COMMD10 inhibits tumor progression and induces apoptosis by blocking NF‐κB signal and values up BCLC staging in predicting overall survival in hepatocellular carcinoma

Abstract Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide. Currently, there is limited knowledge of dysregulation of cellular proliferation and apoptosis that contribute to the malignant phenotype in HCC. Copper metabolism gene MURR1 domain 10 (COMMD10) is initially identified as a suppressor gene in the pathogenesis of HCC in our observations. Here we aimed to explore its function and prognostic value in the progression of HCC. Methods Functional experiments were performed to explore the role of COMMD10 in HCC. The molecular mechanisms of COMMD10 were determined by luciferase assay, immunofluorescence, and immunoprecipitation. The nomogram was based on a retrospective and multicenter study of 516 patients who were pathologically diagnosed with HCC from three Chinese hospitals. The predictive accuracy and discriminative ability of the nomogram were determined by a C‐index and calibration curve and were compared with COMMD10 and the Barcelona Clinic Liver Cancer (BCLC) staging system. The primary endpoint was overall survival (OS). Results COMMD10 expression was significantly lower in HCC than that in normal liver tissues. In vitro and in vivo experiments revealed that COMMD10 suppressed cell proliferation and induced apoptosis in HCC. Mechanistically, COMMD10 inhibits TNFα mediated ubiquitination of IκBα and p65 nuclear translocation through the combination of COMMD10‐N terminal to the Rel homology domain of p65, which inhibited NF‐κB activity and increased expression of cleaved caspase9/3 in HCC. Clinically, COMMD10 stratifies early‐stage HCC patients into two risk groups with significantly different OS. Additionally, the nomogram based on COMMD10 and BCLC stage yielded more accuracy than BCLC stage alone for predicting OS of HCC patients in three cohorts. Conclusions COMMD10 suppresses proliferation and promotes apoptosis by inhibiting NF‐κB signaling and values up BCLC staging in predicting OS, which provides evidence for the identification of potential therapeutic targets and the accurate prediction of prognosis for patients with HCC.

by a C-index and calibration curve and were compared with COMMD10 and the Barcelona Clinic Liver Cancer (BCLC) staging system. The primary endpoint was overall survival (OS). Results: COMMD10 expression was significantly lower in HCC than that in normal liver tissues. In vitro and in vivo experiments revealed that COMMD10 suppressed cell proliferation and induced apoptosis in HCC. Mechanistically, COMMD10 inhibits TNFα mediated ubiquitination of IκBα and p65 nuclear translocation through the combination of COMMD10-N terminal to the Rel homology domain of p65, which inhibited NF-κB activity and increased expression of cleaved caspase9/3 in HCC. Clinically, COMMD10 stratifies early-stage HCC patients into two risk groups with significantly different OS. Additionally, the nomogram based on COMMD10 and BCLC stage yielded more accuracy than BCLC stage alone for predicting OS of HCC patients in three cohorts. Conclusions: COMMD10 suppresses proliferation and promotes apoptosis by inhibiting NF-κB signaling and values up BCLC staging in predicting OS, which provides evidence for the identification of potential therapeutic targets and the accurate prediction of prognosis for patients with HCC.

