DNA hypermethylation is associated with invasive phenotype of malignant melanoma

Unveiling the role of RAC3 in the growth and invasion of cisplatin-resistant bladder cancer cells

Bladder cancer is one of the most prevalent cancers worldwide, and its morbidity and mortality rates have been increasing over the years. However, how RAC family small GTPase 3 (RAC3) affects the proliferation, migration and invasion of cisplatin-resistant bladder cancer cells remains unclear. Bioinformatics techniques were used to investigate the expression of RAC3 in bladder cancer tissues. Influences of RAC3 in the grade, stage, distant metastasis, and survival rate of bladder cancer were also examined. Analysis of the relationship between RAC3 expression and the immune microenvironment (TIME), genomic mutations, and stemness index. In normal bladder cancer cells (T24, 5637, and BIU-87) and cisplatin-resistant bladder cancer cells (BIU-87-DDP), the expression of RAC3 was detected separately with Western blotting. Plasmid transfection was used to overexpress or silence the expression of RAC3 in bladder cancer cells resistant to cisplatin (BIU-87-DDP). By adding activators and inhibitors, the activities of the JNK/MAPK signalling pathway were altered. Cell viability, invasion, and its level of apoptosis were measured in vitro using CCK-8, transwell, and flow cytometry. The bioinformatics analyses found RAC3 levels were elevated in bladder cancer tissues and were associated with a poor prognosis in bladder cancer. RAC3 in BIU-87-DDP cells expressed a higher level than normal bladder cancer cells. RAC3 overexpression promoted BIU-87-DDP proliferation. The growth of BIU-87-DDP cells slowed after the knockdown of RAC3, and RAC3 may have had an impact on the activation of the JNK/MAPK pathway.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

Integrated DNA methylation analysis reveals a potential role for PTPRN2 in Marfan syndrome scoliosis

Background

Marfan syndrome (MFS) is a rare genetic disorder caused by mutations in the Fibrillin-1 gene (FBN1) with significant clinical features in the skeletal, cardiopulmonary, and ocular systems. To gain deeper insights into the contribution of epigenetics in the variability of phenotypes observed in MFS, we undertook the first analysis of integrating DNA methylation and gene expression profiles in whole blood from MFS and healthy controls (HCs).

Methods

The Illumina 850K (EPIC) DNA methylation array was used to detect DNA methylation changes on peripheral blood samples of seven patients with MFS and five HCs. Associations between methylation levels and clinical features of MFS were analyzed. Subsequently, we conducted an integrated analysis of the outcomes of the transcriptome data to analyze the correlation between differentially methylated positions (DMPs) and differentially expressed genes (DEGs) and explore the potential role of methylation-regulated DEGs (MeDEGs) in MFS scoliosis. The weighted gene co-expression network analysis was used to find gene modules with the highest correlation coefficient with target MeDEGs to annotate their functions in MFS.

Results

Our study identified 1253 DMPs annotated to 236 genes that were primarily associated with scoliosis, cardiomyopathy, and vital capacity. These conditions are typically associated with reduced lifespan in untreated MFS. We calculated correlations between DMPs and clinical features, such as cobb angle to evaluate scoliosis and FEV1% to assess pulmonary function. Notably, cg20223687 (PTPRN2) exhibited a positive correlation with cobb angle of scoliosis, potentially playing a role in ERKs inactivation.

Conclusions

Taken together, our systems-level approach sheds light on the contribution of epigenetics to MFS and offers a plausible explanation for the complex phenotypes that are linked to reduced lifespan in untreated MFS patients.

Machine Learning Methods for Gene Selection in Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignancy with a limited five-year survival for metastatic patients. Limited therapeutic treatments are currently available for metastatic disease, even if the genomics of this tumor has been deeply studied using next-generation sequencing (NGS) and functional experiments. The profound knowledge of the molecular features that characterize this tumor has not led to the development of efficacious therapies, and the survival of metastatic patients has not changed for decades. Several bioinformatics methods have been applied to mine NGS tumor data in order to unveil tumor biology and detect possible molecular targets for new therapies. Each application can be single domain based while others are more focused on data integration from multiple genomics domains (as gene expression and methylation data). Examples of single domain approaches include differentially expressed gene (DEG) analysis on gene expression data with statistical methods such as SAM (significance analysis of microarray) or gene prioritization with complex algorithms such as deep learning. Data fusion or integration methods merge multiple domains of information to define new clusters of patients or to detect relevant genes, according to multiple NGS data. In this work, we compare different strategies to detect relevant genes for metastatic disease prediction in the TCGA uveal melanoma (UVM) dataset. Detected targets are validated with multi-gene score analysis on a larger UM microarray dataset.

