Human Melanoma-Cell Metabolic Profiling: Identification of Novel Biomarkers Indicating Metastasis

Cutaneous Melanoma and 486 Human Blood Metabolites: A Mendelian Randomization Study

BACKGROUND

Cutaneous melanoma (CM) has long been recognized as a lethal form of cancer. Despite persistent research endeavors, the precise underlying pathological mechanisms remain largely unclear, and the optimal treatment for this patient population remains undetermined.

OBJECTIVES

This study aims to examine the causal associations between CM and 486 metabolites.

METHODS

A two-sample Mendelian randomization (MR) analysis was conducted to ascertain the causal relationship between blood metabolites and CM. The causality analysis involved the inverse variance weighted (IVW) method, followed by the MR-Egger and weighted median (WM) methods. To increase the robustness of our findings, several sensitivity analyses, including the MR-Egger intercept, Cochran's Q test, and MR-pleiotropy residual sum and outlier (MR-PRESSO), were performed. The robustness of our results was further validated in independent outcome samples followed by a meta-analysis. Additionally, a metabolic pathway analysis was carried out.

RESULTS

The two-sample MR analysis yielded a total of 27 metabolites as potential causal metabolites. After incorporating the outcomes of the sensitivity analyses, seven causal metabolites remained. Palmitoylcarnitine (OR 0.9903 95% CI 0.9848-0.9958, p = 0.0005) emerged as the sole metabolite with a significant causality after Bonferroni correction. Furthermore, the reverse MR analysis provided no evidence of reverse causality from CM to the identified metabolites.

CONCLUSIONS

This study suggested a causal relationship between seven human blood metabolites and the development of CM, thereby offering novel insights into the underlying mechanisms involved.

NO LEVEL ASSIGNED

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1H-NMR metabolomics analysis identifies hypoxanthine as a novel metastasis-associated metabolite in breast cancer

Breast cancer is one of the leading causes of death in females, mainly because of metastasis. Oncometabolites, produced via metabolic reprogramming, can influence metastatic signaling cascades. Accordingly, and based on our previous results, we propose that metabolites from highly metastatic breast cancer cells behave differently from less-metastatic cells and may play a significant role in metastasis. For instance, we aim to identify these metabolites and their role in breast cancer metastasis. Less metastatic cells (MCF-7) were treated with metabolites secreted from highly metastatic cells (MDA-MB-231) and the gene expression of three epithelial-to-mesenchymal transition (EMT) markers including E-cadherin, N-cadherin and vimentin were examined. Some metabolites secreted from MDA-MB-231 cells significantly induced EMT activity. Specifically, hypoxanthine demonstrated a significant EMT effect and increased the migration and invasion effects of MCF-7 cells through a hypoxia-associated mechanism. Hypoxanthine exhibited pro-angiogenic effects via increasing the VEGF and PDGF gene expression and affected lipid metabolism by increasing the gene expression of PCSK-9. Notably, knockdown of purine nucleoside phosphorylase, a gene encoding for an important enzyme in the biosynthesis of hypoxanthine, and inhibition of hypoxanthine uptake caused a significant decrease in hypoxanthine-associated EMT effects. Collectively for the first time, hypoxanthine was identified as a novel metastasis-associated metabolite in breast cancer cells and represents a promising target for diagnosis and therapy.

Plasma metabolomic analysis of human hepatocellular carcinoma before and after transcatheter arterial chemoembolization

