Skip to main content
Fig. 3 | Biology Direct

Fig. 3

From: Integrated machine learning reveals the role of tryptophan metabolism in clear cell renal cell carcinoma and its association with patient prognosis

Fig. 3

Development and validation of a consensus tryptophan metabolism-related signature (TMRS). (A) The top 50 machine learning combinations by average concordance index (C-index) in the validation set, selected from 246 possible combinations. (B) The relative importance of variables within the TMRS prognostic model. (C) Partial dependence plots demonstrating the impact of specific variables on the TMRS prognostic model’s predictions. (D) The correlation between TMRS risk scores and tryptophan metabolism enrichment scores in TCGA and E-MTAB-1980 datasets. (E) Kaplan-Meier survival analyses revealing a significant correlation between TMRS risk scores and overall survival in patients with ccRCC, using the median value as the cut-off point, across the TCGA and E-MTAB-1980 datasets. (F) Time-dependent ROC curves assessing the TMRS prognostic model’s ability to predict 1, 3, and 5-year overall survival rates in the TCGA and E-MTAB-1980 datasets. SC, stepwise Cox regression; bwd, backward; GBM, generalized boosted regression modeling; fwd, forward; EN, elastic net; CB, CoxBoost; sPC, supervised principal components; Lasso, least absolute shrinkage and selection operator; RSF, random survival forest; SSVM, survival support vector machine; plsRcox, partial least squares regression for Cox; C-Index, concordance index; TMRS, tryptophan metabolism-related signature; AUC, area under the curve

Back to article page

Biology Direct

ISSN: 1745-6150

Contact us