scholarly journals Identifying Apoptosis-Related Transcriptomic Aberrations and Revealing Clinical Relevance as Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Jinyu Zhu ◽  
Bufu Tang ◽  
Xiuling Lv ◽  
Miaomiao Meng ◽  
Qiaoyou Weng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Rna Sequencing ◽  
Cox Regression ◽  
Risk Group ◽  
Early Stage ◽  
Prognostic Signature ◽  
Sequencing Data ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker ◽  
Diagnostic Models

In view of the unsatisfactory treatment outcome of liver cancer under current treatment, where the mortality rate is high and the survival rate is poor, in this study we aimed to use RNA sequencing data to explore potential molecular markers that can be more effective in predicting diagnosis and prognosis of hepatocellular carcinoma. RNA sequencing data and corresponding clinical information were obtained from multiple databases. After matching with the apoptotic genes from the Deathbase database, 14 differentially expressed human apoptosis genes were obtained. Using univariate and multivariate Cox regression analyses, two apoptosis genes (BAK1 and CSE1L) were determined to be closely associated with overall survival (OS) in HCC patients. And subsequently experiments also validated that knockdown of BAK1 and CSE1L significantly inhibited cell proliferation and promoted apoptosis in the HCC. Then the two genes were used to construct a prognostic signature and diagnostic models. The high-risk group showed lower OS time compared to low-risk group in the TCGA cohort (P < 0.001, HR = 2.11), GSE14520 cohort (P = 0.003, HR = 1.85), and ICGC cohort (P < 0.001, HR = 4). And the advanced HCC patients showed higher risk score and worse prognosis compared to early-stage HCC patients. Moreover, the prognostic signature was validated to be an independent prognostic factor. The diagnostic models accurately predicted HCC from normal tissues and dysplastic nodules in the training and validation cohort. These results indicated that the two apoptosis-related signature effectively predicted diagnosis and prognosis of HCC and may serve as a potential biomarker and therapeutic target for HCC.

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.

A novel signature based on m6A related genes as the potential prognostic factor in hepatocellular carcinoma.

2020 ◽  
Author(s):  
Zhuomao Mo ◽  
Shaoju Luo ◽  
Hao Hu ◽  
Ling Yu ◽  
Zhirui Cao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Immune Therapy ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Potential Biomarker ◽  
Significant Difference

Abstract Background Many different signatures and models have been established for patients with hepatocellular carcinoma (HCC), but no signature based on m6A related genes was developed. The objective of this research was to establish the signature with m6A related genes in HCC. Methods Data from 377 HCC patients from The Cancer Genome Atlas (TCGA) database was downloaded. The included m6A related genes were selected by Cox regression analysis and the signature was verified by survival analysis and multiple receiver operating characteristic (ROC) curve. Furthermore, the nomogram was constructed and evaluated by C-index, calibration plot and ROC curve. Results The signature was established with the four m6A related genes (YTHDF2, YTHDF1, METTL3 and KIAA1429). Under the grouping from signature, patients in high risk group of showed the poor prognosis than those in low risk group. And significant difference was found in two kinds of immune cells (T cell gamma delta and NK cells activated) between two groups. The univariate and multivariate Cox regression analysis indicated that m6A related signature can be the potential independent prognosis factor in HCC. Finally, we developed a clinical risk model predicting the HCC prognosis and successfully verified it in C-index, calibration and ROC curve. Conclusion Our study identified the m6A related signature for predicting prognosis of HCC and provided the potential biomarker between m6A and immune therapy.

scholarly journals A Novel Pyroptosis-related Genes Prognostic Signature Affects the Immune Infiltration Patterns in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Yiqun Jin ◽  
Bai. Xue-song
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Checkpoint ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Gene Set Enrichment

Abstract PurposePyroptosis is an inflammatory form of cell death associated with tumorigenesis and progression. However, the prognostic value of pyroptosis-related genes (PRGs) in hepatocellular carcinoma (HCC) have not been elucidated.MethodsWe downloaded mRNA expression profiles and clinical information from TCGA and ICGC database. Then, differently expressed PRGs were screened to construct a multigene prognostic signature by least absolute contraction and selection operator (LASSO) Cox regression method in TCGA cohort. Date from ICGC was used to validate the robustness of this signature. Kaplan-Meier analysis was used to compare overall survival (OS) between high- and low-risk group. Univariate and multivariate Cox analysis were performed to identify the independent prognostic value of the signature. Gene set enrichment analysis (GSEA) was utilized to conduct GO and KEGG analysis. Single-sample gene set enrichment analysis was implemented to assess the immune cell infiltration and immune-related function. TIDE algorithm evaluated the significance of this signature in predicting immunotherapeutic sensitivity. ResultsAn 8-PRGs prognostic model was established. The OS of low-risk group was significantly increased compared to high-risk group. Receiver operating characteristic curve showed the model had a good prognostic predictive accuracy. Cox regression analysis proved the model an independent predictor for OS in HCC. GSEA indicated that the risk score was associated with immune response. Furthermore, different subgroups exhibited different immunoinfiltration patterns, different immune-checkpoint levels and different potential responses for immune-checkpoint blockade therapy.ConclusionAn 8-PRGs signature can predict the prognosis of HCC patients and may act as an immunotherapeutic potential target for HCC.

