Biomarker For Melanoma Research Articles

Machine Learning Analysis of Immune Cells for Diagnosis and Prognosis of Cutaneous Melanoma

Tumor infiltration, known to associate with various cancer initiations and progressions, is a promising therapeutic target for aggressive cutaneous melanoma. Then, the relative infiltration of 24 kinds of immune cells in melanoma was assessed by a single sample gene set enrichment analysis (ssGSEA) program from a public database. The multiple machine learning algorithms were applied to evaluate the efficiency of immune cells in diagnosing and predicting the prognosis of melanoma. In comparison with the expression of immune cell in tumor and normal control, we built the immune diagnostic models in training dataset, which can accurately classify melanoma patients from normal (LR AUC = 0.965, RF AUC = 0.99, SVM AUC = 0.963, LASSO AUC = 0.964, and NNET AUC = 0.989). These diagnostic models were also validated in three outside datasets and suggested over 90% AUC to distinguish melanomas from normal patients. Moreover, we also developed a robust immune cell biomarker that could estimate the prognosis of melanoma. This biomarker was also further validated in internal and external datasets. Following that, we created a nomogram with a composition of risk score and clinical parameters, which had high accuracies in predicting survival over three and five years. The nomogram's decision curve revealed a bigger net benefit than the tumor stage. Furthermore, a risk score system was used to categorize melanoma patients into high- and low-risk subgroups. The high-risk group has a significantly lower life expectancy than the low-risk subgroup. Finally, we observed that complement, epithelial-mesenchymal transition, and inflammatory response were significantly activated in the high-risk group. Therefore, the findings provide new insights for understanding the tumor infiltration relevant to clinical applications as a diagnostic or prognostic biomarker for melanoma.

Ferroptosis-related genes are candidate diagnostic and prognostic biomarkers for skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is a disease with the highest mortality rate among skin cancers. As a new type of programmed cell death, ferroptosis has been confirmed to be related to the occurrence and development of a variety of cancers. At present, the expression and prognostic value of ferroptosis-related genes (FRGs) in SKCM are still unclear. In this study, we selected sevenFRGs that were differentially expressed in SKCM and related to the patient's prognosis through the databases. Further studies have shown that these genes are closely related to immune cell infiltration and immune checkpoints. All in all, these sevenFRGs may be potential targets for clinical diagnosis, prognosis and treatment of SKCM patients.

Prognostic biomarkers of cutaneous melanoma.

Melanomas account for only approximately 4% of diagnosed skin cancers in the United States but are responsible for the majority of deaths caused by skin cancer. Both genetic factors and ultraviolet (UV) radiation exposure play a role in the development of melanoma. Although melanomas have a strong propensity to metastasize when diagnosed late, melanomas that are diagnosed and treated early pose a low mortality risk. In particular, the identification of patients with increased metastatic risk, who may benefit from early adjuvant therapies, is crucial, especially given the advent of new melanoma treatments. However, the accuracy of classic clinical and histological variables, including the Breslow thickness, presence of ulceration, and lymph node status, might not be sufficient to identify such individuals. Thus, there is a need for the development of additional prognostic melanoma biomarkers that can improve early attempts to stratify melanoma patients and reliably identify high-risk subgroups with the aim of providing effective personalized therapies. In our current work, we discuss and assess emerging primary melanoma tumor biomarkers and prognostic circulating biomarkers. Several promising biomarkers show prognostic value (eg, exosomal MIA (ie, melanoma inhibitory activity), serum S100B, AMLo signatures, and mRNA signatures); however, the scarcity of reliable data precludes the use of these biomarkers in current clinical applications. Further research is needed on several promising biomarkers for melanoma. Large-scale studies are warranted to facilitate the clinical translation of prognostic biomarker applications for melanoma in personalized medicine.

CD96 as a Potential Diagnostic Biomarker and New Target for Skin Cutaneous Melanoma.

