Diagnosis Of Hepatocellular Carcinoma Research Articles

Machine Learning Platform for Disease Diagnosis with Contrast CT Scans

Machine learning has gained significant recognition as a powerful approach for medical diagnosis using medical images. Among various medical imaging modalities, contrast-enhanced CT (CECT) is utilized to obtain additional diagnostic information that improves visualization and evaluation of certain abnormalities in the human body, as well as to observe temporal changes in lesions and tumors across different time phases. However, developing such medical diagnostic systems presents two significant challenges: high technical complexity and substantial development effort. This paper presents a software platform that effectively addresses these challenges. Specifically, we propose a unified software process that fully automates contrast-enhanced CT (CECT)-specific disease diagnosis, with key tasks performed by leveraging task-specific machine learning models to enhance accuracy. The platform incorporates a suite of specialized machine learning models into the diagnostic process, enabling precise diagnosis of lesions, malignancies, tumors, tumor characteristics, and temporal changes over phases. Moreover, the platform has been designed according to the Open–Closed Principle, allowing it to be applicable to a wide range of CECT-based diagnostic systems. The platform has been implemented in Python using the Scikit-learn and TensorFlow libraries. To validate its applicability and reusability, a hepatocellular carcinoma (HCC) diagnosis system has been implemented.

Survival Outcomes Among Patients With Hepatocellular Carcinoma in a Large Integrated US Health System

Hepatocellular carcinoma (HCC) is the leading oncologic cause of death among patients with cirrhosis, but large studies examining mortality trends are lacking. To evaluate survival among patients with HCC in one of the largest integrated health care systems in the US. This retrospective cohort study included 3441 adult patients who received a diagnosis of HCC between January 1, 2006, and December 31, 2019, with end of follow-up on December 31, 2020. The study period was further categorized as era 1, defined as 2006 to 2012, and era 2, defined as 2013 to 2019. Statistical analysis was conducted from January 2021 to June 2024. Patient demographic characteristics and disease factors. All-cause and HCC-specific mortality were used as primary end points, and survival probabilities were estimated using the Kaplan-Meier method. Cox proportional hazards regression analyses were adjusted for age at diagnosis, sex, race and ethnicity, cause of disease, Barcelona Clinic Liver Cancer (BCLC) stage, alpha-fetoprotein level, and treatment type. Of 3441 patients with HCC, 2581 (75.0%) were men, and the median age was 65 years (IQR, 58-73 years). A total of 1195 patients (34.7%) received curative treatment, 1374 (39.9%) received noncurative treatment, and 872 (25.3%) received no treatment. During the study period, 2500 patients (72.7%) experienced all-cause mortality, and 1809 (52.6%) had HCC-specific mortality. In multivariable analysis, being 70 years of age or older (adjusted hazard ratio [AHR], 1.39; 95% CI, 1.22-1.59), male sex (AHR, 1.20; 95% CI, 1.07-1.35), BCLC stage C or D (AHR, 2.40; 95% CI, 2.15-2.67), increasing alpha-fetoprotein level (vs <20 ng/mL; 20-99 ng/mL: AHR, 1.20; 95% CI, 1.04-1.38; ≥1000 ng/mL: AHR, 2.84; 95% CI, 2.45-3.25), noncurative treatment (AHR, 2.51; 95% CI, 2.16-2.90), and no treatment (AHR, 3.15; 95% CI, 2.64-3.76) were associated with higher all-cause mortality, while Asian or Other Pacific Islander race and ethnicity (vs non-Hispanic White; AHR, 0.76; 95% CI, 0.65-0.88) was associated with lower all-cause mortality. Survival improved in diagnosis era 2 (2013-2019; n = 2007) compared with diagnosis era 1 (2006-2012; n = 1434). This large, racially and ethnically diverse cohort study of patients with HCC found improving survival over time, especially among individuals with early-stage HCC receiving potentially curative treatments. This study highlights the importance of surveillance for detection of HCC at early stages, particularly among groups at risk for poorer outcomes.