Introduction: Hepatocellular carcinoma (HCC) is the fourth most prevalent cancer in China. Transcatheter arterial chemoembolization (TACE) is a common interventional therapy for HCC. In this study, we aimed to explore specific metabolites that can accurately predict prognosis after TACE in patients with HCC. Methods: Patients with HCC and healthy volunteers (n = 20 each) were recruited to our study; plasma samples were collected from patients before and after TACE and from healthy volunteers. Plasma samples were subjected to untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry metabolomics analysis, to identify metabolites significantly associated with the prognosis of patients with HCC after TACE. Results: Orthogonal filtered partial least squares discriminant analysis confirmed significant separation of the pre-TACE, post-TACE, and healthy groups, and 34 differential metabolites were identified between the pre-TACE and post-TACE groups. KEGG analysis revealed that phenylalanine, tyrosine, and tryptophan biosynthesis pathways and the phenylalanine metabolism pathway were potentially altered in HCC genesis and during TACE. Phenylalanine and tyrosine are involved in both pathways and were increased in the pre-TACE group relative to controls, with phenylalanine further increased in the post-TACE group. Receiver operating characteristic (ROC) curve analysis indicated that PC 36:4|PC 18:2_18:2 (area under the ROC curve (AUC) = 0.798) is a potential marker for assessment of prognosis in patients with HCC after TACE. Moreover, ROC curve analysis indicated that palmitoylcarnitine (AUC = 1) is a marker with potential value for HCC diagnosis. Conclusions: Limited studies had been conducted on the detection of metabolites in the plasma of HCC patients before and after TACE. PC 36:4|PC 18:2_18:2 is a potential marker for evaluation of the therapeutic effects of TACE. This finding may be beneficial for the treatment of patients with HCC after TACE.

Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The "Omics" field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

NRF2-directed PRPS1 upregulation to promote the progression and metastasis of melanoma

Phosphoribosyl pyrophosphate synthetase 1 (PRPS1) is the first enzyme in the de novo purine nucleotide synthesis pathway and is essential for cell development. However, the effect of PRPS1 on melanoma proliferation and metastasis remains unclear. This study aimed to investigate the regulatory mechanism of PRPS1 in the malignant progression of melanoma. Here, we found PRPS1 was upregulated in melanoma and melanoma cells. In addition, our data indicated that PRPS1 could promote the proliferation and migration and invasion of melanoma both in vitro and in vivo. PRPS1 also could inhibit melanoma cell apoptosis. Furthermore, we found NRF2 is an upstream transcription factor of PRPS1 that drive malignant progression of melanoma.

Apprising Diagnostic and Prognostic Biomarkers in Cutaneous Melanoma—Persistent Updating

The incidence of melanoma, a very aggressive skin cancer, has increased over the past few decades. Although there are well-established clinical, dermoscopic and histopathological criteria, the diagnosis is often performed late, which has important implications on the patient’s clinical outcome. Unfortunately, melanoma is one of the most challenging tumors to diagnose because it is a heterogeneous neoplasm at the clinical, histopathological, and molecular level. The use of reliable biomarkers for the diagnosis and monitoring of disease progression is becoming a standard of care in modern medicine. In this review, we discuss the latest studies, which highlight findings from the genomics, epitranscriptomics, proteomics and metabolomics areas, pointing out different genes, molecules and cells as potential diagnostic and prognostic biomarkers in cutaneous melanoma.

Current Knowledge in Skin Metabolomics: Updates from Literature Review

Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

M-CSF as a therapeutic target in BRAFV600E melanoma resistant to BRAF inhibitors

BACKGROUND

Disseminated BRAF^V600E melanoma responds to BRAF inhibitors (BRAFi) but easily develops resistance with poor prognosis. Secretome plays a pivotal role during tumour progression causing profound effects on therapeutic efficacy. Secreted M-CSF is involved in both cytotoxicity suppression and tumour progression in melanoma. We aimed to analyse the M-CSF contribution in resistant metastatic melanoma to BRAF-targeted therapies.

METHODS

Conditioned media from melanoma cells were analysed by citoarray. Viability and migration/invasion assays were performed with paired melanoma cells and tumour growth in xenografted SCID mice. We evaluated the impact of M-CSF plasma levels with clinical prognosis from 35 metastatic BRAF^V600E-mutant melanoma patients.

RESULTS

BRAFi-resistant melanoma cells secretome is rich in pro-tumour cytokines. M-CSF secretion is essential to induce a Vemurafenib-resistant phenotype in melanoma cells. Further, we demonstrated that M-CSF mAb in combination with Vemurafenib and autophagy blockers synergistically induce apoptosis, impair migration and reduce tumour growth in BRAFi-resistant melanoma cells. Interestingly, lower M-CSF plasma levels are associated with better prognosis in metastatic melanoma patients.

CONCLUSIONS

Secreted M-CSF induces a BRAFi-resistant phenotype and means worse prognosis in BRAF^V600E metastatic melanoma patients. These results identify secreted M-CSF as a promising therapeutic target toward BRAFi-resistant melanomas.

