《生物技术创新与创业》课程介绍

授课教师 张泽民 开课学期 秋季
课程名称 生物技术创新与创业 学  分 1
英文名称 Biotechnology Innovation and Entrepreneurship 授课对象(博/硕) 博士生、硕士生

课程简介:

近几年,随着新技术的发展和精准医疗概念的提出,生命科学领域的涌现大量科研成果和发现。但对于大多数研究来说,将新技术和新成果转化为面向大众的产品或服务模式使其发挥应有的价值仍然不甚明了。

本课程旨在通过生命科学业界精英结合个人发展和创业经历,以课程讲座等形式和学生分享包括产业发展历史,生物技术现状,生命科学发展前景,科研成果转化思路和创业创新思维等,使学生了解目前我国生命科学产业最前沿动态,丰富学生视野、提升学术能力,学习创新创业理念和技术成果转化经验,启发多向思考。

上课安排:

1-16周每单周上课 时间 地点 备注
9月19日 3:00-5:00 pm 二教423
10月3日
10月17日 3:00-5:00 pm 二教423 刘毓文
10月31日 3:00-5:00 pm 二教423 Jasmine Cui
11月14日 3:00-5:00 pm 二教423 刘立宇
11月28日 3:00-5:00 pm 二教423 李英睿,碳云
12月12日 3:00-5:00 pm 二教423 李瑞强
12月26日 3:00-5:00 pm 二教423

嘉宾介绍:

张泽民教授:http://cancer-pku.cn/index.php/people/zemin-zhang/

刘毓文:http://cancer-pku.cn/index.php/2018/10/08/yuwen-liu/

Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing

Cancer immunotherapies have shown sustained clinical responses in treating non-small-cell lung cancer, but efficacy varies and depends in part on the amount and properties of tumor infiltrating lymphocytes. To depict the baseline landscape of the composition, lineage and functional states of tumor infiltrating lymphocytes, here we performed deep single-cell RNA sequencing for 12,346 T cells from 14 treatment-naïve non-small-cell lung cancer patients. Combined expression and T cell antigen receptor based lineage tracking revealed a significant proportion of inter-tissue effector T cells with a highly migratory nature. As well as tumor-infiltrating CD8+ T cells undergoing exhaustion, we observed two clusters of cells exhibiting states preceding exhaustion, and a high ratio of “pre-exhausted” to exhausted T cells was associated with better prognosis of lung adenocarcinoma. Additionally, we observed further heterogeneity within the tumor regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of those activated tumor Tregs, which included IL1R2, correlated with poor prognosis in lung adenocarcinoma. Our study provides a new approach for patient stratification and will help further understand the functional states and dynamics of T cells in lung cancer.

Continue reading

Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing

Systematic interrogation of tumor-infiltrating lymphocytes is key to the development of immunotherapies and the prediction of their clinical responses in cancers. We performed deep single-cell RNA sequencing on 5,063 single T cells isolated from peripheral blood, tumor, and adjacent normal tissues from six hepatocellular carcinoma patients. The transcriptional profiles of these individual cells, coupled with assembled T cell receptor (TCR) sequences, enable us to identify 11 T cell subsets based on their molecular and functional properties and delineate their developmental trajectory. Specific subsets such as exhausted CD8+ T cells and Tregs are preferentially enriched and potentially clonally expanded in hepatocellular carcinoma (HCC), and we identified signature genes for each subset. One of the genes, layilin, is upregulated on activated CD8+ T cells and Tregs and represses the CD8+ T cell functions in vitro. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the immune landscape in cancers.

Continue reading

Want to touch cancer big data in 1 second? Go GEPIA!

Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA is available at http://gepia.cancer-pku.cn/.

Continue reading

Check out our APP – GE-mini

Here we present to you our new Android APP: GE-mini.

This GE-mini APP is designed to exhibit gene expression profiling of a given gene over many tissue types including tumors. The underlying data are based on RNA Sequencing results from both TCGA and GTEx after they are normalized and integrated. The current version, based on the September 2015 release of TCGA and the phs000424.v6.p1 release of GTEx, contains >19,000 total samples across 33 cancer types and 53 normal tissue types.

Continue reading