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Journal of Big Data
Fig. 6 | Journal of Big Data

Fig. 6

From: Integration of transcriptomic analysis and multiple machine learning approaches identifies NAFLD progression-specific hub genes to reveal distinct genomic patterns and actionable targets

Fig. 6

Distinct immune and stromal patterns were observed among different CTNNB1/COL1A2 groups. (a) A comprehensive heatmap showed that most of the immune and stromal cells are enriched in the CTNNB1-WT/COL1A2-high samples, regardless of the TMB level. (b) The xCell algorithm inferred the absolute infiltration of a total of 36 cell types involved in the TME, and the chord diagram showed that the infiltrating abundance is significantly higher in the CTNNB1-WT/COL1A2-high and CTNNB1-Mut/COL1A2-high samples than the other groups. (c - e) CAFs are significantly enriched in the CTNNB1-WT/COL1A2-high samples. (f - h) Different levels of representative immune checkpoints including CD274, PDCD1 and TIGIT indicate heterogenous tumor immunogenicity and distinct potential response to immunotherapy among different groups. (i) The ESTIMATE algorithm was applied to infer the immune infiltration and tumor purity for each sample, and the CTNNB1-WT/COL1A2-high and CTNNB1-Mut/COL1A2-high groups are labelled with high immune infiltration, and (j) a significantly negative correlation (r = -0.916, p < 0.001) was observed between the immune score and tumor purity across the four groups. Similarly, (k) the inflammatory response activity exhibits distinct distributions among the four groups, and (l) a significantly positive correlation (r = 0.839, p < 0.001) between immune score and inflammatory response was also observed across the four groups. *** p < 0.001

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