Automatic Diagnosis of Hepatocellular Carcinoma and Metastases Based on Computed Tomography Images.

Liver cancer, a leading cause of cancer mortality, is often diagnosed by analyzing the grayscale variations in liver tissue across different computed tomography (CT) images. However, the intensity similarity can be strong, making it difficult for radiologists to visually identify hepatocellular carcinoma (HCC) and metastases. It is crucial for the management and prevention strategies to accurately differentiate between these two liver cancers. This study proposes an automated system using a convolutional neural network (CNN) to enhance diagnostic accuracy to detect HCC, metastasis, and healthy liver tissue. This system incorporates automatic segmentation and classification. The liver lesions segmentation model is implemented using residual attention U-Net. A 9-layer CNN classifier implements the lesions classification model. Its input is the combination of the results of the segmentation model with original images. The dataset included 300 patients, with 223 used to develop the segmentation model and 77 to test it. These 77 patients also served as inputs for the classification model, consisting of 20 HCC cases, 27 with metastasis, and 30 healthy. The system achieved a mean Dice score of in segmentation and a mean accuracy of in classification, both in the test phase. The proposed method is a preliminary study with great potential in helping radiologists diagnose liver cancers.

Comparing barriers to early stage diagnosis of hepatocellular carcinoma between safety net hospitals and academic medical centers: An analysis from the United States Safety-Net Collaborative.

Early detection of hepatocellular carcinoma (HCC) is associated with improved survival. However, a greater proportion of patients treated at safety net hospitals (SNHs) present with late-stage disease compared to those at academic medical centers (AMCs). This study aims to identify barriers to diagnosis of HCC, highlighting differences between SNHs and AMCs. The US Safety Net Collaborative-HCC database was queried. Patients were stratified by facility of diagnosis (SNH or AMC). Patient demographics and HCC screening rates were examined. The primary outcome was stage at diagnosis (AJCC I/II-"early"; AJCC III/IV-"late"). 1290 patients were included; 50.2% diagnosed at SNHs and 49.8% at AMCs. At SNHs, 44.4% of patients were diagnosed late, compared to 27.6% at AMCs. On multivariable regression, Black race was associated with late diagnosis in both facilities (SNH: odds ratio 1.96, p = 0.03; AMC: 2.27, <0.01). Screening was associated with decreased odds of late diagnosis (SNH: 0.46, p = 0.04; AMC: 0.37, p < 0.01). Black race was associated with late diagnosis of HCC, while screening was associated with early diagnosis across institutional types. These results suggest socially constructed racial bias in screening and diagnosis of HCC. Screening efforts targeting SNH patients and Black patients at all facilities are essential to reduce disparities.

A Phase 3 Biomarker Validation of GALAD for the Detection of Hepatocellular Carcinoma in Cirrhosis

Better surveillance tests for hepatocellular carcinoma (HCC) are needed. The GALAD score (gender, age, α-fetoprotein [AFP] L3, AFP, and des carboxyprothrombin) has been shown to have excellent sensitivity and specificity for HCC in phase 2 studies. We performed a phase 3 biomarker validation study to compare GALAD with AFP in detecting HCC. This is a prospective study of patients with cirrhosis enrolled at 7 centers. Surveillance for HCC was performed every 6 months at each site, and HCC diagnosis was confirmed per American Association for the Study of Liver Diseases guidelines. Blood for biomarker research was obtained at each follow-up visit and stored in a biorepository. Measurements of AFP, AFP-L3, and des-γ carboxyprothrombin) were performed in a FujiFilm laboratory by staff blinded to clinical data. The performance of GALAD in detecting HCC was retrospectively evaluated within 12 months before the clinical diagnosis. All analyses were conducted by an unblinded statistician in the EDRN data management and coordinating center. A total of 1,558 patients with cirrhosis were enrolled and followed for a median of 2.2 years. A total of 109 patients developed HCC (76 very early or early stage), with an annual incident rate of 2.4%. The areas under the curve for AFP and GALAD within 12 months before HCC were 0.66 and 0.78 (P < .001), respectively. Using a cutoff for GALAD of -1.36, the specificity was 82%, and the sensitivity at 12 months before HCC diagnosis was 62%. For comparison, performance of AFP at 82% specificity showed 41% sensitivity at 12 months before HCC diagnosis (P= .001). GALAD score, compared to AFP, improves the detection of HCC within 12 months before the actual diagnosis.

