scholarly journals Prognostic significance and oncogene function of cathepsin A in hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Huaxiang Wang ◽  
Fengfeng Xu ◽  
Fang Yang ◽  
Lizhi Lv ◽  
Yi Jiang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Oxidative Phosphorylation ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinical Value ◽  
Lysosomal Protease

AbstractCathepsin A (CTSA) is a lysosomal protease that regulates galactoside metabolism. The previous study has shown CTSA is abnormally expressed in various types of cancer. However, rarely the previous study has addressed the role of CTSA in hepatocellular carcinoma (HCC) and its prognostic value. To study the clinical value and potential function of CTSA in HCC, datasets from the Cancer Genome Atlas (TCGA) database and a 136 HCC patient cohort were analyzed. CTSA expression was found to be significantly higher in HCC patients compared with normal liver tissues, which was supported by immunohistochemistry (IHC) validation. Both gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that CTSA co-expressed genes were involved in ATP hydrolysis coupled proton transport, carbohydrate metabolic process, lysosome organization, oxidative phosphorylation, other glycan degradation, etc. Survival analysis showed a significant reduction both in overall survival (OS) and recurrence-free survival (RFS) of patients with high CTSA expression from both the TCGA HCC cohort and 136 patients with the HCC cohort. Furthermore, CTSA overexpression has diagnostic value in distinguishing between HCC and normal liver tissue [Area under curve (AUC) = 0.864]. Moreover, Gene set enrichment analysis (GSEA) showed that CTSA expression correlated with the oxidative phosphorylation, proteasome, and lysosome, etc. in HCC tissues. These findings demonstrate that CTSA may as a potential diagnostic and prognostic biomarker in HCC.

scholarly journals Prognostic Significance and Oncogene Function of Cathepsin A in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Huaxiang Wang ◽  
Fengfeng Xu ◽  
Fang Yang ◽  
Lizhi Lv ◽  
Yi Jiang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Oxidative Phosphorylation ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Normal Liver ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinical Value ◽  
Lysosomal Protease

Abstract Cathepsin A (CTSA) is a lysosomal protease that regulates galactoside metabolism. The previous study has shown CTSA is abnormally expressed in various types of cancer. However, rarely the previous study has addressed the role of CTSA in hepatocellular carcinoma (HCC) and its prognostic value. To study the clinical value and potential function of CTSA in HCC, datasets from the Cancer Genome Atlas (TCGA) database and a 136 HCC patient cohort were analyzed. CTSA expression was found to be significantly higher in HCC patients compared with normal liver tissues, which was supported by immunohistochemistry (IHC) validation. Both gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that CTSA co-expressed genes were involved in ATP hydrolysis coupled proton transport, carbohydrate metabolic process, lysosome organization, oxidative phosphorylation, other glycan degradation, etc. Survival analysis showed a significant reduction both in overall survival (OS) and recurrence-free survival (RFS) of patients with high CTSA expression from both the TCGA HCC cohort and 136 patients with the HCC cohort. Furthermore, CTSA overexpression has diagnostic value in distinguishing between HCC and normal liver tissue (Area under curve (AUC) = 0.864). Moreover, Gene set enrichment analysis (GSEA) showed that CTSA expression correlated with the oxidative phosphorylation, proteasome, and lysosome, etc. in HCC tissues. These findings demonstrate that CTSA may as a potential diagnostic and prognostic biomarker in HCC.

scholarly journals An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dengliang Lei ◽  
Yue Chen ◽  
Yang Zhou ◽  
Gangli Hu ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Roc Curves ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Highly Correlated

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers worldwide. Neovascularization is closely related to the malignancy of tumors. We constructed a signature of angiogenesis-related long noncoding RNA (lncRNA) to predict the prognosis of patients with HCC. The lncRNA expression matrix of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA). First, gene set enrichment analysis (GSEA) was used to distinguish the differentially expressed genes of the angiogenesis genes in liver cancer and adjacent tissues. Next, a signature of angiogenesis-related lncRNAs was constructed using univariate and multivariate analyses, and receiver operating characteristic (ROC) curves were used to assess the accuracy. The signature and relevant clinical information were used to construct the nomogram. A 5-lncRNA signature was highly correlated with overall survival (OS) in HCC patients and performed well in evaluations using the C-index, areas under the curve, and calibration curves. In summary, the 5-lncRNA model can serve as an accurate signature to predict the prognosis of patients with liver cancer, but its mechanism of action must be further elucidated by experiments.