13-lncRNAs Signature to Improve Diagnostic and Prognostic Prediction of Hepatocellular Carcinoma

2020 ◽  
Vol 23 ◽  
Author(s):  
Xinxin Zhang ◽  
Jia Yu ◽  
Juan Hu ◽  
Fang Tan ◽  
Juan Zhou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Survival Curve ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Survival Prediction ◽  
Diagnostic Model ◽  
Diagnosis And Prognosis ◽  
Potential Marker

Background: Hepatocellular carcinoma (HCC) is a common cancer with a high mortality rate and is usually detected at middle or late stage, missing the optimal treatment period. The current study aims to identify potential long noncoding RNAs (lncRNAs) biomarkers that contribute to diagnosis and prognosis of HCC. Method: The differentially expressed lncRNAs (DElncRNAs) in HCC patients were detected from the Cancer Genome Atlas (TCGA) dataset. LncRNAs signature was screened by LASSO regression, univariate and multivariate Cox regression. The models for predicting diagnosis and prognosis were established respectively. The prognostic model was evaluated by Kaplan-Meier survival curve receiver operating characteristic (ROC) curve and stratified analysis. The diagnostic model was validated by ROC. The lncRNAs signature was further demonstrated by functional enrichment analysis. Results: We found the 13-lncRNAs signature that had a good performance in predicting prognosis and could help to improve the value of diagnosis. In the training set, testing set and entire cohort, the low risk group had longer survival than the high risk group (median OS: 3124 vs 649 days, 2456 vs 770 days and 3124 vs 755 days ). It performed well in 1-, 3-, and 5- year survival prediction. 13-lncRNAs-based risk score, age and race were good predictors of prognosis. The AUC of diagnosis were 0.9487, 0.9265 and 0.9376 respectively. Meanwhile the 13-lncRNAs were involved in important pathways including the cell cycle and multiple metabolic pathways. Conclusion: In our study, the 13-lncRNAs signature may be a potential marker for prognosis of HCC and improve the diagnosis.

scholarly journals Prognostic Values of Stabilin-2 in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhicheng Du ◽  
Pengfei Zhu ◽  
Long Yu ◽  
Kunlun Chen ◽  
Janwen Ye ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Survival Time ◽  
Cox Regression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Primary Malignancy ◽  
Diagnosis And Prognosis ◽  
Kaplan Meier ◽  
Potential Biomarker

Abstract Background: Hepatocellular carcinoma (HCC) is the primary malignancy of the liver. However, biomarkers for early HCC diagnosis are not available. Stabilin (STAB) proteins are scavenger receptors involved in apoptosis and clearance of hyaluronic acid .The role of STAB in HCC has not been previously explored; therefore, the aim of this study was to assess whether STAB gene expression can be used as a novel HCC biomarker.Materials and Methods: Data on 370 HCC patients in the Cancer Genome Atlas database and 221 patients in the Gene Expression Comprehensive Database were retrieved and analyzed. Kaplan–Meier analysis and Cox regression model were used to calculate median survival time using hazard ratio (HR) and 95% confidence interval (CI). Results: The Gene Expression Omnibus dataset showed that high Stabilin-2（STAB2） expression implies longer overall survival (HR after correction = 0.541; 95% CI, 0.339–0.865; p = 0.0182, after correction p = 0.010) and longer recurrence-free survival time (adjusted HR = 0.554; 95% CI, 0.376-0.816; p = 0.0085, adjusted p = 0.003). Conclusions: STAB2 is a potential biomarker for the diagnosis and prognosis of HCC.

scholarly journals A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongdong Zhou ◽  
Xiaoli Liu ◽  
Xinhui Wang ◽  
Fengna Yan ◽  
Peng Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Surgical Therapy ◽  
Calibration Curve ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Alpha Fetoprotein ◽  
Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

scholarly journals Clinical value evaluation of microRNA-324-3p and other available biomarkers in patients with HBV-infection-related hepatocellular carcinoma

2021 ◽  
Author(s):  
Li Zhao ◽  
Qian Yang ◽  
Jianbo Liu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Hepatitis B ◽  
Diagnostic Performance ◽  
Cox Regression ◽  
Hbv Infection ◽  
Healthy Controls ◽  
Survival Prognosis ◽  
Diagnosis And Prognosis ◽  
Hcc Cells

