Xiangkun Wang

Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

Background Molecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy. Methods An RNA sequencing dataset of PDAC was obtained from The Cancer Genome Atlas. Survival analysis and weighted gene co-expression network analysis were used to investigate the prognostic markers of early-stage PDAC after pancreaticoduodenectomy. Results Using whole genome expression level screening, we identified 1,238 markers that were related to the prognosis of PDAC after pancreaticoduodenectomy, and identified 9 hub genes (ARHGAP30, HCLS1, CD96, FAM78A, ARHGAP15, SLA2, CD247, GVINP1, and IL16) using the weighted gene co-expression network analysis approach. We also constructed a signature comprising the 9 hub genes and weighted by the regression coefficient derived from a multivariate Cox proportional hazards regression model to divide patients into a high-risk group, with increased risk of death, and a low-risk group, with significantly improved overall survival (adjusted P=0.026, adjusted HR =0.513, 95% CI =0.285–0.924). The prognostic signature of the 9 genes demonstrated good performance for predicting 1-year overall survival (area under the respective receiver operating characteristic curves =0.641). Conclusion Our results have provided a new prospect for prognostic biomarkers of PDAC after pancreaticoduodenectomy, and may have a value in clinical application.

Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

Background The aim of the present study was to identify potential prognostic microRNA (miRNA) biomarkers for hepatocellular carcinoma (HCC) prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA). Materials and methods A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs), and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394), and time-dependent receiver–operating characteristic (ROC) analysis showed an area under the curve (AUC) of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS) prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration regulation, pathways in cancer, and the cyclic adenosine monophosphate (cAMP) signaling pathway. Conclusion Our study indicates that the novel miRNA expression signature may be a potential prognostic biomarker for HCC patients.

NLRC and NLRX gene family mRNA expression and prognostic value in hepatocellular carcinoma

Nucleotide‐binding oligomerization domain (NOD)‐like receptor (NLR)C and NLRX family proteins play a key role in the innate immune response. The relationship between these proteins and hepatocellular carcinoma (HCC) remains unclear. This study investigated the prognostic significance of NLRC and NLRX family protein levels in HCC patients. Data from 360 HCC patients in The Cancer Genome Atlas database and 231 patients in the Gene Expression Omnibus database were analyzed. Kaplan–Meier analysis and a Cox regression model were used to determine median survival time (MST) and overall and recurrence‐free survival by calculating the hazard ratio (HR) and 95% confidence interval (CI). High NOD2 and low NLRX1 expression in tumor tissue was associated with short MST (P = 0.012 and 0.014, respectively). A joint‐effects analysis of NOD2 and NLRX1 combined revealed that groups III and IV had reduced risk of death from HCC as compared to group I (adjusted P = 0.001, adjusted HR = 0.31, 95% CI = 0.16–0.61 and adjusted P = 0.043, adjusted HR = 0.63, 95%CI = 0.41–0.99, respectively). NOD2 and NLRX1 expression levels are potential prognostic markers in HCC following hepatectomy.

Distinct Diagnostic and Prognostic Values of Minichromosome Maintenance Gene Expression in Patients with Hepatocellular Carcinoma

Background: The aim of the present study was to identify diagnostic and prognostic values of minichromosome maintenance (MCM) gene expression in patients with hepatocellular carcinoma (HCC). Methods: The biological function of the MCM genes were investigated by bioinformatics analysis. The diagnostic and prognostic values of the MCM genes were investigated by using the data of HCC patients from the GSE14520 and The Cancer Genome Atlas (TCGA) databases. Results: Bioinformatics analysis of the MCM genes substantiated that MCM2-7 genes were significantly enriched in DNA replication and cell cycle, and co-expressed with each other. These genes also co-expressed in HCC tumor tissue in both the GSE14520 and TCGA cohort. We also observed that the expression of the MCM2-7 genes was increased in tumor tissue, and diagnostic receiver operating characteristic analysis of MCM2-7 indicated that these genes could serve as sensitive diagnostic markers in HCC. Survival analysis in the GSE14520 cohort suggested that expression of MCM2, MCM4, MCM5, and MCM6 were significantly associated with hepatitis B virus-related HCC overall survival (OS). However, none of the MCM genes were associated with recurrence-free survival in the GSE14520 cohort. The validation cohort of TCGA suggested that the expression of MCM2, MCM6, and MCM7 were significantly correlated with HCC OS. Conclusion: Our study indicated that MCM2-7 genes may be potential diagnostic biomarkers in patients with HCC. Among them, MCM2 and MCM6 may serve as potential prognostic biomarkers for HCC.

