scholarly journals LncRNA ELF3-AS1 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tianming Chen ◽  
Changhao Zhu ◽  
Xing Wang ◽  
Yaozhen Pan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Noncoding Rna ◽  
Cox Regression ◽  
Radioligand Binding ◽  
Gene Set Enrichment Analysis ◽  
Rank Test ◽  
Hepatic Tissue ◽  
Poor Overall Survival ◽  
Cox Regression Analysis ◽  
The Relationship

Background. Expression of long noncoding RNA (lncRNA) ELF3 antisense RNA 1 (ELF3-AS1) is observed in some cancers, while its role in hepatocellular carcinoma (HCC) is unclear. The study aimed to investigate the relationship between ELF3-AS1 and HCC based on database, bioinformatics, and statistical analysis. Methods. In this study, Kruskal–Wallis test, Wilcoxon sign-rank test, logistic regression, Kaplan–Meier method, Cox regression analysis, gene set enrichment analysis (GSEA), and immunoinfiltration analysis were used to assess the relationship between ELF3-AS1 expression and clinical characteristics of HCC patients, the relationship between ELF3-AS1 expression and prognosis of HCC patients, and the possible functions of ELF3-AS1 in HCC. Results. High expression of ELF3-AS1 in patients with HCC was related to T stage ( P  < 0.001), gender ( P  = 0.006), residual tumor ( P  = 0.008), histologic grade ( P  < 0.001), adjacent hepatic tissue inflammation ( P  = 0.011), AFP ( P  < 0.001), and vascular invasion ( P  = 0.028). High ELF3-AS1 expression was associated with poor overall survival (OS) ( P  = 0.001) and DSS ( P  = 0.047). ELF3-AS1 expression ( P  = 0.011) was independently correlated with OS in HCC patients. In the high ELF3-AS1 expression group, GPCR-radioligand binding, M phase, Class A/1 (rhodopsin-like receptors), cell cycle checkpoints, translation, mitotic metaphase and anaphase, signaling by robo receptors, keratinization, and rRNA processing were differentially enriched by GESA. ELF3-AS1 expression was associated with immune infiltrating cells. Conclusions. ELF3-AS1 expression was associated with poor prognosis in HCC. ELF3-AS1 expression was significantly associated with immune infiltration. ELF3-AS1 is a promising biomarker that can be used for the diagnosis and prognosis of HCC.

scholarly journals Rab25 Acts as a Promising Novel Bio-Marker in the Prognosis of Patients with Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhong Dai ◽  
Ke-Qing Yao ◽  
Xing-Sheng Hu ◽  
Yi-Qun Li ◽  
Yu-Tao Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Chi Square ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Chi Square Test ◽  
The Relationship

Abstract Background: Rab25 was indicated to be involved in several human tumors. However, the clinical significance of Rab25 in hepatocellular carcinoma (HCC) was still unclear. The purpose of this study was to investigate the expression and prognostic value of Rab25 in HCC.Methods: The relative mRNA expression levels of Rab25 in HCC tissues and adjacent normal tissues were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Chi-square test was used to analyze the relationship between Rab25 expression and clinical characteristics of patients. The prognostic value of Rab25 in HCC was estimated through Kaplan-Meier method and cox regression analysis.Results: Rab25 gene expression level was significantly higher in HCC tissues than that in normal tissues (P<0.001). Importantly, the increased Rab25 expression was closely associated with TNM stage (P=0.024), metastasis (P=0.022) and invasion classification (P=0.039). Moreover, patients with high Rab25 expression tended to have obviously shorter overall survival than those with low expression of Rab25 (log rank test, P<0.001) via Kaplan-Meier analysis. Univariate and multivariate cox regression analyses revealed that Rab25 was an independent prognostic factor of HCC.Conclusions: Rab25 is up-regulated in HCC and contributes to the progression of this tumor. What’s more, Rab25 may be a potential bio-marker for the prognosis of HCC.