Novelty Detection for Metabolic Dynamics Established On Breast Cancer Tissue Using 2D NMR TOCSY Spectra

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Automatic novelty detection of metabolites of 2D-TOCSY NMR spectra.

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Metabolic profiling of the dynamics changes in Breast cancer tissue sample.

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Accurate and fast automatic multicomponent peak assignment of 2D NMR spectrum.

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One- and multi- novelty detection of metabolites.

Most metabolic profiling approaches focus only on identifying pre-known metabolites on NMR TOCSY spectrum using configured parameters. However, there is a lack of tasks dealing with automating the detection of new metabolites that might appear during the dynamic evolution of biological cells. Novelty detection is a category of machine learning that is used to identify data that emerge during the test phase and were not considered during the training phase. We propose a novelty detection system for detecting novel metabolites in the 2D NMR TOCSY spectrum of a breast cancer-tissue sample. We build one- and multi-class recognition systems using different classifiers such as, Kernel Null Foley-Sammon Transform, Kernel Density Estimation, and Support Vector Data Description. The training models were constructed based on different sizes of training data and are used in the novelty detection procedure. Multiple evaluation measures were applied to test the performance of the novelty detection methods. Depending on the training data size, all classifiers were able to achieve 0% false positive rates and total misclassification error in addition to 100% true positive rates. The median total time for the novelty detection process varies between 1.5 and 20 seconds, depending on the classifier and the amount of training data. The results of our novel metabolic profiling method demonstrate its suitability, robustness and speed in automated metabolic research.

Study on Closely Related Citrus CMMs based on Chemometrics and Prediction of Components-Targets-Diseases Network by Ingenuity Pathway Analysis

As the representatives of closely related Chinese medicinal materials (CMMs) originated from Rutaceae family, Aurantii fructus immaturus (AFI), Aurantii fructus (AF), Citri reticulatae pericarpium viride (CRPV), and Citri reticulatae pericarpium (CRP) have better functions in regulating qi and promoting gastrointestinal motility. However, differences in the quality of closely related Citrus CMMs have not yet been revealed until now. Herein, this study focused on the systematic differentiation and in-depth understanding of closely related Citrus CMMs by a strategy integrating chemometrics and network pharmacology. Determined by ultra performance liquid chromatography, the content of nine flavonoids showed obvious fluctuations in the decoction pieces from different species (Citrus aurantium Linnaeus and Citrus reticulate Blanco) with decreasing levels in the samples of ripe fruits. Decoction pieces from the different species and ripening stages were well distinguished by orthogonal projection to latent structure-discriminate analysis (OPLS-DA) and cluster analysis. As a result, four active components including narirutin, naringenin, hesperidin, and 3,5,6,7,8,3′,4′-heptemthoxyflavone were filtered out by variable importance for the projection (VIP) value (VIP > 1.0), which were regarded as chemotaxonomic markers. Furthermore, a components-targets-diseases network was constructed via ingenuity pathway analysis (IPA), and the correlations were predicted between four chemotaxonomic markers, 223 targets, and three diseases including colitis, breast cancer, and colorectal cancer. The obtained results will be of great significance for identifying closely related Citrus CMMs and conduce to improving the resource utilization of CMMs.

Liquid Biopsy and Dielectrophoretic Analysis—Complementary Methods in Skin Cancer Monitoring

The incidence and prevalence of skin cancers is currently increasing worldwide, with early detection, adequate treatment, and prevention of recurrences being topics of great interest for researchers nowadays. Although tumor biopsy remains the gold standard of diagnosis, this technique cannot be performed in a significant proportion of cases, so that the use of alternative methods with high sensitivity and specificity is becoming increasingly desirable. In this context, liquid biopsy appears to be a feasible solution for the study of cellular and molecular markers relevant to different types of skin cancers. Circulating tumor cells are just one of the components of interest obtained from performing liquid biopsy, and their study by complementary methods, such as dielectrophoresis, could bring additional benefits in terms of characterizing skin tumors and subsequently applying personalized therapy. One purpose of this review is to demonstrate the utility of liquid biopsy primarily in monitoring the most common types of skin tumors: basal cell carcinoma, squamous cell carcinoma, and malign melanoma. In addition, the originality of the article is based on the detailed presentation of the dielectrophoretic analysis method of the most important elements obtained from liquid biopsy, with direct impact on the clinical and therapeutic approach of skin tumors.

