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Pathways associated with G9a copy number in the Leeds melanoma cohort

Epigenetic regulators, when genomically altered, may become driver oncogenes that mediate otherwise unexplained pro-oncogenic changes lacking a clear genetic stimulus, such as activation of the WNT/β-catenin pathway in melanoma. This study identifies previously unrecognized recurrent activating mutations in the G9a histone methyltransferase gene, as well as G9a genomic copy gains in approximately 26% of human melanomas, which collectively drive tumor growth and an immunologically sterile microenvironment beyond melanoma. Furthermore, the WNT pathway is identified as a key tumorigenic target of G9a gain-of-function, via suppression of the WNT antagonist DKK1. Importantly, genetic or pharmacologic suppression of mutated or amplified G9a using multiple in vitro and in vivo models demonstrates that G9a is a druggable target for therapeutic intervention in melanoma and other cancers harboring G9a genomic aberrations.Significance:Oncogenic G9a abnormalities drive tumorigenesis and the “cold” immune microenvironment by activating WNT signaling through DKK1 repression. These results reveal a key druggable mechanism for tumor development and identify strategies to restore “hot” tumor immune microenvironments.This article is highlighted in the In This Issue feature, p. 890

The immune response to melanoma improves the survival in untreated patients and predicts the response to immune checkpoint blockade. Here, we report genetic and environmental predictors of the immune response in a large primary cutaneous melanoma cohort. Bioinformatic analysis of 703 tumor transcriptomes was used to infer immune cell infiltration and to categorize tumors into immune subgroups, which were then investigated for association with biological pathways, clinicopathologic factors, and copy number alterations. Three subgroups, with “low”, “intermediate”, and “high” immune signals, were identified in primary tumors and replicated in metastatic tumors. Genes in the low subgroup were enriched for cell-cycle and metabolic pathways, whereas genes in the high subgroup were enriched for IFN and NF-κB signaling. We identified high MYC expression partially driven by amplification, HLA-B downregulation, and deletion of IFNγ and NF-κB pathway genes as the regulators of immune suppression. Furthermore, we showed that cigarette smoking, a globally detrimental environmental factor, modulates immunity, reducing the survival primarily in patients with a strong immune response. Together, these analyses identify a set of factors that can be easily assessed that may serve as predictors of response to immunotherapy in patients with melanoma.Significance:These findings identify novel genetic and environmental modulators of the immune response against primary cutaneous melanoma and predict their impact on patient survival.See related commentary by Anichini, p. 2457

Gene lists per immune cell type after successive filtration steps.

Purpose:Previously identified transcriptomic signatures have been based on primary and metastatic melanomas with relatively few American Joint Committee on Cancer (AJCC) stage I tumors, given difficulties in sampling small tumors. The advent of adjuvant therapies has highlighted the need for better prognostic and predictive biomarkers, especially for AJCC stage I and stage II disease.Experimental Design:A total of 687 primary melanoma transcriptomes were generated from the Leeds Melanoma Cohort (LMC). The prognostic value of existing signatures across all the AJCC stages was tested. Unsupervised clustering was performed, and the prognostic value of the resultant signature was compared with that of sentinel node biopsy (SNB) and tested as a biomarker in three published immunotherapy datasets.Results:Previous Lund and The Cancer Genome Atlas signatures predicted outcome in the LMC dataset (P = 10−8 to 10−4) but showed a significant interaction with AJCC stage (P = 0.04) and did not predict outcome in stage I tumors (P = 0.3–0.7). Consensus-based classification of the LMC dataset identified six classes that predicted outcome, notably in stage I disease. LMC class was a similar indicator of prognosis when compared with SNB, and it added prognostic value to the genes reported by Gerami and colleagues. One particular LMC class consistently predicted poor outcome in patients receiving immunotherapy in two of three tested datasets. Biological characterization of this class revealed high JUN and AXL expression and evidence of epithelial-to-mesenchymal transition.Conclusions:A transcriptomic signature of primary melanoma was identified with prognostic value, including in stage I melanoma and in patients undergoing immunotherapy.

