Characteristics and prognosis of patients with large well-differentiated hepatocellular carcinoma who have undergone resection

Application of CT-based radiomics combined with laboratory tests such as AFP and PIVKA-II in preoperative prediction of pathologic grade of hepatocellular carcinoma

BACKGROUND

To investigate how effectively clinical features and CT-based radiomic features predict the pathological grade of hepatocellular carcinoma (HCC).

METHODS

We retrospectively analyzed 108 patients diagnosed with hepatocellular carcinoma who underwent pathological examination between May 2020 and May 2024 at the Second Hospital of Jilin University. All patients underwent laboratory tests and contrast-enhanced computed tomography (CECT) scanning of the liver within one month prior to pathological examination. First, we analyzed laboratory tests, such as alpha fetoprotein (AFP) and des-γ-carboxy prothrombin (PIVKA-II), to identify risk factors associated with the pathological grading of HCC. Then, we built and evaluated the performance of the clinical model. Next, we imported the arterial-phase and venous-phase images of the CECT images into the uAI Research Portal research platform for 'one-stop' processing, which included semiautomatic ROI outlining, feature extraction, dimensionality reduction, model construction and evaluation. To evaluate the model's diagnostic effectiveness, receiver operating characteristic (ROC) curves were produced, and the related accuracy, sensitivity, specificity, and area under the curve (AUC) were computed. The models were compared using the Delong test, and the clinical value of the predictive model was assessed via the use of calibration curves and decision curve analysis (DCA) to quantify the agreement between the model and the actual outcomes.

RESULTS

Poorly differentiated hepatocellular carcinoma (pHCC) is associated with risk variables such as hepatitis C virus antibodies(HCVAb), PIVKA-II, and sex. In the training and validation cohorts, the AUC values of the clinical model were 0.719 and 0.692, respectively; those of the AP model were 0.843 and 0.773; those of the VP model were 0.806 and 0.804; those of the AP + VP model were 0.953 and 0.844; and those of the AP + VP + clinical model were 0.926 (95% CI: 0.88-0.995) and 0.863 (95% CI: 0.711-1). The DCA curves revealed that the overall net benefit of the AP + VP + clinical model was greater than that of the other models and that it had the best diagnostic results.

CONCLUSIONS

CT-based radiomic modeling combined with clinical features (sex) and laboratory tests (e.g., AFP and PIVKA-II) can reliably predict the pathological grade of HCC patients prior to surgery.

Macroscopic Characterization of Hepatocellular Carcinoma: An Underexploited Source of Prognostic Factors

The macroscopic appearance of a tumor such as hepatocellular carcinoma (HCC) may be defined as its phenotype which is de facto dictated by its genotype. Therefore, macroscopic characteristics of HCC are unlikely random but rather reflect genomic traits of cancer, presumably acting as a valuable source of information that can be retrieved and exploited to infer prognosis. This review aims to provide a comprehensive overview of the available data on the prognostic value of macroscopic characterization in HCC. A total of 57 studies meeting eligible criteria were identified, including patients undergoing liver resection (LR; 47 studies, 83%) or liver transplant (LT; 9 studies, 16%). The following macroscopic variables were investigated: tumor size (n = 42 studies), number of nodules (n = 28), vascular invasion (n = 24), bile duct invasion (n = 6), growth pattern (n = 15), resection margin (n = 11), tumor location (n = 6), capsule (n = 2) and satellite (n = 1). Although the selected studies provided insightful data with notable prognostic performances, a lack of standardization and substantial gaps were noted in the report and the analysis of gross findings. This topic remains incompletely covered. While the available studies underscored the value of macroscopic variables in HCC prognostication, important lacks were also observed. Macroscopic characterization of HCC is likely an underexploited source of prognostic factors that must be actively explored by future multidisciplinary research.

Circular RNA hsa_circ_0005218 promotes the early recurrence of hepatocellular carcinoma by targeting the miR-31-5p/CDK1 pathway

Increasing evidence has manifested that circular RNAs (circRNAs) exhibited critical function in regulating various signaling pathways related to hepatocellular carcinoma (HCC) recurrence. However, the role and mechanism of the circRNAs in the HCC early recurrence remain elusive. In this study, high-throughput RNA-sequencing (RNA-seq) analysis was conducted to identify the expression profile of circRNAs in HCC tissues and circ_0005218 was identified as one circRNA that significantly up-regulated in early recurrent HCC tissues. And patients with high expression of circ_0005218 showed worsen overall survival (OS) and disease-free survival (DFS). Moreover, the promotion effects of circ_0005218 on HCC cells in term of proliferation, invasion and metastasis were confirmed both in vitro and vivo by gain- and loss-of function assays. In addition, dual-luciferase reporter assays showed that circ_0005218 could competitively bind to micro-RNA (miR)-31-5p. Furthermore, we showed that suppression of CDK1 by miR-31-5p could be partially rescued by up-regulating circ_0005218. Taken together, the present study indicates that circ_0005218 absorbed miR-31-5p as a sponge to weaken its suppression on CDK1 expression, and thus boost HCC cell invasion and migration, which would act as a potential biomarker to predict the HCC early recurrence and as a new therapeutic target for treatment of HCC.