K E Y W O R D S
Barcelona Clinic Liver Cancer (BCLC), copper metabolism MURR1 domain-containing 10 (COMMD10), hepatocellular carcinoma, proliferation and apoptosis

INTRODUCTION
Hepatocellular carcinoma (HCC) is the sixth most frequently diagnosed cancer and the third leading cause of cancer mortality worldwide, with an estimated 907,100 new cases and 821,700 deaths every year. 1 Although various adjuvant therapeutic treatment of HCC is innovatory, the 5-year survival rate of HCC is still less than 30%. 2 Therefore, there is a pressing requirement to define the underlying molecular mechanisms during HCC tumor growth to develop novel therapeutic strategies. We previously demonstrated formin-like 2 (FMNL2) as a tumor suppressor gene in HCC 3 and further identified seven interacting proteins of FMNL2 by yeast two-hybrid assay, 4 such as COMMD10, DNAJA1, and SHANK2. COMMD10 is initially identified as a tumor regulator in the pathogenesis of multiple human tumors in our observations. 5 Here we focus on COMMD10 to further refine the molecular mechanism of HCC development. The transcription factor nuclear factor kappa B (NF-κB), a central player critically involved in both inflammation and hepatocyte regeneration, 6 is hyperactivated in HCC. 7 HCC with high NF-κB activity has uncontrolled inflammation accompanied by aggressive pathologic features and has poor treatment outcomes, whereas blockade of the NF-κB pathway suppresses proliferation, demonstrating the essential role of NF-κB activity inhibition in preventing HCC progression. 8 COMMD (copper metabolism MURR1 domain-containing) protein family members (COMMD1-COMMD10) have been shown to negatively regulate NF-κB signaling in different ways, 9 but the mechanism of NF-κB in regulating HCC progression remains to be explored.
COMMD10, a member of the copper metabolism MURR1 domain-containing protein family, has been found to participate in the control of several biological processes. COMMD10 was found to facilitate clearance of staphylococcus by promoting phagolysosomal maturation and acidification in infected liver kupffer cells. 10 COMMD10 protects colon mucosa from systemic inflammation and inflammatory bowel disease by inhibiting the activation of Ly6C hi monocyte of inflammasome. 11 COMMD10 was also found to regulate the trafficking and ubiquitination of epithelial sodium channel by inhibition of Nedd4-2, leading to Na + transport alteration, which could be involved in the long-term management of salt homeostasis and blood pressure. 12 In addition, genome-wide analysis showed that COMMD10 was a novel biologically relevant associated with systemic inflammation before fenofibrate treatment, 13 and single nucleotide polymorphisms in the COMMD10 loci was associated with both asthma and chronic obstructive pulmonary disease. 14 High-throughput RNA sequencing identified COMMD10-AP3S1 as a novel fusion transcript in colorectal cancer, which may aid the development of improved diagnostics and treatment. 15 Moreover, our previous study elucidated the functions of COMMD10 in various human tumors based on expression profile and bioinformatics analysis, indicating its valuable role in the development and progression of tumor. 5 Additionally, we found that COMMD10 inhibited the invasiveness and metastasis of colorectal cancer. 4 To date, the role and mechanism of COMMD10 in HCC remain unknown. In this work, we investigated the role of COMMD10 in regulating cell proliferation and explored the underlying mechanisms and clinical values of COMMD10 in HCC.  recurrent HCC, tumors with mixed types on histopathologic analysis or of uncertain origin, perioperative mortality, and incomplete follow-up data. In addition, we used GSE14520 dataset of GEO database as an external validation cohort.
The optimal cut-off scores of COMMD10 were automatically selected based on Kaplan-Meier analysis and log-rank test by the X-tile software. 16 Firstly, we applied the X-tile program software to generate an optimal value of COMMD10 staining cut-off score to precisely classify patients according to clinical outcome in the training cohort. Then the value of COMMD10 staining cut-off score was used to examine the correlation between COMMD10 expression and patients' survival in validation cohorts.

Follow-up and outcome
Postoperative follow-up examinations were conducted at least every 3-6 months in the first 3 years and every 6-12 months thereafter. Follow-up protocol was conducted on the recommendation of the European society of oncology. 17 These include a detailed history, a complete physical examination, laboratory tests, and imaging examinations. The primary end point was overall survival (OS), which was calculated from the date of surgery to death. The data of patients without a documented OS event were censored at the last follow-up.

Statistical analysis
The continuous variables were transformed into categoric variables according to the routine cut-off points in clinical practice. Survival curves of patients were generated by the Kaplan-Meier method and the log-rank test. When a variable reached a p value less than 0.05 in the univariate analysis, it was selected for multivariate Cox regression analysis.
