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基于生物信息学和深度学习,探索和验证皮肤黑色素瘤患者病理学特征和基因组学的预后价值
Xiaoyuan Li1, Xiaoqian Yu2, Duanliang Tian3
1Department of Traditional Chinese Medicine, The affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Medical physics
|September 18, 2023
概括
病理学特征在预测皮肤黑色素瘤 (CM) 预后方面具有很高的准确性,仅仅优于基因表达. 结合病理学和基因组学,为个性化CM患者风险评估提供了一个强大的工具.
科学领域:
- 在瘤学瘤学.
- 计算病理学计算病理学
- 基因组学就是基因组学.
背景情况:
- 皮肤黑色素瘤 (CM) 是一种流行性皮肤癌.
- 调查预后标志物对于有效的CM管理至关重要.
- 这项研究结合了病理学和基因组学,以评估CM的预后价值.
研究的目的:
- 探索皮肤黑色素瘤病理学特征的预后潜力.
- 整合病理学和基因组学数据,以改善CM预后预测.
主要方法:
- 从TCGA下载了CM患者的病理图像,临床和基因组学数据.
- 利用CellProfiler用于病理学特征提取和人工神经网络 (ANN) 模型用于预后预测.
- 进行了差异基因表达分析,生存分析和病理学和基因组学之间的相关性分析.
主要成果:
- 病理学签名在CM预后的二进制分类中达到99%的精度.
- 不同表达的基因显示98%的精度,而组合模型达到97%的精度.
- 存活率分析表明,通过基因表达和病理学特征识别的高风险群体的存活率明显较低.
结论:
- 病理学特征,特别是当用ANN模型分析时,显示CM预后预测的高准确性.
- 病理学和基因组学的整合提供了一个强大的方法来分层CM患者的风险.
- 确定了关键的临床因素 (年龄,活检部位,T,N和整体阶段) 以及病理和基因表达之间的初步联系.
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