Wang Shanshan, Xing Hailong
Department of Dermatovenereology, Binzhou Central Hospital, Binzhou, Shandong, China.
Department of Neurosurgery, Binzhou Medical University Hospital, Binzhou, Shandong, China.
Medicine (Baltimore). 2025 Jun 13;104(24):e42888. doi: 10.1097/MD.0000000000042888.
Melanoma skin cancer occurs mostly in melanocytes, with a high degree of malignancy and poor prognosis. The continuous development of Mendelian stochastic analysis in the field of medicine has led to the discovery of new therapeutic genes and drug targets for many diseases. Therefore, we aim to discover more possible melanoma therapeutic targets through Mendelian randomization analysis. Based on the published genome-wide association study data, 2-sample MR was used to analyze the 2-way causal relationship between 731 immune cell characteristics and melanoma skin cancer. The results of the inverse variance weighted method were used as the main screening criteria to obtain the characteristics of immune cells associated with melanoma. Heterogeneity analysis, multiplicity analysis and one-to-one elimination test also ensure the robustness and sensitivity of the results. We obtained 26 related immune cell characteristics, of which 15 immune cell characteristics are protective factors for melanoma. Including CD25 on transitional B cell, switched memory B cell, IgD+ CD38- B cell, BAFF-R on transitional B cell, CD38 on IgD+ CD38dim B cell, CD24+ CD27+ B cell, CD39+ activated CD4 regulatory T cell, BAFF-R on IgD- CD38- B cell, BAFF-R on IgD+ CD38+ B cell, CD28 on CD4 regulatory T cell, CD66b on CD66b++ myeloid cell, CD25 on CD24+ CD27+ B cell, BAFF-R on switched memory B cell, CD11b on granulocytic myeloid-derived suppressor cells and CD4RA on terminally differentiated CD4+ T cell. 11 immune cell characteristics were risk factors, including CD14+ CD16- monocyte, CD25++ CD45RA- CD4 not regulatory T cell absolute count, activated CD4 regulatory T cell absolute count, CD39+ CD8+ T cell absolute count, CCR2 on myeloid dendritic cell, CD127 on CD45RA+ CD4+ T cell, CD11c+ monocyte, CD3 on central memory CD8+ T cell, CD4+/CD8+ T cell, CD3 on HLA DR+ CD4+ T cell and CD4- CD8- T cell. Reverse analysis showed that melanoma had no effect on immune cell characteristics. Our study used MR method to analyze the causal relationship between 731 immune cell characteristics and melanoma from a genetic point of view, which provides more possible ways for the treatment of melanoma patients.
皮肤黑色素瘤主要发生于黑素细胞，恶性程度高，预后差。医学领域孟德尔随机分析的不断发展，促使人们发现了许多疾病的新治疗基因和药物靶点。因此，我们旨在通过孟德尔随机化分析发现更多可能的黑色素瘤治疗靶点。基于已发表的全基因组关联研究数据，采用两样本孟德尔随机化方法分析731种免疫细胞特征与皮肤黑色素瘤之间的双向因果关系。以逆方差加权法的结果作为主要筛选标准，获取与黑色素瘤相关的免疫细胞特征。异质性分析、多重性分析和一对一剔除检验也确保了结果的稳健性和敏感性。我们获得了26种相关免疫细胞特征，其中15种免疫细胞特征是黑色素瘤的保护因素。包括过渡性B细胞上的CD25、转换记忆B细胞、IgD+CD38-B细胞、过渡性B细胞上的BAFF-R、IgD+CD38dimB细胞上的CD38、CD24+CD27+B细胞、CD39+活化CD4调节性T细胞、IgD-CD38-B细胞上的BAFF-R、IgD+CD38+B细胞上的BAFF-R、CD4调节性T细胞上的CD28、CD66b++髓样细胞上的CD66b、CD24+CD27+B细胞上的CD25、转换记忆B细胞上的BAFF-R、粒细胞性髓源性抑制细胞上的CD11b以及终末分化CD4+T细胞上的CD4RA。11种免疫细胞特征为危险因素，包括CD14+CD16-单核细胞、CD25++CD45RA-CD4非调节性T细胞绝对计数、活化CD4调节性T细胞绝对计数、CD39+CD8+T细胞绝对计数、髓样树突状细胞上CCR2、CD45RA+CD4+T细胞上的CD127、CDllc+单核细胞、中枢记忆CD8+T细胞上的CD3、CD4+/CD8+T细胞、HLA DR+CD4+T细胞上的CD3以及CD4-CD8-T细胞。反向分析表明黑色素瘤对免疫细胞特征无影响。我们的研究从遗传学角度采用孟德尔随机化方法分析了731种免疫细胞特征与黑色素瘤之间的因果关系，为黑色素瘤患者的治疗提供了更多可能途径。