The nomogram was established according to the results of multivariate Cox regression analysis in the NF training cohort. The final predictive model was selected via a backward step-down selection process using the Akaike information criterion. 18 The discriminatory ability of the nomogram was quantified by the C-index and evaluated by comparing survival probability of nomogram-predicted and observed Kaplan-Meier estimates, for which bootstrapping with 1000 resamples was applied. Comparison between the nomogram and Barcelona Clinic Liver Cancer (BCLC) stage was performed using the rcorrp.cens function of the Hmisc package in R version (http://www. r-project.org/) and tested using the C-index. The nomogram was also assessed in terms of area under the receiver operating characteristic (ROC) curve. The total score of each patient in the validation cohort was calculated in the light of the established nomogram, and then the total score was used as a factor for Cox regression analysis. Ultimately, the C-index and calibration curve were obtained on the basis of regression analysis. The identification of risk factors was performed with SPSS software (IBM Corp., Armonk, USA). The rms package in R was used to establish the nomogram.
Data analysis was performed using the method of logrank test, Student's 2-tailed t-test, Fisher's exact test, and χ2 test. Data are reported as the mean ± SD, two-sided, and p values of less than 0.05 were considered statistically significant.

COMMD10 disturbed the growth of HCC in vitro and in vivo by regulating the NF-κB signaling pathway
To investigate the potential role of COMMD10 in the development of HCC, we firstly examined COMMD10 expression in HL-7702 normal hepatocytes and HCC cell lines (HepG2, Huh7, QGY-7701, QGY-7703, SMMC-7721) ( Figure S1A). The level of COMMD10 expression was significantly reduced in HCC cell lines compared to HL-7702 cells. Then COMMD10 was overexpressed or depleted in the following function experiments according to the endogenous expression level ( Figure S1B and S1C). Colony formation assay showed that overexpression of COMMD10 significantly inhibited while depletion of COMMD10 obviously increased the proliferation ability of HepG2 cells (both p < 0.001, Figure 1A). Consistently, cell counting kit-8 (CCK-8) assays of COMMD10-overexpressing SMMC-7721 and HepG2 cells revealed significantly decreased cell viability. Conversely, QGY-7703 and HepG2 cells with COMMD10 knockdown had strongly elevated cell viability compared to that in control cells (all p < 0.001, Figure 1B).
We previously have predicted the potential regulation of NF-κB by COMMD10 using bioinformatics analysis, 5 thus we tested whether COMMD10 expression would be involved in cell proliferation of HCC via NF-κB regulation. Luciferase activity assay showed that COMMD10 overexpression strongly inhibited tumor necrosis factor alpha (TNFα)-mediated NF-κB activation (p < 0.001, Figure 1C left). Conversely, NF-κB was activated in COMMD10depleted cells (p < 0.001, Figure 1C right). These data suggest that COMMD10 can impair NF-κB signaling, while silencing COMMD10 enhances NF-κB activity in HCC. We further tested the effect of IκBα-mut, a NF-κB pathway inhibitor, on COMMD10 depletion-induced HCC proliferation. As expected, ectopic expression of IκBα-mut significantly decreased COMMD10 depletioninduced cell viability (p < 0.001, Figure 1D). The capability of COMMD10 to suppress HCC progression was further examined using a xenograft tumor model. Tumors derived from HepG2/shCOMMD10 cells were larger and had higher Ki67 proliferation index compared to those in vector group (p < 0.001, Figure 1E). However, overexpression of IκBα-mut could significantly decreased size and Ki67 proliferation index of tumors derived from HepG2/shCOMMD10 cells (p < 0.001, Figure 1E). In addition, COMMD10 was significantly decreased in tumors derived from both HepG2/shCOMMD10 and HepG2/shCOMMD10/IκBα-mut cells compared to tumors derived from HepG2/vector cells (p < 0.001, Figure 1E). Collectively, the above findings verified that COMMD10 functions as a HCC suppressor through inhibiting NF-κB signaling pathway.

