Early Hepatocellular Carcinoma Research Articles

Diagnostic and prognostic performances of GALAD score in staging and 1-year mortality of hepatocellular carcinoma: A prospective study

BACKGROUND The GALAD score has improved early hepatocellular carcinoma (HCC) detection rate. The role of the GALAD score in staging and predicting tumor characteristics or clinical outcome of HCC remains of particular interest. AIM To determine the diagnostic/prognostic performances of the GALAD score at various phases of initial diagnosis, tumor features, and 1-year mortality of HCC and compare the performance of the GALAD score with those of other serum biomarkers. METHODS This prospective, diagnostic/prognostic study was conducted among patients with newly diagnosed HCC at the liver center of Vajira Hospital. Eligible patients had HCC staging allocation using the Barcelona Clinic Liver Cancer (BCLC) categorization. Demographics, HCC etiology, and HCC features were recorded. Biomarkers and the GALAD score were obtained at baseline. The performance of the GALAD score and biomarkers were prospectively assessed. RESULTS Exactly 115 individuals were diagnosed with HCC. The GALAD score increased with disease severity. Between BCLC-0/A and BCLC-B/C/D, the GALAD score predicted HCC staging with an area under the curve (AUC) of 0.868 (95%CI: 0.80–0.93). For identifying the curative HCC, the AUC of GALAD score was significantly higher than that of Alpha-fetoprotein (AFP) (0.753) and Lens culinaris agglutinin-reactive fraction of AFP-L3 (0.706), and as good as that of Protein induced by vitamin K absence-II (PIVKA-II) (0.897). For detecting aggressive features, the GALAD score gave an AUC of 0.839 (95%CI: 0.75–0.92) and significantly outperformed compared to that of AFP (0.761) and AFP-L3 (0.697), with a trend of superiority to that of PIVKA-II (0.772). The performance to predict 1-year mortality of GALAD score (AUC: 0.711, 95%CI: 0.60–0.82) was better than that of AFP (0.541) and as good as that of PIVKA-II (0.736). The optimal cutoff value of GALAD score was ≥ 6.83, with a specificity of 72.63% for exhibiting substantial reduction in the 1-year mortality. CONCLUSION The GALAD model can diagnose HCC at the curative stage, including the characteristic of advanced disease, more than that by AFP and AFP-L3, but not PIVKA-II. The GALAD score can be used to predict the 1-year mortality of HCC.

Does depressurization of the portal vein before liver transplantation affect the recurrence of HCC? A nested case-control study

BackgroundPortal hypertension (PHT) has been proven to be closely related to the development of hepatocellular carcinoma (HCC). Whether PHT before liver transplantation (LT) will affect the recurrence of HCC is not clear.Methods110 patients with depressurization of the portal vein (DPV) operations (Transjugular Intrahepatic Portosystemic Shunt—TIPS, surgical portosystemic shunt or/and splenectomy) before LT from a HCC LT cohort, matched with 330 preoperative non-DPV patients; this constituted a nested case-control study. Subgroup analysis was based on the order of DPV before or after the occurrence of HCC.ResultsThe incidence of acute kidney injury and intra-abdominal bleeding after LT in the DPV group was significantly higher than that in non-DPV group. The 5-year survival rates in the DPV and non-DPV group were 83.4% and 82.7% respectively (P = 0.930). In subgroup analysis, patients in the DPV prior to HCC subgroup may have a lower recurrence rate (4.7% vs.16.8%, P = 0.045) and a higher tumor free survival rate (88.9% vs.74.4%, P = 0.044) after LT under the up-to-date TNMI–II stage, while in TNM III stage, there was no difference for DPV prior to HCC subgroup compared with the DPV after HCC subgroup or the non-DPV group.ConclusionCompared with DPV after HCC, DPV treatment before HCC can reduce the recurrence rate of HCC after early transplantation (TNM I-II). DPV before LT can reduce the recurrence of early HCC.

Treatments for early Hepatocellular carcinoma: Resection or Ablation, How to make a decision？

Treatments for early Hepatocellular carcinoma: Resection or Ablation, How to make a decision？

The Role of HSP90 and TRAP1 Targets on Treatment in Hepatocellular Carcinoma.

