Diagnosis Of Hepatocellular Carcinoma Research Articles

Role of Α-L-Fucosidase as a Diagnostic Marker versus Α-Fetoprotein in HCC Post Viral Cirrhotic Patients

Abstract Background Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third cause of cancer-related mortality world- wide. The incidence of HCC is on the increase, and it is a major threat to our modern life. Epidemiological studies have indicated that HCC are related to chronic hepatitis B virus (HBV) and chronic hepatitis C virus (HCV) infection. Aim of the Work To evaluate the role of AFU as a diagnostic marker versus AFP in HCC post viral cirrhotic Egyptian patients. Patients and Methods This study had been carried out on 90 subjects, age range 21-75 year selected from Internal medicine and Hepatology outpatient clinics and inpatient wards at Ain shams university hospitals from January 2022 to June 2022. Results We found that serum levels of AFU were highest in patients of group A with HCC (129.867 ± 32.997 μl U/ml) compared to those with liver cirrhosis (33.433± 14.818 μl U/ml) with P value < 0.001 and the control groups (3.177 ± 1.199 μl U/ml) with P value < 0.001. Similarly alpha fetoprotein its serum levels were much higher in the HCC group (4688.223±11490.009 ng/ml) compared to the cirrhotic patients (4.407±3.107 ng/ml) with P value 0.02 Also, compared to healthy individuals (2.623±1.566 ng/ml) with p value 1.00. We found that there is No significant statistical correlation between serum AFP and AFU in our studied HCC and cirrhotic patients (R 0.332, P 0.073 for HCC and R 0.222, P 0.238 for cirrhotic). Regarding the negative correlation between serum AFU level and AFP level in order to predict the diagnostic value, sensitivity and specificity of both of them in term of tumor size, our study show that for AFU when the best cut off value was >52μl U/ml the sensitivity was 100% and specificity was 90% while for AFP when the best cut off value was > 10.5 ng/ml the sensitivity was 96.67% and specificity 96.67%. AFU is a promising serum tumor marker for HCC diagnosis and can be combined with AFP. Conclusion We concluded from this study that: Serum AFP was highly significant increase in HCC patients compared to cirrhotic and healthy controls, this is in agreement with many several reports that consider AFP in high serum levels as diagnostic for HCC combined with triphasic CT abdomen or dynamic MRI. Serum AFU levels were significantly higher in patients with HCC and mildly elevated in patients with liver cirrhosis compared to the control group. So it can be used as a tumor marker for HCC diagnosis. No correlation between AFU and laboratory data and child score. AFU was not influenced by clinical condition of the liver itself but with HCC. Around 40% of HCC patients have normal or low AFP level so AFU may be useful as a diagnostic marker in those patients. Serum AFP is the standard tumor marker used in clinical practice for diagnosis and surveillance of HCC in cirrhotic patients in spite of normal and low AFP HCC patients that may reach 40%. Sensitivity and specificity of AFU was nearly similar to sensitivity and specificity of AFP. Combined use of AFU with AFP or possibly other markers will improve the diagnostic field and can help in early detection of HCC in surveillance programms.

Monocyte distribution width as a promising biomarker for differential diagnosis of chronic hepatitis, cirrhosis, and hepatocellular carcinoma.

We aimed to investigate the association and diagnostic value of monocyte distribution width (MDW) for chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). MDW levels were measured in 483 individuals (103 CHB, 77 LC, 153 HCC, and 150 controls). MDW was detected using UniCel Dx900 for specific cell volume parameters and the distribution of cell volumes. Our findings revealed a dynamic upward change in MDW levels across different stages of chronic liver disease, from CHB to LC and HCC. In CHB, MDW levels were highest among HBeAg-positive CHB patients and exhibited a negative correlation with HBV markers while positively correlating with ALT levels. In LC, MDW showed a positive association with the pathological progression of LC, demonstrating consistency with CP scores. MDW proved to be equally effective as traditional detection for diagnosing LC. In HCC, MDW was positively correlated with HCC occurrence and development, with higher levels observed in the high MDW group, which also exhibited elevated AFP levels, MELD scores, and 90-day mortality rates. MDW surpassed predictive models in its effectiveness for diagnosing HCC, as well as CHB and LC, with respective areas under the curve of 0.882, 0.978, and 0.973. Furthermore, MDW emerged as an independent predictor of HCC. MDW holds significant diagnostic efficacy in identifying CHB, LC, and HCC. These findings suggest that MDW could serve as a promising biomarker for predicting the severity of liver diseases and aid in rational clinical treatment strategies.

