ABSTRACT
A number of genomic regions have been associated with melanoma risk through genome-wide association studies; however, the causal variants underlying the majority of these associations remain unknown. Here, we sequenced either the full locus or the functional regions including exons of 19 melanoma-associated loci in 1959 British melanoma cases and 737 controls. Variant filtering followed by Fisher's exact test analyses identified 66 variants associated with melanoma risk. Sequential conditional logistic regression identified the distinct haplotypes on which variants reside, and massively parallel reporter assays provided biological insights into how these variants influence gene function. We performed further analyses to link variants to melanoma risk phenotypes and assessed their association with melanoma-specific survival. Our analyses replicate previously known associations in the melanocortin 1 receptor (MC1R) and tyrosinase (TYR) loci, while identifying novel potentially causal variants at the MTAP/CDKN2A and CASP8 loci. These results improve our understanding of the architecture of melanoma risk and outcome.
Subject(s)
Melanoma , Skin Neoplasms , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Melanoma/genetics , Phenotype , Polymorphism, Single Nucleotide/genetics , Receptor, Melanocortin, Type 1/genetics , Skin Neoplasms/geneticsABSTRACT
BACKGROUND: Checkpoint inhibitors (CPIs) are widely used in cancer treatment, with transformative impacts on survival. They nonetheless carry a significant risk of toxicity in the form of immune-related adverse events (IrAEs), which may be sustained and life-altering. IrAEs may require high-dose and/or prolonged steroid use and represent a significant healthcare burden. They mimic immune-mediated inflammatory diseases (IMIDs) but understanding of their pathogenesis is limited. The MEDALLION project aims to determine targetable mechanisms of immune dysregulation in IrAE development, employing an immune monitoring approach to determine changes in circulating and tissue resident cells of CPI recipients who do/do not develop them and assessing the contribution of the microbiome in parallel. METHODS: MEDALLION is a non-randomised longitudinal cohort study aiming to recruit 66 cancer patient recipients of anti-PD1/PD-L1, anti-CTLA-4 or combination therapy. Eligible participants include those with malignant melanoma in the adjuvant or metastatic setting, mesothelioma and non-small cell lung carcinoma (NSCLC) treated in the metastatic setting. Comprehensive clinical evaluation is carried out alongside blood, skin swab and stool sampling at the time of CPI initiation (baseline) and during subsequent routine hospital visits on 6 occasions over a 10-month follow-up period. It is conservatively anticipated that one third of enrolled patients will experience a "significant IrAE" (SirAE), defined according to pre-determined criteria specific to the affected tissue/organ system. Those developing such toxicity may optionally undergo a biopsy of affected tissue where appropriate, otherwise being managed according to standard of care. Peripheral blood mononuclear cells will be analysed using multi-parameter flow cytometry to investigate immune subsets, their activation status and cytokine profiles. Stool samples and skin swabs will undergo DNA extraction for 16 S ribosomal RNA (rRNA) sequencing and internal transcribed spacer (ITS) gene sequencing to determine bacterial and fungal microbiome diversity, respectively, including species associated with toxicity. Stored tissue biopsies will be available for in situ and single-cell transcriptomic evaluation. Analysis will focus on the identification of biological predictors and precursors of SirAEs. DISCUSSION: The pathogenesis of IrAEs will be assessed through the MEDALLION cohort, with the potential to develop tools for their prediction and/or strategies for targeted prevention or treatment. TRIAL REGISTRATION: The study was registered on 18/09/2023 in the ISRCTN registry (43,419,676).
