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预测结直肠癌的预后和免疫治疗益处的机器学习衍生基因签名

Guangda Yang¹, Jieming Xiao², Huixiang He³

¹Department of Cancer Chemotherapy, The Fourth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 511300, People's Republic of China.

ImmunoTargets and therapy

|September 2, 2025

概括

这项研究确定了与缩相关的基因特征 (NRGS),可预测结直肠癌 (CRC) 患者的结果和治疗反应. 该NRGS强调了改善CRC治疗耐药性的潜在治疗目标.

科学领域:

癌症学
分子生物学
生物信息学

背景情况:

结肠直肠癌 (CRC) 由于耐治疗性而构成全球重大健康挑战.
缩是一种翻译后的修饰,影响瘤的进展和免疫反应,但其在CRC中的作用仍未得到充分研究.

研究的目的:

研究结直肠癌亚型中与缩相关的基因 (NRG) 的作用.
开发和验证与缩相关的基因特征 (NRGS),用于预测CRC患者的预后和治疗反应.

主要方法:

来自TCGA和GEO数据库的CRC单细胞RNA测序 (scRNA-seq) 和大量RNA-seq数据的分析
使用十个机器学习算法和外部验证开发NRGS.
在高风险和低风险组之间对生物功能,免疫细胞透,基因组突变和治疗反应进行比较分析.

主要成果:

在CRC中高的缩分数与恶性和多样化的免疫/肌瘤细胞增加有关,促进瘤生长和扩散.
鉴定出两种不同的缩模式,其中B组与较低的存活率,免疫抑制和瘤进展有关.
开发的NRGS准确预测了高AUC值的整体存活期,并与晚期疾病,复发和转移相关.

结论:

在CRC患者中,NRGS有效预测了免疫治疗和化疗的预后和潜在耐药性.
这种特征有助于制定个性化结直肠癌治疗策略.
建议进一步验证NRGS的临床实用性.

关键词:

美国大肠直肠癌免疫疗法机器学习没有缩预后情况

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