深度转移学习通过转录学将良性腺与前列腺癌进展联系起来
Justin L Couetil1,2, Ziyu Liu3, Chao Chen4
1Department of Medical and Molecular Genetics, IU School of Medicine, Indianapolis, IN 46202, USA.
Genomics, proteomics & bioinformatics
|November 29, 2025
概括
研究人员发现,瘤附近的看似正常的前列腺组织表现出分子变化,表明可能推动癌症进展的"场效应". 这些变化,包括改变基因表达和免疫细胞活性,与转移风险增加有关.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 场效应描述了易患癌症的细胞变化,但在高分辨率的奥米学中未得到充分研究.
- 前列腺癌的进展涉及瘤微环境中的复杂相互作用.
研究的目的:
- 用深度学习和空间转录学来研究前列腺癌中的场效应.
- 识别与癌症攻击性相关的形态良性组织中的分子变化.
主要方法:
- 使用单细胞诊断证据计 (DEGAS) 深度转移学习框架.
- 分析了前列腺癌空间转录组和集成的单细胞转录组与深度学习图像分析.
- 量化MSMB蛋白 (PSP-94) 用免疫组织化学在患者组织上的表达.
主要成果:
- DEGAS发现了良性腺体,MSMB表达减少,与抗原呈现和侵略性瘤相关的基因升级.
- 在瘤微环境中观察到免疫细胞透的变化.
- 较低的MSMB蛋白表达在形态正常组织与远程转移的风险增加相关.
结论:
- 表面上正常的前列腺组织中微妙的分子和免疫变化,代表一个场效应,有助于侵袭性疾病的进展.
- 这些发现强调了分析更广泛的组织背景对于理解癌症攻击性的重要性.
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