Hepatocellular Carcinoma (HCC) is the predominant form of liver cancer and arises due to dysregulation of the cell cycle control machinery. Heat Shock Protein 90 (HSP90) and mitochondrial HSP90, also referred to as TRAP1 are important critical chaperone target receptors for early diagnosis and targeting HCC. Both HSP90 and TRAP1 expression was found to be higher in HCC patients. Hence, the importance of HSP90 and TRAP1 inhibitors mechanism and mitochondrial targeted delivery of those inhibitors function is widely studied. This review also focuses on importance of protein-protein interactions of HSP90 and TRAP1 targets and association of its interacting proteins in various pathways of HCC. To further elucidate the mechanism, systems biology approaches and computational biology approach studies are well explored in the association of inhibition of herbal plant molecules with HSP90 and its mitochondrial type in HCC.

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.

Effectiveness and Safety of Radiofrequency Ablation versus Liver Resection in the Treatment of Early-stage Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

To systematically evaluate the efficacy and safety of radiofrequency ablation and liver resection in the therapeutic management of early-stage hepatocellular carcinoma. We conducted a comprehensive search of domestic and foreign databases including PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Wanfang to retrieve literature on radiofrequency ablation and liver resection for the treatment of early hepatocellular carcinoma. The retrieved literature underwent thorough screening, and relevant data were extracted. Following the evaluation of the literature's quality, Meta-analysis was performed using RevMan 5.4 software. In this study, a total of 11 documents were selected, comprising 1334 patients with hepatocellular carcinoma. Meta-analysis results indicated that there was no statistically significant difference in the 1-year overall survival rate [Relative risk (RR) = 1.01, 95% confidence intervals (CI) (0.98; 1.04)] and the 3-year overall survival rate [RR = 0.95, 95% CI (0.90; 1.01)] between the radiofrequency ablation and liver resection groups (p > 0.05). Similarly, there was no statistically significant difference in the 1-year disease-free survival rate [RR = 0.94, 95% CI (0.87; 1.01)] between the two groups. However, the 3-year disease-free survival rate [RR = 0.84, 95% CI (0.74; 0.96)] of patients in the radiofrequency ablation group was significantly lower than that in the hepatectomy group (p < 0.05). Notably, the incidence of complications [RR = 0.42, 95% CI (0.33; 0.55)] was significantly lower in the radiofrequency ablation group compared to the hepatectomy group. Conversely, the local recurrence rate [RR = 1.45, 95% CI (1.22; 1.73)] was significantly higher in the radiofrequency ablation group compared to the hepatectomy group (p < 0.05). During the treatment of hepatocellular carcinoma, hepatectomy demonstrates superior clinical efficacy compared to radiofrequency ablation, particularly in its ability to control tumor recurrence. However, radiofrequency ablation presents with fewer complications and a higher level of safety. These findings can serve as a valuable foundation for clinicians when selecting the most suitable treatment approaches for liver cancer.

Development and comprehensive validation of a predictive prognosis model for very early HCC recurrence within one year after curative resection: a multicenter cohort study

Background: The high incidence of early recurrence after liver resection for hepatocellular carcinoma (HCC) is the main obstacle in achieving good long-term survival outcomes. The aim of the present study is to develop a prognostic model in predicting the risk of very early (1-year) recurrence. Material and Methods: Consecutive patients who underwent liver resection for HCC with curative intent at multi-centers in China were enrolled in this study. The VERM-pre (the Preoperative Very Early Recurrence Model of HCC) with good performance was derived and validated by internal and external cohorts retrospectively and by another two-center cohort prospectively. Results: 7401 patients were enrolled and divided randomly into 3 cohorts. Eight variables (tumor diameter, tumor number, macrovascular invasion, satellite nodule, alpha-fetoprotein, level of HBV-DNA, γ-GT and prothrombin time) were identified as independent risk factors for recurrence-free survival on uni- and multi-variate analyses. The VERM-pre model was developed which showed a high capacity of discrimination (C-index: 0.722; AUROC at 1 year: 0.722)) and was validated comprehensively by the internal, external and prospective cohorts, retrospectively. Calibration plots showed satisfactory fitting of probability of early HCC recurrence in the cohorts. Three risk strata were derived to have significantly different recurrence free survival rates (low-risk: 80.4%-85.4%; intermediate-risk: 59.7%-64.8%; high-risk: 32.6%-42.6%). In the prospective validation cohort, the swimming plot illustrated consistent outcomes with the beginning predictive score. Conclusion: The VERM-pre model accurately predicted the 1-year recurrence rates of HCC after liver resection with curative intent. The model was retrospectively and prospectively validated and then developed as the online tool.

