O124 A BLOOD-BASED 3-GENE SIGNATURE WITH SUFFICIENT SENSITIVITY AND SPECIFICITY TO DETECT EARLY STAGE HUMAN HEPATOCELLULAR CARCINOMA IN HIGH-RISK PATIENTS WITH CHRONIC HEPATITIS AND CIRRHOSIS

Abstract Objectives The American College of Radiology (ACR) contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS), which includes diagnostic criteria for hepatocellular carcinoma (HCC) and other hepatic malignancies (OM), is increasingly used in clinical practice. This study performed a meta-analysis to assess the diagnostic accuracy of CEUS LI-RADS for differentiating between HCC and OM in high-risk patients. Methods PubMed, Embase (Ovid), and Cochrane (CENTRAL) were searched for relevant studies. All studies that reported the percentage of HCC and OM in the LI-RADS categories were included. Random-effects models were used to calculate the pooled sensitivity and specificity, diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve. Results Eight studies involving 4215 focal liver lesions were included in the final analysis. The pooled sensitivity and specificity of the LR-5 criteria for HCC were 0.71 (95 % CI, 0.69–0.72) and 0.88 (0.85–0.91), respectively, the DOR was 18.36 (7.41–45.52), and the area under the SROC curve (AUC) was 0.8128. The pooled sensitivity and specificity of the LR-M criteria for OMs were 0.85 (0.81–0.88) and 0.86 (0.85–0.87), the DOR was 27.82 (11.83–65.40), respectively, and the SROC AUC was 0.9098. Conclusion The CEUS LI-RADS can effectively distinguish HCC from other hepatic malignancy in high-risk patients based on LR-5 criteria and LR-M criteria. However, further studies are needed for validation due to the limited number of included studies and the potential heterogeneity among the included studies.

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Hepatocarcinoma: from pathogenic mechanisms to target therapy

Oncology Reviews ◽

10.4081/oncol.2008.214 ◽

2011 ◽

Vol 2 (4) ◽

pp. 214

Author(s):

Luigi Manzione ◽

Antonio Maria Grimaldi ◽

Rosangela Romano ◽

Domenica Ferrara ◽

Angelo Dinota

Keyword(s):

Hepatocellular Carcinoma ◽

Chronic Hepatitis ◽

High Risk ◽

Molecular Mechanisms ◽

Therapeutic Option ◽

Target Therapy ◽

The United States ◽

Percutaneous Ablation ◽

High Risk Patients ◽

Risk Patients

Hepatocellular carcinoma (HCC) is among the most prevalent and lethal cancers worldwide. It is currently estimated that there are 14,000–18,000 new cases of hepatocellular carcinoma in the United States each year. It is often difficult to identify individuals at risk for HCC. The main associated diseases are chronic hepatitis B and chronic hepatitis C viral infections. While a significant number of potential mutations have been generated including p53 and Insulin-like Growth Factor, our understanding of the molecular mechanisms driving the genesis and progression of HCC remain limited. HCC screening is recommended in high-risk patients. High-risk patients include virtually all patients with cirrhosis and some HBV-infected patients irrespective of cirrhosis (>40 years in men and >50 years in women). A diagnostic approach to HCC has been developed incorporating serology, cytohistology, and radiological characteristics. A precise staging of the disease may help decide on prognosis as well as choice of therapy with the greatest survival potential. Liver transplantation, in theory, is the optimal therapeutic option for HCC; it simultaneously removes the tumor and underlying cirrhosis thus minimizing the risk of HCC recurrence. When it is impossible for this to be performed, percutaneous ablation, chemoembolization, chemotherapy and the newer molecular therapies can be used. Sorafenib is the only drug registered today for the treatment of advanced HCC.

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A Novel Epigenetic Machine Learning Model to Define Risk of Progression for Hepatocellular Carcinoma Patients

International Journal of Molecular Sciences ◽

10.3390/ijms22031075 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1075

Author(s):

Luca Bedon ◽

Michele Dal Bo ◽

Monica Mossenta ◽

Davide Busato ◽

Giuseppe Toffoli ◽

...

Keyword(s):

Machine Learning ◽

Hepatocellular Carcinoma ◽

High Risk ◽

Progression Free Survival ◽

Low Risk ◽

Functional Enrichment ◽

Free Survival ◽

High Risk Patients ◽

Risk Of Progression ◽

Risk Patients

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.

