皮肤黑色素瘤（SKCM）是一种恶性癌症，以其高侵袭性和不良预后而闻名，特别是在晚期肿瘤中。失巢凋亡是一种与肿瘤再生、迁移和转移相关的程序性细胞死亡的特定模式。然而，关于失巢凋亡在 SKCM 中的功能的研究还很有限。从Genecards中提取失巢凋亡相关基因（ARG）来识别SKCM亚型并探索不同亚型之间的免疫微环境。 SKCM 的预后模型是通过 LASSO COX 回归分析开发的。随后，进一步探讨了 SKCM 风险评分的预测价值以及与免疫治疗的关联。最后通过免疫组化和PCR检测模型构建中涉及的6个ARGs的表达。本研究鉴定了20个与SKCM预后显着相关的ARG，并根据这些基因对样本进行了疾病亚型分析，不同亚型表现出显着不同的临床特征和肿瘤免疫微环境（TIME）景观。通过对六种 ARG 的进一步筛选和鉴定，生成风险评分预后模型。该模型对预测 SKCM 个体的预后表现出高度的敏感性和特异性。这些高危和低危人群表现出不同的免疫状态和药物敏感性。进一步的免疫组织化学和 PCR 实验发现肿瘤和正常样本中 6 种 ARG 的表达存在显着差异。基于失巢凋亡的特征可以作为 SKCM 的新型预后生物标志物，并可以为生存预测和个体化治疗开发提供重要的新见解。© 2024。作者获得 Springer-Verlag GmbH 德国（Springer Nature 旗下公司）的独家许可。

Skin cutaneous melanoma (SKCM) is malignant cancer known for its high aggressiveness and unfavorable prognosis, particularly in advanced tumors. Anoikis is a specific pattern of programmed cell death associated with tumor regeneration, migration, and metastasis. Nevertheless, limited research has been conducted to investigate the function of anoikis in SKCM. Anoikis-related genes (ARGs) were extracted from Genecards to identify SKCM subtypes and to explore the immune microenvironment between the different subtypes. Prognostic models of SKCM were developed by LASSO COX regression analysis. Subsequently, the predictive value of risk scores in SKCM and the association with immunotherapy were further explored. Finally, the expression of 6 ARGs involved in the model construction was detected by immunohistochemistry and PCR. This study identified 20 ARGs significantly associated with SKCM prognosis and performed disease subtype analysis of samples based on these genes, different subtypes exhibited significantly different clinical features and tumor immune microenvironment (TIME) landscapes. The risk score prognostic model was generated by further screening and identification of the six ARGs. The model exhibited a high degree of sensitivity and specificity to predict the prognosis of individuals with SKCM. These high- and low-risk populations showed different immune statuses and drug sensitivity. Further immunohistochemical and PCR experiments identified significant differential expression of the six ARGs in tumor and normal samples. Anoikis-based features may serve as novel prognostic biomarkers for SKCM and may provide important new insights for survival prediction and individualized treatment development.© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.