scholarly journals Exploration of prognostic index based on immune-related genes in patients with liver hepatocellular carcinoma

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Weidong Shi ◽  
Lanyun Feng ◽  
Shu Dong ◽  
Zhouyu Ning ◽  
Yongqiang Hua ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Function Analysis ◽  
Prognostic Index ◽  
Prognostic Indicator ◽  
Expression Level ◽  
Clinical Feature ◽  
Molecular Characteristics ◽  
Synthetic Index ◽  
Immune Related Genes ◽  
Liver Hepatocellular Carcinoma

Abstract The present study aimed to screen the immune-related genes (IRGs) in patients with liver hepatocellular carcinoma (LIHC) and construct a synthetic index for indicating the prognostic outcomes. The bioinformatic analysis was performed on the data of 374 cancer tissues and 50 normal tissues, which were downloaded from TCGA database. We observed that 17 differentially expressed IRGs were significantly associated with survival in LIHC patients. These LIHC-specific IRGs were validated with function analysis and molecular characteristics. Cox analysis was applied for constructing a RiskScore for predicting the survival. The RiskScore involved six IRGs and corresponding coefficients, which was calculated with the following formula: RiskScore = [Expression level of FABP5 *(0.064)] + [Expression level of TRAF3 * (0.198)] + [Expression level of CSPG5 * (0.416)] + [Expression level of IL17D * (0.197)] + [Expression level of STC2 * (0.036)] + [Expression level of BRD8 * (0.140)]. The RiskScore was positively associated with the poor survival, which was verified with the dataset from ICGC database. Further analysis revealed that the RiskScore was independent of any other clinical feature, while it was linked with the infiltration levels of six types of immune cells. Our study reported the survival-associated IRGs in LIHC and then constructed IRGs-based RiskScore as prognostic indicator for screening patients with high risk of short survival. Both the screened IRGs and IRGs-based RiskScore were clinically significant, which may be informative for promoting the individualized immunotherapy against LIHC.

Biomarker Identification for Liver Hepatocellular Carcinoma and Cholangiocarcinoma Based on Gene Regulatory Network Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Qiuyan Huo ◽  
Yuying Ma ◽  
Yu Yin ◽  
Guimin Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Networks ◽  
Primary Liver Cancer ◽  
Endocrine Resistance ◽  
Molecular Characteristics ◽  
Network Clustering ◽  
Resistance Pathway ◽  
Gene Regulatory ◽  
Tf Gene ◽  
Liver Hepatocellular Carcinoma

Aims: We aimed to find common and distinct molecular characteristics between LIHC and CHOL based on miRNA-TF-gene FFL. Background: Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are two main histological subtypes of primary liver cancer with a unified molecular landscape, and feed-forward loops (FFLs) have been shown to be relevant in these complex diseases. Objective: To date, there has been no comparative analysis of the pathogenesis of LIHC and CHOL based on regulatory relationships. Therefore, we investigated the common and distinct regulatory properties of LIHC and CHOL in terms of gene regulatory networks. Method: Based on identified FFLs and an analysis of pathway enrichment, we constructed pathway-specific co-expression networks and further predicted biomarkers for these cancers by network clustering. Resul: We identified 20 and 36 candidate genes for LIHC and CHOL, respectively. The literature from PubMed supports the reliability of our results. Conclusion: Our results indicated that the hsa01522-Endocrine resistance pathway was associated with both LIHC and CHOL. Additionally, six genes (SPARC, CTHRC1, COL4A1, EDIL3, LAMA4 and OLFML2B) were predicted to be highly associated with both cancers, of which SPARC was significantly highly ranked. Other: In addition, we inferred that the Collagen gene family, which appeared more frequently in our overall prediction results, might be closely related to cancer development.

scholarly journals Relationship between IL10 and PD-L1 in Liver Hepatocellular Carcinoma Tissue and Cell Lines

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qian Qian ◽  
Changping Wu ◽  
Jianping Chen ◽  
Weibing Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Monoclonal Antibody ◽  
Cell Lines ◽  
Western Blotting ◽  
Large Scale ◽  
Expression Level ◽  
Survival Duration ◽  
Great Promise ◽  
Clinical Response Rate ◽  
Liver Hepatocellular Carcinoma

