Baseline apparent diffusion coefficients: Validation study of new predictor of survival in patients with unresectable hepatocellular carcinoma following chemoembolization

2021 ◽  
pp. 1-10
Author(s):  
Lichao Xu ◽  
Shiqin Wang ◽  
Shengping Wang ◽  
Ying Wang ◽  
Wentao Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Response To Treatment ◽  
Roc Curve Analysis ◽  
Adc Value ◽  
Apparent Diffusion Coefficients ◽  
Apparent Diffusion ◽  
Response Biomarker ◽  
The Difference

OBJECTIVES: To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS: Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start of the second course of chemoembolization. Receiver operating characteristic (ROC) curve analysis is performed to evaluate the diagnostic performance and determine optimal cut-off values. Cox regression and Kaplan–Meier survival analyses are used to explore the differences in overall survival (OS) between the responders and non-responders. RESULTS: The difference is statistically significant in the baseline ADC between the responders and non-responders (P <  0.001). ROC analyses indicate that the baseline ADC value is a good predictor of response to treatment with an area under the ROC curve (AUC) of 0.744 and the optimal cut-off value of 1.22×10–3 mm2/s. The Cox regression model shows that the baseline ADC is an independent predictor of OS, with a 57.2% reduction in risk. CONCLUSION: An optimal baseline ADC value is a functional imaging response biomarker that has higher discriminatory power to predict tumor response and prolonged survival following chemoembolization in HCC patients.

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 Autophagy-Related Gene Pairs Signature for the Prognosis of Hepatocellular Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Yiming Luo ◽  
Furong Liu ◽  
Shenqi Han ◽  
Yongqiang Qi ◽  
Xinsheng Hu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Liver Cancer ◽  
Roc Curve ◽  
Prognostic Model ◽  
Cox Regression ◽  
Curve Analysis ◽  
Related Gene ◽  
Roc Curve Analysis ◽  
Gene Pairs

Hepatocellular carcinoma (HCC) has been recognized as the third leading cause of cancer-related deaths worldwide. There is increasing evidence that the abnormal expression of autophagy-related genes plays an important role in the occurrence and development of HCC. Therefore, the study of autophagy-related genes can further elucidate the genetic drivers of cancer and provide valuable therapeutic targets for clinical treatment. In this study, we used 232 autophagy-related genes extracted from the Human Autophagy Database (HADb) and Molecular Signatures Database (MSigDB) to construct 1884 autophagy-related gene pairs. On this basis, we developed a prognostic model based on autophagy-related gene pairs using least absolute shrinkage and selection operator (LASSO) Cox regression to evaluate the prognosis of patients after liver cancer resection. We then used 845 liver cancer samples from three different databases to test the reliability of the risk signature through survival analysis, receiver operating characteristic (ROC) curve analysis, univariate and multivariate analysis. To further explore the underlying biological mechanisms, we conducted an enrichment analysis of autophagy-related genes. Finally, we combined the signature with independent prognostic factors to construct a nomogram. Based on the autophagy-related gene pair (ARGP) signature, we can divide patients into high- or low-risk groups. Survival analysis and ROC curve analysis verified the validity of the signature (AUC: 0.786—0.828). Multivariate Cox regression showed that the risk score can be used as an independent predictor of the clinical outcomes of liver cancer patients. Notably, this model has a more accurate predictive effect than most prognostic models for hepatocellular carcinoma. Moreover, our model is a powerful supplement to the HCC staging indicator, and a nomogram comprising both indicators can provide a better prognostic effect. Based on pairs of multiple autophagy-related genes, we proposed a prognostic model for predicting the overall survival rate of HCC patients after surgery, which is a promising prognostic indicator. This study confirms the importance of autophagy in the occurrence and development of HCC, and also provides potential biomarkers for targeted treatments.

scholarly journals High IKBIP expression as a biomarker for poor prognosis and correlated with immune infiltrates in hepatocellular carcinoma (HCC)

2021 ◽  
Author(s):  
Mingxin Lin ◽  
Jingping Liu ◽  
Xiaoli Shi ◽  
Jiajun Li ◽  
Huiming Ye
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Poor Prognosis ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Rank Test ◽  
Roc Curve Analysis ◽  
Ppi Networks ◽  
Diagnostic Potential

