Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies

Objective

Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy.

Methods

We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC.

Results

We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines.

Conclusion

The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma

Liver cancer is the main reason of cancer deaths globally, with an unfavorable prognosis. DNA methylation is one of the epigenetic modifications and maintains the right adjustment of gene expression and steady gene silencing. We aim to explore the novel signatures for prognosis by using DNA methylation-driven genes. To acquire the DNA methylation-driven genes, we perform the difference analysis from the gene expression data and DNA methylation data in TCGA or GEO databases. And we obtain the 31 DNA methylation-driven genes. Subsequently, consensus clustering analysis was utilized to identify the molecular subtypes based on the 31 DNA methylation-driven genes. So, two molecular subtypes were identified to perform those analyses: Survival, immune cell infiltration, and tumor mutation. Results showed that two subtypes were clustered with distinct prognoses, tumor-infiltrating immune cell and tumor mutation burden. Furthermore, the 31 DNA methylation-driven genes were applied to perform the survival analysis to select the 14 survival-related genes. Immediately, a five methylation-driven genes risk model was built, and the patients were divided into high and low-risk groups. The model was established with TCGA as the training cohort and GSE14520 as the validation cohort. According to the risk model, we perform the systematical analysis, including survival, clinical feature, immune cell infiltration, somatic mutation status, underlying mechanisms, and drug sensitivity. Results showed that the high and low groups possessed statistical significance. In addition, the ROC curve was utilized to measure the accuracy of the risk model. AUCs at 1-year, 3-years, and 5-years were respectively 0.770, 0.698, 0.676 in training cohort and 0.717, 0.649, 0.621 in validation cohort. Nomogram was used to provide a better prediction for patients’ survival. Risk score increase the accuracy of survival prediction in HCC patients. In conclusion, this study developed a novel risk model of five methylation-driven genes based on the comprehensive bioinformatics analysis, which accurately predicts the survival of HCC patients and reflects the immune and mutation features of HCC. This study provides novel insights for immunotherapy of HCC patients and promotes medical progress.

Cyclin B2 overexpression promotes tumour growth by regulating jagged 1 in hepatocellular carcinoma

Background: Our previous study showed that Cyclin B2 (CCNB2) is closely related to the occurrence and progression of hepatocellular carcinoma (HCC).

Aim of the study: This study aimed to clarify the effect of CCNB2 gene silencing on tumorigenesis in nude mice and to detect the potential mechanism.

Methods: The effect of CCNB2 on HCC was tested in vivo. The downstream target genes of CCNB2 were predicted by proteomics and confirmed by western blot assay. The regulatory functions of CCNB2 in the proliferation and migration of HCC cells were determined through functional recovery experiments. The expression of the downstream target genes of CCNB2 was detected by immunohistochemistry.

Results: Knockdown of CCNB2 decreased tumour formation rate and tumour volume and weight and inhibited tumour proliferation. A total of 130 differentially expressed proteins were detected by proteomics, and Jagged 1 (JAG1) was predicted as the potential downstream target of CCNB2. Western blot assay revealed that CCNB2 and JAG1 expression was significantly correlated in HCC cells. The results of functional recovery experiments suggested that CCNB2 knockdown weakened the proliferation and migration ability of HCC cells, while JAG1 overexpression restored this ability of HCC cells that was weakened by CCNB2 knockdown. Immunohistochemistry showed that JAG1 expression was higher in HCC tissues than in paracancerous tissues and was related to tumour size and number and tumour thrombus formation.

Conclusions: The proliferation of HCC cells in vivo was inhibited by CCNB2 knockdown. CCNB2 may accelerate the proliferation and metastasis of HCC cells by increasing JAG1 expression.

