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Background and aimsSecond-generation direct-acting antivirals (2G DAA) to cure HCV have led to dramatic clinical improvements. HCV-associated hepatocellular carcinoma (HCC), however, remains common. Impaired immune tumor surveillance may play a role in HCC development. Our cohort evaluated the effects of innate immune types and clinical variables on outcomes including HCC.MethodsParticipants underwent full HLA class I/KIR typing and long-term HCV follow-up.ResultsA total of 353 HCV+ participants were followed for a mean of 7 years. Cirrhosis: 25% at baseline, developed in 12% during follow-up. 158 participants received 2G DAA therapy. HCC developed without HCV therapy in 20 subjects, 24 HCC after HCV therapy, and 10 of these after 2G DAA. Two predictors of HCC among 2G DAA-treated patients: cirrhosis (OR, 10.0, p = 0.002) and HLA/KIR profiles predicting weak natural killer (NK) cell-mediated immunity (NK cell complementation groups 6, 9, 11, 12, OR of 5.1, p = 0.02). Without 2G DAA therapy: cirrhosis was the main clinical predictor of HCC (OR, 30.8, p < 0.0001), and weak NK-cell-mediated immunity did not predict HCC.ConclusionCirrhosis is the main risk state predisposing to HCC, but weak NK-cell-mediated immunity may predispose to post-2G DAA HCC more than intermediate or strong NK-cell-mediated immunity.

BackgroundOne challenge for primary care providers caring for patients with nonalcoholic fatty liver disease is to identify those at the highest risk for clinically significant liver disease.AimTo derive a risk stratification tool using variables from structured electronic health record (EHR) data for use in populations which are disproportionately affected with obesity and diabetes.MethodsWe used data from 344 participants who underwent Fibroscan examination to measure liver fat and liver stiffness measurement [LSM]. Using two approaches, multivariable logistic regression and random forest classification, we assessed risk factors for any hepatic fibrosis (LSM > 7 kPa) and significant hepatic fibrosis (> 8 kPa). Possible predictors included data from the EHR for age, gender, diabetes, hypertension, FIB-4, body mass index (BMI), LDL, HDL, and triglycerides.ResultsOf 344 patients (56.4% women), 34 had any hepatic fibrosis, and 15 significant hepatic fibrosis. Three variables (BMI, FIB-4, diabetes) were identified from both approaches. When we used variable cut-offs defined by Youden's index, the final model predicting any hepatic fibrosis had an AUC of 0.75 (95% CI 0.67-0.84), NPV of 91.5% and PPV of 40.0%. The final model with variable categories based on standard clinical thresholds (i.e., BMI ≥ 30 kg/m2; FIB-4 ≥ 1.45) had lower discriminatory ability (AUC 0.65), but higher PPV (50.0%) and similar NPV (91.3%). We observed similar findings for predicting significant hepatic fibrosis.ConclusionsOur results demonstrate that standard thresholds for clinical risk factors/biomarkers may need to be modified for greater discriminatory ability among populations with high prevalence of obesity and diabetes.

4D MRI with high spatiotemporal resolution is desired for image-guided liver radiotherapy. Acquiring densely sampled k-space data is time-consuming. Accelerated acquisition with sparse sampling is desirable but often causes degraded image quality or long reconstruction time. We propose the Reconstruct Paired Conditional Generative Adversarial Network (Re-Con-GAN) for shortening the 4D MRI reconstruction time while maintaining the reconstruction quality. Methods: Patients underwent free-breathing liver 4D MRI were included in the study. Fully- and retrospectively under-sampled data at 3, 6 and 10 times (3x, 6x and 10x) were first reconstructed using the nuFFT algorithm. Re-Con-GAN then trained input and output in pairs. Three types of networks, ResNet9, UNet and reconstruction swin transformer, were explored as generators. PatchGAN was selected as the discriminator. Re-Con-GAN processed the data (3D+t) as temporal slices (2D+t). A total of 48 patients with 12332 temporal slices were split into training (37 patients with 10721 slices) and test (11 patients with 1611 slices). Compressed sensing (CS) reconstruction with spatiotemporal sparsity constraint was used as a benchmark. Reconstructed image quality was further evaluated with a liver gross tumor volume (GTV) localization task using Mask-RCNN trained from a separate 3D static liver MRI dataset (70 patients; 103 GTV contours).Results: Re-Con-GAN consistently achieved comparable/better PSNR, SSIM, and RMSE scores compared to CS/UNet models. The inference time of Re-Con-GAN, UNet and CS are 0.15s, 0.16s, and 120s. The GTV detection task showed that Re-Con-GAN and CS, compared to UNet, better improved the dice score (3x Re-Con-GAN 80.98%; 3x CS 80.74%; 3x UNet 79.88%) of unprocessed under-sampled images (3x 69.61%). Conclusion: A generative network with adversarial training is proposed with promising and efficient reconstruction results demonstrated on an in-house dataset. The rapid and qualitative reconstruction of 4D liver MR has the potential to facilitate online adaptive MR-guided radiotherapy for liver cancer.

