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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #379556
Research Project: Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection

Location: Animal Genomics and Improvement Laboratory

Title: Bioinformatics of T-cell and primary tumor cells - Fundamental of adoptive T-cell immunotherapy

Author
item Liu, Ge - George
item ZHENG, JIE - Nanyang Technological University
item LI, BIAORU - Augusta University

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 11/3/2020
Publication Date: 11/3/2020
Citation: Liu, G., Zheng, J., Li, B. 2020. Bioinformatics of T-cell and primary tumor cells - Fundamental of adoptive T-cell immunotherapy (Chapter 8). In: Li, B., Larson, A., Li, S. editors. Personalized Immunotherapy for Tumor Diseases and Beyond. Singapore, Singapore: Bentham Science Publishers Pte. Ltd. p. 118-136.

Interpretive Summary: Comprehensive analyses of genetic regulatory variants will benefit our understanding of genetic bases for complex traits. Using tumor as a model, we provided a new bioinformatics platform for analyzing GWAS, genomic expression profile along with system modeling. This platform will also similarly fill our knowledge gaps and provide the foundation for incorporating new transcriptome insights into the future animal breeding program. Farmers, scientist, and policy planners who need improve animal health and production based on genome-enabled animal selection will benefit from this study.

Technical Abstract: Epitope discovery of tumor antigen and mutant proteins has enabled a better application of T-cell immunotherapy. Genomic profiles analyzed by genomic expression and single nucleotide polymorphisms (SNP) by genome-wide association studies (GWAS) are an essential fundamental to screen and define T-cell therapeutic targets. To determine tumor antigens or mutant proteins related to T-cell targets with their TCR or CAR reconstruction, we will introduce the SNP technique related to primary tumor cells for personalized T-cell immunotherapy, including global and local SNP detection of the therapeutic targets. Moreover, the use of mRNA genomic expression can discover gene expression signature and further uncover tumor-associated antigen (TAA) or tumorspecific antigen (TSA) for T-cell immunotherapy. Accompany with the ongoing development of next-generation sequencing, epitope discovery of tumor neoantigen and mutant proteins will be irreplaceable for a novel generation of T-cell adoptive immunotherapy. Systems biology, which is a mathematical modeling of complex biological systems, can integrate data of SNP signature and genomic expression signature. Thus, a new bioinformatics platform with the analysis of GWAS and genomic expression profile along with system modeling is an essential fundamental for T-cell adoptive immunotherapy.