Single cell analysis to dissect molecular heterogeneity and disease evolution in metastatic melanoma

Tumor-infiltrating lymphocytes as a prognostic and predictive factor for Melanoma

INTRODUCTION

Tumor-infiltrating lymphocytes (TILs) have been investigated as prognostic factors in melanoma. Recent advancements in assessing the tumor microenvironment in the setting of more widespread use of immune checkpoint blockade have reignited interest in identifying predictive biomarkers. This review examines the function and significance of TILs in cutaneous melanoma, evaluating their potential as prognostic and predictive markers.

AREAS COVERED

A literature search was conducted on papers covering tumor infiltrating lymphocytes in cutaneous melanoma available online in PubMed and Web of Science from inception to 1 December 2023, supplemented by citation searching. This article encompasses the assessment of TILs, the role of TILs in the immune microenvironment, TILs as a prognostic factor, TILs as a predictive factor for immunotherapy response, and clinical applications of TILs in the treatment of cutaneous melanoma.

EXPERT OPINION

Tumor-infiltrating lymphocytes play a heterogeneous role in cutaneous melanoma. While they have historically been associated with improved survival, their status as independent prognostic or predictive factors remains uncertain. Novel methods of TIL assessment, such as determination of TIL subtypes and molecular signaling, demonstrate potential for predicting therapeutic response. Further, while their clinical utility in risk-stratification in melanoma treatment shows promise, a lack of consensus data hinders standardized application.

Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses

Background

Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with a discernible rise in prevalence among younger cohorts observed in recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated.

Methods

We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize the tumor epithelial cells derived from four specimens of cervical carcinoma (CC) patients. This method enabled the identification of pivotal subpopulations of tumor epithelial cells and elucidation of their contributions to CC progression. Subsequently, we assessed the influence of associated molecules in bulk RNA sequencing (Bulk RNA-seq) cohorts and performed cellular experiments for validation purposes.

Results

Through our analysis, we have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as a noteworthy subpopulation in cervical carcinoma (CC), exerting a pivotal influence on the differentiation and progression of CC. We have established an independent prognostic indicator-the PLP2+ Tumor EPCs score. By stratifying patients into high and low score groups based on the median score, we have observed that the high-score group exhibits diminished survival rates compared to the low-score group. The correlations observed between these groups and immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, among other factors, further underscore their impact on CC prognosis. Cellular experiments have validated the significant impact of ATF6 on the proliferation and migration of CC cell lines.

Conclusion

This study enriches our comprehension of the determinants shaping the progression of CC, elevates cognizance of the tumor microenvironment in CC, and offers valuable insights for prospective CC therapies. These discoveries contribute to the refinement of CC diagnostics and the formulation of optimal therapeutic approaches.

scROSHI: robust supervised hierarchical identification of single cells

Identifying cell types based on expression profiles is a pillar of single cell analysis. Existing machine-learning methods identify predictive features from annotated training data, which are often not available in early-stage studies. This can lead to overfitting and inferior performance when applied to new data. To address these challenges we present scROSHI, which utilizes previously obtained cell type-specific gene lists and does not require training or the existence of annotated data. By respecting the hierarchical nature of cell type relationships and assigning cells consecutively to more specialized identities, excellent prediction performance is achieved. In a benchmark based on publicly available PBMC data sets, scROSHI outperforms competing methods when training data are limited or the diversity between experiments is large.

Identification of immune subtypes of melanoma based on single-cell and bulk RNA sequencing data

The tumor microenvironment plays a crucial role in melanoma. In this study, the abundance of immune cells in melanoma samples was assessed and analyzed using single sample gene set enrichment analysis (ssGSEA), and the predictive value of immune cells was assessed using univariate COX regression analysis. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression analysis was applied to construct an immune cell risk score (ICRS) model with a high predictive value for identifying the immune profile of melanoma patients. The pathway enrichment between the different ICRS groups was also elucidated. Next, five hub genes for diagnosing the prognosis of melanoma were screened by two machine learning algorithms, LASSO and random forest. The distribution of hub genes in immune cells was analyzed on account of Single-cell RNA sequencing (scRNA-seq), and the interaction between genes and immune cells was elucidated by cellular communication. Ultimately, the ICRS model on account of two types of immune cells (Activated CD8 T cell and Immature B cell) was constructed and validated, which can determine melanoma prognosis. In addition, five hub genes were identified as potential therapeutic targets affecting the prognosis of melanoma patients.

Oncosuppressive miRNAs loaded in lipid nanoparticles potentiate targeted therapies in BRAF-mutant melanoma by inhibiting core escape pathways of resistance

BRAF-mutated melanoma relapsing after targeted therapies is an aggressive disease with unmet clinical need. Hence the need to identify novel combination therapies able to overcome drug resistance. miRNAs have emerged as orchestrators of non-genetic mechanisms adopted by melanoma cells to challenge therapies. In this context we previously identified a subset of oncosuppressor miRNAs downregulated in drug-resistant melanomas. Here we demonstrate that lipid nanoparticles co-encapsulating two of them, miR-199-5p and miR-204-5p, inhibit tumor growth both in vitro and in vivo in combination with target therapy and block the development of drug resistance. Mechanistically they act by directly reducing melanoma cell growth and also indirectly by hampering the recruitment and reprogramming of pro-tumoral macrophages. Molecularly, we demonstrate that the effects on macrophages are mediated by the dysregulation of a newly identified miR-204-5p-miR-199b-5p/CCL5 axis. Finally, we unveiled that M2 macrophages programs are molecular signatures of resistance and predict response to therapy in patients. Overall, these findings have strong translational implications to propose new combination therapies making use of RNA therapeutics for metastatic melanoma patients.

