Comprehensive characterization and database construction of immune repertoire in the largest Chinese glioma cohort

Abstract

Immune receptor repertoire is valuable for developing immunotherapeutic interventions, but remains poorly understood across glioma subtypes including IDH wild type, IDH mutation without 1p/19q codeletion (IDHmut-noncodel) and IDH mutation with 1p/19q codeletion (IDHmut-codel). We assembled over 320,000 TCR/BCR clonotypes from the largest glioma cohort of 913 RNA sequencing samples in the Chinese population, finding that immune repertoire diversity was more prominent in the IDH wild type (the most aggressive glioma). Fewer clonotypes were shared within each glioma subtype, indicating high heterogeneity of the immune repertoire. The TRA-CDR3 was longer in private than in public clonotypes in IDH wild type. CDR3 variable motifs had higher proportions of hydrophobic residues in private than in public clonotypes, suggesting private CDR3 sequences have greater potential for tumor antigen recognition. Finally, we developed GTABdb, a web-based database designed for hosting, exploring, visualizing, and analyzing glioma immune repertoire. Our study will facilitate developing glioma immunotherapy.

Keywords: Health sciences; Immunology.

Graphical abstract

Figure 1

The characteristics of TRA and TRB repertoire across IDH wild type, IDHmut-noncodel, and IDHmut-codel (A) Graphical representation of the diversity of TRA and TRB repertoire from IDH wild type, IDHmut-noncodel, and IDHmut-codel. Each dot represents a unique V-gene and J-gene pair clonotypes, and the size of the dot is the relative frequency of that rearrangement in the entire population. (B–M) Quantification of the diversity of TRA and TRB repertoire across IDHwt, IDHmut-noncodel and IDHmut-codel including Shannon diversity index for TRA (B) and TRB (C) repertoire, Gini-Simpson diversity index for TRA (D) and TRB (E) repertoire, Chao1 richness index for TRA (F) and TRB (G), Ace index for TRA (H) and TRB (I), the number of clonotypes for TRA (J) and TRB (K), and Pielou evenness index for TRA (L) and TRB (M). IDHwt is IDH wild type gliomas. IDHmut-noncodel is gliomas with IDH mutation but not 1p/19q codeletion. IDHmut-codel is gliomas with IDH mutation and 1p/19q codeletion. Data are represented as median +/−IQR, where IQR is interquartile range. Significance was determined by Mann-Whitney U test (ns, p > 0.05; ∗, p ≤ 0.05; ∗∗, p ≤ 0.01; ∗∗∗, p ≤ 0.001; ∗∗∗∗, p ≤ 0.0001).

Figure 2

Differential usage of V genes in TRA and TRB repertoire of patients in IDHwt, IDHmut-noncodel and IDHmut-codel (A and B) Heatmap representing the frequency of V gene usage among unique TRA (A) and TRB (B) sequences from IDHwt, IDHmut-noncodel and IDHmut-codel. Significance was determined by Chi-square test for goodness of fit. (C and D) The distribution of the length of unique TRA-CDR3 (C) and TRB-CDR3 (D) in IDHwt. (E and F) The amino acid composition of unique TRA-CDR3 (E) and TRB-CDR3 (F) sequences in IDHwt. (G) The comparison of the length between private and public TRA-CDR3 sequences. Significance was determined by Mann-Whitney U test. (H) The comparison of proportion of hydrophobic amino acids in the three middle positions of public and private TRA-CDR3 and TRB-CDR3 sequences. P1, P2 and P3 are the positions. IDHwt is IDH wild type gliomas. IDHmut-noncodel is gliomas with IDH mutation but not 1p/19q codeletion. IDHmut-codel is gliomas with IDH mutation and 1p/19q codeletion. Data are represented as median +/−IQR. Significance was determined by binomial test and Benjamini–Hochberg correction (ns, p > 0.05; ∗, p ≤ 0.05; ∗∗, p ≤ 0.01; ∗∗∗, p ≤ 0.001; ∗∗∗∗, p ≤ 0.0001).

Figure 3

The characteristics of IGH, IGL and IGK repertoire across IDH wild type, IDHmut-noncodel, and IDHmut-codel (A) Graphical representation of the diversity of IGH, IGL and IGK repertoire from IDH wild type, IDHmut-noncodel, and IDHmut-codel. Each dot represents a unique V-gene and J-gene pair clonotypes, and the size of the dot is the relative frequency of that rearrangement in the entire population. (B—G) Quantification of the diversity of IGH, IGL and IGK repertoire across IDHwt, IDHmut-noncodel and IDHmut-codel including Shannon diversity index for IGH (B), IGL (D), and IGK (F), and the number of clonotypes for IGH (C), IGL (E), and IGK (G). IDHwt is IDH wild type gliomas. IDHmut-noncodel is gliomas with IDH mutation but not 1p/19q codeletion. IDHmut-codel is gliomas with IDH mutation and 1p/19q codeletion. Data are represented as median +/−IQR. Significance was determined by Mann-Whitney U test (ns, p > 0.05; ∗, p ≤ 0.05; ∗∗, p ≤ 0.01; ∗∗∗, p ≤ 0.001; ∗∗∗∗, p ≤ 0.0001).

Figure 4

Schematic overview of data collection, data processing and key functionality of GTABdb GTABdb collects TCR and BCR immune repertoire generated by TRUST4 from 913 RNA-sequencing data of gliomas in CGGA. A variety of methods for quantification of TCR and BCR immune repertoire were calculated for each patient including CDR3 sequence length, immune diversity, VDJ contribution and gene usage frequency. Model-View-Controller architecture was used in GTABdb. The Model component handles data from multiple sources in MySQL databases, calculating the quantitative metrics of immune repertoire, performing statistical analysis and visualization. The View component provides heterogeneous and synchronized views for presenting information and interacting with users, and the front-end template engine of Bootstrap plus HTML and JavaScript provide better visibility and usability of our functionality. The Controller component deals with the application logic, functioning as a mediator between the Model and View components.

Figure 5

Functionality at GTABdb showing information and immune repertoire characteristics of gliomas (A) Kaplan-Meier analysis for comparing overall survival among different selected groups of gliomas by ‘OS’ page. (B) The distribution of CDR3 sequences from TCR immune repertoire by ‘Length’ page. (C) The usage frequency of VDJ genes encoding BCR by ‘Gene’ page. (D) The diversity indexes for selected gliomas by ‘Diversity’ page. (E) The combined frequency of VDJ gene rearrangements of CDR3 by ‘Rearrangement’ page. (F) The ‘Search’ page for TCR and BCR CDR3 sequence. (G) The information associated with a CDR3 sequences by ‘Search’ page.