Expression pattern of osteopontin isoforms in malignant melanoma cell lines

Osteopontin (OPN) is a secreted integrin-binding protein that plays a role in inflammation, cellular viability, cell adhesion and migration, cancer development, and diabetes through different mechanisms. The splice variants of OPN can play essential roles in cancer development, progression, and metastasis formation; however, limited data are available about the role of OPN isoforms in human malignant melanoma. Our goal was to define the gene expression patterns of five OPN variants (OPN4, OPN5, OPNa, OPNb, and OPNc), integrin, and CD44 receptor genes in primary and metastatic melanoma-originated cell lines (n = 19), and to explore the association of the expression patterns with clinicopathological parameters. We evaluated the invasive property of the cell lines and investigated the potential association between the invasion and gene expression of OPN isoforms. We found a significant rise in the expression of OPNc in the invasive cell lines compared to the noninvasive cells and detected significantly higher expression of the OPN splice variants in melanoma cell lines originating from more advanced stages tumors than cell lines originating from early-stage melanomas. The correlation analysis revealed that all five OPN variants positively correlated with ITGB3 and ITGA9, whereas OPN5 positively correlated with ITGB1, ITGAV, ITGA6, and CD44. OPN can activate extracellular signal-regulated kinase signaling through binding to α9β1 integrin, promoting melanoma tumor cell migration. It is possible that such associations between OPN splice variants and integrin receptors may play a role in melanoma progression. In conclusion, our findings suggest that high expression of OPNc correlates with the invasive behavior of melanoma cells.

Development and validation of a nomogram for the prediction of brain metastases in small cell lung cancer

INTRODUCTION

The aim was to develop and validate a nomogram for the prediction of brain metastases (BM) in small cell lung cancer (SCLC), to explore the risk factors and assist clinical decision-making.

METHODS

We reviewed the clinical data of SCLC patients between 2015 and 2021. Patients between 2015 and 2019 were included to develop, whereas patients between 2020 and 2021 were used for external validation. Clinical indices were analysed by using the least absolute shrinkage and selection operator (LASSO) logistic regression analyses. The final nomogram was constructed and validated by bootstrap resampling.

RESULTS

A total of 631 SCLC patients between 2015 and 2019 were included to construct model. Gender, T stage, N stage, Eastern Cooperative Oncology Group (ECOG), haemoglobin (HGB), the absolute value of lymphocyte (LYMPH #), platelet (PLT), retinol-binding protein (RBP), carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) were identified as risk factors and included into the model. The C-indices were 0.830 and 0.788 in the internal validation by 1000 bootstrap resamples. The calibration plot revealed excellent agreement between the predicted and the actual probability. Decision curve analysis (DCA) showed better net benefits with a wider range of threshold probability (net clinical benefit was 1%-58%). The model was further externally validated in patients between 2020 and 2021 with a C-index of 0.818.

CONCLUSIONS

We developed and validated a nomogram to predict the risk of BM in SCLC patients, which could help clinicians to rationally schedule follow-ups and promptly implement interventions.

Expression Mapping and Functional Analysis of Orphan G-Protein-Coupled Receptor GPR158 in the Adult Mouse Brain Using a GPR158 Transgenic Mouse

