Detection Of Hepatocellular Carcinoma Research Articles

Deciphering the cross-talk between miRNA and tight junctions in hepatocellular carcinoma

The most common type of liver cancer is hepatocellular carcinoma (HCC) causes a lower survival rate even after systemic treatment. Previous studies have shown evidence that various molecular and epigenetic mechanisms are involved in the transition of HCC from normal liver cells. Epigenetics plays an important role in maintaining genomic stability in normal liver cells. Apart from the mutation of genes, epigenetic factors are involved in HCC progression. miRNA tends to be a major epigenetic factor involved in regulating major cell cycle pathways. miRNA regulates the HCC progression by inhibiting the major apoptotic pathways and favors angiogenesis and tumor microenvironment. Apart from regulating major pathways, miRNA appears to regulate tight junction integrity. Tight junction proteins appear to be strong barrier proteins involved in cell adhesion and integrity. Disturbance in cell adhesion and integrity leads to the major dysregulation of cell cycle resulting in cancer progression. Moreover, dysregulation of tight junction integrity was observed in the pathogenesis of HCC. The regulation of tight junction proteins via miRNA were studied in various diseases. Here, we discussed the regulation of tight junction proteins via miRNA in HCC progression. This review may focus on the significance of miRNA in cellular function and its role in regulating tight junction proteins that impact in HCC progression which opens a new approach to develop a new diagnostic marker for an early detection of HCC and novel therapeutic approach against HCC.

Re-assessing the diagnostic value of the enhancing "capsule" in hepatocellular carcinoma imaging.

The enhancing "capsule" (EC) in hepatocellular carcinoma (HCC) diagnosis has received varying degrees of recognition across major guidelines. This study aimed to assess the diagnostic utility of EC in HCC detection. We retrospectively analyzed patients who underwent pre-surgical computed tomography (CT) and hepatobiliary agent-enhanced magnetic resonance imaging (HBA-MRI) between January 2016 and December 2019. A single hepatic tumor was confirmed based on the pathology of each patient. Three radiologists independently reviewed the images according to the Liver Imaging Reporting and Data System (LIRADS) v2018 criteria and reached a consensus. Interobserver agreement for EC before reaching a consensus was quantified using Fleiss κ statistics. The impact of EC on the LI-RADS classification was assessed by comparing the positive predictive values for HCC detection in the presence and absence of EC. In total, 237 patients (median age, 60 years; 184 men) with 237 observations were included. The interobserver agreement for EC detection was notably low for CT (κ=0.169) and HBA-MRI (κ=0.138). The presence of EC did not significantly alter the positive predictive value for HCC detection in LI-RADS category 5 observations on CT (94.1% [80/85] vs. 94.6% [88/93], P=0.886) or HBA-MRI (95.7% [88/92] vs. 90.6% [77/85], P=0.178). The diagnostic value of EC in HCC diagnosis remains questionable, given its poor interobserver agreement and negligible impact on positive predictive values for HCC detection. This study challenges the emphasis on EC in certain diagnostic guidelines and suggests the need to re-evaluate its role in HCC imaging.

Transforming 'Junk' DNA into Cancer Warriors: The Role of Pseudogenes in Hepatocellular Carcinoma.

In the dynamic landscape of hepatocellular carcinoma (HCC) or the liver cancer research, pseudogenes have emerged from the shadows of genetic obscurity to become central figures, significantly influencing the disease molecular development and clinical trajectory. This review explores a transformative shift in perspective, recognizing pseudogenes not as genetic remnants without function, but as critical regulators in the molecular underpinnings of HCC. Engaging in complex interactions such as microRNA sponging, gene expression modulation, and signaling pathway disruptions, pseudogenes orchestrate a part of the molecular complexity driving tumor genesis, progression, and drug resistance in the liver cancer. Their unique expression patterns in hepatoma tissues herald new opportunities for early HCC detection, offering insights into patient prognosis, and identifying novel targets for therapeutic intervention of this disease. Such advancements underscore the importance of pseudogenes in enriching our understanding and management of HCC, paving the way for more effective diagnostic strategies and targeted therapies in the ongoing battle against this challenging malignancy.

Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study.

Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood-based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. A three-phase multicentre study was conducted to screen, optimise and validate HCC-specific differentially methylated regions (DMRs) using next-generation sequencing and quantitative methylation-specific PCR (qMSP). Genome-wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre- and postoperative plasma samples from 103 HCC patients and correlated with 2-year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p<.001). HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC-specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at-risk populations.