COMMD10 inhibits TNFα-mediated ubiquitination and degradation of IκBα and suppresses the NF-κB signaling pathway
To investigate the potential molecular mechanisms by which COMMD10 suppresses HCC proliferation through . Representative images of IHC staining of the proliferation marker Ki67 in the indicated group, and quantification of the positive nuclei for this marker (n = 6, right). COMMD10 content of tumor xenografts in each group was detected by Western blot (right). GAPDH was used as loading control. Each bar represents the mean ± SD; *p < 0.05; **p < 0.01; ***p < 0.001 regulating NF-κB activity, we examined the effect of COMMD10 overexpression or depletion on the expression of IκBα subunit. We found that COMMD10 deficiency affected neither the IκBα mRNA, the IκBα protein nor the phosphorylated IκBα (p-IκBα) protein in HepG2 cells without TNFα stimulation ( Figures S2A, S2B, and 2A). Similarly, we found that COMMD10 overexpression did not affect the expression level of IκBα and p-IκBα protein in SMMC7721 cells without TNFα stimulation ( Figure 2B). However, COMMD10 deficiency caused a faster decrease and lower expression of IκBα, and COMMD10 overexpression induced a higher expression of IκBα, which is independent on the IκBα phosphorylation (Figures 2A  and 2B).
Considering that the degradation of IκBα is mediated by phosphorylation and subsequent ubiquitinationproteasome degradation, we speculated that COMMD10 may regulate the ubiquitination of IκBα protein. To verify this, we detected the expression level of IκBα in HCC cells treated with proteasome inhibitor MG132 and found that IκBα protein was not affected by COMMD10 deficiency or overexpression compared to corresponding control cells ( Figures 2C and 2D). Indeed, we found that COMMD10 deficiency significantly increased the level of ubiquitinated IκBα protein ( Figure 2E). The above results indicate that COMMD10 inhibits TNFα-mediated ubiquitination and degradation of IκBα and suppresses the NF-κB signaling pathway.

COMMD10 interacts with RHD of p65 and suppresses the nuclear translocation of p65
The activation of the NF-κB pathway depends on the nuclear translocation of homodimers or heterodimers, the most abundant form of which is the p65:p50 heterodimer via the canonical pathway. 19 We further examined the effect of COMMD10 overexpression or depletion on expression levels of NF-κB subunits. Unexpectedly, none NF-κB subunit (i.e., p65, RelB, cRel, NF-κB1/p50, NF-κB2/p52) was changed ( Figure S3A), indicating that COMMD10 inhibits NF-κB signaling without altering the levels of subunits. The possibility that COMMD10 interacts with the NF-κB complex was evaluated in HepG2 cells using coimmunoprecipitation assays. COMMD10 interacted with p65, but not with other of NF-κB subunits ( Figure 3A). Immunofluorescence co-localization assay showed that COMMD10 and p65 mainly co-localized in the cytoplasm, and rarely in the nucleus ( Figure 3B). Interestingly, p65 was significantly reduced in the cytoplasm and highly increased in the nucleus after COMMD10 expression was silenced, whereas total p65 was unchanged ( Figures 3C   and 3D). These data indicate that p65 accumulation in the nucleolus is a consequence of deficiency of endogenous COMMD10. To further identify the potential combination sites of p65 in COMMD10, C-terminal (amino acids 1-132) and N-terminal (amino acids 132-202) truncation mutants of COMMD10 were constructed ( Figure 3E top). GSTpulldown assay showed that N-terminal of COMMD10 specifically combined with the wild type p65 ( Figure 3E bottom). Moreover, the binding domain of p65 with the N-terminal of COMMD10 was further investigated by constructing two truncation mutants of p65 ( Figure 3F top): one composed of the Rel homology domain (RHD, amino acids 1-305) that includes the function of DNA binding, dimerization, and nuclear localization, and the other is a fusion of a C-terminal region of p65 (amino acids 306-551) that includes the transcription activation domain. As expected, COMMD10 specifically bound to the wild type p65 and truncated mutant p65 (amino acids 1-305) (Figure 3F bottom). These data suggested that N-terminal of COMMD10 combines with RHD of p65 and suppresses NF-κB signaling pathway.