Case report: Real-world experience using a personalized cancer-specific circulating tumor DNA assay in different metastatic melanoma scenarios

Circulating-tumor DNA (ctDNA) has emerged as an important biomarker for monitoring disease status in cancer patients. Different ctDNA testing platforms have shown promising results in the early detection of disease, monitoring response to treatment, and prognostication in metastatic melanoma. However, several challenges exist, including the reduced shedding of ctDNA into the bloodstream in the metastatic setting, differences in sensitivity among various ctDNA assays, and the inherent inability to distinguish tumor-specific mutations from other mutations that are not related to the cancer of interest. Using a ctDNA assay that is designed to detect multiple single-nucleotide variants (SNVs) that are specific to the tumor itself may allow for more accurate monitoring of disease status in metastatic melanoma. In this case series, we describe a real-world experience using a personalized, tumor-informed ctDNA assay to monitor the clinical trajectories of four patients with metastatic melanoma. Our report highlights potential benefits and limitations using ctDNA in this setting to inform clinical decision-making. This report provides a proof of concept of the technique using an mPCR-NGS-based ctDNA assay (Signatera TM) in the clinical context and in adjunct with other radiological information. Large cohort prospective trials would be needed to validate the utility and validity of this approach.

The future of targeted kinase inhibitors in melanoma

Melanoma is a cancer of the pigment-producing cells of the body and its incidence is rising. Targeted inhibitors that act against kinases in the MAPK pathway are approved for BRAF-mutant metastatic cutaneous melanoma and increase patients' survival. Response to these therapies is limited by drug resistance and is less durable than with immune checkpoint inhibition. Conversely, rare melanoma subtypes have few therapeutic options for advanced disease and MAPK pathway targeting agents show minimal anti-tumor effects. Nevertheless, there is a future for targeted kinase inhibitors in melanoma: in new applications such as adjuvant or neoadjuvant therapy and in novel combinations with immunotherapies or other targeted therapies. Pre-clinical studies continue to identify tumor dependencies and their corresponding actionable drug targets, paving the way for rational targeted kinase inhibitor combinations as a personalized medicine approach for melanoma.

The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution

Cutaneous melanoma is a highly immunogenic malignancy that is surgically curable at early stages but life-threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially resolved microregion transcriptomics to study immune evasion and immunoediting in primary melanoma. We find that recurrent cellular neighborhoods involving tumor, immune, and stromal cells change significantly along a progression axis involving precursor states, melanoma in situ, and invasive tumor. Hallmarks of immunosuppression are already detectable in precursor regions. When tumors become locally invasive, a consolidated and spatially restricted suppressive environment forms along the tumor-stromal boundary. This environment is established by cytokine gradients that promote expression of MHC-II and IDO1, and by PD1-PDL1-mediated cell contacts involving macrophages, dendritic cells, and T cells. A few millimeters away, cytotoxic T cells synapse with melanoma cells in fields of tumor regression. Thus, invasion and immunoediting can coexist within a few millimeters of each other in a single specimen.

SIGNIFICANCE

The reorganization of the tumor ecosystem in primary melanoma is an excellent setting in which to study immunoediting and immune evasion. Guided by classic histopathology, spatial profiling of proteins and mRNA reveals recurrent morphologic and molecular features of tumor evolution that involve localized paracrine cytokine signaling and direct cell-cell contact. This article is highlighted in the In This Issue feature, p. 1397.

Intercellular Communication-Related Molecular Subtypes and a Gene Signature Identified by the Single-Cell RNA Sequencing Combined with a Transcriptomic Analysis

Background. The tumor microenvironment (TME) of lung adenocarcinoma (LUAD) comprise various cell types that communicate with each other through ligand-receptor interactions. This study focused on the identification of cell types in LUAD by single-cell RNA sequencing (scRNA-seq) data and screening of intercellular communication-related genes. Methods. The Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo) provided the RNA-seq data of LUAD patients in the GSE149655, GSE31210, and GSE72094 datasets. Quality control of the scRNA-seq data in GSE149655 was performed by the Seurat package (http://seurat.r-forge.r-project.org) for identifying highly variable genes for principal component analysis (PCA) and cell clustering. The CellPhoneDB (http://www.cellphonedb.org) was used for filtering intercellular communication-related ligand-receptor pairs. According to ligand and receptor expressions, LUAD samples were clustered using ConsensusClusterPlus (https://www.bioconductor.org/packages/release/bioc/html/ConsensusClusterPlus). Additionally, the identification of prognosis-related ligand and receptor genes was conducted along with the development of a risk prediction model by the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results. This study identified twelve cell types in 8170 cells of LUAD tissues along with 219 ligand and receptor genes. LUAD was classified into three different molecular subtypes, among which cluster 3 (C3) had the longest overall survival (OS) time and cluster (C1) had the shortest OS time. In comparison with the other two molecular subtypes, it was observed that C1 had a higher rate of somatic mutations and lower levels of infiltrating immune cells and immune scores. Ten genes were screened from the total ligand and receptor genes to construct a risk model, which showed a strong prediction power in the prognosis of patients with LUAD. Conclusion. The results of this study revealed cell types specific to LUAD, which were classified into different molecular subtypes according to intercellular communication-related genes. A novel prognostic risk model was developed in this study, providing new insights into prognostic assessment models for LUAD.