The Future Role of Abdominal US in Hepatocellular Carcinoma Surveillance.

Abdominal US is currently the best-validated surveillance strategy for hepatocellular carcinoma (HCC) in at-risk patients. It is the only modality shown to have completed all five phases of validation and can achieve high sensitivity and specificity for HCC detection, especially when conducted by expert sonographers in high-volume centers. However, US also has limitations, including operator dependency and varying sensitivity in clinical practice. Further, the sensitivity of US for early-stage HCC detection is lower in patients with obesity or nonviral liver disease, increasingly common populations undergoing surveillance. Imaging-based and blood-based surveillance strategies, including abbreviated MRI and biomarker panels, may overcome some limitations of US-based surveillance. Both strategies have promising test performance in phase II and phase III biomarker studies and are undergoing prospective validation. Considering the variation in HCC risk and test performance between patients, there will likely be a shift away from a one-size-fits-all approach and toward precision screening, in which the "best" test is selected based on individual patient characteristics. In this upcoming era of precision HCC screening among patients with cirrhosis, US will likely continue to have an important, albeit reduced, surveillance role.

Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

Background & AimsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of the screening modalities. MethodsWe developed a multicenter prospective cohort of cirrhotic patients undergoing surveillance with MRI, and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up. ResultsWe identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who didn’t develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine, had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, patatin-like phospholipase domain-containing protein 3 (PNPLA3) and transmembrane 6 superfamily member 2 (TMS6SF2) SNPs, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top 6 variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC=0.88 [0.83-0.93]). Finally, 23 metabolites distinguished Cases with Liver Imaging Reporting and Data System (LI-RADS)-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases-LR3. ConclusionsThis study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as main biomarkers of HCC risk, and microbiota-derived metabolites as main contributors to HCC development. Impact and ImplicationsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, blood biomarkers in particular. Longitudinal collection of paired blood samples and MRI images from cirrhotic patients is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early stage HCC detection for cirrhotic patients undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.

Clinical outcomes of hepatocellular carcinoma surveillance in Melbourne, Australia.

Ultrasound surveillance for hepatocellular carcinoma (HCC) may improve early tumour detection but may additionally result in surveillance-related harm through increased evaluation of non-HCC lesions. The incidence of these outcomes has not been reported outside North America. We aimed to report the outcomes of HCC surveillance with respect to both surveillance-related benefits and harms. We reviewed all HCC surveillance ultrasounds at a large Victorian tertiary hospital network in 2017 and followed their outcomes until 2021. Surveillance-related benefits were defined as early-stage HCC detection. Surveillance-related harm was defined as contrast imaging, biopsies or surgery performed to evaluate non-HCC liver lesions or false-positive alpha-fetoprotein levels. Five hundred and fifty-three patients were included (mean age 54.5 ± 12.3 years, males 67.5%, cirrhosis 50.3%). The most common liver disease aetiology was hepatitis B (53.9%). Over a median of 4.7 years follow-up, early-stage HCC was detected in 3.3% (5.4% in cirrhotic vs 1.1% in non-cirrhotic patients, P < 0.01). 75% of all HCCs were early-stage. Surveillance-related harm occurred in 12.5% (15.5% in cirrhotic vs 9.5% in non-cirrhotic patients, P < 0.04), although most harm was mild (12.1%). In subgroup analysis, the detection of early-stage HCC ranged between 0% (screened outside of guideline criteria and alcoholic cirrhotic patients) and 7.2% (hepatitis C cirrhosis). Harm occurred between 9% (non-cirrhotic hepatitis B) and 20.8% (thrombocytopenia). In our study, HCC surveillance was associated with early tumour detection, although many patients experienced mild surveillance-related harm. Novel surveillance strategies and pathways are required to improve detection in high-risk patients and minimise harm in low-risk patients.

