Skin Cancer Detection Technology

Enhancing Diagnosis in Squamous Cell Carcinoma: Non-Invasive Imaging and Multimodal Approach

Background/Objectives: Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer, with diverse clinical presentations. This study aims to correlate findings from dermoscopy, ultrasonography, ex vivo confocal microscopy, and histology to improve diagnostic accuracy and guide better clinical management of cSCC. Methods: This cross-sectional study, conducted between July 2022 and December 2024, included 26 patients with 35 clinically suspicious cSCC tumors, analyzed through clinical, dermoscopic, high-frequency ultrasound (HFUS), ex vivo confocal fluorescence microscopy (FCM), and histopathology. Tumors were evaluated for various clinical, imaging, and histopathological criteria, such as tumor thickness, vascularization, differentiation degree, and invasion level, with FCM applied to 24 tumors for advanced microscopic analysis. Results: The study analyzed 35 cases of histopathologically confirmed cSCC, finding that invasive SCC was associated with greater tumor thickness, increased vascularization, and ulceration on both ultrasound and dermatoscopy, while in situ SCC showed homogeneous echogenicity and specific dermoscopic patterns like dotted vessels and white halos. Strong correlations were identified between ultrasound and histopathological measurements of tumor thickness and invasion depth, and confocal microscopy revealed that features like plump bright cells and nest-like structures were linked to invasive and poorly differentiated tumors. Conclusions: This study uniquely integrates advanced imaging techniques-dermatoscopy, skin ultrasound, and ex vivo confocal microscopy-with histopathological analysis to provide new insights into tumor grade, vascularity, and invasion depth in cSCC, enhancing non-invasive diagnosis.

A narrative review on the use of Green synthesized metallic nanoparticles for targeted cancer therapy

Cancer is a leading cause of death worldwide. While traditional and synthetic medical therapies are in place for cancer treatment, their effectiveness is hindered by various limitations, such as toxic side effects, limited availability, and high costs. In recent years, a promising alternative approach has emerged in the form of green-synthesized metallic nanoparticles (MNPs), which offer targeted cancer therapy. These nanoparticles (NPs) have garnered significant attention from cancer researchers owing to their natural or surface-induced anticancer properties, versatility of metals as agents, and eco-friendly nature. This approach may positively impact healthy cells surrounding the cancerous cells. Green-synthesized MNPs have gained popularity in cancer management because of their ease of handling in the laboratory and the affordability of starting materials compared to synthetic methods. This review analyzes green-synthesized MNPs for targeted cancer therapy, highlighting tumor-targeting strategies, synthesis methods, and clinical challenges. Unlike general reviews, it compares plant-, microbial-, and enzyme-mediated synthesis approaches, emphasizing their impact on nanoparticle stability, functionalization, and interactions with the tumor microenvironment for enhanced therapeutic efficacy.

An automatic approach to detect skin cancer utilizing active infrared thermography

Skin cancer is a growing global concern, with cases steadily rising. Typically, malignant moles are identified through visual inspection, using dermatoscopy and patient history. Active thermography has emerged as an effective method to distinguish between malignant and benign lesions. Our previous research showed that spatio-temporal features can be extracted from suspicious lesions to accurately determine malignancy, which was applied in a distance-based classifier. In this study, we build on that foundation by introducing a set of novel spatial and temporal features that enhance classification accuracy and can be integrated into any machine learning approach. These features were implemented in a support-vector machine classifier to detect malignancy. Notably, our method addresses a common limitation in existing approaches-manual lesion selection-by automating the process using a U-Net convolutional neural network. We validated our system by comparing U-Net's performance with expert dermatologist segmentations, achieving a 17% improvement in the Jaccard index over a semi-automatic algorithm. The detection algorithm relies on accurate lesion segmentation, and its performance was evaluated across four segmentation techniques. At an 85% sensitivity threshold, expert segmentation provided the highest specificity at 87.62%, while non-expert and U-Net segmentations achieved comparable results of 69.63% and 68.80%, respectively. Semi-automatic segmentation lagged behind at 64.45%. This automated detection system performs comparably to high-accuracy methods while offering a more standardized and efficient solution. The proposed automatic system achieves 3% higher accuracy compared to the ResNet152V2 network when processing low-quality images obtained in a clinical setting.