Subject(s)
Immune Checkpoint Inhibitors , Neoplasms , Humans , Immune Checkpoint Inhibitors/therapeutic use , Immune Checkpoint Inhibitors/adverse effects , Neoplasms/drug therapy , Neoplasms/immunology , Longitudinal Studies , Immunotherapy/methods , Immunotherapy/adverse effects , Cohort Studies , Monitoring, Immunologic/methods , Melanoma/drug therapy , Melanoma/immunologyABSTRACT
PURPOSE: Much of the heredity of melanoma remains unexplained. We sought predisposing germline copy-number variants using a rare disease approach. METHODS: Whole-genome copy-number findings in patients with melanoma predisposition syndrome congenital melanocytic nevus were extrapolated to a sporadic melanoma cohort. Functional effects of duplications in PPP2R3B were investigated using immunohistochemistry, transcriptomics, and stable inducible cellular models, themselves characterized using RNAseq, quantitative real-time polymerase chain reaction (qRT-PCR), reverse phase protein arrays, immunoblotting, RNA interference, immunocytochemistry, proliferation, and migration assays. RESULTS: We identify here a previously unreported genetic susceptibility to melanoma and melanocytic nevi, familial duplications of gene PPP2R3B. This encodes PR70, a regulatory unit of critical phosphatase PP2A. Duplications increase expression of PR70 in human nevus, and increased expression in melanoma tissue correlates with survival via a nonimmunological mechanism. PPP2R3B overexpression induces pigment cell switching toward proliferation and away from migration. Importantly, this is independent of the known microphthalmia-associated transcription factor (MITF)-controlled switch, instead driven by C21orf91. Finally, C21orf91 is demonstrated to be downstream of MITF as well as PR70. CONCLUSION: This work confirms the power of a rare disease approach, identifying a previously unreported copy-number change predisposing to melanocytic neoplasia, and discovers C21orf91 as a potentially targetable hub in the control of phenotype switching.
Subject(s)
Melanoma , Nevus , Skin Neoplasms , Humans , Immunohistochemistry , Melanoma/genetics , Phenotype , Skin Neoplasms/geneticsABSTRACT
BACKGROUND: Receptor tyrosine kinase-like orphan receptor 2 (ROR2) is a Wnt5a receptor aberrantly expressed in cancer that was shown to either suppress or promote carcinogenesis in different tumor types. Our goal was to study the role of ROR2 in melanoma. METHODS: Gain and loss-of-function strategies were applied to study the biological function of ROR2 in melanoma. Proliferation assays, flow cytometry, and western blotting were used to evaluate cell proliferation and changes in expression levels of cell-cycle and proliferation markers. The role of ROR2 in tumor growth was assessed in xenotransplantation experiments followed by immunohistochemistry analysis of the tumors. The role of ROR2 in melanoma patients was assessed by analysis of clinical data from the Leeds Melanoma Cohort. RESULTS: Unlike previous findings describing ROR2 as an oncogene in melanoma, we describe that ROR2 prevents tumor growth by inhibiting cell-cycle progression and the proliferation of melanoma cells. The effect of ROR2 is mediated by inhibition of Akt phosphorylation and activity which, in turn, regulates the expression, phosphorylation, and localization of major cell-cycle regulators including cyclins (A, B, D, and E), CDK1, CDK4, RB, p21, and p27. Xenotransplantation experiments demonstrated that ROR2 also reduces proliferation in vivo, resulting in inhibition of tumor growth. In agreement with these findings, a higher ROR2 level favors thin and non-ulcerated primary melanomas with reduced mitotic rate and better prognosis. CONCLUSION: We conclude that the expression of ROR2 slows down the growth of primary tumors and contributes to prolonging melanoma survival. Our results demonstrate that ROR2 has a far more complex role than originally described.
Subject(s)
Cell Cycle , Cell Proliferation , Melanoma/genetics , Proto-Oncogene Proteins c-akt/genetics , Receptor Tyrosine Kinase-like Orphan Receptors/genetics , Proto-Oncogene Proteins c-akt/metabolismABSTRACT
Recent genome-wide association studies (GWAS) and subsequent meta-analyses have identified over 25 SNPs at 18 loci, together accounting for >15% of the genetic susceptibility to testicular germ cell tumour (TGCT). To identify further common SNPs associated with TGCT, here we report a three-stage experiment, involving 4098 cases and 18 972 controls. Stage 1 comprised previously published GWAS analysis of 307 291 SNPs in 986 cases and 4946 controls. In Stage 2, we used previously published customised Illumina iSelect genotyping array (iCOGs) data across 694 SNPs in 1064 cases and 10 082 controls. Here, we report new genotyping of eight SNPs showing some evidence of association in combined analysis of Stage 1 and Stage 2 in an additional 2048 cases of TGCT and 3944 controls (Stage 3). Through fixed-effects meta-analysis across three stages, we identified a novel locus at 3q25.31 (rs1510272) demonstrating association with TGCT [per-allele odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.06-1.27; P = 1.2 × 10(-9)].
