plaque, predominantly located on the trunk. It is characterized by indolent course and surgical excision is the treatment of choice. Both pigmented and non-pigmented variants of FeP may display dermoscopic features suggestive of malignant melanoma. In the paper, a case of FeP is presented, and the dermoscopic findings in this entity are discussed. [ABSTRACT FROM AUTHOR]

Objectives Metastasis to the oral cavity is a rare phenomenon. Basal cell carcinoma (BCC) is the most common skin malignancy, followed by squamous cell carcinoma (SCC) and melanoma. Nevertheless, BCC rarely metastasizes, and most cases of cutaneous metastasis to the oral cavity include melanoma and SCC. Oral metastatic lesions are not typical differential diagnoses and may cause diagnostic challenges. Case In this paper, we present the case of a 36-year-old female patient with a rapidly growing gingival mass. She had a history of undifferentiated skin carcinoma almost 18 months ago. An incisional biopsy was performed, and according to microscopic findings and medical history, a diagnosis of undifferentiated metastatic carcinoma was made. Conclusion Oral metastasis needs to be considered in the differential diagnosis of lesions in patients with a history of malignancy. [ABSTRACT FROM AUTHOR]

Skin cancer has been one of the major worldwide public health issue with more than 1 million cases every year. Skin cancer is classified into three categories: Basal Cell Carcinoma, Melanoma and Squamous Cell Carcinoma [ 1 ]. Melanoma is the most critical category of skin cancer with very thin chances of recovery and survival of the patient. Early diagnosis of skin cancer can drastically improve survival rate to as high as 95 percent. This served as a motivation to contribute to this noble cause using technology based solutions. In the process of diagnosis for the disease, the process is divided into four basic components: image processing including hair removal, noise removal, sharpening, and increasing the resolution of the image given to the skin dimension. Recent developments in identification of skin cancer technology uses machine learning and in-depth based reading segmentation algorithms. Most used algorithms are: InceptionV3, ResNet, VGGNet. This paper suggests an artificial skin cancer screening process using techniques like image processing and machine learning. Image super-resolution (ISR) techniques recreate an image with high resolution or sequence from visual LR images. An approach using deep learning on the Image super resolution was used to boost the accuracy of the convolutional neural network model. This model was developed using the Keras backend and tested the model by modifying the layers of neural network which are used for training. The model is built on publicly sourced dataset from the ISIC data archives. [ABSTRACT FROM AUTHOR]