The role of COMMD10 in apoptosis was further explored in vitro. Flow cytometry showed that overexpression of COMMD10 significantly increased while depletion of COMMD10 significantly decreased apoptotic rates compared to control cells in HCC (p < 0.001, Figure 4A). Consistently, AO/EB double staining indicated that the amount of apoptotic cells in COMMD10 expressing group was obviously more than that in mock group. On the contrary, depletion of COMMD10 significantly decreased the number of apoptotic cells compared to vector group. However, overexpression of IκBα-mut could attenuate the inhibition effect of COMMD10 depletion on cell apoptosis in HepG2 cells (p < 0.001, Figure 4B, top). Table S1 summarizes the apoptosis rates in each group. Moreover, both TUNEL assay (p < 0.001, Figure 4B, middle) and the caspase-3/caspase-7 activation assay (p < 0.01, Figure 4B,

F I G U R E 4 COMMD10/NF-κB/Bcl-2/Bax/Caspase9/3 axis associates with apoptosis. (A) Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) staining of indicated cells treated with irradiation (6 Gy). (B)
A series of apoptosis assay induced by cisplatin (10ug/ml). Representative images of AOEB staining (upper), TUNEL assay (middle) and caspase3/7 activation assay (bottom) were showed from top to bottom, and the corresponding statistical analysis chart arranged from left to right. (C) Western blot of Bcl2/, Bax, cleaved-caspase3, cleaved-caspase9, and cleaved-PARP expression in the indicated cells exposed to cisplatin (100μg/ml). GAPDH was used as a loading control. (D) Analysis of mRNA level (left) and correlation (right) of COMMD10 with BAX, BCL2, CASP3, and CASP9 in 10 freshly collected human HCC samples. The data are shown from a single representative experiment of three repeats. Each bar represents the mean ± SD; *p < 0.05; **p < 0.01; ***p < 0.001 bottom) yielded consistent results with the AO/EB double staining.
To investigate the underlying mechanism involved in the regulation of apoptosis, we investigated intrinsic apoptosis-related proteins in SMMC-7721/COMMD10 and HepG2/siCOMMD10 cells treated with cisplatin, radiation or TNFα. The result of western blot revealed that COMMD10 overexpression significantly reduced Bcl-2 while enhanced Bax levels in HCC cells exposed to cisplatin. Some apoptosis proteins regulated by Bcl-2/Bax were also correspondingly changed, such as cleaved CASP9, cleaved CASP3, and cleaved PARP ( Figure 4C). Similarly, COMMD10 also increases the expression level of pro-apoptotic proteins while inhibits the expression of BCL-2 expression in irradiated or TNFα treated HCC cells (Figures S4A and S4B). Consistently, COMMD10 levels in freshly collected clinical HCC samples correlated positively with the mRNA levels of BAX (r = 0.702, p = 0.024), CASP3 (r = 0.887, p = 0.001), CASP9 (r = 0.662, p = 0.037), and negatively with BCL-2 (r = -0.668, p = 0.035) ( Figure 4D). We also found that extrinsic apoptosis pathway inducer cleaved CASP8 was elevated in COMMD10-overexpressing HCC cells, but was downregulated in COMMD10-silenced HCC cells. However, cleaved CASP8 expression was unchanged when NF-κB activity was inhibited by IκBα-mut, indicating that the apoptosis pathway involving CASP8 might not be a downstream target of the COMMD10/NF-κB pathway ( Figure S5A). The significant positive correlation between COMMD10 and CASP8 mRNA levels in the clinical samples provides further evidence that COMMD10 is functionally and clinically relevant to HCC cell apoptosis ( Figure S5B). Accumulating evidence showed that IAP protein family members (XIAP, cIAP1 [baculoviral IAP repeat-containing 2], cIAP2) downstream of NF-κB can suppress different apoptotic pathways by inhibiting distinct caspases. However, XIAP and cIAP1 expression was unchanged in the COMMD10-overexpressing and COMMD10-silenced HCC cells ( Figure S5A). Therefore, our findings validate that the COMMD10/NF-κB axis promotes intrinsic apoptosis by modulating Bcl-2/Bax/caspase-9/3 pathway in HCC.