Increased prevalence but decreased survival of nonviral hepatocellular carcinoma compared to viral hepatocellular carcinoma in recent ten years

Due to the comprehensive hepatitis B virus vaccination program in Taiwan since 1986, the development of antiviral therapy for chronic hepatitis B and chronic hepatitis C infection and covered by National health insurance. Besides, the increased prevalence of nonalcoholic fatty liver disease (NAFLD) and currently, approved therapy for NAFLD remain developing. The etiology of liver-related diseases such as cirrhosis and hepatocellular carcinoma required reinterpretation. This study aimed to analyze the incidence and outcome of hepatocellular carcinoma (HCC) due to viral (hepatitis B and hepatitis C) infection compared to that of nonviral etiology. We retrospectively analyzed patients with HCC from January 2011 to December 2020 from the cancer registry at our institution. Viral-related hepatitis was defined as hepatitis B surface antigen positivity or anti-hepatitis C virus (HCV) antibody positivity. A total of 2748 patients with HCC were enrolled, of which 2188 had viral-related HCC and 560 had nonviral-related HCC. In viral HCC group, the median age at diagnosis was significantly lower (65 years versus 71 years, p < 0.001), and the prevalence of early-stage HCC, including stage 0 and stage A Barcelona Clinic Liver Cancer, was significantly higher (52.9% versus 33.6%, p < 0.001). In nonviral HCC group, alcohol use was more common (39.9% versus 30.1%, p < 0.001), the prevalence of type 2 diabetes mellitus (T2DM) was higher (54.5% versus 35.1%, p < 0.001), and obesity was common (25.0% versus 20.5%, p = 0.026). The prevalence of nonviral HCC increased significantly from 19.2 to 19.3% and 23.0% in the last 10 years (p = 0.046). Overall survival was better in the viral HCC group (5.95 years versus 4.00 years, p < 0.001). In the early stage of HCC, overall survival was still better in the viral HCC group (p < 0.001). The prevalence of nonviral HCC has significantly increased in the last ten years. The overall survival was significantly lower in the nonviral HCC, perhaps because the rate of early HCC detection is lower in nonviral HCC and anti-viral therapy. To detect nonviral HCC early, we should evaluate liver fibrosis in high-risk groups (including people with obesity or T2DM with NAFLD/NASH and alcoholic liver disease) and regular follow-up for those with liver fibrosis, regardless of cirrhosis.

Elevation of S2-bound α1-acid glycoprotein is associated with chronic hepatitis C virus infection and hepatocellular carcinoma.

There is an urgent need for new high-quality markers for the early detection of hepatocellular carcinoma (HCC). Åström etal. suggested that S2-bound α1-acid glycoprotein (AGP) might be a promising marker. Consequently, we evaluated the predictive advantage of S2-bound AGP in the early detection of HCC. In a retrospective case-control study of patients chronically infected with hepatitis C virus (HCV) and treated with direct-acting antiviral agents (n = 93), we measured S2-bound AGP using the HepaCheC® ELISA kit (Glycobond AB, Linköping, SE) at the start of treatment, end of treatment and follow-up (maximum: 78 months). Patients were retrospectively propensity score matched (1:2). Thirty-one patients chronically infected with HCV developed HCC after a sustained virological response, while 62 did not. In addition, samples of patients with chronic hepatitis B virus infection, metabolic dysfunction-associated steatotic liver disease and HCC of different etiologies were analysed. S2-bound AGP elevation in HCC patients was confirmed. However, we did not observe a predictive advantage of S2-bound AGP for the early detection of HCC during treatment and follow-up. Interestingly, S2-bound AGP levels correlated with aspartate aminotransferase (ρ = .56, p = 9.5×10-15) and liver elastography (ρ = .67, p = 2.2×10-16). Of note, S2-bound AGP decreased in patients chronically infected with HCV after treatment-induced HCV clearance. Fucosylated S2-bound AGP levels were elevated in patients with chronic HCV and HCC. The potential role of S2-bound AGP as a novel tumour marker requires further investigation.