Extracellular Vesicles Contribute to Viral-Induced Hepatocellular Carcinoma: Understanding Their Involvement in Viral Hepatitis and Their Potential as Biomarkers for Early Hepatocellular Carcinoma Detection.

The high global prevalence of hepatitis B and hepatitis C and the poor prognosis of hepatitis B and hepatitis C-associated hepatocellular carcinoma (HCC), necessitates the early diagnosis and treatment of the disease. Recent studies show that cell-to-cell communication via extracellular vesicles (EVs) is involved in the HCC progression. The objective of the following study was to explore the role of EVs in the progression of viral-induced HCC and investigate their potential for the early diagnosis of cancer. First, the mRNA derived from EVs of HCC patients was compared to the mRNA derived from EVs from the healthy controls. Expression analysis of ANGPTL3, SH3BGRL3, and IFITM3 genes from the EVs was done. Afterward, to confirm whether hepatocytes can uptake EVs, HuH7 cells were exposed to EVs, and the expression analysis of downstream target genes (AKT, TNF-α, and MMP-9) in Huh7 cells was done. Transcriptional analysis showed that in the EVs from HCC patients, the expression levels of ANGPTL3, SH3BGRL3, and IFITM3 were significantly increased by 2.62-, 4.3-, and 9.03-folds, respectively. The downstream targets, AKT, TNF-α, and MMP-9, also showed a considerable change of 4.1-, 1.46-, and 5.05-folds, respectively, in Huh7 cells exposed to HCC EVs. In conclusion, the following study corroborates the role of EVs in HCC progression. Furthermore, the significant alteration in mRNA levels of the selected genes demonstrates their potential to be used as possible biomarkers for the early diagnosis of HCC.

Upfront multi-bipolar radiofrequency ablation for HCC in transplant-eligible cirrhotic patients with salvage transplantation in case of recurrence.

We aim to assess the long-term outcomes of percutaneous multi-bipolar radiofrequency (mbpRFA) as the first treatment for hepatocellular carcinoma (HCC) in transplant-eligible cirrhotic patients, followed by salvage transplantation for intrahepatic distant tumour recurrence or liver failure. We included transplant-eligible patients with cirrhosis and a first diagnosis of HCC within Milan criteria treated by upfront mbp RFA. Transplantability was defined by age <70 years, social support, absence of significant comorbidities, no active alcohol use and no recent extrahepatic cancer. Baseline variables were correlated with outcomes using the Kaplan-Meier and Cox models. Among 435 patients with HCC, 172 were considered as transplantable with HCCs >2 cm (53%), uninodular (87%) and AFP >100 ng/mL (13%). Median overall survival was 87 months, with 75% of patients alive at 3 years, 61% at 5 years and 43% at 10 years. Age (p = .003) and MELD>10 (p = .01) were associated with the risk of death. Recurrence occurred in 118 patients within Milan criteria in 81% of cases. Local recurrence was observed in 24.5% of cases at 10 years and distant recurrence rates were observed in 69% at 10 years. After local recurrence, 69% of patients were still alive at 10 years. At the first tumour recurrence, 75 patients (65%) were considered transplantable. Forty-one patients underwent transplantation, mainly for distant intrahepatic tumour recurrence. The overall 5-year survival post-transplantation was 72%, with a tumour recurrence of 2.4%. Upfront multi-bipolar RFA for a first diagnosis of early HCC on cirrhosis coupled with salvage liver transplantation had a favourable intention-to-treat long-term prognosis, allowing for spare grafts.