Comparison of Metastasectomy and Stereotactic Body Radiation Therapy for Pulmonary Oligometastasis From Hepatocellular Carcinoma: A Propensity Score-Weighted Analysis

Although there is a growing role for local therapy in patients with hepatocellular carcinoma (HCC) and pulmonary oligometastasis, it remains unclear whether metastatectomy or stereotactic body radiation therapy (SBRT) is the more effective treatment for these patients. We aimed to compare the oncologic outcomes of metastasectomy and SBRT for HCC with pulmonary oligometastasis. We retrospectively analyzed 209 patients with HCC with 322 metastatic lung lesions who underwent either metastasectomy (150 patients with 241 lesions) or SBRT (59 patients with 81 lesions) between January 2008 and December 2018. Propensity score-based inverse probability of treatment weighting was used to minimize potential bias between the 2 groups. The median follow-up duration was 39.8 months (range, 2.3-166.9 months). The 2-year rate of freedom from local progression was 98.2% in the metastasectomy group and 97.0% in the SBRT group (P = .197). The 2-year rates of overt systemic progression-free survival (PFS) (51.0% vs 46.1%; P = .274), PFS (26.3% vs 9.1%; P = .074), and overall survival (OS, 74.0% vs 57.6%; P = .006) were higher in the metastasectomy group. After the probability of treatment weighting adjustment, the 2-year rates of overt systemic PFS (50.8% vs 52.7%; P = .396), PFS (23.0% vs 24.7%; P = .478), and OS (72.6% vs 83.0%, P = .428) were not significantly different between the 2 groups. In multivariate analysis, viable intrahepatic lesions and the number of prior liver-directed therapies were found to be significant prognostic factors for OS and PFS. The time interval between HCC diagnosis and the development of pulmonary metastases was also significantly associated with OS. Both metastasectomy and SBRT demonstrated excellent local control and comparable oncologic outcomes in patients with pulmonary oligometastasis from HCC. The treatment modality for these patients could be determined based on the individual patient's condition and intrahepatic disease status.

Five miRNAs identified in fucosylated extracellular vesicles as non-invasive diagnostic signatures for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that presents significant challenges for early detection. This study introduces the GlyExo-Capture method for isolating fucosylated extracellular vesicles (Fu-EVs) from serum. We analyze microRNA (miRNA) profiles from Fu-EVs in 88 HCC patients and 179 non-HCC controls using next-generation sequencing (NGS) and identify five miRNAs (hsa-let-7a, hsa-miR-21, hsa-miR-125a, hsa-miR-200a, and hsa-miR-150) as biomarkers for HCC diagnosis. The five-miRNA panel demonstrates exceptional HCC diagnostic performance, with a sensitivity of 0.90 and specificity of 0.92 in a combined cohort of 194 HCC and 412 non-HCC controls, significantly surpassing the performance of alpha-fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP). Notably, the miRNA model achieves recall rates of 85.7% and 90.8% for stage 0 and stage A early-stage HCC, respectively, identifies 88.1% of AFP-negative HCC cases, and effectively differentiates HCC from other cancers. This study provides a high-throughput, rapid, and non-invasive approach for early HCC detection.

Analytical and Diagnostic Performance of a Dual-Target Blood Detection Test for Hepatocellular Carcinoma.