Dual-tracer PET/CT in the management of hepatocellular carcinoma

Background & AimsCombined 18F-fluorodeoxyglucose (FDG) and 11C-acetate (dual-tracer) positron emission tomography-computed tomography (PET-CT) is being increasingly performed for the management of hepatocellular carcinoma (HCC), although its role is not well defined. Therefore, we evaluated its effectiveness in (i) staging, (ii) characterization of indeterminate lesions on conventional imaging, and (iii) detection of HCC in patients with unexplained elevations in serum alpha-fetoprotein (AFP) levels. MethodsWe retrospectively assessed 525 consecutive patients from three tertiary centers between 2014 and 2020. For staging, we recorded new lesion detection rates, changes in the Barcelona Clinic Liver Cancer (BCLC) classification, and treatment allocation due to dual-tracer PET-CT. To characterize indeterminate lesions and unexplained elevation of serum AFP levels, the sensitivity and specificity of dual-tracer PET-CT in diagnosing HCC were evaluated. A Multidisciplinary external review and a cost-benefit analysis of patients for metastatic screening were also performed. ResultsDual-tracer PET/CT identified new lesions in 14.3% of 273 staging patients, resulting in BCLC upstaging in 11.7% and treatment modifications in 7.7%. It upstaged 8.1% of 260 patients undergoing metastatic screening, with an estimated savings of US$495 per patient. It had a sensitivity and specificity of 80.7% (95% CI 71.2-88.6%) and 94.8% (95% CI 90.4-98.6%), respectively, for diagnosing HCC in 201 indeterminate lesions. It detected HCC in 45.1% of 51 patients with unexplained elevations in serum AFP concentrations. External review revealed substantial agreement between local and external image interpretation and patient assessment (n=273, κ=0.822; 95% CI 0.803-0.864). ConclusionsDual-tracer PET/CT provides additional value to conventional imaging in HCC patients by improving staging, confirming HCC diagnosis with high accuracy in patients with indeterminate lesions, and detecting HCC in patients with unexplained elevation of serum AFP.• Impact and implications• Dual-tracer PET-CT detected 12% more disease in HCC patients undergoing staging than CT or MRI, resulting in change in treatment in 8% of cases and a cost saving of US$495 per patient.• It is also able to accurately detect HCC in high-risk cases where CT or MRI are equivocal or normal.• Dual-tracer PET/CT provides additional value to conventional imaging in HCC patients by improving staging, confirming HCC diagnosis with high accuracy in patients with indeterminate lesions, and detecting HCC in patients with unexplained elevation of serum AFP.

Clinical Utility of Cytokeratins for Accurate Diagnosis of Hepatocellular Carcinoma Among Hepatitis C Virus High-Risk Patients.

Hepatocellular carcinoma (HCC) is a primary malignancy of the liver and a global health problem. It is often diagnosed at advanced stage where hopeless for effective therapies. Identification of more reliable biomarkers for early detection of HCC is urgently needed. Cytokeratins are a marker of hepatic progenitor cells and act as a key player in tumor invasion. Herein, we sought to develop a novel score based on the combination of cytokeratin 18 (CK18) and cytokeratin 19 (CK19) with routine laboratory tests for accurate detection of HCC. Serum CK18, CK 19, α-fetoprotein, albumin and platelets count were assayed in HCC patients (75), liver cirrhosis patients (55) and healthy control (20). Areas under receiving operating curve (AUCs) were calculated and used for construction on novel score. A novel score named CK-HCC = CK 19 (ng/ml)×0.001+ CK18 (ng/ml)×0.004 + AFP (U/L)×5.4 - Platelets count (×109)/L×0.003 - Albumin (g/L)×0.27-36 was developed. CK-HCC score produces AUC of 0.919 for differentiating patients with HCC from those with liver cirrhosis with sensitivity and specificity of a cut-off 1.3 (i.e., less than 1.3 the case is considered cirrhotic, whereas above 1.3 it is considered HCC. CK-HCC score could replace AFP during screening of HCV patients and early detection of HCC.

Evaluation of Circular RNA SMARCA5 as a Novel Biomarker for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the fourth most prevalent type of cancer in Egypt and the sixth globally. Most patients with HCC are typically diagnosed during the advanced stages of the disease due to the absence of biomarkers for early detection. Consequently, these patients miss the optimal timeframe for receiving therapy. we aimed to assess the circular RNA SMARCA5 level and SMARCA5 mRNA gene expression as a potential biomarker for early detection of HCC. The present study utilized a case-control design comprising 159 participants. Participants were selected from both inpatient and outpatient hepatology and gastroenterology clinics at the National Liver Institute Hospital, Menoufia University. They were evenly distributed among three groups: Group I: 53 control subjects, Group II: 53 HCV cirrhotic patients, and Group III: 53 HCC patients. Tumor staging was done using BCLC staging system. Each patient underwent a thorough clinical examination, radiological examination, complete history taking, and serum Alpha-fetoprotein (AFP) assessment and detection of circular RNASMARCA5 and SMARCA5mRNA gene sutilizing quantitative real-time polymerase chain reaction. Statistically substantial differences were observed in the examined groups in terms of AFP, SMARCA5, and CircSMARCA5 (P-value = 0.001, 0.001 & 0.001). CircSMARCA5 and SMARCA5mRNA were markedly down regulated in the HCC group compared to HCV cirrhotic patients and controls. ROC analysis for early HCC diagnosis demonstrated that the CircSMARCA5 area under the curve (AUC) at cut-off point 4.55 yielded a specificity of 83.8% and sensitivity of 91.7%. The AUC for AFP at a cut-off point of 515ng/ml yielded a specificity of 89.2% and a sensitivity of 91.3%. CircSMARCA5 has the potential to be a more sensitive predictor of HCC disease compared to AFP.

