Ribosomal protein L32 enhances hepatocellular carcinoma progression

The underlying mechanisms of hepatocellular carcinoma (HCC) have not been fully investigated, and effective biomarkers for HCC are still needed to be explored. Therefore, our study sought to thoroughly examine the clinical significance and biological functions of the ribosomal protein L32 (RPL32) in HCC by coupling bioinformatic methods with experimental analysis.


| INTRODUCTION
Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality worldwide. 1 Despite a variety of effective therapeutic advances benefiting patients with HCC, the 5-year survival of these patients is still low. 2 HCC is thought to be induced by chronic liver disorders or hepatitis B infection. 3 It has been suggested that pivotal genetic aberrations (i.e., mutations in CTNNB1 and P53 genes) may be triggered by these inducers of HCC tumorigenesis. 4 Although targeted inhibitors for key genes, such as refametinib which blocks MEK activity, 5 have been utilized clinically to intervene in HCC, patient survival improvement is still greatly hindered by drug resistance and cancer recurrence. Therefore, uncovering the mechanisms underlying HCC will contribute significantly to the identification of novel therapeutic targets, based on which adjuvant therapeutic strategies can be further explored. Furthermore, identifying effective prognostic biomarkers is important for the clinical treatment of patients with HCC.
Ribosomal protein (RP) L32 (RPL32), which encodes the 60S ribosomal subunit, is a cytoplasmic protein. 6 RPs assemble ribosomes, and thus, play essential roles in protein translation. Although RPs function broadly in cellular processes, their expression patterns are unique in certain tissues, and some are dysregulated during pathological processes such as cancer. 7 In specific cancers, including pancreatic and bladder cancer, specific RPs have been demonstrated to be misexpressed and enhance or inhibit cancer progression. [8][9][10] In lung cancer, RPL32 was shown to interact with MDM2 protein (an E3 ligase for P53 protein), thereby enhancing the degradation of P53, resulting in lung cancer progression. 11 RPL32 expression was upregulated in breast cancer patient samples and cell lines. Functional investigation demonstrated that the loss of RPL32 leads to reduced breast cancer cell viability and migration. 12 However, the expression pattern of RPL32 in HCC patients and the biological functions of RPL32 during HCC progression have not been investigated.
In this study, we confirmed that RPL32 expression was elevated in patients with HCC and was strongly associated with patient malignancy. Moreover, higher RPL32 expression is associated with poor outcomes in patients with HCC. Importantly, RPL32 is an independent predictor of prognosis in HCC patients. In addition, we found that RPL32 expression was strongly correlated with promoter methylation and copy number variation. The correlation between RPL32 expression and infiltration of diverse immune cells was also systematically investigated. Finally, RPL32 depletion significantly attenuated the viability, migration, and invasion of HCC cells. Our study couples bioinformatics methods and experimental analyses to thoroughly study the clinical significance and biological functions of RPL32 in HCC.

| Western Blotting
Cells were lysed in freshly prepared RIPA buffer (Beyotime, P0013B) with 1 × complete protease inhibitor cocktail on ice, and the protein concentration was determined using a bicinchoninic acid protein assay kit (Thermo Fisher, 23,225). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) was performed to separate the proteins. The resolved proteins were transferred onto a 0.45-μm polyvinylidene difluoride (PVDF) membrane. A blocking buffer consisting of 5% non-fat dry milk in Tris-buffered saline with 0.1% Tween 20 (TBST) was applied to the membranes to inhibit non-specific binding. After 1 h incubation at room temperature, the blocked membranes were subjected to corresponding primary antibodies raised against RPL32 (Sabbiotech, 27,860-2) or βactin (Proteintech, Wuhan, China, 20,536-1-AP) diluted in TBST supplemented with 5% bovine serum albumin overnight at 4°C. The membranes were then washed with TBST three times before incubation with horseradish peroxidase (HRP)-conjugated secondary antibody raised against mouse IgG (Proteintech, SA00001-1) or rabbit IgG (Proteintech, SA00001-2) for 2 h at room temperature. Finally, the signal was detected with the aid of Clarity™ Western ECL Substrate (Thermo Fisher, 32,209) and ChemiDoc Imaging System following the manufacturer's instructions.