Evaluation the Role of Lipocalin 2 as a New Non-Invasive Diagnostic Marker for Hepatocellular Carcinoma in Egyptian Cirrhotic Patients

Abstract Background Hepatocellular carcinoma (HCC) represents the sixth most common cancer worldwide. In Egypt, it represents the fourth common cancer. Significant risk factors for hepatocellular carcinoma include viral hepatitis (hepatitis B and hepatitis C), alcoholic liver disease, and non-alcoholic liver steatohepatitis/non-alcoholic fatty liver disease. HCC occurs in 80%-90% of patients with cirrhosis. The annual incidence of HCC in patients with cirrhosis is 2-4%. Aim of the Work The aim of this study is to evaluate the role of lipocalin 2 (LCN 2) as a diagnostic marker in HCC Egyptian patients. Patients and Methods A case-control study in Ain- Shams University Hospital for 6 months period and the study will be conducted on 96 Egyptian patients (32 HCC patients, 32 liver cirrhosis without HCC, 32 normal control persons). Res1ults We found that LCN 2 level ranged from 150 to 380 in HCC group with mean±SD = 292.750±50.940, from 88 to 280 in cirrhotic patients with mean± SD = 129.313±36.605, from 40 to 62 in control group with mean± SD = 53.250± 4.958, being statistically significant higher in HCC group more than both cirrhotic group and control group and in cirrhotic patients more than control group (p-value = <0.001). The results showing sensitivity of 96.87% and specificity 96.87% of LCN 2 as a marker for HCC with accuracy of 98.4%,with cut off > 160. The presence of (LCN-2) in blood and urine, in combination with α-Fetoprotein (AFP), is a biomarker of early stages of HCC. LCN 2 is a promising serum tumor marker for HCC diagnosis. Conclusion We concluded from this study that: Serum LCN 2 level was significantly higher in patients with HCC and mildly elevated in patients with liver cirrhosis compared to the control group. So it can be used as a tumor marker for HCC diagnosis. Use of LCN 2 with AFP or possibly other markers will improve the diagnostic field and can help in early detection of HCC in surveillance programms. We need further studies on large number of HCC patients of different etiologies and on metastaic liver tumors to clarify the accuracy and potential diagnostic role of LCN 2 in the future.

The Value of CEUS LI-RADS combined with AFP in early diagnosis of hepatocellular carcinoma in low- and high-risk patients.