Comparison of non-contrast abbreviated MRI and ultrasound as surveillance modalities for HCC

Ultrasonography (US) is recommended for HCC surveillance in high-risk patients, but has limited performance in detecting early-stage HCC. We aimed to compare the diagnostic performance of biannual US and annual non-contrast abbreviated magnetic resonance imaging (NC-AMRI) as HCC surveillance modalities in high-risk patients. This prospective, multicenter cohort study enrolled participants with an estimated annual risk of HCC greater than 5% between October 2015 and April 2017. Participants underwent six rounds of HCC surveillance at 6-month intervals, with both US and NC-AMRI at rounds 1, 3, and 5, and only US at rounds 2, 4, and 6. The sensitivity, diagnostic yield (DY), and false referral rate (FRR) for HCC detection by US and NC-AMRI were compared. In total, 208 participants underwent 980 US and 516 NC-AMRI examinations during 30 months of follow-up. Among them, 34 HCCs were diagnosed in 31 participants, with 20 (64.5%) classified as very early and 11 (35.5%) as early-stage. The sensitivity of annual NC-AMRI (71.0%, 22/31) was marginally higher than that of biannual US (45.2%, 14/31; p = 0.077). NC-AMRI showed a significantly higher DY than US (4.26% vs. 1.43%, p < 0.001), with a similar FRR (2.91% vs. 3.06%, p = 0.885). A simulation of alternating US and NC-AMRI at 6-month intervals yielded a sensitivity of 83.0% (26/31), significantly exceeding that of biannual US (p = 0.006). Annual NC-AMRI showed a marginally higher sensitivity than biannual US for HCC detection in high-risk patients. The DY of annual NC-AMRI was significantly higher than that of biannual US, without increasing the FRR. Alternating US and NC-AMRI at 6-month intervals could be an optimal surveillance strategy for high-risk patients. Current guidelines permit the use of magnetic resonance imaging (MRI) as a surveillance tool for hepatocellular carcinoma (HCC) in patients in whom ultrasonography (US) is inadequate. However, the specific indications, imaging sequences, and surveillance intervals for MRI surveillance remain unclear. In our study, we found that annual non-contrast (NC)-abbreviated MRI (AMRI) exhibited marginally higher sensitivity and significantly better diagnostic yield than biannual US in high-risk patients for HCC. Adopting alternating US and NC-AMRI at 6-month intervals demonstrated significantly improved sensitivity compared to biannual US, making it a potentially optimal surveillance strategy for high-risk patients. ClinicalTrials.gov Identifier: NCT02551250.

MASLD-Related HCC-Update on Pathogenesis and Current Treatment Options.

Hepatocellular carcinoma (HCC) is a common complication of chronic liver diseases and remains a relevant cause of cancer-related mortality worldwide. The global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) as a risk factor for hepatocarcinogenesis is on the rise. Early detection of HCC has been crucial in improving the survival outcomes of patients with metabolic dysfunction-associated steatohepatitis (MASH), even in the absence of cirrhosis. Understanding how hepatocarcinogenesis develops in MASH is increasingly becoming a current research focus. Additive risk factors such as type 2 diabetes mellitus (T2DM), genetic polymorphisms, and intestinal microbiota may have specific impacts. Pathophysiological and epidemiological associations between MASH and HCC will be discussed in this review. We will additionally review the available tumor therapies concerning their efficacy in MASH-associated HCC treatment.

Three-Dimensional Structure of Novel Liver Cancer Biomarker Liver Cancer-Specific Serine Protease Inhibitor Kazal (LC-SPIK) and Its Performance in Clinical Diagnosis of Hepatocellular Carcinoma (HCC).

