HCC advances in diagnosis and prognosis: Digital and Imaging

Synthesis and biological evaluation of 68Ga-DOTA-AngII as a radiotracer for PET/MR imaging of hepatocellular carcinoma

The precise diagnosis of HCC is confronted with severe challenges due to the tumor heterogeneity and insidious symptoms of hepatocellular carcinoma (HCC), and meanwhile the limitations of positron emission tomography (PET) with traditional 2-deoxy-2-[fluorine-18] fluoro-d-glucose (18F-FDG) tracer. Given that angiotensin II type 1 receptor (AT1R) is significantly upregulated in HCC and closely related to its progression, we have developed a novel 68Ga-radiolabeled compound, 68Ga-DOTA-AngII (68Ga-DOTA-GGDRVYIHPF), and evaluated its HCC detection capability. 68Ga-DOTA-AngII demonstrated acceptable stability in both human plasma and phosphate buffered saline. In vivo imaging and in vitro biodistribution analysis in tumor-bearing mice showed that 68Ga-DOTA-AngII demonstrate a high tumor uptake, and the tumor tissue exhibited rapid uptake. In brief, this radiotracer possesses a promising potency for imaging the expression of AT1R for further clinical application.

Integrated spatial and single cell transcriptomics identifies PRKDC as a dual prognostic biomarker and therapeutic target in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with a pressing need for effective biomarkers and therapeutic targets. Despite the clinical use of alpha-fetoprotein (AFP) as a diagnostic biomarker, its limitations in sensitivity and specificity necessitate the identification of novel markers. In this study, we investigated the role of Protein Kinase, DNA-Activated, Catalytic Subunit (PRKDC) in HCC prognosis and its potential as a therapeutic target. Utilizing spatial transcriptomics and single-cell RNA sequencing (scRNA-seq), we dissected the cellular composition of PRKDC in HCC tissue samples, revealing its high expression in malignant cell subpopulations and its association with the tumor immune microenvironment. Through clinical signature analysis, we observed widespread PRKDC expression in HCC tissues, particularly in immune cells, highlighting its link to immune cell infiltration. Further analyses confirmed high PRKDC expression in malignant cells and its inhibitory effect on immune cell infiltration. Copy number variation (CNV) analysis revealed significant genomic instability, with PRKDC exhibiting both amplifications and deletions across chromosomal regions, underscoring its role in tumorigenesis. Functional overexpression of PRKDC in HCC cell lines enhanced cell proliferation, migration, and altered cell cycle dynamics, with a notable increase in the G2/S phase. Taken together, we first to integrate spatial transcriptomics and single-cell transcriptomics and bulk RNA-seq to reveal that PRKDC is a reliable prognostic biomarker and a potential therapeutic target. High PRKDC expression is associated with shorter survival times and an abnormal tumor microenvironment, highlighting its impact on immune cell infiltration and HCC prognosis. Targeting PRKDC could selectively inhibit its expression in tumor cells, providing new strategies for HCC treatment.

Unveiling expression patterns, mechanisms, and therapeutic opportunities of transmembrane protein 106C: From pan-cancers to hepatocellular carcinoma

BACKGROUND

Although transmembrane protein 106C (TMEM106C) has been elucidated to be overexpressed in cancers, its underlying mechanisms have not yet been fully understood.

AIM

To investigate the expression levels and molecular mechanisms of TMEM106C across 34 different cancer types, including liver hepatocellular carcinoma (LIHC).

METHODS

We analyzed TMEM106C expression patterns in pan-cancers using microenvironment cell populations counter to evaluate its association with the tumor microenvironment. Gene set enrichment analysis was conducted to identify molecular pathways related to TMEM106C. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) analysis was conducted to identify upstream transcriptional regulators of TMEM106C. In LIHC, we examined mRNA profiles, performed in-house quantitative polymerase chain reaction, immunohistochemistry, and constructed a co-expression gene network. Functional assays, including cell counting kit-8, cell cycle, apoptosis, migration, and invasion, were conducted. The effect of nitidine chloride (NC) on LIHC xenograft was evaluated through RNA sequencing and molecular docking. Finally, potential therapeutic agents targeting TMEM106C were predicted.

RESULTS

TMEM106C was significantly overexpressed in 27 different cancer types and presaged poor prognosis in four of these types, including LIHC. Across pan-cancers, TMEM106C was inversely correlated to the abundances of immune and stromal cells. Furthermore, TMEM106C was significantly linked to cell cycle and DNA replication pathways in pan-cancers. ChIP-seq analysis predicted CCCTC-binding factor as a pivotal transcriptional factor targeting the TMEM106C gene in pan-cancers. Integrated analysis showed that TMEM106C was upregulated in 4657 LIHC compared with 3652 normal liver tissue [combined standardized mean difference = 1.31 (1.09, 1.52)]. In-house LIHC samples verified the expression status of TMEM106C. Higher TMEM106C expression signified worse survival conditions in LIHC patients treated with sorafenib, a tyrosine kinase inhibitor (TKI). Co-expressed analysis revealed that TMEM106C were significantly enriched in the cell cycle pathway. Knockout experiments demonstrated that TMEM106C plays a crucial role in LIHC cell proliferation, migration, and invasion, with cell cycle arrest occurring at the DNA synthesis phase, and increased apoptosis. Notably, TMEM106C upregulation was attenuated by NC treatment. Finally, TMEM106C expression levels were significantly correlated with the drug sensitivity of anti-hepatocellular carcinoma agents, including JNJ-42756493, a TKI agent.