Abstract LB090: Predictive genomic biomarkers for atezolizumab plus bevacizumab combination immunotherapy response in liver cancer: Insights from the IMbrave150 trial

Abstract Introduction: Combination immunotherapy regimens, exemplified by atezolizumab plus bevacizumab or sintilimab paired with a bevacizumab biosimilar (IBI305), have become the established standard of care for individuals with inoperable hepatocellular carcinoma (HCC). Despite this advancement, the absence of clear predictive biomarkers and a comprehensive understanding of the mechanisms governing response and resistance to these combined therapies pose challenges. Our aim is to evaluate whether previously defined immune signature scores (ISS) from the TCGA pan-cancer study can identify HCC patients likely to derive enhanced benefit from the combination immunotherapy. Methods: We applied ISS predictor to gene expression data from IMbrave150 clinical trial in which HCC patients were treated with atezolizumab plus bevacizumab or sorafenib and stratify the patients into responders and non-responders (cutoff of 0.5). The significance of the stratification was assessed by multiple statistical approaches using Kaplan-Meier plots, the log-rank test, chi-square tests, and cox regression analysis. Results: In the IMBrave150 trial cohort, data on gene expression and outcomes were accessible for 247 patients who received atezolizumab plus bevacizumab, and 48 patients who received sorafenib. The high ISS demonstrated a significant association with enhanced PFS in the atezolizumab plus bevacizumab group (p=0.003), while no such association was observed in the sorafenib group (p=0.6). Similarly, in the high ISS subgroup, the combination therapy exhibited superior OS (p.0.001) and PFS (p=0.02) compared to sorafenib, but no discernible benefit was noted in the low ISS subgroup (both p&amp;gt;0.7). The OS hazard ratio for the combination versus sorafenib was 0.26 (95% CI 0.14-0.51, p&amp;lt;0.001) among high ISS patients, while it was not statistically significant in low ISS (HR 0.88, p=0.68). Interaction testing confirmed a notable interaction between ISS subtype and treatment benefit, particularly for OS (p=0.01). In the combination arm, the objective response rate was 45.6% in the high ISS group versus 22.8% in the low ISS group. Conclusions: Our study suggests that ISS may serve as a promising predictive biomarker for enhanced therapeutic outcomes in patients undergoing combination immunotherapy for HCC. The identification of such markers is crucial for refining patient stratification and personalized treatment approaches, thereby advancing the effectiveness of current standard-of-care regimens in both early and advanced stage HCC. Further validation studies are warranted to solidify the clinical utility of ISS and its integration into the decision-making process for HCC immunotherapy. Citation Format: Ju-Seog Lee, Sun Young Yim, Seung-Woo Baek, Sung Hwan Lee, BoHwa Sohn, Yun Seong Jeong, Sanghee Kang, Kena Park, Hyewon Park, Sunyoung S. Lee, Ahmed O. Kaseb, Ji Hoon Kim, In-Sun Chu. Predictive genomic biomarkers for atezolizumab plus bevacizumab combination immunotherapy response in liver cancer: Insights from the IMbrave150 trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB090.

High Ki67 Gene Expression Is Associated With Aggressive Phenotype in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) with high Ki67 protein expression, the most commonly used cell proliferation marker, is associated with an aggressive biologic phenotype; however, conventional immunostaining is hampered by variability in institutional protocol, specific antibody probe, and by assessor subjectivity. To this end, we hypothesized that Ki67 gene (MKi67) expression would identify highly proliferative HCC, and clarify its association with oncologic outcome, tumor progression, and immune cell population in the tumor microenvironment (TME). Furthermore, we sought to identify the cell-cycle gene expression profile that confers this aggressive phenotype. A total of 473 HCC patients with clinicopathological data associated with transcriptome were selected for this study: 358 patients from The Cancer Genome Atlas (TCGA) as the testing cohort, and 115 from GSE76427 as the validation cohort. Each cohort was divided into a highly proliferative group (MKi67-high) and the low MKi67 group (MKi67-low) by the median of Ki67 gene (MKi67) expression levels. MKi67-high HCC patients had worse disease-free survival (DFS), disease-specific survival (DSS), and overall survival (OS) independent of histological grade in the TCGA cohort. MKi67 expression correlated with histological grade and tumor size. MKi67 expression increased throughout the HCC carcinomatous sequence from normal liver, cirrhotic liver, early HCC, and advanced HCC. MKi67-high HCC was associated with higher intratumor heterogeneity, homologous recombination deficiency, and altered fraction as well as intratumoral infiltration of T helper type 1 (Th1) and Th2 cells, but lower interferon-gamma response and M2 macrophage infiltration. Cell proliferation-related gene sets in the Hallmark collection (E2F targets, G2M checkpoint, Myc target v1 and mitotic spindle), MTORC1 signaling, DNA repair, PI3K MTOR signaling, and unfolded protein response were all enriched in the MKi67-high HCC (false discovery rate (FDR) < 0.25). High MKi67 gene expression identified highly proliferative HCC with aggressive biology involving classical pathways in cell cycle regulation and DNA repair, as well as poor overall oncologic outcomes. This suggests potential for personalized treatment strategies, but validation and refinement of these observations require further research to elucidate the underlying mechanisms and validate therapeutic targeting of these pathways in MKi67-high HCC tumors.