scholarly journals Identification of a five-gene signature in association with overall survival for hepatocellular carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11273
Author(s):  
Lei Yang ◽  
Weilong Yin ◽  
Xuechen Liu ◽  
Fangcun Li ◽  
Li Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Overall Survival ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Hub Genes ◽  
Cox Regression Analysis

Background Hepatocellular carcinoma (HCC) is considered to be a malignant tumor with a high incidence and a high mortality. Accurate prognostic models are urgently needed. The present study was aimed at screening the critical genes for prognosis of HCC. Methods The GSE25097, GSE14520, GSE36376 and GSE76427 datasets were obtained from Gene Expression Omnibus (GEO). We used GEO2R to screen differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed by Cytoscape in order to find hub genes by module analysis. The Metascape was performed to discover biological functions and pathway enrichment of DEGs. MCODE components were calculated to construct a module complex of DEGs. Then, gene set enrichment analysis (GSEA) was used for gene enrichment analysis. ONCOMINE was employed to assess the mRNA expression levels of key genes in HCC, and the survival analysis was conducted using the array from The Cancer Genome Atlas (TCGA) of HCC. Then, the LASSO Cox regression model was performed to establish and identify the prognostic gene signature. We validated the prognostic value of the gene signature in the TCGA cohort. Results We screened out 10 hub genes which were all up-regulated in HCC tissue. They mainly enrich in mitotic cell cycle process. The GSEA results showed that these data sets had good enrichment score and significance in the cell cycle pathway. Each candidate gene may be an indicator of prognostic factors in the development of HCC. However, hub genes expression was weekly associated with overall survival in HCC patients. LASSO Cox regression analysis validated a five-gene signature (including CDC20, CCNB2, NCAPG, ASPM and NUSAP1). These results suggest that five-gene signature model may provide clues for clinical prognostic biomarker of HCC.

scholarly journals Clinical Value of lncRNA LUCAT1 Expression in Liver Cancer and its Potential Pathways

2019 ◽  
Vol 28 (4) ◽  
pp. 439-447 ◽  
Author(s):  
Yan Jiao ◽  
Yanqing Li ◽  
Bai Ji ◽  
Hongqiao Cai ◽  
Yahui Liu
Keyword(s):  
Liver Cancer ◽  
Roc Curve ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Rank Test ◽  
P Value ◽  
Rna Seq ◽  
Cox Regression Analysis

Background and Aims: Emerging studies indicate that long noncoding RNAs (lncRNAs) play a role as prognostic markers in many cancers, including liver cancer. Here, we focused on the lncRNA lung cancer-associated transcript 1 (LUCAT1) for liver cancer prognosis. Methods: RNA-seq and phenotype data were downloaded from the Cancer Genome Atlas (TCGA). Chisquare tests were used to evaluate the correlations between LUCAT1 expression and clinical features. Survival analysis and Cox regression analysis were used to compare different LUCAT1 expression groups (optimal cutoff value determined by ROC). The log-rank test was used to calculate the p-value of the Kaplan-Meier curves. A ROC curve was used to evaluate the diagnostic value. Gene Set Enrichment Analysis (GSEA) was performed, and competing endogenous RNA (ceRNA) networks were constructed to explore the potential mechanism. Results: Data mining of the TCGA -Liver Hepatocellular Carcinoma (LIHC) RNA-seq data of 371 patients showed the overexpression of LUCAT1 in cancerous tissue. High LUCAT1 expression was associated with age (p=0.007), histologic grade (p=0.009), T classification (p=0.022), and survival status (p=0.002). High LUCAT1 patients had a poorer overall survival and relapse-free survival than low LUCAT1 patients. Multivariate analysis identified LUCAT1 as an independent risk factor for poor survival. The ROC curve indicated modest diagnostic performance. GSEA revealed the related signaling pathways, and the ceRNA network uncovered the underlying mechanism. Conclusion: High LUCAT1 expression is an independent prognostic factor for liver cancer.

