Clinical and Molecular-Based Approach in the Evaluation of Hepatocellular Carcinoma Recurrence after Radical Liver Resection

Impact of inflammation and the immune system on hepatocellular carcinoma recurrence after hepatectomy

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Hepatectomy remains the first-line treatment for patients with resectable HCC. However, the reported recurrence rate of HCC at 5 years after surgery is between 50% and 70%. Tumor-related factors, including tumor size, number and differentiation, and underlying liver disease are well-known risk factors for recurrence after treatment. In addition to tumor-related factors, ever-increasing amounts of studies are finding that the tumor microenvironment also plays an important role in the recurrence of HCC, including systemic inflammatory response and immune regulation. Based on this, some inflammatory and immune markers were used in predicting postoperative cancer recurrence. These include neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, cytotoxic T cells, and regulatory T cells, among others. In this review, we summarized the inflammatory and immune markers that affect recurrence after HCC resection in order to provide direction for adjuvant therapy after HCC resection and ultimately achieve the goal of reducing recurrence.

Molecular Clues for Prediction of Hepatocellular Carcinoma Recurrence After Liver Transplantation

Recurrence after liver transplantation (LT) for hepatocellular carcinoma (HCC) is one of the commonest causes of cancer-related mortality. Thus, advances in the HCC molecular features have paid researchers great attention to identifying the different risk factors that could aid in liver cancer initiation and progression for earlier prediction of post-operative HCC recurrence risk. Our review has focused on the possible molecular onco-drivers' for HCC recurrence post-LT that may represent diagnostic/prognostic tools and scoring models for the proper selection of LT candidates with HCC.

Nomograms for Predicting Hepatocellular Carcinoma Recurrence and Overall Postoperative Patient Survival

Background

Few studies have focused on the prognosis of patients with hepatocellular carcinoma (HCC) of Barcelona Clinic Liver Cancer (BCLC) stage 0‒C in terms of early recurrence and 5-years overall survival (OS). We sought to develop nomograms for predicting 5-year OS and early recurrence after curative resection of HCC, based on a clinicopathological‒radiological model. We also investigated whether different treatment methods influenced the OS of patients with early recurrence.

Methods

Retrospective data, including clinical pathology, radiology, and follow-up data, were collected for 494 patients with HCC who underwent hepatectomy. Nomograms estimating OS and early recurrence were constructed using multivariate Cox regression analysis, based on the random survival forest (RSF) model. We evaluated the discrimination and calibration abilities of the nomograms using concordance indices (C-index), calibration curves, and Kaplan‒Meier curves. OS curves of different treatments for patients who had recurrence within 2 years after curative surgery were depicted and compared using the Kaplan–Meier method and the log-rank test.

Results

Multivariate Cox regression revealed that BCLC stage, non-smooth margin, maximum tumor diameter, age, aspartate aminotransferase levels, microvascular invasion, and differentiation were prognostic factors for OS and were incorporated into the nomogram with good predictive performance in the training (C-index: 0.787) and testing cohorts (C-index: 0.711). A nomogram for recurrence-free survival was also developed based on four prognostic factors (BCLC stage, non-smooth margin, maximum tumor diameter, and microvascular invasion) with good predictive performance in the training (C-index: 0.717) and testing cohorts (C-index: 0.701). In comparison to the BCLC staging system, the C-index (training cohort: 0.787 vs. 0.678, 0.717 vs. 0.675; external cohort 2: 0.748 vs. 0.624, 0.729 vs. 0.587 respectively, for OS and RFS; external cohort1:0.716 vs. 0.627 for RFS, all p value<0.05), and model calibration curves all showed improved performance. Patients who underwent surgery after tumor recurrence had a higher reOS than those who underwent comprehensive treatments and supportive care.

Conclusions

The nomogram, based on clinical, pathological, and radiological factors, demonstrated good accuracy in estimating OS and recurrence, which can guide follow-up and treatment of individual patients. Reoperation may be the best option for patients with recurrence in good condition.