Spinster Homologue 2 Expression Correlates With Improved Patient Survival in Hepatocellular Carcinoma Despite Association With Lymph-Angiogenesis.

Spinster homologue 2 (SPNS2) is a transporter of sphingosine-1-phosphate (S1P), a bioactive lipid linked to cancer progression. We studied the link between SPNS2 gene expression, tumor aggressiveness, and outcomes in patients with hepatocellular carcinoma (HCC). Gene expression in patients with HCC was analyzed from the Cancer Genome Atlas (TCGA) (n = 350) and GSE76427 (n = 115) as a validation cohort, as well as liver tissue cohort GSE6764 (n = 75). High-SPNS2 HCC was significantly associated with high level of lymph-angiogenesis-related factors. SPNS2 expression was significantly higher in normal liver and early HCC versus advanced HCC (P < 0.02). High SPNS2 levels enriched immune response-related gene sets; inflammatory, interferon (IFN)-α, IFN-γ responses, and tumor necrosis factor (TNF)-α, interleukin (IL)-6/Janus kinase/signal transducer and activator of transcription (JAK/STAT3) signaling, complement and allograft rejection, but did not significantly infiltrate specific immune cells nor cytolytic activity score. High-SPNS2 HCC enriched tumor aggravating pathway gene sets such as KRAS (Kirsten rat sarcoma virus) signaling, but inversely correlated with Nottingham histological grade, MKI67 (marker of proliferation Ki-67) expression, and cell proliferation-related gene sets. Further, high-SPNS2 HCC had significantly high infiltration of stromal cells, showing that low-SPNS2 HCC is highly proliferative. Finally, high-SPNS2 HCC was associated with better disease-free, disease-specific, and overall survival (P = 0.031, 0.046, and 0.040, respectively). Although SPNS2 expression correlated with lymph-angiogenesis and other cancer-promoting pathways, it also enriched immune response. SPNS2 levels were higher in normal liver compared to HCC, and inversely correlated with cancer cell proliferation and better survival. SPNS2 expression may be beneficial in HCC patients despite detrimental in-vitro effects.

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.

Abstract 3745: Metabolomic profiling of lipid and metabolite in cirrhosis patients with and without hepatocellular carcinoma

Abstract Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, as curative treatments are most effective at the early stages of the disease. The lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis. Established biomarkers for HCC including alpha-fetoprotein (AFP), have shown suboptimal performance in early disease stages. This study aimed to develop a combined metabolite and lipid panel to differentiate early-stage HCC from cirrhosis. Unbiased metabolomic and lipidomic analyses of serum samples were performed for 28 and 30 patients with early HCC and cirrhosis, respectively. We developed an unbiased high-resolution liquid chromatography mass spectrometry (LC-MS) based metabolic profiling platform and evaluated differences in the serum global metabolome and lipidome. This method enabled the detection of over 1200 metabolites and up to 800 lipid molecules in this select cohort. We identified 124 metabolites and 246 lipids that were upregulated and 208 metabolites and 73 lipids that were downregulated in HCC compared to cirrhosis. Using multiomic integrative analysis, we identified the overlap between differentially expressed metabolites and lipid and previously published transcriptomic signatures and illustrate that the overlapping signature associates with clinical disease progression. Lastly, we leveraged machine learning models to identify a minimal panel of lipids and metabolites that accurately distinguish between cirrhosis patients with HCC and without HCC. The best performing classifier was derived using Support Vector Machines, achieving a median AUC of 0.98 over 100 cross-validation iterations, and we showed that we need as little as 12 metabolite and lipids for effective discrimination between cirrhosis and early HCC. Citation Format: Hannah Powell, Elisa Ruiz, Sandra L. Grimm, Omar Najjar, Luis Olivares, Michael Scheurer, Hashem B. El Serag, Cristain Coarfa, Salma Kaochar. Metabolomic profiling of lipid and metabolite in cirrhosis patients with and without 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 3745.