CONCLUSION

Overexpressed TMEM106C was predicted as an oncogene in pan-cancers, which may serve as a promising therapeutic target for various cancers, including LIHC. Targeting TMEM106C could potentially offer a novel direction in overcoming TKI resistance specifically in LIHC. Future research directions include in-depth experimental validation and exploration of TMEM106C's role in other cancer types.

Unlocking the potential of Traditional Chinese Medicine (TCM): Shipi Xiaoji formula (SPXJF) as a novel ferroptosis inducer in hepatocellular carcinoma

ETHNOPHARMACOLOGICAL RELEVANCE

Hepatocellular Carcinoma (HCC) is a major health concern with limited treatment options. Traditional Chinese Medicine (TCM) offers potential therapeutic approaches for HCC, and SPXJF, a TCM formula, has shown promise in clinical observations for prolonging the survival of liver cancer patients.

AIM OF THE STUDY

To investigate the anti-tumor effects of SPXJF on HCC cells and explore its potential mechanism, focusing on ferroptosis induction.

MATERIALS AND METHODS

LC/Q-TOF-MS was used for compound identification. Cell viability assays, EdU proliferation assay, colony formation assay, wound healing assay, Transwell assay, and Western-blotting were conducted to evaluate the effects of SPXJF on HCC cell proliferation, migration, and invasion. Bioinformatics analysis and RT-PCR were employed to identify potential ferroptosis-related genes and validate the results. Ferroptosis induction was investigated using ferroptosis inhibitors, ROS and lipid peroxidation detection, and TEM. In vivo experiments using a subcutaneous xenograft tumor model confirmed the anti-tumor effects of SPXJF and its ability to induce ferroptosis in HCC.

RESULTS

SPXJF effectively inhibited the proliferation, migration, and invasion of HCC cells in vitro. The mechanism of action was found to be related to the induction of ferroptosis, as evidenced by increased intracellular Fe2+ and ROS levels, decreased GSH levels, altered mitochondrial morphology, and upregulation of ferroptosis-inducing proteins ACSL4 and LPCAT3, along with downregulation of ferroptosis-inhibiting proteins xCT and GPX4. Bioinformatics analysis and RT-PCR further identified GSTZ1, CDC25A, AURKA, NOX4, and CAPG as potential ferroptosis-related genes regulated by SPXJF. In vivo experiments confirmed the anti-tumor effects of SPXJF and its ability to induce ferroptosis in HCC.

CONCLUSIONS

SPXJF exerts anti-tumor effects on HCC cells by inducing ferroptosis, and its mechanism of action involves the regulation of ferroptosis-related genes and proteins. This study provides a theoretical basis for the clinical treatment of HCC and the development of new anti-cancer drugs, offering a valuable contribution to the field of ethnopharmacology.

Qualitative and quantitative differentiation efficiency of dual-tracer PET/CT with 18F-fluorodeoxyglucose and 11C-acetate for primary hepatocellular carcinoma: a systematic review and meta-analysis

PURPOSE

Primary hepatocellular carcinoma (HCC) represents a substantial global health challenge. Early diagnosis of HCC is crucial for improved patient outcomes. The aim of this study was to assess qualitative and quantitative diagnostic performance of PET/CT using 11C-acetate and [18F]-fluorodeoxyglucose (FDG) in detection of primary HCC and to determine if 11C-acetate added to [18F]-FDG alleviates the low sensitivity rate mentioned in guidelines.

METHODS

Protocol was pre-registered at https://osf.io/2vcb9 . We searched PubMed, Web of Science, Embase, and the Cochrane Library for included studies. Quality Assessment of Diagnostic Accuracy Studies 2 was used to assess the risk of bias. Possible sources of statistical heterogeneity were explored. Additionally, mentioned three PET/CT tests were evaluated for their diagnostic performance in differentiating HCC from its differential diagnoses. Grades of Recommendation, Assessment, Development, and Evaluation was used to assess quality of generated evidence.

RESULTS

Twenty-four studies were analyzed. Qualitative dual-tracer PET/CT demonstrated 92.0% per-lesion sensitivity, and a significantly higher direct sensitivity difference of 30% to conventional CT, 44.7% to [18F]-FDG, and 12.0% to 11C-acetate. Regarding differentiation rate, [18F]-FDG was superior to 11C-acetate in poorly differentiated lesions while 11C-acetate was superior in well-differentiated lesions. Regarding size, dual tracer combination solved the high missing rate of HCC lesions in 1-2 cm and 2-5 cm groups but could not help in size < 1 cm.

CONCLUSION

Dual-tracer PET/CT utilizing 11C-acetate and [18F]-FDG represents a sensitive method for detecting primary HCC. By concurrently quantifying or qualifying the uptake of 11C-acetate and [18F]-FDG, this multimodal approach enables precise localization of intrahepatic lesions.

