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研究内容:

本实验室研究方向聚焦肿瘤的精准诊断和精准免疫治疗。恶性肿瘤本质上是由体细胞 DNA 变异驱动的系统疾病,本实验室方向是从基因组 DNA 变异角度系统研究肿瘤发生以及演化的规律,寻找预测肿瘤临床表现的标志物,并设计针对性的治疗策略,尤其是针对性的免疫治疗策略。目前实验室的具体研究内容包括:

1 ,肿瘤基因组 DNA 拷贝数变异特征模式分析、机制研究,以及“拷贝数指纹”标志物的优化与应用。 结合基因组分析、人工智能与体外细胞实验,研究拷贝数变异的特征模式,产生机制。开发便捷的拷贝数指纹实验检测手段,并在肿瘤早筛、监测、免疫治疗以及靶向治疗临床标志物开发中的推广应用。

2 ,肿瘤基因组 DNA 变异编码的免疫原性分析以及生成式 AI 驱动的肿瘤精准免疫治疗。 利用人工智能大数据分析技术,结合细胞以及小鼠模型实验,深入研究抗原肽 /MHC/TCR 三元体互作的机制,实现高效新抗原疫苗设计、新抗原靶向 TCR 生成验证与应用,并转化于肿瘤病人的精准免疫治疗实践。

3 ,开发多模态组学整合可解释性 AI 方法,研发肿瘤精准分子分型策略以及精准治疗靶点。 关注难治肿瘤(如粘液腺癌、黏膜恶黑等)的精准分子分型,为难治性肿瘤提供有效的直接指导临床的分型策略。关注肿瘤代谢靶点的发掘,探究代谢对肿瘤免疫治疗有效性的影响。


课题组网站:

5 年来本实验室在肿瘤基因组大数据分析以及肿瘤精准诊疗方向取得一系列原创的、具有临床应用前景的重要发现。结合基因组人工智能( AI )分析检测,提出全新的“拷贝数指纹”标志物,大幅提升了癌症复发预测、化疗及免疫治疗诊断预测的精度,同时降低了检测成本。创新地开发了“肿瘤免疫原性指数”标志物,利用 AI 开发出肿瘤新抗原免疫原性预测工具。利用 AI 首次实现对肿瘤代谢依赖性靶点的系统发掘并实验验证,发现肿瘤缺氧适应的新靶点 FLAD1 并开发首个 FLAD1 抑制剂。实验室的研究工作紧密联系肿瘤临床的实际痛点问题,以第一负责人申报国家发明专利 10 项(已授权 8 项),部分专利的产业化工作正在稳步推进中。实验室负责人编著有国内第一本《癌症生物学》教科书(上海科学技术出版社,约 60 万字)。近 5 年在知名学术期刊(如 Cancer Res, eLife Brief Bioinform Oncogene )发表唯一通讯作者研究论文超过 20 篇,多篇通讯作者研究论文被 ESI 标记为“高被引论文”,连续入选 2022 2023 年度 Elsevier 发布的“中国高被引学者”榜单。


《癌症生物学》刘雪松编著,上海科学技术出版社,2024年出版




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