Assessing spatial distribution of bioindicator elements in various cutaneous tumors using correlative imaging with laser-ablation-based analytical methods

Correlative imaging of cutaneous tumors provides additional information to the standard histopathologic examination. However, the joint progress in the establishment of analytical techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) in clinical practice is still limited. Their combination provides complementary information as it is also shown in our study in terms of major biotic (Ca, Mg, and P) and trace (Cu and Zn) elements. To elucidate changes in the elemental composition in tumors, we have compiled a set of malignant tumors (Squamous Cell Carcinoma, Basal Cell Carcinoma, Malignant Melanoma, and Epithelioid Angiosarcoma), one benign tumor (Pigmented Nevus) and one healthy-skin sample. The data processing was based on a methodological pipeline involving binary image registration and affine transformation. Thus, our paper brings a feasibility study of a practical methodological concept that enables us to compare LIBS and LA-ICP-MS results despite the mutual spatial distortion of original elemental images. Moreover, we also show that LIBS could be a sufficient pre-screening method even for a larger number of samples according to the speed and reproducibility of the analyses. Whereas LA-ICP-MS could serve as a ground truth and reference technique for preselected samples.

Skin-CAD: Explainable deep learning classification of skin cancer from dermoscopic images by feature selection of dual high-level CNNs features and transfer learning

Skin cancer (SC) significantly impacts many individuals' health all over the globe. Hence, it is imperative to promptly identify and diagnose such conditions at their earliest stages using dermoscopic imaging. Computer-aided diagnosis (CAD) methods relying on deep learning techniques especially convolutional neural networks (CNN) can effectively address this issue with outstanding outcomes. Nevertheless, such black box methodologies lead to a deficiency in confidence as dermatologists are incapable of comprehending and verifying the predictions that were made by these models. This article presents an advanced an explainable artificial intelligence (XAI) based CAD system named "Skin-CAD" which is utilized for the classification of dermoscopic photographs of SC. The system accurately categorises the photographs into two categories: benign or malignant, and further classifies them into seven subclasses of SC. Skin-CAD employs four CNNs of different topologies and deep layers. It gathers features out of a pair of deep layers of every CNN, particularly the final pooling and fully connected layers, rather than merely depending on attributes from a single deep layer. Skin-CAD applies the principal component analysis (PCA) dimensionality reduction approach to minimise the dimensions of pooling layer features. This also reduces the complexity of the training procedure compared to using deep features from a CNN that has a substantial size. Furthermore, it combines the reduced pooling features with the fully connected features of each CNN. Additionally, Skin-CAD integrates the dual-layer features of the four CNNs instead of entirely depending on the features of a single CNN architecture. In the end, it utilizes a feature selection step to determine the most important deep attributes. This helps to decrease the general size of the feature set and streamline the classification process. Predictions are analysed in more depth using the local interpretable model-agnostic explanations (LIME) approach. This method is used to create visual interpretations that align with an already existing viewpoint and adhere to recommended standards for general clarifications. Two benchmark datasets are employed to validate the efficiency of Skin-CAD which are the Skin Cancer: Malignant vs. Benign and HAM10000 datasets. The maximum accuracy achieved using Skin-CAD is 97.2 % and 96.5 % for the Skin Cancer: Malignant vs. Benign and HAM10000 datasets respectively. The findings of Skin-CAD demonstrate its potential to assist professional dermatologists in detecting and classifying SC precisely and quickly.

M, Alshehri S, Khormi AMS, Almalki MEM, Hussain SA, Rabbani SI, Asdaq SMB. Development of topical silver nano gel formulation of Bixin: Characterization, and evaluation of anticancer activity

Objective

Skin cancer refers to the pathological condition characterized by the proliferation of atypical skin cells in an uncontrolled manner. Plant-based products such as bixin although show promising anticancer properties, but maintaining their stability in a formulation is a difficult task. The objective of the research is to formulate a silver nanoparticle gel preparation of bixin and evaluate its anticancer properties.

Methods

The extract from Bixa orellana seed was prepared by hot extraction technique to isolate the active ingredient, bixin. A green synthesis approach was utilized for preparing the silver nanoparticle gel of bixin (BOAgNPs). Characterization of silver nanoparticles was done using FTIR, scanning electron microscopy, compatibility study, homogeneity testing, pH evaluation, and drug content determination. The in-vitro anticancer activity was performed using cell lines (B16F10) and in-vivo by chemical carcinogen (7,12-dimethylbenz (a) anthracene) in mice.