Abstract Background: I kappa B kinase interacting protein (IKBIP) is dysregulated and closely correlated with prognosis in tumor. However, the potential functions of IKBIP have not been utterly revealed in hepatocellular carcinoma (HCC). Thus, we explored the clinical values of IKBIP and its correlation with immune infiltrates in HCC.Methods: IKBIP expression in different tumor types was analyzed through the Tumor Immunity Evaluation Resource (TIMER) database. IKBIP expression between HCC and normal tissues were readily available for retrospective analyses from GEPIA, UALCAN and the Cancer Genome Atlas (TCGA) databases. The association between clinical features and IKBIP expression in HCC was analyzed by the Wilcoxon signed-rank test and logistic regression. Human Protein Atlas (HPA) was used to analyze the protein expression of IKBIP. A receiver operating characteristic (ROC) curve was performed to explore diagnostic potential of IKBIP. Kaplan-Meier (K-M) method and Cox regression were conducted to evaluate the influence of IKBIP on the prognosis of HCC patients. Protein-protein interaction (PPI) networks were established using STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The interrelation between IKBIP expression and immune infiltrates in HCC was analyzed through TIMER and tumor-immune system interaction database (TISIDB).Results: Our results revealed that IKBIP expression was abnormally upregulated in HCC, and ROC curve analysis confirmed the diagnostic power of IKBIP. High IKBIP expression was related to tumor sizes, pathologic stage and histologic grade. K-M plotter analysis showed that high IKBIP expression was correlated with poor prognosis of HCC patients. Moreover, multivariate Cox analysis further verified that high IKBIP expression was an independent risk factor in HCC patients. Correlation analysis found that IKBIP expression was associated with infiltrating immune cells.Conclusion: High IKBIP expression is associated with poor prognosis and immune infiltrates, which may serve as a prognostic biomarker and therapeutic target for HCC.

scholarly journals The Diagnostic Value of Eosinophil Count And Platelet-To-Lymphocyte Ratio In Eosinophilic Gastroenteritis

2021 ◽  
Author(s):  
Qiong Lin ◽  
Renmin Zhou ◽  
Hao Wujuan ◽  
Zhumeng Ni ◽  
Xiaozhong Li
Keyword(s):  
Blood Cell ◽  
Roc Curve ◽  
Diagnostic Value ◽  
Eosinophilic Gastroenteritis ◽  
Control Group ◽  
Platelet To Lymphocyte Ratio ◽  
Roc Curve Analysis ◽  
Record System ◽  
Lymphocyte Ratio ◽  
The Difference

Abstract Objective: To evaluate the diagnostic value of eosinophil (EO) count and platelet-to-lymphocyte ratio (PLR) in eosinophilic gastroenteritis (EGE). Methods: In total, 91 patients with EGE and 83 age–sex matched patients without EGE were selected as study subjects during January 2018 to December 2020. Data on blood cell count, and serum, C-reactive protein (CRP), and albumin levels were obtained from the Wuxi children's hospital electronic medical record system; the neutrophil-to-lymphocyte ratio (NLR), PLR, and CRP-to-albumin ratio (CAR) in the peripheral blood were recorded. Independent sample t-test, non-parametric test, or χ2 test was used according the data type to compare the difference between two groups, and receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value for EGE. Results: The EO counts and PLR were significantly higher in the EGE group than those in the control group, whereas differences in the white blood cell, lymphocyte, neutrophil, and platelet counts, and the CRP level, NLR, and CAR were not significant. After treatment(Corticosteroids, 1mg/kg.d, lasting for 2 weeks）, the EO counts and PLR in the EGE group decreased gradually and the difference was significant. The diagnostic value of EO counts and PLR was determined with an area under the ROC curve as 0.756 and 0.616, sensitivity was 75.00% and 34.29%, and specificity was 74.29% and 92.31%, respectively. Conclusions EO and PLR represent potential predictive markers for diagnosing EGE.

scholarly journals Clinical significance of fucosylated GP73 in the differential diagnosis of hepatocellular carcinoma

2018 ◽  
Vol 33 (4) ◽  
pp. 439-446 ◽  
Author(s):  
Yunsheng Zhao ◽  
Lina Zhang ◽  
Lijing Huo ◽  
Liu Pei ◽  
Qiuping Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differential Diagnosis ◽  
Roc Curve ◽  
Enzyme Linked Immunosorbent Assay ◽  
Diagnostic Efficiency ◽  
Roc Curve Analysis ◽  
Diagnostic Significance ◽  
Node Metastasis ◽  
Tumor Node Metastasis Stage ◽  
Normal Controls

