Publications by authors named "Guifu Wang"

6 Publications

  • Page 1 of 1

Identification of CDC20 as an immune infiltration-correlated prognostic biomarker in hepatocellular carcinoma.

Invest New Drugs 2021 May 3. Epub 2021 May 3.

Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, 98 West Nantong Rd, 225009, Yangzhou, Jiangsu, China.

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. E3 ubiquitin-protein ligases play essential roles in HCC, such as regulating progression, migration, and metastasis. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell infiltration in HCC. Cell division cycle 20 (CDC20) was identified as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) using HCC data from the International Cancer Genome Consortium (ICGC) and the gene list of 919 E3 ubiquitin-protein ligases. DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune infiltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). CDC20 expression was significantly higher in HCC than in normal tissues (all P < 0.05). High CDC20 expression predicted a poor prognosis and might be an independent risk factor in HCC (P < 0.05). Additionally, CDC20 was correlated with the immune infiltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This study reveals the potential prognostic value of CDC20 in HCC and demonstrates that CDC20 may be an immune-associated therapeutic target in HCC because of its correlation with immune infiltration.
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http://dx.doi.org/10.1007/s10637-021-01126-1DOI Listing
May 2021

A prognostic model for hepatocellular carcinoma based on apoptosis-related genes.

World J Surg Oncol 2021 Mar 12;19(1):70. Epub 2021 Mar 12.

Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University, Yangzhou, 225009, Jiangsu, People's Republic of China.

Background: Dysregulation of the balance between proliferation and apoptosis is the basis for human hepatocarcinogenesis. In many malignant tumors, such as hepatocellular carcinoma (HCC), there is a correlation between apoptotic dysregulation and poor prognosis. However, the prognostic values of apoptosis-related genes (ARGs) in HCC have not been elucidated.

Methods: To screen for differentially expressed ARGs, the expression levels of 161 ARGs from The Cancer Genome Atlas (TCGA) database ( https://cancergenome.nih.gov/ ) were analyzed. Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to evaluate the underlying molecular mechanisms of differentially expressed ARGs in HCC. The prognostic values of ARGs were established using Cox regression, and subsequently, a prognostic risk model for scoring patients was developed. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to determine the prognostic value of the model.

Results: Compared with normal tissues, 43 highly upregulated and 8 downregulated ARGs in HCC tissues were screened. GO analysis results revealed that these 51 genes are indeed related to the apoptosis function. KEGG analysis revealed that these 51 genes were correlated with MAPK, P53, TNF, and PI3K-AKT signaling pathways, while Cox regression revealed that 5 ARGs (PPP2R5B, SQSTM1, TOP2A, BMF, and LGALS3) were associated with prognosis and were, therefore, obtained to develop the prognostic model. Based on the median risk scores, patients were categorized into high-risk and low-risk groups. Patients in the low-risk groups exhibited significantly elevated 2-year or 5-year survival probabilities (p < 0.0001). The risk model had a better clinical potency than the other clinical characteristics, with the area under the ROC curve (AUC = 0.741). The prognosis of HCC patients was established from a plotted nomogram.

Conclusion: Based on the differential expression of ARGs, we established a novel risk model for predicting HCC prognosis. This model can also be used to inform the individualized treatment of HCC patients.
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http://dx.doi.org/10.1186/s12957-021-02175-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955636PMC
March 2021

Identification of a Novel Metastasis-Related miRNAs-Based Signature for Predicting the Prognosis of Hepatocellular Carcinoma.

J Oncol 2021 31;2021:6629633. Epub 2021 Jan 31.

Department of Hepatobiliary and Pancreatic Surgery, Yangzhou University Clinical Medical College, Yangzhou, Jiangsu, China.

Hepatocellular carcinoma (HCC) is one of the most common internal malignancies worldwide and is associated with a poor prognosis. Abnormal expression of miRNAs is believed to play a role in the recurrent metastasis of HCC. However, limited studies on the role of miRNAs in HCC metastasis have been carried out. Therefore, this study is aimed at exploring the potential value of metastasis-related miRNAs (MRMs) in HCC. We retrieved MRMs were from the Human Cancer Metastasis Database. Differential miRNAs were identified for tumor samples of HCC patients and normal samples based on the TCGA database. Further, univariate and multivariate Cox regression analyses were used to screen MRMs known to be independent prognostic factors in HCC. These MRMs were then used to build a prognostic signature. All patients were classified into high-risk and low-risk groups based on the median of the signature scores. Moreover, GO and KEGG pathway enrichment analyses were performed to predict the function of these MRMs. Finally, a nomogram was constructed to predict the OS of patients at 1, 2, and 3 years. In our study, a total of seven prognostic MRMs (miR-140-3p, miR-9-5p, miR-942-5p, miR-324-3p, miR-29c-5p, miR-551a, and miR-149-5p) were identified and used for constructing the prognostic signature based on the training cohort. Patients in the low-risk HCC group showed better overall survival (OS) than those in the high-risk group. The results were validated using the validation cohort. In summary, the findings of this study provide evidence that MRMs-based prognostic signature is an independent biomarker in the prognosis of HCC patients.
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http://dx.doi.org/10.1155/2021/6629633DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870303PMC
January 2021

GIT1 overexpression promotes epithelial-mesenchymal transition and predicts poor prognosis in hepatocellular carcinoma.

