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使用生物信息学和机器学习识别MAPK12作为食道癌的预后生物标志物

Shuyuan Gu¹, Xinyang Yan^2,3, Shihui Chen⁴

¹Department of General Surgery, Xi'an No. 9 Hospital, Xi'an, Shaanxi Province, China.

BioMed research international

|December 31, 2025

概括

这项研究使用生物信息学和机器学习开发了一种基于端粒的食道癌 (ESCA) 预后模型. 该模型准确预测患者的生存率,并将MAPK12确定为潜在的治疗点.

科学领域:

在瘤学瘤学.
生物信息学是一种生物信息学.
基因组学就是基因组学.

背景情况:

食道癌 (ESCA) 构成了全球重大健康挑战.
准确的预后标记对于有效的ESCA患者管理至关重要.
端粒功能障碍与各种癌症有关,包括ESCA.

研究的目的:

开发一种新的与端粒相关的预后特征,用于食道癌 (ESCA).
为了确定关键的基因和涉及ESCA进展的途径.
验证预后模型并探索治疗目标.

主要方法:

生物信息学和机器学习技术的整合.
鉴定差异表达基因 (DEGs) 和枢纽基因.
使用LASSO和考克斯回归构建和验证预后模型.
实验验证包括细胞学检测.

主要成果:

为ESCA开发了一种强大的与端粒相关的预后签名.
该模型在独立数据集中展示了患者存活率的显著预测能力.
线素激活蛋白激酶12 (MAPK12) 被确定为ESCA细胞迁移的关键驱动因素.

结论:

开发的预后模型提供了一个可靠的工具来预测ESCA患者的结果.
MAPK12成为ESCA的潜在诊断生物标志物和治疗点.
这项研究为了解ESCA病原和开发向治疗提供了基础.

关键词:

生物信息学是一种生物信息学.这是食道癌,食道癌.预后预后预后签名签名签名签名端粒是什么意思端粒是什么意思

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