Additional file 1 of Integrated proteogenomic characterization reveals an imbalanced hepatocellular carcinoma microenvironment after incomplete radiofrequency ablation
journal contributionposted on 2023-05-26, 03:25 authored by Zheng-Rong Shi, Yu-Xin Duan, Fang Cui, Zhong-Jun Wu, Mao-Ping Li, Pei-Pei Song, Qi-Ling Peng, Wen-Tao Ye, Kun-Li Yin, Mei-Qing Kang, Yan-Xi Yu, Jian Yang, Wei Tang, Rui Liao
Additional file 1 Figure S1. Sequence data qualitycontrol before transcriptomics analysis. A-B: Representativeimagines showing error rate distribution along sequencedata (reads). C-D: Representative pie graphs showing the classification of raw readsfilter. E-F: Representative imagines showing bases content alongsequence reads. Figure S2. Genomemapping, gene expression distribution and pearson correlation between samples.A-B: Representative pie graphs showing thepercentage of genome regions based on the reads mapping. C: box plotdisplaying the distribution of gene expression levels in different samplesafter calculating the expression value (FPKM) of all genes in each sample. D:Pearson correlation between samples according to FPKMvalue. Figure S3. Thealternative splicing events. Analysis of rMATS software showingdifferential alternative 3′ splice site (A3SS) event of UBXN11 (A) and skippedexon (SE) events of AHI1 (B), ENTR1 (C), IQCB1 (D), KIAA1191 (E), LCN12 (F),LRR1 (G) and ZNF26 (H) in different samples. RFA test representsthe group with iRFA treated patient; RFA Ctrl represents the group without iRFAtreated patient. Figure S4. The frequency ofinsertion-deletion (INDEL) and single nucleotide polymorphisms (SNP)alterations in various genes. A-B: Impact andregion of INDEL. C-E: Impact (C)function (D) and region (E) of SNP. Figure S5. Circos plots of fusion gene events in eachsample. Figure S6. Protein qualitative and sample pepeatabilitydetection. A: Histogram 0f protein identification results showing2014926 total spectrums, 879371 matched spectrums, 76509 peptides, 72533 uniquepeptides and 7380 protein groups were identified. B: Boxplot showing therelative standard deviation of protein quantification values between two groupsof samples. C: Pearson’s Correlation Coefficient between two samples. Figure S7. PPI network analysis ofPRTN3 and the association with immune cells. A: PPI network analysis of PRTN3 based on the STRINGdatabase. B-C: PPI network analyses of PRTN3 in HCC (B) and adjacent tumortissues (C). D: The relationship between PRTN3 and immune infiltration in HCCusing the TIMER online tool based on TCGA data. E: The links between genomicaberrations of PRTN3 and the abundance of TIICs by the "SCAN" modulein the TIMER database. Figure S8. The single-cell sequencing of PRTN3+ cells in livertissues from The Human Protein Atlas database. Figure S9. Expression of PRTN3detected by qRT-PCR in HCC cell lines (A, Hep 3B and SMMC-7721) and Kupffercells (B). Figure S10. Migrative and invasive abilities analysis and the relative proteinexpression levels of western blotting. A:Migrative abilities analysis of HCC cell after cultured with KC-CM transfected for PR3OE or PR3KD. B-C: Invasive and migrative abilities of HCCcell after cultured with KC-CM transfected for PR3OE or PR3KD according to transwell assay analysis. D-L: The relative protein expression levels of CXCL5(D), MPO (E), MMP9 (F), IL-6 (G), p-AKT (H), p-ERK1 (I), p-ERK2 (J), p-P38 (K)and PI3K (L), respectively.All data are presented as the means ± SD of three independent experiments. *p< 0.01. Table S1. 389 dysregulated genes detected detected in two groups. Table S2. 20 dysregulated proteinsdetected in two groups. Table S3.Proteins with significantly differential expression in subcellular location. Table S4. Transcription factorassociated proteins. Table S5.Integrated data of transcriptome and proteome for GO and KEGG pathwayenrichment analysis.