We found that the occurrence of hepatocellular carcinoma (HCC) has increased significantly in non-cirrhotic individuals, with HCC being frequently overlooked or misdiagnosed. Contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) is known to have a high diagnostic quality in high-risk HCC patients. Therefore, we aimed to compare the detection accuracy of CEUS LI-RADS for HCC between low- and high-risk individuals, to confirm its value in low-risk patients at increased risk of HCC, but not yet included in the high-risk groups of LI-RADS. In addition, since CEUS LR-4 and LR-M categories contain a relatively high proportion of HCC, and serum alpha-fetoprotein (AFP) is the most commonly used biomarker for HCC, and the clinically valid, we attempted to further improve the early diagnostic capability of CEUS LI-RADS for HCC in the low-risk and high-risk patients by combining CEUS LR-4 and LR-M categories with AFP. We defined high-risk groups (HR)-included in the high-risk patients of LI-RADS, low-risk groups (LR)-not included in the high-risk patients of LI-RADS and enrolled 189 HCC patients with LR and HR settings in a retrospective study. All lesions were confirmed histopathologically. The CEUS LI-RADS accuracy for detecting HCC in these two patients was compared. In addition, the diagnostic algorithm in our study was proposed (for CEUS LR-4 and LR-M patients with AFP>20 ng/ml). we analyzed the ability of CEUS LI-RADS as a valid method of establishing the early diagnosis of HCC in LR and HR patients by combining LR-4 and LR-M categories with AFP. Through comparative analysis, the specificity of the CEUS LR-5 category for HCC in the HR group was 78.4%, whereas in the LR group, it was 94.2%. Meanwhile, the sensitivity (63.2% vs. 63.0%) and positive predictive value (PPV) (75.0% vs. 88.7%) did not differ between the LR and HR groups ( P = 0.990, P = 0.299). It is noteworthy that there were the high proportion of HCC in CEUS LR-4 and LR-M categories in our cases and when we combined CEUS LR-4 and LR-M categories with AFP significantly improved the sensitivity by 21.0% (84.2%) in the LR group, and by 16.0% (79.0%) in the HR group, with statistically difference in sensitivity after combination in the HR group ( P = 0.014). The CEUS LR-5 category has real meaningful utility in the diagnosis of HCC in both LR and HR patients. The early detection power of the CEUS LI-RADS category for HCC patients was further increased when the CEUS LR-4 and LR-M categories were combined with elevated AFP.

Tenofovir Is Associated With a Better Prognosis Than Entecavir for Hepatitis B Virus–Related Hepatocellular Carcinoma

Whether tenofovir or entecavir has different effects on the prevention of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) in secondary and tertiary preventive settings is still a matter of debate. This study aimed to compare the long-term prognosis of HCC between tenofovir and entecavir in patients with chronic hepatitis B. Chronic hepatitis B patients diagnosed with HCC between November 2008 and December 2018 and treated with either entecavir or tenofovir at a tertiary center in Korea were included. The effect of tenofovir compared with entecavir on the prognosis of HBV-related HCC was assessed using multivariable-adjusted Cox and propensity score (PS)-matched analyses. Various predefined subgroup analyses were conducted. During a median follow-up period of 3.0 years, the mortality rate for entecavir-treated patients (n= 3469) was 41.2%, while tenofovir-treated patients (n= 3056) had a mortality rate of 34.6%. Overall survival (OS) was better in the tenofovir group (adjusted hazard ratio [aHR], 0.79; P < .001), which were consistently observed in the PS-matched analysis. The magnitude of the risk difference in OS was more prominent 2 years after the diagnosis of HCC (aHR, 0.50; P < .001) than 2 years before (aHR, 0.88; P= .005), and it was more pronounced in patients with earlier HCC stages. In all subgroups, except for those with shorter life expectancy, such as those with compromised liver function, tenofovir was associated with better OS compared with entecavir. Among patients with HBV-related HCC, those treated with tenofovir had a better prognosis than those treated with entecavir, particularly among those with prolonged survival.

Applications and challenges of pathomics technique in the management of hepatocellular carcinoma

The incidence and mortality rate of hepatocellular carcinoma rank among the top of all cancer types,seriously threatening the life and health of human beings. In recent years,the rapid development of artificial intelligence and the deepening of the concept of precision medicine have led to a boom in interdisciplinary research. Pathomics,as an emerging omics technology driven by artificial intelligence,can mine massive information from high-resolution whole slide images,and shows broad application prospects in the diagnosis,treatment and prognosis assessment of hepatocellular carcinoma. However, pathomics research in hepatocellular carcinoma is still in its infancy, and its research patterns and clinical applications still face several controversies and challenges, including data security, ethics, and "black box" issues. Future research should focus on conducting prospective studies, integrating multimodal data, improving computational technologies, and establishing professional standards to promote the high-quality development of pathomics technology in both clinical and basic research of hepatocellular carcinoma.

Key points for imaging diagnosis and response assessment for hepatocellular carcinoma in Latin America

Key points for imaging diagnosis and response assessment for hepatocellular carcinoma in Latin America

Research Progress in Predicting Hepatocellular Carcinoma with Portal Vein Tumour Thrombus in the Era of Artificial Intelligence.

