Prediction of Overall Survival Rate in Patients With Hepatocellular Carcinoma Using an Integrated Model Based on Autophagy Gene Marker

The autophagy cell, which can inhibit the formation of tumor in the early stage and can promote the development of tumor in the late stage, plays an important role in the development of tumor. Therefore, it has potential significance to explore the influence of autophagy-related genes (AAGs) on the prognosis of hepatocellular carcinoma (HCC). The differentially expressed AAGs are selected from HCC gene expression profile data and clinical data downloaded from the TCGA database, and human autophagy database (HADB). The role of AAGs in HCC is elucidated by GO functional annotation and KEGG pathway enrichment analysis. Combining with clinical data, we selected age, gender, grade, stage, T state, M state, and N state as Cox model indexes to construct the multivariate Cox model and survival curve of Kaplan Meier (KM) was drawn to estimate patients’ survival between high- and low-risk groups. Through an ROC curve drawn by univariate and multivariate Cox regression analysis, we found that seven genes with high expression levels, including HSP90AB1, SQSTM1, RHEB, HDAC1, ATIC, HSPB8, and BIRC5 were associated with poor prognosis of HCC patients. Then the ICGC database is used to verify the reliability and robustness of the model. Therefore, the prognosis model of HCC constructed by autophagy genes might effectively predict the overall survival rate and help to find the best personalized targeted therapy of patients with HCC, which can provide better prognosis for patients.

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Clinical factors affecting prognosis of limb osteosarcoma in China: a multicenter retrospective analysis

Journal of International Medical Research ◽

10.1177/0300060520920053 ◽

2020 ◽

Vol 48 (8) ◽

pp. 030006052093085

Author(s):

Jia Han ◽

Yiyang Yu ◽

Sujia Wu ◽

Zhen Wang ◽

Weibin Zhang ◽

...

Keyword(s):

Overall Survival ◽

Survival Rate ◽

Cox Regression ◽

Survival Rates ◽

Treatment Method ◽

Overall Survival Rate ◽

Clinical Factors ◽

Standard Chemotherapy ◽

Factors Affecting ◽

Cox Regression Analysis

Objective This study was performed to explore the relationship between various clinical factors and the prognosis of limb osteosarcoma. Methods We retrospectively analyzed the clinical data of 336 patients with limb osteosarcoma treated from June 2000 to August 2016 at 7 Chinese cancer centers. Data on the patients’ clinical condition, treatment method, complications, recurrences, metastasis, and prognosis were collected and analyzed. Kaplan–Meier analysis and Cox regression models were used to analyze the data. Results The patients comprised 204 males and 132 females ranging in age from 6 to 74 years (average, 21.1 years). The overall 3- and 5-year survival rates were 65.0% and 55.0%, respectively. The 5-year overall survival rate was 64.0% with standard chemotherapy and 45.6% with non-standard chemotherapy. Cox regression analysis demonstrated that standard chemotherapy, surgery, recurrence, and metastasis were independent factors associated with the prognosis of limb osteosarcoma. Conclusion The survival of patients with limb osteosarcoma can be significantly improved by combining standard chemotherapy and surgery. The overall survival rate can also be improved by adding methotrexate to doxorubicin–cisplatin–ifosfamide triple chemotherapy.

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Crosstalk between Activated and Inactivated c-Src in Hepatocellular Carcinoma

Disease Markers ◽

10.1155/2011/946295 ◽

2011 ◽

Vol 30 (6) ◽

pp. 325-333 ◽

Cited By ~ 8

Author(s):

Mei-Lin Chen ◽

Chee-Yin Chai ◽

Kun-Tu Yeh ◽

Shen-Nien Wang ◽

Chia-Jung Tsai ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Survival Rate ◽