Additional information on methods used and supplementary figures and tables. Figure S1: Schematic summary of consensus clustering; Figure S2: Comparison of the newly obtained immune subgroups with two published melanoma molecular signatures; Figure S3: Whole transcriptome differences among the three immune subgroups; Figure S4: Association of GPR15 gene expression, smoking and the three immune subgroups; Table S1: Survival analysis for the immune cell scores in our data (LMC) and TCGA datasets; Table S2: Association between clinico-pathological characteristics and the three immune subgroups in the LMC; Table S3: Differences in the immune cell scores between ever and never smokers in the High Immune Subgroup; Table S4: Association between smoking and tumor histological features in the High Immune Subgroup.

List of 70 genes shared between the signature used to generate the three immune subgroups in this study and the TCGA signature as well as tables of additional results from the analysis of the 3 immune subgroups: Genes and pathways upregulated in the High and Low Immune Subgroups; List of genes significantly correlating with MYC in melanoma cell lines; Results of copy number data analysis for MYC, NF-kappa B and IFN-gamma pathways; Results of the survival analyses of environmental and clinico-pathological factors with alternative definitions of smoking variable.

Supplementary Figures and tables

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 β-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.

Purpose: Previously identified transcriptomic signatures have been based on primary and metastatic melanomas with relatively few American Joint Committee on Cancer (AJCC) stage I tumors, given difficulties in sampling small tumors. The advent of adjuvant therapies has highlighted the need for better prognostic and predictive biomarkers, especially for AJCC stage I and stage II disease. Experimental Design: A total of 687 primary melanoma transcriptomes were generated from the Leeds Melanoma Cohort (LMC). The prognostic value of existing signatures across all the AJCC stages was tested. Unsupervised clustering was performed, and the prognostic value of the resultant signature was compared with that of sentinel node biopsy (SNB) and tested as a biomarker in three published immunotherapy datasets. Results: Previous Lund and The Cancer Genome Atlas signatures predicted outcome in the LMC dataset (P = 10−8 to 10−4) but showed a significant interaction with AJCC stage (P = 0.04) and did not predict outcome in stage I tumors (P = 0.3–0.7). Consensus-based classification of the LMC dataset identified six classes that predicted outcome, notably in stage I disease. LMC class was a similar indicator of prognosis when compared with SNB, and it added prognostic value to the genes reported by Gerami and colleagues. One particular LMC class consistently predicted poor outcome in patients receiving immunotherapy in two of three tested datasets. Biological characterization of this class revealed high JUN and AXL expression and evidence of epithelial-to-mesenchymal transition. Conclusions: A transcriptomic signature of primary melanoma was identified with prognostic value, including in stage I melanoma and in patients undergoing immunotherapy.

Skin Cutaneous Melanoma (SKCM) is a type of cancer that arises from the occurrence of genetic mutations in melanocytes and is the most aggressive and fatal type of cancer affecting mostly the Caucasian population with increasing incidences in Asia. Tumors and lesions are highly heterogeneous comprised of cancerous and non-cancerous cells, and the admixture is thought to have an important role in tumor growth and progression of the disease. This study features a system capable of estimating tumor purity from RNA-Seq gene expression data using Gradient Boosting Machines and providing individual-specific survival prediction (death or progression of the disease) using a set of clinical features and the tumor purity estimate from the trained model. The performance of the models for tumor purity using the entire set of gene expression and selected features by importance scores were compared. The survival models have shown that the tumor purity estimate from the trained model provided additional prognostic information over established clinical features including age, tumor stage, and sex. Survival models using Cox Proportional Hazards are provided to allow users to evaluate and probe the models for further in-sights, whether with past historical cases, current or hypothetical patients. Future model improvements and prospective replication will be necessary to demonstrate true clinical utility.