scholarly journals Prognostic Role of Serum Cytokeratin-19 Fragment (CYFRA 21-1) in Patients with Hepatocellular Carcinoma

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2776 ◽  
Author(s):  
Gian Paolo Caviglia ◽  
Michela Ciruolo ◽  
Antonella Olivero ◽  
Patrizia Carucci ◽  
Emanuela Rolle ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Treatment Strategies ◽  
Stem Cell Marker ◽  
Rank Test ◽  
Cytokeratin 19 ◽  
Serum Samples ◽  
Cox Regression Analysis ◽  
Keratin 19 ◽  
New Diagnosis

Keratin 19 (K19) is a cancer stem cell marker expressed by a subpopulation of hepatocellular carcinoma (HCC), associated with tumor aggressiveness. We evaluated the prognostic value of serum K19 fragment (CYFRA 21-1), in comparison or in combination with alpha-fetoprotein (AFP) and protein induced by vitamin-K absence or antagonist-II (PIVKA-II), in patients with HCC. A total of 160 patients (28F/132M; median age 62, range 44–86 years) with a new diagnosis of HCC and available serum samples collected at tumor diagnosis were analyzed retrospectively. Median overall survival (OS) after HCC diagnosis was 35.1, 95% CI 27.1–70.5 months. Multivariate Cox regression analysis showed that CYFRA 21-1 > 2.7 ng/mL (hazard ratio (HR) = 3.39, p < 0.001), AFP > 20 ng/mL (HR = 2.27, p = 0.007), and PIVKA-II > 200 mAU/mL (HR = 2.17, p = 0.020) were independent predictors of OS. The combination of biomarkers positivity allowed us to stratify patients with HCC into four risk categories associated with a progressively lower survival probability (log-rank test, p < 0.001). CYFRA 21-1 resulted an independent prognostic factor of patients with HCC and its combination with AFP and PIVKA-II might be useful to tailor personalized treatment strategies.

scholarly journals Lymphopenia Is Associated with Gross Target Volumes and Fractions in Hepatocellular Carcinoma Patients Treated with External Beam Radiation Therapy and Also Indicates Worse Overall Survival

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Hai-Ge Zhang ◽  
Ping Yang ◽  
Tao Jiang ◽  
Jian-Ying Zhang ◽  
Xue-Juan Jin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
External Beam Radiation ◽  
Rank Test ◽  
Beam Radiation ◽  
Kaplan Meier ◽  
Target Volumes ◽  
The Relationship

Purpose. To investigate whether lymphocyte nadir induced by radiation is associated with survival and explore its underlying risk factors in patients with hepatocellular carcinoma (HCC). Methods. Total lymphocyte counts were collected from 184 HCC patients treated by radiotherapy (RT) with complete follow-up. Associations between gross tumor volumes (GTVs) and radiation-associated parameters with lymphocyte nadir were evaluated by Pearson/Spearman correlation analysis and multiple linear regression. Kaplan–Meier analysis, log-rank test, as well as univariate and multivariate Cox regression were performed to assess the relationship between lymphocyte nadir and overall survival (OS). Results. GTVs and fractions were negatively related with lymphocyte nadir (p<0.001 and p=0.001, respectively). Lymphocyte nadir and Barcelona Clinic Liver Cancer (BCLC) stage were independent prognostic factors predicting OS of HCC patients (all p<0.001). Patients in the GTV ≤55.0 cc and fractions ≤16 groups were stratified by lymphocyte nadir, and the group with the higher lymphocyte counts (LCs) showed longer survival than the group with lower LCs (p<0.001 and p=0.006, respectively). Patient distribution significantly differed among the RT fraction groups according to BCLC stage (p<0.001). However, stratification of patients in the same BCLC stage by RT fractionation showed that the stereotactic body RT (SBRT) group achieved the best survival. Furthermore, there were significant differences in lymphocyte nadir among patients in the SBRT group. Conclusions. A lower lymphocyte nadir during RT was associated with worse survival among HCC patients. Smaller GTVs and fractions reduced the risk of lymphopenia.