Results

The BOAgNPs-loaded topical gel was found to be homogeneous (clear orange color) and pH-compatible (pH ≈ 6.66) with the skin. The characterization studies indicated the presence of all functional groups in the formulation. An optimized batch of bixin-nano gel showed about 60% inhibitory effects on B16F10 cell lines (in-vitro activity) when equated with a reference drug, 5-fluorouracil. The in-vivo anticancer study suggested suppression of tumorigenesis and promotion of the healing process with bixin-nano gel application on the skin.

Conclusion

The results suggested the promising anticancer property of bixin when formulated in silver nanoparticle gel. The preparation of silver particles nano gel with bixin might provide an effective alternative option for treating skin cancers, provided more research complements the findings of the present study.

Screening of key modules and key genes in the prevention of skin cancer development based on gene volcano plot and WGCNA

BACKGROUND

Skin cancer, a prevalent form of cancer that is on the rise worldwide, requires proactive prevention strategies to reduce the burden of screening, treatment, and mortality. The KEGG research highlighted the significant involvement of red module genes in protein digestion and absorption. These findings provide valuable insights into the underlying molecular mechanisms associated with skin cancer susceptibility, offering potential targets for further research and development of preventive strategies.

MATERIALS AND METHODS

Hub genes numbered 130. "limma" in R found 600 DEGs from GSE66359 dataset. DEGs are enriched in BP: chromosome segregation, CC: chromosomal region, and MF: DNA replication origin binding, according to GO analysis. Cell cycle was enriched in DEGs by KEGG and GSEA. Finally, significant genes were COL5A1, CTHRC1, ECM1, FSTL1, KDELR3, and WIPI1.

RESULTS

ECM1 and WIPI1 greatly prevented skin cancer. This study created a coexpression network using WGCNA to investigate skin cancer susceptibility modules and cardiovascular disease genes.

CONCLUSION

Our study finds a module and many important genes that are essential building blocks in the etiology of skin cancer, which may help us understand the molecular mechanisms of disease prevention.

Diagnostic accuracy of high-frequency ultrasound for cutaneous neoplasms: a narrative review of the literature

High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of evidence about the diagnostic accuracy of high-frequency ultrasound in dermatology. A narrative review of the PubMed database was performed to establish the correlation between ultrasound findings and histopathologic/dermoscopic findings for cutaneous neoplasms. Articles were divided into the following four categories: melanocytic, keratinocytic/epidermal, appendageal, and soft tissue/neural neoplasms. Review of the literature revealed that ultrasound findings and histopathology findings were strongly correlated regarding the depth of a cutaneous neoplasm. Morphological characteristics were correlated primarily in soft tissue/neural neoplasms. Overall, there is a paucity of literature on the correlation between high-frequency ultrasound and histopathology of cutaneous neoplasms. Further studies are needed to investigate this correlation in various dermatologic conditions.

Mohs micrographic surgery challenges and new technologies to optimize care of cutaneous malignancies of the ear

Cutaneous malignancies affecting the ear, exacerbated by extensive ultraviolet (UV) exposure, pose intricate challenges owing to the organ's complex anatomy. This article investigates how the anatomy contributes to late-stage diagnoses and ensuing complexities in surgical interventions. Mohs Micrographic Surgery (MMS), acknowledged as the gold standard for treating most cutaneous malignancies of the ear, ensures superior margin control and cure rates. However, the ear's intricacy necessitates careful consideration of tissue availability and aesthetic outcomes. The manuscript explores new technologies like Reflectance Confocal Microscopy (RCM), Optical Coherence Tomography (OCT), High-Frequency, High-Resolution Ultrasound (HFHRUS), and Raman spectroscopy (RS). These technologies hold the promise of enhancing diagnostic accuracy and providing real-time visualization of excised tissue, thereby improving tumor margin assessments. Dermoscopy continues to be a valuable non-invasive tool for identifying malignant lesions. Staining methods in Mohs surgery are discussed, emphasizing hematoxylin and eosin (H&E) as the gold standard for evaluating tumor margins. Toluidine blue is explored for potential applications in assessing basal cell carcinomas (BCC), and immunohistochemical staining is considered for detecting proteins associated with specific malignancies. As MMS and imaging technologies advance, a thorough evaluation of their practicality, cost-effectiveness, and benefits becomes essential for enhancing surgical outcomes and patient care. The potential synergy of artificial intelligence with these innovations holds promise in revolutionizing tumor detection and improving the efficacy of cutaneous malignancy treatments.