| Colony formation assay
Cells (1.5 × 10 3 ) were seeded in a 6-well plate and cultured for 14 days. The cells were washed with PBS, fixed in methanol for 15 min, and stained with crystal violet for 15 min. The colonies formed were then photographed and counted for statistical analysis.

| Cell cycle analysis
Cell cycle analysis was performed using flow cytometry. Briefly, cells were dissociated into single-cell suspensions and stained with propidium iodide (PI; Vazyme; A211-02). Flow cytometry was performed using a NovoCyte (ACEA), and the data were analyzed using NovoExpress 1.4.1.

| Cell apoptosis analysis
The Annexin V-FITC Kit (Beyotime Biotechnology) was used to measure the apoptosis of SMMC-7721 and SK-HEP-1 cells treated with siRPL32. After treatment and isolation, cells were stained with PI staining solution and Annexin V-FITC at 25°C for 15 min away from light according to the manufacturer's instructions. Subsequently, the apoptosis rate was analyzed using flow cytometry and associated software.

| Cell migration and invasion assays
5 × 10 5 SMMC 7721 cells were plated in the top chamber of an 8 μmpore 24-well transwell plate (Corning, 3422) in DMEM without serum. The bottom chamber was filled with DMEM containing 10% FBS. After 2 days of culture, the cells on the bottom of the membrane were fixed, stained, and photographed. For invasion analysis, the membrane was precoated with Matrigel (BD Biosciences).

| Statistical analyses
GraphPad Prism version 9.0 software was used for statistical analyses and all the quantitative data are shown as mean ± standard deviation. Statistical significances were calculated by an unpaired Student's t-test and p < 0.05 was considered as statistically significant (*0.01 < p < 0.05, **0.001 < p < 0.01, ***0.0001 < p < 0.001). ns, not significant.

| RPL32 expression is elevated in HCC patients
To evaluate the expression pattern of RPL32 in a pancancer manner, we performed bioinformatics analysis on TNMplot, TIMER, and GTEx (coupled with TCGA) databases, and found that RPL32 was highly expressed in a large proportion of cancers (Figure S1A-C), indicating RPL32 is an oncogene. We focused on HCC due to the lack of RPL32 investigation in HCC. Baseline demographic, clinicopathologic, and tumor characteristics of patients with HCC from TCGA-LIHC are summarized in Table 1. Surprisingly, a dramatic increase in RPL32 expression levels was found in HCC samples compared to normal tissue samples (through both unpaired and paired comparisons) in the TCGA-LIHC database ( Figure 1A,B). Importantly, the estimated receiver operator characteristic (ROC) curve revealed the diagnostic sensitivity and specificity of RPL32 in patients with HCC (area under the ROC curve [AUC] = 0.852; Figure 1C). In addition, data from ICGC-LIRI-JP, TNMplot, UALCAN (TCGA), and gene expression omnibus (accession numbers: GSE14520, GSE76427, GSE14811, GSE36376, GSE112790) showed that RPL32 expression levels were higher in HCC tissues than in normal tissues ( Figure 1D-F, Figure S1D-I). These findings strongly suggested that RPL32 may contribute to HCC tumorigenesis. Moreover, the correlations between RPL32 expression and clinical stages were explored using the TCGA-LIHC database, in which such information is accessible. Although RPL32 was not differentially expressed in patients classified into different T stages, N stages, M stages, pathologic stages, Child-Pugh grades, adjacent hepatic tissue inflammation levels, or vascular invasion levels ( Figure S2A-G), RPL32 mRNA was positively correlated with higher histologic grade and higher alpha fetoprotein (AFP) levels ( Figure S2H-I). These results suggest that RPL32 expression was enhanced in patients with HCC.

