Mitoribosome Defect in Hepatocellular Carcinoma Promotes an Aggressive Phenotype with Suppressed Immune Reaction

Abstract

Mitochondrial ribosomes (mitoribosomes), the specialized translational machinery for mitochondrial genes, exclusively encode the subunits of the oxidative phosphorylation (OXPHOS) system. Although OXPHOS dysfunctions are associated with hepatic disorders including hepatocellular carcinoma (HCC), their underlying mechanisms remain poorly elucidated. In this study, we aimed to investigate the effects of mitoribosome defects on OXPHOS and HCC progression. By generating a gene signature from HCC transcriptome data, we developed a scoring system, i.e., mitoribosome defect score (MDS), which represents the degree of mitoribosomal defects in cancers. The MDS showed close associations with the clinical outcomes of patients with HCC and with gene functions such as oxidative phosphorylation, cell-cycle activation, and epithelial-mesenchymal transition. By analyzing immune profiles, we observed that mitoribosomal defects are also associated with immunosuppression and evasion. Taken together, our results provide new insights into the roles of mitoribosome defects in HCC progression.

Keywords: Cancer; Cancer Systems Biology; Immunology.

Graphical abstract

Figure 1

Mitoribosomal Defect Gene Signature Is a Good Indicator of HCC Prognosis (A) Schematic view of the analysis of MRPs to define three distinctive signatures (Up-MRPs, Dn-MRPs, and Other-MRPs). (B) Comparison of MRPs' expression between NT and PT. (C) Heatmap shows the expression of 82 MRPs in 371 PT and 50 NT samples from TCGA-LIHC cohort. (D) Comparison of maximum absolute deviation (MAD) among MRPs' expression between NT and PT. (E) (Top) Enrichment of three distinctive signatures (Up-MRPs, Dn-MRPs, and Other-MRPs) among PT. (Bottom) Heatmap shows the expression of variable MRPs (n = 38) among PT. (Right) Bar plot indicates the fold difference in the expression of variable MRPs (n = 38) between PT and NT. (F and G) Mitoribosome defect scores (MDSs) were calculated based on the three distinctive signatures (Up-MRPs, Dn-MRPs, and Other-MRPs) and total MRPs; MDS_up, MDS_dn, MDS_other, and MDS_all, respectively. Heatmap indicates the association of MDS_up and MDS_dn with Cancer Hallmark gene sets. According to the direction of the association between MDS_up and MDS_dn, gene sets were classified into the opposite, Only-MDS_up, Only-MDS_dn, or common, which were associated with MDS_up and MDS_dn in the opposite manner, MDS_up specifically, MDS_dn specifically, or in the same direction, respectively. A positive or negative association is shown in red or blue, respectively. Gene set with a non-significant association (p > 0.001) is shown in the blank (F). Forest plot indicates hazard ratios for MDSs based on the Cox-regressional univariate survival analysis (G). (H) Comparison of MDS between male (n = 250) and female (n = 121) samples from TCGA-LIHC cohort. Boxplots of MDSs of males and females are shown as first quartile, median, and third quartile (bottom box, middle line, and top box, respectively). Whiskers represent the minimum and maximum values. See also Figures S1 and S2; Table S2 and Table S3

Figure 2

Identification of Molecular Features Linked to Mitochondrial Defects Based on the MDS_dn, TCGA-LIHC samples were stratified into the subgroup with higher mitoribosome defect (H-MD) and one with lower mitoribosome defect (L-MD), and molecular features associated with H-MD or L-MD were compared. (A–C) GSEA results based on the OXPHOS (A), mitochondria respiratory chain complex assembly (B), and TGF-β signaling (C) were shown. Normalized enrichment scores (NES) and FDR for each gene set are noted. (D) Overall survival time of H-MD and L-MD was compared based on the Kaplan-Meier survival analysis. (E) Volcano plot indicates fold change (FC) and FDR based on the permutation t test between H-MD and L-MD groups. Differentially expressed genes (DEGs) were marked with red- or blue-colored points (FC > 1 or < −1 & FDR <0.005, respectively). (F) The expression of upregulated (n = 83) or downregulated (n = 161) DEGs in either H-MD or L-MD is shown. Samples are represented in columns, grouped by H-MD or L-MD. (G) Enrichment plots based on the 83 upregulated genes and 161 downregulated genes are shown in the left and right panels, respectively. NES and FDR for each gene set are noted. (H) Gene ontology (GO) analysis was performed based on the up and down DEGs. The -log₁₀(p value) is shown in red and blue bars for up- and downregulated genes, respectively. See also Figure S3; Table S4 and S5.

Figure 3

Mitoribosomal Defects Are Closely Associated with Immune Cell Response in HCC (A–D) preRanked GSEA was performed based on the HCC immune-related signature (A), cancer-associated ECM signature (B), activated stroma-associated signature (C), and normal stroma-associated signature (D). NES for each gene set is compared between H-MD and L-MD. (E and F) The proportion of immune cells with pro-cancer (Mast cells, Th2 cells, and T_regs) (E) and with anti-cancer properties (CD8+ T cells, NK-T cells, and Th1 cells) (F) are compared between H-MD and L-MD based on the xCell analysis output. (G) The average expression values of immune-modulatory cytokines in either H-MD or L-MD group are shown in colored scale. According to their immune response-related properties, cytokines were classified as inhibitory; stimulatory; MHC classes I, II, and non-classified (NC) and marked with green-, purple-, sky blue-, navy blue-, and gray-colored bars, respectively. A significant association with MDS_dn is shown as a colored scale, and non-significant association is shown as blank. (H) Permutation t test was performed between H-MD and L-MD among the immune-modulatory cytokines. The x axis indicates the expression fold change between H-MD and L-MD, and the y axis indicates the -log₁₀FDR for each cytokine. Cytokines significantly associated with MDS_dn are depicted in color coded in (G) according to their immune-related properties. (I) TGFB1 expression is compared between H-MD and L-MD. Boxplots are shown as first quartile, median, and third quartile (bottom box, middle line, and top box, respectively) with Welch two-sample t test p values. Whiskers represent the minimum and maximum values. See also Figure S4 and S5; Tables S6 and S7.