NRF3 Decreases during Melanoma Carcinogenesis and Is an Independent Prognostic Marker in Melanoma

The prognostic significance of the major redox regulator, nuclear factor erythroid-2-related factor 2 (NRF2), is recognized in many cancers, but the role of NRF3 is not studied. Analysis from the Gene Expression Omnibus datasets showed that NRF3 mRNA levels increased from benign to dysplastic naevi (p = 0.04). We characterized the immunohistochemical expression of NRF3 in 81 naevi, 67 primary skin melanomas, and 51 lymph node metastases. The immunohistochemical expression of cytoplasmic NRF3 decreased from benign to dysplastic naevi (p < 0.001) and further to primary melanomas (p < 0.001). High cytoplasmic NRF3 protein expression in pigment cells of the primary melanomas associated with worse melanoma-specific survival in multivariate analysis, specifically in the subgroup of patients with the lymph node metastases at the time of diagnosis (hazard ratio 3.179; 95% confidence interval 1.065-9.493; p = 0.038). Intriguingly, we did not observe associations between NRF3 and the traditional prognostic factors such as Breslow thickness, ulceration, or stage. Together, this data represents the primary description about the role of NRF3 in pigment tumours that is worthy of further explorations.

Evidence that the transcriptional repressor ICER is regulated via the N-end rule for ubiquitination

ICER is a transcriptional repressor that is mono- or poly-ubiquitinated. This either causes ICER to be translocated from the nucleus, or degraded via the proteasome, respectively. In order to further studies the proteins involved in ICER regulation mass spectrometry analysis was performed to identify potential candidates. We identified twenty eight ICER-interacting proteins in human melanoma cells, Sk-Mel-24. In this study we focus on two proteins with potential roles in ICER proteasomal degradation in response to the N-end rule for ubiquitination: the N-alpha-acetyltransferase 15 (NAA15) and the E3 ubiquitin-protein ligase UBR4. Using an HA-tag on the N- or C-terminus of ICER (_NHAICER or ICER_CHA) it was found that the N-terminus of ICER is important for its interaction to UBR4, whereas NARG1 interaction is independent of HA-tag position. Silencing RNA experiments show that both NAA15 and UBR4 up-regulates ICER levels and that ICER's N-terminus is important for this regulation. The N-terminus of ICER was found to have dire consequences on its regulation by ubiquitination and cellular functions. The half-life of _NHAICER was found to be about twice as long as ICER_CHA. Polyubiquitination of ICER was found to be dependent on its N-terminus and mediated by UBR4. This data strongly suggests that ICER is ubiquitinated as a response to the N-end rule that governs protein degradation rate through recognition of the N-terminal residue of proteins. Furthermore, we found that _NHAICER inhibits transcription two times more efficiently than ICER_CHA, and causes apoptosis 5 times more efficiently than ICER_CHA. As forced expression of ICER has been shown before to block cells in mitosis, our data represent a potentially novel mechanism for apoptosis of cells in mitotic arrest.

Revisiting miRNA Association with Melanoma Recurrence and Metastasis from a Machine Learning Point of View

The diagnostic and prognostic value of miRNAs in cutaneous melanoma (CM) has been broadly studied and supported by advanced bioinformatics tools. From early studies using miRNA arrays with several limitations, to the recent NGS-derived miRNA expression profiles, an accurate diagnostic panel of a comprehensive pre-specified set of miRNAs that could aid timely identification of specific cancer stages is still elusive, mainly because of the heterogeneity of the approaches and the samples. Herein, we summarize the existing studies that report several miRNAs as important diagnostic and prognostic biomarkers in CM. Using publicly available NGS data, we analyzed the correlation of specific miRNA expression profiles with the expression signatures of known gene targets. Combining network analytics with machine learning, we developed specific non-linear classification models that could successfully predict CM recurrence and metastasis, based on two newly identified miRNA signatures. Subsequent unbiased analyses and independent test sets (i.e., a dataset not used for training, as a validation cohort) using our prediction models resulted in 73.85% and 82.09% accuracy in predicting CM recurrence and metastasis, respectively. Overall, our approach combines detailed analysis of miRNA profiles with heuristic optimization and machine learning, which facilitates dimensionality reduction and optimization of the prediction models. Our approach provides an improved prediction strategy that could serve as an auxiliary tool towards precision treatment.

Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis-and what ceases to work in diverse dermatological diseases-have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-the-art of skin biology using single-cell technologies, with a special focus on skin pathologies and the translation of mechanistic findings to the clinic. The main implications of this review are to summarize the benefits and limitations of single-cell analysis and thus help translate the emerging insights from these novel techniques to the bedside.