Performance evaluation of E-VGG19 model: Enhancing real-time skin cancer detection and classification

Skin cancer is a pervasive and potentially life-threatening disease. Early detection plays a crucial role in improving patient outcomes. Machine learning (ML) techniques, particularly when combined with pre-trained deep learning models, have shown promise in enhancing the accuracy of skin cancer detection. In this paper, we enhanced the VGG19 pre-trained model with max pooling and dense layer for the prediction of skin cancer. Moreover, we also explored the pre-trained models such as Visual Geometry Group 19 (VGG19), Residual Network 152 version 2 (ResNet152v2), Inception-Residual Network version 2 (InceptionResNetV2), Dense Convolutional Network 201 (DenseNet201), Residual Network 50 (ResNet50), Inception version 3 (InceptionV3), For training, skin lesions dataset is used with malignant and benign cases. The models extract features and divide skin lesions into two categories: malignant and benign. The features are then fed into machine learning methods, including Linear Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), Logistic Regression (LR) and Support Vector Machine (SVM), our results demonstrate that combining E-VGG19 model with traditional classifiers significantly improves the overall classification accuracy for skin cancer detection and classification. Moreover, we have also compared the performance of baseline classifiers and pre-trained models with metrics (recall, F1 score, precision, sensitivity, and accuracy). The experiment results provide valuable insights into the effectiveness of various models and classifiers for accurate and efficient skin cancer detection. This research contributes to the ongoing efforts to create automated technologies for detecting skin cancer that can help healthcare professionals and individuals identify potential skin cancer cases at an early stage, ultimately leading to more timely and effective treatments.

An overview of cutaneous squamous cell carcinoma imaging diagnosis methods

Cutaneous squamous cell carcinoma, a type of non-melanoma skin cancer, is a form of keratinocyte carcinoma that stands as one of the most prevalent cancers, exhibiting a rising frequency. This review provides an overview of the latest literature on imaging methods for diagnosing squamous cell carcinoma (SCC) and actinic keratosis (AK). It discusses the diagnostic criteria, advantages, and disadvantages of various techniques such as dermatoscopy, skin ultrasound (US), in vivo and ex-vivo reflectance confocal microscopy (RCM), and line-field confocal optical coherence tomography (LC-OCT). These methods offer benefits including non-invasiveness, rapidity, comprehensive lesion imaging, and enhanced sensitivity, but face challenges like high costs and the need for specialized expertise. Despite obstacles, the use of these innovative techniques is expected to increase with ongoing technological advancements, improving diagnosis and treatment planning for keratinocyte carcinomas. Standardizing LC-OCT imaging algorithms for AK, Bowen's disease, and SCC remains an area for further research.

A novel long non-coding RNA SLNCR1 promotes proliferation, migration, and invasion of melanoma via transcriptionally regulating SOX5

Steroid receptor RNA activator (SRA)-like non-coding RNA (SLNCR1) has been implicated in various tumorigenic processes, but the precise regulatory role in melanoma progression remains uncertain. We performed a comprehensive analysis to investigate the prognostic value of SLNCR1 expression in patients with melanoma by TCGA database and melanoma tissue samples via the Kaplan-Meier method. Subsequently, we conducted qRT-PCR and Fluorescence in Situ Hybridization (FISH) assays to identify SLNCR1 expression levels and localization in tissues and cells, respectively. Loss-of-function assays utilizing shRNAs vectors were used to investigate the potential impact of SLNCR1. Our data showed that SLNCR1 is significantly up-regulated in human malignant melanoma tissues and cell lines and functions as an oncogene. Silencing of SLNCR1 suppressed melanoma cell proliferation, migration, invasion, and inhibited tumorigenesis in a mouse xenograft model. Additionally, we employed bioinformatic predictive analysis, combined with dual-luciferase reporter analysis and functional rescue assays, to elucidate the mechanistic target of the SLNCR1/SOX5 axis in melanoma. Mechanistically, we discovered that SLNCR1 promotes EMT of human melanoma by targeting SOX5, as downregulation of SLNCR1 expression leads to a decrease in SOX5 protein levels and inhibits melanoma tumorigenesis. Our research offers promising insights for more precise diagnosis and treatment of human melanoma.

