RBPs interact with other proteins or RNA to form ribonucleoprotein complexes, regulate RNA processing, translation, export, and localization, thereby maintaining the stability of the intracellular environment. Abnormal expression levels and changes in activity can lead to various diseases, including tumors [19–21]. Studies have shown that the post-transcription of RBPs are involved in the tumorigenesis and tumor development. However, their roles in tumors have not been completely revealed . Thus, further research on the differential expression and interaction of RBPs in various tumors may reveal new mechanism for tumor progression and new targets for anti-tumor therapy. HCC is one of the most common malignant tumors of the digestive tract and has a poor prognosis. Hence, the development of effective and early screening and prognostic markers has positive significance for early treatment, intervention, and prognostic judgement.
This study collected the gene expression and clinical information data of 374 HCC samples and 50 non-tumor tissue samples from the TCGA database and identified 82 differentially expressed RBPs, including 55 upregulated and 27 downregulated RBPs, followed by performing systematic analysis of the related biological pathways to construct PPI network of some RBPs. In addition, univariate and multivariate Cox regression analyses of the RBPs were performed to construct a risk model for predicting the prognosis of HCC based on five RBPs genes, followed by performing cohort verification based on a test cohort.
The results of enrichment analyses showed that in biological functions, various differentially expressed RBPs were greatly enriched in BP, CC, and MF terms. These differentially expressed RBPs were significantly enriched in mRNA surveillance pathway, miRNAs in cancer, RNA transport, and hepatitis C- and influenza A-related signaling pathways. RBPs interact with miRNAs, mRNAs, long ncRNAs, and cRNAs to form ribonucleoprotein complexes, thereby improving the stability of target genes, promoting gene expression, and playing a key role in the tumorigenesis and progression of many tumors [23–27]. For example, the abnormal expression of RBP-eIF3c promotes the proliferation of HCC, which is positively correlated with KRAS, vascular endothelial growth factor, and Hedgehog signaling pathways . A previous study showed that the effects of RBPs in HCC on biological functions are mainly focused on RNA splicing, translation, transcription termination, RNA localization and transport, RNA surveillance and degradation, RNA modification, ribosome, tRNA, among others . These findings are consistent with the results of this study.
In addition, this study constructed a PPI network of differentially expressed RBPs, including 64 key RBPs to also collect 6 hub proteins including GSPT2, DDX39A, ELAVL2, IGF2BP1, BOP1, and OASL. GSPT2 is highly expressed in HCC, promoting the progression of HCC by affecting cell cycles . DDX39A is upregulated in HCC tissue and cells. High DDX39A expression is positively correlated with advanced clinical stage and DDX39A activates the Wnt/β-catenin signaling pathway through β-catenin to promote HCC growth, invasion, and metastasis . ELAVL2 activates endogenous proto-oncogenes, causing the progression of a variety of tumors  and is involved in tumor resistance to chemotherapy. High ELAVL2 expression may be an independent risk factor for poor chemotherapy response in patients with esophageal squamous cell carcinoma . IGF2BP1 regulates the expression of some important mRNA targets required for tumor cell proliferation, growth, invasion, and chemotherapy resistance and is related to the overall survival rate and metastatic rate of various human cancers . BOP1 regulates the epithelial-mesenchymal transition, leading to the invasion and migration of HCC cells  and playing an important role in the metastasis of colorectal cancer, with mechanism being related to the regulation of Wnt/β-catenin signaling pathway . In addition to the core RBPs, a variety of other RBPs play an important role in tumorigenesis and tumor progression. For example, TERT is an important catalytic subunits of telomerase activation. It upregulates the transcription/activity in 80–90% of malignant tumors and is closely related to cell proliferation, tumor invasion, and transformation . TRIM71 promotes the proliferation of non-small cell lung cancer (NSCLC) cells by inhibiting the kappa B/nuclear factor kappa B pathway. Upregulated expression of TRIM71 is related to the tumor size, lymph node metastasis, tumor-node-metastasis staining, and poor prognosis of NSCLC . NR0B1 protein is detected in more than 50% of the human lung adenocarcinoma tissues and is highly expressed in the poorly differentiated cancer tissues in male . It promotes HCC proliferation, invasion, and metastasis by regulating the Wnt/β-catenin signaling pathway . By analyzing the key modules in the PPI network, this study showed that these modules were mainly related to defense response to virus, nuclear-transcribed mRNA catabolic process, and DNA modification.
Subsequently, univariate Cox regression analysis was used to obtain 22 prognosis-related RBPs in this study. The multivariate Cox regression analysis of the TCGA training cohort was performed to obtain a construction of 5-RBP (i.e., LIN28B, SMG5, PPARGC1A, LARP1B, and ANG) prognostic risk model. LIN28B is highly expressed in liver cells and is related to the level of alpha-fetoprotein, which promotes the tumorigenesis and progression of HCC. The overall survival rate of HCC patients with high LIN28B expression in significantly shortened, which is related to the multidrug resistance of HCC . SMG5 is highly expressed in malignant tumors, especially prostate cancer and it is a potential molecular marker for the early diagnosis of cancers . A survey of HCC in the Han population in eastern China has shown that PPARGC1A is associated with the risk of HCC . LARP1B belongs to one of the La ribonucleoprotein 1, translational Regulator (LARP1) genes. A study showed that high LARP1 protein levels in HCC tissue increased the risk of patient’s death by approximately 35% (compared to the low protein levels), and are related to tumor size, survival time, and the Child-Pugh score . However, the existing research mostly focuses on LARP1A, and only few studies in LARP1B are available. One report has showed that ANG-2 is highly expressed in HCC tissues. Related survival analysis has also shown that ANG-2 is a useful tumor marker for differential diagnosis of patients with HCC from those with chronic liver diseases or healthy subjects and prognosis prediction of HCC .
Further verification of the reliability and stability of the model showed that our model accurately predicted the prognosis of HCC patients. ROC curve analysis also indicated that the prognostic model had good diagnostic capabilities to identify the HCC patients with poor prognosis. Subsequently, survival analysis and ROC curve analysis in the TCGA test cohort showed that the results supported the above conclusion, and our model independently predict the prognosis of the patients with HCC. A nomogram based on this model was constructed to help us more intuitively predict the 1-, 3-, and 5-year prognosis of the HCC patients. The HPA database was used to verify the expression of 5 RBPs in immunohistochemistry. The results showed that the expression of LARP1B was positive in tumor tissues and negative in normal tissues. Consistent with the results of this study, LIN28B was negative expressed in the normal and tumor tissues. No relevant data on SMG5, PPARGC1A, and ANG were available, which may be related to the limitations of the data included in the database. In brief, our prognostic prediction model was relatively reliable and could be used to identify HCC patients with poor prognosis, which is conducive to the early intervention and treatment of the patients.
This study systematically explored the expression and prognostic value of differentially expressed RBPs in HCC through a series of bioinformatics analyses. This study also constructed a prognostic model based on 5-RBP encoding genes that better predicted the prognosis of the patients with HCC and helped physicians to make clinical decision. However, this study still has some limitations. First, the prognostic model constructed in this study was only based on the TCGA database. It needs to be further verified by a large cohort of the patients. Second, in vitro and in vivo experiments are needed to further reveal the mechanism of the selected RBPs’ action in HCC.