Single-Cell RNA Sequencing Reveals Multiple Pathways and the Tumor Microenvironment Could Lead to Chemotherapy Resistance in Cervical Cancer

Background

Cervical cancer is one of the most common gynecological cancers worldwide. The tumor microenvironment significantly influences the therapeutic response and clinical outcome. However, the complex tumor microenvironment of cervical cancer and the molecular mechanisms underlying chemotherapy resistance are not well studied. This study aimed to comprehensively analyze cells from pretreated and chemoresistant cervical cancer tissues to generate a molecular census of cell populations.

Methods

Biopsy tissues collected from patients with cervical squamous cell carcinoma, cervical adenocarcinoma, and chronic cervicitis were subjected to single-cell RNA sequencing using the 10× Genomics platform. Unsupervised clustering analysis of cells was performed to identify the main cell types, and important cell clusters were reclustered into subpopulations. Gene expression profiles and functional enrichment analysis were used to explore gene expression and functional differences between cell subpopulations in cervicitis and cervical cancer samples and between chemoresistant and chemosensitive samples.

Results

A total of 24,371 cells were clustered into nine separate cell types, including immune and non-immune cells. Differentially expressed genes between chemoresistant and chemosensitive patients enriched in the phosphoinositide 3-kinase (PI3K)/AKT pathway were involved in tumor development, progression, and apoptosis, which might lead to chemotherapy resistance.

Conclusions

Our study provides a comprehensive overview of the cancer microenvironment landscape and characterizes its gene expression and functional difference in chemotherapy resistance. Consequently, our study deepens the insights into cervical cancer biology through the identification of gene markers for diagnosis, prognosis, and therapy.

Radiotherapy in the Treatment of Subcutaneous Melanoma

Simple Summary

The non-surgical treatment of cutaneous and/or subcutaneous melanoma lesions involves a multitude of local treatments, including radiotherapy. This is often used when other local methods fail, and there are currently no clear guidelines or evidence-based recommendations to support its use in this setting. This review, collecting the retrospective and prospective experiences on radiotherapy alone or in combination with other methods, aims to provide a scenario of the possible advantages and disadvantages related to its use in the treatment of skin/subcutaneous melanoma lesions.

Abstract

Malignant melanoma frequently develops cutaneous and/or subcutaneous metastases during the course of the disease. These may present as non-nodal locoregional metastases (microsatellite, satellite, or in-transit) included in stage III or as distant metastases in stage IV. Their presentation is heterogeneous and associated with significant morbidity resulting from both disease-related functional damage and treatment side effects. The standard treatment is surgical excision, whereas local therapies or systemic therapies have a role when surgery is not indicated. Radiotherapy can be used in the local management of ITM, subcutaneous relapses, or distant metastases to provide symptom relief and prolong regional disease control. To increase the local response without increasing toxicity, the addition of hyperthermia and intralesional therapies to radiotherapy appear to be very promising. Boron neutron capture therapy, based on nuclear neutron capture and boron isotope fission reaction, could be an alternative to standard treatments, but its use in clinical practice is still limited. The potential benefit of combining radiotherapy with targeted therapies and immunotherapy has yet to be explored in this lesion setting. This review explores the role of radiotherapy in the treatment of cutaneous and subcutaneous lesions, its impact on outcomes, and its association with other treatment modalities.

High-Dimensional Single-Cell Transcriptomics in Melanoma and Cancer Immunotherapy

Recent advances in single-cell transcriptomics have greatly improved knowledge of complex transcriptional programs, rapidly expanding our knowledge of cellular phenotypes and functions within the tumour microenvironment and immune system. Several new single-cell technologies have been developed over recent years that have enabled expanded understanding of the mechanistic cells and biological pathways targeted by immunotherapies such as immune checkpoint inhibitors, which are now routinely used in patient management with high-risk early-stage or advanced melanoma. These technologies have method-specific strengths, weaknesses and capabilities which need to be considered when utilising them to answer translational research questions. Here, we provide guidance for the implementation of single-cell transcriptomic analysis platforms by reviewing the currently available experimental and analysis workflows. We then highlight the use of these technologies to dissect the tumour microenvironment in the context of cancer patients treated with immunotherapy. The strategic use of single-cell analytics in clinical settings are discussed and potential future opportunities are explored with a focus on their use to rationalise the design of novel immunotherapeutic drug therapies that will ultimately lead to improved cancer patient outcomes.

Single-cell trajectories of melanoma cell resistance to targeted treatment

OBJECTIVE

Cellular heterogeneity is regarded as a major factor affecting treatment response and resistance in malignant melanoma. Recent developments in single-cell sequencing technology have provided deeper insights into these mechanisms.

METHODS

Here, we analyzed a BRAFV600E-mutant melanoma cell line by single-cell RNA-seq under various conditions: cells sensitive to BRAF inhibition with BRAF inhibitor vemurafenib and cells resistant to BRAF inhibition with vemurafenib alone or vemurafenib in combination with the MEK1/2 inhibitors cobimetinib or trametinib. Dimensionality reduction by t-distributed stochastic neighbor embedding and self-organizing maps identified distinct trajectories of resistance development clearly separating the 4 treatment conditions in cell and gene state space.

RESULTS

Trajectories associated with resistance to single-agent treatment involved cell cycle, extracellular matrix, and de-differentiation programs. In contrast, shifts detected in double-resistant cells primarily affected translation and mitogen-activated protein kinase pathway reactivation, with a small subpopulation showing markers of pluripotency. These findings were validated in pseudotime analyses and RNA velocity measurements.