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 CXCL5 Has Potential to Be a Marker for Hepatocellular Carcinoma Prognosis and Was Correlating With Immune Infiltrates

2021 ◽  
Vol 11 ◽  
Author(s):  
Yuan Nie ◽  
Mei-chun Jiang ◽  
Cong Liu ◽  
Qi Liu ◽  
Xuan Zhu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Hospital Data ◽  
Gene Set Enrichment ◽  
Local Hospital ◽  
High Expression Group ◽  
Cancer Genome Atlas

BackgroundsTumor microenvironment (TME) plays a crucial role in the initiation and progression of Hepatocellular Carcinoma (HCC), especially immune infiltrates. However, there is still a challenge in understanding the modulation of the immune and stromal components in TME, especially TME related genes.MethodsThe proportion of tumor-infiltrating immune cells (TICs) and the immune and stromal scores in 374 HCC patients from The Cancer Genome Atlas (TCGA) database were determined using CIBERSORT and ESTIMATE computational methods. The final screened genes were confirmed by the PPI network and univariate Cox regression of the differentially expressed genes based on different immune or stromal scores. The correlation between the expression levels of the final gene interactions and the clinical characteristics was based on TCGA database and local hospital data. Gene set enrichment analysis (GSEA) and the effect of CXCL5 expression on TICs were conducted.ResultsThere were correlations between the expression of CXCL5 and survival of HCC patients and TMN classification both in TCGA database and local hospital data. The immune-related activities were enriched in the high-expression group; however, the metabolic pathways were enriched in the low-expression group. The result of CIBERSORT analyzing had indicated that CXCL5 expression were correlated with the proportion of NK cells activated, macrophages M0, Mast cells resting, Neutrophils.ConclusionsCXCL5 was a potential prognostic marker for HCC and provides clues regarding immune infiltrates, which offers extra insight for therapeutics of HCC, however, more independent cohorts and functional experiments of CXCL5 are warranted.

scholarly journals Bioinformatics Analysis of Autophagy-related LncRNAs in Esophageal Carcinoma

2020 ◽  
Author(s):  
junbai fan ◽  
Dan Wu ◽  
Yi Ding
Keyword(s):  
High Risk ◽  
Esophageal Carcinoma ◽  
Cox Regression ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Risk Patients ◽  
Risk Patients

Abstract Background: Esophageal carcinoma (ESCA) is a malignant tumor with high invasiveness and mortality. Autophagy has multiple roles in the development of cancer; however, there are limited data on autophagy genes associated with long non-coding RNAs (lncRNAs) in ESCA. The purpose of this study was to screen potential diagnostic and prognostic molecules, and to identify gene co-expression networks associated with autophagy in ESCA. Methods: We downloaded transcriptome expression profiles from The Cancer Genome Atlas and autophagy-related gene data from the Human Autophagy Database, and analyzed the co-expression of mRNAs and lncRNAs. In addition, the diagnostic and prognostic value of autophagy-related lncRNAs was analyzed by multivariate Cox regression. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis was carried out for high-risk patients, and enriched pathways were analyzed by gene set enrichment analysis. Results: The results showed that genes of high-risk patients were enriched in protein export and spliceosome. Based on Cox stepwise regression and survival analysis, we identified seven autophagy-related lncRNAs with prognostic and diagnostic value, with the potential to be used as a combination to predict the prognosis of patients with ESCA. Finally, a co-expression network related to autophagy was constructed. Conclusion: These results suggest that autophagy-related lncRNAs and the spliceosome play important parts in the pathogenesis of ESCA. Our findings provide new insight into the molecular mechanism of ESCA and suggest a new method for improving its treatment.

scholarly journals Bioinformatics Analysis of Autophagy-related lncRNAs in Esophageal Carcinoma

2021 ◽  
Vol 24 ◽  
Author(s):  
Dan Wu ◽  
Yi Ding ◽  
JunBai Fan
Keyword(s):  
High Risk ◽  
Esophageal Carcinoma ◽  
Cox Regression ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
High Risk Patients ◽  
Risk Patients

