Department of Dermatology, The First Medical Center of PLA General Hospital, Beijing, China.
Department of Dermatology, The First Affiliated Hospital of Qiqihar Medical College, Qiqihar City, Heilongjiang Province, China.
Adv Med Sci. 2022 Sep;67(2):364-378. doi: 10.1016/j.advms.2022.09.004. Epub 2022 Sep 22.
Although skin cutaneous melanoma (SKCM) is a relatively immunotherapy-sensitive tumor type, there is still a certain fraction that benefits less from treatment. Ferroptosis has been demonstrated to modulate tumor progression in many cancer types. This study focused on ferroptosis-related genes to construct a prognostic model for SKCM patients.
Gene expression profiles of SKCM samples were obtained from public databases. Unsupervised consensus clustering was used to determine molecular subtypes related to ferroptosis. Least absolute shrinkage and selection operator (LASSO) and stepwise Akaike information criterion (stepAIC) were applied to construct a prognostic model based on differentially expressed genes between two molecular subtypes.
C1 and C2 subtypes were identified with differential prognosis and immune infiltration. A 7-gene prognostic model was constructed to classify samples into high-FPRS and low-FPRS groups. Low-FPRS group with favorable prognosis had higher immune infiltration and more enriched immune-related pathways than the high-FPRS group. The two groups showed distinct sensitivity to immunotherapy, with the low-FPRS group predicted to have more positive response to immunotherapy than the high-FPRS group. A nomogram based on the FPRS score and clinical features was built for more convenient use.
The critical role of ferroptosis involved in SKCM development was further validated in this study. The prognostic model was efficient and stable to be applied in clinical conditions to support clinicians in determining personalized therapy for SKCM patients especially those with metastasis.
尽管皮肤黑色素瘤（SKCM）是一种相对对免疫疗法敏感的肿瘤类型，但仍有一定比例的患者受益较少。铁死亡已被证明能调节许多癌症类型的肿瘤进展。本研究专注于铁死亡相关基因，以构建 SKCM 患者的预后模型。
从公共数据库中获取 SKCM 样本的基因表达谱。采用无监督共识聚类确定与铁死亡相关的分子亚型。最小绝对值收缩和选择算子（LASSO）和逐步 Akaike 信息准则（stepAIC）用于构建基于两种分子亚型之间差异表达基因的预后模型。
确定了具有不同预后和免疫浸润的 C1 和 C2 亚型。构建了一个 7 基因预后模型，用于将样本分为高-FPRS 和低-FPRS 组。预后良好的低-FPRS 组的免疫浸润更高，免疫相关途径更丰富。两组对免疫治疗的敏感性明显不同，低-FPRS 组预测对免疫治疗的反应更积极。基于 FPRS 评分和临床特征的列线图构建，以便更方便地使用。
本研究进一步验证了铁死亡在 SKCM 发展中的关键作用。该预后模型在临床条件下是有效且稳定的，可用于支持临床医生为 SKCM 患者，特别是有转移的患者，制定个性化治疗方案。