Surveillance approaches with high sensitivity and specificity for hepatocellular carcinoma (HCC) are still urgently needed. Previous studies have shown that methylation of GNB4 and Riplet can effectively diagnose HCC. This study plan to analyze the performance of a blood test for detecting HCC using GNB4 and Riplet methylation. This study mainly investigated the analytical performance of the dual-target HCC blood test (DT-HBT), including cut-off value, limit of detection (LOD), precision, analytical specificity, and coincidence rate. In addition, the detection performance for HCC was validated in 1030 clinical plasma samples (214 HCC and 816 non-HCC). Plasma samples from 25 HCC patients after hepatectomy were collected to assess the feasibility of the kit for postoperative recurrence monitoring. All analytical performance of the DT-HBT met prespecified requirements. The LOD for GNB4, Riplet, and β-actin was 1% methylation/100 copies/μL with cut-offs of 43, 43, and 35, respectively. The DT-HBT showed excellent precision, within 5% CV. It had a specificity of 91.5% for detecting other cancers, and 100% for breast, lung, and bladder cancer. No cross-reactions were observed with 9 potential interfering substances. The DT-HBT achieved a 100% coincidence rate in detecting reference and clinical samples. The clinical performance study found that the kit showed a sensitivity of 81.7% for stage I HCC, and an overall sensitivity and specificity of 87.4% and 92.3%, respectively. The detection sensitivity for postoperative recurrent patients was 95.8%, with a specificity of 100%. The analytical performance of the DT-HBT met prespecified criteria. It provided HCC patients with a reliable and high-performing new blood test for the HCC diagnosis and surveillance. ClinicalTrials.gov identifier: NCT05685524.

Identification of a prognostic disulfidptosis-related gene signature in hepatocellular cancer.

Disulfidptosis regulate various biological processes in cancer. However, there is limited research on the genes related to disulfidptosis in predicting the prognosis of hepatocellular carcinoma (HCC). We aimed to develop a reliable disulfidptosis-related gene signature, which will characterize different HCC subtypes and predict their prognosis. The Cancer Genome Atlas (TCGA)-HCC dataset, comprising RNA sequencing data and clinical information, was obtained from the TCGA database. The crucial disulfidptosis-related genes were selected for bioinformatic analysis in HCC. HCC tumor classification was established through a consistent cluster analysis. The prognosis and immune-cell infiltration were investigated in association with a disulfidptosis-related HCC model. In TCGA-HCC patients, a total of 3,621 prognostic genes and 30 key prognostic disulfidptosis-related genes were identified. Using key prognostic disulfidptosis-related genes, TCGA-HCC patients were categorized into low- and high-risk clusters. The upregulated differentially expressed genes (DEGs) in high-risk cluster 1 (C1) could significantly impact cell cycle, DNA replication, and the p53 signaling pathway, whereas the pathways associated with the downregulated DEGs in high-risk C1 could significantly impact metabolism of xenobiotics by cytochrome P450, the PPAR signaling pathway, and tyrosine metabolism. Furthermore, the immune activity of the high-risk C1 group was different to that of the low-risk cluster 2 (C2) group. The 13 disulfidptosis-related genes were finally screened using least absolute shrinkage and selection operator (LASSO) regression analysis, including ANP32E, BOP1, RPN1, SLC7A11, PPIH, PCBP2, ME1, PRDX1, FLNC, INF2, MYH11, LRPPRC, and HNRNPM. The genes related to disulfidptosis are closely associated with tumor classification and immunity in patients with HCC. This is the first gene signature related to disulfidptosis demonstrated a strong predictive performance for the prognosis of HCC, which provide new perspectives for the diagnosis and treatment of HCC.

Conversion Therapy to Transplant or Surgical Resection in Patients with Unresectable Hepatocellular Carcinoma Treated with Boosted Dose of Yttrium-90 Radiation Segmentectomy.