Epigenetic regulators, when genomically altered, may become driver oncogenes that mediate otherwise unexplained pro-oncogenic changes lacking a clear genetic stimulus, such as activation of the WNT/β-catenin pathway in melanoma. This study identifies previously unrecognized recurrent activating mutations in the G9a histone methyltransferase gene, as well as G9a genomic copy gains in approximately 26% of human melanomas, which collectively drive tumor growth and an immunologically sterile microenvironment beyond melanoma. Furthermore, the WNT pathway is identified as a key tumorigenic target of G9a gain-of-function, via suppression of the WNT antagonist DKK1. Importantly, genetic or pharmacologic suppression of mutated or amplified G9a using multiple in vitro and in vivo models demonstrates that G9a is a druggable target for therapeutic intervention in melanoma and other cancers harboring G9a genomic aberrations. Significance: Oncogenic G9a abnormalities drive tumorigenesis and the “cold” immune microenvironment by activating WNT signaling through DKK1 repression. These results reveal a key druggable mechanism for tumor development and identify strategies to restore “hot” tumor immune microenvironments. This article is highlighted in the In This Issue feature, p. 890

9548 Background: The field of liquid biopsy provides a promising alternative to standard tissue biopsies. Previous work has shown that plasma circulating cell-free DNA (ctDNA) can reflect the heterogeneous spectrum of mutations in cancer including metastatic melanoma. Our project aimed to establish and statistically validate plasma-based assays for tumour load and therapy monitoring in melanoma. Methods: On a large cohort of stage III and stage IV melanoma patients (N = 96) who received signalling targeted or immune checkpoint inhibitors we showed that the most common oncogenic drivers of this disease such as the BRAFV600E, NRASQ61 and the TERTC250T and TERTC228T promoter mutations (termed TERTprom) can be analysed in ctDNA with highly sensitive droplet digital PCR technology (detection of mutant ctDNA down to 0.01% analytical sensitivity). Results: Our research has demonstrated that ctDNA (irrespective of the genotype) significantly correlates with tumour stage (P < 0.05). Using receiver operating characteristics (ROC) analyses thresholds were established for risk stratification and response prediction. Elevated ctDNA at baseline was a significant predictor of disease progression compared to elevated LDH or S100 in multivariable cox proportional hazards model (Hazard ratio [HR] 7.43, P = 0.05). During therapy, patients with low ctDNA load (below the ROC threshold) had significantly better radiological outcomes and prolonged progression free survival (PFS) compared to patients with high ctDNA load (P < 0.0001). Our findings were confirmed on an independent cohort of metastatic melanoma patients (N = 35) treated with immune checkpoint inhibitors, where also during therapy low ctDNA load correlated with prolonged PFS (P = 0.003). An added benefit of ctDNA was demonstrated in about 80% of the patients, where ctDNA analyses preceded the radiological diagnosis of response or relapse. Progression was detected in plasma ctDNA in average 3.5 months earlier as compared to routine imaging techniques. Finally, we demonstrated that the occurrence of NRASQ61 mutation in BRAFV600-inhibitor treated patients at therapy baseline was associated with treatment failure. The sub-clonal NRASQ61 mutation at therapy baseline was an independent predictor of shorter PFS (HR 2.69, P = 0.02) as compared to BRAFV600E patients without the NRASQ61 mutation at therapy baseline. Conclusions: In sum, our results support the value of ctDNA as a sensitive biomarker for real-time therapy monitoring and early detection of disease progression.

The immune response to melanoma improves the survival in untreated patients and predicts the response to immune checkpoint blockade. Here, we report genetic and environmental predictors of the immune response in a large primary cutaneous melanoma cohort. Bioinformatic analysis of 703 tumor transcriptomes was used to infer immune cell infiltration and to categorize tumors into immune subgroups, which were then investigated for association with biological pathways, clinicopathologic factors, and copy number alterations. Three subgroups, with “low”, “intermediate”, and “high” immune signals, were identified in primary tumors and replicated in metastatic tumors. Genes in the low subgroup were enriched for cell-cycle and metabolic pathways, whereas genes in the high subgroup were enriched for IFN and NF-κB signaling. We identified high MYC expression partially driven by amplification, HLA-B downregulation, and deletion of IFNγ and NF-κB pathway genes as the regulators of immune suppression. Furthermore, we showed that cigarette smoking, a globally detrimental environmental factor, modulates immunity, reducing the survival primarily in patients with a strong immune response. Together, these analyses identify a set of factors that can be easily assessed that may serve as predictors of response to immunotherapy in patients with melanoma. Significance: These findings identify novel genetic and environmental modulators of the immune response against primary cutaneous melanoma and predict their impact on patient survival. See related commentary by Anichini, p. 2457