A Comprehensive Model Outperformed the Single Radiomics Model in Noninvasively Predicting the HER2 Status in Patients with Breast Cancer

RATIONALE AND OBJECTIVES

This study aimed to develop predictive models based on conventional magnetic resonance imaging (cMRI) and radiomics features for predicting human epidermal growth factor receptor 2 (HER2) status of breast cancer (BC) and compare their performance.

MATERIALS AND METHODS

A total of 287 patients with invasive BC in our hospital were retrospectively analyzed. All patients underwent preoperative breast MRI consisting of fat-suppressed T2-weighted imaging, axial dynamic contrast-enhanced MRI, and diffusion-weighted imaging sequences. From these sequences, radiomics features were derived. Three distinct models were established utilizing cMRI features, radiomics features, and a comprehensive model that amalgamated both. The predictive capabilities of these models were assessed using the receiver operating characteristic curve analysis. The comparative performance was then determined through the DeLong test and net reclassification improvement (NRI).

RESULTS

In a randomized split, the 287 patients with BC were allotted to either training (234; 46 HER2-zero, 107 HER2-low, 81 HER2-positive) or test (53; 8 HER2-zero, 27 HER2-low, 18 HER2-positive) at an 8:2 ratio. The mean area under the curve (AUCs) for cMRI, radiomics, and comprehensive models predicting HER2 status were 0.705, 0.819, and 0.859 in training set and 0.639, 0.797, and 0.842 in test set, respectively. DeLong's test indicated that the combined model's AUC surpassed the radiomics model significantly (p < 0.05). NRI analysis verified superiority of the combined model over the radiomics for BC HER2 prediction (NRI 25.0) in the test set.

CONCLUSION

The comprehensive model based on the combination of cMRI and radiomics features outperformed the single radiomics model in noninvasively predicting the three-tiered HER2 status in patients with BC.

Alterations of Krüppel-like Factor Signaling and Potential Targeted Therapy for Hepatocellular Carcinoma

Krüppel-like factors (KLFs, total 18 members) from the zinc finger protein (ZFP) super-family have a wide range of biological functions in hepatocellular carcinoma (HCC). This paper reviews the recent some progresses of aberrant KLFs with their potential values for diagnosis, prognosis, and targeted therapy in HCC. The recent advances of oncogenic KLFs in the diagnosis, prognosis, and targeted therapy of HCC were reviewed based on the related literature on PUBMED and clinical investigation. Based on the recent literature, KLFs, according to biological functions in HCC, are divided into 4 subgroups: promoting (KLF5, 7, 8, 13), inhibiting (KLF3, 4, 9~12, 14, 17), dual (KLF2, 6), and unknown functions (KLF1, 15, 16, or 18 ?). HCC-related KLFs regulate downstream gene transcription during hepatocyte malignant transformation, participating in cell proliferation, apoptosis, invasion, and metastasis. Some KLFs have diagnostic or prognostic value, and other KLFs with inhibiting promoting function or over-expressing inhibiting roles might be molecular targets for HCC therapy. These data have suggested that Abnormal expressions of KLFs were associated with HCC progression. Among them, some KLFs have revealed the clinical values of diagnosis or prognosis, and other KLFs with the biological functions of promotion or inhibition might be as effectively molecular targets for HCC therapy.

Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms

Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in the progression and prognosis of HCC. We applied the machine learning algorithm-CIBERSORT, to quantify cellular compositions within the HCC TME, focusing on M2 macrophages. Gene expression profiles were analysed to identify key molecules, with ATP6V1E1 as a primary focus. We employed Gene Set Enrichment Analysis (GSEA) and Kaplan-Meier survival analysis to investigate the molecular pathways and prognostic significance of ATP6V1E1. A prognostic model was developed using multivariate Cox regression analysis based on ATP6V1E1-related molecules, and functional impacts were assessed through cell proliferation assays. M2 macrophages were the dominant cell type in the HCC TME, significantly correlating with adverse survival outcomes. ATP6V1E1 was robustly associated with advanced disease stages and poor prognostic features such as vascular invasion and elevated alpha-fetoprotein levels. GSEA linked high ATP6V1E1 expression to critical oncogenic pathways, including immunosuppression and angiogenesis, and reduced activity in metabolic processes like bile acid and fatty acid metabolism. The prognostic model stratified HCC patients into distinct risk categories, showing high predictive accuracy (1-year AUC = 0.775, 3-year AUC = 0.709 and 5-year AUC = 0.791). In vitro assays demonstrated that ATP6V1E1 knockdown markedly inhibited the proliferation of HCC cells. The study underscores the significance of M2 macrophages and ATP6V1E1 in HCC, highlighting their potential as therapeutic and prognostic targets.

Early warning of hepatocellular carcinoma in cirrhotic patients by three-phase CT-based deep learning radiomics model: a retrospective, multicentre, cohort study

BACKGROUND

The diagnosis of hepatocellular carcinoma (HCC) often experiences latency, ultimately leading to unfavorable patient outcomes due to delayed therapeutic interventions. Our study is designed to develop and validate a model that employs triple-phase computerized tomography (CT)-based deep learning radiomics and clinical variables for early warning of HCC in patients with cirrhosis.