An Insight on Skin Cancer About Different Targets With Update on Clinical Trials and Investigational Drugs

Cancer is a diverse disease caused by transcriptional changes involving genetic and epigenetic features that influence a huge variety of genes and proteins. Skin cancer is a potentially fatal disease that affects equally men and women globally and is characterized by many molecular changes. Despite the availability of various improved approaches for detecting and treating skin cancer, it continues to be the leading cause of death throughout society. This review highlights a general overview of skin cancer, with an emphasis on epidemiology, types, risk factors, pathological and targeted facets, biomarkers and molecular markers, immunotherapy, and clinical updates of investigational drugs associated with skin cancer. The skin cancer challenges are acknowledged throughout this study, and the potential application of novel biomarkers of skin cancer formation, progression, metastasis, and prognosis is explored. Although the mechanism of skin carcinogenesis is currently poorly understood, multiple articles have shown that genetic and molecular changes are involved. Furthermore, several skin cancer risk factors are now recognized, allowing for efficient skin cancer prevention. There have been considerable improvements in the field of targeted treatment, and future research into additional targets will expand patients' therapeutic choices. In comparison to earlier articles on the same issue, this review focused on molecular and genetic factors and examined various skin cancer-related factors in depth.

From the Cochrane Library: Optical Coherence Tomography for Diagnosing Skin Cancer in Adults

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Detection of cutaneous malignant melanoma by tape stripping of pigmented skin lesions - A systematic review

BACKGROUND

Cutaneous malignant melanoma (MM) is potentially aggressive, and numerous clinically suspicious pigmented skin lesions are excised, causing unnecessary mutilation for patients at high healthcare costs, but without histopathological evidence of MM. The high number of excisions may be lowered by using more accurate diagnostics. Tape stripping (TS) of clinically suspicious lesions is a non-invasive diagnostic test of MM that can potentially lower the number needed to biopsy/excise.

MATERIALS AND METHODS

The aim is to determine the diagnostic accuracy of TS in detecting MM in clinically suspicious pigmented skin lesions. This systematic review following PRISMA guidelines searched PubMed, Web of Science, and Embase (September 2022) using melanoma combined with tape stripping, adhesive patch(es), pigmented lesion assay, or epidermal genetic information retrieval.

RESULTS

Ten studies were included. Sensitivity ranged from 68.8% (95% confidence interval [CI] 51.5, 82.1) to 100% (95% CI 91.0, 100). Specificity ranged from 69.1% (95% CI 63.8, 74.0) to 100% (95% CI 78.5, 100). A pooled analysis of five studies testing the RNA markers LINC00518 and PRAME found a sensitivity of 86.9% (95% CI 81.7, 90.8) and a specificity of 82.4% (95% CI 80.8, 83.9).

CONCLUSION

Overall quality of studies was low, and the reliability of sensitivity and specificity is questionable. However, TS may supplement well-established diagnostic methods as pooled analysis of five studies indicates a moderate sensitivity. Future studies are needed to obtain more reliable data as independent studies with no conflict of interest.

Enhancing Skin Cancer Immunotheranostics and Precision Medicine through Functionalized Nanomodulators and Nanosensors: Recent Development and Prospects

Skin cancers, especially melanomas, present a formidable diagnostic and therapeutic challenge to the scientific community. Currently, the incidence of melanomas shows a high increase worldwide. Traditional therapeutics are limited to stalling or reversing malignant proliferation, increased metastasis, or rapid recurrence. Nonetheless, the advent of immunotherapy has led to a paradigm shift in treating skin cancers. Many state-of-art immunotherapeutic techniques, namely, active vaccination, chimeric antigen receptors, adoptive T-cell transfer, and immune checkpoint blockers, have achieved a considerable increase in survival rates. Despite its promising outcomes, current immunotherapy is still limited in its efficacy. Newer modalities are now being explored, and significant progress is made by integrating cancer immunotherapy with modular nanotechnology platforms to enhance its therapeutic efficacy and diagnostics. Research on targeting skin cancers with nanomaterial-based techniques has been much more recent than other cancers. Current investigations using nanomaterial-mediated targeting of nonmelanoma and melanoma cancers are directed at augmenting drug delivery and immunomodulation of skin cancers to induce a robust anticancer response and minimize toxic effects. Many novel nanomaterial formulations are being discovered, and clinical trials are underway to explore their efficacy in targeting skin cancers through functionalization or drug encapsulation. The focus of this review rivets on theranostic nanomaterials that can modulate immune mechanisms toward protective, therapeutic, or diagnostic approaches for skin cancers. The recent breakthroughs in nanomaterial-based immunotherapeutic modulation of skin cancer types and diagnostic potentials in personalized immunotherapies are discussed.