CONCLUSIONS

The single-cell transcriptomic analyses reported here employed a spectrum of bioinformatics methods to identify mechanisms of melanoma resistance to single- and double-agent treatments. This study deepens our understanding of treatment-induced cellular reprogramming and plasticity in melanoma cells and identifies targets of potential relevance to the management of treatment resistance.

Single-Cell Transcriptome Analysis in Melanoma Using Network Embedding

Single-cell sequencing technology provides insights into the pathology of complex diseases like cancer. Here, we proposed a novel computational framework to explore the molecular mechanisms of cancer called melanoma. We first constructed a disease-specific cell–cell interaction network after data preprocessing and dimensionality reduction. Second, the features of cells in the cell–cell interaction network were learned by node2vec which is a graph embedding technology proposed previously. Then, consensus clusters were identified by considering different clustering algorithms. Finally, cell markers and cancer-related genes were further analyzed by integrating gene regulation pairs. We exploited our model on two independent datasets, which showed interesting results that the differences between clusters obtained by consensus clustering based on network embedding (CCNE) were observed obviously through visualization. For the KEGG pathway analysis of clusters, we found that all clusters are extremely related to MicroRNAs in cancer and HTLV-I infection, and the hub genes in cluster specific regulatory networks, i.e., ETS1, TP53, E2F1, and GATA3 are highly associated with melanoma. Furthermore, our method can also be extended to other scRNA-seq data.

The human melanoma proteome atlas-Defining the molecular pathology

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.

Diagnostic and prognostic potential of the proteomic profiling of serum-derived extracellular vesicles in prostate cancer

Extracellular vesicles (EVs) and their cargo represent an intriguing source of cancer biomarkers for developing robust and sensitive molecular tests by liquid biopsy. Prostate cancer (PCa) is still one of the most frequent and deadly tumor in men and analysis of EVs from biological fluids of PCa patients has proven the feasibility and the unprecedented potential of such an approach. Here, we exploited an antibody-based proteomic technology, i.e. the Reverse-Phase Protein microArrays (RPPA), to measure key antigens and activated signaling in EVs isolated from sera of PCa patients. Notably, we found tumor-specific protein profiles associated with clinical settings as well as candidate markers for EV-based tumor diagnosis. Among others, PD-L1, ERG, Integrin-β5, Survivin, TGF-β, phosphorylated-TSC2 as well as partners of the MAP-kinase and mTOR pathways emerged as differentially expressed endpoints in tumor-derived EVs. In addition, the retrospective analysis of EVs from a 15-year follow-up cohort generated a protein signature with prognostic significance. Our results confirm that serum-derived EV cargo may be exploited to improve the current diagnostic procedures while providing potential prognostic and predictive information. The approach proposed here has been already applied to tumor entities other than PCa, thus proving its value in translational medicine and paving the way to innovative, clinically meaningful tools.

Discrimination of melanoma cell lines with Fourier Transform Infrared (FTIR) spectroscopy

Among skin cancers, melanoma is the lethal form and the leading cause of death in humans. Melanoma begins in melanocytes and is curable at early stages. Thus, early detection and evaluation of its metastatic potential are crucial for effective clinical intervention. Fourier transform infrared (FTIR) spectroscopy has gained considerable attention due to its versatility in detecting biochemical and biological features present in the samples. Changes in these features are used to differentiate between samples at different stages of the disease. Previously, FTIR spectroscopy has been mostly used to distinguish between healthy and diseased conditions. With this study, we aim to discriminate between different melanoma cell lines based on their FTIR spectra. Formalin-fixed paraffin embedded samples from three melanoma cell lines (IPC-298, SK-MEL-30 and COLO-800) were used. Statistically significant differences were observed in the prominent spectral bands of three cell lines along with shifts in peak positions. A partial least square discriminant analysis (PLS-DA) model built for the classification of three cell lines showed an overall accuracy of 92.6% with a sensitivity of 85%, 95.75%, 96.54%, and specificity of 97.80%, 92.14%, 98.64% for the differentiation of IPC-298, SK-MEL-30, and COLO-800, respectively. The results suggest that FTIR spectroscopy can differentiate between different melanoma cell lines and thus potentially characterize the metastatic potential of melanoma.

Noncontact Multiphysics Probe for Spatiotemporal Resolved Single-Cell Manipulation and Analyses

Heterogeneity and spatial arrangement of individual cells within tissues are critical to the identity of the host multicellular organism. While current single-cell techniques are capable of resolving heterogeneity, they mostly rely on extracting target cells from their physiological environment and hence lose the spatiotemporal resolution required for understanding cellular networks. Here, a multifunctional noncontact scanning probe that can precisely perform multiple manipulation procedures on living single-cells, while within their physiological tissue environment, is demonstrated. The noncontact multiphysics probe (NMP) consists of fluidic apertures and "hump" shaped electrodes that simultaneously confine reagents and electric signals with a single-cell resolution. The NMP's unique electropermealization-based approach in transferring macromolecules through the cell membrane is presented. The technology's adjustable spatial ability is demonstrated by transfecting adjacent single-cells with different DNA plasmid vectors. The NMP technology also opens the door for controllable cytoplasm extraction from living single-cells. This powerful application is demonstrated by executing multiple time point biopsies on adherent cells without affecting the integrity of the extracted macromolecules or the viability of cells. Furthermore, the NMP's function as an electro-thermal based microfluidic whole-cell tweezer is reported. This work offers a multifunctional tool with unprecedented probing features for spatiotemporal single-cell analysis within tissue samples.

