The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325015, People's Republic of China.
The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, 214200, People's Republic of China.
Arch Dermatol Res. 2024 May 24;316(6):219. doi: 10.1007/s00403-024-03085-y.
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.
皮肤皮肤黑色素瘤(SKCM)是一种恶性肿瘤,以其高度侵袭性和不良预后为特征,尤其是在晚期肿瘤中。失巢凋亡是一种与肿瘤再生、迁移和转移相关的特定程序性细胞死亡模式。然而,对于失巢凋亡在 SKCM 中的作用,研究还很有限。从 Genecards 中提取了与失巢凋亡相关的基因(ARGs),以鉴定 SKCM 亚型,并探讨不同亚型之间的免疫微环境。通过 LASSO COX 回归分析构建了 SKCM 的预后模型。随后,进一步探讨了风险评分在 SKCM 中的预测价值及其与免疫治疗的相关性。最后,通过免疫组化和 PCR 检测了模型构建中涉及的 6 个 ARGs 的表达。本研究鉴定了 20 个与 SKCM 预后显著相关的 ARGs,并基于这些基因对样本进行了疾病亚型分析,不同亚型表现出明显不同的临床特征和肿瘤免疫微环境(TIME)景观。通过进一步筛选和鉴定这 6 个 ARGs,构建了风险评分预后模型。该模型对预测 SKCM 患者的预后具有较高的敏感性和特异性。这些高低风险人群表现出不同的免疫状态和药物敏感性。进一步的免疫组化和 PCR 实验鉴定了这 6 个 ARGs 在肿瘤和正常样本中的差异表达。基于失巢凋亡的特征可作为 SKCM 的新型预后生物标志物,并为生存预测和个体化治疗的发展提供重要的新见解。
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