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Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma

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A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 10069

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Special Issue Editors

Prof. Ying-Hsiu Su

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Guest Editor

Department of Translational Medical Science, The Baruch S. Blumberg Institute, Doylestown, PA, USA
Interests: hepatocellular carcinoma; liver cance; cancer biomarker discovery and development; cancer screening and early detection; precision medicine; molecular diagnosis; tumor heterogeneity; tumor evolution; liquid biopsy; circulating tumor DNA

Dr. Amy K. Kim

E-Mail Website
Guest Editor

Department of Medicine Division of Gastroenterology/Hepatology, Johns Hopkins School of Medicine, Baltimore, MD, USA
Interests: liver cancer; hepatocellular carcinoma; liquid biopsy; cancer biomarkers; liver transplantation

Special Issue Information

Dear Colleagues,

Hepatocellular carcinoma (HCC) is the world’s second leading cause of cancer-related deaths, with more than 50% of patients dying within five years of diagnosis. A lack of effective early detection tools, the limited treatment options for advanced stages, and the high frequency of HCC recurrence contribute to this poor prognosis. Despite the implementation of HCC screening programs for well-known at-risk populations, the majority of HCCs are diagnosed at late stages, indicating the need for more sensitive early biomarkers and patient-friendly (patient-accessible?) diagnostic tests for HCC screening. Like other cancers, HCC is a disease of the genome. The identification of the genomic alterations that drive hepato-carcinogenesis should reveal the most effective biomarkers for HCC screening, diagnosis, and disease management. HCC is also a multifactorial disease. Technological advances have enhanced our understanding of HCC carcinogenesis, from a histopathological definition to molecular characterization of the genome and epigenome. Identifying the genomic alterations that drive hepato-carcinogenesis should reveal the most effective biomarkers for HCC screening, diagnosis, and disease management. This fundamental genetic understanding of HCC reveals its high heterogeneity and evolutionary dynamics (tumor evolution) as a function of time, particularly in response to treatment. This highlights the importance of tumor genetic analysis for the precise diagnosis of cancer, as well as the potential of patient selection in targeted drug development. Due to its high heterogeneity, a combination of biomarkers in different categories such as protein and nucleic acids may be needed to increase performance.

This Special Issue will cover recent advances in biomarkers discovery and development for HCC screening, diagnosis, stratification, management, and drug development. The scope of the issue includes both technology and biomarkers.

Prof. Ying-Hsiu Su
Dr. Amy K. Kim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

hepatocellular carcinoma
liver cancer
cancer biomarker
biomarker discovery and development
early detection
cancer screening
precision medicine
molecular diagnosis
tumor heterogeneity
tumor evolution
liquid biopsy
circulating tumor DNA

Published Papers (5 papers)

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Research

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18 pages, 7514 KiB

Open AccessArticle

by Jiahao Li, Lansi Chen, Jingjing Pang, Chunxiu Yang, Wen Xie, Guoyan Shen, Hongshan Chen, Xiaoyi Li, Shu-Yuan Xiao and Yueying Li

Diagnostics 2023, 13(5), 906; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics13050906 - 27 Feb 2023

Cited by 1 | Viewed by 1342

Abstract

Hepatocellular carcinoma (HCC) is a highly aggressive malignant tumor. It has been found that autophagy plays a role both as a tumor promoter and inhibitor in HCC carcinogenesis. However, the mechanism behind is still unveiled. This study aims to explore the functions and mechanism of the key autophagy-related proteins, to shed light on novel clinical diagnoses and treatment targets of HCC. Bioinformation analyses were performed by using data from public databases including TCGA, ICGC, and UCSC Xena. The upregulated autophagy-related gene WDR45B was identified and validated in human liver cell line LO2, human HCC cell line HepG2 and Huh-7. Immunohistochemical assay (IHC) was also performed on formalin-fixed paraffin-embedded (FFPE) tissues of 56 HCC patients from our pathology archives. By using qRT-PCR and Western blots we found that high expression of WDR45B influenced the Akt/mTOR signaling pathway. Autophagy marker LC3- II/LC3-I was downregulated, and p62/SQSTM1 was upregulated after knockdown of WDR45B. The effects of WDR45B knockdown on autophagy and Akt/mTOR signaling pathways can be reversed by the autophagy inducer rapamycin. Moreover, proliferation and migration of HCC can be inhibited after the knockdown of WDR45B through the CCK8 assay, wound-healing assay and Transwell cell migration and invasion assay. Therefore, WDR45B may become a novel biomarker for HCC prognosis assessment and potential target for molecular therapy. Full article

(This article belongs to the Special Issue Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma)

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14 pages, 1607 KiB

Open AccessArticle

The Additive Value of Radiomics Features Extracted from Baseline MR Images to the Barcelona Clinic Liver Cancer (BCLC) Staging System in Predicting Transplant-Free Survival in Patients with Hepatocellular Carcinoma: A Single-Center Retrospective Analysis

by Mohammad Mirza-Aghazadeh-Attari, Bharath Ambale Venkatesh, Mounes Aliyari Ghasabeh, Alireza Mohseni, Seyedeh Panid Madani, Ali Borhani, Haneyeh Shahbazian, Golnoosh Ansari and Ihab R. Kamel

Diagnostics 2023, 13(3), 552; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics13030552 - 02 Feb 2023