Aberrant expression of G-protein-coupled receptor 158 (GPR158) has been reported to be inextricably linked to a variety of diseases affecting the central nervous system, including Alzheimer’s disease (AD), depression, intraocular pressure, and glioma, but the underlying mechanism remains elusive due to a lack of biological and pharmacological tools to elaborate its preferential cellular distribution and molecular interaction network. To assess the cellular localization, expression, and function of GPR158, we generated an epitope-tagged GPR158 mouse model (GPR158Tag) that exhibited normal motor, cognitive, and social behavior, no deficiencies in social memory, and no anxiety-like behavior compared to C57BL/6J control mice at P60. Using immunofluorescence, we found that GPR158+ cells were distributed in several brain regions including the cerebral cortex, hippocampus, cerebellum, and caudate putamen. Next, using the cerebral cortex of the adult GPR158Tag mice as a representative region, we found that GPR158 was only expressed in neurons, and not in microglia, oligodendrocytes, or astrocytes. Remarkably, the majority of GPR158 was enriched in Camk2a+ neurons whilst limited expression was found in PV+ interneurons. Concomitant 3D co-localization analysis revealed that GPR158 was mainly distributed in the postsynaptic membrane, but with a small portion in the presynaptic membrane. Lastly, via mass spectrometry analysis, we identified proteins that may interact with GPR158, and the relevant enrichment pathways were consistent with the immunofluorescence findings. RNA-seq analysis of the cerebral cortex of the GPR158−/− mice showed that GPR158 and its putative interacting proteins are involved in the chloride channel complex and synaptic vesicle membrane composition. Using these GPR158Tag mice, we were able to accurately label GPR158 and uncover its fundamental function in synaptic vesicle function and memory. Thus, this model will be a useful tool for subsequent biological, pharmacological, and electrophysiological studies related to GPR158.

Evaluation and Comparison of Multi-Omics Data Integration Methods for Subtyping of Cutaneous Melanoma

There is a growing number of multi-domain genomic datasets for human tumors. Multi-domain data are usually interpreted after separately analyzing single-domain data and integrating the results post hoc. Data fusion techniques allow for the real integration of multi-domain data to ideally improve the tumor classification results for the prognosis and prediction of response to therapy. We have previously described the joint singular value decomposition (jSVD) technique as a means of data fusion. Here, we report on the development of these methods in open source code based on R and Python and on the application of these data fusion methods. The Cancer Genome Atlas (TCGA) Skin Cutaneous Melanoma (SKCM) dataset was used as a benchmark to evaluate the potential of the data fusion approaches to improve molecular classification of cancers in a clinically relevant manner. Our data show that the data fusion approach does not generate classification results superior to those obtained using single-domain data. Data from different domains are not entirely independent from each other, and molecular classes are characterized by features that penetrate different domains. Data fusion techniques might be better suited for response prediction, where they could contribute to the identification of predictive features in a domain-independent manner to be used as biomarkers.

Identification and Validation of Ferroptosis-Related DNA Methylation Signature for Predicting the Prognosis and Guiding the Treatment in Cutaneous Melanoma

Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan-Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients.

Targeting the epigenome in malignant melanoma: Facts, challenges and therapeutic promises

Malignant melanoma is the most lethal type of skin cancer with high rates of mortality. Although current treatment options provide a short-clinical benefit, acquired-drug resistance highlights the low 5-year survival rate among patients with advanced stage of the disease. In parallel, the involvement of an aberrant epigenetic landscape, (e.g., alterations in DNA methylation patterns, histone modifications marks and expression of non-coding RNAs), in addition to the genetic background, has been also associated with the onset and progression of melanoma. In this review article, we report on current therapeutic options in melanoma treatment with a focus on distinct epigenetic alterations and how their reversal, by specific drug compounds, can restore a normal phenotype. In particular, we concentrate on how single and/or combinatorial therapeutic approaches have utilized epigenetic drug compounds in being effective against malignant melanoma. Finally, the role of deregulated epigenetic mechanisms in promoting drug resistance to targeted therapies and immune checkpoint inhibitors is presented leading to the development of newly synthesized and/or improved drug compounds capable of targeting the epigenome of malignant melanoma.

Epigenetic Mechanisms Underlying Melanoma Resistance to Immune and Targeted Therapies

Melanoma is an aggressive skin cancer reliant on early detection for high likelihood of successful treatment. Solar UV exposure transforms melanocytes into highly mutated tumor cells that metastasize to the liver, lungs, and brain. Even upon resection of the primary tumor, almost thirty percent of patients succumb to melanoma within twenty years. Identification of key melanoma genetic drivers led to the development of pharmacological BRAF^V600E and MEK inhibitors, significantly improving metastatic patient outcomes over traditional cytotoxic chemotherapy or pioneering IFN-α and IL-2 immune therapies. Checkpoint blockade inhibitors releasing the immunosuppressive effects of CTLA-4 or PD-1 proved to be even more effective and are the standard first-line treatment. Despite these major improvements, durable responses to immunotherapy and targeted therapy have been hindered by intrinsic or acquired resistance. In addition to gained or selected genetic alterations, cellular plasticity conferred by epigenetic reprogramming is emerging as a driver of therapy resistance. Epigenetic regulation of chromatin accessibility drives gene expression and establishes distinct transcriptional cell states. Here we review how aberrant chromatin, transcriptional, and epigenetic regulation contribute to therapy resistance and discuss how targeting these programs sensitizes melanoma cells to immune and targeted therapies.