Skin cutaneous melanoma has high morbidity and mortality. Identification of reliable and quantitative melanoma biomarkers could facilitate an early diagnosis and improve survival and morbidity rates. CD96 has a significant role in adjusting immune function. Although the abnormal expression of CD96 has been reported to participate in carcinogenesis in many human types of cancer, the bioinformatics role of the CD96 in melanoma is unknown. Expression degrees and their underlying functions were first studied by this study. According to TCGA, GTEx, and gene expression profile interaction analysis dataset in this paper, compared with normal skin tissues, CD96 was expressed at higher levels in human cutaneous melanoma skin tissues. Meanwhile, we detected the relative CD96 expression levels by immunohistochemistry. Gene functional enrichment analyses were applied through cBioPortal database analysis. CD96 was clearly upregulated in skin cutaneous melanoma patients and carried out its effects through regulating several signaling pathways, containing the JAK-STAT, PI3K-Akt, and MAPK. Taken together, the analysis results indicated that CD96 could be used as a new clinical bioindicator as well as an underlying medicinal target for cutaneous melanoma.

Identification of Potential Core Genes Between Primary and Metastatic Malignant Melanoma and Analysis of Their Immune Correlation.

PurposeTo identify the potential differential genes between primary and metastatic melanoma, screen out immune-related genes in core genes and analyze their immune correlation, thus searching for the early diagnostic biomarkers of cutaneous malignant melanoma (CMM) and the targets of curbing metastasis.Materials and MethodsWe analyzed two microarray datasets (GSE8401 and GSE46517) derived from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between primary and metastatic melanoma were screened out using the GEO2R tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to identify the functions and pathways of DEGs. We analyzed protein–protein interaction of these DEGs based on the Search Tool for the Retrieval of Interacting Genes database and showed by Cytoscape software. In addition, the online Gene Expression Profiling Interactive Analysis tool (GEPIA) was used to analyze the prognostic value of hub genes expressed in metastatic melanoma patients. Immune-related genes in hub genes were screened and further analyzed.ResultsA total of 178 upregulated DEGs and 4 downregulated DEGs were identified. 23 terms and 4 pathways were confirmed related to metastatic melanoma. Ten hub genes with a high degree of connectivity were found. Overexpression of three hub genes (DSG1, FLG, PKP1) (P<0.01) was associated with metastasis and poor prognosis of CMM. Among them, the patients with overexpression of PKP1 suffered shorter survival. In addition, 2 immune-related genes (EGFR and CDH1) in hub genes were screened out and both of them were related to anti-tumor immunity, although their expression level did not affect the overall survival of CMM patients significantly.ConclusionOur study suggests that DSG1, FLG and PKP1 were overexpressed in metastatic melanoma compared with primary melanoma, and overexpression of these three genes was an unfavorable prognostic factor ifor CMM patients, which may indicate that they are associated with promoting metastasis of malignant melanoma. EGFR and CDH1 play a crucial role in anti-tumor immunity for CMM. Further research is needed to explore the value of these genes in the inhibition of metastasis and treatment of CMM.

A simple electrochemical immunosensor based on a chitosan/reduced graphene oxide nanocomposite for sensitive detection of biomarkers of malignant melanoma.

The sensitive and specific detection of tumor biomarkers is crucial for early diagnosis and treatment of malignant melanoma. Immunoassay with a simple sensing interface and high sensitivity is highly desirable. In this work, a simple electrochemical immunosensor based on a chitosan/reduced graphene oxide (CS–rGO) nanocomposite was developed for sensitive determination of an S-100B protein, a tumor marker of malignant melanoma. CS–rGO nanocomposite were prepared by chemical reduction of graphene oxide in the presence of chitosan and modified on glassy carbon electrode (GCE) to provide a biofriendly, conductive, and easily chemically modified matrix for further immobilization of antibodies. Anti-S-100B antibodies were grafted onto the chitosan molecules to fabricate the immunorecognition interface by a simple glutaraldehyde cross-linking method. Electrochemical determination of S-100B was achieved by measuring the decreased current signal of solution phase electrochemical probes, which originated from the increased steric hindrance and insulation caused by the formation of antigen–antibody complexes at the electrode interface. Due to the good conductivity, high surface area, excellent biocompatibility, and good film-forming ability of CS–rGO, the constructed immunosensor exhibited good stability, high selectivity and sensitivity, a wide dynamic range from 10 fg mL−1 to 1 ng mL−1 and a low limit of detection of 1.9 pg mL−1 (S/N = 3). Moreover, the sensor was also applicable for the sensitive detection of S-100B protein in real human serum samples.