METHODS

We studied 1858 patients with cirrhosis primarily from the PreCar cohort (NCT03588442) between June 2018 and January 2020 at 11 centres, and collected triple-phase CT images and laboratory results 3-12 months prior to HCC diagnosis or non-HCC final follow-up. Using radiomics and deep learning techniques, early warning model was developed in the discovery cohort (n = 924), and then validated in an internal validation cohort (n = 231), and an external validation cohort from 10 external centres (n = 703).

FINDINGS

We developed a hybrid model, named ALARM model, which integrates deep learning radiomics with clinical variables, enabling early warning of the majority of HCC cases. The ALARM model effectively predicted short-term HCC development in cirrhotic patients with area under the curve (AUC) of 0.929 (95% confidence interval 0.918-0.941) in the discovery cohort, 0.902 (0.818-0.987) in the internal validation cohort, and 0.918 (0.898-0.961) in the external validation cohort. By applying optimal thresholds of 0.21 and 0.65, the high-risk (n = 221, 11.9%) and medium-risk (n = 433, 23.3%) groups, which covered 94.4% (84/89) of the patients who developed HCC, had significantly higher rates of HCC occurrence compared to the low-risk group (n = 1204, 64.8%) (24.3% vs 6.4% vs 0.42%, P < 0.001). Furthermore, ALARM also demonstrated consistent performance in subgroup analysis.

INTERPRETATION

The novel ALARM model, based on deep learning radiomics with clinical variables, provides reliable estimates of short-term HCC development for cirrhotic patients, and may have the potential to improve the precision in clinical decision-making and early initiation of HCC treatments.

FUNDING

This work was supported by National Key Research and Development Program of China (2022YFC2303600, 2022YFC2304800), and the National Natural Science Foundation of China (82170610), Guangdong Basic and Applied Basic Research Foundation (2023A1515011211).

The liquid-liquid phase separation signature predicts the prognosis and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common and fatal malignancy characterized by poor patient prognosis and treatment outcome. The process of liquid-liquid phase separation in tumour cells alters the dysfunction of biomolecular condensation in tumour cells, which affects tumour progression and treatment. We downloaded the data of HCC samples from TCGA database and GEO database, and used a machine learning method to build a new liquid-liquid phase separation index (LLPSI) by liquid-liquid phase separation related genes. The LLPSI-related column line Figure was constructed to provide a quantitative tool for clinical practice. HCC patients were divided into high and low LLPSI groups based on LLPSI, and clinical features, tumour immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analysed. LLPSI, which consists of five liquid-liquid phase separation-associated genes (MAPT, WDR62, PLK1, CDCA8 and TOP2A), is a reliable predictor of survival in patients with HCC and has been validated in multiple external datasets. We found that the high LLPSI group showed higher levels of immune cell infiltration and better response to immunotherapy compared to the low LLPSI group, and LLPSI can also be used for prognostic prediction in various cancers other than HCC. In vitro experiments verified that knockdown of MAPT could inhibit the proliferation and migration of HCC. The LLPSI identified in this study can accurately assess the prognosis of patients with HCC and identify patient populations that will benefit from immunotherapy, providing valuable insights into the clinical management of HCC.

Comprehensively analysis of IL33 in hepatocellular carcinoma prognosis, immune microenvironment and biological role

IL33 plays an important role in cancer. However, the role of liver cancer remains unclear. Open-accessed data was obtained from the Cancer Genome Atlas, Xena, and TISCH databases. Different algorithms and R packages are used to perform various analyses. Here, in our comprehensive study on IL33 in HCC, we observed its differential expression across cancers, implicating its role in cancer development. The single-cell analysis highlighted its primary expression in endothelial cells, unveiling correlations within the HCC microenvironment. Also, the expression level of IL33 was correlated with patients survival, emphasizing its potential prognostic value. Biological enrichment analyses revealed associations with stem cell division, angiogenesis, and inflammatory response. IL33's impact on the immune microenvironment showcased correlations with diverse immune cells. Genomic features and drug sensitivity analyses provided insights into IL33's broader implications. In a pan-cancer context, IL33 emerged as a potential tumour-inhibitor, influencing immune-related molecules. This study significantly advances our understanding of IL33 in cancer biology. IL33 exhibited differential expression across cancers, particularly in endothelial cells within the HCC microenvironment. IL33 is correlated with the survival of HCC patients, indicating potential prognostic value and highlighting its broader implications in cancer biology.

Evaluating the diagnostic accuracy of heat shock proteins and their combination with Alpha-Fetoprotein in the detection of hepatocellular carcinoma: a meta-analysis

BACKGROUND

A growing body of research suggests that heat shock proteins (HSPs) may serve as diagnostic biomarkers for hepatocellular carcinoma (HCC), but their results are still controversial. This meta-analysis endeavors to evaluate the diagnostic accuracy of HSPs both independently and in conjunction with alpha-fetoprotein (AFP) as novel biomarkers for HCC detection.

METHODS

Pooled statistical indices, including sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals (CI), were computed to assess the diagnostic accuracy of HSPs, AFP, and their combinations. Additionally, the area under the summary receiver operating characteristic (SROC) curve (AUC) was determined.