A 9‑gene expression signature to predict stage development in resectable stomach adenocarcinoma

BACKGROUND

Stomach adenocarcinoma (STAD) is a highly heterogeneous disease and is among the leading causes of cancer-related death worldwide. At present, TNM stage remains the most effective prognostic factor for STAD. Exploring the changes in gene expression levels associated with TNM stage development may help oncologists to better understand the commonalities in the progression of STAD and may provide a new way of identifying early-stage STAD so that optimal treatment approaches can be provided.

METHODS

The RNA profile retrieving strategy was utilized and RNA expression profiling was performed using two large STAD microarray databases (GSE62254, n = 300; GSE15459, n = 192) from the Gene Expression Omnibus (GEO) and the RNA-seq database within the Cancer Genome Atlas (TCGA, n = 375). All sample expression information was obtained from STAD tissues after radical resection. After excluding data with insufficient staging information and lymph node number, samples were grouped into earlier-stage and later-stage. Samples in GSE62254 were randomly divided into a training group (n = 172) and a validation group (n = 86). Differentially expressed genes (DEGs) were selected based on the expression of mRNAs in the training group and the TCGA group (n = 156), and hub genes were further screened by least absolute shrinkage and selection operator (LASSO) logistic regression. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the hub genes in distinguishing STAD stage in the validation group and the GSE15459 dataset. Univariate and multivariate Cox regressions were performed sequentially.

RESULTS

22 DEGs were commonly upregulated (n = 19) or downregulated (n = 3) in the training and TCGA datasets. Nine genes, including MYOCD, GHRL, SCRG1, TYRP1, LYPD6B, THBS4, TNFRSF17, SERPINB2, and NEBL were identified as hub genes by LASSO-logistic regression. The model achieved discrimination in the validation group (AUC = 0.704), training-validation group (AUC = 0.743), and GSE15459 dataset (AUC = 0.658), respectively. Gene Set Enrichment Analysis (GSEA) was used to identify the potential stage-development pathways, including the PI3K-Akt and Calcium signaling pathways. Univariate Cox regression indicated that the nine-gene score was a significant risk factor for overall survival (HR = 1.28, 95% CI 1.08-1.50, P = 0.003). In the multivariate Cox regression, only SCRG1 was an independent prognostic predictor of overall survival after backward stepwise elimination (HR = 1.21, 95% CI 1.11-1.32, P < 0.001).

CONCLUSION

Through a series of bioinformatics and validation processes, a nine-gene signature that can distinguish STAD stage was identified. This gene signature has potential clinical application and may provide a novel approach to understanding the progression of STAD.

Current understanding of epigenetics role in melanoma treatment and resistance

Melanoma is the most aggressive form of skin cancer resulting from genetic mutations in melanocytes. Several factors have been considered to be involved in melanoma progression, including genetic alteration, processes of damaged DNA repair, and changes in mechanisms of cell growth and proliferation. Epigenetics is the other factor with a crucial role in melanoma development. Epigenetic changes have become novel targets for treating patients suffering from melanoma. These changes can alter the expression of microRNAs and their interaction with target genes, which involves cell growth, differentiation, or even death. Given these circumstances, we conducted the present review to discuss the melanoma risk factors and represent the current knowledge about the factors related to its etiopathogenesis. Moreover, various epigenetic pathways, which are involved in melanoma progression, treatment, and chemo-resistance, as well as employed epigenetic factors as a solution to the problems, will be discussed in detail.

Morphology of inner cell mass: a better predictive biomarker of blastocyst viability

Background

Transfer of embryos at the blastocyst stage is one of the best approaches for achieving a higher success rate in In vitro fertilization (IVF) treatment as it demonstrates an improved uterine and embryonic synchrony at implantation. Despite novel biochemical and genetic markers proposed for the prediction of embryo viability in recent years, the conventional morphological grading of blastocysts remains the classical way of selection in routine practice. This study aims to investigate the association between the morphological features of blastocysts and pregnancy outcomes.

