构建前列腺腺癌分子分类:整合空间转录学与追溯队列验证
Bingnan Lu1, Yifan Liu1, Guo Ji2
1Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
Journal of translational medicine
|July 2, 2025
概括
前列腺腺癌 (PRAD) 的新分类系统基于恶性细胞分化对患者进行了分层. 这种工具有助于识别高风险个体和容易发生骨转移的人,以便进行早期干预.
科学领域:
- 在瘤学瘤学.
- 基因组学就是基因组学.
- 分子生物学分子生物学
背景情况:
- 前列腺腺癌 (PRAD) 是一种异质性疾病,其亚型与预后不佳有关.
- 精确的PRAD分子分类对于改善患者的治疗结果至关重要.
研究的目的:
- 开发一种基于细胞分化的PRAD新型分子分类系统.
- 在PRAD中识别与恶性细胞分化和预后相关的基因.
- 为了验证新分类系统的预后价值.
主要方法:
- 空间转录组分析以确定PRAD细胞类型.
- 单眼2用于细胞命运和分化基因识别.
- 预后相关基因的卡普兰-梅尔和考克斯回归.
- 共识ClusterPlus用于分类构建.
- 多omics相关性和网络分析.
- 免疫组织化学和队列验证.
主要成果:
- 确定了三种恶性斑点类型和33种恶性细胞分化相关的预后基因 (MDPG).
- 开发了基于恶性细胞分化的PRAD分类 (MDPC) 的三种亚型.
- MDPC证明了预后预测价值,与基因组学和免疫学相关联.
- COL1A1+MYLK+MDPC亚型是整体存活率和无进展存活率的独立风险因素.
结论:
- 成功构建并验证了PRAD的MDPC系统.
- MDPC提供了一个工具来分层PRAD患者,并识别高风险个体.
- 这种分类有助于预测骨转移风险,并使早期干预策略成为可能.
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