Cox Regression ◽

Patient Survival ◽

Survival Curve ◽

Clinicopathological Characteristics ◽

Active State ◽

Overall Survival Rate ◽

Independent Prognostic Marker

C-Src activity is regulated by tyrosine phosphorylation at two distinct sites, Tyr416 and Tyr527, with opposite effects. However, the clinical roles of these sites in human cancers are not well defined. This study aims to determine whether the alterations and crosstalk of these two sites may contribute to hepatocellular carcinoma (HCC). Specimens from 85 patients who had undergone curative hepatectomy were collected for this study. The patterns of p-Tyr416-Src and p-Tyr527-Src, as well as the non-phosphorylated status for each site, were determined using immunohistochemistry and statistically correlated with clinicopathological characteristics and overall survival rate. The active state of c-Src, p-Tyr416-c-Src, was positively correlated with tumour grade (P= 0.062) but inversely correlated with vascular invasion (P= 0.071). Its non-phosphorylated status, non-p-Tyr416-c-Src, was positively correlated with tumour stage and grade (P= 0.041 and 0.020). The inactive state of c-Src, p-Tyr527-c-Src, was decreased in male patients but increased HCV-infected patients (P= 0.044 and 0.033). The Kaplan-Meier survival curve further showed that increased p-Tyr416-c-Src and decreased non-p-Tyr527-c-Src expression were associated with a poor patient survival rate (P= 0.004 and 0.025). Interestingly, the expression of non-p-Tyr416-c-Src was positively correlated with that of p-Tyr527-c-Src in the HCC lesions (P= 0.040). In addition, the patients with concomitantly low p-Tyr416-c-Src and non-p-Tyr527-c-Src expression had a prolonged overall survival rate (P= 0.030). A multivariable COX regression model showed that p-Tyr416-c-Src expression was an effective predictor for patient survival in HCC [OR = 3.78, 95%CI = 1.46–9.76;P= 0.006]. Our results suggest that the active state of c-Src, p-Tyr416-c-Src, may serve as an independent prognostic marker of patient survival in HCC. Relative levels of other phosphorylated or non-phosphorylated c-Src kinases may also present different statuses during HCC development and require further investigation.

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The relationship between RECK Gene Polymorphisms and the prognosis of cholangiocarcinoma

10.21203/rs.3.rs-44943/v1 ◽

2020 ◽

Author(s):

Ning Wang ◽

Yanni Li ◽

Yanfang Zheng ◽

Huoming Chen ◽

Xiaolong Wen ◽

...

Keyword(s):

Overall Survival ◽

Survival Rate ◽

Cox Regression ◽

Univariate Analysis ◽

Overall Survival Rate ◽

Chi Square ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Chi Square Test ◽

The Relationship

Abstract Background The study was designed to examine the reversion inducing cysteine rich protein with Kazal motifs (RECK) levels in patients with cholangiocarcinoma (CCA) and assess its role in CCA prognosis. Methods Quantitative real-time PCR (qRT-PCR) was used to determine the expression of RECK mRNA in 127 pairs of CCA samples and controls. Chi-square test was conducted to analyze the effects of clinical features on RECK expression. Kaplan-Meier curves were plotted to determine the overall survival rate of CCA patients with different RECK expression. The prognostic biomarkers for CCA patients were identified using the Cox regression analysis. Results Significantly down-regulated expression of RECK mRNA was determined in CCA tissues compared to noncancerous controls (P < 0.05). Chi-square test suggested reduced RECK expression was related with invasion depth (P = 0.026), differentiation (P = 0.025), lymphatic metastasis (P = 0.010) and TNM stage (P = 0.015). However, age, sex, tumor size and family history had no significant links with RECK expression (all, P > 0.05). The survival curves showed that patients with low RECK expression had a shorter overall survival rate than those with high RECK expression. Both the univariate analysis (P = 0.000, HR = 5.290, 95%CI = 3.195–8.758) and multivariate analysis (P = 0.000, HR = 5.376, 95%CI = 2.231–8.946) demonstrated that RECK was an independent biomarker for predicting the outcomes of CCA patients. Conclusions Taken together, the expression of RECK was down-regulated in CCA and it might be an efficient biomarker for CCA patients.

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Identification of Biomarkers of Hepatocellular Carcinoma Gene Prognosis Based on Immune-Related lncRNA Signature of Transcriptome Data

10.21203/rs.3.rs-57303/v1 ◽

2020 ◽

Author(s):

Andi Ma ◽

Yukai Sun ◽

Racheal O. Ogbodu ◽

Ling Xiao ◽

Haibing Deng ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Cox Regression ◽

Risk Group ◽

Enrichment Analysis ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Pathway Enrichment Analysis ◽