Diagnostics Using Non-Invasive Technologies in Dermatological Oncology

The growing incidence of skin cancer, with its associated mortality and morbidity, has in recent years led to the developing of new non-invasive technologies, which allow an earlier and more accurate diagnosis. Some of these, such as digital photography, 2D and 3D total-body photography and dermoscopy are now widely used and others, such as reflectance confocal microscopy and optical coherence tomography, are limited to a few academic and referral skin cancer centers because of their cost or the long training period required. Health care professionals involved in the treatment of patients with skin cancer need to know the implications and benefits of new non-invasive technologies for dermatological oncology. In this article we review the characteristics and usability of the main diagnostic imaging methods available today.

Melanoma Management: From Epidemiology to Treatment and Latest Advances

Melanoma is the deadliest skin cancer, whose morbidity and mortality indicators show an increasing trend worldwide. In addition to its great heterogeneity, melanoma has a high metastatic potential, resulting in very limited response to therapies currently available, which were restricted to surgery, radiotherapy and chemotherapy for many years. Advances in knowledge about the pathophysiological mechanisms of the disease have allowed the development of new therapeutic classes, such as immune checkpoint and small molecule kinase inhibitors. However, despite the incontestable progress in the quality of life and survival rates of the patients, effectiveness is still far from desired. Some adverse side effects and resistance mechanisms are the main barriers. Thus, the search for better options has resulted in many clinical trials that are now investigating new drugs and/or combinations. The low water solubility of drugs, low stability and rapid metabolism limit the clinical potential and therapeutic use of some compounds. Thus, the research of nanotechnology-based strategies is being explored as the basis for the broad application of different types of nanosystems in the treatment of melanoma. Future development focus on challenges understanding the mechanisms that make these nanosystems more effective.

Synthesis of novel isoxazole-carboxamide derivatives as promising agents for melanoma and targeted nano-emulgel conjugate for improved cellular permeability

BACKGROUND

Cancer is one of the most dangerous and widespread diseases in the world today and it has risen to the position of the leading cause of death around the globe in the last few decades. Due to the inherent resistance of many types of cancer to conventional radiotherapy and chemotherapy, it is vital to develop innovative anticancer medications. Recently, a strategy based on nanotechnology has been used to improve the effectiveness of both old and new cancer drugs.

OBJECTIVES

The present study aimed to design and synthesize a series of phenyl-isoxazole-Carboxamide derivatives, evaluate their anticancer properties, and improve the permeability of potent compounds into cancer cells by using a nano-emulgel strategy.

METHODS

The coupling reaction of aniline derivatives and isoxazole-Carboxylic acid was used to synthesize a series of isoxazole-Carboxamide derivatives. IR, HRMS, 1H-NMR, and 13C-NMR spectroscopy techniques, characterized all the synthesized compounds. The in-vitro cytotoxic evaluation was performed by using the MTS assay against seven cancer cell lines, including hepatocellular carcinoma (Hep3B and HepG2), cervical adenocarcinoma (HeLa), breast carcinoma (MCF-7), melanoma (B16F1), colorectal adenocarcinoma (Caco-2), and colon adenocarcinoma (Colo205), as well as human hepatic stellate (LX-2) in addition to the normal cell line (Hek293T). A nano-emulgel was developed for the most potent compound, using a self-emulsifying technique.

RESULTS

All synthesized compounds were found to have potent to moderate activities against B16F1, Colo205, and HepG2 cancer cell lines. The results revealed that the 2a compound has broad spectrum activity against B16F1, Colo205, HepG2, and HeLa cancer cell lines with an IC₅₀ range of 7.55-40.85 µM. Moreover, compound 2e was the most active compound against B16F1 with an IC₅₀ of 0.079 µM compared with Dox (IC₅₀ = 0.056 µM). Nanoemulgel was used to increase the potency of the 2e molecule against this cancer cell line, and the IC₅₀ was reduced to 0.039 µM. The antifibrotic activities were investigated against the LX-2 cell line, and it was found that our synthesized molecules showed better antifibrotic activities at 1 µM than 5-FU, and the cell viability values were 67 and 95%, respectively.

CONCLUSION

This study suggests that a 2e nano-formalized compound is a potential and promising anti-melanoma agent.