Subject(s)
Chromosomes, Human, Pair 3 , Genetic Loci , Genetic Predisposition to Disease , Genome-Wide Association Study , Neoplasms, Germ Cell and Embryonal , Testicular Neoplasms , Alleles , Case-Control Studies , Female , Gene Frequency , Genotype , Humans , Linkage Disequilibrium , Male , Odds Ratio , Polymorphism, Single NucleotideABSTRACT
Determining early-stage prognostic markers and stratifying patients for effective treatment are two key challenges for improving outcomes for melanoma patients. Previous studies have used tumour transcriptome data to stratify patients into immune subgroups, which were associated with differential melanoma specific survival and potential predictive biomarkers. However, acquiring transcriptome data is a time-consuming and costly process. Moreover, it is not routinely used in the current clinical workflow. Here, we attempt to overcome this by developing deep learning models to classify gigapixel haematoxylin and eosin (H&E) stained pathology slides, which are well established in clinical workflows, into these immune subgroups. We systematically assess six different multiple instance learning (MIL) frameworks, using five different image resolutions and three different feature extraction methods. We show that pathology-specific self-supervised models using 10x resolution patches generate superior representations for the classification of immune subtypes. In addition, in a primary melanoma dataset, we achieve a mean area under the receiver operating characteristic curve (AUC) of 0.80 for classifying histopathology images into 'high' or 'low immune' subgroups and a mean AUC of 0.82 in an independent TCGA melanoma dataset. Furthermore, we show that these models are able to stratify patients into 'high' and 'low immune' subgroups with significantly different melanoma specific survival outcomes (log rank test, P< 0.005). We anticipate that MIL methods will allow us to find new biomarkers of high importance, act as a tool for clinicians to infer the immune landscape of tumours and stratify patients, without needing to carry out additional expensive genetic tests.
Subject(s)
Melanoma , Humans , Melanoma/diagnostic imaging , Melanoma/genetics , ROC Curve , Staining and Labeling , Workflow , BiomarkersABSTRACT
Peripheral blood transcriptomes from 383 patients with newly diagnosed melanoma were subjected to differential gene expression analysis. The hypotheses were that impaired systemic immunity is associated with poorer prognosis (thicker tumors and fewer tumor-infiltrating lymphocytes) and evidence of systemic inflammation (high-sensitivity CRP and fibrinogen levels). Higher fibrinogen levels were associated with thicker primary tumors. In single-gene analysis, high-sensitivity CRP levels were significantly associated with higher blood CD274 expression (coding for PD-L1), but each was independently prognostic, with high-sensitivity CRP associated with increased mortality and higher CD274 protective, independent of age. Pathway analysis identified downregulation of immune cell signaling pathways in the blood of people with thicker tumors and notable upregulation of signal transducer and activator of transcription 1 gene STAT1 in people with brisk tumor-infiltrating lymphocytes. Transcriptomic data provided evidence for increased NF-kB signaling with higher inflammatory markers but with reduction in expression of HLA class II molecules and higher CD274, suggesting that aberrant systemic inflammation is a significant mediator of reduced immune function in melanoma. In summary, transcriptomic data revealed evidence of reduced immune function in patients with thicker tumors and fewer tumor-infiltrating lymphocytes at diagnosis. Inflammatory markers were associated with thicker primaries and independently with death from melanoma, suggesting that systemic inflammation contributes to that reduced immune function.