Hepatocellular Carcinoma (HCC) is a condition associated with significant morbidity and mortality. The presence of Portal Vein Tumour Thrombus (PVTT) typically signifies advanced disease stages and poor prognosis. Artificial intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), has emerged as a promising tool for extracting quantitative data from medical images. AI is increasingly integrated into the imaging omics workflow and has become integral to various medical disciplines. This paper provides a comprehensive review of the mechanisms underlying the formation and progression of PVTT, as well as its impact on clinical management and prognosis. Additionally, it outlines the advancements in AI for predicting the diagnosis of HCC and the development of PVTT. The limitations of existing studies are critically evaluated, and potential future research directions in the realm of imaging for the diagnostic prediction of HCC and PVTT are discussed, with the ultimate goal of enhancing survival outcomes for PVTT patients.

Engineering Tb(III)-functionalized HOF fluorescence sensing system for intelligent visual detection of two biomarkers of hepatocellular carcinoma

Abnormal levels of bilirubin and human serum albumin are precursors to hepatocellular carcinoma and many fatal diseases. Establishing a portable, highly sensitive and intuitive dual biomarker detection method for bilirubin and human serum albumin is important to protect human health. Combined with the excellent photoluminescence properties of lanthanide functionalized hydrogen bond organic framework, a novel ratiometric fluorescence intelligent sensing system was engineered with the outstanding features of large Stokes shifts, high luminous stability and the self-calibration effect of dual emission centers in this paper. With the advantage of high sensitivity, strong stability and strong anti-interference, the simultaneous detection of dual biomarkers was realized successfully. The developed fluorescence sensing system had a wide detection range of bilirubin and human serum albumin (13.5 nM ∼ 30.0 μM and 448 nM ∼ 15.0 μM), low detection limits (7.20 nM and 15.6 nM). Furthermore, the developed sensing system realized the smartphone-assisted fluorescence visual detection of bilirubin and human serum albumin in serum and urine successfully with the detection limit of 85 nM and 163 nM, providing a promising detection strategy for the early diagnosis of hepatocellular carcinoma.

Development and Validation of a Noninvasive Model for the Detection of High-Risk Varices in Patients with Unresectable HCC

Background and AimsNon-invasive variceal risk stratification systems have not been validated in patients with hepatocellular carcinoma (HCC), which presents logistical barriers for patients in the setting of systemic HCC therapy. We aimed to develop and validate a non-invasive algorithm for the prediction of varices in patients with unresectable HCC. MethodsWe performed a retrospective cohort study in 21 centers in the US including adult patients with unresectable HCC and Child Pugh A5-B7 cirrhosis diagnosed between 2007 and2019. We included patients who completed an esophagogastroduodonoscopy (EGD) within 12 months of index imaging but prior to HCC treatment. We divided the cohort into a 70:30 training set and validation set, with the goal of maximizing negative predictive value (NPV) to avoid EGD in low-risk patients. ResultsWe included 707 patients (median age 64.6 years, 80.6% male and 74.0% White). Median time from HCC diagnosis to EGD was 47 (IQR: 114) days, with 25.0% of patients having high-risk varices. A model using clinical variables alone achieved a NPV of 86.3% in the validation cohort, while a model integrating clinical and imaging variables had an NPV 97.4% in validation. The clinical and imaging model would avoid EGDs in over half of low-risk patients while misclassifying 7.7% of high-risk patients. ConclusionA model incorporating clinical and imaging data can accurately predict the absence of high-risk varices in patients with HCC and avoid EGD in many low-risk patients prior to the initiation of systemic therapy, thus expediting their care and avoiding treatment delays.