LC-SPIK is a liver cancer-specific isoform of Serine Protease Inhibitor Kazal and has been proposed as a new biomarker for the detection of HCC given its unique 3D structure, which differs from normal pancreatic SPIK. An ELISA technology based on its unique structure was developed to use LC-SPIK as an effective biomarker for the clinical diagnosis of HCC. AFP, the most widely used biomarker for HCC surveillance currently, suffers from poor clinical performance, especially in the detection of early-stage HCC. In one case-control study, which included 164 HCC patients and 324 controls, LC-SPIK had an AUC of 0.87 compared to only 0.70 for AFP in distinguishing HCC from liver disease controls (cirrhosis, HBV/HCV). LC-SPIK also performed significantly better than AFP for the 81 patients with early-stage HCC (BCLC stage 0 and A), with an AUC of 0.85 compared to only 0.61 for AFP. Cirrhosis is the major risk factor for HCC; about 80% of patients with newly diagnosed HCC have preexisting cirrhosis. LC-SPIK's clinical performance was also studied in HCC patients with viral and non-viral cirrhosis, including cirrhosis caused by metabolic dysfunction-associated steatotic liver disease (MASLD) and alcoholic liver disease (ALD). In a total of 163 viral cirrhosis patients with 93 HCC patients (50 early-stage), LC-SPIK had an AUC of 0.85, while AFP had an AUC of 0.70. For patients with early-stage HCC, LC-SPIK had a similar AUC of 0.83, while AFP had an AUC of only 0.60. For 120 patients with nonviral cirrhosis, including 62 HCC (23 early-stage) patients, LC-SPIK had an AUC of 0.84, while AFP had an AUC of only 0.72. For the 23 patients with early-stage HCC, LC-SPIK had a similar AUC of 0.83, while the AUC for AFP decreased to 0.65. All these results suggest that LC-SPIK exhibits significantly better performance in the detection of HCC than AFP in all etiologies of liver diseases. In addition, LC-SPIK accurately detected the presence of HCC in 71-91% of HCC patients with false-negative AFP test results in viral-associated HCC and non-viral-associated HCC.

A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images

BackgroundAutomatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning based network to detect HCC from dynamic CT images.MethodsDynamic CT images of 595 patients with HCC were used. Tumors in dynamic CT images were labeled by radiologists. Patients were randomly divided into training, validation and test sets in a ratio of 5:2:3, respectively. We developed a hierarchical fusion strategy of deep learning networks (HFS-Net). Global dice, sensitivity, precision and F1-score were used to measure performance of the HFS-Net model.ResultsThe 2D DenseU-Net using dynamic CT images was more effective for segmenting small tumors, whereas the 2D U-Net using portal venous phase images was more effective for segmenting large tumors. The HFS-Net model performed better, compared with the single-strategy deep learning models in segmenting small and large tumors. In the test set, the HFS-Net model achieved good performance in identifying HCC on dynamic CT images with global dice of 82.8%. The overall sensitivity, precision and F1-score were 84.3%, 75.5% and 79.6% per slice, respectively, and 92.2%, 93.2% and 92.7% per patient, respectively. The sensitivity in tumors < 2 cm, 2–3, 3–5 cm and > 5 cm were 72.7%, 92.9%, 94.2% and 100% per patient, respectively.ConclusionsThe HFS-Net model achieved good performance in the detection and segmentation of HCC from dynamic CT images, which may support radiologic diagnosis and facilitate automatic radiomics analysis.

Abstract 3774: Evaluation of FibraChek™ for non-invasive detection of hepatic fibrosis and hepatocellular carcinoma

Abstract Introduction and Objectives: The incidence of hepatocellular carcinoma (HCC) has almost tripled since the early 1980s in the United States where it is the fastest rising cause of cancer-related deaths. Advanced liver fibrosis and cirrhosis are ones of major risk factors for HCC. The recent evidence demonstrates that successfully treating the cause of early to moderate hepatic fibrosis may reverse most. For this reason, detecting hepatic fibrosis in an early stage is crucial. Liver biopsy is currently the gold standard for the assessment of hepatic fibrosis in clinical practice. Thus, there is an urgent clinical need for the development of non-invasive blood-based tests because of its ease of obtaining biological material. Previously, we developed FibraChek™, non-invasive blood-based tests. In this study, we tested the performance of FibraChek™ on detecting hepatic fibrosis and HCC in the US. Methods: The performance of FibraChek™ was evaluated in a single-institutional cohort of 14 prospectively collected subjects presenting for chronic liver disease (NAFLD/NASH) patients with hepatic fibrosis, 19 prospectively collected subjects diagnosed with HCC, and 12 prospectively collected controls from the US. The algorithm uses weighted value of the 5 biomarkers: AST, ALT, Platelet, Taurocholic Acid (TCA) &amp; Tyrosine plus age to derive a risk score. The ability of the test to identify patients harboring hepatic fibrosis or HCC was assessed. Hepatic fibrosis status was confirmed by tissue biopsy or definitive surgery. Diagnostic performance was assessed using AUC. Results: FibraChek™ provided an AUC of 0.923 with an overall sensitivity of 93.9%, specificity of 81.8%, NPV 91.2% and PPV 81.8%. Interestingly, risk scores in HCC cohort indicated higher than those in patients with hepatic fibrosis. Thus, FibraChek™ may be also able to use for HCC detection. Conclusions: Serum levels of a biomarker panel enabled the accurate discrimination of hepatic fibrosis and controls. The FibraChek™ test can achieve the easy, efficient, and accurate detection of hepatic fibrosis and HCC in a non-invasive patient setting. Citation Format: Sunao Tanaka, Guoxiang Xie, Hideki Furuya, Wei Jia, Charles J. Rosser. Evaluation of FibraChek™ for non-invasive detection of hepatic fibrosis and hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3774.