The aim of this study was to assess the efficacy of boosted dose yttrium-90 radioembolization (TARE) as a modality for conversion therapy to transplant or surgical resection in patients with unresectable hepatocellular carcinoma (HCC). In this single-center retrospective study, all patients with a diagnosis of HCC who were treated with boosted dose TARE (>190 Gy) between January 2013 and December 2023 were reviewed. Treatment response and decrease in tumor size were assessed with the RECIST v1.1 and mRECIST criteria. Milan and University of California, San Francisco (UCSF), criteria were used to determine transplant eligibility, and Barcelona Clinic Liver Cancer (BCLC) surgical resection recommendations were used to evaluate tumor resectability. Thirty-eight patients with primary HCC who were treated with boosted dose TARE were retrospectively analyzed. The majority of the patients were Child-Pugh A (n = 35; 92.1%), BCLC C (n = 17; 44.7%), and ECOG performance status 0 (n = 25; 65.8%). The mean sum of the target lesions was 6.0 cm (standard deviation; SD = 4.0). The objective response rate (ORR) was 31.6% by RECIST and 84.2% by mRECIST. The disease control rate (DCR) was 94.7% by both RECIST and mRECIST. Among patients outside of Milan or UCSF, 13/25 (52.0%, Milan) and 9/19 (47.4%, UCSF) patients were successfully converted to within transplant criteria. Of patients who were initially unresectable, conversion was successful in 7/26 (26.9%) patients. This study provides further real-world data demonstrating that boosted-dose TARE is an effective modality for conversion of patients with unresectable HCC to transplant or resection.

Locoregional Treatments in Peritoneal Metastasis from Gastric Cancer

Background: Liver cancer is among the top five causes of cancer death globally. Hepatocellular Carcinoma (HCC) accounts for up to 90% of primary liver neoplasms in adults. The incidence of thyroid me-tastasis from HCC is rare and estimated from 0.8 to 12%. This report describes a 51-year-old man presenting with hypercalcemia and known metastatic HCC with new metastasis to the thyroid gland. Case Report: A 51-year-old male was admitted due to symptomatic hypercalcemia. His medical history included HCC with metastasis to the retroperitoneal lymph nodes diagnosed one year prior. Computed tomography revealed an enlarging liver mass, diffuse lymphadenopathy and many osseous lytic lesions. Ultrasound of the neck revealed abnormal right cervical lymph nodes and a heterogeneous mass replacing the right thyroid gland. Biopsy of the right cervical lymph node immunohistochemical stained positive for PAN-K, Glypican-3, HepPar1 and Anti-Arginase and negative for p40 and CEA-poly, supporting the diagnosis for metastatic HCC. His hospital course was complicated by dysphagia, spontaneous bacterial peritonitis and acute-on-chronic liver failure. Despite aggressive resuscitation, he continued to decline and ultimately pursued hospice care. Conclusion: This case illustrates the need to have a high index of suspicion for thyroid metastasis in HCC patients presenting with a new-onset cervical mass, dysphagia or hypercalcemia. Metastatic cancer to the thyroid gland is generally considered a poor prognostic factor, as seen in this case with the rapid decline. This case demonstrates an extremely rare presentation of HCC with metastasis to the thyroid gland.

Impact of metformin, statin, aspirin and insulin on the prognosis of uHCC patients receiving first line Lenvatinib or Atezolizumab plus Bevacizumab