Role of Circular RNAs in the Pathogenesis of Malignant Melanoma.

Malignant melanoma is one of the most aggressive types of skin cancer. Thus, efficient diagnosis and treatment methods are crucial for advanced melanoma. Circular RNAs (circRNAs) have been regarded as a 'splicing noise' in the past decades. However, several circRNAs have been recently reported to be differentially expressed in melanoma, and the cell or tissue-specific expression makes these suitable candidate diagnostic or therapeutic biomarkers. In addition, emerging studies have confirmed that circular RNAs play pivotal roles in the proliferation, invasion, metastasis, and migration of malignant melanoma. However, specific pathogenic mechanisms between melanoma and circRNAs remain unclear. In the present study, it was summarized that circRNAs are associated with the pathogenesis of melanoma, including hsa_circ_0083444, hsa_circ_0005320, hsa_circ_0067531, hsa_circ_0084043, hsa_circ_0000082, hsa_circ_0016418, hsa_circ_0085533 and hsa_circ_0025039, hsa_circ_0001946, hsa_circ_0002770, hsa_circ_0079593, hsa_circ_0027247, hsa_circ_0017247, hsa_circ_0020710. These can provide potential diagnosis, treatment, and prognostication biomarkers for advanced melanoma in clinical applications.

Systemic adjuvant therapy for high-risk cutaneous melanoma.

Cutaneous melanoma continues to increase in incidence and poses a significant mortality risk. Surgical excision of melanoma in its early stages is often curative. However, patients with resected stages IIB-IV are considered at high risk for relapse and death from melanoma where systemic adjuvant therapy is indicated. The long-studied high-dose interferon-α was shown to improve relapse-free survival (RFS) and overall survival (OS) but is no longer in use. Adjuvant therapy with ipilimumab at 10 mg/kg (ipi10) demonstrated significant RFS and OS improvements but at a high cost in terms of toxicity, while adjuvant ipilimumab 3 mg/kg was shown to be equally effective and less toxic. More recently, the adjuvant therapy for resected stages III-IV melanoma in clinical practice has changed in favor of nivolumab, pembrolizumab, and BRAF-MEK inhibitors dabrafenib plus trametinib (for BRAF mutant melanoma) based on significant improvements in RFS as compared to ipi10 (nivolumab and pembrolizumab) and placebo (dabrafenib plus trametinib). For resected stages IIB-IIC melanoma, pembrolizumab achieved regulatory approval in the United States based on significant RFS benefits. In this article, we review completed and ongoing phase III adjuvant therapy trials. We also briefly discuss neoadjuvant therapy for locoregionally advanced melanoma. Finally, we explore recent studies on predictive and prognostic melanoma biomarkers in the adjuvant setting.

Epstein-Barr Virus-induced Gene 3 as a Novel Biomarker in Metastatic Melanoma With Infiltrating CD8+ T Cells: A Study Based on The Cancer Genome Atlas (TCGA).