RESULTS

A total of 2013 HCC patients and 1031 control subjects from nine studies were included in this meta-analysis. The summary estimates for HSPs and AFP are as follows: sensitivity of 0.78 (95% CI: 0.69-0.85) compared to 0.73 (95% CI: 0.65-0.80); specificity of 0.89 (95% CI: 0.81-0.95) compared to 0.86 (95% CI: 0.77-0.91); PLR of 7.4 (95% CI: 3.7-14.9) compared to 5.1 (95% CI: 3.3-8.1); NLR of 0.24 (95% CI: 0.16-0.37) compared to 0.31 (95% CI: 0.24-0.41); DOR of 30.19 (95% CI: 10.68-85.37) compared to 16.34 (95% CI: 9.69-27.56); and AUC of 0.90 (95% CI: 0.87-0.92) compared to 0.85 (95% CI: 0.82-0.88). The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.90 (95% CI: 0.82-0.95), 0.94 (95% CI: 0.82-0.98), 14.5 (95% CI: 4.6-45.4), 0.11 (95% CI: 0.06-0.20), 133.34 (95% CI: 29.65-599.61), and 0.96 (95% CI: 0.94-0.98) for the combination of HSPs and AFP.

CONCLUSION

Our analysis suggests that HSPs have potential as a biomarker for clinical use in the diagnosis of HCC, and the concurrent utilization of HSPs and AFP shows notable diagnostic effectiveness for HCC.

Identification of metabolism terms significantly affecting hepatocellular carcinoma immune microenvironment and immunotherapy response

Metabolic pathways exert a significant influence on the onset and progression of cancer. Public data on hepatocellular carcinoma (HCC) patients were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Analysis was performed in R software using different R packages. Here, we integrated the data from multiple independent HCC cohorts, including TCGA-LIHC, ICGC-FR and ICGC-JP. Then, the enrichment score of 21 metabolism-related pathways was quantified using the ssGSEA algorithm. Next, univariate Cox regression analysis was applied to identify the metabolic terms with significant correlation to patient survival. Finally, a prognosis model based on linoleic acid metabolism, sphingolipid metabolism and regulation of lipolysis in adipocytes was established, which showed good performance in predicting patients' survival. Furthermore, we conducted a biological enrichment analysis to delineate the biological disparities between high- and low-risk patients. Notably, we discerned differences in the microenvironments between these two patient groups. We also found that low-risk patients could potentially respond better to immunotherapy. Drug sensitivity analysis suggested that low-risk patients are more susceptible to bexarotene and erlotinib, yet exhibit resistance to ATRA and bleomycin. Furthermore, through the use of LASSO logistic regression analysis, we identified 19 characteristic genes, which could robustly indicate the risk groups. Our research underscores the role of linoleic acid metabolism, sphingolipid metabolism and the regulation of lipolysis in adipocytes in HCC, pointing towards potential avenues for future research.

The action and resistance mechanisms of Lenvatinib in liver cancer

Lenvatinib is a tyrosine kinase inhibitor that prevents the formation of new blood vessels namely by inhibiting tyrosine kinase enzymes as the name suggests. Specifically, Lenvatinib acts on vascular endothelial growth factor receptors 1-3 (VEGFR1-3), fibroblast growth factor receptors 1-4 (FGFR1-4), platelet-derived growth factor receptor-alpha (PDGFRα), tyrosine-kinase receptor (KIT), and rearranged during transfection receptor (RET). Inhibition of these receptors works to inhibit tumor proliferation. It is through these inhibition mechanisms that Lenvatinib was tested to be noninferior to Sorafenib. However, resistance to Lenvatinib is common, making the positive effects of Lenvatinib on a patient's survival null after resistance is acquired. Therefore, it is crucial to understand mechanisms related to Lenvatinib resistance. This review aims to piece together various mechanisms involved in Lenvatinib resistance and summarizes the research done so far investigating it.

DCE-MRI-based radiomics in predicting angiopoietin-2 expression in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the sixth most common cancer, and the third leading cause of cancer death worldwide. Studies have shown that increased angiopoietin-2 (Ang-2) expression relative to Ang-1 expression in tumors is associated with a poor prognosis.The purpose of this study was to investigate the efficacy of predicting Ang-2 expression in HCC by preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-based radiomics.

METHODS

The data of 52 patients with HCC who underwent surgical resection in our hospital were retrospectively analyzed. Ang-2 expression in HCC was analyzed by immunohistochemistry. All patients underwent preoperative upper abdominal DCE-MRI and intravoxel incoherent motion diffusion-weighted imaging scans. Radiomics features were extracted from the early and late arterial and portal phases of axial DCE-MRI. Univariate analysis and least absolute shrinkage and selection operator (LASSO) was performed to select the optimal radiomics features for analysis. A logistic regression analysis was performed to establish a DCE-MRI radiomics model, clinic-radiologic (CR) model and combined model integrating the radiomics score with CR factors. The stability of each model was verified by 10-fold cross-validation. Receiver operating characteristic (ROC) curve analysis, calibration curve analysis and decision curve analysis (DCA) were employed to evaluate these models.