Recently, in Hepatocellular carcinoma (HCC) setting, the use of metformin has been associated to a trend toward worse response rate, overall survival and progression free survival in patients who received immunotherapy. The study population included individuals from both Eastern and Western regions with a confirmed diagnosis of HCC and receiving first line treatment with Atezolizumab plus bevacizumab or Lenvatinib. Univariate and multivariate analyses were performed by Cox proportional. For the analysis, patients were stratified based on their use of concomitant medication or not. At the time of database lock, 319 deaths were observed: 209 in the Lenvatinib cohort, 110 in the Atezolizumab plus bevacizumab cohort. In the Atezolizumab plus Bevacizumab arm, 50 (16.5%) patients were on chronic metformin use. At the univariate analysis for OS, patients who used metformin showed significantly shorter OS compared to patients who did not use metformin (HR 1.9, 95% CI 1.1–3.2). Multivariate analysis confirmed that patients in metformin group had significantly shorter OS compared to patients in no-metformin group (HR 1.9; 95% CI 1.1–3.1). At the univariate analysis for PFS, patients in metformin group had significantly shorter PFS compared to patients in no-metformin group (HR 1.6, 95% CI 1.0–2.6). Multivariate analysis confirmed that patients in metformin group had significantly shorter PFS compared to patients in no-metformin group (HR 1.7; 95% CI 1.1–2.7; p = 0.0147). No differences were reported in terms of ORR and DCR between patients in metformin group and those in no-metformin group. In the Lenvatinib cohort, 65 (15%) patients were recorded to chronically use metformin. No statistically significant differences in terms of both OS and PFS were found between patients in metformin group and patients in no-metformin group. This analysis unveils a negative prognostic role associated with metformin use specifically within the Atezolizumab plus Bevacizumab group.

Clinical Nomogram Model for Pre-Operative Prediction of Microvascular Invasion of Hepatocellular Carcinoma before Hepatectomy.

Background and Objectives: Microvascular invasion (MVI) significantly impacts recurrence and survival rates after liver resection in hepatocellular carcinoma (HCC). Pre-operative prediction of MVI is crucial in determining the treatment strategy. This study aims to develop a nomogram model to predict the probability of MVI based on clinical features in HCC patients. Materials and Methods: A total of 489 patients with a pathological diagnosis of HCC were enrolled from our hospital. Those registered from 2012-2015 formed the derivation cohort, and those from 2016-2019 formed the validation cohort for pre-operative prediction of MVI. A nomogram model for prediction was created using a regression model, with risk factors derived from clinical and tumor-related features before surgery. Results: Using the nomogram model to predict the odds ratio of MVI before hepatectomy, the AFP, platelet count, GOT/GPT ratio, albumin-alkaline phosphatase ratio, ALBI score, and GNRI were identified as significant variables for predicting MVI. The Youden index scores for each risk variable were 0.287, 0.276, 0.196, 0.185, 0.115, and 0.112, respectively, for the AFP, platelet count, GOT/GPT ratio, AAR, ALBI, and GNRI. The maximum value of the total nomogram scores was 220. An increase in the number of nomogram points indicated a higher probability of MVI occurrence. The accuracy rates ranged from 55.9% to 64.4%, and precision rates ranged from 54.3% to 68.2%. Overall survival rates were 97.6%, 83.4%, and 73.9% for MVI(-) and 80.0%, 71.8%, and 41.2% for MVI(+) (p < 0.001). The prognostic effects of MVI(+) on tumor-free survival and overall survival were poor in both the derivation and validation cohorts. Conclusions: Our nomogram model, which integrates clinical factors, showed reliable calibration for predicting MVI and provides a useful tool enabling surgeons to estimate the probability of MVI before resection. Consequently, surgical strategies and post-operative care programs can be adapted to improve the prognosis of HCC patients where possible.

Rational Design of Mono-Substituted Gd-DOTA as Highly Stable and Efficient MRI Contrast Agents for Hepatobiliary and Inflammation Imaging.

Hepatobiliary-specific magnetic resonance imaging contrast agents (MRI CAs) play a crucial role in the early diagnosis of hepatocellular carcinoma (HCC). However, only two acyclic CAs, Gd-BOPTA and Gd-EOB-DTPA, exhibit unfavorable kinetic inertness. Our study focused on the development of superior stable innovative macrocyclic CAs. By introducing a lipophilic benzyloxy group (OBn) into the H4DOTA ring (Gd-L1), we achieved significant enhancement in kinetic inertness. In vivo experiments in mice demonstrated that 40% of the dosage was distributed to the liver at 5 min, providing sustained hepatic enhancement for over 35 min. We also developed an MPO-responsive MRI CA (Gd-L3), which can participate in the "peroxidase cycle" as the substrate, generating oligomers with a 3.8-fold increase in relaxivity, and selectively enhance the lesion in an acute gout mouse model. Overall, our work represents a significant advancement in the field of hepatic and inflammatory MRI, offering promising avenues for early diagnosis and improved imaging outcomes.