Epstein-Barr virus-induced gene 3 (EBI3) is an immunomodulatory protein-coding gene. So far, the prognostic role of EBI3 in human metastatic melanoma has been unclear. This study aimed to evaluate the EBI3 expression as a potential biomarker using the public database with tumor-infiltrating lymphocytes (TILs) data. Survival analyses were performed in the database of The Cancer Genome Atlas (TCGA) and GSE65904, GSE19234, GSE22153, and GSE22154. The mRNA levels, the distribution pattern of TILs, and the estimated fractions of TILs from the TCGA database were integrated. Higher EBI3 expression in tumors was significantly associated with longer overall survival in TCGA and the other independent cohorts. Interestingly, the patients with high EBI3 expression had a brisk pattern of TILs and increased CD8+ T cells over regulatory T cells with less pigmentation-related gene expressions. EBI3 could serve as a novel biomarker in metastatic melanoma with a favorable TILs profile.

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

Simple SummaryMalignant melanoma is the most lethal form of skin cancer. While new therapeutic approaches have improved survival in patients with metastatic melanoma, responses are rarely sustained due to the high degree of heterogeneity at the inter- and intra-metastatic levels. The development of reliable biomarkers to monitor therapeutic response and disease progression is critical. While attention has been focused on dissecting the molecular basis responsible for treatment resistance, it is clear that epigenetic changes warrant further in-depth investigation. Indeed, many aberrantly methylated genes play a role in cell cycle control, apoptosis, and cell invasion, as well as in melanoma progression. Longitudinal monitoring of DNA methylation via liquid biopsy can provide real-time information on the behavior and stage of melanoma.Malignant melanoma is the most serious, life-threatening form of all dermatologic diseases, with a poor prognosis in the presence of metastases and advanced disease. Despite recent advances in targeted therapy and immunotherapy, there is still a critical need for a better understanding of the fundamental mechanisms behind melanoma progression and resistance onset. Recent advances in genome-wide methylation methods have revealed that aberrant changes in the pattern of DNA methylation play an important role in many aspects of cancer progression, including cell proliferation and migration, evasion of cell death, invasion, and metastasization. The purpose of the current review was to gather evidence regarding the usefulness of DNA methylation tracking in liquid biopsy as a potential biomarker in melanoma. We investigated the key genes and signal transduction pathways that have been found to be altered epigenetically in melanoma. We then highlighted the circulating tumor components present in blood, including circulating melanoma cells (CMC), circulating tumor DNA (ctDNA), and tumor-derived extracellular vesicles (EVs), as a valuable source for identifying relevant aberrations in DNA methylation. Finally, we focused on DNA methylation signatures as a marker for tracking response to therapy and resistance, thus facilitating personalized medicine and decision-making in the treatment of melanoma patients.

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out.

Simple SummaryMalignant melanoma is one of the most aggressive cancer types among the solid tumors; therefore, more clinically applicable protein biomarkers predicting survival and therapy response have mandatory importance, impacting patient treatment. The aim of the study was to discover new proteins in biobanked FFPE samples that relate to progression-free survival and response to targeted- and immuno-therapies in patients with melanoma. Protein expressions were detected and quantified by high-resolution mass spectrometry and were integrated with the clinical data and in-depth histopathology characterization. Sample groups with distinct protein expression profiles were connected to longer and shorter survival as well as other clinicopathologic features. In addition, key regulating proteins were assigned, as predictive of progression-free survival in immuno- and/or targeted therapy. Some of the proteins exhibited functionally important correlations to progression and therapy response, which ultimately contributes to a better understanding of melanoma pathology.The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort’s heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient’s response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.

CEACAM1 - A Promising Biomarker for Melanoma

Abstract Malignant melanoma is the third most common skin cancer, but it also remains the most aggressive. Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is a promising diagnostic and prognostic biomarker for melanoma, because its expression is important for tumour development. This review aims at highlighting the most recent discoveries regarding CEACAM1 and its correlation to the diagnosis and prognosis of malignant melanoma. National Library of Medicine (NIH) PubMed was used for selecting articles published between 2004-2021, based on their relevance and novelty. With its multiple and somewhat contradictory effects, CEACAM1 seems to influence melanoma invasion, migration, immunomodulation and tumour suppression, serving as a useful diagnostic biomarker and target for therapy. While the incidence of malignant melanoma has been increasing over the last decades without signs of prognosis improvement, it is crucial that new biomarkers for diagnosis and detection of metastatic progression are discovered, and CEACAM1 might be a viable option.