The aim of the present study is to provide a rational background for silencing the V-set and transmembrane domain containing 2 like (VSTM2L) in consort with recognising soluble VSTM2L against cholangiocarcinoma. A therapeutic target against cholangiocarcinoma was selected using iterative patient partitioning (IPP) calculation, and it was verified by in vitro and in silico analyses. VSTM2L was selected as a potential therapeutic target against cholangiocarcinoma. Silencing the VSTM2L expression significantly attenuated the viability and survival of cholangiocarcinoma cells through blockade of the intracellular signalling pathway. In silico analysis showed that VSTM2L affected the positive regulation of cell growth in cholangiocarcinoma. Liptak's z value revealed that the expression of VSTM2L worsened the prognosis of cholangiocarcinoma patients. In addition, soluble VSTM2L was significantly detected in the whole blood of cholangiocarcinoma patients compared with that of healthy donors. Our report reveals that VSTM2L might be the potential therapeutic target and a soluble prognostic biomarker against cholangiocarcinoma.

Transcriptomic contributions to the anatomical, functional, and network layout of the human cerebral cortex (HCC) have become a major interest in cognitive and systems neuroscience. Here, we tested if transcriptomic differences support a modern, algorithmic cytoarchitectonic parcellation of HCC. Using a data-driven approach, we identified a sparse subset of genes that differentially contributed to the cytoarchitectonic parcellation of HCC. A combined metric of cortical thickness and myelination (CT/M ratio), as well as cell density, correlated with gene expression. Enrichment analyses showed that genes specific to the cytoarchitectonic parcellation of the HCC were related to molecular functions such as transmembrane transport and ion channel activity. Together, the relationship between transcriptomics and cytoarchitecture bridges the gap among (i) gradients at the macro-scale (including thickness and myelination), (ii) areas at the meso-scale, and (iii) cell density at the microscale, as well as supports the recently proposed cortical spectrum theory and structural model.

In pre-disposed individuals, a reprogramming of the hepatic lipid metabolism may support liver cancer initiation. We conducted a high-resolution mass spectrometry based untargeted lipidomics analysis of pre-diagnostic serum samples from a nested case-control study (219 liver cancer cases and 219 controls) within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. Out of 462 annotated lipids, 158 (34.2%) were associated with liver cancer risk in a conditional logistic regression analysis at a false discovery rate (FDR)

Sorafenib, FDA-approved therapy for patients with advanced hepatocellular carcinoma (HCC), leads to limited improvement in overall survival. However, it may indirectly impact the expansion and activity of natural killer (NK) cells. While NK cell-based immunotherapies generally exhibit favorable safety profiles, their effectiveness in controlling solid tumor growth is constrained, primarily due to the absence of antigen specificity and suboptimal expansion and persistence within the tumor microenvironment. In this study, we postulated that enhancing NK cell functionality via cytokine activation could bolster their viability and cytotoxic capabilities, leading to an improved therapeutic response when combined with sorafenib. Memory-like (ML)-NK cells were generated through the supplementation of optimal concentrations of interleukin (IL)-12 and IL-18 cytokines. Following a single day of treatment, cytotoxicity against rat and human HCC cells was evaluated via flow cytometry analysis. A rat HCC model was developed in 30 animals via subcapsular implantation and assigned to control, NK, sorafenib, ML-NK, and combination groups. Sorafenib was administered orally, and NK cells were delivered via the intrahepatic artery. Tumor growth was measured one week after treatment evaluation. Therapeutic efficacy during in-vitro and in-vivo analysis was investigated through a one-way ANOVA test, followed by pairwise two-tailed Student t-tests, considering P < 0.05 statistically significant. The in-vitro experiment results demonstrated that sorafenib and conventional NK cell therapies induced more substantial cell death than the control group (P < 0.01). ML NK cells significantly improved cell death compared to conventional NK cell immunotherapy. Furthermore, sorafenib in combination with ML-NK cells significantly decreased the viability of HCC cells (P < 0.05) compared to sorafenib plus conventional NK cell combination therapy. In vivo experiments have shown that sorafenib and ML-NK cell immunotherapy reduced the growth rate of HCC tumors compared to conventional NK immunotherapy and control groups. Notably, a combination of sorafenib and ML-NK cell immunochemotherapy resulted in the most significant suppression of tumor growth when compared to other therapies. In conclusion, our experimental findings demonstrate that the concurrent administration of sorafenib and ML-NK immunotherapy enhances cytotoxicity against HCC by optimizing the therapeutic response through cytokine activation, resulting in a significant decrease in tumor growth.

