Fig. 7: Prediction of ICI response. | Communications Biology

Fig. 7: Prediction of ICI response.

From: The landscape of immune checkpoint-related long non-coding RNAs core regulatory circuitry reveals implications for immunoregulation and immunotherapy responses

Fig. 7

a ROC curves of three machine learning algorithms constructed using ICP-LncCRCTs to predict ICI responses. b Comparison of the ability of ICP-LncCRCT to predict ICI response with that of other clinical biomarkers. c UMAP dimension reduction and clustering of responders and nonresponders based on the expression of ICP-LncCRCTs in the SKCM dataset (Gide et al. [anti-PD-1]). d Impact of the TMB in combination with the ICP-LncCRCT on tumor predictive performance. e Kaplan–Meier curves of overall survival in SKCM patients between two groups divided by the expression levels of ICP-LncCRCTs in responders and nonresponders. The survival difference is calculated by log-rank test. Solid blue lines indicate the responding group, and solid yellow lines indicate the nonresponding group. Shaded areas indicate 95% confidence intervals. Asterisks on the curves indicate censoring points.

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