GNAQ and GNA11 mutant nonuveal melanoma: a subtype distinct from both cutaneous and uveal melanoma

Molecular Frontiers in Melanoma: Pathogenesis, Diagnosis, and Therapeutic Advances

Melanoma, a highly aggressive skin cancer, is characterized by rapid progression and high mortality. Recent advances in molecular pathogenesis have shed light on genetic and epigenetic changes that drive melanoma development. This review provides an overview of these developments, focusing on molecular mechanisms in melanoma genesis. It highlights how mutations, particularly in the BRAF, NRAS, c-KIT, and GNAQ/GNA11 genes, affect critical signaling pathways. The evolution of diagnostic techniques, such as genomics, transcriptomics, liquid biopsies, and molecular biomarkers for early detection and prognosis, is also discussed. The therapeutic landscape has transformed with targeted therapies and immunotherapies, improving patient outcomes. This paper examines the efficacy, challenges, and prospects of these treatments, including recent clinical trials and emerging strategies. The potential of novel treatment strategies, including neoantigen vaccines, adoptive cell transfer, microbiome interactions, and nanoparticle-based combination therapy, is explored. These advances emphasize the challenges of therapy resistance and the importance of personalized medicine. This review underlines the necessity for evidence-based therapy selection in managing the increasing global incidence of melanoma.

Spatiotemporal Optical Control of Gαq-PLCβ Interactions

Cells experience time-varying and spatially heterogeneous chemokine signals in vivo, activating cell surface proteins including G protein-coupled receptors (GPCRs). The Gαq pathway activation by GPCRs is a major signaling axis with broad physiological and pathological significance. Compared with other Gα members, GαqGTP activates many crucial effectors, including PLCβ (Phospholipase Cβ) and Rho GEFs (Rho guanine nucleotide exchange factors). PLCβ regulates many key processes, such as hematopoiesis, synaptogenesis, and cell cycle, and is therefore implicated in terminal-debilitating diseases, including cancer, epilepsy, Huntington's Disease, and Alzheimer's Disease. However, due to a lack of genetic and pharmacological tools, examining how the dynamic regulation of PLCβ signaling controls cellular physiology has been difficult. Since activated PLCβ induces several abrupt cellular changes, including cell morphology, examining how the other pathways downstream of Gq-GPCRs contribute to the overall signaling has also been difficult. Here we show the engineering, validation, and application of a highly selective and efficient optogenetic inhibitor (Opto-dHTH) to completely disrupt GαqGTP-PLCβ interactions reversibly in user-defined cellular-subcellular regions on optical command. Using this newly gained PLCβ signaling control, our data indicate that the molecular competition between RhoGEFs and PLCβ for GαqGTP determines the potency of Gq-GPCR-governed directional cell migration.

Genetic Aspects of Conjunctival Melanoma: A Review

Conjunctival melanoma (CM) is a rare but aggressive cancer. Over the past decade, molecular studies using rapidly advancing technologies have increasingly improved our understanding of CM genetics. CMs are mainly characterized by dysregulated MAPK and PI3K/AKT/mTOR pathways, driven by commonly mutated (BRAF, NRAS, NF1) or less commonly mutated (KIT, PTEN) genes. Another group of genes frequently mutated in CMs include TERT and ATRX, with known roles in telomere maintenance and chromatin remodeling/epigenetic regulation. Uveal melanoma-related genes (BAP1, SF3B1, GNAQ/11) can also be mutated in CMs, albeit infrequently. Additional CM-related mutated genes have increasingly been identified using more comprehensive genetic analyses, awaiting further confirmation in additional/larger studies. As a tumor arising in a partly sun-exposed mucosal tissue, CM exhibits a distinct genomic profile, including the frequent presence of an ultraviolet (UV) signature (and high mutational load) and also the common occurrence of large structural variations (distributed across the genome) in addition to specific gene mutations. The knowledge gained from CM genetic studies to date has led to new therapeutic avenues, including the use of targeted and/or immuno-therapies with promising outcomes in several cases. Accordingly, the implementation of tumor genetic testing into the routine clinical care of CM patients holds promise to further improve and personalize their treatments. Likewise, a growing knowledge of poor prognosis-associated genetic changes in CMs (NRAS, TERT, and uveal melanoma signature mutations and chromosome 10q deletions) may ultimately guide future strategies for prognostic testing to further improve clinical outcomes (by tailoring surveillance and considering prophylactic treatments in patients with high-risk primary tumors).

