Adaptive immune receptor (IR) chemical features have been used as signatures of an immune response for numerous medical conditions, raising the question of whether certain approaches to assessing the IR chemical features are more robust than others? In the cancer setting, a very large dataset of IR complementarity determining region-3 (CDR3) amino acid (AA) sequences has become available via the mining of cancer specimen and blood genomics files for IR recombination reads. The IR CDR3 AA sequences have been evaluated for chemical features, and survival rates have been correlated with distinct chemical features. Two common approaches have been i) to assign a single value to the CDR3, representing a chemical attribute, such as aromaticity; or ii) to reduce the actual CDR3 AA sequence to a chemical sequence motif, which merges similar CDR3 chemistries represented by distinct AA sequences but preserves potential functional aspects of the order of the AAs in the sequence. While a controlled comparison of the two approaches is not possible, the application of the two approaches to the same clinical datasets offers the opportunity to appreciate a trend with regard to the overall potential in distinguishing survival probabilities. We demonstrate that application of the chemical sequence motif approach is more likely to identify survival distinctions within cancer datasets, for both tumor specimen and blood sourced, adaptive IR CDR3 AA sequences.
Keywords: amino acid motifs; blood and tumor samples; complementarity determining region-3; immune receptors; physicochemical features.
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