Jacqueline Wahura Waweru1, Kennedy Wanjau Mwangi1, Vayda R Barker2, Etienne C Gozlan2, Michelle Yeagley2, George Blanck3,4, Francis W Makokha5. 1. Department of Biochemistry, Jomo Kenyatta University of Agriculture and Technology, Nairobi, 62000-00200, Kenya. 2. Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, USA. 3. Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, USA. gblanck@usf.edu. 4. Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, 12901 Bruce B. Downs Bd. MDC7, Tampa, FL, 33612, USA. gblanck@usf.edu. 5. Directorate of Research and Innovation, Mount Kenya University, Thika, 342-01000, Kenya.
Abstract
PURPOSE: A very large and still expanding collection of adaptive immune receptor (IR) recombination reads, representing many diseases, is becoming available for downstream analyses. Among the most productive approaches has been to establish risk stratification parameters via the chemical features of the IR complementarity determining region-3 (CDR3) amino acid (AA) sequences, particularly for large datasets where clinical information is available. Because the IR CDR3 AA sequences often play a large role in antigen binding, the chemistry of these AAs has the likelihood of representing a disease-related fingerprint as well as providing pre-screening information for candidate antigens. To approach this issue in a novel manner, we developed a bladder cancer, case evaluation approach based on CDR3 aromaticity. METHODS: We developed and applied a simple and efficient algorithm for assessing aromatic, chemical complementarity between T-cell receptor (TCR) CDR3 AA sequences and the cancer specimen mutanome. RESULTS: Results indicated a survival distinction for aromatic CDR3-aromatic mutanome complementary, versus non-complementary, bladder cancer case sets. This result applied to both tumor resident and blood TCR CDR3 AA sequences and was supported by CDR3 AA sequences represented by both exome and RNAseq files. CONCLUSION: The described aromaticity factor algorithm has the potential of assisting in prognostic assessments and guiding immunotherapies for bladder cancer.
PURPOSE: A very large and still expanding collection of adaptive immune receptor (IR) recombination reads, representing many diseases, is becoming available for downstream analyses. Among the most productive approaches has been to establish risk stratification parameters via the chemical features of the IR complementarity determining region-3 (CDR3) amino acid (AA) sequences, particularly for large datasets where clinical information is available. Because the IR CDR3 AA sequences often play a large role in antigen binding, the chemistry of these AAs has the likelihood of representing a disease-related fingerprint as well as providing pre-screening information for candidate antigens. To approach this issue in a novel manner, we developed a bladder cancer, case evaluation approach based on CDR3 aromaticity. METHODS: We developed and applied a simple and efficient algorithm for assessing aromatic, chemical complementarity between T-cell receptor (TCR) CDR3 AA sequences and the cancer specimen mutanome. RESULTS: Results indicated a survival distinction for aromatic CDR3-aromatic mutanome complementary, versus non-complementary, bladder cancer case sets. This result applied to both tumor resident and blood TCR CDR3 AA sequences and was supported by CDR3 AA sequences represented by both exome and RNAseq files. CONCLUSION: The described aromaticity factor algorithm has the potential of assisting in prognostic assessments and guiding immunotherapies for bladder cancer.
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