Background: Esophageal carcinoma (ESCA) is a malignant tumor with high invasiveness and mortality. Autophagy has multiple roles in the development of cancer; however, there are limited data on autophagy genes associated with long non-coding RNAs (lncRNAs) in ESCA. The purpose of this study was to screen potential diagnostic and prognostic molecules and to identify gene co-expression networks associated with autophagy in ESCA. Methods: We downloaded transcriptome expression profiles from The Cancer Genome Atlas and autophagy-related gene data from the Human Autophagy Database and analyzed the co-expression of mRNAs and lncRNAs. In addition, the diagnostic and prognostic value of autophagy-related lncRNAs was analyzed by multivariate Cox regression. Furthermore, Kyoto Encyclopedia of Genes and Genomes analysis was carried out for high-risk patients, and enriched pathways were analyzed by gene set enrichment analysis. Results: The results showed that genes of high-risk patients were enriched in protein export and spliceosome. Based on Cox stepwise regression and survival analysis, we identified seven autophagy-related lncRNAs with prognostic and diagnostic value, with the potential to be used as a combination to predict the prognosis of patients with ESCA. Finally, a co-expression network related to autophagy was constructed. Conclusion: These results suggest that autophagy-related lncRNAs and the spliceosome play important parts in the pathogenesis of ESCA. Our findings provide new insight into the molecular mechanism of ESCA and suggest a new method for improving its treatment.

scholarly journals ANXA9 as a novel prognostic biomarker associated with immune infiltrates in gastric cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12605
Author(s):  
Tongtong Zhang ◽  
Suyang Yu ◽  
Shipeng Zhao
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Survival Curve ◽  
Enrichment Analysis ◽  
Prognostic Indicator ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
The Relationship

Background Gastric cancer (GC) is the most prevalent malignancy among the digestive system tumors. Increasing evidence has revealed that lower mRNA expression of ANXA9 is associated with a poor prognosis in colorectal cancer. However, the role of ANXA9 in GC remains largely unknown. Material and Methods The Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas databases were used to investigate the expression of ANXA9 in GC, which was then validated in the four Gene Expression Omnibus (GEO) datasets. The diagnostic value of ANXA9 for GC patients was demonstrated using a receiver operating characteristic (ROC) curve. The correlation between ANXA9 expression and clinicopathological parameters was analyzed in The Cancer Genome Atlas (TCGA) and UALCAN databases. The Kaplan-Meier (K-M) survival curve was used to elucidate the relationship between ANXA9 expression and the survival time of GC patients. We then performed a gene set enrichment analysis (GSEA) to explore the biological functions of ANXA9. The relationship of ANXA9 expression and cancer immune infiltrates was analyzed using the Tumor Immune Estimation Resource (TIMER). In addition, the potential mechanism of ANXA9 in GC was investigated by analyzing its related genes. Results ANXA9 was significantly up-regulated in GC tissues and showed obvious diagnostic value. The expression of ANXA9 was related to the age, gender, grade, TP53 mutation, and histological subtype of GC patients. We also found that ANXA9 expression was associated with immune-related biological function. ANXA9 expression was also correlated with the infiltration level of CD8+ T cells, neutrophils, and dendritic cells in GC. Additionally, copy number variation (VNV) of ANXA9 occurred in GC patients. Function enrichment analyses revealed that ANXA9 plays a role in the GC progression by interacting with its related genes. Conclusions Our results provide strong evidence of ANXA9 expression as a prognostic indicator related to immune responses in GC.

Integrative Analysis Reveals the Prognostic Value and Functions of Splicing Factors Implicated in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Yue Wang ◽  
Fan Yang ◽  
Jiaqi Shang ◽  
Haitao He ◽  
Qing Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Model ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Splicing Factors ◽  
Biological Functions ◽  
Clinical Value ◽  
Multiple Cancer ◽  
Protein Coding ◽  
Protein Coding Genes