Cox Regression Analysis

Abstract Background: It is well known that long non-coding RNAs (lncRNAs) play a vital role in cancer. We aimed to explore the prognostic value of potential immune-related lncRNAs in hepatocellular carcinoma (HCC). Methods: Validated the established lncRNA signature of 343 patients with HCC from The Cancer Genome Atlas (TCGA) and 81 samples from Gene Expression Omnibus (GEO). Immune-related lncRNAs for HCC prognosis were evaluated using Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. LASSO analysis was performed to calculate a risk score formula to explore the difference in overall survival between high- and low-risk groups in TCGA, which was verified using GEO, Gene Ontology (GO), and pathway-enrichment analysis. These analyses were used to identify the function of screened genes and construct a co-expression network of these genes. Results: Using computational difference algorithms and lasso Cox regression analysis, the differentially expressed and survival-related immune-related genes (IRGs) among patients with HCC were established as five novel immune-related lncRNA signatures (AC099850.3, AL031985.3, PRRT3-AS1, AC023157.3, MSC-AS1). Patients in the low‐risk group showed significantly better survival than patients in the high‐risk group ( P = 3.033e−05). The signature identified can be an effective prognostic factor to predict patient survival. The nomogram showed some clinical net benefits predicted by overall survival. In order to explore its underlying mechanism, several methods of enrichment were elucidated using Gene Set Enrichment Analysis. Conclusion: Identifying five immune-related lncRNA signatures has important clinical implications for predicting patient outcome and guiding tailored therapy for patients with HCC with further prospective validation.

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

PeerJ ◽

10.7717/peerj.11273 ◽

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.

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Surgical Resection Significantly Promotes the Overall Survival of Patients with Hepatocellular Carcinoma: A Propensity Score Matching Analysis

10.21203/rs.3.rs-148506/v1 ◽

2021 ◽

Author(s):

Pei-Min Hsieh ◽

Hung-Yu Lin ◽

Chao-Ming Hung ◽

Gin-Ho Lo ◽

I-Cheng Lu ◽

...

Keyword(s):

Risk Factors ◽

Hepatocellular Carcinoma ◽

Overall Survival ◽

Propensity Score ◽

Propensity Score Matching ◽

Surgical Resection ◽

Cox Regression ◽

Survival Rates ◽

Hbv Infection ◽

Cox Regression Analysis

Abstract Background: The benefits of surgical resection (SR) for various Barcelona Clinic Liver Cancer (BCLC) stages of hepatocellular carcinoma (HCC) remain unclear. We investigated the risk factors of overall survival (OS) and survival benefits of SR over nonsurgical treatments in patients with HCC of various BCLC stages.Methods: Overall, 2316 HCC patients were included, and their clinicopathological data and OS were recorded. OS was analyzed by the Kaplan-Meier method and Cox regression analysis. Propensity score matching (PSM) analysis was performed.Results: In total, 66 (2.8%), 865 (37.4%), 575 (24.8%) and 870 (35.0%) patients had BCLC stage 0, A, B, and C disease, respectively. Furthermore, 1302 (56.2%) of all patients, and 37 (56.9%), 472 (54.6%), 313 (54.4%) and 480 (59.3%) of patients with BCLC stage 0, A, B, and C disease, respectively, died. The median follow-up duration time was 20 (range 0-96) months for the total cohort and was subdivided into 52 (8-96), 32 (1-96), 19 (0-84), and 12 (0-79) months for BCLC stages 0, A, B, and C cohorts, respectively. The risk factors for OS were 1) SR and cirrhosis; 2) SR, cirrhosis, and Child-Pugh (C-P) class; 3) SR, hepatitis B virus (HBV) infection, and C-P class; and 4) SR, HBV infection, and C-P class for the BCLC stage 0, A, B, and C cohorts, respectively. Compared to non-SR treatment, SR resulted in significantly higher survival rates in all cohorts. The 5-year OS rates for SR vs non-SR were 44.0% vs 28.7%, 72.2% vs 42.6%, 42.6% vs 36.2, 44.6% vs 23.5%, and 41.4% vs 15.3% (all p-values<0.05) in the total and BCLC stage 0, A, B, and C cohorts, respectively. After PSM, SR resulted in significantly higher survival rates compared to non-SR treatment in various BCLC stages.Conclusion: SR conferred significant survival benefits to patients with HCC of various BCLC stages and should be considered a recommended treatment for select HCC patients, especially patients with BCLC stage B and C disease.

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Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma

Technology in Cancer Research & Treatment ◽

10.1177/15330338211041425 ◽

2021 ◽

Vol 20 ◽

pp. 153303382110414

Author(s):

Xiaoyong Li ◽

Jiaqong Lin ◽

Yuguo pan ◽

Peng Cui ◽

Jintang Xia

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Regression Analysis ◽

Prognostic Model ◽

Cox Regression ◽

Risk Group ◽

Gene Signature ◽

Regression Analyses ◽

Related Gene ◽

Cox Regression Analysis

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.

