Melanocortin-1 receptor expression as a predictive factor for postoperative outcomes in melanoma patients: a retrospective study.

BACKGROUND AND OBJECTIVE

This study aims to explore the relationship between melanocortin-1 receptor (MC1R) expression levels and clinical pathological parameters of melanoma, as well as its potential as a prognostic biomarker.

METHODS

This retrospective study included 99 melanoma patients in our hospital from June 2017 to July 2023. MC1R expression was assessed by immunohistochemistry assays. Histochemistry score (H-score) determined the level of MC1R immunohistochemistry expression in melanoma. The relationships among MC1R expression, clinical pathological parameters in melanoma patients were assessed using Chi-square and Fisher's precision probability tests. Kaplan-Meier assay and log-rank test were utilized to estimate survival curves. Potential independent factors among the enrolled patients were investigated using COX regression analysis.

RESULTS

According to median value of H-score, 38 cases with low MC1R expression and 61 cases with high MC1R expression in melanoma tumor tissues were observed. Patients with high MC1R expression in melanoma tissues exhibited a worse prognosis compared to patients with low MC1R expression. The survival time difference was statistically significant [MC1R expression in melanoma tumor tissue (MC1RT): median DFS, 12.83 vs. 17.53 months, χ2 = 5.395, P=0.0202; median OS, 16.47 vs. 21.77 months, χ2 = 5.082, P=0.0243. MC1R expression in normal adjacent to melanoma tissue (MC1RN): median DFS, 12.03 vs. 14.29 months, χ2 = 6.864, P=0.0088; median OS, 16.73 vs. 21.77 months, χ2 = 5.649, P=0.0175]. Multivariate COX regression model analysis indicated that MC1RN, MC1RT, sex, ESR, tumor site, targeted therapy, and immunotherapy were potential prognostic factors for the DFS. Furthermore, MC1RN, MC1RT, sex, tumor site, TLN, PLN, and immunotherapy were potential prognostic factors for the OS. Calibration curve indicated the predicted probabilities of nomogram models were in accordance with the actual probabilities, and the prediction accuracy was relatively high at one year and three years following surgery. The decision clinical curve revealed that the nomogram models had better predictive performance for DFS and OS than the MC1RT or MC1RN thresholds.

CONCLUSIONS

Low MC1R expression in melanoma tumor tissues and adjacent normal tissue might be beneficial for the prognosis of melanoma patients. MC1R was a predictive factor for the prognosis of melanoma patients. Nomogram models based on MC1R demonstrated good prediction ability.