14-CpG-Based Signature Improves the Prognosis Prediction of Hepatocellular Carcinoma Patients

Background. Epigenetic dysregulation via alteration of DNA methylation often occurs during the development and progression of cancer, including hepatocellular carcinoma (HCC). In the past, many patterns of single-gene DNA methylation have been extensively explored in the context of HCC prognosis prediction. However, the combined model of a mixture of CpGs has rarely been evaluated. In the present study, we aimed to develop and validate a CpG-based signature model for HCC patient prognosis. Methods. Data from methylation profiling of GSE73003, GSE37988, and GSE57958 from the Gene Expression Omnibus (GEO) database and 371 HCC patients from the Cancer Genome Atlas (TCGA) were downloaded. The 371 HCC patients were randomly divided into a development cohort (N = 263) and a validation cohort (N = 108). Two algorithms, least absolute shrinkage and selection operator (LASSO) and robust likelihood-based survival analysis, were used to select the most significant CpGs associated with overall survival (OS) time and were used to develop and validate a methylation-based signature (MSH) for HCC patient prognosis. In addition, the prognostic efficacy of the MSH was compared with that of AJCC TNM classification and other CpG-based MSHs from TCGA. Finally, a nomogram incorporating the MSH and clinicopathologic factors was also developed. Results. Fourteen differential CpGs associated with OS were identified in HCC patients. The MSH, based on these 14 differential CpGs, could effectively divide HCC patients into two distinct subgroups with high risk or low risk of death (P<0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56–5.90, P<0.0001) and in the validation cohort (40.37 vs 107.03 months, HR = 2.23, 95% CI: 1.22–4.17, P=0.01). Univariate analysis showed that the MSH was significantly associated with OS, and the multivariate analysis also showed that the MSH was an independent prognostic factor for the OS of HCC patients in the two cohorts. In addition, stratified survival analysis indicated that the MSH still exhibited good prognostic value in different subgroups classified by AFP, cirrhosis, Child-Pugh A, tumor histologic grade, and AJCC stage. Moreover, time-dependent ROC analysis showed better performance of the MSH in predicting 3-year and 5-year survival of HCC patients than of AJCC stage and other CpG-based signatures from TCGA. The MSH-based nomogram also performed well in predicting 1-year, 3-year, and 5-year OS (C-index: 0.709). Conclusion. The 14-CpG-based signature is significantly associated with OS and may be used as a novel prognostic biomarker for HCC patients.

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Risk of Death due to Hepatocellular Carcinoma among Smokers and Ex-smokers. Univariate Analysis of JACC Study Data

The Kurume Medical Journal ◽

10.2739/kurumemedj.51.71 ◽

2004 ◽

Vol 51 (1) ◽

pp. 71-81 ◽

Cited By ~ 9

Author(s):

ITSURO OGIMOTO ◽

AKIRA SHIBATA ◽

YOUICHI KUROZAWA ◽

TAKAYUKI NOSE ◽

TAKESUMI YOSHIMURA ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Univariate Analysis ◽

Study Data ◽

Risk Of Death

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Dietary Habits and Risk of Death due to Hepatocellular Carcinoma in a Large Scale Cohort Study in Japan. Univariate Analysis of JACC Study Data

The Kurume Medical Journal ◽

10.2739/kurumemedj.51.141 ◽

2004 ◽

Vol 51 (2) ◽

pp. 141-149 ◽

Cited By ~ 55

Author(s):

YOUICHI KUROZAWA ◽

ITSURO OGIMOTO ◽

AKIRA SHIBATA ◽

TAKAYUKI NOSE ◽

TAKESUMI YOSHIMURA ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cohort Study ◽

Large Scale ◽

Dietary Habits ◽

Univariate Analysis ◽

Study Data ◽

Risk Of Death

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miRNA Profiling Predicts Survival and Identifies a Novel Putative Oncomir in Diffuse Large B-Cell Lymphoma Treated with Immunochemotherapy

Blood ◽

10.1182/blood.v120.21.1548.1548 ◽

2012 ◽

Vol 120 (21) ◽

pp. 1548-1548

Author(s):

Christoffer Hother ◽

Ditte Reker ◽

Konstantions Dimopoulos ◽

Steen Knudsen ◽

Thomas Jensen ◽

...