Upregulated phospholipase D2 expression and activity is related to the metastatic properties of melanoma

The incidence rates of melanoma have increased steadily in recent decades and nearly 25% of the patients diagnosed with early-stage melanoma will eventually develop metastasis, for which there is currently no fully effective treatment. The link between phospholipases and tumors has been studied extensively, particularly in breast and colon cancers. With the aim of finding new biomarkers and therapeutic options for melanoma, the expression of different phospholipases was assessed in 17 distinct cell lines in the present study, demonstrating that phospholipase D2 (PLD2) is upregulated in metastatic melanoma as compared to normal skin melanocytes. These results were corroborated by immunofluorescence and lipase activity assays. Upregulation of PLD2 expression and increased lipase activity were observed in metastatic melanoma relative to normal skin melanocytes. So far, the implication of PLD2 activity in melanoma malignancies has remained elusive. To the best of our knowledge, the present study was the first to demonstrate that the overexpression of PLD2 enhances lipase activity, and its effect to increase the proliferation, migration and invasion capacity of melanoma cells was assessed with XTT and Transwell assays. In addition, silencing of PLD2 in melanoma cells reduced the metastatic potential of these cells. The present study provided evidence that PLD2 is involved in melanoma malignancy and in particular, in its metastatic potential, and established a basis for future studies evaluating PLD2 blockade as a therapeutic strategy to manage this condition.

Non-targeted LC-MS and CE-MS for biomarker discovery in bioreactors: Influence of separation, mass spectrometry and data processing tools

Liquid separation coupled to mass spectrometry is often used for non-targeted analyses in various fields, such as metabolomics. However, the combination of non-standardized methods, various mass spectrometers (MS) and processing tools for data evaluation affect biomarker discovery potentially. Here, we present a comprehensive study of these factors based on non-targeted liquid chromatography coupled to time-of-flight (TOF) and Orbitrap MS and capillary zone electrophoresis to Orbitrap analyses of the same bioreactor samples, describing the correlation of its gas yield with changing feature signal intensity. The three datasets were processed with MZmine 2 and XCMS online and subsequential Partial Least Square Regression (PLSR) with Variable Importance in Projection (VIP) ranking for feature prioritization. The six feature tables were compared to evaluate their overlap of shared features and the influence of the processing software and MS instrument on the VIP values and fold changes. The overlaps, defined as a fraction of one feature table found in the comparative table, were from 27% to 57% for the comparison of MZmine and XCMS and from 15% to 50% between Orbitrap and TOF data sets, respectively. Considering the most relevant features only (VIP >1.5), the overlaps were increased significantly in all cases from 26% to 95%. For the same data set, both VIP values and fold changes were well correlated, however, varied significantly between TOF and Orbitrap. CE-MS showed higher total feature numbers compared to LC-MS, most likely due to its more appropriate selectivity, different sample preparation, and/or the sensitive nano-ESI interface. Since only less than 10% of MS/MS data overlapped, CE-MS provided complementary information to LC-MS. Overall, our systematic study proves the benefits of using different separation techniques and processing tools but also indicates a significant influence of mass spectrometry on comprehensive biomarker discovery.

Inhibitory Effect of Dihydroartemisinin on the Proliferation and Migration of Melanoma Cells and Experimental Lung Metastasis From Melanoma in Mice