Abstract 2585: First in human study with a novel peptide binder to glypican-3, demonstrates high specificity as a PET imaging agent in patients with hepatocellular carcinoma

Abstract Introduction: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy. The American Association for the Study of Liver Disease recommends surveillance for high-risk individuals with abdominal ultrasound, triple phase contrast CT or MRI. However, these imaging techniques have limited sensitivity in classifying lesions smaller than 2 centimeters. The use of [18F]FDG Positron Emission Tomography (PET) is constrained due to insufficient uptake by HCC lesions over background liver uptake. Hence, there is an urgent need for more precise radiotracers for HCC. This study introduces the development of a novel radiotracer that binds to glypican-3 (GPC3), a cell membrane-anchored oncofetal protein overexpressed in HCC with minimal normal tissue expression. Methods: [68Ga]Ga-RYZ-GPC3 is composed of a small macrocyclic peptide binder with high affinity to GPC3 linked with a tetraxetan moiety capable of chelating a variety of radioisotopes including positron-emitting 68Ga and other radiometals. The unlabeled binder to GPC3 was synthesized by the sponsor and provided to three imaging centers in India as part of investigator-initiated trials reviewed and approved by each site’s institutional review board and ethics committee. Labeling with 68Ga and quality checks of the product was performed locally at each center. Patients with high clinical suspicion or with confirmed HCC who gave informed consent received injections of 1.5-5.5 mCi of [68Ga]Ga-RYZ-GPC3 and underwent PET-CT scanning at predetermined intervals. Some patients underwent companion [18F]FDG PET-CT scans in accordance with local guidelines. Results: A total of 64 patients underwent [68Ga]Ga-RYZ-GPC3 PET-CT scans. The median age within the cohort was 61 (41-83), 22% were female. Liver cirrhosis was present in 72% of patients, attributed to hepatitis B, hepatitis C or NASH in 17%, 13% and 20% of cases. Notably, 92% of patients exhibited at least one positive lesion on [68Ga]Ga-RYZ-GPC3 scans. The median SUVmax of GPC3-avid liver lesions was 15.5 (range 1.1 to 137.0) while the median liver SUVmean was 1.6 (0.3-7.9). Physiologic uptake was predominantly observed in the kidneys, the primary route of clearance, with a median SUVmean of 10.9 (2.2-20.7). Additionally, 20 patients underwent [18F]FDG PET-CT scan for comparison. The median SUVmax of lesions on 68Ga-RYZ-GPC3 vs [18F]FDG PET was 11.0 (1.1-137.0) vs 3.8 (1.2-12.2). Conclusion: Early human imaging results in patients with HCC indicate that [68Ga]Ga-RYZ-GPC3 has high tumor lesion specificity compared to normal liverand demonstrates the potential of [68Ga]Ga-RYZ-GPC3 to improve detection of HCC over conventional [18F]FDG PET-CT. In addition, the binder could be complexed with a therapeutic radioisotope as a novel targeted therapeutic option for HCC. Further investigation of this first-in-class binder to HCC is warranted. Citation Format: Chandresakhar Bal, Sanjana Ballal, Kumar Kallur, Anna Karmann, Ye Yuan, Jessica Rearden, Kathryn Shah, Charlotte Lorenz, Susan Moran, Ken Song, Ishita Sen. First in human study with a novel peptide binder to glypican-3, demonstrates high specificity as a PET imaging agent in patients with hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2585.