ABSTRACT
The second most common mutation in melanoma occurs in NRAS oncogene, being a more aggressive disease that has no effective approved treatment. Besides, cellular plasticity limits better outcomes of the advanced and therapy-resistant patients. Peroxiredoxins (PRDXs) control cellular processes through direct hydrogen peroxide oxidation or by redox-relaying processes. Here, we demonstrated that PRDX2 could act as a modulator of multiple EMT markers in NRAS-mutated melanomas. PRDX2 knockdown lead to phenotypic changes towards invasion in human reconstructed skin and the treatment with a PRDX mimetic (gliotoxin), decreased migration in PRDX2-deficient cells. We also confirmed the favorable clinical outcome of patients expressing PRDX2 in a large primary melanoma cohort. This study contributes to our knowledge about genes involved in phenotype switching and opens a new perspective for PRDX2 as a biomarker and target in NRAS-mutated melanomas.
Subject(s)
Epithelial-Mesenchymal Transition , GTP Phosphohydrolases , Melanoma , Membrane Proteins , Mutation , Neoplasm Invasiveness , Peroxiredoxins , Humans , Melanoma/genetics , Melanoma/pathology , Melanoma/drug therapy , Melanoma/metabolism , Peroxiredoxins/genetics , Peroxiredoxins/metabolism , Cell Line, Tumor , GTP Phosphohydrolases/genetics , GTP Phosphohydrolases/metabolism , Membrane Proteins/genetics , Membrane Proteins/metabolism , Epithelial-Mesenchymal Transition/genetics , Epithelial-Mesenchymal Transition/drug effects , Cell Movement/drug effects , Cell Movement/genetics , Skin Neoplasms/genetics , Skin Neoplasms/pathology , Skin Neoplasms/metabolism , Skin Neoplasms/drug therapy , Female , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Gene Expression Regulation, NeoplasticABSTRACT
The analyses of genetic interaction between maternal and offspring genotypes are usually conducted considering a single locus. Here, we propose testing maternal × offspring (M×O) and maternal × maternal (M×M) genotype interactions involving two unlinked loci. We reformulate the log-linear approach of analyzing cases and their parents (family trios) to accommodate two loci, fit fuller models to avoid confounding in a first analysis step and propose that the model be reduced to the most prominent effects in a second step. We conduct extensive simulations to assess the validity and power of this approach under various model assumptions. We show that the approach is valid and has good power to detect M×O and M×M interactions. For example, the power to detect a dominant interaction relative risk of 1.5 (both M×O and M×M) is 70% with 300 trios and approaches 100% with 1,000 trios. Unlike the main effects, M×O and M×M interactions are conditionally independent of mating types, and consequently, their power is not affected by missing paternal genotypes. When applied to single-locus M×O interaction, our method is as powerful as other existing methods. Applying the method to testicular cancer, we found a nominally significant M×M interaction between single nucleotide polymorphisms from C-Kit Ligand (KITLG) and Sex Hormone Binding Globulin (SHBG) using 210 families (relative risk 2.2, P = 0.03). This finding supports a role of maternal hormones in offspring testicular cancer and warrants confirmation in a larger dataset.
