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T-cell receptor (TCR) detection can examine the extent of T-cell immune responses. Therefore, the article analyzed characteristic data of glioma obtained by DNA-based TCR high-throughput sequencing, to predict the disease with fewer biomarkers and higher accuracy. We downloaded data online and obtained six TCR-related diversity indices to establish a multidimensional classification system. By comparing actual presence of the 602 correlated sequences, we obtained two-dimensional and multidimensional datasets. Multiple classification methods were utilized for both datasets with the classification accuracy of multidimensional data slightly less to two-dimensional datasets. This study reduced the TCR β sequences through feature selection methods like RFECV (Recursive Feature Elimination with Cross-Validation). Consequently, using only the presence of these three sequences, the classification AUC value of 96. 67% can be achieved. The combination of the three correlated TCR clones obtained at a source data threshold of 0. 1 is: CASSLGGNTEAFFTRBV12TRBJ1-1, CASSYSDTGELFFTRBV6TRBJ2-2, and CASSLTGNTEAFFTRBV12TRBJ1-1. At 0. 001, the combination is: CASSLGETQYFTRBV12TRBJ2-5, CASSLGGNQPQHFTRBV12TRBJ1-5, and CASSLSGNTIYFTRBV12TRBJ1-3. This method can serve as a potential diagnostic and therapeutic tool, facilitating diagnosis and treatment of glioma and other cancers.
Zhou et al. (Thu,) studied this question.