RESULTS

Among the 52 HCC patients, high Ang-2 expression was found in 30, and low Ang-2 expression was found in 22. The areas under the ROC curve (AUCs) for the radiomics model, CR model and combined model for predicting Ang-2 expression were 0.800, 0.874, and 0.933, respectively. The DeLong test showed that there was no significant difference in the AUC between the radiomics model and the CR model (p > 0.05) but that the AUC for the combined model was significantly greater than those for the other 2 models (p < 0.05). The DCA results showed that the combined model outperformed the other 2 models and had the highest net benefit.

CONCLUSION

The DCE-MRI-based radiomics model has the potential to predict Ang-2 expression in HCC patients; the combined model integrating the radiomics score with CR factors can further improve the prediction performance.

Survival of Patients with Hepatitis B-Related Hepatocellular Carcinoma with Concomitant Metabolic Associated Fatty Liver Disease

Purpose

Metabolic associated fatty liver disease is a novel concept defined as fatty liver associated with metabolic disorders. We investigated the effect of metabolic associated fatty liver disease on hepatocellular carcinoma patient mortality.

Patients and Methods

A total of 624 patients with hepatocellular carcinoma between 2012 and 2020 were enrolled in this retrospective study. Hepatic steatosis was diagnosed using computed tomography or magnetic resonance imaging. Metabolic associated fatty liver disease was defined based on the proposed criteria in 2020. Propensity score matching was performed for patients with metabolic associated fatty liver disease and those without the condition. A Cox proportional hazards regression model was used to evaluate the association between metabolic associated fatty liver disease and hepatocellular carcinoma patient outcomes.

Results

Patients with hepatocellular carcinoma and metabolic associated fatty liver disease tended to achieve better outcomes than did those without metabolic associated fatty liver disease after matching (p<0.001). Metabolic associated fatty liver disease was significantly associated with better prognosis in patients with concurrent hepatitis B infection (p<0.001). Moreover, high levels of hepatitis B viral DNA in serum samples was associated with a significantly increased risk of death in patients without non-metabolic associated fatty liver disease (p=0.045). Additionally, the association between metabolic associated fatty liver disease and survival in hepatitis B virus-related hepatocellular carcinoma was similar in all subgroups based on metabolic traits.

Conclusion

Metabolic associated fatty liver disease increases the survival rate of patients with hepatocellular carcinoma and hepatitis B virus infection. The potential interaction of steatosis and virus replication should be considered for future research and clinical treatment strategies.

Preoperative MRI-based multiparametric model for survival prediction in hepatocellular carcinoma patients with portal vein tumor thrombus following hepatectomy

PURPOSE

To develop a predictive model integrating clinical and MRI features for postoperative survival in patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT).

METHOD

Between January 2008 and May 2021, consecutive HCC patients with PVTT who underwent preoperative contrast-enhanced MRI and surgical resection at a tertiary hospital were retrospectively enrolled. The MR images were independently reviewed by two blinded radiologists. Univariate and multivariate Cox regression analyses were performed to construct a prognostic score for overall survival (OS).

RESULTS

Ninety-four patients were included (mean age, 50.1 years; 84 men). During a median follow-up period of 15.3 months, 72 (76.6%) patients died (median OS, 15.4 months; median disease-free survival [DFS], 4.6 months). The sum size of the two largest tumors (hazard ratio [HR], 3.050; p < 0.001) and tumor growth subtype (HR, 1.928; p = 0.006) on MRI, serum albumin (HR, 0.948; p = 0.02), and age (HR, 0.978; p = 0.04) were associated with OS and incorporated in the prognostic score. Accordingly, patients were stratified into a high-risk or low-risk group, and the OS in the high-risk group was shorter than that in the low-risk group for the entire cohort (11.7 vs. 25.0 months, p < 0.001) and for patients with Cheng's type I (12.1 vs. 25.9 months, p = 0.002) and type II PVTT (11.7 vs. 25.0 months, p = 0.004). The DFS in the high-risk group was shorter than that in the low-risk group for the entire cohort (4.5 vs. 6.1 months, p = 0.001).

CONCLUSIONS

Based on the sum size of the two largest tumors, tumor growth subtype, albumin, and age, the prognostic score allowed accurate preoperative risk stratification in HCC patients with PVTT, independent of Cheng's PVTT classification.

The role of N-glycosylation modification in the pathogenesis of liver cancer

N-glycosylation is one of the most common types of protein modifications and it plays a vital role in normal physiological processes. However, aberrant N-glycan modifications are closely associated with the pathogenesis of diverse diseases, including processes such as malignant transformation and tumor progression. It is known that the N-glycan conformation of the associated glycoproteins is altered during different stages of hepatocarcinogenesis. Characterizing the heterogeneity and biological functions of glycans in liver cancer patients will facilitate a deeper understanding of the molecular mechanisms of liver injury and hepatocarcinogenesis. In this article, we review the role of N-glycosylation in hepatocarcinogenesis, focusing on epithelial-mesenchymal transition, extracellular matrix changes, and tumor microenvironment formation. We highlight the role of N-glycosylation in the pathogenesis of liver cancer and its potential applications in the treatment or diagnosis of liver cancer.

