Updates in Melanoma

Identification of a CpG-based signature coupled with gene expression as prognostic indicators for melanoma: a preliminary study

DNA methylation is an important part of the genomic biology, which recently allowed the identification of key biomarkers for a variety of cancers, including cutaneous melanoma. Despite the current knowledge in cutaneous melanoma, there is a clear need for new efficient biomarkers in clinical application of detection. We use The Cancer Genome Atlas data as a training set and a multi-stage screening strategy to identify prognostic characteristics of melanoma based on DNA methylation. Three DNA methylation CpG sites were identified to be related to the overall survival in the skin cutaneous melanoma cohort. This signature was validated in two independent datasets from Gene Expression Omnibus. The stratified analysis by clinical stage, age, gender, and grade retained the statistical significance. The methylation signature was significantly correlated with immune cells and anti-tumor immune response. Moreover, gene expression corresponding to the candidate CpG locus was also significantly correlated with the survival rate of the patient. About 49% of the prognostic effects of methylation are mediated by affecting the expression of the corresponding genes. The prognostic characteristics of DNA methylation combined with clinical information provide a better prediction value tool for melanoma patients than the clinical information alone. However, more experiments are required to validate these findings. Overall, this signature presents a prospect of novel and wide-ranging applications for appropriate clinical adjuvant trails.

Combined signature of G protein-coupled receptors and tumor microenvironment provides a prognostic and therapeutic biomarker for skin cutaneous melanoma

BACKGROUND

G protein-coupled receptors (GPCRs) have been shown to have an important role in tumor development and metastasis, and abnormal expression of GPCRs is significantly associated with poor prognosis of tumor patients. In this study, we analyzed the GPCRs-related gene (GPRGs) and tumor microenvironment (TME) in skin cutaneous melanoma (SKCM) to construct a prognostic model to help SKCM patients obtain accurate clinical treatment strategies.

METHODS

SKCM expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression analysis, LASSO algorithm, and univariate and multivariate cox regression analysis were used to screen prognosis-related genes (GPR19, GPR146, S1PR2, PTH1R, ADGRE5, CXCR3, GPR143, and OR2I1P) and multiple prognosis-good immune cells; the data set was analyzed according to above results and build up a GPR-TME classifier. The model was further subjected to immune infiltration, functional enrichment, tumor mutational load, immunotherapy prediction, and scRNA-seq data analysis. Finally, cellular experiments were conducted to validate the functionality of the key gene GPR19 in the model.

RESULTS

The findings indicate that high expression of GPRGs is associated with a poor prognosis in patients with SKCM, highlighting the significant role of GPRGs and the tumor microenvironment (TME) in SKCM development. Notably, the group characterized by low GPR expression and a high TME exhibited the most favorable prognosis and immunotherapeutic efficacy. Furthermore, cellular assays demonstrated that knockdown of GPR19 significantly reduced the proliferation, migration, and invasive capabilities of melanoma cells in A375 and A2058 cell lines.

CONCLUSION

This study provides novel insights for the prognosis evaluation and treatment of melanoma, along with the identification of a new biomarker, GPR19.

Current Patterns of Treatment and Outcomes in Advanced Melanoma at a Single Institution

INTRODUCTION

Treatment of advanced melanoma has been transformed by novel systemic therapies. The purpose of this study is to describe the current utilization patterns of immunotherapies with respect to survival outcomes in advanced melanoma.

METHODS

We performed a retrospective cohort study of patients with Stage 3 and 4 melanoma at our institution (2009-2019). Primary outcomes included overall survival (OS) and progression free survival (PFS). Kaplan-Meier survival analysis and Cox proportional hazards regression analysis evaluated associations between covariates and survival outcomes.

RESULTS

Of 244 patients, 5-y OS was 62.4%. Lymphovascular invasion (hazard ratio [HR] = 2.462, P = 0.030) was associated with shorter PFS whereas female gender (HR = 0.324, P = 0.010) was associated with longer PFS. Residual tumor (HR = 146, P = 0.006) and Stage 4 disease (HR = 3.349, P = 0.011) were associated with shorter OS. Use of immunotherapy increased from 2% to 23% over the study period, and use of neoadjuvant immunotherapy also increased up to 2016. Timing of immunotherapy administration was not significantly associated with survival. Of the 193 patients who received 2 or more treatment types, the most common treatment sequence was surgery followed by immunotherapy (n = 117, 60.6%).

CONCLUSIONS

Immunotherapy is increasingly used for treatment of advanced melanoma. In this heterogeneous cohort, there was no significant association between timing of immunotherapy and survival outcomes.