Identification of an m6A Regulators-Mediated Prognosis Signature For Survival Prediction and Its Relevance to Immune Infiltration in Melanoma.

Despite robust evidence for the role of m6A in cancer development and progression, its association with immune infiltration and survival outcomes in melanoma remains obscure. Here, we aimed to develop an m6A-related risk signature to improve prognostic and immunotherapy responder prediction performance in the context of melanoma. We comprehensively analyzed the m6A cluster and immune infiltration phenotypes of public datasets. The TCGA (n = 457) and eleven independent melanoma cohorts (n = 758) were used as the training and validation datasets, respectively. We identified two m6A clusters (m6A-clusterA and m6A-clusterB) based on the expression pattern of m6A regulators via unsupervised consensus clustering. IGF2BP1 (7.49%), KIAA1429 (7.06%), and YTHDC1 (4.28%) were the three most frequently mutated genes. There was a correlation between driver genes mutation statuses and the expression of m6A regulators. A significant difference in tumor-associated immune infiltration between two m6A clusters was detected. Compared with m6A-clusterA, the m6A-clusterB was characterized by a lower immune score and immune cell infiltration but higher mRNA expression-based stemness index (mRNAsi). An m6A-related risk signature consisting of 12 genes was determined via Cox regression analysis and divided the patients into low- and high-risk groups (IL6ST, MBNL1, NXT2, EIF2A, CSGALNACT1, C11orf58, CD14, SPI1, NCCRP1, BOK, CD74, PAEP). A nomogram was developed for the prediction of the survival rate. Compared with the high-risk group, the low-risk group was characterized by high expression of immune checkpoints and immunophenoscore (IPS), activation of immune-related pathways, and more enriched in immune cell infiltrations. The low-risk group had a favorable prognosis and contained the potential beneficiaries of the immune checkpoint blockade therapy and verified by the IMvigor210 cohort (n = 298). The m6A-related signature we have determined in melanoma highlights the relationships between m6A regulators and immune cell infiltration. The established risk signature was identified as a promising clinical biomarker of melanoma.

P2X7 promotes metastatic spreading and triggers release of miRNA-containing exosomes and microvesicles from melanoma cells

Tumor growth and metastatic spreading are heavily affected by the P2X7 receptor as well as microvesicles and exosomes release into the tumor microenvironment. P2X7 receptor stimulation is known to trigger vesicular release from immune and central nervous system cells. However, P2X7 role in microvesicles and exosomes delivery from tumor cells was never analyzed in depth. Here we show that P2X7 is overexpressed in patients affected by metastatic malignant melanoma and that its expression closely correlates with reduced overall survival. Antagonism of melanoma cell-expressed P2X7 receptor inhibited in vitro anchorage-independent growth and migration and in vivo dissemination and lung metastasis formation. P2X7 stimulation triggered the release of miRNA-containing microvesicles and exosomes from melanoma cells, profoundly altering the nature of their miRNA content, as well as their dimensions and quantity. Among the more than 200 miRNAs that we found up-or-down-modulated for each vesicular fraction tested, we identified three miRNAs, miR-495-3p, miR-376c-3p, and miR-6730-3p, that were enriched in both the exosome and microvesicle fraction in a P2X7-dependent fashion. Interestingly, upon transfection, these miRNAs promoted melanoma cell growth or migration, and their vesicular release was minimized by P2X7 antagonism. Our data unveil an exosome/microvesicle and miRNA-dependent mechanism for the pro-metastatic activity of the P2X7 receptor and highlight this receptor as a suitable prognostic biomarker and therapeutic target in malignant melanoma.