Methods

This prospective study included women undergoing single or double frozen blastocyst transfers following their autologous cycles in a period between October 2020 and September 2021. The morphological grades (A-good, B-average, and C-poor) of inner cell mass (ICM) and trophectoderm (TE) of blastocysts with known implantation were compared to assess their predictive potential of pregnancy outcome. It was further explored by measuring the relationship between the two variables using logistic regression and receiver operating characteristic (ROC) analysis.

Results

A total of 1,972 women underwent frozen embryo transfer (FET) cycles with a total of 3,786 blastocysts. Known implantation data (KID) from 2,060 blastocysts of 1,153 patients were subjected to statistical analysis, the rest were excluded. Implantation rates (IR) from transfer of ICM/TE grades AA, AB, BA, BB were observed as 48.5%, 39.4%, 23.4% and 25% respectively. There was a significantly higher IR observed in blastocysts with ICM grade A (p < 0.001) than those with B irrespective of their TE scores. The analysis of the interaction between the two characteristics confirmed the superiority of ICM over TE as a predictor of the outcome. The rank biserial correlation value for ICM was also greater compared to that of TE (0.11 vs 0.05).

Conclusion

This study confirms that the morphology of ICM of the blastocyst is a stronger predictor of implantation and clinical pregnancy than that of TE and can be utilized as a biomarker of viability.

Characterization of the CpG Island Hypermethylated Phenotype Subclass in Primary Melanomas

Cutaneous melanoma can be lethal even if detected at an early stage. Epigenetic profiling may facilitate the identification of aggressive primary melanomas with unfavorable outcomes. We performed clustering of whole-genome methylation data to identify subclasses that were then assessed for survival, clinical features, methylation patterns, and biological pathways. Among 89 cutaneous primary invasive melanomas, we identified three methylation subclasses exhibiting low methylation, intermediate methylation, or hypermethylation of CpG islands, known as the CpG island methylator phenotype (CIMP). CIMP melanomas occurred as early as tumor stage 1b and, compared with low-methylation melanomas, were associated with age at diagnosis ≥65 years, lentigo maligna melanoma histologic subtype, presence of ulceration, higher American Joint Committee on Cancer stage and tumor stage, and lower tumor-infiltrating lymphocyte grade (all P < 0.05). Patients with CIMP melanomas had worse melanoma-specific survival (hazard ratio = 11.84; confidence interval = 4.65‒30.20) than those with low-methylation melanomas, adjusted for age, sex, American Joint Committee on Cancer stage, and tumor-infiltrating lymphocyte grade. Genes hypermethylated in CIMP compared with those in low-methylation melanomas included PTEN, VDR, PD-L1, TET2, and gene sets related to development/differentiation, the extracellular matrix, and immunity. CIMP melanomas exhibited hypermethylation of genes important in melanoma progression and tumor immunity, and although present in some early melanomas, CIMP was associated with worse survival independent of known prognostic factors.

Genome-wide promoter methylation profiling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival

The epigenetic changes associated with melanoma progression to advanced and metastatic stages are still poorly understood. To shed light on the CpG methylation dynamics during melanoma development, we analyzed the methylome profiles of a four-stage cell line model of melanoma progression: non-tumorigenic melanocytes (melan-a), premalignant melanocytes (4C), non-metastatic melanoma cells (4C11−), and metastatic melanoma cells (4C11+). We identified 540 hypo- and 37 hypermethylated gene promoters that together characterized a malignancy signature, and 646 hypo- and 520 hypermethylated promoters that distinguished a metastasis signature. Differentially methylated genes from these signatures were correlated with overall survival using TCGA-SKCM methylation data. Moreover, multivariate Cox analyses with LASSO regularization identified panels of 33 and 31 CpGs, respectively, from the malignancy and metastasis signatures that predicted poor survival. We found a concordant relationship between DNA methylation and transcriptional levels for genes from the malignancy (Pyroxd2 and Ptgfrn) and metastasis (Arnt2, Igfbp4 and Ptprf) signatures, which were both also correlated with melanoma prognosis. Altogether, this study reveals novel CpGs methylation markers associated with malignancy and metastasis that collectively could improve the survival prediction of melanoma patients.