Machine learning modeling and prognostic value analysis of invasion-related genes in cutaneous melanoma

In this study, we aimed to develop an invasion-related risk signature and prognostic model for personalized treatment and prognosis prediction in skin cutaneous melanoma (SKCM), as invasion plays a crucial role in this disease. We identified 124 differentially expressed invasion-associated genes (DE-IAGs) and selected 20 prognostic genes (TTYH3, NME1, ORC1, PLK1, MYO10, SPINT1, NUPR1, SERPINE2, HLA-DQB2, METTL7B, TIMP1, NOX4, DBI, ARL15, APOBEC3G, ARRB2, DRAM1, RNF213, C14orf28, and CPEB3) using Cox and LASSO regression to establish a risk score. Gene expression was validated through single-cell sequencing, protein expression, and transcriptome analysis. Negative correlations were discovered between risk score, immune score, and stromal score using ESTIMATE and CIBERSORT algorithms. High- and low-risk groups exhibited significant differences in immune cell infiltration and checkpoint molecule expression. The 20 prognostic genes effectively differentiated between SKCM and normal samples (AUCs >0.7). We identified 234 drugs targeting 6 genes from the DGIdb database. Our study provides potential biomarkers and a risk signature for personalized treatment and prognosis prediction in SKCM patients. We developed a nomogram and machine-learning prognostic model to predict 1-, 3-, and 5-year overall survival (OS) using risk signature and clinical factors. The best model, Extra Trees Classifier (AUC = 0.88), was derived from pycaret's comparison of 15 classifiers. The pipeline and app are accessible at https://github.com/EnyuY/IAGs-in-SKCM.

A practical nomogram and risk stratification system predicting the cancer-specific survival for patients aged >50 with advanced melanoma

Objective

To investigate risk factors for advanced melanoma over 50 years of age and to develop and validate a new line chart and classification system.

Methods

The SEER database was screened for patients diagnosed with advanced melanoma from 2010 to 2019 and Cox regression analysis was applied to select variables affecting patient prognosis. The area under curve (AUC), relative operating characteristic curve (ROC), Consistency index (C-index), decision curve analysis (DCA), and survival calibration curves were used to verify the accuracy and utility of the model and to compare it with traditional AJCC tumor staging. The Kaplan-Meier curve was applied to compare the risk stratification between the model and traditional AJCC tumor staging.

Results

A total of 5166 patients were included in the study. Surgery, age, gender, tumor thickness, ulceration, the number of primary melanomas, M stage and N stage were the independent prognostic factors of CSS in patients with advanced melanoma (P<0.05). The predictive nomogram model was constructed and validated. The C-index values obtained from the training and validation cohorts were 0.732 (95%CI: 0.717-0.742) and 0.741 (95%CI: 0.732-0.751). Based on the observation and analysis results of the ROC curve, survival calibration curve, NRI, and IDI, the constructed prognosis model can accurately predict the prognosis of advanced melanoma and performs well in internal verification. The DCA curve verifies the practicability of the model. Compared with the traditional AJCC staging, the risk stratification in the model has a better identification ability for patients in different risk groups.

Conclusion

The nomogram of advanced melanoma and the new classification system were successfully established and verified, which can provide a practical tool for individualized clinical management of patients.

New Insights in Topical Drug Delivery for Skin Disorders: From a Nanotechnological Perspective

Skin, the largest organ in humans, is an efficient route for the delivery of drugs as it circumvents several disadvantages of the oral and parenteral routes. These advantages of skin have fascinated researchers in recent decades. Drug delivery via a topical route includes moving the drug from a topical product to a locally targeted region with dermal circulation throughout the body and deeper tissues. Still, due to the skin's barrier function, delivery through the skin can be difficult. Drug delivery to the skin using conventional formulations with micronized active components, for instance, lotions, gels, ointments, and creams, results in poor penetration. The use of nanoparticulate carriers is one of the promising strategies, as it provides efficient delivery of drugs through the skin and overcomes the disadvantage of traditional formulations. Nanoformulations with smaller particle sizes contribute to improved permeability of therapeutic agents, targeting, stability, and retention, making nanoformulations ideal for drug delivery through a topical route. Achieving sustained release and preserving a localized effect utilizing nanocarriers can result in the effective treatment of numerous infections or skin disorders. This article aims to evaluate and discuss the most recent developments of nanocarriers as therapeutic agent vehicles for skin conditions with patent technology and a market overview that will give future directions for research. As topical drug delivery systems have shown great preclinical results for skin problems, for future research directions, we anticipate including in-depth studies of nanocarrier behavior in various customized treatments to take into account the phenotypic variability of the disease.

Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status

Aims: To explore whether the expression of pyroptosis-related lncRNAs makes a difference in the prognosis and antitumor immunity of cutaneous melanoma (CM) patients. Methods: A series of analyses were conducted to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to further assess the associations among immune status, tumor microenvironment and the prognostic risk model. Results: Eight pyroptosis-related lncRNAs relevant to prognosis were ascertained and applied to establish the prognostic risk model. The low-risk group had a higher overall survival rate. Conclusion: The established prognostic risk model presents better prediction ability for the prognosis of CM patients and provides new possible therapeutic targets for CM.

Sustained release of tumor cell lysate and CpG from an injectable, cytotoxic hydrogel for melanoma immunotherapy

Many basic research studies have shown the potential of autologous cancer vaccines in the treatment of melanoma. However, some clinical trials showed that simplex whole tumor cell vaccines can only elicit weak CD8⁺ T cell-mediated antitumor responses which were not enough for effective tumor elimination. So efficient cancer vaccine delivery strategies with improved immunogenicity are needed. Herein, we described a novel hybrid vaccine "MCL" (Melittin-RADA₃₂-CpG-Lysate) which was composed of melittin, RADA₃₂, CpG and tumor lysate. In this hybrid vaccine, antitumor peptide melittin and self-assembling fusion peptide RADA₃₂ were assembled to form the hydrogel framework melittin-RADA₃₂(MR). Then, whole tumor cell lysate and immune adjuvant CpG-ODN were loaded into MR to develop an injectable and cytotoxic hydrogel MCL. MCL showed excellent ability for sustained drug release, to activate dendritic cells and directly kill melanoma cells in vitro. In vivo, MCL not only exerted direct antitumor activity, but also had robust immune initiation effects including the activation of dendritic cells in draining lymph nodes and the infiltration of cytotoxic T lymphocytes (CTLs) in tumor microenvironment. In addition, MCL can efficiently inhibit melanoma growth in B16-F10 tumor bearing mice, which suggested that MCL is a potential cancer vaccine strategy for melanoma treatment.

C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment

Skin cutaneous melanoma (SKCM) is the most lethal form of skin cancers owing to high invasiveness and high metastatic potential. Tumor microenvironment (TME) provides powerful evidences for discerning SKCM, raising the prospect to identify biomarkers of SKCM. Based on the transcriptome profiles of patients with SKCM and the corresponding clinical information from The Cancer Genome Atlas (TCGA), we used ESTIMATE algorithm to calculate ImmuneScore and StromalScore and identified the TME-Related differentially expressed genes (DEGs), than the intersected TME-Related DEGs were used for subsequent functional enrichment analysis. Protein-protein interaction (PPI) analysis was used to identify the functionality-related DEGs and univariate Cox regression analysis was used to identify the survival-related DEGs. Furthermore, SKCM-related DEGs were identified based on two Gene Expression Omnibus (GEO) datasets. Finally, we intersected functionality-related DEGs, survival-related DEGs, and SKCM-related DEGs, ascertaining that six DEGs (CCL4, CXCL10, CCL5, GZMB, C1QA, and C1QB) function as core TME-related genes (CTRGs). Significant differences of GZMB, C1QA, and C1QB expressions were found in gender and clinicopathologic staging of SKCM. High levels of GZMB, C1QA, and C1QB expressions were associated with favorable prognosis. Gene set enrichment analysis (GSEA) showed that cell-cell interaction, cell behavior, and intracellular signaling transduction may be mainly involved in both C1QA, C1QB and GZMB expressions and metabolism of phospholipid and amino acid, transcription, and translation may be implicated in low GZMB expressions. C1QA, C1QB, and GZMB are novel SKCM-relating CTRGs, providing promising immune-related prognostic biomarkers for SKCM.

M6A-Related Bioinformatics Analysis Reveals a New Prognostic Risk Signature in Cutaneous Malignant Melanoma

Cutaneous malignant melanoma (CMM) is the most deadly skin cancer worldwide. Despite advances in the treatments of CMM, its incidence and mortality rates are still increasing. N6-methyladenosine (m6A) is the most common form of RNA modification and has attracted increasing interest in cancer initiation and progression. However, the role of m6A regulators in CMM and their correlation with prognosis remain elusive. Here, we demonstrated that by applying consensus clustering, all CMM patient cases can be divided into two clusters based on overall expression levels of 25 m6A genes. We systematically analyzed the prognostic value of the 25 m6A RNA methylation regulators in CMM and found that ELAVL1, ABCF1, and IGF2BP1 yield the highest scores for predicting the prognosis of CMM. Accordingly, we derived a risk signature consisting of three selected m6A genes as an independent prognostic marker for CMM and validated our findings with data derived from a different CMM cohort. Next, we determined that CNVs in m6A genes had a significant negative impact on patient survival. The mRNA expression levels of m6A genes were correlated with CNV mutation. Moreover, in the selected three risk signature m6A regulators, GSEA analysis showed that they were closely correlated with inflammation and immune pathways. TME analysis proved that m6A gene expressions were negatively correlated with immune cell infiltration. In conclusion, m6A regulators are vital participants in CMM pathology; and ELAVL1, ABCF1, and IGF2BP1 mRNA levels are valuable factors for prognosis prediction and treatment strategy development.