scholarly journals Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Honglan Guo ◽  
Qinqiao Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

scholarly journals PD-L1+NEUT, Foxp3+Treg, and NLR as New Prognostic Marker with Low Survival Benefits Value in Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110458
Author(s):  
Lin Zhou ◽  
Jing Wang ◽  
Shao-cheng Lyu ◽  
Li-chao Pan ◽  
Xian-jie Shi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hepatocellular Carcinoma ◽  
Peripheral Blood ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Rank Test ◽  
Cancer Tissue ◽  
Cox Regression Analysis ◽  
Poorly Differentiated ◽  
Independent Risk Factors

Background: This presented study was aimed to evaluate the diagnostic and prognostic value of PD-L1+Neutrophils (PD-L1+NEUT) and neutrophil to lymphocyte ratio (NLR) based on our previous experience of Foxp3+Treg in transplantation. Methods: the NLR cutoff value of 1.79 was used to include 136 cases from the 204 patients with hepatocellular carcinoma (HCC) confirmed by clinical pathology, which were divided into highly-moderately and poorly differentiated HCC groups. The expressions of PD-L1+NEUT and Foxp3+Treg in peripheral blood and cancer tissue were detected with flow cytometry, meanwhile, PD-L1 and Foxp3 expressed in carcinoma and para-carcinoma tissues were marked by immunohistochemistry. Survival rates, including overall survival and disease-free survival, were calculated by the Kaplan–Meier curve and evaluated with the log-rank test. Finally, Cox risk regression model was used to analyze the independent risk factors for prognostic survival. Results: The level of PD-L1+NEUT, Foxp3+Treg, and NLR in peripheral blood of patients with poorly differentiated HCC were significantly increased (all P < .001). Both PD-L1+NEUT and NLR were positively correlated with Foxp3+Treg ( r = 0.479, P = .0017; r = 0.58, P < .0001). The level of PD-L1+NEUT and Foxp3+Treg as well as PD-L1 and Foxp3 in cancer tissue and patients with poorly differentiated HCC were obviously increased (all P < .01), respectively. Cox regression analysis indicated that PD-L1+NEUT, NLR, and Foxp3+Treg were independent risk factors for the prognosis ( P = .000, .000, .006) with a RR and 95%CI of 2.704-(2.155-3.393), 3.139-(2.361-4.173), 1.409-(1.105-1.798), respectively. Conclusion: PD-L1+NEUT, NLR, and Foxp3+Treg are independent risk factors for prognosis which maybe new marker of lower survival benefits.

scholarly journals Identification of a Five-Autophagy-Related-lncRNA Signature as a Novel Prognostic Biomarker for Hepatocellular Carcinoma

2021 ◽  
Vol 7 ◽  
Author(s):  
Xiaoyu Deng ◽  
Qinghua Bi ◽  
Shihan Chen ◽  
Xianhua Chen ◽  
Shuhui Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Prediction Ability ◽  
Cox Regression Analysis

Although great progresses have been made in the diagnosis and treatment of hepatocellular carcinoma (HCC), its prognostic marker remains controversial. In this current study, weighted correlation network analysis and Cox regression analysis showed significant prognostic value of five autophagy-related long non-coding RNAs (AR-lncRNAs) (including TMCC1-AS1, PLBD1-AS1, MKLN1-AS, LINC01063, and CYTOR) for HCC patients from data in The Cancer Genome Atlas. By using them, we constructed a five-AR-lncRNA prognostic signature, which accurately distinguished the high- and low-risk groups of HCC patients. All of the five AR lncRNAs were highly expressed in the high-risk group of HCC patients. This five-AR-lncRNA prognostic signature showed good area under the curve (AUC) value (AUC = 0.751) for the overall survival (OS) prediction in either all HCC patients or HCC patients stratified according to several clinical traits. A prognostic nomogram with this five-AR-lncRNA signature predicted the 3- and 5-year OS outcomes of HCC patients intuitively and accurately (concordance index = 0.745). By parallel comparison, this five-AR-lncRNA signature has better prognosis accuracy than the other three recently published signatures. Furthermore, we discovered the prediction ability of the signature on therapeutic outcomes of HCC patients, including chemotherapy and immunotherapeutic responses. Gene set enrichment analysis and gene mutation analysis revealed that dysregulated cell cycle pathway, purine metabolism, and TP53 mutation may play an important role in determining the OS outcomes of HCC patients in the high-risk group. Collectively, our study suggests a new five-AR-lncRNA prognostic signature for HCC patients.