Pre-mRNA processing factor 19 functions in DNA damage repair and radioresistance by modulating cyclin D1 in hepatocellular carcinoma

Pre-mRNA processing factor 19 (PRP19) is elevated in hepatocellular carcinoma (HCC); however, little is known about its function in DNA damage repair in HCC. In this study, analysis of The Cancer Genome Atlas data and our tumor models after ionizing radiation (IR) treatment indicated that increased expression of PRP19 was positively correlated with DNA damage repair. Gain of PRP19 expression induced by plasmids resulted in decreases in apoptosis and double-strand breaks (DSBs), and an increase in cell survival after IR. Loss of PRP19 expression induced by small interfering RNAs resulted in the accumulation of apoptosis and DSBs, and a decrease in cell survival. Mechanistically, the effect of PRP19 on DNA damage repair was mediated by the modulation of cyclin D1 expression in HCC. PRP19 controlled the translation of cyclin D1 by modulating eukaryotic initiation factor 4E. PRP19 affected the DNA damage repair ability of cyclin D1 by interacting with the WD40 domain. The combination of PRP19 and cyclin D1 was more valuable than each single marker for predicting the prognosis of patients. Taken together, the present results demonstrate that PRP19 promotes DNA damage repair by modulating cyclin D1 expression and function, thereby contributing to the radioresistance in HCC.

Upregulation of Nei-Like DNA Glycosylase 3 Predicts Poor Prognosis in Hepatocellular Carcinoma

Background

Accumulating evidence has suggested that Nei-like DNA glycosylase 3 (NEIL3) is associated with human tumors. However, there are few studies on the role of NEIL3 in hepatocellular carcinoma (HCC). The aim of this study was to investigate the expression profile of NEIL3 and its clinical relevance in HCC.

Materials and Methods

A total of 130 HCC and corresponding nontumor tissues were collected to perform immunohistochemistry (IHC). The clinical relevance and prognostic value of NEIL3 in HCC were analyzed by the chi-square test, Kaplan–Meier analysis, the Cox proportional hazard model, and nomogram.

Results

IHC showed that the NEIL3 protein level was remarkably upregulated in tumor tissues compared with nontumor tissues (fold change = 1.24; P < 0.001). High NEIL3 expression was significantly correlated with BCLC stage (P=0.004) and TNM stage (P=0.005). Overall survival (OS) and disease-free survival (DFS) rates in the high NEIL3 expression group were significantly worse than those in the low NEIL3 expression group (P=0.007 and P=0.004, respectively). Furthermore, subgroup analysis showed that high NEIL3 expression predicted worse OS and DFS for HCC patients with advanced TNM stage, poorly differentiated tumor, HBsAg positive, or cirrhosis. Multivariate analysis and the prognostic nomograms revealed that tumor NEIL3 level may serve as a promising prognostic indicator for OS and DFS in HCC patients.

Conclusion

Our findings suggested that NEIL3 might be a potential prognosis assessment marker and therapeutic target for HCC patients.

Sorafenib-Conjugated Zinc Phthalocyanine Based Nanocapsule for Trimodal Therapy in an Orthotopic Hepatocellular Carcinoma Xenograft Mouse Model

Sorafenib, a multitargeted kinase inhibitor, has been reported to elicit a limited therapeutic effect in hepatocellular carcinoma (HCC). Currently, phototherapy, including photodynamic therapy (PDT) and photothermal therapy (PTT), is emerging as a powerful modality for cancer therapy. However, few studies have been reported the effectiveness of the combination of sorafenib with PDT and PTT in HCC. Herein, we designed and synthesized bovine serum albumin (BSA)-coated zinc phthalocyanine (ZnPc) and sorafenib (SFB) nanoparticle (ZnPc/SFB@BSA). The obtained ZnPc/SFB@BSA was able to trigger PDT, PTT, and chemotherapy. After irradiation by a 730 nm light, ZnPc/SFB@BSA significantly suppressed HCC cell proliferation and metastasis while promoted cell apoptosis in vitro. Furthermore, intravenous injection of ZnPc/SFB@BSA led to dramatically reduced tumor growth in an orthotopic xenograft HCC model. More importantly, ZnPc/SFB@BSA presented low toxicity and adequate blood compatibility. Therefore, a combination of ZnPc with sorafenib via BSA-assembled nanoparticle can markedly suppress HCC growth, representing a promising strategy for HCC patients.