Integration of single-cell and bulk RNA-seq via machine learning to reveal ferroptosis- and lipid metabolism-driven immune landscape heterogeneity and predict immunotherapy response in colon cancer.

Similarly, in the IMvigor210 (anti–PD-L1), GSE35640 (MAGE-A3), Melanoma- GSE78220 (anti–PD-1), and Melanoma- GSE100797 (ACT) cohorts, the low-risk group also presented higher response rates to immunotherapy ( Figures 9G–J ); however, these differences did not reach statistical significance (P > 0.05). 3.9.

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Compared with Cluster 1, cluster 3 exhibited significantly higher activity scores for “ferroptosis” (adjusted P = 0.025, δ = −0.29), “lipid peroxidation” (adjusted P = 0.025, δ = −0.28), and “glycerolipid metabolism” (adjusted P = 0.028, δ = −0.26), along with an increasing trend for “fatty acid metabolism” (adjusted P = 0.07, δ = −0.22) ( Figure 3E ).

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