Overcoming Resistance to Tumor-Targeted and Immune-Targeted Therapies

Resistance to anticancer therapies includes primary resistance, usually related to lack of target dependency or presence of additional targets, and secondary resistance, mostly driven by adaptation of the cancer cell to the selection pressure of treatment. Resistance to targeted therapy is frequently acquired, driven by on-target, bypass alterations, or cellular plasticity. Resistance to immunotherapy is often primary, orchestrated by sophisticated tumor-host-microenvironment interactions, but could also occur after initial efficacy, mostly when only partial responses are obtained. Here, we provide an overview of resistance to tumor and immune-targeted therapies and discuss challenges of overcoming resistance, and current and future directions of development. SIGNIFICANCE: A better and earlier identification of cancer-resistance mechanisms could avoid the use of ineffective drugs in patients not responding to therapy and provide the rationale for the administration of personalized drug associations. A clear description of the molecular interplayers is a prerequisite to the development of novel and dedicated anticancer drugs. Finally, the implementation of such cancer molecular and immunologic explorations in prospective clinical trials could de-risk the demonstration of more effective anticancer strategies in randomized registration trials, and bring us closer to the promise of cure.

The Promise of Liquid Biopsy to Predict Response to Immunotherapy in Metastatic Melanoma

Metastatic melanoma is the deadliest form of skin cancer whose incidence has been rising dramatically over the last few decades. Nowadays, the most successful approach in treating advanced melanoma is immunotherapy which encompasses the use of immune checkpoint blockers able to unleash the immune system's activity against tumor cells. Immunotherapy has dramatically changed clinical practice by contributing to increasing long term overall survival. Despite these striking therapeutic effects, the clinical benefits are strongly mitigated by innate or acquired resistance. In this context, it is of utmost importance to develop methods capable of predicting patient response to immunotherapy. To this purpose, one major step forward may be provided by measuring non-invasive biomarkers in human fluids, namely Liquid Biopsies (LBs). Several LB approaches have been developed over the last few years thanks to technological breakthroughs that have allowed to evaluate circulating components also when they are present in low abundance. The elements of this so-called "circulome" mostly encompass: tumor DNA, tumor and immune cells, soluble factors and non-coding RNAs. Here, we review the current knowledge of these molecules as predictors of response to immunotherapy in metastatic melanoma and predict that LB will soon enter into routine practice in order to guide clinical decisions for cancer immunotherapy.

The current landscape of single-cell transcriptomics for cancer immunotherapy

Immunotherapies such as immune checkpoint blockade and adoptive cell transfer have revolutionized cancer treatment, but further progress is hindered by our limited understanding of tumor resistance mechanisms. Emerging technologies now enable the study of tumors at the single-cell level, providing unprecedented high-resolution insights into the genetic makeup of the tumor microenvironment and immune system that bulk genomics cannot fully capture. Here, we highlight the recent key findings of the use of single-cell RNA sequencing to deconvolute heterogeneous tumors and immune populations during immunotherapy. Single-cell RNA sequencing has identified new crucial factors and cellular subpopulations that either promote tumor progression or leave tumors vulnerable to immunotherapy. We anticipate that the strategic use of single-cell analytics will promote the development of the next generation of successful, rationally designed immunotherapeutics.

Decoding Immune Heterogeneity of Melanoma and identifying immune-prognostic hub genes

Melanoma is an aggressive skin cancer that has gained attention worldwide. Growing evidence has highlighted that the tumor microenvironment (TME) is an important feature of carcinogenesis and contributes to therapeutic efficacy in melanoma. However, additional advances in melanoma immuno-oncology are necessary to achieve a comprehensive knowledge of the immune infiltrate population and to identify accurate and readily measurable biomarkers. In this study, we analyzed gene expression of 468 melanoma cases from the TCGA database, which led to the identification of three melanoma clusters (representedby low, median and high infiltration) that display unique immune features. We found that the microenvironment clusters had substantial prognostic efficacy. The median cluster was characterized by an inability to draw immune cells, highlighting possible immune escape mechanisms, and lower CXCL9 and CXCL10 expression, which was correlated to poor prognosis. Deep molecular characterization of immune cells, cytolytic-activity and tumor-inflammatory status revealed diversity of the local immune infiltration landscape in the melanoma clusters. Differentially expressed genes related to TME were extracted from each infiltration cluster. Functional annotations revealed that these genes were mainly related to immune system activation and the processes of immunoreaction. The top ten hub genes in immune infiltration-related protein-protein interaction (PPI) networks were selected for further prognostic investigation. Further validation showed that five of ten hub genes were good prognostic biomarkers for melanoma in two independent groups from the Gene Expression Omnibus database. In brief, these data highlight that systemic characterization of melanoma could uncover tumor infiltrate characteristics, which can help select the most adequate treatment and identify consistent and important indicators of the local immune tumor microenvironment in melanoma patients.

