Fig. 7: Implications of IRLS for ICI treatment. | Nature Communications

Fig. 7: Implications of IRLS for ICI treatment.

From: Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer

Fig. 7

A The relationship between IRLS and immune cell infiltrations in TCGA-CRC. B Chorograms were derived based on Pearson r value between IRLS and immune cell infiltrations in TCGA-CRC and Meta-GEO. C, D Scatterplots between IRLS and CD8A expression with microsatellite state were shown in TCGA-CRC (n = 584, P = 5.20e−15) (C) and in-house cohort (n = 232, P = 4.45e−32) (D). Statistic test: Pearson’s correlation coefficient, two-sided unpaired t test. Data are presented as mean ± 95% confidence interval [CI]. E Representative IHC staining images of CD8A between two risk groups (n = 104). Scale bars = 50 μm. F Analysis of IHC scores between two risk groups according to CD8A staining results (n = 104, P = 0.009). Statistic test: two-sided unpaired t test. Data are presented as mean ± 95% CI. G, H. Scatterplots between IRLS and PD-L1 expression with microsatellite state were shown in TCGA-CRC (n = 584, P = 1.30e−30) (G) and in-house cohort (n = 232, P = 1.37e−19) (H). Statistic test: Pearson’s correlation coefficient, two-sided unpaired t test. Data are presented as mean ± 95% CI. I Representative IHC staining images of PD-L1 between two risk groups (n = 104). Scale bars = 50 μm. J Analysis of IHC scores between two risk groups according to PD-L1 staining results (n = 104, P = 1.34e−5). Statistic test: two-sided unpaired t test. Data are presented as mean ± 95% CI. K–M ROC curves of IRLS to predict the dMMR/MSI-H phenotype in TCGA-CRC (K), Meta-GEO (L), and in-house cohort (M). N ROC curves of IRLS, PD-L1, and CD8A to predict the benefits of pembrolizumab. Statistic test: two-sided unpaired DeLong test. **P < 0.01; ***P < 0.001; ****P < 0.0001.

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