Cited by 2 | Viewed by 1891

Abstract

Background: To study the additive value of radiomics features to the BCLC staging system in clustering HCC patients. Methods: A total of 266 patients with HCC were included in this retrospective study. All patients had undergone baseline MR imaging, and 95 radiomics features were extracted from 3D segmentations representative of lesions on the venous phase and apparent diffusion coefficient maps. A random forest algorithm was utilized to extract the most relevant features to transplant-free survival. The selected features were used alongside BCLC staging to construct Kaplan–Meier curves. Results: Out of 95 extracted features, the three most relevant features were incorporated into random forest classifiers. The Integrated Brier score of the prediction error curve was 0.135, 0.072, and 0.048 for the BCLC, radiomics, and combined models, respectively. The mean area under the receiver operating curve (ROC curve) over time for the three models was 81.1%, 77.3%, and 56.2% for the combined radiomics and BCLC models, respectively. Conclusions: Radiomics features outperformed the BCLC staging system in determining prognosis in HCC patients. The addition of a radiomics classifier increased the classification capability of the BCLC model. Texture analysis features could be considered as possible biomarkers in predicting transplant-free survival in HCC patients. Full article

(This article belongs to the Special Issue Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma)

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13 pages, 2223 KiB

Open AccessArticle

Role of MRI-Derived Radiomics Features in Determining Degree of Tumor Differentiation of Hepatocellular Carcinoma

by Sanaz Ameli, Bharath Ambale Venkatesh, Mohammadreza Shaghaghi, Maryam Ghadimi, Bita Hazhirkarzar, Roya Rezvani Habibabadi, Mounes Aliyari Ghasabeh, Pegah Khoshpouri, Ankur Pandey, Pallavi Pandey, Li Pan, Robert Grimm and Ihab R. Kamel

Diagnostics 2022, 12(10), 2386; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics12102386 - 30 Sep 2022

Cited by 8 | Viewed by 1552

Abstract

Background: To investigate radiomics ability in predicting hepatocellular carcinoma histological degree of differentiation by using volumetric MR imaging parameters. Methods: Volumetric venous enhancement and apparent diffusion coefficient were calculated on baseline MRI of 171 lesions. Ninety-five radiomics features were extracted, then random forest classification identified the performance of the texture features in classifying tumor degree of differentiation based on their histopathological features. The Gini index was used for split criterion, and the random forest was optimized to have a minimum of nine participants per leaf node. Predictor importance was estimated based on the minimal depth of the maximal subtree. Results: Out of 95 radiomics features, four top performers were apparent diffusion coefficient (ADC) features. The mean ADC and venous enhancement map alone had an overall error rate of 39.8%. The error decreased to 32.8% with the addition of the radiomics features in the multi-class model. The area under the receiver-operator curve (AUC) improved from 75.2% to 83.2% with the addition of the radiomics features for distinguishing well- from moderately/poorly differentiated HCCs in the multi-class model. Conclusions: The addition of radiomics-based texture analysis improved classification over that of ADC or venous enhancement values alone. Radiomics help us move closer to non-invasive histologic tumor grading of HCC. Full article

(This article belongs to the Special Issue Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma)

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11 pages, 1043 KiB

Open AccessArticle

Older Age and High α-Fetoprotein Predict Higher Risk of Hepatocellular Carcinoma in Chronic Hepatitis-B-Related Cirrhotic Patients Receiving Long-Term Nucleos(t)ide Analogue Therapy

by Yuh-Ying Liu, Chih-Lang Lin, Cheng-Hao Weng, Pei-Hung Chang, Cheng-Hung Chien, Kuang-Chen Huang, Man-Chin Hua and Ching-Chih Hu

Diagnostics 2022, 12(9), 2085; https://doi.org/10.3390/diagnostics12092085 - 28 Aug 2022

Cited by 2 | Viewed by 1434

Abstract

Background: Nucleos(t)ide analogues (NUCs) were proved to reduce hepatocellular carcinoma (HCC) development in chronic hepatitis B (CHB) patients, but data were limited on their efficacy in cirrhotic CHB patients. Methods: A total of 447 cirrhotic CHB patients treated with tenofovir/entecavir were retrospectively analyzed and divided into HCC (n = 48) and non-HCC (n = 399) groups. The median follow-up period was 62.1 months. Results: A total of 48 patients (10.7%) developed HCC during surveillance. The annual incidence rate of HCC was 2.04 per 100 person-years. The cumulative incidence of HCC was 0.9%, 9.8%, and 22.1% at 1, 5, and 10 years, respectively. Significant predictors for HCC identified using a multiple Cox regression analysis were age ≥50 years (hazard ratio (HR): 2.34) and α-fetoprotein (AFP) ≥8 ng/mL (HR: 2.05). The incidence rate of HCC was 8.67-fold higher in patients with age ≥50 years and AFP ≥8 ng/mL (3.14 per 100 person-years) than those with age <50 years and AFP <8 ng/mL (0.36 per 100 person-years). Conclusions: Cirrhotic CHB patients with age <50 years and AFP <8 ng/mL had the lowest annual incidence of HCC. However, those with age ≥50 years or/and AFP ≥8 ng/mL had a significantly higher risk for HCC development and warrant a careful surveillance schedule. Full article

(This article belongs to the Special Issue Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma)

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Review

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17 pages, 881 KiB

Open AccessReview

Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings

by Annabelle Pan, Thai N. Truong, Ying-Hsiu Su and Doan Y Dao

Diagnostics 2023, 13(4), 676; https://0-doi-org.brum.beds.ac.uk/10.3390/diagnostics13040676 - 11 Feb 2023

Cited by 5 | Viewed by 2955

Abstract

Hepatocellular carcinoma (HCC) is among the world’s third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant. Full article

(This article belongs to the Special Issue Biomarkers in Diagnosis and Management of Hepatocellular Carcinoma)

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