The Use and Technique of Sentinel Node Biopsy for Skin Cancer

LEARNING OBJECTIVES

After studying this article, the participant should be able to: 1. Understand the indications for and prognostic value of sentinel lymph node biopsy in skin cancer. 2. Learn the advantages and disadvantages of various modalities used alone or in combination when performing sentinel lymph node biopsy. 3. Understand how to perform sentinel lymph node biopsy in skin cancer patients.

SUMMARY

Advances in technique used to perform sentinel lymph node biopsy to assess lymph node status have led to increased accuracy of the procedure and improved patient outcomes.

Bis-nor-diterpene from Cnidoscolus quercifolius (Euphorbiaceae) induces tubulin depolymerization-mediated apoptosis in BRAF-mutated melanoma cells

A phytochemical investigation of cytotoxic extract and fractions of Cnidoscolus quercifolius Pohl led to isolation of five terpenoids, including three lupane-type triterpenes (1-3) and two bis-nor-diterpenes (4-5). Compounds 4 (phyllacanthone) and 5 (favelanone) are commonly found in this species and have unique chemical structure. Although their cytotoxic activity against cancer cells has been previously reported, the anticancer potential of these molecules remains poorly explored. In this paper, the antimelanoma potential of phyllacanthone (PHY) was described for the first time. Cell viability assay showed a promising cytotoxic activity (IC₅₀ = 40.9 μM) against chemoresistant human melanoma cells expressing the BRAF oncogenic mutation (A2058 cell line). After 72 h of treatment, PHY inhibited cell migration and induced apoptosis and cell cycle arrest (p < 0.05). Immunofluorescence assay showed that the pro-apoptotic effect of PHY is probably associated with tubulin depolymerization, resulting in cytoskeleton disruption of melanoma cells. Molecular docking investigation confirmed this hypothesis given that satisfactory interaction between PHY and tubulin was observed, particularly at the colchicine binding site. These results suggest PHY from C. quercifolius could be potential leader for the design of new antimelanoma drugs.

Skin cancer therapeutics: nano-drug delivery vectors—present and beyond

Background

Skin cancers are among the widely prevalent forms of cancer worldwide. The increasing industrialization and accompanied environmental changes have further worsened the skin cancer statistics. The stern topical barrier although difficult to breach is a little compromised in pathologies like skin cancer. The therapeutic management of skin cancers has moved beyond chemotherapy and surgery.

Main body of the abstract

The quest for a magic bullet still prevails, but topical drug delivery has emerged as a perfect modality for localized self-application with minimal systemic ingress for the management of skin cancers. Advances in topical drug delivery as evidenced by the exploration of nanocarriers and newer technologies like microneedle-assisted/mediated therapeutics have revolutionized the paradigms of topical treatment. The engineered nanovectors have not only been given the liberty to experiment with a wide-array of drug carriers with very distinguishing characteristics but also endowed them with target specificity. The biologicals like nucleic acid-based approaches or skin penetrating peptide vectors are another promising area of skin cancer therapeutics which has demonstrated potential in research studies. In this review, a panoramic view is presented on the etiology, therapeutic options, and emerging drug delivery modalities for skin cancer.

Short conclusion

Nanocarriers have presented innumerable opportunities for interventions in skin cancer therapeutics. Challenge persists for the bench to bedside translation of these highly potential upcoming therapeutic strategies.

Graphic abstract

The review of the light parameters and mechanisms of Photobiomodulation on melanoma cells

Photobiomodulation (PBM) uses low-intensity visible or near-infrared light to produce beneficial effects on cells or tissues, such as brain therapy, wound healing. Still there is no consistent recommendation on the parameters (dose, light mode, wavelength, irradiance) and protocols (repetition, treatment duration) for its clinical application. Herein, we summarize the current PBM parameters for the treatment of melanoma, and we also discuss the potential photoreceptors and downstream signaling mechanisms in the PBM treatment of melanoma cells. It is hypothesized that PBM may inhibit the melanoma cells by activating mitochondria, OPNs, and other receptors. Regardless of the underlying mechanisms, PBM has been shown to be beneficial in treating melanoma. Through further in-depth studies of the underlying potential mechanisms, it can strengthen the applications of PBM for the therapy of melanoma.