The relationship between COMMD10 expression and patient clinic-pathologic features
To explore the correlations between COMMD10 and clinicpathologic features in HCC, the expression of COMMD10 was measured in HCC samples. Real-time PCR and western blots results showed that COMMD10 was significantly decreased at both mRNA (p = 0.027) and protein (p < 0.001) levels in the HCC tissues in comparison with that in normal liver tissues (Figures 5A, 5B, and S6). Moreover, IHC staining results showed that COMMD10 expression was remarkably reduced in tumor regions compared to that in healthy human liver ( Figure 5C).
To further assess the clinical values of COMMD10, we evaluated the relationship between COMMD10 expression and clinicpathologic parameters in HCC patients from multi-centered cohorts. COMMD10 expression was divided into low and high subgroup according to the optimal cut-off value automatically generated by X-tile software. A total of 48.1% (125 of 260), 44% (59 of 134), and 54.9% (67 of 122) tumors were scored as low COMMD10 expression in the Nanfang (NF) training, Nanfang (NF) internal and Zhujiang and Yuebei Hospital (ZY) external validation sets, respectively. Table 1 shows the clinical characteristics of the patients in the NF training cohort (n = 260), NF internal validation cohort (n = 134), and ZY external validation cohort (n = 122). Median follow-up was 34.0 months (IQR 11.8-54.3) for patients in the NF training cohort, 34.0 months (IQR 9.0-45.0) for those in the NF internal validation cohort, and 38.5 months (IQR 14.8-52.3) for those in the ZY external validation cohort. More than 80% of the patients were men, and most HCC was hepatitis B virus (HBV)-related in the three sets. Most patients were diagnosed as stage 0 or A, which were considered as early stage according to BCLC stage. In addition, high expression of COMMD10 negatively correlated with tumor size while positively correlated with tumor differentiation in training cohort. Moreover, COMMD10 staining density decreased gradually accompanied with disease progression from well to poor differentiation in HCC specimens (p = 0.005, Figure 5D).

COMMD10 is a predictor of stratification and prognosis in HCC
To investigate whether COMMD10 expression was an independent prognostic predictor of OS, Kaplan-Meier survival analysis was applied to compare OS of HCC patients according to COMMD10 expression. Patients with low COMMD10 expression had a significantly poorer OS than those with a high COMMD10 expression in the NF training, NF internal, and ZY external validation cohorts (p = 0.001, p < 0.001, and p = 0.005, respectively; Figures 6A-6C). The median of 1-, 2-, 3-, and 5-year OS in three cohorts is shown in Table S2. We further examined whether COMMD10 expression could stratify patients with early-stage (stage 0 and A) and late-stage (stage B and C) according to BCLC stage. When the analysis was limited to early-stage HCC, patients in three cohorts could be significantly stratified by COMMD10 expression (p = 0.001, p < 0.001, and p = 0.019 respectively; Figures 6D-6F). However, the COMMD10 expression was not predictive in latestage HCC in our three sets (p = 0.774, p = 0.154, and p = 0.486, respectively; Figures S7A-S7C). The above findings suggest that COMMD10 is a predictor of stratification and prognosis in HCC.

Extension of the BCLC staging prognostic model with COMMD10 expression for HCC patients
To investigate whether incorporation of the COMMD10 expression into the clinicpathologic variables of BCLC system would improve its predictive accuracy, we firstly performed univariate analysis and found various prognosis factors for OS in the NF training cohort, such as age, tumor size, albumin (ALB), tumor embolus, tumor differentiation, and COMMD10 (Table S3). Multivariate Cox regression analysis revealed that COMMD10, age, tumor size, tumor embolus, and ALB remained strong and independent prognostic factors for OS in the NF training cohort (Table S4). Then we generate a composite prognostic nomogram including COMMD10, age, tumor size, tumor embolus, and ALB level to predict 1-, 2-, and 3-year OS in the NF training cohort ( Figure 7A). Each factor in the nomogram was assigned a number of weighted points, and the total points of each patient were relevant to a specificity prediction of 1-, 2-, and 3-year OS. The bootstrapped calibration plots of 1-, 2-, and 3-year OS showed that nomogram prediction was consistent with the actual observation in three cohorts ( Figures 7B-7D, respectively).
