During tumor progression, the host immune system is constantly evolving with the malignant cells in an antigen-dependent manner. Identification of tumor-reactive lymphocytes has become one of the most critical task in finding effective treatments for late-stage cancers. Li lab studies the complicated interactions between cancer and the immune system using genomics, computational, statistical and experimental approaches. We are particularly interested in the antigen-specific tumor-infiltrating T cells, and have developed a number of computational methods to identify their cognate targets. In addition, we developed deep learning methods to perform de novo prediction of cancer-associated T cells in the blood samples. Our ongoing research could provide an alternative solution to the long-standing challenge of early cancer detection.
Education and Professional Experience:
2017-Present: Assistant Professor, UT Southwestern
2014-2017: Postdoc research fellow at Dana-Farber Cancer Institute and Harvard Statistics Department
2009-2014: Graduate student research assistant at University of Michigan
- Immune-based early cancer detection
- Single cell analysis of tumor-infiltrating T cells
- Statistical and computational analysis of the hyper-diversified TCR repertoire
- GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation.
- Zhang H, Zhan X, Li B, Nat Commun 2021 08 12 1 4699
- De novo prediction of cancer-associated T cell receptors for noninvasive cancer detection.
- Beshnova D, Ye J, Onabolu O, Moon B, Zheng W, Fu YX, Brugarolas J, Lea J, Li B, Sci Transl Med 2020 Aug 12 557
- Landscape of tumor-infiltrating T cell repertoire of human cancers.
- Li B, Li T, Pignon JC, Wang B, Wang J, Shukla SA, Dou R, Chen Q, Hodi FS, Choueiri TK, Wu C, Hacohen N, Signoretti S, Liu JS, Liu XS Nat. Genet. 2016 May
- Investigation of antigen-specific T cell receptor clusters in human cancers.
- Li B, Zhang H, Liu L, Zhang J, Chen J, Ye J, Shukla SA, Qiao J, Zhan X, Chen H, Wu CJ, Fu YX, Clin. Cancer Res. 2019 Dec
- TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.
- Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, Li B, Liu XS Cancer Res. 2017 Nov 77 21 e108-e110
- Ultrasensitive detection of TCR hypervariable-region sequences in solid-tissue RNA-seq data.
- Li B, Li T, Wang B, Dou R, Zhang J, Liu JS, Liu XS Nat. Genet. 2017 Mar 49 4 482-483
- Comprehensive analyses of tumor immunity: implications for cancer immunotherapy.
- Li B, Severson E, Pignon JC, Zhao H, Li T, Novak J, Jiang P, Shen H, Aster JC, Rodig S, Signoretti S, Liu JS, Liu XS Genome Biol. 2016 17 1 174
- A general framework for analyzing tumor subclonality using SNP array and DNA sequencing data.
- Li B, Li JZ Genome Biol. 2014 Sep 15 9 473
- Genomic estimates of aneuploid content in glioblastoma multiforme and improved classification.
- Li B, Senbabaoglu Y, Peng W, Yang ML, Xu J, Li JZ Clin. Cancer Res. 2012 Oct 18 20 5595-605
Computational deconvolution of tumor-infiltrating immune components with bulk tumor gene expression data. In Bioinformatics for Cancer Immunotherapy
Bo Li (2020). New York, NY, Humana
Honors & Awards
- Circle of Friends Cancer Research Award
- Harvard Medical School Yongjin Chinese Scholar Award