The role of N-glycosylation modification in the pathogenesis of liver cancer

N-glycosylation is one of the most common types of protein modifications and it plays a vital role in normal physiological processes. However, aberrant N-glycan modifications are closely associated with the pathogenesis of diverse diseases, including processes such as malignant transformation and tumor progression. It is known that the N-glycan conformation of the associated glycoproteins is altered during different stages of hepatocarcinogenesis. Characterizing the heterogeneity and biological functions of glycans in liver cancer patients will facilitate a deeper understanding of the molecular mechanisms of liver injury and hepatocarcinogenesis. In this article, we review the role of N-glycosylation in hepatocarcinogenesis, focusing on epithelial-mesenchymal transition, extracellular matrix changes, and tumor microenvironment formation. We highlight the role of N-glycosylation in the pathogenesis of liver cancer and its potential applications in the treatment or diagnosis of liver cancer.

Oncogenic lncRNA BBOX1-AS1 promotes PHF8-mediated autophagy and elicits sorafenib resistance in hepatocellular carcinoma

Some long non-coding RNAs (lncRNAs) have been documented to be involved in cancer progression and anticancer drug resistance in hepatocellular carcinoma (HCC). Thus, approaches designed to target these genes may facilitate the development of promising strategies for treating HCC. Previously, we showed that lncRNA BBOX1-AS1 was highly expressed and played an oncogenic role in HCC. However, the potential functions and mechanisms through which BBOX1-AS1 regulates HCC progression and drug resistance remain unclear. This study revealed that BBOX1-AS1 could promote tumor progression, autophagy, and drug resistance by upregulating PHF8 in HCC cells. Mechanistically, BBOX1-AS1 enhanced the stability of PHF8 mRNA by targeting the PHF8 inhibitor miR-361-3p to regulate tumor progression and autophagy in HCC. The functional rescue experiments showed that PHF8 acted as a key factor in regulating the biological effects induced by BBOX1-AS1 and miR-361-3p in HCC, indicating that BBOX1-AS1 promotes tumor progression and sorafenib resistance by regulating miR-361-3p/PHF8. Finally, mouse tumor models and patient-derived organoid models were established to further confirm these findings. Taken together, the results demonstrate that BBOX1-AS1 promotes HCC progression and sorafenib resistance via the miR-361-3p/PHF8 axis.

ALKBH5-mediated m6A modification of lincRNA LINC02551 enhances the stability of DDX24 to promote hepatocellular carcinoma growth and metastasis

As the most important RNA epigenetic regulation in eukaryotic cells, N6-metheyladenosine (m⁶A) modification has been demonstrated to play significant roles in cancer progression. However, this modification in long intergenic non-coding RNAs (lincRNAs) and the corresponding functions remain elusive. Here, we showed a lincRNA LINC02551 was downregulated by AlkB Homolog 5 (ALKBH5) overexpression in a m⁶A-dependent manner in hepatocellular carcinoma (HCC). Functionally, LINC02551 was required for the growth and metastasis of HCC. Mechanistically, LINC02551, a bona fide m⁶A target of ALKBH5, acted as a molecular adaptor that blocked the combination between DDX24 and a E3 ligase TRIM27 to decrease the ubiquitination and subsequent degradation of DDX24, ultimately facilitating HCC growth and metastasis. Thus, ALKBH5-mediated LINC02551 m⁶A methylation was required for HCC growth and metastasis.

Circular RNA circRASSF5 Functions as an Anti-Oncogenic Factor in Hepatocellular Carcinoma by Acting as a Competitive Endogenous RNA Through Sponging miR-331-3p

Objective

Recently, emerging studies have validated that circular RNAs participate in multiple biological progresses in various human malignant tumors, including hepatocellular carcinoma (HCC). However, until now, the elucidated mechanism of circular RNAs is only the tip of the iceberg. In this study, we firstly identify a novel circular RNA circRASSF5 (the only circular RNA derived from the RASSF5 gene), and attempt to investigate its biological function and underlying mechanism in HCC.

Methods

qRT-PCR, Western blotting and IHC were applied to detect the expression of related genes. CCK-8 assay, EdU staining, wound healing and transwell assays were used to investigate HCC proliferation, migration and invasion abilities. Animal model studies were included to investigate the function of circRASSF5 in HCC tumorigenesis and metastasis. RNA pull-down assay, luciferase reporter assay and FISH (fluorescence in situ hybridization) assay were performed to explore the potential biological mechanism underlying circRASSF5 function in HCC.

Results

CircRASSF5 is obviously downregulated in both HCC tissues and cell lines. Low level of circRASSF5 is negatively associated with larger tumor size, severe vascular invasion, more portal vein tumor embolus and unfavorable prognosis. Loss-of-function assay reveals that circRASSF5 remarkably impedes the growth and metastasis of HCC cells in vitro and in vivo. Mechanistically, circRASSF5 directly interacts with miR-331-3p as a sponge, and then enhances the expression of PH domain and leucine-rich repeat protein phosphatase (PHLPP), thus restraining the progression of HCC cells.

Conclusion

Altogether, we validate that circRASSF5 is a tumor suppressor in HCC, which competitively sponges with miR-331-3p and then enhances the tumor inhibitory effect of PHLPP, indicating the potential application value of circRASSF5 for HCC diagnosis and clinical treatment.