Objective: To investigate the clinical value of fucosylated GP73 (Fuc-GP73) levels for differential diagnosis of hepatocellular carcinoma from other liver diseases. Methods: Serum specimens were collected from 50 patients with hepatocellular carcinoma, 60 patients with other digestive system diseases (ODSD), and 40 normal controls. Lectin affinity chromatography column combining with the enzyme-linked immunosorbent assay (ELISA) using the ELISA index was utilized to measure the level of Fuc-GP73. By receiver operating characteristic (ROC) curve analysis its sensitivity and specificity were used to evaluate the diagnostic significance of Fuc-GP73 in hepatocellular carcinoma. Results: The median serum Fuc-GP73 level of hepatocellular carcinoma (20.4 μg/L) was much higher than that of ODSD patients (1.8 μg/L) and the normal controls group (0.3 μg/L), significantly ( P <0.01). There was no significant correlation between serum Fuc-GP73 level and sex, age, and tumor size in the hepatocellular carcinoma group ( P > 0.05); however, it was related to tumor, node, metastasis stage and lymph node metastasis ( P <0.05). The area under the ROC curve (AUC) of Fuc-GP73 to detect hepatocellular carcinoma alone was 0.885; with the prespecified specificity of 95%, the sensitivity and the cutoff value were 82% and 3.1 μg/L. In addition, the combined test of Fuc-GP73 with other biomarkers can improve the clinical diagnostic efficiency; the AUC can reach to 0.983; and with the prespecified specificity of 95% its sensitivity increased to 94%. Conclusion: Fuc-GP73 can act as a superior glycobiomarker for the differential diagnosis of hepatocellular carcinoma; its combined detection with other biomarkers can improve diagnostic accuracy.

scholarly journals Serum Zonulin in HBV-Associated Chronic Hepatitis, Liver Cirrhosis, and Hepatocellular Carcinoma

2019 ◽  
Vol 2019 ◽  
pp. 1-6 ◽  
Author(s):  
Xin Wang ◽  
Ming-ming Li ◽  
Ye Niu ◽  
Xin Zhang ◽  
Ji-bin Yin ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cirrhosis ◽  
Chronic Hepatitis ◽  
Diagnostic Accuracy ◽  
Roc Curve ◽  
Healthy Subjects ◽  
Serum Levels ◽  
Curve Analysis ◽  
Advanced Stage ◽  
Roc Curve Analysis

Background. The gut microbiota is involved in the occurrence and development of chronic liver diseases. Zonulin is considered a marker of intestinal permeability. The purpose of this study was to assess zonulin levels in patients with chronic hepatitis B (CHB), HBV-associated liver cirrhosis (LC), and HBV-associated hepatocellular carcinoma (HCC). Materials and Methods. The study population consisted of 90 HBV-associated HCC patients, 90 HBV-associated LC patients, 90 CHB patients, and 90 healthy subjects. Serum levels of zonulin and AFP were determined. The diagnostic accuracy of each marker was evaluated using receiver operating characteristic (ROC) curve analysis (AUC). Results. Serum zonulin levels were significantly higher in patients with HCC than in patients with LC or CHB or healthy subjects (p<0.001). Moreover, the zonulin levels were increased in the advanced stage of LC and HCC. ROC curve analysis revealed that serum zonulin could be used to differentiate CHB from cirrhosis. In addition, the combination of zonulin and AFP exhibited a significantly larger AUC compared with zonulin or AFP alone. Conclusions. Serum zonulin levels were significantly increased both in LC and in HCC and correlated with the advanced stage of LC and HCC. Moreover, the combination of zonulin and AFP confers significant benefit to diagnostic accuracy in differentiating LC from HCC.

Diffusion of Radionuclides in Compacted Bentonite : Results from Combined Glass Dissolution and Migration Tests

1994 ◽  
Vol 353 ◽  
Author(s):  
Masaki Tsukamoto ◽  
T. Ohe ◽  
T. Fujita ◽  
R. HesbÖl ◽  
H-P. Hermansson
Keyword(s):  
Dry Density ◽  
Apparent Diffusion Coefficients ◽  
Glass Dissolution ◽  
Glass Corrosion ◽  
Gas Atmosphere ◽  
Apparent Diffusion ◽  
Calculation Results ◽  
The Difference ◽  
And Migration ◽  
Elemental Mass

AbstractDiffusion experiments of radionuclides in compacted sodium bentonite with a dry density of 1.0 g/cm3 were performed in nitrogen gas atmosphere at 90 °C for 208 d and 375 d. The corrosion experiments of crushed radioactive glass, JSS-A, carried out simultaneously to provide the source of the radionuclides for the diffusion experiments. The normalized elemental mass losses of cesium isotopes and 238Pu were lower than those of boron (ca. 10 g/m2) probably because of the difference of sorption and/or precipitation. The apparent diffusion coefficients of 238Pu, 234U and 125Sb were determined to be 2x 10-14 m2/s, 5x 10-12 m2/s and 2x 10-12 m2/s, respectively. The distribution coefficient of Pu estimated from the diffusion data was of the same order as that from batch sorption experiments. The glass corrosion and the plutonium diffusion were described by the geochemical codes PHREEQE, STRAG4 and GESPER. The calculation results well fitted the observed data.

scholarly journals A Novel Ferroptosis-Related Long Non-coding RNA Prognostic Risk Model for Gastric Cancer