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How to restrict liver biopsy to high-risk patients in early-stage Hodgkin's disease

Annals of Hematology ◽

10.1007/s002770050013 ◽

2000 ◽

Vol 79 (2) ◽

pp. 73-78 ◽

Cited By ~ 9

Author(s):

D. Lieberz ◽

M. Sextro ◽

U. Paulus ◽

J. Franklin ◽

H. Tesch ◽

...

Keyword(s):

High Risk ◽

Liver Biopsy ◽

Hodgkin's Disease ◽

Early Stage ◽

Hodgkin’S Disease ◽

High Risk Patients ◽

Risk Patients

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Outcomes After Surgery in High-Risk Patients With Early Stage Lung Cancer

The Annals of Thoracic Surgery ◽

10.1016/j.athoracsur.2015.08.088 ◽

2016 ◽

Vol 101 (3) ◽

pp. 1043-1051 ◽

Cited By ~ 14

Author(s):

Manu S. Sancheti ◽

John N. Melvan ◽

Rachel L. Medbery ◽

Felix G. Fernandez ◽

Theresa W. Gillespie ◽

...

Keyword(s):

Lung Cancer ◽

High Risk ◽

Early Stage ◽

Early Stage Lung Cancer ◽

High Risk Patients ◽

Risk Patients ◽

Stage Lung Cancer

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Prevention of hepatocellular carcinoma and surveillance of high risk patients

Hepatology Forum ◽

10.14744/hf.2021.2021.0033 ◽

2021 ◽

Author(s):

Ali Canbay

Keyword(s):

Hepatocellular Carcinoma ◽

High Risk ◽

High Risk Patients ◽

Risk Patients

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Contrast-Enhanced Ultrasound Liver Imaging Reporting and Data System in Diagnosing Hepatocellular Carcinoma: Diagnostic Performance and Interobserver Agreement

Ultraschall in der Medizin - European Journal of Ultrasound ◽

10.1055/a-1168-6321 ◽

2020 ◽

Author(s):

Hang Zhou ◽

Chao Zhang ◽

Linyao Du ◽

Jiapeng Jiang ◽

Qing Zhao ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

High Risk ◽

Diagnostic Performance ◽

Data System ◽

Liver Imaging ◽

Contrast Enhanced Ultrasound ◽

High Risk Patients ◽

Contrast Enhanced ◽

Sensitivity Range ◽

Risk Patients

Abstract Objectives To determine the diagnostic performance and inter-reader agreement of the contrast-enhanced ultrasound liver imaging reporting and data system (CEUS-LI-RADS) for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. Methods In this prospective study, CEUS-LI-RADS categories (LR-5 for predicting HCC) were assigned by six blinded readers and compared to the definitive HCC diagnosis in patients with liver cirrhosis per the 2017 China Liver Cancer Guidelines (CLCG). CEUS features were recorded in 96 patients with 96 histology-proven lesions. The diagnostic performance of LR-5 was described by the sensitivity, specificity and accuracy. Multi-reader agreement was assessed by using intraclass correlation coefficients (ICC). Results In cirrhotic patients, the specificity of LR-5 (range: 92.7–100.0 %) was statistically higher than that of CLCG for each reader (range: 28.6–64.3 %). However, the sensitivity (range: 38.6–63.6 %) and accuracy (range: 53.4–70.7 %) were statistically lower in CEUS-LIRADS than in CLCG (sensitivity range: 88.6–100.0 %; accuracy range: 77.6–86.2 %). Only fair to moderate inter-reader agreement was achieved for the CEUS-LI-RADS category (ICC = 0.595) and washout appearance (ICC range: 0.338 to 0.555). Neither nodule-in-nodule nor mosaic architecture was observed more often in HCC (all P > 0.05), with poor inter-reader consistency for both (both ICC < 0.20). Conclusion CEUS-LI-RADS category 5 has a high specificity but a low accuracy for identifying HCC in high-risk patients. Inter-reader agreement is not satisfactory concerning CEUS-LIRADS category and washout appearance. Moreover, the clinical value of ancillary features favoring HCC is quite limited.

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