scholarly journals NUCKS1 Acts As A Promising Novel Bio-Marker in The Prognosis of Patients with Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Xianfeng Zhang ◽  
Xianjun Zhang ◽  
Xinguo Li ◽  
Hongbing Bao ◽  
Guang Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mrna Expression ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Kinase Substrate ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Relative Mrna Expression

Abstract Background: Nuclear casein kinase and cyclin-dependent kinase substrate 1 (NUCKS1) was over-expressed in some tumors, including hepatocellular carcinoma (HCC). However, the clinical significance of NUCKS1 in HCC was still unclear. The aim of this study was to explore the expression and prognostic value of NUCKS1 in HCC. Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative mRNA expression of NUCKS1 in HCC tissues and corresponding adjacent normal tissues. The relationship between NUCKS1 expression and clinical characteristics of patients was analyzed by c2 test. Kaplan-Meier method and cox regression analysis were applied to estimate the prognostic value of NUCKS1 in HCC. Results: Compared with normal tissues, the relative mRNA expression level of NUCKS1 was significantly up-regulated in HCC tissues (P < 0.001). And high NUCKS1 expression was closely associated with tumor differentiation, TNM stage, vascular invasion and metastasis (P < 0.05). Kaplan-Meier analysis revealed that the overall survival of HCC patients with low expression of NUCKS1 was obviously longer than those with high NUCKS1 expression (log rank test, P = 0.001). NUCKS1 was an independent prognostic factor of HCC patients via univariate and multivariate cox regression analyses.Conclusions: NUCKS1 may be correlated with the progression of HCC and may serve as a potential factor for the prognosis of this disease.

scholarly journals Identification and Validation of Tumour Microenvironment-Based Immune Related Signature for Hepatocellular Carcioma: Immunotherapeutic Implications

2021 ◽  
Author(s):  
Hong Yu ◽  
Shao Wang ◽  
Tao Zhou ◽  
Jia Sun ◽  
Tian Qi ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Treatment Outcomes ◽  
Predictive Model ◽  
Cox Regression ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Patient Treatment ◽  
Cox Regression Analysis

Abstract Background: Even though treatment outcomes for hepatocellular carcinoma patients have significantly improved, prognostic clinical evaluation remains a substantial challenge due to the heterogeneity and complexity of cancer. Accumulating evidence has revealed that the tumor immune microenvironment is critical for progression and prognosis of hepatocellular carcinoma. A powerful predictive model could assist physicians to better monitor patient treatment outcomes and improve overall survival rates. Therefore, we introduced tumor immune-related genes into a model that could be used for patient risk classification. Results: First, the Single-sample gene set enrichment analysis (ssGSEA) and Weighted gene co-expression networks construction (WGCNA) methods were applied to identify highly associated immunity genes. Following this, a multi-immune-related gene-based signature determined by The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to determine risk stratification. In addition, this predictive model was evaluated according to its performance as a prognostic model in the training and testing datasets. Furthermore, tumor mutation burden and biological enrichment analysis were applied to reveal the potential mechanisms through which the gene signature functions. Conclusion: In conclusion, our four-gene signature model may be clinically applied in hepatocellular carcinoma patients at high risk of mortality for personalized therapy.

Sign in / Sign up

Export Citation Format

Share Document