Spatiotemporal optical control of Gαq-PLCβ interactions

Cells experience time-varying and spatially heterogeneous chemokine signals in vivo, activating cell surface proteins, including G protein-coupled receptors (GPCRs). The Gαq pathway activation by GPCRs is a major signaling axis with a broad physiological and pathological significance. Compared to other Gα members, GαqGTP activates many crucial effectors, including PLCβ (Phospholipase Cβ) and Rho GEFs (Rho guanine nucleotide exchange factors). PLCβ regulates many key processes, such as hematopoiesis, synaptogenesis, and cell cycle, and is therefore implicated in terminal - debilitating diseases, including cancer, epilepsy, Huntington's Disease, and Alzheimer's Disease. However, due to a lack of genetic and pharmacological tools, examining how the dynamic regulation of PLCβ signaling controls cellular physiology has been difficult. Since activated PLCβ induces several abrupt cellular changes, including cell morphology, examining how the other pathways downstream of Gq-GPCRs contribute to the overall signaling has also been difficult. Here we show the engineering, validation, and application of a highly selective and efficient optogenetic inhibitor (Opto-dHTH) to completely disrupt GαqGTP-PLCβ interactions reversibly in user-defined cellular-subcellular regions on optical command. Using this newly gained PLCβ signaling control, our data indicate that the molecular competition between RhoGEFs and PLCβ for GαqGTP determines the potency of Gq-GPCR-governed directional cell migration.

Integrative analysis of DNA methylomes reveals novel cell-free biomarkers in lung adenocarcinoma

Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.

Trametinib in Patients With NF1-, GNAQ-, or GNA11-Mutant Tumors: Results From the NCI-MATCH ECOG-ACRIN Trial (EAY131) Subprotocols S1 and S2

PURPOSE

NCI-MATCH is a precision medicine trial using genomic testing to allocate patients with advanced malignancies to targeted treatment subprotocols. This report combines two subprotocols evaluating trametinib, a MEK1/2 inhibitor, in patients with Neurofibromatosis 1 (NF1[S1] or GNA11/Q [S2]) altered tumors.

METHODS

Eligible patients had tumors with deleterious inactivating NF1 or GNA11/Q mutations by the customized Oncomine AmpliSeq panel. Prior MEK inhibitor treatment was excluded. Glioblastomas (GBMs) were permitted, including malignancies associated with germline NF1 mutations (S1 only). Trametinib was administered at 2 mg once daily over 28-day cycles until toxicity or disease progression. Primary end point was objective response rate (ORR). Secondary end points included progression-free survival (PFS) at 6 months, PFS, and overall survival. Exploratory analyses included co-occurring genomic alterations and PTEN loss.

RESULTS

Fifty patients were eligible and started therapy: 46 with NF1 mutations (S1) and four with GNA11 mutations (S2). In the NF1 cohort, nonsense single-nucleotide variants were identified in 29 and frameshift deletions in 17 tumors. All in S2 had nonuveal melanoma and GNA11 Q209L variant. Two partial responses (PR) were noted in S1, one patient each with advanced lung cancer and GBM for an ORR of 4.3% (90% CI, 0.8 to 13.1). One patient with melanoma in S2 had a PR (ORR, 25%; 90% CI, 1.3 to 75.1). Prolonged stable disease (SD) was also noted in five patients (four in S1 and one in S2) with additional rare histologies. Adverse events were as previously described with trametinib. Comutations in TP53 and PIK3CA were common.

CONCLUSION

Although these subprotocols did not meet the primary end point for ORR, significant responses or prolonged SD noted in some disease subtypes warrants further investigation.