Cancer Cell Phenotype Plasticity as a Driver of Immune Escape in Melanoma

Immunotherapies blocking negative immune checkpoints are now approved for the treatment of a growing number of cancers. However, even in metastatic melanoma, where sustained responses are observed, a significant number of patients still do not respond or display resistance. Increasing evidence indicates that non-genetic cancer cell-intrinsic alterations play a key role in resistance to therapies and immune evasion. Cancer cell plasticity, mainly associated with the epithelial-to-mesenchymal transition in carcinoma, relies on transcriptional, epigenetic or translational reprogramming. In melanoma, an EMT-like dedifferentiation process is characterized by the acquisition of invasive or neural crest stem cell-like features. Herein, we discuss recent findings on the specific roles of phenotypic reprogramming of melanoma cells in driving immune evasion and resistance to immunotherapies. The mechanisms by which dedifferentiated melanoma cells escape T cell lysis, mediate T cell exclusion or remodel the immune microenvironment will be detailed. The expanded knowledge on tumor cell plasticity in melanoma should contribute to the development of novel therapeutic combination strategies to further improve outcomes in this deadly metastatic cancer.

Research Status of the Orphan G Protein Coupled Receptor 158 and Future Perspectives

G-protein-coupled receptors (GPCRs) remain one of the most successful targets for therapeutic drugs approved by the US Food and Drug Administration (FDA). Many novel orphan GPCRs have been identified by human genome sequencing and considered as putative targets for refractory diseases. Of note, a series of studies have been carried out involving GPCR 158 (or GPR158) since its identification in 2005, predominantly focusing on the characterization of its roles in the progression of cancer and mental illness. However, advances towards an in-depth understanding of the biological mechanism(s) involved for clinical application of GPR158 are lacking. In this paper, we clarify the origin of the GPR158 evolution in different species and summarize the relationship between GPR158 and different diseases towards potential drug target identification, through an analysis of the sequences and substructures of GPR158. Further, we discuss how recent studies set about unraveling the fundamental features and principles, followed by future perspectives and thoughts, which may lead to prospective therapies involving GPR158.

Cytokine and Chemokine Receptor Patterns of Human Malignant Melanoma Cell Lines

Cytokine and chemokine receptors can promote tumor progression, invasion, and metastasis development by inducing different intracellular signaling pathways. The aim of this study was to determine the cytokine and chemokine receptor gene expression patterns in human melanoma cell lines. We found a large set of cytokine and chemokine receptor genes that were significantly differentially expressed between melanoma cell lines that originated from different subtypes of primary melanomas as well as cell lines that originated from melanoma metastases. The relative expressions of two receptor genes (CCR2 and TNFRSF11B) were positively correlated with the invasive potential of the cell lines, whereas a negative correlation was observed for the TNFRSF14 gene expression. We also found a small set of receptor genes that exhibited a significantly decreased expression in association with a BRAFV600E mutation. Based on our results, we assume that the analyzed cytokine and chemokine receptor collection may provide potential to distinguish the different subtypes of melanomas, helping us to understand the biological behavior of BRAFV600E-mutated melanoma cells.

The ncRNA-Mediated Overexpression of Ferroptosis-Related Gene EMC2 Correlates With Poor Prognosis and Tumor Immune Infiltration in Breast Cancer

Ferroptosis is an iron-dependent programmed cell death process. Although ferroptosis inducers hold promising potential in the treatment of breast cancer, the specific role and mechanism of the ferroptosis-related gene EMC2 in breast cancer have not been entirely determined. The potential roles of EMC2 in different tumors were explored based on The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Tumor Immune Estimation Resource (TIMER), Shiny Methylation Analysis Resource Tool (SMART), starBase, and cBioPortal for cancer genomics (cBioPortal) datasets. The expression difference, mutation, survival, pathological stage, DNA methylation, non-coding RNAs (ncRNAs), and immune cell infiltration related to EMC2 were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify the differences in biological processes and functions among different related genes. The expression levels of core prognostic genes were then verified in breast invasive carcinoma samples using immunohistochemistry and breast invasive carcinoma cell lines using real-time polymerase chain reaction. High expression levels of EMC2 were observed in most cancer types. EMC2 expression in breast cancer tissue samples correlated with poor overall survival. EMC2 was mutated and methylated in a variety of tumors and affected survival. The LINC00665-miR-410-3p axis was identified as the most potential upstream ncRNA-related pathway of EMC2 in breast cancer. EMC2 levels were significantly positively correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Our study offers a comprehensive understanding of the oncogenic roles of EMC2 across different tumors. The upregulation of EMC2 expression mediated by ncRNAs is related to poor prognosis and tumor immune infiltration in breast cancer.