2021 ◽  
Author(s):  
Shenglan Huang ◽  
Dan Li ◽  
Lingling Zhuang ◽  
Liying Sun ◽  
Jianbing Wu
Keyword(s):  
Gastric Cancer ◽  
Risk Score ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Clinical Stage ◽  
Curve Analysis ◽  
Clinicopathological Features ◽  
Roc Curve Analysis ◽  
Kaplan Meier

Abstract Background：Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is a novel and distinct type of non-apoptotic cell death that is closely associated with metabolism, redox biology, and tumor prognosis. Recently, ferroptosis-related long non-coding RNAs (lncRNAs) have received increasing attention in predicting cancer prognosis. Thus, we aimed to construct an ferroptosis-related lncRNAs signature for predicting the prognosis of patients with gastric cancer.Methods：We built an ferroptosis-related lncRNA risk signature by using Cox regression based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. Cox regression was performed to explore whether the signature could be used as an independent factor. A nomogram was built involving the risk score and clinicopathological features. Furthermore, we explored the biological functions and immune states in two groups.Results：Eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in gastric cancer. Kaplan–Meier curve analysis revealed that patients in the high-risk group had worse survival than those in the low-risk group. The survival outcome was also appropriate for subgroup analysis, including age, sex, grade, and clinical stage. Multivariate Cox regression analysis and receiver operating characteristic (ROC) curve analysis demonstrated that the risk score was an independent prognostic factor and superior to traditional clinicopathological features in predicting GC prognosis. Next, we established a nomogram according to clinical parameters (age, sex, grade, and clinical stage) and risk score. All the verified results, including ROC curve analysis, calibration curve, and decision curve analysis, demonstrated that the nomogram could accurately predict the survival of patients with gastric cancer. Gene set enrichment analysis revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation.Conclusion: We established a novel ferroptosis-related prognostic risk signature including eight lncRNAs and constructed a nomogram to predict the prognosis of gastric cancer patients, which may improve prognostic predictive accuracy and guide individualized treatment for patients with GC.

scholarly journals AGLR is a Novel Index for the Prognosis of Hepatocellular Carcinoma Patients: A Retrospective Study

2020 ◽  
Author(s):  
Yan Liao ◽  
Rongyu Wei ◽  
Renzhi Yao ◽  
Liling Qin ◽  
Jun Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Validation Cohort ◽  
Multivariate Analyses ◽  
The Novel ◽  
Gamma Glutamyl Transpeptidase ◽  
Roc Curve Analysis ◽  
Training Cohort ◽  
Scoring Model ◽  
Kaplan Meier

Abstract Background: Most hepatocellular carcinoma (HCC) patients’ liver function indexes are abnormal. We aimed to investigate the relationship between (alkaline phosphatase + gamma-glutamyl transpeptidase) / lymphocyte ratio (AGLR) and the progression as well as the prognosis of HCC. Methods: A total of 495 HCC patients undergoing radical hepatectomy were retrospectively analyzed. We randomly divided these patients into the training cohort (n = 248) and the validation cohort (n = 247). In the training cohort, receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of AGLR for predicting postoperative survival of HCC patients, and the predictive value of AGLR was evaluated by concordance index (C-index). Further analysis of clinical and biochemical data of patients and the correlation analysis between AGLR and other clinicopathological factors were finished. Univariate and multivariate analyses were performed to identify prognostic factors for HCC patients. Survival curves were analyzed using the Kaplan-Meier method.Results: According to the ROC curve analysis, the optimal predictive cut-off value of AGLR was 90. The C-index of AGLR was 0.637 in the training cohort and 0.654 in the validation cohort, respectively. Based on this value, the HCC patients were divided into the low-AGLR group (AGLR ≤ 90) and the high-AGLR group (AGLR > 90). Preoperative AGLR level was positively correlated with α-fetoprotein (AFP), tumor size, tumor-node-metastasis (TNM) stage, and microvascular invasion (MVI) (all p < 0.05). In the training and validation cohorts, patients with AGLR > 90 had significantly shorter OS than patients with AGLR ≤ 90 (p < 0.001). Univariate and multivariate analyses of the training cohort (HR, 1.79; 95% CI, 1.21-2.69; p < 0.001) and validation cohort (HR, 1.82; 95% CI, 1.35-2.57; p < 0.001) had identified AGLR as an independent prognostic factor. A new prognostic scoring model was established based on the independent predictors determined in multivariate analysis.Conclusions: The elevated preoperative AGLR level indicated poor prognosis for patients with HCC; the novel prognostic scoring model had favorable predictive capability for postoperative prognosis of HCC patients, which may bring convenience for clinical management.

Sign in / Sign up

Export Citation Format

Share Document