Subject(s)
Genetic Predisposition to Disease , Models, Genetic , Testicular Neoplasms/genetics , Algorithms , Female , Genotype , Humans , Linear Models , Male , Parents , Polymorphism, Single Nucleotide , Reproducibility of Results , Sex Hormone-Binding Globulin/genetics , Stem Cell Factor/geneticsABSTRACT
Receptor tyrosine kinase-like orphan receptor 2 (ROR2) is a protein with important functions during embryogenesis that is dysregulated in human cancer. An intriguing feature of this receptor is that it plays opposite roles in different tumor types either promoting or inhibiting tumor progression. Understanding the complex role of this receptor requires a more profound exploration of both the altered biological and molecular mechanisms. Here, we describe that ROR2 promotes Epithelial-Mesenchymal Transition (EMT) by inducing cadherin switch and the upregulation of the transcription factors ZEB1, Twist, Slug, Snail, and HIF1A, together with a mesenchymal phenotype and increased migration. We show that ROR2 activates both p38 and ERK mitogen-activated protein kinase pathways independently of Wnt5a. Further, we demonstrated that the upregulation of EMT-related proteins depends on the hyperactivation of the ERK pathway far above the typical high constitutive activity observed in melanoma. In addition, ROR2 also promoted ERK phosphorylation, EMT, invasion, and necrosis in xenotransplanted mice. ROR2 also associates with EMT in tumor samples from melanoma patients where analysis of large cohorts revealed that increased ROR2 levels are linked to EMT signatures. This important role of ROR2 translates into melanoma patient' s prognosis since elevated ROR2 levels reduced overall survival and distant metastasis-free survival of patients with lymph node metastasis. In sum, these results demonstrate that ROR2 contributes to melanoma progression by inducing EMT and necrosis and can be an attractive therapeutic target for melanoma.
ABSTRACT
In melanoma, predicting which tumors will ultimately metastasize guides treatment decisions. Transcriptional signatures of primary tumors have been utilized to predict metastasis, but which among these are driver or passenger events remains unclear. We used data from the adjuvant AVAST-M trial to identify a predictive gene signature in localized tumors that ultimately metastasized. Using a zebrafish model of primary melanoma, we interrogated the top genes from the AVAST-M signature in vivo. This identified GRAMD1B, a cholesterol transfer protein, as a bona fide metastasis suppressor, with a majority of knockout animals rapidly developing metastasis. Mechanistically, excess free cholesterol or its metabolite 27-hydroxycholesterol promotes invasiveness via activation of an AP-1 program, which is associated with increased metastasis in humans. Our data demonstrate that the transcriptional seeds of metastasis are embedded within localized tumors, suggesting that early targeting of these programs can be used to prevent metastatic relapse. SIGNIFICANCE: We analyzed human melanoma transcriptomics data to identify a gene signature predictive of metastasis. To rapidly test clinical signatures, we built a genetic metastasis platform in adult zebrafish and identified GRAMD1B as a suppressor of melanoma metastasis. GRAMD1B-associated cholesterol overload activates an AP-1 program to promote melanoma invasion. This article is highlighted in the In This Issue feature, p. 1.
Subject(s)
Melanoma , Zebrafish , Animals , Humans , Zebrafish/genetics , Transcription Factor AP-1/genetics , Transcription Factor AP-1/metabolism , Neoplasm Recurrence, Local/genetics , Melanoma/pathology , Gene Expression Profiling , Neoplasm Metastasis , Gene Expression Regulation, NeoplasticABSTRACT
Oncogenes can initiate tumors only in certain cellular contexts, which is referred to as oncogenic competence. In melanoma, whether cells in the microenvironment can endow such competence remains unclear. Using a combination of zebrafish transgenesis coupled with human tissues, we demonstrate that GABAergic signaling between keratinocytes and melanocytes promotes melanoma initiation by BRAFV600E. GABA is synthesized in melanoma cells, which then acts on GABA-A receptors in keratinocytes. Electron microscopy demonstrates specialized cell-cell junctions between keratinocytes and melanoma cells, and multielectrode array analysis shows that GABA acts to inhibit electrical activity in melanoma/keratinocyte cocultures. Genetic and pharmacologic perturbation of GABA synthesis abrogates melanoma initiation in vivo. These data suggest that GABAergic signaling across the skin microenvironment regulates the ability of oncogenes to initiate melanoma. SIGNIFICANCE: This study shows evidence of GABA-mediated regulation of electrical activity between melanoma cells and keratinocytes, providing a new mechanism by which the microenvironment promotes tumor initiation. This provides insights into the role of the skin microenvironment in early melanomas while identifying GABA as a potential therapeutic target in melanoma. See related commentary by Ceol, p. 2128. This article is featured in Selected Articles from This Issue, p. 2109.
