Fig. 1: Profiling of genetic alteration and cell diversity in HCC.

a Schematic overview of the research. The numbers of patients and multiple experimental validation methods are provided. The lipidomics datasets (n = 34) comprise two subsets: tumor tissue lipidomics (n = 14) and blood plasma lipidomics (n = 20). b Genetic profiles and associated clinical features of all 157 HCC patients with WES data. The top panel shows mutation numbers followed by clinicopathological features. The middle panel exhibits significantly mutated genes calculated through MutSigCV. The bottom panel shows the CNV profiles of top chromosomal lesions with the most significant q values. Different alteration types and clinical features are signified with different color codes. Significance of these variables between AFP⁻ HCC and AFP⁺ HCC was calculated by chi-square test or Fisher’s exact test, which was provided in Supplementary Data 1. c The UMAP visualization of 47 cell types from scRNA-seq data. d Scatter plot showing positive correlation between serum AFP level and transcriptomic AFP expression in scRNA-seq (left panel) and bulk RNA-seq (right panel) data of FAH-SYSU cohort. Transcriptomic AFP expression in scRNA-seq data was calculated as the average expression across tumor cells per sample. R indicates the correlation coefficient calculated by Spearman correlation test. The number of dots indicates the number of patients. e Representative images of IHC staining in FFPE tissues (left panel) and protein expression of AFP in AFP⁻ HCC and AFP⁺ HCC (right panel). The number of dots indicates the number of patients. Scale bars, 50 μm. Data were shown as mean ± SD. **p < 0.01 by two-sided t-test. f Scatter plot showing positive correlation between proteinic AFP expression and available transcriptomic AFP expression. R indicates the correlation coefficient calculated by Spearman correlation test. The number of dots indicates the number of patients. Source data are provided as a Source Data file.