NEW POSSIBILITIES OF MODERN RADIOLOGY DIAGNOSIS OF HEPATOCELLULAR CARCINOMA: A LITERATURE REVIEW

Relevance: Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor (80-90%), ranks 6th among malignant neoplasms and is the 3rd leading cause of cancer mortality worldwide. Despite advances in locoregional therapy, targeted therapy, and immunotherapy, the median survival for advanced HCC does not exceed 2 years, and the 5-year survival rate is 18%. Diagnosis of the tumor at an early stage allows for resection and liver transplantation, which can increase the 5-year survival rate by 1.5-2 times. The options for biopsy are limited by sensitivity and potential complications for the patient. In most cases, HCC can be detected by non-invasive radiology. The study aimed to evaluate the effectiveness of modern methods of radiological diagnosis of HCC. Methods: This literature review included published articles and studies on the capacity of modern methods of radiological diagnosis of hepatocellular carcinoma. Data were found in PubMed, BMC Medicine, and Google Scientific using the keywords ‘hepatocellular carcinoma,’ ‘ultrasound examination,’ ‘computed tomography,’ ‘magnetic resonance imaging,’ and ‘radiomics.’ A total of 123 publications were found; 49 sources were included in this review. Results: The review article addresses current issues of HCC epidemiology, genetics, etiology, and radiology diagnosis. Updated data on the efficacy of CEUS and MFI, LDCT and DECT, and a-MRI are presented. The prospects of MRI-radiomics, which solves the problem of subjectivity in radiology and offers new possibilities in the non-invasive diagnosis of HCC, are described. The study of the possibilities of radiology methods in the diagnosis of HCC continues. Conclusion: CEUS is highly effective for imaging tumor vascularization. LDCT is superior to ultrasound in sensitivity and specificity. A shortened MRI protocol delivers better results than an ultrasound as a screening tool for high-risk groups. MRI-radiomics can determine the tumor histological classification and radiogenomics, predict recurrence after surgical resection, and evaluate measurement methodology and response to transarterial chemoembolization and systemic therapy.

Prediction of drug targets related to HCC metastasis from the perspective of programmed cell death based on transformer

Hepatocellular carcinoma (HCC) ranks as the sixth most prevalent cancer globally and the third leading cause of cancer-related deaths. The early diagnosis of HCC is challenging, and its propensity for metastasis results in generally poor prognosis. Existing studies have demonstrated a close association between HCC metastasis and programmed cell death (PCD). However, due to the high-dimensional, high-order nonlinear interactions and complex regulatory mechanisms of genes, establishing the biological process from genes to PCD to HCC metastasis through biological experiments is difficult. These genes represent crucial drug targets for blocking HCC progression. Deep learning technologies, particularly Transformer models, have shown great potential in analyzing clinical and genetic data in oncology. In this study, we identified 147 key genes related to PCD that are closely associated with HCC metastasis and developed a Transformer-based predictive model for HCC metastasis. To elucidate the potential of these genes as drug targets, we first investigated the impact of various types of PCD on the pathophysiology of HCC. Subsequently, we validated the drug responses of different patients through immunoassays and drug sensitivity tests. Finally, survival analysis indicated that these genes significantly affect patient survival rates. In summary, we have identified numerous drug targets influencing HCC metastasis through PCD.

Pilot study of humanized glypican-3-targeted zirconium-89 immuno-positron emission tomography for hepatocellular carcinoma.

Glypican-3 (GPC3)-targeted radioisotope immuno-positron emission tomography (immunoPET) may lead to earlier and more accurate diagnosis of hepatocellular carcinoma (HCC), thus facilitating curative treatment, decreasing early recurrence, and enhancing patient survival. We previously demonstrated reliable HCC detection using a zirconium-89-labeled murine anti-GPC3 antibody (89Zr-αGPC3M) for immunoPET. This study evaluated the efficacy of the humanized antibody successor (αGPC3H) to further clinical translation of a GPC3-based theranostic for HCC. In vitro αGPC3 binding to HepG2 cells was assessed by flow cytometry. In vivo 89Zr-αGPC3H and 89Zr-αGPC3M tumor uptake was evaluated by PET/CT and biodistribution studies in an orthotopic xenograft mouse model of HCC. αGPC3H maintained binding to GPC3 in vitro and 89Zr-αGPC3H immunoPET identified liver tumors in vivo. PET/CT and biodistribution analyses demonstrated high 89Zr-αGPC3H tumor uptake and tumor-to-liver ratios, with no difference between groups. Humanized αGPC3 successfully targeted GPC3 in vitro and in vivo. 89Zr-αGPC3H immunoPET had comparable tumor detection to 89Zr-αGPC3M, with highly specific tumor uptake, making it a promising strategy to improve HCC detection.