CD8/PD-L1 immunohistochemical reactivity and gene alterations in cutaneous squamous cell carcinoma

In recent years, several immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) or PD-1 have been developed for cancer therapy. The genetic background of tumors and factors that influence PD-L1 expression in tumor tissues are not yet elucidated in cutaneous squamous cell carcinoma (cSCC). CD8-positive tumor-infiltrating lymphocytes (TILs) are known to be related to tumor immunity. Here, we aimed to study the relationship between CD8/PD-L1 immunohistochemical reactivity and gene alterations in cSCC. Tumorigenic genes were examined to identify gene alterations using next-generation sequencing (NGS). We collected 27 cSCC tissue samples (from 13 metastatic and 14 non-metastatic patients at primary diagnosis). We performed immunohistochemical staining for CD8 and PD-L1, and NGS using a commercially available sequencing panel (Illumina Cancer Hotspot Panel V2) that targets 50 cancer-associated genes. Immunohistochemically, CD8-positive TILs showed a high positive score in cSCC without metastasis; in these cases, cSCC occurred predominantly in sun-exposed areas, the tumor size was smaller, and the total gene variation numbers were notably low. The tumor depth, PD-L1 positivity, and gene variation number with or without tumor metastasis were not related, but the gene variation number tended to be higher in cSCCs arising in non-sun-exposed areas. Tumor metastasis was more common in cSCC arising in non-sun-exposed areas, which decreased the number of TILs or CD8-positive cells. From a genetic perspective, the total gene alterations were higher in cSCC with metastasis. Among them, ERBB4 and NPM1 are presumably involved in cSCC tumorigenesis; in addition, GNAQ, GNAS, JAK2, NRAS, IDH2, and CTNNB1 may be related to tumor metastasis. These results provide information on potential genes that can be targeted for cSCC therapy and on immune checkpoint inhibitors that may be used for cSCC therapy.

PTK6 inhibits autophagy to promote uveal melanoma tumorigenesis by binding to SOCS3 and regulating mTOR phosphorylation

Autophagy dysfunction is one of the common causes of tumor formation and plays an important role in uveal melanoma (UM). However, little is known about the regulatory mechanisms of autophagy in UM. Here, we show that PTK6 can promote the proliferation, migration, and invasion of UM cells by inhibiting autophagy. SOCS3 can inhibit the proliferation, migration, and invasion of UM cells. Overexpression of SOCS3 can partially rescue the PTK6-induced promotion of UM cell proliferation, migration, and invasion. Mechanistically, PTK6 can bind to SOCS3, and SOCS3 can downregulate the expression of PTK6. Furthermore, PTK6 can upregulate the phosphorylation of mTOR to inhibit autophagy. Taken together, our findings demonstrate the functions of PTK6 and SOCS3 in UM cells and targeting the SOCS3-PTK6 signaling axis might be a novel and promising therapeutic strategy for patients with UM.

Somatic mutation distribution across tumour cohorts provides a signal for positive selection in cancer

Cancer gene discovery is reliant on distinguishing driver mutations from a multitude of passenger mutations in tumour genomes. While driver genes may be revealed based on excess mutation recurrence or clustering, there is a need for orthogonal principles. Here, we take advantage of the fact that non-cancer genes, containing only passenger mutations under neutral selection, exhibit a likelihood of mutagenesis in a given tumour determined by the tumour's mutational signature and burden. This relationship can be disrupted by positive selection, leading to a difference in the distribution of mutated cases across a cohort for driver and passenger genes. We apply this principle to detect cancer drivers independently of recurrence in large pan-cancer cohorts, and show that our method (SEISMIC) performs comparably to traditional approaches and can provide resistance to known confounding mutational phenomena. Being based on a different principle, the approach provides a much-needed complement to existing methods for detecting signals of selection.

Uveal Melanoma Metastasis

Uveal melanoma (UM) is characterized by relatively few, highly incident molecular alterations and their association with metastatic risk is deeply understood. Nevertheless, this knowledge has so far not led to innovative therapies for the successful treatment of UM metastases or for adjuvant therapy, leaving survival after diagnosis of metastatic UM almost unaltered in decades. The driver mutations of UM, mainly in the G-protein genes GNAQ and GNA11, activate the MAP-kinase pathway as well as the YAP/TAZ pathway. At present, there are no drugs that target the latter and this likely explains the failure of mitogen activated kinase kinase inhibitors. Immune checkpoint blockers, despite the game changing effect in cutaneous melanoma (CM), show only limited effects in UM probably because of the low mutational burden of 0.5 per megabase and the unavailability of antibodies targeting the main immune checkpoint active in UM. The highly pro-tumorigenic microenvironment of UM also contributes to therapy resistance. However, T-cell redirection by a soluble T-cell receptor that is fused to an anti-CD3 single-chain variable fragment, local, liver specific therapy, new immune checkpoint blockers, and YAP/TAZ specific drugs give new hope to repeating the success of innovative therapy obtained for CM.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