Genome-wide methylation patterns in Marfan syndrome

Background

Marfan syndrome (MFS) is a connective tissue disorder caused by mutations in the Fibrillin-1 gene (FBN1). Here, we undertook the first epigenome-wide association study (EWAS) in patients with MFS aiming at identifying DNA methylation loci associated with MFS phenotypes that may shed light on the disease process.

Methods

The Illumina 450 k DNA-methylation array was used on stored peripheral whole-blood samples of 190 patients with MFS originally included in the COMPARE trial. An unbiased genome-wide approach was used, and methylation of CpG-sites across the entire genome was evaluated. Additionally, we investigated CpG-sites across the FBN1-locus (15q21.1) more closely, since this is the gene defective in MFS. Differentially Methylated Positions (DMPs) and Differentially Methylated Regions (DMRs) were identified through regression analysis. Associations between methylation levels and aortic diameters and presence or absence of 21 clinical features of MFS at baseline were analyzed. Moreover, associations between aortic diameter change, and the occurrence of clinical events (death any cause, type-A or -B dissection/rupture, or aortic surgery) and methylation levels were analyzed.

Results

We identified 28 DMPs that are significantly associated with aortic diameters in patients with MFS. Seven of these DMPs (25%) could be allocated to a gene that was previously associated with cardiovascular diseases (HDAC4, IGF2BP3, CASZ1, SDK1, PCDHGA1, DIO3, PTPRN2). Moreover, we identified seven DMPs that were significantly associated with aortic diameter change and five DMP’s that associated with clinical events. No significant associations at p < 10^–8 or p < 10^–6 were found with any of the non-cardiovascular phenotypic MFS features. Investigating DMRs, clusters were seen mostly on X- and Y, and chromosome 18–22. The remaining DMRs indicated involvement of a large family of protocadherins on chromosome 5, which were not reported in MFS before.

Conclusion

This EWAS in patients with MFS has identified a number of methylation loci significantly associated with aortic diameters, aortic dilatation rate and aortic events. Our findings add to the slowly growing literature on the regulation of gene expression in MFS patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01204-4.

Methylation Markers in Cutaneous Melanoma: Unravelling the Potential Utility of Their Tracking by Liquid Biopsy

Malignant melanoma is the most serious, life-threatening form of all dermatologic diseases, with a poor prognosis in the presence of metastases and advanced disease. Despite recent advances in targeted therapy and immunotherapy, there is still a critical need for a better understanding of the fundamental mechanisms behind melanoma progression and resistance onset. Recent advances in genome-wide methylation methods have revealed that aberrant changes in the pattern of DNA methylation play an important role in many aspects of cancer progression, including cell proliferation and migration, evasion of cell death, invasion, and metastasization. The purpose of the current review was to gather evidence regarding the usefulness of DNA methylation tracking in liquid biopsy as a potential biomarker in melanoma. We investigated the key genes and signal transduction pathways that have been found to be altered epigenetically in melanoma. We then highlighted the circulating tumor components present in blood, including circulating melanoma cells (CMC), circulating tumor DNA (ctDNA), and tumor-derived extracellular vesicles (EVs), as a valuable source for identifying relevant aberrations in DNA methylation. Finally, we focused on DNA methylation signatures as a marker for tracking response to therapy and resistance, thus facilitating personalized medicine and decision-making in the treatment of melanoma patients.

Anti-melanoma effects of concomitant inhibition of SIRT1 and SIRT3 in BrafV600E/PtenNULL mice