Alpha-1-Acid Glycoprotein as a Diagnostic Biomarker for Malignant Melanoma

Alpha-1-Acid Glycoprotein as a Diagnostic Biomarker for Malignant Melanoma

Identification of a novel tumour microenvironment-based prognostic biomarker in skin cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is one of the most destructive skin malignancies and has attracted worldwide attention. However, there is a lack of prognostic biomarkers, especially tumour microenvironment (TME)‐based prognostic biomarkers. Therefore, there is an urgent need to investigate the TME in SKCM, as well as to identify efficient biomarkers for the diagnosis and treatment of SKCM patients. A comprehensive analysis was performed using SKCM samples from The Cancer Genome Atlas and normal samples from Genotype‐Tissue Expression. TME scores were calculated using the ESTIMATE algorithm, and differential TME scores and differentially expressed prognostic genes were successively identified. We further identified more reliable prognostic genes via least absolute shrinkage and selection operator regression analysis and constructed a prognostic prediction model to predict overall survival. Receiver operating characteristic analysis was used to evaluate the diagnostic efficacy, and Cox regression analysis was applied to explore the relationship with clinicopathological characteristics. Finally, we identified a novel prognostic biomarker and conducted a functional enrichment analysis. After considering ESTIMATEScore and tumour purity as differential TME scores, we identified 34 differentially expressed prognostic genes. Using least absolute shrinkage and selection operator regression, we identified seven potential prognostic biomarkers (SLC13A5, RBM24, IGHV3OR16‐15, PRSS35, SLC7A10, IGHV1‐69D and IGHV2‐26). Combined with receiver operating characteristic and regression analyses, we determined PRSS35 as a novel TME‐based prognostic biomarker in SKCM, and functional analysis enriched immune‐related cells, functions and signalling pathways. Our study indicated that PRSS35 could act as a potential prognostic biomarker in SKCM by investigating the TME, so as to provide new ideas and insights for the clinical diagnosis and treatment of SKCM.

The prognostic value of the preoperative lung immune prognostic index in patients with urothelial bladder cancer undergoing radical cystectomy.

The lung immune prognostic index (LIPI) predicts the prognosis of patients with advanced non-small-cell lung cancer and is a prognostic biomarker for renal cell carcinoma and melanoma; however, no study has evaluated its potential as a preoperative biomarker for patients with bladder cancer (BC). We investigated the LIPI as a preoperative prognostic biomarker in patients undergoing radical cystectomy. We retrospectively analyzed the clinical records of 105 patients with BC who underwent radical cystectomy from January 2013 to June 2019. The LIPI was evaluated based on the preoperatively derived neutrophil-lymphocyte ratio and the lactate dehydrogenase levels. Inverse probability of treatment weighting (IPTW)-adjusted Kaplan-Meier curves and decision curve analysis (DCA) were performed to assess the disease-free survival (DFS), cancer-specific survival (CSS), and overall survival (OS) rates. The patients were classified into the good, intermediate, and poor LIPI groups [71 (67.6%), 28 (26.7%), and 6 (5.7%) patients, respectively]. IPTW-adjusted Kaplan-Meier curve analyses showed that patients with intermediate to poor LIPI had worse DFS, CSS, and OS rates than those with good LIPI. The LIPI combined with pT3/4 and lymph node metastasis could better assess the prognosis of DFS at 24months postoperatively by DCA. The preoperative LIPI can predict the prognosis of patients with BC undergoing radical cystectomy and has a better predictive ability when combined with pT3/4 and lymph node metastasis.

Bladder cancer-associated transcript 1 promotes melanoma cell proliferation and invasion via the miR-374b-5p/U2-associated factor homology motif kinase 1 axis.