Subject(s)
Melanoma , Animals , Humans , Melanoma/drug therapy , Melanoma/genetics , Melanoma/pathology , Zebrafish , Melanocytes/pathology , Skin , Keratinocytes , Cell Transformation, Neoplastic/genetics , gamma-Aminobutyric Acid , Tumor MicroenvironmentABSTRACT
The use of high-throughput sequence data in genetic epidemiology allows the investigation of common and rare variants in the entire genome, thus increasing the amount of information and the potential number of statistical tests performed within one study. As a consequence, the problem of multiple testing may become even more pressing than in previous studies. As an important challenge, the exact number of statistical tests depends on the actual statistical method used. Furthermore, many statistical approaches for the analysis of sequence data require permutation. Thus it may be difficult to also use permutation to estimate correct type I error levels as in genome-wide association studies. In view of this, a separate group at Genetic Analysis Workshop 17 was formed with a focus on multiple testing. Here, we present the approaches used for the workshop. Apart from tackling the multiple testing problem, the new group focused on different issues. Some contributors developed and investigated modifications of existing collapsing methods. Others aimed at improving the identification of functional variants through a reduction and analysis of the underlying data dimensions. Two research groups investigated the overall accumulation of rare variation across the genome and its value in predicting phenotypes. Finally, other investigators left the path of traditional statistical analyses by reversing null and alternative hypotheses and by proposing a novel resampling method. We describe and discuss all these approaches.
Subject(s)
Data Interpretation, Statistical , Molecular Epidemiology/methods , Bias , Human Genome Project , Humans , Models, Genetic , Models, Statistical , Phenotype , Regression Analysis , Sequence AnalysisABSTRACT
In addition to mutations, epigenetic alterations are important contributors to malignant transformation and tumor progression. The aim of this work was to identify epigenetic events in which promoter or gene body DNA methylation induces gene expression changes that drive melanocyte malignant transformation and metastasis. We previously developed a linear mouse model of melanoma progression consisting of spontaneously immortalized melanocytes, premalignant melanocytes, a nonmetastatic tumorigenic, and a metastatic cell line. Here, through the integrative analysis of methylome and transcriptome data, we identified the relationship between promoter and/or gene body DNA methylation alterations and gene expression in early, intermediate, and late stages of melanoma progression. We identified adenylate cyclase type 3 (Adcy3) and inositol polyphosphate 4-phosphatase type II (Inpp4b), which affect tumor growth and metastatic potential, respectively. Importantly, the gene expression and DNA methylation profiles found in this murine model of melanoma progression were correlated with available clinical data from large population-based primary melanoma cohorts, revealing potential prognostic markers.
Subject(s)
DNA Methylation , Melanoma , Animals , Cell Transformation, Neoplastic/genetics , DNA Methylation/genetics , Epigenesis, Genetic , Gene Expression Regulation, Neoplastic , Humans , Melanocytes/metabolism , Melanocytes/pathology , Melanoma/pathology , Mice , Phenotype , PrognosisABSTRACT
Microscopic ulceration is an independent predictor of melanoma death. Here, we used systems biology to query the role of host and tumour-specific processes in defining the phenotype. Albumin level as a measure of systemic inflammation was predictive of fewer tumour-infiltrating lymphocytes and poorer survival in the Leeds Melanoma Cohort. Ulcerated melanomas were thicker and more mitotically active (with corresponding transcriptomic upregulated cell cycle pathways). Sequencing identified tumoural p53 and APC mutations, and TUBB2B amplification as associated with the phenotype. Ulcerated tumours had perturbed expression of cytokine genes, consistent with protumourigenic inflammation and histological and transcriptomic evidence for reduced adaptive immune cell infiltration. Pathway/network analysis of multiomic data using neural networks highlighted a role for the ß-catenin pathway in the ulceration, linking genomic changes in the tumour to immunosuppression and cell proliferation. In summary, the data suggest that ulceration is in part associated with genomic changes but that host factors also predict melanoma death with evidence of reduced immune responses to the tumour.
