Fig. 1: TRTpred, a sensitive in silico predictor of tumor-reactive clonotypes.
a, Illustration of TRTpred design, benchmarking and applications. The final algorithm, MixTRTpred, combines TRTpred with a structural avidity predictor16 and TCRpcDist18, a TCR clustering algorithm. b, Alluvial plot showing the fractions of cells and clones annotated as tumor-reactive or non-tumor-reactive (orphan or antigen (Ag)-specific) within the input data (n = 10 patients with melanoma). c, Top, design of the 12 LR and 9 signature scoring models with their hyperparameters (Methods). Bottom, model selection framework estimating the generalization performance of the model through an LOPO NCV. d, Evaluation of the 12 LR (yellow circles) and 9 signature scoring (pink triangles) binary classifiers in the function of MCC and the AUC (Supplementary Table 2). The panel shows the distribution of the best model scores for tumor antigen-specific (red) and viral-specific (blue) clones. e, Volcano plot displaying the differential gene expression analysis comparing tumor-reactive and non-tumor-reactive cells. The 90 upregulated (red) and downregulated (blue) genes obtained by edgeR-QFL are shown (Supplementary Table 4). The P values are calculated using the two-sided quasi-likelihood F-test in the edgeR package and are corrected for multiple testing using the Benjamini–Hochberg procedure. f, Alluvial plots showing the fractions of cells and clones annotated as tumor-reactive or non-tumor-reactive (orphan or Ag-specific) within internal (top) and external (bottom, ref. 14) benchmarking data. g, ROC curve of TRTpred applied on the input data (black), and the internal (orange) and external (green, ref. 14) benchmarking data. h–k, ROC curves of TRTpred and four CD8+ TIL tumor-reactive predictive signatures (refs. 8,11,12,14) applied to the four datasets: ref. 14 (melanoma, n = 4) (h), ref. 12 (lung, n = 4) (i), ref. 8 (n = 1 melanoma, n = 2 breast and n = 12 GI) (j) and ref. 11 (GI, n = 5) (k). All AUCs are reported in Extended Data Fig. 3e. Pt, patient; TAA, tumor-associated antigen; UMI, unique molecular identifier; PCA, principal component analysis; Mel, melanoma; Pan, pan-cancer.