Novel therapeutic strategies are required for the effective and lasting treatment of metastatic melanoma, one of the deadliest skin malignancies. In this study, we determined the anti-melanoma efficacy of 4'-bromo-resveratrol (4'-BR), which is a small molecule dual inhibitor of SIRT1 and SIRT3 in a Braf^V600E/Pten^NULL mouse model that recapitulates human disease, including metastases. Tumors were induced by topical application of 4-hydroxy-tamoxifen on shaved backs of 10-week-old mice, and the effects of 4'-BR (5-30 mg/kg b.wt.; intraperitoneally; 3d/week for 5 weeks) were assessed on melanoma development and progression. We found that 4'-BR at a dose of 30 mg/kg significantly reduced size and volume of primary melanoma tumors, as well as lung metastasis, with no adverse effects. Further, mechanistic studies on tumors showed significant modulation in markers of proliferation, survival and melanoma progression. As SIRT1 and SIRT3 are linked to immunomodulation, we performed differential gene expression analysis via NanoString PanCancer Immune Profiling panel (770 genes). Our data demonstrated that 4'-BR significantly downregulated genes related to metastasis-promotion, chemokine/cytokine-regulation, and innate/adaptive immune functions. Overall, inhibition of SIRT1 and SIRT3 by 4'-BR is a promising anti-melanoma therapy with anti-metastatic and immunomodulatory activities warranting further detailed studies, including clinical investigations.

Quantification of Global DNA Methylation in Canine Melanotic and Amelanotic Oral Mucosal Melanomas and Peripheral Blood Leukocytes From the Same Patients With OMM: First Study

Oral mucosal melanomas (OMMs) are aggressive and resistant cancers of high importance in veterinary oncology. Amelanotic OMM produces comparatively less melanin and is considered to be more aggressive than melanotic OMM. Global DNA methylation profiles with hypomethylated or hypermethylated patterns have both been associated with aggressive neoplasms; however, global DNA hypomethylation seems to correlate to higher aggressiveness. Accordingly, global DNA methylation in peripheral blood leukocytes has been investigated to understand the role of systemic or environmental factors in cancer development. This study aimed to quantify global DNA methylation in canine melanotic and amelanotic OMM samples and in the peripheral blood leukocytes of the same dogs. Tumor tissue samples were collected from 38 dogs, of which 19 were melanotic and 19 were amelanotic OMM. These were submitted to immunohistochemistry (IHC) with anti-5-methylcytosine (5mC) and anti-Ki67 primary antibodies. Ki67- and 5mC-positive nuclei were manually scored with the help of an image analysis system. Peripheral blood samples were collected from 18 among the 38 OMM-bearing dogs and from 7 additional healthy control dogs. Peripheral blood leukocytes were isolated from the 25 dogs, and DNA was extracted and analyzed by high-performance liquid chromatography (HPLC) for global DNA methylation. The pattern of global DNA methylation in both canine melanotic and amelanotic OMM indicated higher percentages of weakly or negatively stained nuclei in most of the OMM cells, presuming predominant global DNA hypomethylation. In addition, Ki67 counts in amelanotic OMM were significantly higher than those in melanotic OMM (p < 0.001). Global DNA methylation different immunostaining patterns (strong, weak or negative) correlated with Ki67 scores. Global DNA methylation in circulating leukocytes did not differ between the 9 melanotic and 9 amelanotic OMM or between the 18 OMM-bearing dogs and the 7 healthy dogs. This study provides new information on canine melanotic and amelanotic OMM based on global DNA methylation and cell proliferation.

Down-regulation of RBP4 indicates a poor prognosis and correlates with immune cell infiltration in hepatocellular carcinoma

Recent research has indicated that metabolically related genes play crucial roles in the pathogenesis of hepatocellular carcinoma (HCC). We evaluated the associations between novel biomarkers and retinol-binding protein 4 (RBP4) for predicting clinical HCC outcomes, hub-related genes, pathway regulation, and immune cells infiltration. Bioinformatic analyses based on data from The Cancer Genome Atlas were performed using online analysis tools. RBP4 expression was low in HCC and was also down-regulated in pan-cancers compared with normal tissues. RBP4 expression was also significantly different based on age (41–60 years old versus 61–80 years old), and low RBP4 expression levels were associated with advanced tumor stages and grades. Higher RBP4 expression was associated with better overall survival time in HCC patients, and we identified a deletion-mutation rate of 1.4% in RBP4. We also identified ten co-expressed genes most related to RBP4 and explored the relationships between six hub genes (APOB, FGA, FGG, SERPINC1, APOA1, and F2) involved in RBP4 regulation. A pathway enrichment analysis for RBP4 indicated complement and coagulation cascades, metabolic pathways, antibiotic biosynthesis pathways, peroxisome proliferator-activated receptor signaling pathways, and pyruvate metabolism pathways. These results suggest that RBP4 may be a novel biomarker for HCC prognosis, and an indicator of low immune response to the disease.