PTPRC functions as a prognosis biomarker in the tumor microenvironment of cutaneous melanoma.

Cutaneous melanoma is one of the most malignant types of skin cancer, with an extremely poor prognosis. Immune cells infiltrated in the tumor microenvironment (TME) affects melanoma initiation, progression, prognosis and immunotherapy strategies in melanoma. The potential utility of TME-related genes as a prognostic model for melanoma and as a predictor of immunotherapeutic response merits further exploration. In this study, we determined that an immune-related gene, protein tyrosine phosphatase receptor type C (PTPRC), was positively correlated with the positive prognosis of melanoma patients. Integration of this gene with TNM classification created a predictive model that showed better performance in determining overall survival than others. PTPRC expression was positively correlated with the levels of immune checkpoint molecules, and PTPRC knockdown significantly enhanced the migration, invasion, and proliferation of melanoma cells. Finally, immunohistochemical results from HPA and Real-time quantitative PCR of clinical tissues confirmed that PTPRC expression was higher in melanoma than in normal skin. In conclusion, PTPRC served as a potential predictor of survival and response to immunotherapy in melanoma patients. The risk model combining the PTPRC and TNM classifications holds the potential to be a promising tool for prognostic prediction of cutaneous melanoma. This will help in the effective clinical management of melanoma patients.

A promising anoikis-related prognostic signature predicts prognosis of skin cutaneous melanoma.

BACKGROUND: Skin cutaneous melanoma (SKCM) is a highly aggressive disease with a poor prognosis for advanced tumors. Anoikis is a caspase-dependent cell death process triggered by extracellular matrix (ECM) detachment, rectifies detachment-induced metabolic defects that compromise cell survival, recent study revealed the crucial role of anoikis for cancer cells to survive during metastasis. However, limited research focused on the role of anoikis in SKCM. METHODS: Our study utilized the 27 anoikis-related genes (ARGs) to divide SKCM patients into two clusters, and obtain differentially expressed genes (DEGs) for each cluster. These DEGs were used in stepwise Cox regression analysis to develop a prediction model for SKCM patients consisting of nine ARGs, called the anoikis-related signature (ARS). Subsequently, we used the risk scores calculated from the ARS to divide SKCM patients into two groups and explored differences in immune microenvironment, immune checkpoint reactivity, and drug sensitivity between the groups. RESULTS: Nine ARGs were identified to stratify SKCM patients into two risk groups, patients in the high-risk group had a poor prognosis and suppressed immune cell infiltration. Moreover, higher expression of immune checkpoint molecules and a greater sensitivity to immunotherapy and chemotherapy drugs were observed in the low-risk group. Finally, all of the ARS hub genes were found to be upregulated in SKCM tissues and cell lines. CONCLUSION: A novel ARGs signature was identified for predicting the prognosis of SKCM. Based on the immune landscape associated with ARS discovered in our study, targeting ARS hub genes may be a promising treatment for SKCM.

Construction and Validation of a 6-Ferroptosis Related Gene Signature for Prognosis and Immune Landscape Prediction in Melanoma.

Ferroptosis is a newly discovered form of non-apoptotic cell death that relies on iron-mediated oxidative damage, playing a crucial role in the progression and therapy resistance of melanoma. Hence, the potential value of ferroptosis-related genes (FRGs) as a prognostic model and therapeutic target in melanoma requires further investigation. In this study, the relationship between FRGs and melanoma was revealed by analyzing the mRNA expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Synthesis (GEO). A 6-FRGs signature was constructed by Univariate, multivariate, and lasso Cox regression analyses in the TCGA cohort. The GEO database was used to validate the efficacy of the signature. The protein and mRNA expression level of the signature genes were examined in real-world melanoma tissues via immunohistochemical and quantificational real-time polymerase chain reaction (qRT-PCR). Functional enrichment analysis and immune-related analysis were conducted to identify the potential biological functions and pathways of the signature. Ten putative small molecule drugs were predicted by Connectivity Map (CMAP). As a result, a 6-FRGs signature was constructed to stratify melanoma patients into two risk groups. Compared with the low-risk group, patients in the high-risk group had a worse prognosis and a lower ImmuneScore. Immune-related pathways were enriched in the low-risk group. Immune Function and immune cell infiltration of the low-risk group were significantly higher than that of the high-risk group. The differential expression of these six FRGs in melanoma and adjacent normal tissues was confirmed. Moreover, higher expression of immune checkpoint molecules and a greater sensitivity to immunotherapy were observed in the low-risk group. Some small molecular drugs in the CMAP database hold the potential to treat melanoma. Overall, we identified a novel FRGs signature for prognostic prediction in melanoma. Based on the signature-related immune infiltration landscape found in our study, targeting the FRGs might be a therapeutic alternative for melanoma.

m6A Methyltransferase METTL3 Promotes the Progression of Primary Acral Melanoma via Mediating TXNDC5 Methylation.

m6A modification is one of the most important post-transcriptional modifications in RNA and plays an important role in promoting translation or decay of RNAs. The role of m6A modifications has been highlighted by increasing evidence in various cancers, which, however, is rarely explored in acral melanoma. Here, we demonstrated that m6A level was highly elevated in acral melanoma tissues, along with the expression of METTL3, one of the most important m6A methyltransferase. Besides, higher expression of METTL3 messenger RNA (mRNA) correlated with a higher stage in primary acral melanoma patients. Knockdown of METTL3 decreased global m6A level in melanoma cells. Furthermore, METTL3 knockdown suppressed the proliferation, migration, and invasion of melanoma cells. In METTL3 knockdown xenograft mouse models, we observed decreased volumes and weights of melanoma tissues. Mechanistically, we found that METTL3 regulates certain m6A-methylated transcripts, thioredoxin domain containing protein 5 (TXNDC5), with the confirmation of RNA-seq, MeRIP-seq, and Western blot. These data suggest that METTL3 may play a key role in the progression of acral melanoma, and targeting the m6A dependent-METTL3 signaling pathway may serve as a promising therapeutic strategy for management of patients of acral melanomas.