| High RPL32 expression is correlated with shorter survival in HCC patients
Next, we determined the correlation between RPL32 expression and HCC patient survival. Notably, HCC patients with higher RPL32 expression levels displayed worse prognosis in terms of overall survival, progression-free survival, and disease-specific survival in multiple databases (Figure 2A-F). In addition, Kaplan-Meier data from the UALCAN database also revealed that RPL32 expression was negatively correlated with patient overall survival and relapse-free interval ( Figure S3A-I). More specifically, we were interested in whether RPL32 expression was associated with patient survival in certain subtypes of HCC. Therefore, we assessed the survival of patients with HCC in various subgroups. Importantly, we observed that in multiple subgroups, including T stage (T1, T3), pathologic stage (I, III), histologic grade (G1, G2, G3, and G4), AFP ≤400, and adjacent hepatic tissue inflammation (none, mild, and severe), HCC patients with higher RPL32 expression exhibited lower survival probabilities T A B L E 1 Demographic, clinical, and histopathologic characteristics of patients with HCC from TCGA-LIHC (n = 371).  ( Figure S4A-I). In summary, RPL32 expression was significantly correlated with unfavorable outcomes in patients with HCC with different clinical characteristics, which confirms the general use of RPL32 expression as a prognostic biomarker.

| RPL32 expression is an independent parameter for HCC patient prognosis
Given the fact that clinical classification standards, such as T stage, M stage, and tumor status, are vital parameters for patient outcome prediction, we continued the clinical relevance analysis by determining whether RPL32 expression could serve as an independent factor for predicting patient malignancy. First, single-gene logistic regression analysis was performed to determine which clinical parameters were significantly correlated with the patient malignancy classification ( Figure 3A). Moreover, multivariate and univariate Cox analyses of these clinical factors or RPL32 expression levels demonstrated that RPL32 expression was a potential predictor of HCC patient prognosis ( Figure 3B-E). This conclusion was further validated in HCC cohorts from the GSE14520 and ICGC-LIRI-JP databases ( Figure 3F-I).
The baseline demographic, clinicopathologic, and tumor characteristics of patients with HCC from GSE14520 and ICGC-LIRI-JP are summarized in Tables 2 and 3. Furthermore, to better quantify the risk and predict the survival of patients with HCC, a nomogram combining RPL32 expression with other effective clinical parameters was established ( Figure S5A). Notably, positive correlations between the predicted and actual survival probabilities were observed in the diverse patient cohorts ( Figure S5B-D). Collectively, these results suggest that RPL32 may act as an independent and effective predictor of patient survival.

| Promoter methylation and copy number variation affect RPL32 mRNA levels in HCC patients
As RPL32 expression was shown to be dysregulated during HCC progression, we next analyzed whether promoter methylation and CNV of RPL32 expression were altered in patients with HCC. Analysis of data from LinkedOmics and TCGA-LIHC databases revealed negative correlations between RPL32 mRNA levels and promoter methylation ( Figure 4A, B). Interestingly, CNV was positively associated with RPL32 mRNA expression ( Figure 4C, D). Moreover, genetic alterations were frequently detected in HCC patients (26%; Figure 4E, F). In addition, we found an inverse correlation between RPL32 expression and methylation at four methylation sites, cg26404568, cg10950202, cg2011520, and cg5638426, in the promoter region ( Figure 4G). Taken together, these results reveal that RPL32 mRNA level variation attributes to promoter methylation and copy number alterations in patients with HCC.