RNA-binding motif protein 28 enhances angiogenesis by improving STAT3 translation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent malignant tumor characterized by extensive angiogenesis. However, the underlying mechanisms of HCC pathogenesis remain unclear. Previous studies have shown that RNA-binding proteins (RBPs) are implicated in HCC pathogenesis. In this study, we observed that increased RBM28 expression in HCC tissues was positively correlated with tumor microvascular density and negatively correlated with patient prognosis. Overexpression of RBM28 in HCC cells promoted tubule formation in human umbilical vein endothelial cells, whereas inhibition of RBM28 had the opposite effect, furthermore, the role of RBM28 in the progression of HCC was assessed using transgenic mouse models and chemically induced HCC models. We used various molecular assays and high-throughput detection methods to evaluate the role of RBM28 in promoting angiogenesis in HCC. Increased RBM28 expression in HCC directly binds to STAT3 mRNA, recruiting EIF4E to increase STAT3 expression and enhancing the secretion and expression of vascular endothelial growth factor A; consequently, promoting neovascularization in HCC. The potential of RBM28 as a viable diagnostic and therapeutic target for HCC was assessed using multi-cohort clinical samples and animal models. In summary, our results provide insights into the pathogenesis, clinical diagnosis, and treatment of HCC.

The role of RNA modifications in hepatocellular carcinoma: functional mechanism and potential applications.

Hepatocellular carcinoma (HCC) is a highly aggressive cancer with a poor prognosis. The molecular mechanisms underlying its development remain unclear. Recent studies have highlighted the crucial role of RNA modifications in HCC progression, which indicates their potential as therapeutic targets and biomarkers for managing HCC. In this review, we discuss the functional role and molecular mechanisms of RNA modifications in HCC through a review and summary of relevant literature, to explore the potential therapeutic agents and biomarkers for diagnostic and prognostic of HCC. This review indicates that specific RNA modification pathways, such as N6-methyladenosine, 5-methylcytosine, N7-methylguanosine, and N1-methyladenosine, are erroneously regulated and are involved in the proliferation, autophagy, innate immunity, invasion, metastasis, immune cell infiltration, and drug resistance of HCC. These findings provide a new perspective for understanding the molecular mechanisms of HCC, as well as potential targets for the diagnosis and treatment of HCC by targeting specific RNA-modifying enzymes or recognition proteins. More than ten RNA-modifying regulators showed the potential for use for the diagnosis, prognosis and treatment decision utility biomarkers of HCC. Their application value for HCC biomarkers necessitates extensive multi-center sample validation in the future. A growing number of RNA modifier inhibitors are being developed, but the lack of preclinical experiments and clinical studies targeting RNA modification in HCC poses a significant obstacle, and further research is needed to evaluate their application value in HCC treatment. In conclusion, this review provides an in-depth understanding of the complex interplay between RNA modifications and HCC while emphasizing the promising potential of RNA modifications as therapeutic targets and biomarkers for managing HCC.

Application and prospects of magnetic resonance imaging techniques in the diagnosis and evaluation of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver. MRI has become an important imaging method for non-invasive diagnosis and evaluation of HCC in clinics because of its advantageous aspects, such as its non-radiative nature, superior detection, and qualitative accuracy over CT and ultrasound. Various MRI techniques, including hepatobiliary-specific contrast agents, magnetic resonance elastography, diffusion-weighted imaging, and others, can diagnose HCC or evaluate its malignant biological behavior from different dimensions such as blood supply, cell function, tissue hardness, and water molecule diffusion. This article introduces the current status and prospects of various MRI techniques for HCC diagnosis and evaluation.

