破译透明细胞肾细胞癌的肿瘤微环境:使用机器学习从程序性死亡基因中获得预后见解。
Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning.
发表日期:2024 Jul
作者:
Hongtao Tu, Qingwen Hu, Yuying Ma, Jinbang Huang, Honghao Luo, Lai Jiang, Shengke Zhang, Chenglu Jiang, Haotian Lai, Jie Liu, Jianyou Chen, Liwei Guo, Guanhu Yang, Ke Xu, Hao Chi, Haiqing Chen
来源:
Cellular & Molecular Immunology
摘要:
透明细胞肾细胞癌(ccRCC)是一种常见的肾癌形式,其特点是侵袭性和异质性,给晚期预后和治疗结果带来了挑战。程序性细胞死亡机制对于消除癌细胞至关重要,为恶性肿瘤的诊断、治疗和预后提供了重要的见解。本研究旨在提供基于15种程序性细胞死亡相关基因(PCDRG)的模型,用于评估ccRCC患者的免疫微环境和预后。来自 TCGA 和 arrayexpress 队列的 ccRCC 患者根据 PCDRG 进行分组。构建了使用 Lasso 和 SuperPC 的组合模型来识别预后基因特征。 arrayexpress 队列验证了该模型,证实了其稳健性。在 PCDRG 的推动下,免疫微环境分析采用了多种方法,包括 CIBERSORT。药物敏感性分析指导临床治疗决策。单细胞数据支持程序性细胞死亡相关评分、随后的伪时间和细胞间通讯分析。 PCDRGs 签名是使用 TCGA-KIRC 数据建立的。 arrayexpress 队列的外部验证强调了该模型相对于传统临床特征的优越性。此外,我们的单细胞分析揭示了基于 PCDRG 的单细胞亚群在 ccRCC 中在伪时间进展和细胞间通讯中的作用。最后,我们进行了CCK-8测定和其他实验来研究csf2。总之,这些发现表明csf2抑制与肾透明细胞癌相关的细胞的生长、浸润和运动。本研究介绍了一种 PCDRG 预后模型,该模型有益于 ccRCC 患者,同时阐明了程序性细胞死亡基因在塑造 ccRCC 患者免疫微环境中的关键作用。© 2024 作者。细胞与分子医学基金会和约翰·威利出版的《细胞与分子医学杂志》
Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late-stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating cancer cells, offer substantial insights into malignant tumour diagnosis, treatment and prognosis. This study aims to provide a model based on 15 types of Programmed Cell Death-Related Genes (PCDRGs) for evaluating immune microenvironment and prognosis in ccRCC patients. ccRCC patients from the TCGA and arrayexpress cohorts were grouped based on PCDRGs. A combination model using Lasso and SuperPC was constructed to identify prognostic gene features. The arrayexpress cohort validated the model, confirming its robustness. Immune microenvironment analysis, facilitated by PCDRGs, employed various methods, including CIBERSORT. Drug sensitivity analysis guided clinical treatment decisions. Single-cell data enabled Programmed Cell Death-Related scoring, subsequent pseudo-temporal and cell-cell communication analyses. A PCDRGs signature was established using TCGA-KIRC data. External validation in the arrayexpress cohort underscored the model's superiority over traditional clinical features. Furthermore, our single-cell analysis unveiled the roles of PCDRG-based single-cell subgroups in ccRCC, both in pseudo-temporal progression and intercellular communication. Finally, we performed CCK-8 assay and other experiments to investigate csf2. In conclusion, these findings reveal that csf2 inhibit the growth, infiltration and movement of cells associated with renal clear cell carcinoma. This study introduces a PCDRGs prognostic model benefiting ccRCC patients while shedding light on the pivotal role of programmed cell death genes in shaping the immune microenvironment of ccRCC patients.© 2024 The Author(s). Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.