Keyword(s):

Survival Analysis ◽

B Cell ◽

Alternative Treatment ◽

Cell Lymphoma ◽

Univariate Analysis ◽

B Cell Lymphoma ◽

Treatment Modalities ◽

Large B Cell Lymphoma ◽

Robust Likelihood ◽

Large B Cell

Abstract Abstract 1548 Introduction: The introduction of Rituximab as supplement to chemotherapy has significantly improved outcome in diffuse large B-cell lymphoma (DLBCL). Still, a fraction of patients are resistant or relapse shortly after treatment. Improved stratification of patients with DLBCL for standard immunochemotherapy or alternative treatment strategies is therefore urgently needed. Although DLBCL profiling based on mRNA expression may be helpful, this has not proven clinically efficient, and the prognostic value of immunohistochemical algorithms is controversial. In addition, novel therapeutic options are essential since the current alternative treatment modalities are often not curative. MicroRNAs (miRs) are particularly attractive molecules for clinical use since they are well conserved in formalin fixed paraffin embedded (FFPE) tissue, and novel data imply that they may be targeted directly in the patients. Materials and methods: RNA was extracted from diagnostic biopsies from DLBCL patients (n=97) treated uniformly with immunochemotherapy (R-CHOP n=80 or R-CHOEP n=17). GCB/non-GCB profiling was done by immunohistochemistry according to the Hans classification. MiR profiles were generated using Affymetrix microRNA version 1.0 arrays. Data analyses were performed using R/biocondutor and the webtool “SignS” that uses parallel computing for finding survival related genes and signatures from gene-expression datasets. Survival analysis was performed in R using the survival package. Univariate analysis was performed by comparing Kaplan-Meier survival estimates using Log-rank test. Cox proportional hazards regression model was used for multivariate analysis. Results and discussion: The median follow-up time for all patients was 3.4 years. The estimated 3-year over all survival probability was 82.8% (95% CI: 75.4%-90.9%). No difference in survivability was observed between the R-CHOP and the R-CHOEP treated cohort (P=0.145). High IPI (> 2) was significantly associated with inferior overall survival (OS, P = 0.038), but not progression free survival (PFS, P = 0.083). Univariate analysis showed that in this cohort the Hans classification was not prognostic (P=0.73; (52 GBC and 37 non-GCB subtypes; 8 NA)). Seven miRs were differentially regulated between GCB and non-GCB using a cutoff of P< 0.05. Five miRs were upregulated in non-GCB lymphomas: miR-625, miR-222, miR-221, miR-155 and miR-503, two were downregulated (miR-181a, miR-181b). For survival analysis, we initially applied a multivariate approach (Robust likelihood-based survival modeling, RBsurv), which identified a subset of miRs that significantly associates with poor survival. These include one upregulated miR, and four down regulated miRs. In order to obtain cross validated survival estimates, we applied three different algorithms; FCSM(SignS), TGD(SignS) and GLMboost(SignS) to the same sample set. These combined bioinformatic models identified a total of 17 deregulated miRs that significantly associate with survival. Among these, 9 are predicted by more that one algorithm, and interestingly, all 4 models identify a novel upregulated and potential oncogenic miR in patients treated by immunochemotherapy. When the cross-validated predictors were combined into a unified robust “miR-survival-predictor”, the performance is as good as, or even better, than the IPI. In addition, our model is a superior predictor of survival than the GCB/non-GCB classification according to Hans. Our data are currently being validated in a test set of 60 patients, and functional studies of the novel putative oncomiR are ongoing. Disclosures: No relevant conflicts of interest to declare.

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The Prognostic Correlation of Heart Rate Variability at Diagnosis with Survival of Patients with Hepatocellular Carcinoma

Diagnostics ◽

10.3390/diagnostics11050890 ◽

2021 ◽

Vol 11 (5) ◽

pp. 890

Author(s):

Ana-Maria Ciurea ◽

Dan Ionuț Gheonea ◽

Michael Schenker ◽

Alina Maria Mehedințeanu ◽

Georgică Costinel Târtea ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Heart Rate ◽