Abstract Background Patients with hepatitis B virus (HBV) infection are at high risk of hepatocellular carcinoma (HCC). This study aimed to evaluate the expression of microRNA-324-3p (miR-324-3p) in HBV-related HCC, and explore the clinical significance of serum miR-324-3p and other available biomarkers in the diagnosis and prognosis of HBV-related HCC. Methods Expression of miR-324-3p in HBV-infection-related cells and patients was estimated using quantitative real-time PCR. The receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance of serum miR-324-3p, AFP and PIVKA-II in the differentiation of HBV-related HCC from healthy controls and chronic hepatitis B (CHB). The relationship between serum miR-324-3p and patients’ clinical features was assessed using Chi-square test, and the value of miR-324-3p to predict overall survival prognosis was evaluated using Kaplan-Meier methods and Cox regression assay in patients with HBV-related HCC. Results HBV-related HCC cells had significantly increased miR-324-3p compared with normal and HBV-unrelated HCC cells, and serum miR-324-3p in HCC patients with HBV infection was also higher than that in healthy controls and CHB. Serum miR-324-3p had relatively high diagnostic accuracy for the screening of HCC case with HBV infection, and the combination of miR-324-3p, AFP and PIVKA-II showed the improved diagnostic performance. Additionally, high serum miR-324-2p in HBV-related HCC patients was associated with cirrhosis, tumor size, clinical stage and poor overall survival prognosis. Conclusion Serum increased miR-324-3p may be involved in the progression of HBV-related hepatitis to HCC, and may serve as a candidate biomarker for the diagnosis and prognosis of HBV-related HCC.

scholarly journals Identification of BHLHE40 expression in peripheral blood mononuclear cells as a novel biomarker for diagnosis and prognosis of hepatocellular carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pattapon Kunadirek ◽  
Chaiyaboot Ariyachet ◽  
Supachaya Sriphoosanaphan ◽  
Nutcha Pinjaroen ◽  
Pongserath Sirichindakul ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Peripheral Blood Mononuclear Cells ◽  
Peripheral Blood ◽  
Mononuclear Cells ◽  
Early Stage ◽  
High Sensitivity ◽  
Peripheral Blood Mononuclear ◽  
Diagnosis And Prognosis ◽  
Transcription Profiles ◽  
Blood Mononuclear Cells

AbstractNovel and sensitive biomarkers is highly required for early detection and predicting prognosis of hepatocellular carcinoma (HCC). Here, we investigated transcription profiles from peripheral blood mononuclear cells (PBMCs) of 8 patients with HCC and PBMCs from co-culture model with HCC using RNA-Sequencing. These transcription profiles were cross compared with published microarray datasets of PBMCs in HCC to identify differentially expressed genes (DEGs). A total of commonly identified of 24 DEGs among these data were proposed as cancer-induced genes in PBMCs, including 18 upregulated and 6 downregulated DEGs. The KEGG pathway showed that these enriched genes were mainly associated with immune responses. Five up-regulated candidate genes including BHLHE40, AREG, SOCS1, CCL5, and DDIT4 were selected and further validated in PBMCs of 100 patients with HBV-related HCC, 100 patients with chronic HBV infection and 100 healthy controls. Based on ROC analysis, BHLHE40 and DDIT4 displayed better diagnostic performance than alpha-fetoprotein (AFP) in discriminating HCC from controls. Additionally, BHLHE40 and DDIT4 had high sensitivity for detecting AFP-negative and early-stage HCC. BHLHE40 was also emerged as an independent prognostic factor of overall survival of HCC. Together, our study indicated that BHLHE40 in PBMCs could be a promising diagnostic and prognostic biomarker for HBV-related HCC.

scholarly journals A genomic mutation signature predicts the clinical outcomes of immunotherapy and characterizes immunophenotypes in gastrointestinal cancer

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Xi Jiao ◽  
Xin Wei ◽  
Shuang Li ◽  
Chang Liu ◽  
Huan Chen ◽  
...  
Keyword(s):  
Gastrointestinal Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Cancer Center ◽  
Genomic Profile ◽  
Prognostic Signature ◽  
Powerful Predictor ◽  
Potential Biomarker ◽  
Peking University

AbstractThe association between genetic variations and immunotherapy benefit has been widely recognized, while such evidence in gastrointestinal cancer remains limited. We analyzed the genomic profile of 227 immunotherapeutic gastrointestinal cancer patients treated with immunotherapy, from the Memorial Sloan Kettering (MSK) Cancer Center cohort. A gastrointestinal immune prognostic signature (GIPS) was constructed using LASSO Cox regression. Based on this signature, patients were classified into two subgroups with distinctive prognoses (p < 0.001). The prognostic value of the GIPS was consistently validated in the Janjigian and Pender cohort (N = 54) and Peking University Cancer Hospital cohort (N = 92). Multivariate analysis revealed that the GIPS was an independent prognostic biomarker. Notably, the GIPS-high tumor was indicative of a T-cell-inflamed phenotype and immune activation. The findings demonstrated that GIPS was a powerful predictor of immunotherapeutic survival in gastrointestinal cancer and may serve as a potential biomarker guiding immunotherapy treatment decisions.

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