根据对12种癌症的研究,确定参与肥胖相关癌症的关键基因和生物过程
1Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.
The international journal of biochemistry & cell biology
|March 1, 2025
概括
肥胖会增加癌症的风险. 一个名为OCEC_eDMN的新算法通过分析生物网络来识别与肥胖相关的癌症和关键基因,帮助预防和治疗策略.
科学领域:
- 在瘤学瘤学.
- 遗传学 遗传学 是一个
- 计算生物学 计算生物学
背景情况:
- 肥胖是许多疾病,特别是各种癌症的主要风险因素,构成了重大的公共卫生挑战.
- 了解肥胖和癌症之间的遗传和分子联系对于开发有效的预防和治疗策略至关重要.
研究的目的:
- 开发和验证一种新的算法,基于扩展模块化疾病基因和扩展模块化网络 (OCEC_eDMN) 的肥胖和癌症边缘连接,用于识别与肥胖相关的癌症.
- 阐明涉及肥胖与癌症之间联系的病理途径和关键基因.
主要方法:
- 该OCEC_eDMN算法集成了与疾病相关的基因,生物过程 (BP) 基因和蛋白质与蛋白质相互作用 (PPI) 网络.
- 它使用Random Walk with Restart (RWR) 扩展基因组并产生扩展模块化网络 (eMN) 和扩展模块化疾病基因 (eMD).
- 该算法计算了eMN内部eMD之间的边缘连接,并使用关键驱动器分析 (KDA).
主要成果:
- OCEC_eDMN成功预测和排名了12种与肥胖/致病性肥胖相关的癌症,达到高AUC值 (0.93/0.84).
- 该研究确定了重要的生物过程,如"葡萄糖生成",作为肥胖和癌症之间的关键联系.
- 关键驱动基因,如GRB2,被确定为关键连接器,例如,在特定网络模块内将病态肥胖与结直肠癌联系起来.
结论:
- OCEC_eDMN算法提供了一个强大的框架,用于识别肥胖与癌症的关联及其潜在的分子机制.
- 鉴定到的关键基因和通路为针对性预防和治疗与肥胖相关的癌症提供了宝贵的见解.
- 这项研究对理解代谢健康和瘤发生之间的复杂相互作用具有重要的理论意义.
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