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Establishment and Validation of an MTORC1 Signaling-Related Gene Signature to Predict Overall Survival in Patients with Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2021/6299472 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Zheng Yao ◽

Song Wen ◽

Jun Luo ◽

Weiyuan Hao ◽

Weiren Liang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Decision Tree ◽

Survival Data ◽

Cox Regression ◽

Gene Signature ◽

Related Gene ◽

Cox Regression Analysis ◽

Cancer Hallmarks ◽

Mtorc1 Signaling

Background. Accurate and effective biomarkers for the prognosis of patients with hepatocellular carcinoma (HCC) are poorly identified. A network-based gene signature may serve as a valuable biomarker to improve the accuracy of risk discrimination in patients. Methods. The expression levels of cancer hallmarks were determined by Cox regression analysis. Various bioinformatic methods, such as GSEA, WGCNA, and LASSO, and statistical approaches were applied to generate an MTORC1 signaling-related gene signature (MSRS). Moreover, a decision tree and nomogram were constructed to aid in the quantification of risk levels for each HCC patient. Results. Active MTORC1 signaling was found to be the most vital predictor of overall survival in HCC patients in the training cohort. MSRS was established and proved to hold the capacity to stratify HCC patients with poor outcomes in two validated datasets. Analysis of the patient MSRS levels and patient survival data suggested that the MSRS can be a valuable risk factor in two validated datasets and the integrated cohort. Finally, we constructed a decision tree which allowed to distinguish subclasses of patients at high risk and a nomogram which could accurately predict the survival of individuals. Conclusions. The present study may contribute to the improvement of current prognostic systems for patients with HCC.

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Treatments for the early stage Hepatocellular Carcinoma: Laparoscopic Liver Resection or Percutaneous Radiofrequency, How to make the decision?

Liver Cancer ◽

10.1159/000521136 ◽

2021 ◽

Author(s):

Jinli Zheng ◽

Wei Xie ◽

Yunfeng Zhu ◽

Li Jiang

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Survival Rate ◽

Liver Resection ◽

Complication Rate ◽

Early Stage ◽

Line Treatment ◽

Overall Survival Rate ◽

First Line ◽

First Line Treatment

Hepatectomy is still as the first-line treatment for the early stage HCC, but the complication rate is higher than p-RFA and the overall survival rate is comparable in these two treatments. Therefore, the patients with small single nodular HCCs could get more benefit from p-RFA, and we need to do further research about p-RFA.

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Decreased Expression of KPNA2 in Hepatocellular Carcinoma Infers Favorable Prognosis and High Immune Infiltrating Level

10.21203/rs.3.rs-691618/v1 ◽

2021 ◽

Author(s):

kangming zhu ◽

yvndi zhang ◽

hui yvan ◽

jing li

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Logistic Regression ◽

Survival Rate ◽

Western Blotting ◽

Good Prognosis ◽

Overall Survival Rate ◽

Pathological Stage ◽

Down Regulation ◽

Immune Infiltration

Abstract BackgroundLiver hepatocellular carcinoma (LIHC) is an important pathological type of liver cancer. The immune infiltration of the tumor microenvironment is negatively correlated with the overall survival rate of LIHC. At present , the role and molecular mechanism of KPNA2 in LIHC have not been elucidated, and the prognostic correlation between the two and the immune infiltration of LIHC are still unclear. Our study evaluated the role of KPNA2 in LIHC through TCGA data.MethodGene expression profiling interactive analysis (GEPIA) is used to analyze the expression of KPNA2 in LIHC. We evaluated the impact of KPNA2 on the survival of LIHC patients through the survival module. Then, We downloaded the LIHC data set from TCGA. Logistic regression was used to analyze the correlation between clinical information and KPNA2 expression. Cox regression analysis was used to analyze the clinicopathological characteristics related to the overall survival rate of TCGA patients. In addition, we used the "correlation" modules of CIBERSORT and GEPIA to explore the correlation between KPNA2 and cancer immune infiltrate. Western blotting was used to detect the expression of KPNA2.ResultUsing logistic regression for univariate analysis, increased KPNA2 expression was significantly correlated with pathological stage, tumor status, and lymph node status. In addition, multivariate analysis showed that down-regulation of KPNA2 expression, negative pathological stage and distant metastasis are independent prognostic factors for good prognosis. Specifically, CIBERSORT analysis was used to establish a negative correlation between the up-regulated expression of KPNA2 and the level of immune infiltration of B cells, NK cells, mast cells, and T cells. In addition, we confirmed this in the "Association" module of GEPIA. The expression of KPNA2 in LIHC tissues was significantly lower than that in adjacent normal tissues by western blotting.ConclusionThe down-regulation of KPNA2 expression is associated with a good prognosis and an increase in the proportion of immune cells in LIHC. These conclusions indicate that KPNA2 is related to the level of immune infiltration of LIHC and can be used as a potential prognostic biomarker of LIHC and a potential target for clinical tumor treatment.

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