Biomarkers for Diagnosis, Prognosis and Response to Immunotherapy in Melanoma

Simple Summary

Cutaneous Melanoma is a form of skin cancer characterized by an elevated mutational load that favors high spread to distant organs and resistance to therapies. The identification of biomarkers, able to dissect normal and pathogenic biological processes and response to therapeutic intervention, is necessary to describe melanoma as accurately as possible, having a positive impact on early diagnosis, in turn selecting the best therapeutic option. Recently, a great number of new biomarkers were evaluated, in order to identify those patients who may have clinical benefit from a therapeutic choice, particularly for immunotherapy. At present, these new biomarkers wait to be validated before clinical use. Hence, the requirement to look at and periodically update the advances in this field.

Abstract

Cutaneous Melanoma classification is constantly looking for specific and sensitive biomarkers capable of having a positive effect on diagnosis, prognosis and risk assessment, eventually affecting clinical outcome. Classical morphological, immunohistochemical and the well-known BRAF and NRAS genetic biomarkers do not allow the correct categorization of patients, being melanoma conditioned by high genetic heterogeneity. At the same time, classic prognostic methods are unsatisfactory. Therefore, new advances in omics and high-throughput analytical techniques have enabled the identification of numerous possible biomarkers, but their potentiality needs to be validated and standardized in prospective studies. Melanoma is considered an immunogenic tumor, being the first form of cancer to take advantage of the clinical use of the immune-checkpoint blockers. However, as immunotherapy is effective only in a limited number of patients, biomarkers associated with different responses are essential to select the more promising therapeutic approach and maximize clinical benefits. In this review, we summarize the most utilized biomarkers for Cutaneous Melanoma diagnosis, focusing on new prognostic and predictive biomarkers mainly associated with immunotherapy.

Identification of Genes Related to Immune Infiltration in the Tumor Microenvironment of Cutaneous Melanoma

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

Cutaneous melanoma: cost of illness under Brazilian health system perspectives

BACKGROUND

The landscape of cutaneous melanoma (CM) diagnosis, staging, prognosis, and treatment has undergone fundamental changes in the past decade. While the benefits of new health resources are recognized, there is a distinct lack of accurate cost-of-illness information to aid healthcare decision makers.

METHODS

The cost-of-illness study for CM was conducted from the perspective of two health systems in Brazil: the public health system (Unified Health System, SUS) and the private health system (Health Management Organization, HMO). The study considered the direct medical cost in a bottom-up analysis, using melanoma incidence, knowledge of the disease's progression, and the overall survival rates. The executional costs for the complete healthcare delivery cycle were investigated considering different disease stages and possible clinical course variations. The structural cost was assessed qualitatively considering the health value chain in Brazil.

RESULTS

CM represents a critical financial burden in Brazil, and the cost of illness varied according to the health system and by stage at diagnosis. HMO patient costs are approximately 10-fold and 90-fold more than a SUS patient in the early-stage and advanced disease, respectively. Overall, spending on advanced disease patients can be up to 34-fold (SUS) or 270-fold (HMO) higher than that required for the early-stage disease. Given the massive amount of resources spent by the SUS and HMO, significant efforts must be made to improve the health value chain to deliver the right mix of medical care goods and services using available resources.

CONCLUSION

The cost-of-illness study for CM has the potential to inform policymakers and decision-makers regarding the economic burden that melanoma impose on a society in terms of the use of health care services, assisting them in making projections of future health care costs and resource allocation decisions. We believe that cost-of-illness analysis from a strategic perspective could be of help in assessing executional costs and be used to support the change in structural costs required for long-term strategies related to the health value chain.

Innate Lymphoid Cells in the Malignant Melanoma Microenvironment

Simple Summary

Innate lymphoid cells (ILCs) are the innate counterparts of adaptive immune cells. Emerging data indicate that they are also key players in the progression of multiple tumors. In this review we briefly describe ILCs’ functions in the skin, lungs and liver. Next, we analyze the role of ILCs in primary cutaneous melanoma and in its most frequent and deadly metastases, those in liver and lung. We focus on their dual anti– and pro-tumoral functions, depending on the cross-interactions among them and with the surrounding stromal cells that form the tumor microenvironment (TME) in each organ. Next, we detail the role of extracellular vesicles secreted to the TME by ILCs and melanoma on both cell populations. We conclude that the identification of markers and tools to allow the modulation of individual ILC subsets, in addition to the development of standardized protocols, is essential for addressing the therapeutic modulation of ILCs.