Biomarkers for Diagnosis, Prognosis and Response to Immunotherapy in Melanoma

Simple Summary

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

Abstract

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

Construction of a Promising Tumor-Infiltrating CD8+ T Cells Gene Signature to Improve Prediction of the Prognosis and Immune Response of Uveal Melanoma

Background

CD8+ T cells work as a key effector of adaptive immunity and are closely associated with immune response for killing tumor cells. It is crucial to understand the role of tumor-infiltrating CD8+ T cells in uveal melanoma (UM) to predict the prognosis and response to immunotherapy.

Materials and Methods

Single-cell transcriptomes of UM with immune-related genes were combined to screen the CD8+ T-cell-associated immune-related genes (CDIRGs) for subsequent analysis. Next, a prognostic gene signature referred to tumor-infiltrating CD8+ T cells was constructed and validated in several UM bulk RNA sequencing datasets. The risk score of UM patients was calculated and classified into high- or low-risk subgroup. The prognostic value of risk score was estimated by using multivariate Cox analysis and Kaplan–Meier survival analysis. Moreover, the potential ability of gene signature for predicting immunotherapy response was further explored.

Results

In total, 202 CDIRGs were screened out from the single-cell RNA sequencing of GSE139829. Next, a gene signature containing three CDIRGs (IFNGR1, ANXA6, and TANK) was identified, which was considered as an independent prognostic indicator to robustly predict overall survival (OS) and metastasis-free survival (MFS) of UM. In addition, the UM patients were classified into high- and low-risk subgroups with different clinical characteristics, distinct CD8+ T-cell immune infiltration, and immunotherapy response. Gene set enrichment analysis (GSEA) showed that immune pathways such as allograft rejection, inflammatory response, interferon alpha and gamma response, and antigen processing and presentation were all positively activated in low-risk phenotype.

Conclusion

Our work gives an inspiration to explain the limited response for the current immune checkpoint inhibitors to UM. Besides, we constructed a novel gene signature to predict prognosis and immunotherapy responses, which may be regarded as a promising therapeutic target.

Cutaneous Melanoma Classification: The Importance of High-Throughput Genomic Technologies

Cutaneous melanoma is an aggressive tumor responsible for 90% of mortality related to skin cancer. In the recent years, the discovery of driving mutations in melanoma has led to better treatment approaches. The last decade has seen a genomic revolution in the field of cancer. Such genomic revolution has led to the production of an unprecedented mole of data. High-throughput genomic technologies have facilitated the genomic, transcriptomic and epigenomic profiling of several cancers, including melanoma. Nevertheless, there are a number of newer genomic technologies that have not yet been employed in large studies. In this article we describe the current classification of cutaneous melanoma, we review the current knowledge of the main genetic alterations of cutaneous melanoma and their related impact on targeted therapies, and we describe the most recent high-throughput genomic technologies, highlighting their advantages and disadvantages. We hope that the current review will also help scientists to identify the most suitable technology to address melanoma-related relevant questions. The translation of this knowledge and all actual advancements into the clinical practice will be helpful in better defining the different molecular subsets of melanoma patients and provide new tools to address relevant questions on disease management. Genomic technologies might indeed allow to better predict the biological - and, subsequently, clinical - behavior for each subset of melanoma patients as well as to even identify all molecular changes in tumor cell populations during disease evolution toward a real achievement of a personalized medicine.

Making a melanoma: Molecular and cellular changes underlying melanoma initiation

Melanoma arises from the melanocyte lineage and is the most aggressive and lethal form of skin cancer. There are several genetic, genomic, and cellular changes associated with melanoma initiation. Here, we discuss these alterations and the melanoma cells of origin in which they are proposed to promote melanomagenesis.