Identification of Potential Prognostic Long Non-Coding RNA Biomarkers for Predicting Survival in Patients with Hepatocellular Carcinoma

Background/Aims: The aim of the current study was to identify potential prognostic long non-coding RNA (lncRNA) biomarkers for predicting survival in patients with hepatocellular carcinoma (HCC) using The Cancer Genome Atlas (TCGA) dataset and bioinformatics analysis. Methods: RNA sequencing and clinical data of HCC patients from TCGA were used for prognostic association assessment by univariate Cox analysis. A prognostic signature was built using stepwise multivariable Cox analysis, and a comprehensive analysis was performed to evaluate its prognostic value. The prognostic signature was further evaluated by functional assessment and bioinformatics analysis. Results: Thirteen differentially expressed lncRNAs (DELs) were identified and used to construct a single prognostic signature. Patients with high risk scores showed a significantly increased risk of death (adjusted P < 0.0001, adjusted hazard ratio = 3.522, 95% confidence interval = 2.307–5.376). In the time-dependent receiver operating characteristic analysis, the prognostic signature performed well for HCC survival prediction with an area under curve of 0.809, 0.782 and 0.79 for 1-, 3- and 5-year survival, respectively. Comprehensive survival analysis of the 13-DEL prognostic signature suggested that it serves as an independent factor in HCC, showing a better performance for prognosis prediction than traditional clinical indicators. Functional assessment and bioinformatics analysis suggested that the prognostic signature was associated with the cell cycle and peroxisome proliferator-activated receptor signaling pathway. Conclusions: The novel lncRNA expression signature identified in the present study may be a potential biomarker for predicting the prognosis of HCC patients.

The prognostic value of differentially expressed CYP3A subfamily members for hepatocellular carcinoma

Objective The activities of four cytochrome P3A (CYP3A) subfamily members (CYP3A4, CYP3A5, CYP3A7, and CYP3A43) are well documented in drug metabolism. However, the association between CYP3A subfamily members and hepatocellular carcinoma (HCC) remains unclear. This study investigated the prognostic value of CYP3A subfamily mRNA expression levels with HCC prognosis. Materials and methods Data from a total of 360 HCC patients were retrieved from The Cancer Genome Atlas database, and data from 231 HCC patients were retrieved from the Gene Expression Omnibus database. Kaplan–Meier analysis and Cox regression models were utilized to determine median survival, overall survival, and recurrence-free survival. Hazard ratios and 95% CI were calculated. Results Low expression of CYP3A4, CYP3A5, and CYP3A43 in the tumor tissue was associated with short median survival (crude p=0.004, 0.001, and 0.001; adjusted p=0.022, 0.005, and 0.013, respectively). Joint-effects combination analysis of CYP3A4, CYP3A5/CYP3A4, CYP3A43/CYP3A5, and CYP3A43 revealed that high expression groups of two genes (group C, group c, group 3) were associated with a reduced risk of death, as compared to low expression of two genes (group A, group a, group 1), and the adjusted p values were 0.001, 0.004, and 0.001, respectively. Joint-effects analysis of CYP3A4, CYP3A5, and CYP3A43 showed that groups III and IV had a reduced risk of death, as compared to group I (adjusted p=0.024 and 0.002, respectively). Conclusion CYP3A4, CYP3A5, and CYP3A43 mRNA expression levels are potential prognostic markers of HCC.

Genetic variants of ALDH2 -rs671 and CYP2E1 -rs2031920 contributed to risk of hepatocellular carcinoma susceptibility in a Chinese population

Objective Acetaldehyde dehydrogenase 2 (ALDH2) and cytochrome P450 2E1 (CYP2E1) have been associated with hepatocellular carcinoma (HCC) susceptibility and prognosis. The polymorphisms ALDH2 rs671 and CYP2E1 rs2031920 are reportedly correlated with the prevalence of HCC in other countries. The aim of this study was to investigate associations between ALDH2 and CYP2E1, and HCC susceptibility in a population of Guangxi, southern China, an area with a high incidence of HCC. Patients and methods The study cohort included 300 HCC cases, 292 healthy controls for HCC susceptibility analysis, and another 20 HCC cases and 10 healthy controls for ascertainment. Genotyping was performed using the polymerase chain reaction-restriction fragment length polymorphism method. Results The study results demonstrated that mutant genotypes of ALDH2 (G/A and A/A) led to significant differences in HCC susceptibility, as compared with the wild genotype (G/G) with the same C1/C1 genotype in non-drinking individuals (adjusted P=0.010, OR=0.20, 95% CI=0.06–0.68). The mutant genotypes of CYP2E1 (C1/C2 and C2/C2) brought about significant differences in HCC susceptibility, as compared with the wild genotype (C1/C1) and the same G/G genotype (adjusted P=0.025, OR=0.42, 95% CI=0.20–0.90). Drinking plays a role in HCC susceptibility in the same G/G genotype individuals (adjusted P=0.004, OR=0.32, 95% CI=0.15–0.69), but had no impact when combined with CYP2E1 for analysis (all P>0.05). Conclusion These results suggest that the mutant genotypes of ALDH2 and CYP2E1 may be protective factors for HCC susceptibility in Guangxi province, China.