Green Metallic Nanoparticles for Cancer Therapy: Evaluation Models and Cancer Applications

Metal-based nanoparticles are widely used to deliver bioactive molecules and drugs to improve cancer therapy. Several research works have highlighted the synthesis of gold and silver nanoparticles by green chemistry, using biological entities to minimize the use of solvents and control their physicochemical and biological properties. Recent advances in evaluating the anticancer effect of green biogenic Au and Ag nanoparticles are mainly focused on the use of conventional 2D cell culture and in vivo murine models that allow determination of the half-maximal inhibitory concentration, a critical parameter to move forward clinical trials. However, the interaction between nanoparticles and the tumor microenvironment is not yet fully understood. Therefore, it is necessary to develop more human-like evaluation models or to improve the existing ones for a better understanding of the molecular bases of cancer. This review provides recent advances in biosynthesized Au and Ag nanoparticles for seven of the most common and relevant cancers and their biological assessment. In addition, it provides a general idea of the in silico, in vitro, ex vivo, and in vivo models used for the anticancer evaluation of green biogenic metal-based nanoparticles.

A plea for standardization of confocal microscopy and optical coherence tomography parameters to evaluate physiological and para-physiological skin conditions in cosmetic science

Non-invasive reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) have been extended to the dermo-cosmetic field, for skin pathophysiology understanding and therapeutics monitoring. However, standardized methodology and parameters to interpret structures and changes in these settings are still lacking. Present study aimed to propose a validated standard methodology and a list of defined parameters for objective non-pathological skin assessments in the cosmetically sensitive cheekbone area of the face. OCT and RCM quantitative, semi-quantitative and qualitative features were considered for assessments. Validation process included 50 sets of images divided into two age groups. Inter-rater reliability was explored to assess the influence of the proposed methodology. Quantitative OCT parameters of "epidermal thickness," "density and attenuation coefficients" and "vascular density" were considered and calculated. Severity scales were developed for semi-quantitative OCT features of "disruption of collagen" and "vascular asset," while extent scales were produced for semi-quantitative RCM "irregular honeycomb," "mottled pigmentation" and "polycyclic papillary contours." Qualitative assessment was obtained for RCM type of collagen, and comparison between age groups was performed for all features considered. Severity visual scales assistance proved excellent inter-rater agreement across all semi-quantitative and qualitative domains. The assistance of shareable software systems allows for objective OCT quantitative parameters measurement. The use of standard reference scales, within a defined assessment methodology, offers high inter-rater reliability and thus reproducibility for semi-quantitative and qualitative OCT and RCM parameters. Taken together, our results may represent a starting point for a standardized application of RCM and OCT in dermo-cosmetic research and practice.

Regenerative Wound Dressings for Skin Cancer

Skin cancer is considered the most prevalent cancer type globally, with a continuously increasing prevalence and mortality growth rate. Additionally, the high risk of recurrence makes skin cancer treatment among the most expensive of all cancers, with average costs estimated to double within 5 years. Although tumor excision is the most effective approach among the available strategies, surgical interventions could be disfiguring, requiring additional skin grafts for covering the defects. In this context, post-surgery management should involve the application of wound dressings for promoting skin regeneration and preventing tumor recurrence and microbial infections, which still represents a considerable clinical challenge. Therefore, this paper aims to provide an up-to-date overview regarding the current status of regenerative wound dressings for skin cancer therapy. Specifically, the recent discoveries in natural biocompounds as anti-cancer agents for skin cancer treatment and the most intensively studied biomaterials for bioactive wound dressing development will be described.

Multimodal imaging of skin lesions by using methylene blue as cancer biomarker

This study aimed the optical imaging of malignant and normal skin tissues with multimodal wide-field fluorescence polarization imaging (WF) technique, by using methylene blue as fluorescence dye. We present optical imaging of skin tissues by different techniques, including reflectance, fluorescence, and polarization imaging for early detection of skin cancer. We collected the reflectance confocal images at 390 and 500 nm. For wide-field fluorescence images, specimens were stimulated at 640 nm and images were collected between 670 and 710 nm. The correlation of the regarded optical modalities with histopathology (H&E), their potentials, capabilities, and limitations to detect skin lesions are discussed. The advantages of multimodal imaging of skin tissues are analyzed to divulge possibilities for precise tumor boundary detection and their classification for malignant and nonmalignant skin tissues. Prior to imaging, the cells were stained in aqueous MB (a dye approved by FDA).