Abstract

The role of innate lymphoid cells (ILCs) in cancer progression has been uncovered in recent years. ILCs are classified as Type 1, Type 2, and Type 3 ILCs, which are characterized by the transcription factors necessary for their development and the cytokines and chemokines they produce. ILCs are a highly heterogeneous cell population, showing both anti– and protumoral properties and capable of adapting their phenotypes and functions depending on the signals they receive from their surrounding environment. ILCs are considered the innate counterparts of the adaptive immune cells during physiological and pathological processes, including cancer, and as such, ILC subsets reflect different types of T cells. In cancer, each ILC subset plays a crucial role, not only in innate immunity but also as regulators of the tumor microenvironment. ILCs’ interplay with other immune and stromal cells in the metastatic microenvironment further dictates and influences this dichotomy, further strengthening the seed-and-soil theory and supporting the formation of more suitable and organ-specific metastatic environments. Here, we review the present knowledge on the different ILC subsets, focusing on their interplay with components of the tumor environment during the development of primary melanoma as well as on metastatic progression to organs, such as the liver or lung.

Tre2-Bub2-Cdc16 Family Proteins Based Nomogram Serve as a Promising Prognosis Predicting Model for Melanoma

Tre2-Bub2-Cdc16 (TBC) proteins are conserved in eukaryotic organisms and function as negative feedback dominating the GAPs for Rab GTPases, while the function of TBC proteins in melanoma remains unclear. In this study, we observed the differential expression of 33 TBC genes in TCGA datasets classified by clinical features. Seven prognostic-associated TBC genes were identified by LASSO Cox regression analysis. Mutation analysis revealed distinctive frequency alteration in the seven prognostic-associated TBCs between cases with high and low scores. High-risk score and cluster 1 based on LASSO Cox regression and consensus clustering analysis were relevant to clinical features and unfavorable prognosis. GSVA analysis showed that prognostic-associated TBCs were related to metabolism and protein transport signaling pathway. Correlation analysis indicated the relationship between the prognostic-associated TBCs with RAB family members, invasion-related genes and immune cells. The prognostic nomogram model was well established to predict survival in melanoma. What's more, interference of one of the seven TBC proteins TBC1D7 was confirmed to inhibit the proliferation, migration and invasion of melanoma cells in vitro. In summary, we preliminarily investigated the impact of TBCs on melanoma through multiple bioinformatics analysis and experimental validation, which is helpful for clarifying the mechanism of melanoma and the development of anti-tumor drugs.

Immune Microenvironment Related Competitive Endogenous RNA Network as Powerful Predictors for Melanoma Prognosis Based on WGCNA Analysis

Cutaneous melanoma is the most life-threatening skin malignant tumor due to its increasing metastasis and mortality rate. The abnormal competitive endogenous RNA network promotes the development of tumors and becomes biomarkers for the prognosis of various tumors. At the same time, the tumor immune microenvironment (TIME) is of great significance for tumor outcome and prognosis. From the perspective of TIME and ceRNA network, this study aims to explain the prognostic factors of cutaneous melanoma systematically and find novel and powerful biomarkers for target therapies. We obtained the transcriptome data of cutaneous melanoma from The Cancer Genome Atlas (TCGA) database, 3 survival-related mRNAs co-expression modules and 2 survival-related lncRNAs co-expression modules were identified through weighted gene co-expression network analysis (WCGNA), and 144 prognostic miRNAs were screened out by univariate Cox proportional hazard regression. Cox regression model and Kaplan-Meier survival analysis were employed to identify 4 hub prognostic mRNAs, and the prognostic ceRNA network consisting of 7 lncRNAs, 1 miRNA and 4 mRNAs was established. After analyzing the composition and proportion of total immune cells in cutaneous melanoma microenvironment through CIBERSORT algorithm, it is found through correlation analysis that lncRNA-TUG1 in the ceRNA network was closely related to the TIME. In this study, we first established cutaneous melanoma’s TIME-related ceRNA network by WGCNA. Cutaneous melanoma prognostic markers have been identified from multiple levels, which has important guiding significance for clinical diagnosis, treatment, and further scientific research on cutaneous melanoma.

