Bo Li, Ph.D.
Assistant Professor

Download Curriculum Vitae

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

Featured Publications

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

 Featured Books

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

• Circle of Friends Cancer Research Award
  (2018)
• Harvard Medical School Yongjin Chinese Scholar Award
  (2017)