Circular RNA hsa_circ_0000437 may be used as a new indicator for the diagnosis and prognosis of hepatocellular carcinoma

Circular RNAs (circRNAs) play an essential role in hepatocellular carcinoma (HCC); however, the precise role of circRNAs in the diagnosis and prognosis of HCC remains unclear. The circRNA circ_0000437 was identified in the microarray dataset GSE166678 and was detected in HCC and paired adjacent tissue and serum samples in both the HCC and control groups by reverse transcription quantitative PCR. The association between circ_0000437 expression and clinicopathological characteristics was investigated. Furthermore, the diagnostic and prognostic values of circ_0000437 were determined using receiver operating characteristic (ROC) and Kaplan-Meier curves. Circ_0000437 expression was markedly upregulated in the tumor group compared with the control group and was correlated with tumor node metastasis (TNM) classification, differentiation degree, tumor size, and Barcelona Clinic Liver Cancer (BCLC) stage (P< 0.05) in both the tumor tissues and serum. Furthermore, poor overall survival (OS) was correlated with high circ_0000437 expression, and the area under the ROC curve (AUC) of circ_0000437 for the diagnosis of HCC was 0.9281 in the serum. Our findings suggest that circ_0000437 may be used as a novel biomarker for the diagnosis and prognosis of patients with HCC.

The Fibrinogen/Albumin Ratio Index as an Independent Prognostic Biomarker for Patients with Combined Hepatocellular Cholangiocarcinoma After Surgery

Purpose

The fibrinogen/albumin ratio (FAR) is increasingly considered as a potential biomarker for predicting prognosis in various malignant tumors, whereas the value of the FAR in predicting the recurrence-free survival (RFS) in patients with combined hepatocellular cholangiocarcinoma (cHCC-CCA) after surgery has not been studied.

Patients and Methods

A total of 104 patients with surgical-pathologically proved cHCC-CCA were retrospectively analyzed. The best cut-off value of the FAR was calculated via receiver operating characteristic (ROC) curve analysis, and the cohort was then divided into two groups as high-FAR (H-FAR) group and low-FAR (L-FAR) group. The correlation between the preoperative FAR and clinicopathological characteristics was analyzed. Uni- and multi-variable analyses for RFS were evaluated using a Cox proportional hazards model to verify the predictive value of FAR on the RFS of cHCC-CCA. Additionally, a novel clinical nomogram based on FAR was developed to preoperatively predict the RFS of HCC-CCA. The C-index and calibration were conducted to evaluate the performance of the developed nomogram.

Results

According to the cut-off value of the FAR, the patients were grouped into the H-FARI (>0.075) and L-FARI (≤0.075) groups. FAR was significantly correlated with several clinical-pathological features, including age, cirrhosis, AFP, CA19-9, BCLC staging, NLR, and PLR. In the multi-variate analysis, FAR, cirrhosis and tumor size were independent prognostic predictors for poor RFS in cHCC-CCA patients after surgery. Moreover, the clinical nomogram based on FAR was constructed, showing well-predictive accuracy.

Conclusion

The preoperative FAR is a convenient and feasible serum biomarker for predicting the RFS of cHCC-CCA after surgery. Such developed FAR-based nomogram integrating tumor size and cirrhosis could be served as a feasible and convenient tool to assist the decision-making of clinical strategy.

Low APOA-1 Expression in Hepatocellular Carcinoma Patients Is Associated With DNA Methylation and Poor Overall Survival

Background: Hepatocellular carcinoma (HCC) is the most frequent fatal malignancy, and it has a poor prognosis. Apolipoprotein 1 (APOA-1), the main protein component of high-density lipoproteins, is involved in numerous biological processes. Thus, this study was performed to detect the clinical significance of APOA-1 mRNA, APOA-1 expression, and APOA-1DNA methylation in patients with HCC.

Methods: Data mining was performed using clinical and survival data from the Cancer Genome Atlas (TCGA) and Oncomine databases. The serum concentration of APOA-1 was measured in 316 patients with HCC and 100 healthy individuals at Renmin Hospital of Wuhan University, and the intact clinical information was reviewed and determined using univariate and multivariate Cox hazard models.

Results: Bioinformatic analysis revealed that APOA-1 mRNA was present at lower levels in the serum of patients with HCC than in that of healthy individuals, and there was a strong negative correlation between levels of APOA-1 mRNA and APOA-1 DNA methylation. High expression of APOA-1 transcription correlated with better overall survival (p = 0.003), and APOA-1 hypermethylation correlated with progress-free survival (p = 0.045) in HCC sufferers. Next, the clinical data analysis demonstrated that APOA-1 protein levels in the serum were significantly lower in patients with HCC than in healthy controls. Furthermore, the expression of APOA-1 was significantly associated with some significant clinical indexes, and elevated APOA-1 expression was significantly associated with favorable (OS; HR:1.693, 95% CI: 1.194–2.401, p = 0.003) and better progression-free survival (PFS; HR = 1.33, 95% CI = 1.194–2.401, p = 0.045). Finally, enrichment analysis suggested that co-expressed genes of APOA-1 were involved in lipoprotein metabolism and FOXA2/3 transcription factor networks.

Conclusion: APOA-1 mRNA expression is negatively regulated by DNA methylation in HCC. Low expression of APOA-1 might be a potential risk biomarker to predict survival in patients with HCC.