Predicting the Risk of Melanoma Metastasis Using an Immune Risk Score in the Melanoma Cohort

Melanoma is a highly aggressive cancer, attracting increasing attention worldwide. The 5-year survival rate of patients with metastatic melanoma is low. Therefore, it is critical to identify potential effective biomarkers for diagnosis of melanoma metastasis. In the present study, the melanoma cohort and immune genes were obtained from the Cancer Genome Atlas (TCGA) database and the ImmPort database, respectively. Then, we constructed the immune risk score (IRS) using univariate and multivariate logistic analysis. The area under the curve (AUC) of IRS in sequencing samples and the initial diagnosis patients was 0.90 and 0.80, respectively. Besides, IRS could add benefits for metastasis diagnosis. For sequencing samples, IRS (OR = 16.35, 95% CI = 8.74–30.59) increased the odds for melanoma metastasis. Similar results were obtained in the initial diagnosis patients (OR = 8.93, 95% CI = 3.53–22.61). A composite nomogram was built based on IRS and clinical information with well-fitted calibration curves. We further used other independent melanoma cohorts from Gene Expression Omnibus (GEO) databases to confirm the reliability and validity of the IRS (AUC > 0.75, OR > 1.04, and P value < 0.01 in all cohorts). In conclusion, IRS is significantly associated with melanoma metastasis and can be a novel effective signature for predicting the metastasis risk.

Development and in-vitro evaluation of co-loaded berberine chloride and evodiamine ethosomes for treatment of melanoma

Berberine chloride (BBR) and evodiamine (EVO) are two main active ingredients of "ZuoJinWan", a classical Chinese herbal medicine, and these compounds are known to have a synergistic inhibitory effect on various cancer cell lines. Several recent studies have reported anti-melanoma effects for both BBR and EVO. However, topical delivery of the two compounds has been challenging, due to their poor aqueous solubility and their low skin penetration. In the current study, we have combined BBR and EVO into an ethosomes delivery system with the future aim to design a novel topical anti-melanoma formulation. The ethosomes formulations were characterized using particle size, entrapment efficiency and an in vitro skin drug deposition study. The ethosome formulation displaying maximum drug deposition in the epidermis was selected for further study. This formulation contained ethosomes with mean size of 171 nm and 90% or above entrapment efficiency for both BBR and EVO. Cell viability tests proved the optimized ethosomes increased the inhibitory effect on B16 melanoma cells. These results corroborate that ethosomes containing a combination of BBR and EVO are a promising delivery system for potential use in melanoma therapy.

Curcumol inhibits the proliferation and metastasis of melanoma via the miR-152-3p/PI3K/AKT and ERK/NF-κB signaling pathways

Melanoma is the most aggressive and treatment-resistant form of skin cancer. Curcumol is a Chinese medicinal herb traditionally used as a cancer remedy. However, the molecular mechanisms underlying the anticancer activity of curcumol in melanoma remains largely unknown. In the present study, we observed that Curcumol decreased mouse melanoma B16 cell proliferation and migration. The xenograft tumor assay showed that curcumol reduced melanoma volume and lung metastasis. Curcumol upregulated the expression of E-cadherin and downregulated the expression of N-cadherin, MMP2 and MMP9 in mouse melanoma B16 cell. Western blot analysis revealed that curcumol reduced the translocation of p65 to the nucleus and decreased p-ERK. Furthermore, curcumol attenuated c-MET, P13K and p-AKT protein expression and upregulated miR-152-3p gene expression. The dual-luciferase reporter assay indicated that c-MET was a target gene of miR-152-3p. Reduced expression of miR-152-3p partially attenuated the effect of curcumol on mouse melanoma B16 cell proliferation and migration. The decrease in c-MET, P13K and p-AKT protein expression following curcumol treatment in mouse melanoma B16 cells was notably attenuated by the miR-152-3p inhibitor. Taken together, our findings suggested that curcumol attenuated melanoma progression and concomitantly suppressed ERK/NF-κB signaling and promoted miR-152-3p expression to inactivate the c-MET/PI3K/AKT signaling pathway.

Bioinformatics Analysis Identifies MicroRNAs and Target Genes Associated with Prognosis in Patients with Melanoma

Background

Melanoma of the skin can be associated with early metastases and poor prognosis. This study aimed to identify microRNAs (miRNAs) and target genes associated with prognosis in melanoma using bioinformatics analysis.

Material/Methods

The Gene Expression Omnibus (GEO) database identified the microarray dataset GSE20994. Differentially expressed miRNAs (DE-miRNAs) were first identified using R language software and validated by GEO2R. Potential target genes of DE-miRNAs were screened, and their targets and prognostic role were evaluated in the miRTarBase database. Pathway enrichment and functional annotation analysis for target genes were established using the DAVID database. miRNA-hub gene networks and protein-protein interaction (PPI) networks were constructed and visualized using the STRING database and Cytoscape. Kaplan-Meier survival curves were constructed using transcriptome and survival data from the UALCAN web tool.

Results

There were 132 upregulated and 134 down-regulated DE-miRNAs identified from human melanoma samples. From the top three upregulated miRNAs, there were 580 potential predicted target genes, and from the top three down-regulated miRNAs, there 543 potential predicted target genes. miR-300 was upregulated, and miR-629 was down-regulated in melanoma. Two pivotal bub genes, TP53 and GAPDH, were identified in the PPI network. Five out of ten hub genes were modulated by upregulated miR-580, and five by miR-629. Increased mRNA expression of DAPK2 was associated with increased OS, and increased mRNA expression of SKCM, TECPR2, and ZNF781 were associated with reduced OS.