Background. Despite the large-scale clinical application of programmed death-ligand 1 (PD-L1) monoclonal antibody, reduction in its clinical response rate has become a gradual problem. As such, use of PD-L1 monoclonal antibody in combination with other anticarcinoma drugs has been the main strategy in improving its efficacy. Interleukin 10 (IL10) is a recognized inflammatory and immunosuppressive factor. Previous studies have suggested that there is a link between PD-L1 and IL10. Objective. This study was aimed at clarifying the relationship between PD-L1 and IL10 in liver hepatocellular carcinoma (LIHC) and whether IL10 enhances the efficacy of PD-L1 inhibitor. Methods. Expression levels of PD-L1 and IL10 in carcinoma and adjacent tissues were tested by immunochemistry, Western blotting, and RT-PCR. Survival duration and follow-up data of each patient were recorded. LIHC cell lines Bel7405 and MHCC 97-H were used for in vitro experiments. Exogenous IL10 and anti-IL10 were added to cell supernatant. Expression level of PD-L1 in the LIHC cell lines was determined using Western blotting and ELISA. CCK8 and transwell assays were adopted to examine the effect of PD-L1 combined with IL10 on proliferation, invasion, and metastasis of LIHC cells. Results. The survival period of patients with low expression of IL10 was longer than that of patients with high expression (P=0.01). Overexpression of PD-L1 increased the IL10 and Met levels in LIHC tissues and cell lines. IL10 downregulated the expression level of PD-L1 and enhanced the efficacy of crizotinib via the Met signaling pathway in the LIHC cells. Conclusions. A combination of IL10 and PD-L1 inhibitor holds great promise as an effective treatment for LIHC.

scholarly journals A novel prognostic index model constructed with five autophagy-related genes may be a potential prognostic biomarker and therapeutic target in liver hepatocellular carcinoma

2020 ◽  
Author(s):  
Qingqing Zhu ◽  
Jia Wang ◽  
Menghan Liu ◽  
Qiujing Zhang ◽  
Miaomiao Shen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Rate ◽  
Therapeutic Target ◽  
Prognostic Biomarker ◽  
Prognostic Index ◽  
Cancer Genome ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Liver Hepatocellular Carcinoma ◽  
Testing Group

Abstract Background Early diagnosis and effective treatment of liver hepatocellular carcinoma (LIHC) are keys to improving the prognosis of patients. Increasing evidences clarify that autophagy-related genes (ARGs) make great differences to the generation and progression of LIHC, and may serve as prognostic biomarkers for LIHC. Methods We randomly divided the LIHC patients in The Cancer Genome Atlas (TCGA) into the training and testing group. Next, use the training group to perform univariate Cox, LASSO and multivariate Cox analysis to construct our prognostic index (PI) model for LIHC; use the testing group and the whole TCGA set to make internal validations; use the International Cancer Genome Consortium to make external validations; and use the whole TCGA, GSE14520 and Oncomine to exam the expression patterns of the five ARGs. Then, we performed the ROC curve as well as univariate and multivariate analysis to evaluate the independent prognostic prediction power of the PI model, and made nomograms to estimate 1,3,5-year survival rate of LIHC patients. Besides, we conducted functional enrichment analyses of differentially expressed ARGs with GO, KEGG and GSEA, and made drug sensitivity analysis for the PI model via the GDSC database. Results A novel PI model which was composed of five key ARGs ( ATG9A , EIF2S1 , GRID1 , SAR1A and SQSTM1 ) succeeded to be constructed. All the internal and external validations testified that the PI model could well distinguish high-risk patients from low-risk ones, with AUC values > 0.60. Further comparison analysis showed that the PI model was no less than some common prognostic factors. People can estimate the 1,3,5-year survival rate of individual LIHC patient with the nomograms. Additionally, we obtained 62 differentially expressed ARGs and studied the potential mechanisms or pathways. Furthermore, we also found some potential targeted drugs associated to the five ARGs for LIHC patients. Conclusions The novel five-ARGs PI model has great potential to serve as a diagnostic or prognostic biomarker and therapeutic target in LIHC, which may guide future clinical applications to some extent and improve the outcome of LIHC patients.

scholarly journals Associations of Serum Tumor Biomarkers with Integrated Genomic and Clinical Characteristics of Hepatocellular Carcinoma

Liver Cancer ◽  
2021 ◽  
pp. 1-13
Author(s):  
Keun Soo Ahn ◽  
Daniel R. O’Brien ◽  
Yong Hoon Kim ◽  
Tae-Seok Kim ◽  
Hiroyuki Yamada ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Lens Culinaris ◽  
Acid Metabolism ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Genetic Profile ◽  
Vegf Signaling ◽  
The Usa ◽  
Cancer Genome Atlas ◽  
Liver Hepatocellular Carcinoma