Diagnostic and prognostic role of LINC01767 in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a primary contributor to cancer-related mortality on a global scale. However, the underlying molecular mechanisms are still poorly understood. Long noncoding RNAs are emerging markers for HCC diagnosis, prognosis, and therapeutic target. No study of LINC01767 in HCC was published. To conduct a multi-omics analysis to explore the roles of LINC01767 in HCC for the first time. DESeq2 Package was used to analyze different gene expressions. Receiver operating characteristic curves assessed the diagnostic performance. Kaplan-Meier univariate and Cox multivariate analyses were used to perform survival analysis. The least absolute shrinkage and selection operator (LASSO)-Cox was used to identify the prediction model. Subsequent to the validation of LINC01767 expression in HCC fresh frozen tissues through quantitative real time polymerase chain reaction, next generation sequencing was performed following LINC01767 over expression (GSE243371), and Gene Ontology/Kyoto Encyclopedia of Genes and Genomes/Gene Set Enrichment Analysis/ingenuity pathway analysis was carried out. In vitro experiment in Huh7 cell was carried out. LINC01767 was down-regulated in HCC with a log fold change = 1.575 and was positively correlated with the cancer stemness. LINC01767 was a good diagnostic marker with area under the curve (AUC) [0.801, 95% confidence interval (CI): 0.751-0.852, P = 0.0106] and an independent predictor for overall survival (OS) with hazard ratio = 1.899 (95%CI: 1.01-3.58, P = 0.048). LINC01767 nomogram model showed a satisfied performance. The top-ranked regulatory network analysis of LINC01767 showed the regulation of genes participating various pathways. LASSO regression identified the 9-genes model showing a more satisfied performance than 5-genes model to predict the OS with AUC > 0.75. LINC01767 was down-expressed obviously in tumor than para-tumor tissues in our cohort as well as in cancer cell line; the over expression of LINC01767 inhibit cell proliferation and clone formation of Huh7 in vitro. LINC01767 was an important tumor suppressor gene in HCC with good diagnostic and prognostic performance.

Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization

BACKGROUND Enhanced magnetic resonance imaging (MRI) is widely used in the diagnosis, treatment and prognosis of hepatocellular carcinoma (HCC), but it can not effectively reflect the heterogeneity within the tumor and evaluate the effect after treatment. Preoperative imaging analysis of voxel changes can effectively reflect the internal heterogeneity of the tumor and evaluate the progression-free survival (PFS). AIM To predict the PFS of patients with HCC before operation by building a model with enhanced MRI images. METHODS Delineate the regions of interest (ROI) in arterial phase, portal venous phase and delayed phase of enhanced MRI. After extracting the combinatorial features of ROI, the features are fused to obtain deep learning radiomics (DLR)_Sig. DeLong's test was used to evaluate the diagnostic performance of different typological features. K-M analysis was applied to assess PFS in different risk groups, and the discriminative ability of the model was evaluated using the C-index. RESULTS Tumor diameter and diolame were independent factors influencing the prognosis of PFS. Delong's test revealed multi-phase combined radiomic features had significantly greater area under the curve values than did those of the individual phases (P &lt; 0.05).In deep transfer learning (DTL) and DLR, significant differences were observed between the multi-phase and individual phases feature sets (P &lt; 0.05). K-M survival analysis revealed a median survival time of high risk group and low risk group was 12.8 and 14.2 months, respectively, and the predicted probabilities of 6 months, 1 year and 2 years were 92%, 60%, 40% and 98%, 90%,73%, respectively. The C-index was 0.764, indicating relatively good consistency between the predicted and observed results. DTL and DLR have higher predictive value for 2-year PFS in nomogram. CONCLUSION Based on the multi-temporal characteristics of enhanced MRI and the constructed Nomograph, it provides a new strategy for predicting the PFS of transarterial chemoembolization treatment of HCC.

Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature.

Hepatocellular carcinoma (HCC) diagnosis mainly relies on its pathognomonic radiological profile, obviating the need for biopsy. The project of incorporating artificial intelligence (AI) techniques in HCC aims to improve the performance of image recognition. Herein, we thoroughly analyze and evaluate proposed AI models in the field of HCC diagnosis. A comprehensive review of the literature was performed utilizing MEDLINE/PubMed and Web of Science databases with the end of search date being the 30th of September 2023. The MESH terms "Artificial Intelligence," "Liver Cancer," "Hepatocellular Carcinoma," "Machine Learning," and "Deep Learning" were searched in the title and/or abstract. All references of the obtained articles were also evaluated for any additional information. Our search resulted in 183 studies meeting our inclusion criteria. Across all diagnostic modalities, reported area under the curve (AUC) of most developed models surpassed 0.900. A B-mode US and a contrast-enhanced US model achieved AUCs of 0.947 and 0.957, respectively. Regarding the more challenging task of HCC diagnosis, a 2021 deep learning model, trained with CT scans, classified hepatic malignant lesions with an AUC of 0.986. Finally, a MRI machine learning model developed in 2021 displayed an AUC of 0.975 when differentiating small HCCs from benign lesions, while another MRI-based model achieved HCC diagnosis with an AUC of 0.970. AI tools may lead to significant improvement in diagnostic management of HCC. Many models fared better or comparable to experienced radiologists while proving capable of elevating radiologists' accuracy, demonstrating promising results for AI implementation in HCC-related diagnostic tasks.

The potentials of nonlinear polarization with hyperspectral imaging of RNA for hepatocellular carcinoma early diagnosis

BackgroundMost cancers acquire numerous genetic changes in proto-oncogenes as well as tumor-suppressor genes. Cancer's early diagnosis remains a challenge. Recently, nonlinear polarization has revealed the potential as a promising tool for early cancer diagnosis. Laser-induced nonlinear polarization can offer a novel fingerprint signature.MethodsIn this study, nonlinear polarization was adopted for the characterization of both DNA and RNA samples from healthy volunteers. Total DNA and RNA were illuminated with a 656-nm LED source, and the resonance frequencies (scattered and re-emitted signals) were captured and recorded using a hyperspectral camera.ResultsChanges in signal frequency as well as phase shift offered a potent means to differentiate DNA (control) from RNA (control). DNA (control) demonstrated characteristic resonance frequencies that differ from total RNA (control) at the 2nd, 3rd, 4th, and 5th harmonics. While DNA demonstrated a phase shift dominating at 0.88 GHz, RNA dominates at 0.106 GHz. The resonance spectral signature of RNA samples from people with hepatocellular carcinoma (HCC) was compared to that of RNA (control). RNA (HCC) demonstrated distinctive frequency signals at 0.014, 0.021, 0.032, and 0.072 GHz. These characteristics feature could facilitate early HCC diagnosis. While RNA (control) dominates at 0.014 and 0.072 MHz, RNA (HCC) dominates at 0.021 and 0.032.ConclusionAs far as we are aware, this is the initial investigation into the use of simple nonlinear polarization to generate spectral fingerprinting signatures of total DNA and RNA. Furthermore, RNA mutations due to HCC were identified via characteristic nonlinear spectral signature.

Label-free electrochemical aptasensor for the detection of HepG2 hepatocellular carcinoma cells