Conclusions

Bioinformatics analysis identified miRNAs and target genes associated with melanoma that may represent potential prognostic and therapeutic biomarkers.

Comprehensive Analysis of a Competing Endogenous RNA Network Identifies Seven-lncRNA Signature as a Prognostic Biomarker for Melanoma

Long non-coding RNAs (LncRNAs) can act as competing endogenous RNA (ceRNA) involving in tumor initiation and progression. Nevertheless, the prognostic roles of lncRNAs in lncRNA-related ceRNA network of melanoma remain elusive. In this study, RNA sequence profiles were downloaded from The Cancer Genome Atlas (TCGA) database, and there were 2020 differentially expressed messenger RNAs (DEmRNAs), 438 differentially expressed lncRNAs (DElncRNAs) and 65 differentially expressed microRNAs (DEmiRNAs) between primary and metastasis melanoma patients. A ceRNA regulatory network was constructed based on the DElncRNAs-DEmiRNAs and DEmiRNAs-DEmRNAs interactions, which contained 39 lncRNAs, 10 miRNAs, and 16 mRNAs. Furthermore, univariate and multivariate Cox regression analysis were carried out to establish a 7-lncRNA prognostic signature. Subsequently, the area under the curve (AUC) value of the receiver operating characteristic (ROC) curve and the Kaplan-Meier risk survival analysis revealed the significant performance of this signature. Finally, pathway enrichment analyses implied that lncRNA MIR205HG and MIAT were associated with multiple cancer-related pathways, especially epidermis development and immune response. The current study provides novel insights into the lncRNA-related ceRNA network and the potential of lncRNAs to be candidate prognostic biomarkers and therapeutic targets in melanoma.

Melanoma Following In Vitro Fertilization: Co-incident or Coincidence?

Melanoma may occur during or after natural or in vitro fertilization-associated pregnancy. A 43-year-old woman, who had received in vitro fertilization and developed a melanoma five months postpartum is described. Some studies have not shown in vitro fertilization to increase melanoma risk; however, several investigations have observed melanoma risk to be greater in women who have had this treatment. Therefore, although a potential increased risk for melanoma has been observed in infertile women who were either pregnant before or following in vitro fertilization, whether in vitro fertilization is an etiologic risk factor in the pathogenesis of melanoma for these individuals-or is merely a coincidental event-remains to be established.

HSV-1 single-cell analysis reveals the activation of anti-viral and developmental programs in distinct sub-populations

Viral infection is usually studied at the population level by averaging over millions of cells. However, infection at the single-cell level is highly heterogeneous, with most infected cells giving rise to no or few viral progeny while some cells produce thousands. Analysis of Herpes Simplex virus 1 (HSV-1) infection by population-averaged measurements has taught us a lot about the course of viral infection, but has also produced contradictory results, such as the concurrent activation and inhibition of type I interferon signaling during infection. Here, we combine live-cell imaging and single-cell RNA sequencing to characterize viral and host transcriptional heterogeneity during HSV-1 infection of primary human cells. We find extreme variability in the level of viral gene expression among individually infected cells and show that these cells cluster into transcriptionally distinct sub-populations. We find that anti-viral signaling is initiated in a rare group of abortively infected cells, while highly infected cells undergo cellular reprogramming to an embryonic-like transcriptional state. This reprogramming involves the recruitment of β-catenin to the host nucleus and viral replication compartments, and is required for late viral gene expression and progeny production. These findings uncover the transcriptional differences in cells with variable infection outcomes and shed new light on the manipulation of host pathways by HSV-1.

N-Glycosylation in progression of skin cancer

Skin cancer can be classified as cutaneous malignant melanoma, basal cell carcinoma, and squamous cell carcinoma. Due to the high level of morbidity and mortality, skin cancer has become a global public health issue worldwide while the pathogenesis of skin cancer is still unclear. It is necessary to further identify the pathogenesis of skin cancer and find candidate targets to diagnose and treat skin cancer. A variety of factors are known to be associated with skin cancer including N-glycosylation, which partly explained the malignant behaviors of skin cancer. In this review, we retrieved databases such as PubMed and Web of Science to elucidate its relationship between glycosylation and skin cancer. We summarized some key glycosyltransferases and proteins during the process of N-glycosylation related to skin cancer, which was helpful to unmask the additional mechanism of skin cancer and find some novel targets of skin cancer.