Programmed cell death-ligand 1 expression in hepatocellular carcinoma and its correlation with clinicopathological characteristics

A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients

Background

Edmondson-Steiner (E-S) grade is a pathological indicator of the degree of hepatocellular carcinoma (HCC) differentiation, and E-S grade III-IV is a poor prognostic factor for HCC patients. Predicting poorly differentiated HCC has essential significance for clinical decision-making. Although some studies have developed predictive models based on magnetic resonance imaging (MRI) and radiomics, radiomic features that require specific software for analysis are impractical for clinical work. This study aims to develop a novel and user-friendly nomogram model to predict E-S grade III-IV.

Patients and Methods

Medical data on patients meeting the inclusion criteria were obtained from the Nanjing Drum Tower Hospital HCC database (January 2020 to December 2022). Univariate analysis was used to screen for risk factors associated with E-S grade III-IV. A novel nomogram was established based on the subsequent multivariate logistic regression analysis. The performance of the established model was evaluated through diagnostic ability, calibration, and clinical benefits.

Results

Overall, 240 HCC patients were included in this study. Among them, 103 were highly differentiated (E-S grade I-II) HCC and 137 were poorly differentiated (E-S grade III-IV) HCC. A nomogram model that integrated alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibodies (HCVAb), aspartate aminotransferase to lymphocyte ratio index (ALRI), and macrovascular invasion was established. The novel model had a good diagnostic performance with an area under the curve (AUC) value of 0.763. Meanwhile, the model had a diagnostic accuracy of 72.5%, a sensitivity of 78.1%, and a specificity of 65.1%. The calibration curve showed good calibration of the nomogram model (mean absolute error = 0.043), and the decision curve analysis (DCA) demonstrated that the clinical benefit was provided.

Conclusion

Our developed nomogram model could successfully predict E-S grade III-IV in HCC patients, which may be helpful in clinical decision-making.

The predictive value of PD-L1 expression in patients with advanced hepatocellular carcinoma treated with PD-1/PD-L1 inhibitors: A systematic review and meta-analysis

BACKGROUND AND AIM

Programmed death 1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors have transformed the treatment landscape of advanced hepatocellular carcinoma (HCC), but consistent responses are not observed in all patients, and prognostic biomarkers to guide treatment decisions are lacking. We aimed to evaluate the predictive value of PD-L1 expression in advanced HCC patients treated with PD-1/PD-L1 inhibitors.

METHODS

A comprehensive search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted. Studies comparing the objective response rate (ORR) and/or disease control rate (DCR) based on the tumor PD-L1 status of HCC were included.

RESULTS

Eleven studies with 1,330 HCC patients treated with PD-1/PD-L1 inhibitors were included. Pooled odds ratio (OR) analysis demonstrated a significantly improved ORR in PD-L1-positive patients compared with PD-L1-negative patients (OR, 1.86, 95% CI, 1.35-2.55). Similar results were observed in the anti-PD-1 treatment (p < 0.001) and anti-PD-1/PD-L1 monotherapy (p < 0.001) subgroups. The pooled ORRs in the PD-L1-positive and PD-L1-negative groups were 26% (95% CI, 20%-32%) and 18% (95% CI, 13%-22%), respectively. For DCR, the pooled OR analysis showed no significant difference between PD-L1-positive patients and PD-L1-negative patients (66% [95% CI, 55%-76%] vs. 69% [95% CI, 62%-76%]; OR, 0.92, 95% CI, 0.59-1.44). The results were consistent across the drug target and combination treatment subgroups.

CONCLUSION

Positive PD-L1 expression is associated with a better ORR in advanced HCC patients treated with anti-PD-1/PD-L1-based therapies. This feature can help to identify HCC patients who will benefit most from PD-1/PD-L1 inhibitors.

Clinical value of identifying genes that inhibit hepatocellular carcinomas

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the fourth most frequent cause of cancer-related death in the world. The most common histological type of liver cancer is hepatocellular carcinoma (HCC, 75-80%).

AREAS COVERED

Based on primary literature, this review provides an updated analysis of studies of genetic characterization of HCC at the level of gene mutation profiling, copy number alterations and gene expression, with definition of molecular subgroups and identification of some molecular biomarkers and therapeutic targets.

EXPERT OPINION

A detailed and comprehensive study of the genetic abnormalities characterizing different HCC subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of these tumors may provide a fundamental contribution to improve the survival of a subset of HCC patients. Immunotherapy represents a new fundamental strategy for the treatment of HCC.