Department of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, Hunan Province, 410000, People's Republic of China.
Sci Rep. 2023 Nov 23;13(1):20617. doi: 10.1038/s41598-023-46794-6.
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.
皮肤黑色素瘤是最恶性的皮肤癌之一，预后极差。浸润在肿瘤微环境（TME）中的免疫细胞影响黑色素瘤的发生、进展、预后和免疫治疗策略。TME 相关基因作为黑色素瘤预后模型和免疫治疗反应预测因子的潜在用途值得进一步探索。在这项研究中，我们确定了一个免疫相关基因，蛋白酪氨酸磷酸酶受体型 C（PTPRC），与黑色素瘤患者的良好预后呈正相关。将该基因与 TNM 分类相结合，创建了一个预测模型，该模型在确定总生存期方面的表现优于其他模型。PTPRC 表达与免疫检查点分子水平呈正相关，PTPRC 敲低显著增强了黑色素瘤细胞的迁移、侵袭和增殖。最后，HPA 的免疫组化结果和临床组织的实时定量 PCR 证实 PTPRC 在黑色素瘤中的表达高于正常皮肤。总之，PTPRC 可作为黑色素瘤患者生存和免疫治疗反应的潜在预测因子。结合 PTPRC 和 TNM 分类的风险模型有可能成为预测皮肤黑色素瘤预后的有前途的工具。这将有助于对黑色素瘤患者进行有效的临床管理。