Melanoma is a malignancy derived from melanocytes and is associated with high mortality rates worldwide. Long noncoding RNAs (lncRNAs) have been confirmed to be pivotal regulators in multiple types of cancer. Many lncRNAs are aberrantly expressed in tumors and perform vital functions in cancer progression. Nevertheless, the biological role of lncRNA bladder cancer-associated transcript 1 (BLACAT1) in melanoma progression remains unexplored. In this study, the collected data showed that BLACAT1 was highly expressed in melanoma. Mechanistically, miR-374b-5p bound to BLACAT1, and U2-associated factor homology motif kinase 1 (UHMK1) was a downstream target of miR-374b-5p. BLACAT1 upregulated UHMK1 expression by acting as a competing endogenous RNA for miR-374-5b. BLACAT1 deficiency resulted in the upregulation of miR-374b-5p expression and the downregulation of UHMK1 expression in melanoma cells. Moreover, BLACAT1 activated PI3K and AKT signaling by upregulating UHMK1 expression, as shown by western blotting analyses. Functionally, UHMK1 overexpression or miR-374b-5p knockdown reversed the suppressive effect of BLACAT1 depletion on melanoma cell proliferation and invasion. In conclusion, BLACAT1 promotes melanoma cell proliferation and invasion by upregulating UHMK1 expression via miR-374b-5p to activate the PI3K/AKT pathway. These results might provide promising insight into the investigation of prognostic biomarkers of melanoma.

1104 Plasma Circulating Cell-Free Messenger RNA as a Potential Biomarker of Melanoma

Abstract Introduction Blood-borne cell-free nucleic acids are increasingly emerging as significant non-invasive adjuncts to current methods of disease status evaluation in cancer patients. In this study, we sought to examine whether significant differences exist in the plasma transcriptomic profile of advanced melanoma patients with a high disease burden compared to patients with therapeutic response. Method Plasma circulating cell-free messenger ribonucleic acid (ccfmRNA) was extracted from twenty patients with stage IV melanoma receiving immunotherapy. Pathway focused gene expression analysis was performed. Patients were assessed with paired blood sample collection and CT scan assessments at baseline and at 3 months follow up. Response Evaluation Criteria in Solid Tumours (RECIST 1.1) was used for tumour burden estimation. Results In stage IV melanoma patients, CCL5, GZMB and MYD88 genes were significantly over-expressed (p &amp;lt; 0.05 versus healthy controls). In patients with high disease burden or progressive disease, CCL18, CCR1, CCR4, CD274, CSF2, and GBP1 genes were significantly over-expressed (p &amp;lt; 0.05 versus patients with therapeutic response). Finally, in stage IV melanoma patients with brain metastases, CCL18, CCR1, CCR4, CD274, CSF2, EGF, GBP1, and PTGS2 genes were significantly over-expressed (p &amp;lt; 0.05, versus patients without brain metastasis). Conclusions Significant differences were observed in the plasma transcriptomic profile between the various melanoma patient groups, and we postulate that these differences may be exploited to identify novel therapeutic targets or biomarkers relevant to melanoma. CCL4 and CCL5 are prognostic in melanoma, both genes had significantly higher expressions in low disease burden patients compared to patients with a high disease burden.

Altered Glycosylation of Human Alpha-1-Acid Glycoprotein as a Biomarker for Malignant Melanoma.

A high-resolution HILIC-MS/MS method was developed to analyze anthranilic acid derivatives of N-glycans released from human serum alpha-1-acid glycoprotein (AGP). The method was applied to samples obtained from 18 patients suffering from high-risk malignant melanoma as well as 19 healthy individuals. It enabled the identification of 102 glycan isomers separating isomers that differ only in sialic acid linkage (α-2,3, α-2,6) or in fucose positions (core, antenna). Comparative assessment of the samples revealed that upregulation of certain fucosylated glycans and downregulation of their nonfucosylated counterparts occurred in cancer patients. An increased ratio of isomers with more α-2,6-linked sialic acids was also observed. Linear discriminant analysis (LDA) combining 10 variables with the highest discriminatory power was employed to categorize the samples based on their glycosylation pattern. The performance of the method was tested by cross-validation, resulting in an overall classification success rate of 96.7%. The approach presented here is significantly superior to serological marker S100B protein in terms of sensitivity and negative predictive power in the population studied. Therefore, it may effectively support the diagnosis of malignant melanoma as a biomarker.