Dados do Resumo

Título

Expression of immunometabolic genes associated with lymph node metastasis in melanoma patients: Insights for new potential biomarkers and therapeutic targets

Introdução

Melanoma represents an important cause of mortality due to its rapid invasion, metastasis, and disease progression. Understanding the signaling pathways and gene expression patterns associated with these processes could facilitate the identification of patients at high risk for unfavorable outcomes. Additionally, this understanding could point out new therapeutic targets.

Objetivo

To identify genes associated with lymph node metastasis at diagnosis of melanoma patients.

Métodos

This study included a cohort of 52 patients diagnosed with melanoma with paraffin-embedded tissue blocks containing at least 60% tumor cells. Clinical data were collected from medical records. RNA was extracted from tumor samples using the RNAeasy Mini Kit and analyzed using the Metabolic Pathways Panel in nCounter NanoString. Differential expression genes were identified using the advanced analysis module of nSolver Analysis v.3.0. Multivariate analyses were performed in SPSS v. 23.0, with logistic binary method with forward conditional adjustment. The predictive score was calculated by multiplying regression coefficient by gene expression. ROC curve analysis was performed to evaluate the accuracy of the model. This study was approved by the Ethics Research Committee (CEP-HCB 1772/2019).

Resultados

The cohort consisted mainly of males (59.6%), with tumors predominantly located in the lower limbs (34.6%) and exhibiting a nodular histological subtype (34.6%). Lymph node metastasis was detected at diagnosis in 29 patients (55.8%). The BRAF V600E variant was detected in 30.8% of patients. From the 748 evaluated genes, 6 genes were upregulated (LTA4H, ADH1B, SLC7A11, PSAT1, ALDH2, and GAPDHS) and 3 genes were downregulated (THBS1, PFKM, CCND1, S100A1, SOX2, and A2M) in patients with lymph node metastasis at diagnosis. In the multivariate analysis, the genes LTA4H, SLC7A11, GAPDHS, THBS1, and S100A1 were highlighted as predictors and a 5-gene score was constructed, with a high accuracy (AUC = 0.883, p < 0.001) in prediction of lymph node metastasis.

Conclusões

This study indicates potential genes associated with melanoma lymph node metastasis, associated with several metabolic pathways and immune function. These markers represent potential prognostic biomarkers in melanoma and may also serve as promising targets for future therapeutic interventions.

Financiador do resumo

This research was funded by the São Paulo Research Foundation (FAPESP, #2019/07111-9), National Council for Scientific and Technological Development (CNPQ, # 444017/2023-2) and Brazilian Melanoma Group (GBM).

Palavras Chave

Immunometabolism; Lymph Node Metastasis; Melanomas