Multiscale Structured Trimetal Oxide Heterojunctions for Urinary Metabolic Phenotype-Dependent Screening of Early and Small Hepatocellular Carcinoma.

Developing a standardized screening tool for the detection of early and small hepatocellular carcinoma (HCC) through urinary metabolic analysis poses a challenging yet intriguing research endeavor. In this study, a range of intricately interlaced 2D rough nanosheets featuring well-defined sharp edges is fabricated, with the aim of constructing diverse trimetal oxide heterojunctions exhibiting multiscale structures. By carefully engineering synergistic effects in composition and structure, including improved adsorption, diffusion, and other surface-driven processes, the optimized heterojunctions demonstrate a substantial enhancement in signal intensity compared to monometallic or bimetallic oxides, as well as fragmented trimetallic oxides. Additionally, optimal heterojunctions enable the extraction of high-quality urinary metabolic fingerprints using high-throughput mass spectrometry. Leveraging machine learning, discrimination of HCC patients from high-risk and healthy populations achieves impressive performance, with area under the curve values of 0.940 and 0.916 for receiver operating characteristic and precision-recall curves, respectively. Six crucial metabolites are identified, enabling accurate detection of early, small-tumor, alpha-fetoprotein-negative HCC (93.3%-97.3%). A comprehensive screening strategy tailored to clinical reality yields precision metrics (accuracy, precision, recall, and F1 score) exceeding 95.0%. This study advances the application of cutting-edge matrices-based metabolic phenotyping in practical clinical diagnostics.

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.

Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma

ObjectiveTo investigate the value of differential diagnosis of hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) based on CT and MR multiphase radiomics combined with different machine learning models and compare the diagnostic efficacy between different radiomics models.BackgroundPrimary liver cancer is one of the most common clinical malignancies, hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, accounting for approximately 90% of cases. A clear diagnosis of HCC is important for the individualized treatment of patients with HCC. However, more sophisticated diagnostic modalities need to be explored.MethodsThis retrospective study included 211 patients with liver lesions: 97 HCC and 124 non-hepatocellular carcinoma (non-HCC) who underwent CT and MRI. Imaging data were used to obtain imaging features of lesions and radiomics regions of interest (ROI). The extracted imaging features were combined to construct different radiomics models. The clinical data and imaging features were then combined with radiomics features to construct the combined models. Support Vector Machine (SVM), K-nearest Neighbor (KNN), RandomForest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Multilayer Perceptron (MLP) six machine learning models were used for training. Five-fold cross-validation was used to train the models, and ROC curves were used to analyze the diagnostic efficacy of each model and calculate the accuracy rate. Model training and efficacy test were performed as before.ResultsStatistical analysis showed that some clinical data (gender and concomitant cirrhosis) and imaging features (presence of envelope, marked enhancement in the arterial phase, rapid contouring in the portal phase, uniform density/signal and concomitant steatosis) were statistical differences (P < 0.001). The results of machine learning models showed that KNN had the best diagnostic efficacy. The results of the combined model showed that SVM had the best diagnostic efficacy, indicating that the combined model (accuracy 0.824) had better diagnostic efficacy than the radiomics-only model.ConclusionsOur results demonstrate that the radiomic features of CT and MRI combined with machine learning models enable differential diagnosis of HCC and non-HCC (malignant, benign). The diagnostic model with dual radiomic had better diagnostic efficacy. The combined model was superior to the radiomic model alone.