Marker of proliferation Ki-67 expression is associated with transforming growth factor beta 1 and can predict the prognosis of patients with hepatic B virus-related hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most frequent malignancy of the liver. Transforming growth factor beta 1 (TGFB1) and marker of proliferation Ki-67 (MKI67) regulate cell proliferation, differentiation, and growth. The association between MKI67 and TGFB1 expression and its clinical implications in HCC remain unknown. Methods Public databases were used to analyze TGFB1 and MKI67 expression in different pathologic grades/stages and tissue types of HCC. The association between MKI67 and TGFB1 expression was explored using pathway analysis and in a HepG2 cell line treated with TGFB1. Survival analysis was performed to evaluate the prognostic value of TGFB1 and MKI67 expression in patients with hepatitis B virus (HBV)-related HCC. Results We identified that MKI67 expression was upregulated in liver cancer tissues. MKI67 and TGFB1 expression levels were different in various stages and tissue types of liver cancer. Furthermore, MKI67 expression was associated with TGFB1 expression in liver cancer tissues and HepG2 cells. Patients with HBV-related HCC and a higher level of MKI67 expression had a worse prognosis. Moreover, a nomogram was conducted to predict the clinical outcomes of patients with HBV-related HCC. Conclusion MKI67 expression level was associated with TGFB1 expression in liver cancer tissues and a HepG2 cell line. MKI67 expression level can predict the clinical outcomes of patients with HBV-related HCC.

Genome-scale analysis to identify prognostic microRNA biomarkers in patients with early stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

Background The aim of the study was to investigate potential prognostic microRNA (miRNA) biomarkers for patients with early stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using a miRNA-sequencing (miRNA-seq) data set from The Cancer Genome Atlas (TCGA). A miRNA expression-based prognostic signature was generated, and the potential role of target genes in overall survival (OS) in patients with PDAC was examined. Methods A miRNA-seq data set of 112 PDAC patients who underwent pancreaticoduodenectomy was obtained from TCGA. Survival analysis was performed to identify potential prognostic biomarkers. Results Eleven miRNAs (hsa-mir-501, hsa-mir-4521, hsa-mir-5091, hsa-mir-24-1, hsa-mir-126, hsa-mir-30e, hsa-mir-3157, hsa-let-7a-3, hsa-mir-133a-1, hsa-mir-4709, and hsa-mir-421) were used to construct a prognostic signature using the step function. The 11-miRNA prognostic signature showed good performance for prognosis prediction (adjusted P<0.0001, adjusted hazard ratio =4.285, 95% confidence interval =2.146–8.554), and the time-dependent receiver operating characteristic analysis showed an area under the curve of 0.864, 0.877, and 0.787 for 1-, 2-, and 3-year PDAC OS predictions, respectively. Comprehensive survival analysis suggested that the prognostic signature could serve as an independent prognostic factor for PDAC OS and performs better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of the miRNAs indicated that they were significantly enriched in multiple biological processes and pathways, including cell proliferation, cell cycle biological processes, the forkhead box O, mitogen-activated protein kinase, Janus kinase/signal transducers and activators of transcription signaling pathways, pathways in cancer, and the ErbB signaling pathway. Several target genes of these miRNAs were also associated with PDAC OS. Conclusion The present study identified a novel miRNA expression signature that showed potential as a prognostic biomarker for PDAC after pancreaticoduodenectomy.

Prognostic value of minichromosome maintenance mRNA expression in early-stage pancreatic ductal adenocarcinoma patients after pancreaticoduodenectomy

Background The aim of the current study was to investigate the potential prognostic value of minichromosome maintenance (MCM) genes in patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy by using the RNA-sequencing dataset from The Cancer Genome Atlas (TCGA). Methods An RNA-sequencing dataset of 112 early-stage PDAC patients who received a pancreaticoduodenectomy was obtained from TCGA. Survival analysis was used to identify potential prognostic values of MCM genes in PDAC overall survival (OS). Results Through mining public databases, we observed that MCM genes (MCM2, MCM3, MCM4, MCM5, MCM6, and MCM7) were upregulated in pancreatic cancer tumor tissue and have a strong positive coexpression with each other. Multivariate survival analysis indicated that a high expression of MCM4 significantly increased the risk of death in patients with PDAC, and time-dependent receiver operating characteristic analysis showed an area under the curve of 0.655, 0.587, and 0.509 for a 1-, 2-, and 3-year PDAC OS prediction, respectively. Comprehensive survival analysis of MCM4 using stratified and joint effects survival analysis suggests that MCM4 may be an independent prognostic indicator for PDAC OS. Gene set enrichment analysis indicated that MCM4 may participate in multiple biologic processes and pathways, including DNA replication, cell cycle, tumor protein p53, and Notch signaling pathways, thereby affecting prognosis of PDAC patients. Conclusions Our study indicates that MCM2–7 were upregulated in pancreatic cancer tumor tissues, and mRNA expression of MCM4 may serve as an independent prognostic indicator for PDAC OS prediction after pancreaticoduodenectomy.