<b><i>Introduction:</i></b> Serum α-fetoprotein (AFP), <i>Lens culinaris</i> agglutinin-reactive AFP (AFP-L3), and des-γ-carboxy­pro­thrombin (DCP) are useful biomarkers of hepatocellular carcinoma (HCC). However, associations among molecular characteristics and serum biomarkers are unclear. We analyzed RNA expression and DNA variant data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) to examine their associations with serum biomarker levels and clinical data. <b><i>Methods:</i></b> From 371 TCGA-LIHC patients, we selected 91 seen at 3 institutions in Korea and the USA and measured AFP, AFP-L3, and DCP from preoperatively obtained serum. We conducted an integrative clinical and molecular analysis, focusing on biomarkers, and validated the findings with the remaining 280 patients in the TCGA-LIHC cohort. <b><i>Results:</i></b> Patients were categorized into 4 subgroups: elevated AFP or AFP-L3 alone (↑AFP&amp;L3), elevated DCP alone (↑DCP), elevation of all 3 biomarkers (elevated levels of all 3 biomarkers [↑All]), and reference range values for all biomarkers (RR). <i>CTNNB1</i> variants were frequently observed in ↑DCP patients (53.8%) and RR patients (38.5%), but ↑DCP patients with a <i>CTNNB1</i> variant had worse survival than RR patients. <i>TP53</i> sequence variants were associated with ↑AFP (30.8%) and ↑DCP (30.8%). The Wnt-β-catenin signaling pathway was activated in the ↑AFP&amp;L3, whereas liver-related Wnt signaling was activated in the RR. TGF-β and VEGF signaling were activated in ↑AFP&amp;L3, whereas dysregulated bile acid and fatty acid metabolism were dominant in ↑DCP. We validated these findings by showing similar results between the test cohort and the remainder of the TCGA-LIHC cohort. <b><i>Conclusions:</i></b> Serum AFP, AFP-L3, and DCP levels can help predict variants in the genetic profile of HCC, especially for <i>TP53</i> and <i>CTNNB1</i>. These findings may facilitate development of an evidence-based approach to treatment.

scholarly journals An Immune-Related Gene Signature for Predicting Survival and Immunotherapy Efficacy in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Yifei Dai ◽  
Weijie Qiang ◽  
Kequan Lin ◽  
Yu Gui ◽  
Xun Lan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Prognostic Index ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Related Gene ◽  
Immune Related Gene ◽  
Clinicopathologic Factors ◽  
Immune Related Genes

Abstract Background: Hepatocellular carcinoma (HCC) ranks the fourth in terms of cancer-related mortality globally. Herein, in this research, we attempted to develop a novel immune-related gene signature that could predict survival and efficacy of immunotherapy for HCC patients.Methods: The transcriptomic and clinical data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) and GSE14520 datasets, followed by acquisition of immune-related genes from the ImmPort database. Afterwards, an immune-related gene-based prognostic index (IRGPI) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. Kaplan-Meier survival curves as well as time-dependent receiver operating characteristic (ROC) curve were performed to evaluate its predictive capability. Besides, both univariate and multivariate analysis on overall survival for the IRGPI and multiple clinicopathologic factors were carried out, followed by the construction of nomogram. Finally, we explored the possible correlation of IRGPI with immune cell infiltration or immunotherapy efficacy. Results: Analysis of 365 HCC samples identified 11 differentially expressed genes, which were selected to establish the IRGPI. Notably, it can predict survival of HCC patients more accurately than published biomarkers. Furthermore, IRGPI can predict the infiltration of immune cells in the tumor microenvironment of HCC, as well as the response of immunotherapy.Conclusion: Collectively, the currently established IRGPI can accurately predict survival, reflect the immune microenvironment, and predict the efficacy of immunotherapy among HCC patients.

scholarly journals Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Yinfang Li ◽  
Ling Zou ◽  
Xuejun Liu ◽  
Judong Luo ◽  
Hui Liu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Prognostic Index ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Risk Patients ◽  
Immune Related Genes

Background: Immune checkpoint inhibitor (ICI) therapy has been proved to be a promising therapy to many types of solid tumors. However, effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study is to build a novel immune-related prognostic index based on transcriptomic profiles.Methods: Weighted gene co-expression network analysis (WGCNA) was conducted to identify immune-related hub genes that are differentially expressed in HCC cohorts. Next, univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to detect hub genes associated to overall survival (OS). To validate the immune-related prognostic index, univariate and multivariate Cox regression analysis were performed. CIBERSORT and ESTIMATE were used to explore the tumor microenvironment and immune infiltration level.Results: The differential expression analysis detected a total of 148 immune-related genes, among which 25 genes were identified to be markedly related to overall survival in HCC patients. LASSO analysis yielded 10 genes used to construct the immune-related gene prognostic index (IRGPI), by which a risk score is computed to estimate low vs. high risk indicating the response to ICI therapy and prognosis. Further analysis confirmed that this immune-related prognostic index is an effective indicator to immune infiltration level, response to ICI treatment and OS. The IRGPI low-risk patients had better overall survival (OS) than IRGPI high-risk patients on two independent cohorts. Moreover, we found that IRGPI high-risk group was correlated with high TP53 mutation rate, immune-suppressing tumor microenvironment, and these patients acquired less benefit from ICI therapy. In contrast, IRGPI-low risk group was associated with low TP53 and PIK3CA mutation rate, high infiltration of naive B cells and T cells, and these patients gained relatively more benefit from ICI therapy.