Cancer Stem Cells and the Slow Cycling Phenotype: How to Cut the Gordian Knot Driving Resistance to Therapy in Melanoma

Simple Summary

Cancer stem cells play a central role in the development of cancer and are poorly sensitive to standard chemotherapy and radiotherapy. Furthermore, they are also responsible for the onset of drug resistance. This also occurs in malignant melanoma, the deadliest form of skin cancer. Hence, cancer stem cells eradication is one of the main challenges for medical oncology. Here, we conducted a bioinformatics approach aimed to identify the main circuits and proteins underpinning cancer stem cell fitness in melanoma. Several lessons emerged from our work and may help to conceptualize future therapeutic approaches to prolong the efficacy of current therapies.

Abstract

Cancer stem cells (CSCs) have historically been defined as slow cycling elements that are able to differentiate into mature cells but without dedifferentiation in the opposite direction. Thanks to advances in genomic and non-genomic technologies, the CSC theory has more recently been reconsidered in a dynamic manner according to a “phenotype switching” plastic model. Transcriptional reprogramming rewires this plasticity and enables heterogeneous tumors to influence cancer progression and to adapt themselves to drug exposure by selecting a subpopulation of slow cycling cells, similar in nature to the originally defined CSCs. This model has been conceptualized for malignant melanoma tailored to explain resistance to target therapies. Here, we conducted a bioinformatics analysis of available data directed to the identification of the molecular pathways sustaining slow cycling melanoma stem cells. Using this approach, we identified a signature of 25 genes that were assigned to four major clusters, namely (1) kinases and metabolic changes, (2) melanoma-associated proteins, (3) Hippo pathway and (4) slow cycling/CSCs factors. Furthermore, we show how a protein−protein interaction network may be the main driver of these melanoma cell subpopulations. Finally, mining The Cancer Genome Atlas (TCGA) data we evaluated the expression levels of this signature in the four melanoma mutational subtypes. The concomitant alteration of these genes correlates with the worst overall survival (OS) for melanoma patients harboring BRAF-mutations. All together these results underscore the potentiality to target this signature to selectively kill CSCs and to achieve disease control in melanoma.

Single-Cell RNA Sequencing Unravels Heterogeneity of the Stromal Niche in Cutaneous Melanoma Heterogeneous Spheroids

Heterogeneous spheroids have recently acquired a prominent position in melanoma research because they incorporate microenvironmental cues relevant for melanoma. In this study, we focused on the analysis of microenvironmental factors introduced in melanoma heterogeneous spheroids by different dermal fibroblasts. We aimed to map the fibroblast diversity resulting from previously acquired damage caused by exposure to extrinsic and intrinsic stimuli. To construct heterogeneous melanoma spheroids, we used normal dermal fibroblasts from the sun-protected skin of a juvenile donor. We compared them to the fibroblasts from the sun-exposed photodamaged skin of an adult donor. Further, we analysed the spheroids by single-cell RNA sequencing. To validate transcriptional data, we also compared the immunohistochemical analysis of heterogeneous spheroids to melanoma biopsies. We have distinguished three functional clusters in primary human fibroblasts from melanoma spheroids. These clusters differed in the expression of (a) extracellular matrix-related genes, (b) pro-inflammatory factors, and (c) TGFβ signalling superfamily. We observed a broader deregulation of gene transcription in previously photodamaged cells. We have confirmed that pro-inflammatory cytokine IL-6 significantly enhances melanoma invasion to the extracellular matrix in our model. This supports the opinion that the aspects of ageing are essential for reliable melanoma 3D modelling in vitro.

Reverse transcriptase inhibition potentiates target therapy in BRAF-mutant melanomas: effects on cell proliferation, apoptosis, DNA-damage, ROS induction and mitochondrial membrane depolarization

Abstract

Target therapies based on BRAF and MEK inhibitors (MAPKi) have changed the therapeutic landscape for metastatic melanoma patients bearing mutations in the BRAF kinase. However, the emergence of drug resistance imposes the necessity to conceive novel therapeutic strategies capable to achieve a more durable disease control. In the last years, retrotransposons laying in human genome have been shown to undergo activation during tumorigenesis, where they contribute to genomic instability. Their activation can be efficiently controlled with reverse transcriptase inhibitors (RTIs) frequently used in the treatment of AIDS. These drugs have demonstrated anti-proliferative effects in several cancer models, including also metastatic melanoma. However, to our knowledge no previous study investigated the capability of RTIs to mitigate drug resistance to target therapy in BRAF-mutant melanomas. In this short report we show that the non-nucleoside RTI, SPV122 in combination with MAPKi strongly inhibits BRAF-mutant melanoma cell growth, induces apoptosis, and delays the emergence of resistance to target therapy in vitro. Mechanistically, this combination strongly induces DNA double-strand breaks, mitochondrial membrane depolarization and increased ROS levels. Our results shed further light on the molecular activity of RTI in melanoma and pave the way to their use as a novel therapeutic option to improve the efficacy of target therapy.

