Lab


lab

About Zhang Lab

We aim to help advance cancer immunotherapies and targeted therapies by applying cutting-edge genomic and informatics technologies to solve important problems in cancer biology.  Our laboratory combines computational (dry) and experimental (wet) approaches to uncover both systematic trends and specific elements influencing oncogenic processes, tumor microenvironment, and drug responses. First, we use single cell sequencing technologies to delineate the detailed composition and functional status of the tumor microenvironment, in particular the landscape of the tumor infiltrating lymphocytes. We also use single cell technologies to address tumor heterogeneity and how such heterogeneity influence cancer cell evolution and drug responses.  Second, we apply advanced bioinformatics methods to the ever expanding cancer genomics “big data” to reveal cancer subtypes, driver genes, and underlying genetics basis leading to functional events such as gene fusions, allele-specific expression, and tumor-specific expression isoforms. Third, we develop innovative bioinformatics tools to analyze, integrate and visualize single cell genomics data as well as large-scale cancer genomics data so that such data can effectively serve the wide research community.

Dr. Zhang obtained his Bachler degree in Genetics from Nankai University, and PhD in Biochemistry and Molecular Biology from Penn State University. He received additional training in Information Technology from UC Berkeley and postdoctoral trainings in Laboratory Medicine from UC San Francisco.

Prior to joining Peking University, Dr. Zhang spent over 16 years at Genentech/Roche, leading the cancer genomics and bioinformatics group to discover anticancer targets and biomarkers using new technologies such as machine learning and high throughput sequencing. He has pioneered multiple research directions in computational cancer biology and cancer genomics including the first ever whole genome tumor sequencing. He is also an inventor for 60 issued US patents, and has directly contributed to the initial finding of the molecular targets of multiple cancer therapeutic agents in clinical trials. He is on the editorial boards for journals including Cell Systems, Genome Medicine, and Cancer Informatics. 

我们致力于用前沿的基因组学和生物信息学技术来解决癌症生物学中的重要问题,结合计算(干)和实验(湿)方法来揭示肿瘤发生过程、微环境和对药物响应中的系统变化和具体遗传因素,以推进癌症免疫治疗和靶向治疗的发展。首先,我们应用单细胞测序技术来研究肿瘤微环境,特别是浸润肿瘤免疫细胞的精确组成和功能状态,应用单细胞测序技术来研究肿瘤的异质性以及各种异质性对癌细胞的功能和药敏的影响。第二,我们将尖端生物信息学方法应用到癌症基因组学大数据中,以揭示癌症的亚型、驱动基因以及其他致癌因素的遗传基础,如基因融合、等位基因差异表达、肿瘤特有的转录异构体等,从而发现新型癌症靶点和标记物。第三,我们开发原创性的生物信息学工具来进行单细胞基因组数据和大规模癌症基因组学数据的分析、整合和可视化,为对这些数据的有效挖掘提供基础。

张博士于南开大学获得遗传学学士学位,于美国宾州州立大学获得生物化学与分子生物学博士学位。此外他还在加州大学伯克利分校获得了IT技术的训练,在加州大学旧金山分校的医学实验室完成了博士后训练。

在加入北京大学之前,张博士在著名生物医药公司基因泰克/罗氏(Genentech/Roche)工作了16年,担任癌症基因组学和生物信息学组的首席,致力于应用机器学习和高通量测序等高新技术进行抗癌药靶和生物标记物的发现。他在计算癌症生物学和癌症基因组学的多个方向上都是开拓者、引领者,如世界首例肿瘤全基因组测序即由张博士领导完成。张博士同时也是60个已获得授权的美国专利的发明人,并在目前正在临床试验中的多项癌症治疗药物的分子靶标的原创发现中做出了直接贡献。他同时也是多家国际知名杂志如Cell Systems、Genome Medicine和Cancer Informatics的编委。

更多详细内容,请访问 http://cancer-pku.cn/