Heart Rate Variability ◽

Tumor Size ◽

Cox Regression ◽

Univariate Analysis ◽

Early Therapy ◽

Reactive Protein ◽

Risk Of Death ◽

Noninvasive Biomarker

Background: Heart rate variability (HRV) indices have been shown to be associated with prognosis in various types of cancer. This study aims to assess the ability of these indices to predict survival in hepatocellular carcinoma (HCC) patients after diagnosis. Methods: We retrospectively collected data from 231 patients diagnosed with HCC between January 2014 and March 2018. The baseline clinical-pathological variables and HRV indices (extracted from Holter electrocardiogram recordings) were analyzed. Results: Univariate and multivariate analyses were performed to identify the predictive value of the above factors for overall survival (OS). The univariate analysis revealed that an age > 60 years, hepatitis C, portal vein involvement (thrombosis), a tumor size > 5 cm, alpha-fetoprotein (AFP) > 400 ng/mL, serum albumin, and C-reactive protein (CRP) were risk factors for poor OS. Multivariable Cox regression analyses identified that a tumor size > 5 cm and AFP > 400 ng/mL predict poorer outcomes in HCC patients. It should be mentioned that, in both the univariate analysis and in the multivariate analysis, between HRV indices, SDNN (standard deviation of all normal-to-normal (NN) intervals) < 110 ms was an independent risk factor for OS with an HR of 3.646 (95% CI 2.143 to 6.205). Conclusion: This study demonstrates that HRV indices identify HCC patients at high risk of death and suggests that such monitoring might guide the need for early therapy in these types of patients, as well as the fact that HRV can be a potential noninvasive biomarker for HCC prognosis.

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Identification of Methylation-Regulated Differentially Expressed Genes and Related Pathways in Hepatocellular Carcinoma: A Study Based on TCGA Database and Bioinformatics Analysis

Frontiers in Oncology ◽

10.3389/fonc.2021.636093 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yu Liang ◽

Bin Ma ◽

Peng Jiang ◽

Hong-Mei Yang

Keyword(s):

Hepatocellular Carcinoma ◽

Dna Methylation ◽

Survival Analysis ◽

Differentially Expressed Genes ◽

Kegg Pathway ◽

Excision Repair ◽

Methylation Status ◽

Differentially Expressed ◽

Kaplan Meier ◽

Pathway Analyses

BackgroundIn recent years, DNA methylation modification has been shown to be a critical mechanism in the field of epigenetics.MethodsHepatocellular carcinoma (HCC) data were obtained from The Cancer Genome Atlas project, including RNA expression profiles, Illumina Human Methylation 450K BeadChip data, clinical information, and pathological features. Then, differentially expressed genes (DEGs) and differentially methylated genes were identified using R software. Methylation-regulated DEGs (MeDEGs) were further analyzed using Spearman’s correlation analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database and ClueGO in Cytoscape software. Kaplan–Meier survival analysis explored the relationship between methylation, expression of MeDEGs, and survival time. Gene set enrichment analysis (GSEA) was conducted to predict the function of prognosis-related MeDEGs.ResultsA total of nine up-regulated and 72 down-regulated MeDEGs were identified. GO and KEGG pathway analyses results indicated that multiple cancer-related terms were enriched. Kaplan–Meier survival analysis showed that the methylation status of four MeDEGs (CTF1, FZD8, PDK4, and ZNF334) was negatively associated with overall survival. Moreover, the methylation status of CDF1 and PDK4 was identified as an independent prognostic factor. According to GSEA, hypermethylation of prognosis-related MeDEGs was enriched in pathways that included “Spliceosome”, “Cell cycle”, “RNA degradation”, “RNA polymerase”, “DNA replication”, “Mismatch repair”, “Base excision repair”, “Nucleotide excision repair”, “Homologous recombination”, “Protein export”, and “Pyrimidine metabolism”.ConclusionsAberrant DNA methylation plays a critical role in malignant progression of HCC. Prognosis-related MeDEGs identified in this research may be potential biomarkers and targets in diagnosis and treatment.

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Comparison of the clinical outcomes and prognostic factors of dedifferentiated chondrosarcoma and chondroblastic osteosarcoma: a population-based analysis

10.21203/rs.3.rs-23594/v1 ◽

2020 ◽

Author(s):

Yiying Bian ◽

Ziliang Zeng ◽

Hao Yao ◽

Yutong Zou ◽

Jian Tu ◽

...

Keyword(s):