BACKGROUND AND AIMS: The change in hepatocellular carcinoma (HCC) care continuum during the coronavirus disease 2019 (COVID-19) pandemic remains unknown at a national level in the United States. We sought to determine the impact of the pandemic on incident HCC cases, clinical characteristics, and treatment in the United States. METHODS: Using the National Cancer Database, we analyzed incident HCC cases from 2010 to 2020. The incidence rate was calculated using the population data for each year from the census bureau. Joinpoint regression analysis was applied for trend analysis, and a polynomial regression model estimated the number of projected HCC cases in 2020 according to the trend of rates from 2010 to 2019. The distribution of cancer stage and treatment modality were assessed. RESULTS: The pandemic led to a significant reduction in reported HCC cases, from 19,597 in 2019 to 16,188 in 2020. The projected number of HCC for 2020 was 19,011, corresponding to a 14.8% reduction in 2020. Extent of reduction in the number of incident HCC cases relative to estimated cases remains consistent in racial and ethnic subgroups. Despite underdiagnosis of HCC in 2020, proportion of patients with early tumor stage (30.5% for Tumour, Node, Metastasis stage 1) and curative treatment receipt (9.1% for surgical resection, 13% for ablation, 4.2% for liver transplant) for HCC remained stable in the first year of the COVID-19 pandemic. CONCLUSION: There was a significant reduction in HCC cases in 2020 compared to pre-COVID years. While tumor stage and proportion of patients receiving curative treatment remained stable, continued follow-up is needed to assess potential changes during subsequent years.

BackgroundThe cause of liver disease is changing, but its impact on liver transplantation (LT) for hepatocellular carcinoma (HCC) in women and men is unclear. We performed a nationwide study to assess the prevalence and posttransplant survival outcomes of the various causes of liver disease in women and men with HCC.MethodsData were obtained from the United Network for Organ Sharing database from 2000 to 2022. Data related to the listing, transplant, waitlist mortality, and posttransplant mortality for HCC were extracted. The proportion of HCC related to the various causes of liver disease among LT candidates and recipients and posttransplant survival were compared between women and men.ResultsA total of 51 721 individuals (39 465 men, 12 256 women) with HCC were included. From 2000 to 2022, nonalcoholic steatohepatitis (NASH) was the fastest-growing cause of liver disease among female LT candidates with HCC (P

TBX3 behaves as a tumor suppressor or oncoprotein across cancer. However, TBX3 function remains undetermined in intrahepatic cholangiocarcinoma (iCCA), a deadly primary liver malignancy with few systemic treatment options. This study sought to investigate the impact of TBX3 on iCCA. We found that overexpression of TBX3 strongly inhibited human iCCA cell growth. In the Akt/FBXW7ΔF mouse iCCA model, overexpression of Tbx3 reduced cholangiocarcinogenesis in vivo, while inducible genetic knockout of Tbx3 accelerated iCCA growth. RNA-seq identified MAD2L1 as a downregulated gene in TBX3-overexpressing cells, and ChIP confirmed that TBX3 binds to the MAD2L1 promoter. CRISPR-mediated knockdown of Mad2l1 significantly reduced the growth of two iCCA models in vivo. Finally, we found that TBX3 expression is upregulated in ~20% of human iCCA samples, and its high expression is associated with less proliferation and better survival. MAD2L1 expression is upregulated in most human iCCA samples and negatively correlated with TBX3 expression. Altogether, our findings suggest that overexpression of TBX3 suppresses CCA progression via repressing MAD2L1 expression.

The aim of the present study is to provide a methodical platform for the development of lead compounds against cholangiocarcinoma. Coptisine was selected as a potential anti-cancer nominee from a pool of phytochemicals using an in silico 3-D docking screening technique and validated the anti-cancer effects against cholangiocarcinoma through the blockade of EGFR signaling depending on the cellular degradation. We also verified that coptisine had no cytotoxicity in different human normal cells when compared with the clinically approved anti-cancer drug, erlotinib. In vitro and in silico analyses revealed that coptisine can suppress the expression of various oncogenic molecules and administrating coptisine showed an anti-cholangiocarcinoma tumor growth or recurrence using in vivo models. Collectively, we propose that a well-organized methodical 3-D docking screening platform is an innovative technique for the discovery of anti-cancer drugs against malignant tumors, and coptisine might be a safe and effective anti-cancer reagent against cholangiocarcinoma.