Abstract Splicing factors (SFs) play critical roles in the pathogenesis of various cancers through regulating tumor-associated alternative splicing (AS) events. However, the clinical value and biological functions of SFs in hepatocellular carcinoma (HCC) remain obscure. In this study, we identified 40 dysregulated SFs in HCC and established a prognostic model composed of four SFs (DNAJC6, ZC3H13, IGF2BP3, DDX19B). The predictive efficiency and independence of the prognostic model were confirmed to be satisfactory. Gene Set Enrichment Analysis (GSEA) illustrated the risk score calculated by our prognostic model was significantly associated with multiple cancer-related pathways and metabolic processes. Furthermore, we constructed the SFs-AS events regulatory network and extracted 108 protein-coding genes from the network for following functional explorations. Protein-protein interaction (PPI) network delineated the potential interactions among these 108 protein-coding genes. GO and KEGG pathway analyses investigated ontology gene sets and canonical pathways enriched by these 108 protein-coding genes. Overlapping the results of GSEA and KEGG, seven pathways were identified to be potential pathways regulated by our prognostic model through triggering aberrant AS events in HCC. In conclusion, the present study established an effective prognostic model based on SFs for HCC patients. Functional explorations of SFs and SFs-associated AS events provided directions to explore biological functions and mechanisms of SFs in HCC tumorigenesis.

scholarly journals Low UGP2 Expression Is Associated with Tumour Progression and Predicts Poor Prognosis in Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Qiuyue Hu ◽  
Shen Shen ◽  
Jianhao Li ◽  
Liwen Liu ◽  
Xin Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Tumour Progression ◽  
Enrichment Analysis ◽  
Malignant Tumour ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
Uridine Diphosphate ◽  
Roc Curve Analysis

Hepatocellular carcinoma (HCC) is a malignant tumour associated with a high mortality rate and poor prognosis worldwide. Uridine diphosphate-glucose pyrophosphorylase 2 (UGP2), a key enzyme in glycogen biosynthesis, has been reported to be associated with the occurrence and development of various cancer types. However, its diagnostic value and prognostic value in HCC remain unclear. The present study observed that UGP2 expression was significantly downregulated at both the mRNA and protein levels in HCC tissues. Receiver operating characteristic (ROC) curve analysis revealed that UGP2 may be an indicator for the diagnosis of HCC. In addition, Kaplan-Meier and Cox regression multivariate analyses indicated that UGP2 is an independent prognostic factor of overall survival (OS) in patients with HCC. Furthermore, gene set enrichment analysis (GSEA) suggested that gene sets negatively correlated with the survival of HCC patients were enriched in the group with low UGP2 expression levels. More importantly, a significant correlation was identified between low UGP2 expression and fatty acid metabolism. In summary, the present study demonstrates that UGP2 may contribute to the progression of HCC, indicating a potential therapeutic target for HCC patients.

scholarly journals Evaluation of FGFR1 as a diagnostic biomarker for ovarian cancer using TCGA and GEO datasets

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10817
Author(s):  
Huiting Xiao ◽  
Kun Wang ◽  
Dan Li ◽  
Ke Wang ◽  
Min Yu
Keyword(s):  
Ovarian Cancer ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Residual Tumor ◽  
Diagnostic Value ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Diagnostic Biomarker

Background Malignant ovarian cancer is associated with the highest mortality of all gynecological tumors. Designing therapeutic targets that are specific to OC tissue is important for optimizing OC therapies. This study aims to identify different expression patterns of genes related to FGFR1 and the usefulness of FGFR1 as diagnostic biomarker for OC. Methods We collected data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. In the TCGA cohort we analyzed clinical information according to patient characteristics, including age, stage, grade, longest dimension of the tumor and the presence of a residual tumor. GEO data served as a validation set. We obtained data on differentially expressed genes (DEGs) from the two microarray datasets. We then used gene set enrichment analysis (GSEA) to analyze the DEG data in order to identify enriched pathways related to FGFR1. Results Differential expression analysis revealed that FGFR1 was significantly downregulated in OC specimens. 303 patients were included in the TCGA cohort. The GEO dataset confirmed these findings using information on 75 Asian patients. The GSE105437 and GSE12470 database highlighted the significant diagnostic value of FGFR1 in identifying OC (AUC = 1, p = 0.0009 and AUC = 0.8256, p = 0.0015 respectively). Conclusions Our study examined existing TCGA and GEO datasets for novel factors associated with OC and identified FGFR1 as a potential diagnostic factor. Further investigation is warranted to characterize the role played by FGFR1 in OC.

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