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Journal of Big Data
Fig. 4 | Journal of Big Data

Fig. 4

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. 4

The risk-stratification gene signature was significantly correlated with malignant progression. (a) In the GSE164760 microarray dataset, all the four genes (COL1A2, COL4A2, UBD, and DTNA) were significantly upregulated in HCC samples derived from NASH when compared to healthy liver tissues and NASH samples. (b) In the combination of GTEx and TCGA-HCC RNA-seq database, all the four genes were also significantly upregulated in HCC samples compared to donated normal tissues and adjacent normal tissues. (c, f and i) Using UMAP dimensionality reduction, three scRNA-seq datasets including GSE125449, GSE146409 and GSE166635 were used to reveal the components of HCC tumor microenvironment (TME) and (d, g and j) the expression profile of COL1A2 in different cell types, respectively. (e, h and k) Violin plots showed that COL1A2 is specifically expressed in fibroblasts, almost not expressed in other cells within HCC TME. *** p < 0.001

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