| Correlation between RPL32 expression and immune cell infiltration
Cancer progression is related to the type of immune infiltrating cells 19 ; therefore, we determined the correlations between RPL32 expression and the infiltration of immune cells on the GSCA platform. 20 We determined that RPL32 levels were associated with immune cell infiltration in HCC, based on the combined scores ( Figure 5A). Patients with higher RPL32 expression exhibited higher tumor purity and lower ESTIMATE scores as well as stromal scores, with no difference in terms of the immune score ( Figure 5B-E). Furthermore, we found that RPL32 expression was positively associated with the infiltration of several immune cells, such as CD8 T cells, gamma delta T cells, effector memory T cells, and B cells ( Figure S6A-E). Nevertheless, inverse correlations were observed in central memory cells, iTreg cells, CD4 naïve T cells, and Th17 cells ( Figure S6A, F-I). We also quantified patient survival in subgroups with specific immune cell enrichment. in all the indicated subclasses of patients. In addition, RPL32 expression was negatively associated with resistance to several drugs such as 5-Fluorouracil, I-BET-762, and BHG712 ( Figure S9).

| Loss of RPL32 mitigates the survival, migration, and invasion of HCC cells
To further uncover the biological effects of RPL32 in HCC cells, we detected the mRNA and protein levels of RPL32 in different HCC cell lines and found that, except for Hep G2, PLC/PRF/5, and SNU-182 cell lines, the expression level of RPL32 in most HCC cell lines (HCC-LM3, Huh-7, MHCC97-H, SMMC-7721, and SK-HEP-1) was significantly higher than that in normal liver cells (L-02) ( Figure 6A, B). Because the expression level of RPL32 was the highest in SMMC-7721 and SK-HEP-1 cells ( Figure 6A, B), RPL32 was knocked down by two independent siRNAs in the HCC cell lines SMMC-7721 and SK-HEP-1. Successful knockdown of RPL32 at the mRNA and protein levels was detected using RT-qPCR and western blotting, respectively ( Figure 6C-E). Next, we evaluated the effect of RPL32 expression on cell survival. As determined by CCK-8 and colony formation analyses, HCC (SMMC-7721 and SK-HEP-1) cell survival and colony formation were greatly diminished upon RPL32 depletion ( Figure 6F-H). Importantly, flow cytometry assays revealed that cell cycle progression was hindered when RPL32 was silenced in HCC cells ( Figure 7A). However, decreased expression of RPL32 enhanced apoptosis ( Figure 7B). Furthermore, the absence of RPL32 resulted in attenuated HCC cell migration and invasion ( Figure 7C, D). Overall, these data demonstrated that RPL32 knockdown alleviates the survival, migration, and invasion of HCC cells.