1α,25-Dihydroxyvitamin D3 signals via the vitamin D receptor (VDR). Higher serum vitamin D is associated with thinner primary melanoma and better outcome, although a causal mechanism has not been established. As patients with melanoma commonly avoid sun exposure, and consequent vitamin D deficiency might worsen outcomes, we interrogated 703 primary melanoma transcriptomes to understand the role of vitamin D–VDR signaling and replicated the findings in The Cancer Genome Atlas metastases. VDR expression was independently protective for melanoma-related death in both primary and metastatic disease. High tumor VDR expression was associated with upregulation of pathways mediating antitumor immunity and corresponding with higher imputed immune cell scores and histologically detected tumor-infiltrating lymphocytes. High VDR–expressing tumors had downregulation of proliferative pathways, notably Wnt/β-catenin signaling. Deleterious low VDR levels resulted from promoter methylation and gene deletion in metastases. Vitamin D deficiency ( Significance: VDR expression could potentially be used as a biomarker to stratify patients with melanoma that may respond better to immunotherapy.

Lung cancer is one of the most fatal types of cancer around the world. The World Cancer Research Fund International estimated that in 2012, 1.8 million new cases of this disease were diagnosed. Early diagnosis and classification of this condition prompts medical professionals on safer and more effective treatment of the patient. Availability of microarray technology has paved the way to exploring the genes and its association in various diseases like lung cancer. This study utilized genetic algorithm as a method of feature (genes) selection for the support vector machine and artificial neural network to classify lung cancer status of a patient. Genetic algorithm (GA) successfully identified genes that classify patient lung cancer status with notable predictive performance.

PURPOSE Circulating cell-free tumor DNA (ctDNA) reflects the heterogeneous spectrum of tumor-specific mutations, especially in systemic disease. We validated plasma-based assays that allow the dynamic quantitative detection of ctDNA as a prognostic biomarker for tumor load and prediction of therapy response in melanoma. MATERIALS and METHODS We analyzed plasma-derived ctDNA from a large training cohort (n = 96) of patients with advanced-stage melanoma, with assays for the BRAFV600E and NRASQ61 driver mutations as well as TERTC250T and TERTC228T promoter mutations. An independent patient cohort (n = 35) was used to validate the utility of ctDNA monitoring under mitogen-activated protein kinase–targeted or immune checkpoint therapies. RESULTS Elevated plasma ctDNA level at baseline was an independent prognostic factor of disease progression when compared with serum S100 and lactate dehydrogenase levels in multivariable analyses (hazard ratio [HR], 7.43; 95% CI, 1.01 to 55.19; P = .05). The change in ctDNA levels during therapy correlated with treatment response, where increasing ctDNA was predictive for shorter progression-free survival (eg, for BRAFV600E ctDNA, HR, 3.70; 95% CI, 1.86 to 7.34; P < .001). Increasing ctDNA levels predicted disease progression significantly earlier than did routine radiologic scans ( P < .05), with a mean lead time of 3.5 months. NRAS-mutant ctDNA was detected in a significant proportion of patients with BRAF-mutant tumors under therapy, but unexpectedly also at baseline. In vitro sensitivity studies suggested that this represents higher-than-expected intratumoral heterogeneity. The detection of NRASQ61 ctDNA in baseline samples of patients with BRAFV600E mutation who were treated with mitogen-activated protein kinase inhibitors significantly correlated with shorter progression-free survival (HR, 3.18; 95% CI, 1.31 to 7.68; P = .03) and shorter overall survival (HR, 4.08; 95% CI, 1.57 to 10.58; P = .01). CONCLUSION Our results show the potential role of ctDNA measurement as a sensitive monitoring and prediction tool for the early assessment of disease progression and therapeutic response in patients with metastatic melanoma.