2-O-Methylmagnolol, a Magnolol Derivative, Suppresses Hepatocellular Carcinoma Progression via Inhibiting Class I Histone Deacetylase Expression

Magnolia officinalis is widely used in Southeast Asian countries for the treatment of fever, headache, diarrhea, and stroke. Magnolol is a phenolic compound extracted from M. officinalis, with proven antibacterial, antioxidant, anti-inflammatory, and anticancer activities. In this study, we modified magnolol to synthesize a methoxylated derivative, 2-O-methylmagnolol (MM1), and investigated the use of MM1, and magnolol in the treatment of liver cancer. We found that both magnolol and MM1 exhibited inhibitory effects on the growth, migration, and invasion of hepatocellular carcinoma (HCC) cell lines and halted the cell cycle at the G1 phase. MM1 also demonstrated a substantially better tumor-suppressive effect than magnolol. Further analysis suggested that by inhibiting class I histone deacetylase expression in HCC cell lines, magnolol and MM1 induced p21 expression and p53 activation, thereby causing cell cycle arrest and inhibiting HCC cell growth, migration, and invasion. Subsequently, we verified the significant tumor-suppressive effects of magnolol and MM1 in an animal model. Collectively, these findings demonstrate the anti-HCC activities of magnolol and MM1 and their potential for clinical use.

Tspan8 Drives Melanoma Dermal Invasion by Promoting ProMMP-9 Activation and Basement Membrane Proteolysis in a Keratinocyte-Dependent Manner

Melanoma is the most aggressive skin cancer with an extremely challenging therapy. The dermal-epidermal junction (DEJ) degradation and subsequent dermal invasion are the earliest steps of melanoma dissemination, but the mechanisms remain elusive. We previously identified Tspan8 as a key actor in melanoma invasiveness. Here, we investigated Tspan8 mechanisms of action during dermal invasion, using a validated skin-reconstruct-model that recapitulates melanoma dermal penetration through an authentic DEJ. We demonstrate that Tspan8 is sufficient to induce melanoma cells’ translocation to the dermis. Mechanistically, Tspan8⁺ melanoma cells cooperate with surrounding keratinocytes within the epidermis to promote keratinocyte-originated proMMP-9 activation process, collagen IV degradation and dermal colonization. This concurs with elevated active MMP-3 and low TIMP-1 levels, known to promote MMP-9 activity. Finally, a specific Tspan8-antibody reduces proMMP-9 activation and dermal invasion. Overall, our results provide new insights into the role of keratinocytes in melanoma dermal colonization through a cooperative mechanism never reported before, and establish for the first time the pro-invasive role of a tetraspanin family member in a cell non-autonomous manner. This work also displays solid arguments for the use of Tspan8-blocking antibodies to impede early melanoma spreading and therefore metastasis.

Non-Apoptotic Cell Death Signaling Pathways in Melanoma

Resisting cell death is a hallmark of cancer. Disturbances in the execution of cell death programs promote carcinogenesis and survival of cancer cells under unfavorable conditions, including exposition to anti-cancer therapies. Specific modalities of regulated cell death (RCD) have been classified based on different criteria, including morphological features, biochemical alterations and immunological consequences. Although melanoma cells are broadly equipped with the anti-apoptotic machinery and recurrent genetic alterations in the components of the RAS/RAF/MEK/ERK signaling markedly contribute to the pro-survival phenotype of melanoma, the roles of autophagy-dependent cell death, necroptosis, ferroptosis, pyroptosis, and parthanatos have recently gained great interest. These signaling cascades are involved in melanoma cell response and resistance to the therapeutics used in the clinic, including inhibitors of BRAFmut and MEK1/2, and immunotherapy. In addition, the relationships between sensitivity to non-apoptotic cell death routes and specific cell phenotypes have been demonstrated, suggesting that plasticity of melanoma cells can be exploited to modulate response of these cells to different cell death stimuli. In this review, the current knowledge on the non-apoptotic cell death signaling pathways in melanoma cell biology and response to anti-cancer drugs has been discussed.

In Vitro Biophysical and Biological Characterization of Lipid Nanoparticles Co-Encapsulating Oncosuppressors miR-199b-5p and miR-204-5p as Potentiators of Target Therapy in Metastatic Melanoma

Uncontrolled MAPK signaling is the main oncogenic driver in metastatic melanomas bearing mutations in BRAF kinase. These tumors are currently treated with the combination of BRAF/MEK inhibitors (MAPKi), but this therapy is plagued by drug resistance. In this context we recently discovered that several microRNAs are involved in the development of drug resistance. In particular miR-204-5p and miR-199b-5p were found to function as antagonists of resistance because their enforced overexpression is able to inhibit melanoma cell growth in vitro either alone or in combination with MAPKi. However, the use of miRNAs in therapy is hampered by their rapid degradation in serum and biological fluids, as well as by the poor intracellular uptake. Here, we developed lipid nanoparticles (LNPs) encapsulating miR-204-5p, miR-199b-5p individually or in combination. We obtained LNPs with mean diameters < 200 nm and high miRNA encapsulation efficiency. These formulations were tested in vitro on several melanoma cell lines sensitive to MAPKi or rendered drug resistant. Our results show that LNPs encapsulating combinations of the two oncosuppressor miRNAs are highly efficient in impairing melanoma cell proliferation and viability, affect key signaling pathways involved in melanoma cell survival, and potentiate the efficacy of drugs inhibiting BRAF and MEK. These results warrant further assessment of the anti-tumor efficacy of oncosuppressor miRNAs encapsulating LNPs in in vivo tumor models.