Comprehensive analysis of cutaneous and uveal melanoma liver metastases

BACKGROUND

The profound disparity in response to immune checkpoint blockade (ICB) by cutaneous melanoma (CM) and uveal melanoma (UM) patients is not well understood. Therefore, we characterized metastases of CM and UM from the same metastatic site (liver), in order to dissect the potential underlying mechanism in differential response on ICB.

METHODS

Tumor liver samples from CM (n=38) and UM (n=28) patients were analyzed at the genomic (whole exome sequencing), transcriptional (RNA sequencing) and protein (immunohistochemistry and GeoMx Digital Spatial Profiling) level.

RESULTS

Comparison of CM and UM metastases from the same metastatic site revealed that, although originating from the same melanocyte lineage, CM and UM differed in somatic mutation profile, copy number profile, tumor mutational burden (TMB) and consequently predicted neoantigens. A higher melanin content and higher expression of the melanoma differentiation antigen MelanA was observed in liver metastases of UM patients. No difference in B2M and human leukocyte antigen-DR (HLA-DR) expression was observed. A higher expression of programmed cell death ligand 1 (PD-L1) was found in CM compared with UM liver metastases, although the majority of CM and UM liver metastases lacked PD-L1 expression. There was no difference in the extent of immune infiltration observed between CM and UM metastases, with the exception of a higher expression of CD163 (p<0.0001) in CM liver samples. While the extent of immune infiltration was similar for CM and UM metastases, the ratio of exhausted CD8 T cells to cytotoxic T cells, to total CD8 T cells and to Th1 cells, was significantly higher in UM metastases.

CONCLUSIONS

While TMB was different between CM and UM metastases, tumor immune infiltration was similar. The greater dependency on PD-L1 as an immune checkpoint in CM and the identification of higher exhaustion ratios in UM may both serve as explanations for the difference in response to ICB. Consequently, in order to improve current treatment for metastatic UM, reversal of T cell exhaustion beyond programmed cell death 1 blockade should be considered.

Dynamic analysis of circulating tumor DNA to predict prognosis and monitor therapeutic response in metastatic relapsed cervical cancer

Limited and inefficient treatment options exist for metastatic relapsed cervical cancer (MRCC), and there are currently no reliable indicators to guide therapeutic selection. We performed deep sequencing analyses targeting 322 cancer-related genes in plasma cell-free DNA and matched white blood cells in 173 serial blood samples from 82 locally advanced CC (LACC) or MRCC patients and when possible during treatment. We identified five notable nonsynonymous mutant genes (PIK3CA, BRAF, GNA11, FBXW7 and CDH1) in the MRCC samples as the metastatic relapse significantly mutated (MSG) genes and found that MRCC patients with any detectable MSG mutations had significantly shorter progression-free survival (PFS) (P = .005) and overall survival (OS) (P = .007) times than those without detectable MSG mutations. Additionally, analyses of matched prechemotherapy and postchemotherapy plasma revealed that a reduction in the number of MSG mutations after chemotherapy was significantly associated with partial remission (PR) and stable disease (SD) (P = .007). Among the patients included in the longitudinal tracking ctDNA analysis, an increase in MSG mutations was observed earlier in response to disease progression than radiological imaging. Our results outline the mutation profiles of MRCC. We show how longitudinal monitoring with ctDNA in liquid biopsy samples provides both predictive and prognostic information during treatment.

Update on GNA Alterations in Cancer: Implications for Uveal Melanoma Treatment

Tumorigenesis is correlated with abnormal expression and activity of G protein-coupled receptors (GPCRs) and associated G proteins. Oncogenic mutations in both GPCRs and G proteins (GNAS, GNAQ or GNA11) encoding genes have been identified in a significant number of tumors. Interestingly, uveal melanoma driver mutations in GNAQ/GNA11 were identified for a decade, but their discovery did not lead to mutation-specific drug development, unlike it the case for BRAF mutations in cutaneous melanoma which saw enormous success. Moreover, new immunotherapies strategies such as immune checkpoint inhibitors have given underwhelming results. In this review, we summarize the current knowledge on cancer-associated alterations of GPCRs and G proteins and we focus on the case of uveal melanoma. Finally, we discuss the possibilities that this signaling might represent in regard to novel drug development for cancer prevention and treatment.