Bioengineered 2021 12;12(1):30-43

Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University , Yangzhou, Jiangsu, P.R. China.

Globally, hepatocellular carcinoma (HCC) is one of the most common causes of cancer-associated mortalities. It has a high rate of metastasis and recurrence, which predict a poor prognosis. G-protein-coupled receptor (GPCR)-kinase interacting protein-1 (GIT1) is a multifunctional scaffold protein that mediates the progression of various tumors. Studies have correlated GIT1 with HCC, however, these correlations have not been fully elucidated. Therefore, we aimed at evaluating the expression of GIT1 in HCC tissues and cells, and to investigate its role and potential mechanisms in HCC progression. The expression levels of GIT1 in HCC tissues and other cancers was determined by using the Oncomine and TCGA databases. Functional analysis of GIT1 in HCC was evaluated through and experiments, whereby, HCC cells were transfected with synthetically overexpressed and short hairpin RNA (shRNA) lentivirus-mediated plasmids. Kaplan-Meier and Cox regression methods were used to establish the associations between GIT1 and clinical outcomes of 158 HCC patients. GIT1 was found to be elevated in HCC tissues where it promoted the invasion, migration, and proliferation of HCC cells. Moreover, the overexpression of GIT1 prompted epithelial-mesenchymal transition (EMT) by activating extracellular regulated kinase 1/2 (ERK1/2) pathway, which was shown to be reversed by SCH772984, a specific ERK1/2 inhibitor. GIT1 was also found to be associated with malignant features of HCC, leading to a poorer prognosis. In conclusion, GIT1 promotes HCC progression by inducing EMT and may reflect the course of HCC patients.
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http://dx.doi.org/10.1080/21655979.2020.1855914DOI Listing
December 2021

A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes.

Bioengineered 2020 12;11(1):1034-1046

Department of Hepatobiliary Surgery, Clinical Medical College, Yangzhou University , Yangzhou, P.R. China.

Several epithelial-mesenchymal transition (EMT)-associated genes (EAGs) have been confirmed to correlate with the prognosis of hepatocellular carcinoma (HCC) patients. Herein, we explored the value of EAGs in the prognosis of HCC relying on data from The Cancer Genome Atlas (TCGA) database. A total of 200 EMT-associated genes were downloaded from the Gene set enrichment analysis (GSEA) website. Moreover, 96 differentially expressed EAGs were identified. Using Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we forecasted the potential molecular mechanisms of EAGs. To identify prognostic EAGs, Cox regression was used in developing a prognostic risk model. Then, the Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the prognostic significance of the model. A total of 5 prognostic correlated EAGs (P3H1, SPP1, MMP1, LGALS1, and ITGB5) were screened via Cox regression, which provided the basis for developing a novel prognostic risk model. Based on the risk model, patients were subdivided into high-risk and low-risk groups. The overall survival of the low-risk group was better compared to the high-risk group (P < 0.00001). The ROC curve of the risk model showed a higher AUC (Area under Curve) (AUC = 0.723) compared to other clinical features (AUC ≤ 0.511). A nomogram based on this model was constructed to predict the 1-year, 2-year, and 3-year overall survival rates (OS) of patients. Conclusively, we developed a novel HCC prognostic risk model based on the expression of EAGs, which help advance the prognostic management of HCC patients. HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; EMT: epithelial-mesenchymal transition; EAGs: EMT-associated genes; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: protein-protein interaction; TF: transcription factor; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; FDR: false discovery rate; TNM: Tumor size/lymph nodes/distance metastasis.
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http://dx.doi.org/10.1080/21655979.2020.1822715DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8291854PMC
December 2020

Blocking HMGB1 signal pathway protects early radiation-induced lung injury.

Int J Clin Exp Pathol 2015 1;8(5):4815-22. Epub 2015 May 1.

Department of Pathology, Liaocheng People's Hospital Liaocheng, China.

It has been reported that HMGB1 participated in various types of lung injury. In this study, we explored whether blocking HMGB1 has a preventive effect on the early radiation-induced lung injury and investigate the mechanism. Mice model of radiation-induced lung injury were accomplished by a single dose irradiation (15 Gy) to the whole thorax. Irradiated mice were treated with HMGB1-neutralizing antibody intraperitoneally dosed 10 μg, 50 μg, 100 μg/mouse respectively and were sacrificed after one week post-irradiation. Lung tissue slices were stained by H&E, and alveolitis was quantified by Szapiel scoring system. The level of cytokines TNF-γ in bronchoalveolar lavage fluid was detected by ELISA method. And p65NF-κB, p50NF-κB protein expression in mice lung tissues was detected by Western blot analysis. The results showed that blocking HMGB1 inhibited the inflammatory response, and thereby decreased the degree of alveolitis of irradiated lung tissue. In addition, HMGB1 antagonist can restrain the expression of type Th2 or Th17 derived inflammatory cytokines TNF-α, IL-6 and IL-17A, promote the expression of Th1 type cytokines INF-γ, and inhibit p65 NF-κB but promote p50 NF-κB activation, which promoted the resolution of the radiation-induced inflammatory response. In conclusion, blocking HMGB1 can reduce the degree of early radiation-induced lung injury, and its mechanism may be related to the promotion of p50NF-κB activation and its downstream molecules expression. Inhibiting HMGB1 may be a new target to deal with early radiation-induced lung injury.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503044PMC
May 2016
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