Melanoma is aggressive and can metastasize in the early stage of tumor. It has been proved that dihydroartemisinin (DHA) positively affects the treatment of tumors and has no apparent toxic and side effects. Our previous research has shown that DHA can suppress the formation of melanoma. However, it remains poorly established how DHA impacts the invasion and metastasis of melanoma. In this study, B16F10 and A375 cell lines and metastatic tumor models will be used to investigate the effects of DHA. The present results demonstrated that DHA inhibited the proliferative capacity in A375 and B16F10 cells. As expected, the migration capacity of A375 and B16F10 cells was also reduced after DHA administration. DHA alleviated the severity and histopathological changes of melanoma in mice. DHA induced expansion of CD8⁺CTL in the tumor microenvironment. By contrast, DHA inhibited Treg cells infiltration into the tumor microenvironment. DHA enhanced apoptosis of melanoma by regulating FasL expression and Granzyme B secretion in CD8⁺CTLs. Moreover, DHA impacts STAT3-induced EMT and MMP_S in tumor tissue. Furthermore, Metabolomics analysis indicated that PGD2 and EPA significantly increased after DHA administration. In conclusion, DHA inhibited the proliferation, migration and metastasis of melanoma in vitro and in vivo. These results have important implications for the potential use of DHA in the treatment of melanoma in humans.

Role of Metastasis Suppressor KAI1/CD82 in Different Cancers

Metastasis is one of the characteristics of malignant tumors and the main cause of death worldwide. The process of metastasis is mainly affected by tumor metastasis genes, tumor metastasis suppressor genes, tumor microenvironment, extracellular matrix degradation, and other factors. Thus, it is essential to elucidate the mechanism of metastasis and find the therapeutic targets in order to prevent the development of malignant tumors. KAI1/CD82, a member of tetraspanin superfamily of glycoproteins, has been reported as a tumor metastasis suppressor gene in various types of cancers without affecting the tumor formation. Many studies have demonstrated that low expression of KAI1/CD82 might lead to poor prognosis due to its interactions with other tetraspanins and integrins, resulting in the regulation of cell motility and invasion, cell-cell adhesion, and apoptosis. Considering its pathological and physiological significance, KAI1/CD82 could be a potential strategy for clinical predicting and preventing tumor progression and metastasis. The present review aims to discuss the role of KAI1/CD82 in metastasis for different cancers and examine its prospects as a metastasis biomarker and a therapeutic target.

From Proteomic Mapping to Invasion-Metastasis-Cascade Systemic Biomarkering and Targeted Drugging of Mutant BRAF-Dependent Human Cutaneous Melanomagenesis

Simple Summary

Despite the recent advances in human malignancy therapy, metastasis and chemoresistance remain the principal causes of cancer-derived deaths. Given the fatal forms of cutaneous metastatic melanoma, we herein employed primary (WM115) and metastatic (WM266-4) melanoma cells, both obtained from the same patient, to identify novel biomarkers and therapeutic agents. Through state-of-the-art technologies including deep proteome landscaping, immunofluorescence phenotyping, and drug toxicity screening, we were able to describe new molecular programs, oncogenic drivers, and drug regimens, controlling the invasion-metastasis cascade during BRAF^V600D-dependent melanomagenesis. It proved that proteomic navigation could foster the development of systemic biomarkering and targeted drugging for successful treatment of advanced disease.

Abstract

Melanoma is classified among the most notoriously aggressive human cancers. Despite the recent progress, due to its propensity for metastasis and resistance to therapy, novel biomarkers and oncogenic molecular drivers need to be promptly identified for metastatic melanoma. Hence, by employing nano liquid chromatography-tandem mass spectrometry deep proteomics technology, advanced bioinformatics algorithms, immunofluorescence, western blotting, wound healing protocols, molecular modeling programs, and MTT assays, we comparatively examined the respective proteomic contents of WM115 primary (n = 3955 proteins) and WM266-4 metastatic (n = 6681 proteins) melanoma cells. It proved that WM115 and WM266-4 cells have engaged hybrid epithelial-to-mesenchymal transition/mesenchymal-to-epithelial transition states, with TGF-β controlling their motility in vitro. They are characterized by different signatures of SOX-dependent neural crest-like stemness and distinct architectures of the cytoskeleton network. Multiple signaling pathways have already been activated from the primary melanoma stage, whereas HIF1α, the major hypoxia-inducible factor, can be exclusively observed in metastatic melanoma cells. Invasion-metastasis cascade-specific sub-routines of activated Caspase-3-triggered apoptosis and LC3B-II-dependent constitutive autophagy were also unveiled. Importantly, WM115 and WM266-4 cells exhibited diverse drug response profiles, with epirubicin holding considerable promise as a beneficial drug for metastatic melanoma clinical management. It is the proteome navigation that enables systemic biomarkering and targeted drugging to open new therapeutic windows for advanced disease.