Trapped in Endosome PEGylated Ultra-Small Iron Oxide Nanoparticles Enable Extraordinarily High MR Imaging Contrast for Hepatocellular Carcinomas.

The early diagnosis of hepatocellular carcinomas (HCCs) remains challenging in the clinic. Primovist-enhanced magnetic resonance imaging (MRI) aids HCC diagnosis but loses sensitivity for tumors <2cm. Therefore, developing advanced MRI contrast agents is imperative for improving the diagnostic accuracy of HCCs in very-early-stage. To address this challenge, PEGylated ultra-small iron oxide nanoparticles (PUSIONPs) are synthesized and employed as liver-specific T1 MRI contrast agents. Intravenous delivery produces simultaneous hyperintense HCC and hypointense hepatic parenchyma signals on T1 imaging, creating an extraordinarily high tumor-to-liver contrast. Systematic studies uncover PUSIONP distribution in hepatic parenchyma, HCC lesions at the organ, tissue, cellular, and subcellular levels, revealing endosomal confinement of PUSIONP without aggregation. By mimicking such situations, the dependency of relaxometric properties on local PUSIONP concentration is investigated, emphasizing the key role of different endosomal concentrations in liver and tumor cells for high tumor-to-liver contrast and clear tumor boundaries. These findings offer exceptional imaging capabilities for early HCC diagnosis, potentially benefiting real HCC patients.

Research progress and prospects of the application of radiographic imaging in the precise diagnosis and treatment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly heterogeneous kind of malignant tumor with a high recurrence rate and low five-year survival rate, which has become one of the major public health issues in China. Currently, HCC is the only solid tumor that can be solely diagnosed based on epidemiological history and typical imaging features without preoperative pathological confirmation. The paradigm for HCC imaging diagnosis has shifted in recent years from anatomy to function, from macroscopic to microscopic, and from diagnosis to prediction in the context of precision medicine, making it possible to study the microscopic processes such as HCC genes and their metabolic laws from the perspective of qualitative and quantitative imaging, thereby providing more accurate biological and imaging information for elucidating the occurrence, development, and clinical treatment decisions of HCC.This paper reviews the research progress of HCC imaging in recent years, demonstrating the rapid horizontal development and enormous potential of imaging in the vertical follow-up of HCC precision diagnosis and treatment. Simultaneously, it also puts forward the shortcomings of current HCC imaging research and looks forward to future development directions in order to be more accurately used in clinical decision support systems.

Analysis of Serum Exosome Metabolites Identifies Potential Biomarkers for Human Hepatocellular Carcinoma.

Currently, the clinical cure rate for primary liver cancer remains low. Effective screening and early diagnosis of hepatocellular carcinoma (HCC) remain clinical challenges. Exosomes are intimately associated with tumor development and their contents have the potential to serve as highly sensitive tumor-specific markers. A comprehensive untargeted metabolomics study was conducted using exosome samples extracted from the serum of 48 subjects (36 HCC patients and 12 healthy controls) via a commercial kit. An ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) strategy was used to identify the metabolic compounds. A total of 18 differential metabolites were identified using the non-targeted metabolomics approach of UPLC-QTOF-MS/MS. Pathway analysis revealed significant alterations in the arachidonic acid metabolism, linoleic acid metabolism, and unsaturated fatty acid metabolism pathways. ROC analysis indicated that three metabolites with AUC values exceeding 0.900 were selected as potential biomarkers: caprylic acid and linoleic acid were upregulated in the HCC group, whereas pentadecanoic acid was downregulated. Linoleic acid, caprylic acid, and pentadecanoic acid are potential biomarkers for diagnosing HCC. The significant alterations in these three metabolic pathways offer new insights into the mechanisms underlying HCC formation and progression.