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration

BackgroundThe morphological attributes could serve as pivotal indicators precipitating early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and quantifying morphological features may better stratify the prognosis of HCC. ObjectiveTo develop a radiomics approach based on 3D tumor morphology features for predicting the prognosis of HCC and identifying differentially expressed genes related to morphology to guide HCC treatment. Materials and methodsRetrospective study of 357 HCC patients. Radiomic features were extracted from MRI tumor regions; 14 morphology-related features predicted early HCC recurrence and patient stratification via LASSO-Cox modeling. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. RNA sequencing from the Cancer Imaging Archive (TCIA) examined drug sensitivity and stratified HCC using morphological immunity genes, validating recurrence and prognosis. ResultsPatients were split into training (n = 225), test (n = 132), and 50 TCIA dataset cohorts. Two features (Maximum2DdiameterColumn, Sphericity) in Cox regression stratified patients into high/low-risk Morphological Radiological Score (Morph-RS) groups. Significant OS and RFS were seen across all sets. Differentially expressed genes focused on T cell receptor signaling; low-risk group had higher T cells (P = 0.039), B cells (P = 0.041), NK cells (P = 0.018). SN-38, GSK2126458 might treat high-risk morphology. Morphology-immune genes stratified HCC, showing significant RFS/OS differences. ConclusionTumor Morph-RS effectively stratifies HCC patients' recurrence and prognosis. Limited immune infiltration seen in Morph-RS high-risk groups signifies the potential of employing tumor morphology as a potent visual biomarker for diagnosing and managing HCC.

Optimal treatment strategy and prognostic analysis of salvage liver transplantation for patients with earlyhepatocellular carcinoma recurrence after hepatectomy.

We aimed to investigate the prognostic factors for salvage liver transplant in patients with early hepatocellular carcinoma recurrence after hepatectomy. This retrospective analysis included 53 patients who underwent salvage living-donor liver transplantation between January 2007 and January 2018. There were 24 and 29 patients in the early (recurrence ≤24months after primary liver resection) and the late recurrence groups, respectively. In the multivariate Cox regression model, pre-liver transplant downstaging therapy, early recurrence (ER) after primary liver resection , and recurrence-to-liver-transplant ≥12months were independent risks to predict recurrent hepatocellular carcinoma recurrence after salvage living-donor liver transplantation. Compared with the late recurrence group, the ER group showed lower disease-free survival rates (p<0.001); however, the overall survival rates did not differ between the two groups (p=0.355). The 1-, 3-, and 5-year disease-free survival rates were 83.3%, 70.6%, and 66.2%, and 96.0%, 91.6%, and 91.6% in the early and late recurrence groups, respectively. When stratified by recurrence-to-liver transplant time and pre-liver transplant downstaging therapy in the ER group, disease-free survival and overall survival rates were significantly different. ER after primary liver resection with advanced tumor status and a longer period of recurrence-to-liver-transplant (≥12months) have a negative impact on salvage liver transplant. Our findings provide novel recommendations for treatment strategies and eligibility for salvage liver transplant candidates.

Development of machine learning-based predictors for early diagnosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains a formidable malignancy that significantly impacts human health, and the early diagnosis of HCC holds paramount importance. Therefore, it is imperative to develop an efficacious signature for the early diagnosis of HCC. In this study, we aimed to develop early HCC predictors (eHCC-pred) using machine learning-based methods and compare their performance with existing methods. The enhancements and advancements of eHCC-pred encompassed the following: (i) utilization of a substantial number of samples, including an increased representation of cirrhosis tissues without HCC (CwoHCC) samples for model training and augmented numbers of HCC and CwoHCC samples for model validation; (ii) incorporation of two feature selection methods, namely minimum redundancy maximum relevance and maximum relevance maximum distance, along with the inclusion of eight machine learning-based methods; (iii) improvement in the accuracy of early HCC identification, elevating it from 78.15 to 97% using identical independent datasets; and (iv) establishment of a user-friendly web server. The eHCC-pred is freely accessible at http://www.dulab.com.cn/eHCC-pred/. Our approach, eHCC-pred, is anticipated to be robustly employed at the individual level for facilitating early HCC diagnosis in clinical practice, surpassing currently available state-of-the-art techniques.