Moreover, the predictive power for OS of HCC between nomogram, BCLC stage, and COMMD10 was compared. As shown in Table S5, the C-index of nomogram for OS prediction was higher than that of BCLC stage alone (p = 0.013, p < 0.001, p = 0.007, respectively) and COMMD10 alone (p < 0.001, p < 0.001, p = 0.216, respectively) in three cohorts. The time dependent ROC curve areas to compare the sensitivity and specificity of the nomogram showed better prognostic value of the OS compared to BCLC staging system alone and COMMD10 alone in three cohorts ( Figures 7E-7G, respectively). These results suggest that COMMD10 provides independent and

DISCUSSION
HCC is the fourth leading reason for cancer mortality worldwide. 21 To date, there is limited knowledge of dysregulation of cellular proliferation and apoptosis that contribute to the malignant phenotype in HCC. 22 COMMD10 is initially identified as a suppressor gene in the pathogenesis of HCC in our observations. 5 However, the underlying mechanisms and clinical values of COMMD10 in suppressing HCC progression remain unknown. COMMD10, a member of the Copper Metabolism MURR1 Domain-containing protein family, is evolutionary conserved in vertebrate 23 and involved in multiple biological processes, such as staphylococcus clearance, 10 inflammation inhibition, 11 and Na + transport. 12 The transcription factor NF-κB has been shown to be activated in HCC, 7 which displays aggressive pathologic features and has poor treatment outcomes. 24 In our study, we found that overexpressing COMMD10 dramatically reduced, whereas silencing COMMD10 promoted the NF-κB luciferase activity. The effects of COMMD10 silence on the proliferation in HCC cells in vitro and in vivo were reversed by NF-κB inhibitor (IκBα-mut), suggesting that COMMD10 suppresses proliferation via NF-κB pathway. Furthermore, we found that COMMD10 suppressed NF-κB signaling pathways by interacting and inhibiting p65 translocation to the nucleus in HCC. Unlike previous study which identified that COMMD10 could associate more broadly with NF-κB subunits in HEK293T cells, 23 we detect no binding affinity between COMMD10 and other endogenous NF-κB subunits except p65 in HepG2 cells, which may indicate that the mechanism by which COMMD10 regulates NF-κB is different across cell types. Although all 10 COMMD proteins interact with NF-κB, the COMMD proteins inhibit NF-κB in different way. 9 COMMD1 interacts with IκBα to inhibit IκBα proteasomal degradation in the cytosol and promote p65 nucleolar retention and proteasomal degradation. 25 Contrary to COMMD1, no combination was found between COMMD6 and IκBα. 9 Interestingly, others reported that the COMMD domain was required for the interaction between COMMD members and NF-κB, 26,27 our results show that N-terminal domain of COMMD10 suppresses p65 nuclear translocation through binding to the RHD of p65. Since the N-terminal region varies, this region might confer specific functions on COMMD10, which needs to be further investigated.