Hepatocellular carcinoma (HCC) is the most common liver malignancy and is characterized by increasing incidence and high mortality rates. Current methods for the screening and diagnosis of HCC exhibit inherent limitations, highlighting the ever-growing need for the development of new methods for the early diagnosis of HCC. The aim of this work was to develop a novel electrochemical aptasensor for the detection of HepG2 cells, a type of circulating tumor cells that can be used as biomarkers for the early detection of HCC. A carbon screen-printed electrode was functionalized with a composite suspension containing graphene oxide, chitosan, and polyaniline nanoparticles to increase the electrode surface and provide anchoring sites for the HepG2 cell-specific aptamer. The aptamer was immobilized on the surface of the functionalized electrode using multipulse amperometry, an innovative technique that significantly reduces the time required for aptamer immobilization. The innovative platform was successfully employed for the first time for the amplification-free detection of HepG2 cells in a linear range from 10 to 200,000 cells/mL, with a limit of detection of 10 cells/mL. The platform demonstrated high selectivity and stability and was successfully used for the detection of HepG2 cells in spiked human serum samples with excellent recoveries.Graphical abstract

Validation of a Machine Learning Algorithm, EVendo, for Predicting Esophageal Varices in Hepatocellular Carcinoma

BackgroundTreatment with atezolizumab and bevacizumab has become standard of care for advanced unresectable hepatocellular carcinoma (HCC) but carries an increased gastrointestinal bleeding risk. Therefore, patients are often required to undergo esophagogastroduodenoscopy (EGD) to rule out esophageal varices (EV) prior to initiating therapy, which can delay care and lead to unnecessary procedural risks and health care costs. In 2019, the EVendo score was created and validated as a noninvasive tool to accurately screen out patients who were at low risk for having EV that required treatment. We sought to validate whether the EVendo score could be used to accurately predict the presence of EV and varices needing treatment (VNT) in patients with HCC.MethodsThis was a retrospective multicenter cohort study of patients with HCC from 9/2004 to 12/2021. We included patients who underwent EGDs within 1 year after their HCC diagnosis. We collected clinical parameters needed to calculate an EVendo score at the time of EGD and compared the EVendo model prediction to the gold standard endoscopic report in predicting presence of VNT.Results112 with HCC were recruited to this study, with 117 qualifying EGDs. VNT occurred in 39 (33.3%) patients. The EVendo score had a sensitivity of 97.4% and a negative predictive value of 96.9%, supporting the validity in applying EVendo in predicting VNT in HCC.ConclusionIn this study, we validated the use of the EVendo score in ruling out VNT in patients with HCC. The application of the EVendo score could safely defer about 30% of EGDs for EV screening in HCC patients. Although additional validation cohorts are needed, this suggests that EVendo score can potentially be applied in patients with HCC to avoid unnecessary EGDs, which can ultimately mitigate healthcare costs and delays in initiating HCC treatment with atezolizumab and bevacizumab.

ATP citrate lyase promotes the progression of hepatocellular carcinoma by activating the REGγ-proteasome pathway.

The search for novel tumor biomarkers and targets is of significant importance for the early clinical diagnosis and treatment of Hepatocellular Carcinoma (HCC). The mechanisms by which ATP citrate lyase (ACLY) promotes HCC progression remain unclear, and the connection between ACLY and REGγ has not been reported in the literature. In vitro, we will perform overexpression/knockdown of ACLY or overexpression/knockdown of REGγ to investigate the impact of ACLY on HCC cells and its underlying mechanisms. In vivo, we will establish mouse tumor models with overexpression/knockdown of ACLY or overexpression/knockdown of REGγ to study the effect of ACLY on mouse tumors and its mechanisms. Firstly, ACLY overexpression upregulated REGγ expression and activated the REGγ-proteasome pathway, leading to changes in the expression of downstream signaling pathway proteins. This promoted HCC cell proliferation, invasion, and migration in vitro, as well as tumor growth and metastasis in vivo. Secondly, ACLY overexpression increased acetyl-CoA production, upregulated the acetylation level of the REGγ promoter region histone H3K27ac, and subsequently induced REGγ expression. Lastly, enhanced acetylation of the REGγ promoter region histone H3K27ac resulted in upregulated REGγ expression, activation of the REGγ-proteasome pathway, changes in downstream signaling pathway protein expression, and promotion of HCC cell proliferation, invasion, and migration in vitro, as well as tumor growth and metastasis in vivo. Conversely, REGγ knockdown reversed these effects. ACLY and REGγ may serve as potential biomarkers and clinical therapeutic targets for HCC.