Figure 4

Mitoribosomal Defects Regulate HCC Immune Modulator Expression in HCC Cells For validation in the HCC cell lines, transcriptome data for HCC cell line was obtained from CCLE dataset. MDS_dn for each HCC cell line was calculated (Methods). (A) According to the increasing order of MDS_dn, MDS_dn of each HCC cell line is plotted. HCC cell lines representing H-MD or L-MD subgroup are marked in red or blue color, respectively. (B–E) Messenger RNA expression of TGFB1 (B), CSF1 (C), and SPP1 (D) are compared between H-MD-type and L-MD-type HCC cell lines of (A). The preRanked GSEA was performed based on the SPP1/CSF1/CSF1R/PDL1 signal axis, which is related to a sensitivity of anti-PD-1 immunotherapy in patients with HCC (E). The NES was compared between D- and ND-type cell lines (E). Boxplots are shown as first quartile, median, and third quartile (bottom box, middle line, and top box, respectively) with Welch two-sample t test p values. Whiskers represent the minimum and maximum values. (F) Protein levels of Dn-MRPs (MRPS31 and MRPL46) and mitochondrial-encoded genes (MT-CO2 and MT-ND6) were validated in representative H-MD-type (JHH4 and SNU475) and L-MD-type cell line (HepG2 and JHH5) by western blot. According to new nomenclature for mitoribosomal protein, we used mS31 and mL46 for proteins of MRPS31and MRPL46. (G) Sucrose gradient sedimentation analysis of MRPs from whole-cell lysates of the indicated cell lines. According to the new nomenclature for mitoribosomal protein, we used mS31, uS22, uS15, uL15, uL13, uL11, and mL46 for proteins of MRPS31, MRPS22, MRPS15, MRPL13, MRPL11, and MRPL46. (H) HCC cells were exposed to various doses of MG132 for 12 h and subjected to western blot analysis. DMSO was used as a vehicle (V). (I and J) Messenger RNA expression of TGFB1 (I) and CSF1 (J) in two H-MD-type (JHH4 and SNU475) and two L-MD-type cell lines (HepG2 and JHH5) were monitored by qRT-PCR. (K–P) L-MD-type cell lines (HepG2 and JHH5) were exposed to various doses of mitochondria-specific translation inhibitor, doxycycline (DOX) for 72 h. JHH5 cells showed higher sensitivity to DOX than HepG2. Western blot analysis for the expression level of mtDNA-encoded proteins, COX2 and ND6, and nuclear DNA-encoded SDHA protein was also examined to prove the inhibitor's specificity (K and N). Messenger RNA expression of TGFB1 (L and O) and CSF1 (M and P) were examined by qRT-PCR. Bar plots are represented as mean ± SEM. ^∗p < 0.05, ^∗∗p < 0.01, ^∗∗∗p < 0.005 (Student's t test, DOX treated group versus non-treated group). See also Table S8.

Figure 5

TBRS Induced by MRP Defects Mediates an Aggressive Phenotype in HCC (A and B) The association of mitoribosomal defects in HCC with TBRS was recapitulated in HCC cell lines. For TBRS in HCC cell line, signatures of epithelial cells (Epi_TBRS) were used. The MDS_dn shows a significant correlation with Epi_TBRS (A). NES based on Epi_TBRS was compared between H-MD- and L-MD-type HCC cell lines (B). (C) MDS_dn shows differential associations with HCC sub-classification signatures (Hoshida_S1, S2, and S3). (D and E) The association of mitoribosomal defect with cancer cell invasiveness was examined. preRanked GSEA was performed based on the invasion signature defined by Anastassiou et al. MDS_dn shows a significant association with cancer cell invasiveness (D). NES based on cancer cell invasiveness signature (Anastassiou et al.) was compared between H-MD and L-MD-type HCC cell lines (E). (F) Cell invasion activity was assayed using Matrigel-coated Transwell as described in the Transparent Methods section. Representative images are shown in the right panel. (G) Cell growth rates were monitored by counting the trypan blue-negative viable cells using the Countess automated cell counter. (H–K) TGF-β signaling in H-MD-type HCC cell lines (SNU475 and JHH4) was abolished by exposure to various concentrations of neutralizing antibodies for TGF-β (GTX14052, GeneTex Inc., Irvine, CA) for 24 h. Normal mouse IgG (sc-2025, Santa Cruz Biotechnology, Inc., Dallas, TX) was used as control. Phosphorylated SMAD2 (P-smad2) and total SMAD2 (T-smad2) levels were examined by western blot to validate the extent of TGF-β signaling inhibition (H and I). Then, the cell invasion assay was performed (J and K). Representative images for invaded cells are shown in the right panels. Boxplots are shown as first quartile, median, and third quartile (bottom box, middle line, and top box, respectively) with Welch two-sample t test p values. Whiskers represent the minimum and maximum values. Bar plots are represented as mean ± SEM. ^∗p<0.05, ^∗∗p<0.01, ^∗∗∗p<0.005 (Student’s t-test, DOX treated group vs. non-treated group). See also Figure S6; Table S9.