Previous studies have reported the role of NF-κB signaling in modulating apoptosis. 20 Some reports suggested a pro-apoptotic role of NF-κB in serum starvation of HEK293 cells, 28 fibroblasts from ataxia telangiectasia patients, 29 ultraviolet light, and daunorubicin/doxorubicin models. 30 Many other reports, however, indicated NF-κB has an anti-apoptotic effect when exposed to radiation, cytotoxic drug, and inflammatory cytokines. 31,32 In our study, we found COMMD10 overexpression enhanced radiation and cis-platinum-induced apoptosis by modulating Bcl-2/Bax/caspase-9/3 pathway in HCC cells. The intrinsic apoptosis pathway is principally regulated by the Bcl-2 family, which contains NF-κB binding sites. 33 Some of Bcl-2 family members (such as Bax, Bad, Bak, or Bid) promote apoptosis, while other members (such as Bcl-2, Bax-XL, Bcl-XS, and Bcl-XL) inhibit the role in the regulation of apoptosis. 34,35 The response of cells to various stimulation was determined by the proportion of proand anti-apoptotic Bcl-2 proteins. In our study, we found that overexpressing COMMD10 significantly reduced the expression of Bcl-2 (anti-apoptotic) and enhanced the Bax (pro-apoptotic) level. We also found that extrinsic apoptosis pathway inducer cleaved caspase-8 was elevated in COMMD10-overexpressing HCC cells, but was downregulated in COMMD10-silenced HCC cells. However, cleaved caspase-8 expression was unchanged when NF-κB activity was inhibited by IκBα-mut, indicating that the apoptosis pathway involving caspase8 might not be a downstream target of the COMMD10/NF-κB pathway. Therefore, our findings validate that COMMD10/NF-κB axis promoted intrinsic apoptosis by modulating Bcl-2/Bax/caspase-9/3 pathway.
Accurate prognostic assessment is of great clinical value in guiding the clinical management and selecting appropriate therapy. However, the current HCC patients determined by the BCLC stage, which is recognized as the best guideline for HCC management, show different prognosis although in the same disease stage. 36,37 This is most likely because this system does not take tumor heterogeneity into account. Despite that several nomograms have been established to improve the accuracy in predicting survival outcomes of HCC patients, [38][39][40] the predictive factors in these nomograms are confined to characteristics of patients and their tumors. However, biological heterogeneity remains the main factor causing the difference in prognosis. Some authors have proposed to refine the prognosis scoring by introducing tumor molecular biomarkers, such as mRNA-based genes, and alternative genomic sources (e.g., microRNAs or epigenomics). 41,42 Thus, novel molecular biomarkers for identifying tumor heterogeneity and accurately predicting clinical outcomes of HCC are urgently required.
In this study, we verified that differential expression of COMMD10 caused difference in HCC proliferation and survival rate, making it a potential molecular biomarker for distinguishing HCC heterogeneity. Then we describe the construction and validation of a composite prognostic nomogram combining COMMD10 and clinic-pathological variables of BCLC system to predict 1-, 2-, and 3-year OS for HCC patients from multi-centered cohorts, which yielded better predictive accuracy than the BCLC staging system. What is more, the external validation of GSE14520 used microarray-based data generated from 219 fresh HCC tissues also revealed that patients with low COMMD10 level showed shorter OS (p = 0.048, Figure S8), which further supports the prediction values of COMMD10 for HCC patients.
Additionally, we found that COMMD10 level categorized patients into high-risk and low-risk groups of earlystage (BCLC stage 0 and A) HCC patients who had significantly different OS. In HCC, the 5-year survival rate achieves up to 70% if patients are diagnosed at an early stage. 43 Despite being diagnosed with early stage, approximately 60% at 5 years of HCC patients eventually experienced recurrence. 44 These imply that defining molecular subgroups by COMMD10 may identify patients who are more likely to relapse and require more individual therapy, and ultimately improve their survival outcomes. However, the COMMD10 expression was difficult to quantify risk in late-stage HCC in our three sets, the most likely reason is the diversity of comorbidities and the insufficient sample size of advanced HCC patients.
There were some limitations in this study. First, our data were available in China, and more than 80% of HCC was HBV-related in the three cohorts. However, the distribution of pathological subtypes and clinical features might be different in other countries. COMMD10-based nomogram requires further validation in prospective studies and multicenter clinical trials. Second, since various causes of HCC, such as HBV infection, hepatitis C virus infection, alcoholic liver disease, non-alcoholic steatohepatitis, environmental and dietary carcinogens factors could contribute to the development and progression of HCC, the mechanism of COMMD10 in regulating different types of HCC might make a great difference. Further work is warranted to obtain precise mechanism of COMMD10 in the occurrence and progression of HCC.