摘要
      皮肤黑色素瘤（SKCM）恶性程度高，预后差。衰老相关基因（ARGs）在SKCM中的功能尚不清楚。在本研究中，根据《癌症基因组图谱》中的SKCM RNA-seq、突变和临床数据构建了ARG的预后风险评分模型。我们的新预后模型包括四种ARG（IRS2、PDGFRA、TFAP2A和SOD2），可以区分低风险组和高风险组。与高危患者相比，低风险患者从免疫疗法和常用靶向药物和化疗药物中获益更多。两组之间的免疫细胞浸润和肿瘤微环境也有相当大的差异。此外，多变量Cox回归分析显示，年龄、pT_分期、pM_分期、体重指数、肿瘤突变负担和风险评分是影响SKCM患者预后的独立因素；因此，我们设计了一个预后列线图。最后，构建了竞争内源性RNA网络的长非编码（lncRNA）NEAT1/miR-33a-5p/IRS2调节轴，以研究SKCM转移进展的机制。基于评分系统的分组可以预测SKCM的预后，并预测患者对免疫疗法、靶向治疗和化疗的敏感性。这有助于制定个性化的治疗策略，并有助于药物研发。这些发现突出了lncRNA NEAT1/miR-33a-5p/IRS2的调节轴，其可能在SKCM转移中发挥作用。
Abstract
Skin cutaneous melanoma (SKCM) has substantial malignancy and a poor prognosis. The function of ageing-related genes (ARGs) in SKCM is unknown. In this study, a prognostic risk-scoring model for ARG was constructed based on SKCM RNA-seq, mutation, and clinical data in The Cancer Genome Atlas. Our novel prognostic model, which included four ARGs (IRS2, PDGFRA, TFAP2A, and SOD2), could distinguish between low-risk and high-risk groups. Low-risk patients benefited more from immunotherapy and commonly used targeted and chemotherapy drugs than high-risk patients. There were also considerable differences in immunocyte infiltration and tumour microenvironment between the two groups. Furthermore, multivariate Cox regression analysis revealed that age, pT_stage, pM_stage, body mass index, tumour mutation burden, and risk score were independent factors influencing the prognosis of patients with SKCM; therefore, we devised a prognosis nomogram. Last, a long non-coding (lncRNA) NEAT1/miR-33a-5p/IRS2 regulatory axis of the competing endogenous RNA network was built to investigate the mechanisms of SKCM metastasis progression. Grouping based on the scoring system could predict the prognosis of SKCM and predict the sensitivity of patients to immunotherapy, targeted therapy, and chemotherapy. This could facilitate the formulation of individualised treatment strategies and help drug research and development. These findings highlight the regulatory axis of the lncRNA NEAT1/miR-33a-5p/IRS2, which may play a role in SKCM metastasis.

https://www.nature.com/articles/s41598-022-22259-0