Subject(s)
Melanoma , Skin Neoplasms , Humans , Inflammation/genetics , Melanoma/metabolism , Skin Neoplasms/genetics , Skin Neoplasms/metabolism , Systems Biology , Ulcer/pathologyABSTRACT
BACKGROUND: Testicular germ cell tumors (TGCT), histologically classified as seminomas and nonseminomas, are believed to arise from primordial gonocytes, with the maturation process blocked when they are subjected to DNA methylation reprogramming. SNPs in DNA methylation machinery and folate-dependent one-carbon metabolism genes have been postulated to influence the proper establishment of DNA methylation. METHODS: In this pathway-focused investigation, we evaluated the association between 273 selected tag SNPs from 28 DNA methylation-related genes and TGCT risk. We carried out association analysis at individual SNP and gene-based level using summary statistics from the Genome Wide Association Study meta-analysis recently conducted by the international Testicular Cancer Consortium on 10,156 TGCT cases and 179,683 controls. RESULTS: In individual SNP analyses, seven SNPs, four mapping within MTHFR, were associated with TGCT risk after correction for multiple testing (q ≤ 0.05). Queries of public databases showed that three of these SNPs were associated with MTHFR changes in enzymatic activity (rs1801133) or expression level in testis tissue (rs12121543, rs1476413). Gene-based analyses revealed MTHFR (q = 8.4 × 10-4), methyl-CpG-binding protein 2 (MECP2; q = 2 × 10-3), and ZBTB4 (q = 0.03) as the top TGCT-associated genes. Stratifying by tumor histology, four MTHFR SNPs were associated with seminoma. In gene-based analysis MTHFR was associated with risk of seminoma (q = 2.8 × 10-4), but not with nonseminomatous tumors (q = 0.22). CONCLUSIONS: Genetic variants within MTHFR, potentially having an impact on the DNA methylation pattern, are associated with TGCT risk. IMPACT: This finding suggests that TGCT pathogenesis could be associated with the folate cycle status, and this relation could be partly due to hereditary factors.
Subject(s)
Neoplasms, Germ Cell and Embryonal , Seminoma , Testicular Neoplasms , DNA Methylation , Folic Acid , Genome-Wide Association Study , Humans , Male , Neoplasms, Germ Cell and Embryonal/genetics , Polymorphism, Single Nucleotide , Seminoma/genetics , Seminoma/metabolism , Seminoma/pathology , Testicular Neoplasms/geneticsABSTRACT
MX2 is an interferon inducible gene that is mostly known for its antiviral activity. We have previously demonstrated that MX2 is also associated with the tumorigenesis process in melanoma. However, it remains unknown which molecular mechanisms are regulated by MX2 in response to interferon signaling in this disease. Here, we report that MX2 is necessary for the establishment of an interferon-induced transcriptional profile partially through regulation of STAT1 phosphorylation and other interferon-related downstream factors, including proapoptotic tumor suppressor XAF1. MX2 and XAF1 expression tightly correlate in both cultured melanoma cell lines and in patient-derived primary and metastatic tumors, where they also are significantly related with survival. MX2 mediates IFN growth-inhibitory signals in both XAF1 dependent and independent ways and in a cell type and context-dependent manner. Higher MX2 expression renders melanoma cells more sensitive to targeted therapy drugs such as vemurafenib and trametinib; however, this effect is XAF1 independent. In summary, we uncovered a new mechanism in the complex regulation of interferon signaling in melanoma that can influence both survival and response to therapy.