scholarly journals Diagnostic and Prognostic Values of MANF Expression in Hepatocellular Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Jingyi He ◽  
Guangbing Li ◽  
Xihan Liu ◽  
Liye Ma ◽  
Peng Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prognostic Value ◽  
Regulatory Networks ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Characteristic Curve ◽  
Prognostic Indicator ◽  
Diagnostic Value ◽  
Expression Level ◽  
Kaplan Meier

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, and its prognosis is still poor. Mesencephalic astrocyte-derived neurotrophic factor (MANF) plays a key role in endoplasmic reticulum stress. ER stress plays a key role in HCC carcinogenesis. To confirm the clinical and prognostic value of MANF in HCC, we investigated the expression level of MANF in HCC as recorded in databases, and the results were verified by experiment. Survival analysis was probed by the Kaplan–Meier method. Cox regression models were used to ascertain the prognostic value of MANF in HCC tissue microarray. The diagnostic value of MANF in HCC was evaluated by receiver operating characteristic curve analysis. Potential correlation between MANF and selected genes was also analyzed. Results showed that MANF was overexpressed in HCC. Patients with high MANF expression levels had a worse prognosis and higher risk of tumor recurrence. Furthermore, the expression level of MANF had good diagnostic power. Correlation analysis revealed potential regulatory networks of MANF in HCC, laying a foundation for further study of the role of MANF in tumorigenesis. In conclusion, MANF was overexpressed in HCC and related to the occurrence and development of HCC. It is a potential diagnostic and prognostic indicator of HCC.

Assessment of miR-212 and Other Biomarkers in the Diagnosis and Treatment of HBV-infection-related Liver Diseases

2019 ◽  
Vol 20 (10) ◽  
pp. 785-798 ◽  
Author(s):  
Yigan Zhang ◽  
Huaze Xi ◽  
Xin Nie ◽  
Peng Zhang ◽  
Ning Lan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chronic Hepatitis ◽  
Liver Cancer ◽  
Hepatitis B ◽  
Chronic Hepatitis B ◽  
Liver Diseases ◽  
Meld Score ◽  
Hbv Infection ◽  
Expression Level ◽  
Control Group

Objective: Our study aims to detect the sensitivity of the new biomarker miR-212 existing in serum exosomes along with other hepatocellular carcinoma biomarkers such as AFP (alpha-fetoprotein), CA125 (carbohydrate antigen-ca125), and Hbx protein in the diagnosis of HBV-related liver diseases. We also aim to study the roles of these biomarkers in the progression of chronic hepatitis B and provide scientific data to show the clinical value of these biomarkers. Methods: We selected 200 patients with HBV-infection (58 cases of chronic hepatitis B, 47 cases of hepatocellular carcinoma, 30 cases of compensatory phase cirrhosis, and 65 cases of decompensatory phase cirrhosis), 31 patients with primary liver cancer without HBV infection, and 70 healthy individuals as the control group. The expression level of serum AFP and CA125 was detected with electrochemiluminescence immunoassay. The expression level of the Hbx protein was detected with ELISA. Meanwhile, the expression level of miR-212 in serum was analyzed with RT-qPCR. We collected patients’ clinical information following the Child-Pugh classification and MELD score criterion, and statistical analysis was made between the expression level of miR-212 and the collected clinical indexes. Lastly, we predicted the target genes of the miR-212 and its functions using bioinformatics methods such as cluster analysis and survival prediction. Results: Compared to the control group, the expression level of miR-212 in HBV infected patients was remarkably increased (P<0.05), especially between the HBV-infection Hepatocellular carcinoma group and the non-HBVinfection liver cancer group (P<0.05). The expression of miR-212 was increased in patients’ Child-Pugh classification, MELD score, and TNM staging. Moreover, the sensitivity and specificity of miR-212 were superior to AFP, CA125, and HBx protein. Conclusion: There is a linear relationship between disease progression and expression level of miR-212 in the serum of HBV infected patients. This demonstrates that miR-212 plays a significant role in liver diseases. miR-212 is expected to be a new biomarker used for the diagnosis and assessment of patients with HBV-infection-related liver diseases.

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