Targeted Metabolomics Identifies Plasma Biomarkers in Mice with Metabolically Heterogeneous Melanoma Xenografts

Melanomas are genetically and metabolically heterogeneous, which influences therapeutic efficacy and contributes to the development of treatment resistance in patients with metastatic disease. Metabolite phenotyping helps to better understand complex metabolic diseases, such as melanoma, and facilitates the development of novel therapies. Our aim was to characterize the tumor and plasma metabolomes of mice bearing genetically different melanoma xenografts. We engrafted the human melanoma cell lines A375 (BRAF mutant), WM47 (BRAF mutant), WM3000 (NRAS mutant), and WM3311 (BRAF, NRAS, NF1 triple-wildtype) and performed a broad-spectrum targeted metabolomics analysis of tumor and plasma samples obtained from melanoma-bearing mice as well as plasma samples from healthy control mice. Differences in ceramide and phosphatidylcholine species were observed between melanoma subtypes irrespective of the genetic driver mutation. Furthermore, beta-alanine metabolism differed between melanoma subtypes and was significantly enriched in plasma from melanoma-bearing mice compared to healthy mice. Moreover, we identified beta-alanine, p-cresol sulfate, sarcosine, tiglylcarnitine, two dihexosylceramides, and one phosphatidylcholine as potential melanoma biomarkers in plasma. The present data reflect the metabolic heterogeneity of melanomas but also suggest a diagnostic biomarker signature for melanoma screening.

Genetic Target Modulation Employing CRISPR/Cas9 Identifies Glyoxalase 1 as a Novel Molecular Determinant of Invasion and Metastasis in A375 Human Malignant Melanoma Cells In Vitro and In Vivo

Metabolic reprogramming is a molecular hallmark of cancer. Recently, we have reported the overexpression of glyoxalase 1 (encoded by GLO1), a glutathione-dependent enzyme involved in detoxification of the reactive glycolytic byproduct methylglyoxal, in human malignant melanoma cell culture models and clinical samples. However, the specific role of GLO1 in melanomagenesis remains largely unexplored. Here, using genetic target modulation, we report the identification of GLO1 as a novel molecular determinant of invasion and metastasis in malignant melanoma. First, A375 human malignant melanoma cells with GLO1 deletion (A375-GLO1_KO) were engineered using CRISPR/Cas9, and genetic rescue clones were generated by stable transfection of KO clones employing a CMV-driven GLO1 construct (A375-GLO1_R). After confirming GLO1 target modulation at the mRNA and protein levels (RT-qPCR, immunodetection, enzymatic activity), phenotypic characterization indicated that deletion of GLO1 does not impact proliferative capacity while causing significant sensitization to methylglyoxal-, chemotherapy-, and starvation-induced cytotoxic stress. Employing differential gene expression array analysis (A375-GLO1_KO versus A375-GLO1_WT), pronounced modulation of epithelial--mesenchymal transition (EMT)-related genes [upregulated: CDH1, OCLN, IL1RN, PDGFRB, SNAI3; (downregulated): BMP1, CDH2, CTNNB1, FN1, FTH1, FZD7, MELTF, MMP2, MMP9, MYC, PTGS2, SNAI2, TFRC, TWIST1, VIM, WNT5A, ZEB1, and ZEB2 (up to tenfold; p < 0.05)] was observed-all of which are consistent with EMT suppression as a result of GLO1 deletion. Importantly, these expression changes were largely reversed upon genetic rescue employing A375-GLO1_R cells. Differential expression of MMP9 as a function of GLO1 status was further substantiated by enzymatic activity and ELISA analysis; phenotypic assessment revealed the pronounced attenuation of morphological potential, transwell migration, and matrigel 3D-invasion capacity displayed by A375-GLO1_KO cells, reversed again in genetic rescue clones. Strikingly, in a SCID mouse metastasis model, lung tumor burden imposed by A375-GLO1_KO cells was strongly attenuated as compared to A375-GLO1_WT cells. Taken together, these prototype data provide evidence in support of a novel function of GLO1 in melanoma cell invasiveness and metastasis, and ongoing investigations explore the function and therapeutic potential of GLO1 as a novel melanoma target.