Abstract 4802: Accuracy of the GALAD serologic model in the diagnosis of hepatocellular carcinoma in Ghanaian patients

Abstract Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide. In sub-Saharan Africa, HCC is the second most common cancer in men and the sixth in women. African patients present with HCC at a young age and at advanced stage of disease. Improved surveillance can increase early HCC detection. The GALAD score has good sensitivity in the diagnosis of HCC in Asia, Europe and North America, however, it has not been validated in an African cohort. The aim of this study was to assess the performance of the GALAD score in the diagnosis of HCC in Ghanaian patients. Methods: Clinical data from patients with cirrhosis (n=93) or HCC (n=78) from out-patient hepatology clinics at 3 teaching hospitals in Ghana were abstracted, and serum samples analyzed. A logistic regression model predicting HCC status based on GALAD score was constructed to obtain the Receiver Operating Characteristics (ROC) curve for GALAD. The area under the curve (AUC) with 95% confidence interval was calculated and used to assess the performance of the GALAD score in surveillance for HCC. Results: The median AFP (5010.2 vs. 3.4), L3% (28.3 vs. 0.3) and DCP (507.6 vs. 0.2) levels were all significantly higher among HCC cases than the controls (p&amp;lt;0.0001). The median GALAD score was also higher among HCC patients (8.0 vs. -4.1, p&amp;lt;0.0001). The AUC of the GALAD score in the diagnosis of HCC was 0.86 (95% CI 0.79 - 0.92). At a cut-off value of -0.37, the GALAD score had a sensitivity of 0.81 and a specificity of 0.86. In a re-fit of the logistic regression model, the most significant factors in the GALAD model in our cohort were AFP-L3% and log(DCP). The AUC of the new GALAD model after model selection was 0.89. Conclusion: The GALAD score can be used to detect HCC in Ghana and has the potential to improve HCC surveillance in low-resource settings in sub-Saharan Africa. Citation Format: Yvonne Ayerki Nartey, Ju Dong Yang, Tyler Zemla, Joshua Ayawin, Shadrack Osei Asibey, Mohamed El-Kassas, Sally Afua Bampoh, Amoako Duah, Adwoa Agyei-Nkansah, Yaw Asante Awuku, Mary Yeboah Afihene, Hiroyuki Yamada, Jun Yin, Amelie Plymoth, Lewis Rowland Roberts. Accuracy of the GALAD serologic model in the diagnosis of hepatocellular carcinoma in Ghanaian patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4802.

Automatic segmentation of hepatocellular carcinoma on dynamic contrast-enhanced MRI based on deep learning

Objective. Precise hepatocellular carcinoma (HCC) detection is crucial for clinical management. While studies focus on computed tomography-based automatic algorithms, there is a rareness of research on automatic detection based on dynamic contrast enhanced (DCE) magnetic resonance imaging. This study is to develop an automatic detection and segmentation deep learning model for HCC using DCE. Approach: DCE images acquired from 2016 to 2021 were retrospectively collected. Then, 382 patients (301 male; 81 female) with 466 lesions pathologically confirmed were included and divided into an 80% training-validation set and a 20% independent test set. For external validation, 51 patients (42 male; 9 female) in another hospital from 2018 to 2021 were included. The U-net architecture was modified to accommodate multi-phasic DCE input. The model was trained with the training-validation set using five-fold cross-validation, and furtherly evaluated with the independent test set using comprehensive metrics for segmentation and detection performance. The proposed automatic segmentation model consisted of five main steps: phase registration, automatic liver region extraction using a pre-trained model, automatic HCC lesion segmentation using the multi-phasic deep learning model, ensemble of five-fold predictions, and post-processing using connected component analysis to enhance the performance to refine predictions and eliminate false positives. Main results. The proposed model achieved a mean dice similarity coefficient (DSC) of 0.81 ± 0.11, a sensitivity of 94.41 ± 15.50%, a precision of 94.19 ± 17.32%, and 0.14 ± 0.48 false positive lesions per patient in the independent test set. The model detected 88% (80/91) HCC lesions in the condition of DSC > 0.5, and the DSC per tumor was 0.80 ± 0.13. In the external set, the model detected 92% (58/62) lesions with 0.12 ± 0.33 false positives per patient, and the DSC per tumor was 0.75 ± 0.10. Significance. This study developed an automatic detection and segmentation deep learning model for HCC using DCE, which yielded promising post-processed results in accurately identifying and delineating HCC lesions.