| DISCUSSION
Increasing evidence shows that there are about 80 kinds of ribosomal proteins in eukaryotes, which not only function to form ribosomes and bind RNA but also have other functions, such as participating in tumor development and regulating tumor resistance to drugs. 11,21 Today, many ribosomal proteins have been found to be involved in regulating the occurrence and development of a variety of cancers, including lung, breast, and liver cancers. 11,12,22 In addition, RNA-binding protein (RBP), a key regulator of gene expression, is involved in the progression of many cancers, such as HCC. [22][23][24] A total of 526 RBPs were abnormally expressed in HCC compared to normal adjacent liver tissues and predicted poor prognosis. 25 A study showed that abnormal expression of RBPs in HCC enhanced tumor metastasis and accelerated tumor progression. 26 Currently, about 1542 human RBPs have been found to be involved in cancer development and progression. 27 However, the number of well-characterized RBPs in HCC remains unknown. RPL32 is a ribosomal component protein 28 and RNA-binding protein. 29 In this study, abnormal expression of RPL32 in HCC was found to be closely related to tumor progression.
In vitro experiments showed that RPL32 depletion had no effect on the proliferation of breast cancer cells 12 but inhibited the proliferation of lung cancer cells. 11 These findings suggest that RPL32 plays different roles in the proliferation of different cancer cells. In our study, the knockdown of RPL32 significantly reduced the proliferation of SMMC-7721 and SK-HEP-1 cells. Additionally, silencing RPL32 blocks the cell cycle in lung cancer cells. 11 Similarly, we found that RPL32 deficiency blocked the cell cycle progression of SMMC-7721 and SK-HEP-1 cells in the G 0 /G 1 phase. Moreover, in yeast, which are also eukaryotic cells, high expression of RPL32-2 promotes cell proliferation, while increased expression of RPL32-1 inhibits cell division. 21 This may be one of the mechanisms by which RPL32 plays different roles in the proliferation of different cancer cells.
In chronic lymphocytic leukemia (CLL), RPL32 expression can be used to predict SF3B1 expression, the major recurrent mutant gene in CLL. 30 The expression level of RPL32 in late androgen-independent cells was significantly higher than that in early androgen-sensitive cells, suggesting that RPL32 may be positively correlated with the progression of prostate cancer. 31 In breast cancer patients, RPL32 expression is higher in circulating tumor cell clusters with greater metastatic potential than in single circulating tumor cells. 32 In addition, silencing of RPL32 significantly reduces cell migration and invasion in breast cancer cells. 12 These results suggest that RPL32 is closely related to tumor metastasis. Similarly, we found that silencing RPL32 resulted in a significant decrease in the number of cells that migrated and invaded. Furthermore, the reduction of RPL32 in SMMC-7721 and SK-HEP-1 cells enhanced apoptosis. Although the increase in apoptosis and decrease in proliferation may also lead to a decrease in the number of migrating and invading cells to a certain extent, a prior study showed that the loss of RPL32 in breast cancer reduces the protein levels of matrix metalloproteinase (MMP)-2 and MMP-9, and significantly reduces cell migration and invasion, 12 suggesting that RPL32 has the potential to inhibit the migration and invasion of cancer cells by downregulating the expression of MMPs.
One study examined whether RPL32 was associated with cisplatin sensitivity in the lung cancer cell lines A549, NCI-H460, and H1299 and showed that knockout of RPL32 significantly increased cisplatin sensitivity in A549 and NCI-H460 cells. 11 In this study, we also analyzed the relationship between RPL32 and HCC drug sensitivity and found that RPL32 expression was negatively correlated with HCC sensitivity to many drugs, including BHG712, I-BET-762, and 5-fluorouracil.
Genetic variation is a major cause of gene dysregulation in cancer. 33 Promoter methylation at CpG sites leads to gene transcription silencing, which usually occurs in tumor suppressors and results in cancer progression. 34 In addition, CNV, such as depletion and gain of copy numbers due to amplification, also contributes to a certain F I G U R E 7 RPL32 silencing mitigates cell cycle progression, migration, and invasion and enhances apoptosis in HCC cells. (A). Flow cytometry analysis (left) and quantification (right) evaluating the cell cycle proportions of SMMC7721 and SK-HEP-1 cells transfected with two separate siRNAs against RPL32. (B) Flow cytometry analysis (left) and quantification (right) evaluating the apoptosis of SMMC7721 and SK-HEP-1 cells transfected with two separate siRNAs against RPL32. (C and D) Representative images and quantification results from transwell assays for assessing the migration (C) and invasion (D) of SMMC7721 and SK-HEP-1 cells after transfection with two siRNAs against RPL32. gene expression and is a frequent event in tumor-related genes. 35 Therefore, quantification of RPL32 promoter methylation and CNV in HCC patients was carried out, and the correlations between them and RPL32 mRNA expression were studied. As expected, RPL32 mRNA levels were negatively and positively associated with its promoter methylation and CNV, respectively.
In brief, in the present study, we analyzed HCC patient data from different databases and systematically revealed that the expression of RPL32 in HCC samples was significantly higher than that in normal tissue samples, which was associated with a lower survival probability in HCC patients. Additionally, RPL32 can be used as an independent predictor of HCC. Moreover, in vitro experiments revealed that RPL32-knockdown in SMMC-7721 and SK-HEP-1 HCC cells reduced cell survival, migration, and invasion. These results suggest that RPL32 can be used as a prognostic biomarker and promising therapeutic target for patients with HCC.