Prognostic Factors ◽

Lung Metastasis ◽

Univariate Analysis ◽

Tumor Stage ◽

Dedifferentiated Chondrosarcoma ◽

Ajcc Stage ◽

Surgical Methods ◽

High Tumor Stage ◽

Chondroblastic Osteosarcoma ◽

Patient Prognosis

Abstract Background Dedifferentiated chondrosarcoma (DDC) and chondroblastic osteosarcoma (COS) have some common morphological characteristics by pathology and involve the same surgical methods and chemotherapy regimen. We explored the prognostic differences and factors of patients with DDC and COS with similar pathological features to analyze the prognostic factors and effect of chemotherapy on the prognosis of each type. Methods From the SEER database, we included 228 patients with DDC and 631 patients with COS who underwent surgery from 1975 to 2016. Patient age was stratified with X-tile, and prognosis was analyzed by the Kaplan-Meier method and Cox proportional hazard regression. Results The 3- and 5-year overall survival (OS) rates for DDC were 33.3% and 26.5%, respectively, and the 3- and 5-year OS rates for COS were 71.5% and 63.8%, respectively. Compared with COS, DDC had an older onset age, a higher proportion of white patients, an increased likelihood of occurrence in soft tissue, a higher pathological grade, a larger tumor volume, more patients with M1-stage, a higher AJCC stage and a lower chemotherapy utilization rate. Univariate analysis showed that age, M1 stage and high tumor stage were negatively correlated with DDC patient prognosis, with a worse prognosis for patients with lung metastasis. In the multivariate analysis, higher tumor stage was an independent factor for reducing OS in DDC. Univariate analysis showed that COS patients were older and male; had tumors located in the pelvis; had high T-, M-, and AJCC-stage tumors; and had lung metastasis. Moreover, no chemotherapy was negatively correlated with patient prognosis. Furthermore, age, male sex and high tumor stage were independent factors for reducing OS in COS. Conclusion The OS of DDC patients is worse than that of COS patients. Chemotherapy cannot benefit patients with DDC. For COS patients, further exploration of the survival benefits of chemotherapy is needed.

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Risk of Death due to Hepatocellular Carcinoma among Drinkers and Ex-drinkers. Univariate Analysis of JACC Study Data

The Kurume Medical Journal ◽

10.2739/kurumemedj.51.59 ◽

2004 ◽

Vol 51 (1) ◽

pp. 59-70 ◽

Cited By ~ 11

Author(s):

ITSURO OGIMOTO ◽

AKIRA SHIBATA ◽

YOUICHI KUROZAWA ◽

TAKAYUKI NOSE ◽

TAKESUMI YOSHIMURA ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Univariate Analysis ◽

Study Data ◽

Risk Of Death

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Epigenomic profiling of DNA methylation for hepatocellular carcinoma diagnosis and prognosis prediction

Journal of Gastroenterology and Hepatology ◽

10.1111/jgh.14694 ◽

2019 ◽

Vol 34 (10) ◽

pp. 1869-1877 ◽

Cited By ~ 5

Author(s):

Cheng Zhang ◽

Shuang Ge ◽

Jun Wang ◽

Xiaotong Jing ◽

Hailing Li ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Dna Methylation ◽

Prognosis Prediction ◽

Diagnosis And Prognosis

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Development and Evaluation of Nomograms to Predict the Cancer-Specific Mortality and Overall Mortality of Patients with Hepatocellular Carcinoma

BioMed Research International ◽

10.1155/2021/1658403 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Xiaofeng Ni ◽

Ding Li ◽

Shengjie Dai ◽

Hao Pan ◽

Hongwei Sun ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Actual Condition ◽

Mortality Data ◽

Risk Of Death ◽

Ajcc Stage ◽

Liver Cancers ◽

Specific Mortality ◽

Long Term Follow Up ◽

Cancer Specific Mortality ◽

Overall Mortality

Hepatocellular carcinoma (HCC) is the most common type among primary liver cancers (PLC). With its poor prognosis and survival rate, it is necessary for HCC patients to have a long-term follow-up. We believe that there are currently no relevant reports or literature about nomograms for predicting the cancer-specific mortality of HCC patients. Therefore, the primary goal of this study was to develop and evaluate nomograms to predict cancer-specific mortality and overall mortality. Data of 45,158 cases of HCC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) program database between 2004 and 2013, which were then utilized to develop the nomograms. Finally, the performance of the nomograms was evaluated by the concordance index (C-index) and the area under the time-dependent receiver operating characteristic (ROC) curve (td-AUC). The categories selected to develop a nomogram for predicting cancer-specific mortality included marriage, insurance, radiotherapy, surgery, distant metastasis, lymphatic metastasis, tumor size, grade, sex, and the American Joint Committee on Cancer (AJCC) stage; while the marriage, radiotherapy, surgery, AJCC stage, grade, race, sex, and age were selected to develop a nomogram for predicting overall mortality. The C-indices for predicted 1-, 3-, and 5-year cancer-specific mortality were 0.792, 0.776, and 0.774; the AUC values for 1-, 3-, and 5-year cancer-specific mortality were 0.830, 0.830, and 0.830. The C-indices for predicted 1-, 3-, and 5-year overall mortality were 0.770, 0.755, and 0.752; AUC values for predicted 1-, 3-, and 5-year overall mortality were 0.820, 0.820, and 0.830. The results showed that the nomograms possessed good agreement compared with the observed outcomes. It could provide clinicians with a personalized predicted risk of death information to evaluate the potential changes of the disease-specific condition so that clinicians can adjust therapy options when combined with the actual condition of the patient, which is beneficial to patients.

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