Subject(s)
Adaptor Proteins, Signal Transducing/metabolism , Apoptosis Regulatory Proteins/metabolism , Biomarkers, Tumor/metabolism , Gene Expression Regulation, Neoplastic/drug effects , Interferons/pharmacology , Melanoma/drug therapy , Molecular Targeted Therapy , Myxovirus Resistance Proteins/metabolism , Adaptor Proteins, Signal Transducing/genetics , Antineoplastic Agents/pharmacology , Apoptosis , Apoptosis Regulatory Proteins/genetics , Biomarkers, Tumor/genetics , Cell Proliferation , Drug Synergism , Humans , Melanoma/metabolism , Melanoma/pathology , Myxovirus Resistance Proteins/genetics , Phosphorylation , Pyridones/pharmacology , Pyrimidinones/pharmacology , STAT1 Transcription Factor/genetics , STAT1 Transcription Factor/metabolism , Tumor Cells, CulturedABSTRACT
Despite advances in therapeutics, the progression of melanoma to metastasis still confers a poor outcome to patients. Nevertheless, there is a scarcity of biological models to understand cellular and molecular changes taking place along disease progression. Here, we characterized the transcriptome profiles of a multi-stage murine model of melanoma progression comprising a nontumorigenic melanocyte lineage (melan-a), premalignant melanocytes (4C), nonmetastatic (4C11-) and metastasis-prone (4C11+) melanoma cells. Clustering analyses have grouped the 4 cell lines according to their differentiated (melan-a and 4C11+) or undifferentiated/"mesenchymal-like" (4C and 4C11-) morphologies, suggesting dynamic gene expression patterns associated with the transition between these phenotypes. The cell plasticity observed in the murine melanoma progression model was corroborated by molecular markers described during stepwise human melanoma differentiation, as the differentiated cell lines in our model exhibit upregulation of transitory and melanocytic markers, whereas "mesenchymal-like" cells show increased expression of undifferentiated and neural crest-like markers. Sets of differentially expressed genes (DEGs) were detected at each transition step of tumor progression, and transcriptional signatures related to malignancy, metastasis and epithelial-to-mesenchymal transition were identified. Finally, DEGs were mapped to their human orthologs and evaluated in uni- and multivariate survival analyses using gene expression and clinical data of 703 drug-naïve primary melanoma patients, revealing several independent candidate prognostic markers. Altogether, these results provide novel insights into the molecular mechanisms underlying the phenotypic switch taking place during melanoma progression, reveal potential drug targets and prognostic biomarkers, and corroborate the translational relevance of this unique sequential model of melanoma progression.
Subject(s)
Cell Plasticity/genetics , Disease Progression , Melanoma/genetics , Melanoma/pathology , Transcriptome/genetics , Animals , Biomarkers, Tumor/analysis , Carcinogenesis/genetics , Carcinogenesis/pathology , Cell Line, Tumor , Disease Models, Animal , Epithelial-Mesenchymal Transition/physiology , Gene Expression Profiling , Gene Expression Regulation, Neoplastic/genetics , Humans , Melanocytes/pathology , Mice , Neoplasm Metastasis/genetics , Phenotype , Prognosis , RNA, Messenger/genetics , Sequence Analysis, RNAABSTRACT
Melanomas can have multiple coexisting cell states, including proliferative (PRO) versus invasive (INV) subpopulations that represent a "go or grow" trade-off; however, how these populations interact is poorly understood. Using a combination of zebrafish modeling and analysis of patient samples, we show that INV and PRO cells form spatially structured heterotypic clusters and cooperate in the seeding of metastasis, maintaining cell state heterogeneity. INV cells adhere tightly to each other and form clusters with a rim of PRO cells. Intravital imaging demonstrated cooperation in which INV cells facilitate dissemination of less metastatic PRO cells. We identified the TFAP2 neural crest transcription factor as a master regulator of clustering and PRO/INV states. Isolation of clusters from patients with metastatic melanoma revealed a subset with heterotypic PRO-INV clusters. Our data suggest a framework for the co-existence of these two divergent cell populations, in which heterotypic clusters promote metastasis via cell-cell cooperation.
Subject(s)
Cluster Analysis , Melanoma/metabolism , Neoplasm Metastasis/pathology , Neoplastic Cells, Circulating/pathology , Animals , Gene Expression Regulation, Neoplastic/physiology , Melanoma/pathology , Neural Crest/pathology , ZebrafishABSTRACT
Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.