Clinical implications and biological features of a novel postoperative recurrent HCC classification: A multi-centre study.

BACKGROUND & AIMS: The multiplicity of hepatocellular carcinoma (HCC) recurrence patterns is the most important determinant of patients' postsurgical survival. A systematic HCC recurrence classification is needed to help prevent and treat postoperative HCC recurrence in the era of precision medicine. METHODS: A total of 1319 patients with recurrent HCC from four hospitals were enrolled and divided into a development cohort (n = 916), internal validation cohort (n = 225) and external validation cohort (n = 178). A comprehensive study of patients' clinicopathological factors and biological features was conducted. RESULTS: Four subtypes of recurrence were identified, which integrated recurrence features, survival, effects on systemic and liver function and potential therapeutics after recurrence: type I (solitary-intrahepatic oligorecurrence); type II (multi-intrahepatic oligorecurrence); type III (progression recurrence) and type IV (hyper-progression recurrence). Type III~IV recurrence indicated exceptionally poor prognosis. Subsequently, two nomogram models were established for type III~IV recurrence prediction, and both demonstrated excellent predictive performance and applicability of pre and postoperative strategy formulation. Multiple biological analyses revealed that HCC cases with type III~IV recurrence were characterized by enrichment in p53 mutations, CCND1 amplification, high proliferation/metastasis potential, inactive metabolism and immune exhaustion features. Over-expression of high mobility group protein 2 (HMGA2) enhanced the highly malignant behaviour of HCC through multiple molecular pathways, making it a potential prognostic predictor and therapeutic target. CONCLUSIONS: This 'recurrent HCC classification' has important potential value in identifying patients with surgical benefit, predicting postsurgical survival and guiding treatment strategies. Multidimensional biological insights also increased knowledge of factors associated with HCC recurrence.

Nomograms for postsurgical extrahepatic recurrence prediction of hepatocellular carcinoma based on presurgical circulating tumor cell status and clinicopathological factors.

BACKGROUND AND AIMS: Extrahepatic recurrence (EHR) is one of the major reasons for the poor prognosis of hepatocellular carcinoma (HCC). The present study aimed to develop and assess the performance of predictive models by using a combination of presurgical circulating tumor cell (CTCs) data and clinicopathological features to screen patients at high risk of EHR to achieve precise decision-making. PATIENTS AND METHODS: A total of 227 patients with recurrent HCC and preoperative CTC data from January 2014 to August 2019 were enrolled. All patients were randomly assigned to one of two cohorts: development or validation. Two preoperative and postoperative nomogram models for EHR prediction were developed and multi-dimensionally validated. RESULTS: Patients with EHR had generally lower recurrence-free survival (p < 0.001), and overall survival (p < 0.001), and significantly higher CTC counts (epithelial CTCs, epithelial/mesenchymal hybrid CTCs, and mesenchymal CTCs count, all p < 0.05) than those without EHR. Univariate and multivariate analyses revealed that EHR was associated with four risk factors in the development cohort: total CTC count (p = 0.014), tumor size (p = 0.028), node number (p = 0.045), and microvascular invasion (p = 0.035). These factors were incorporated into two nomogram models (preoperative and postoperative), which reliably predicted EHR through multidimensional verification (e.g., calibration plot, receiver operating characteristic analysis, decision curve analysis, and clinical impact curve analysis) in the development and validation cohorts, respectively. With threshold of scores of 100.3 and 176.8 before and after surgery respectively, both nomograms were able to stratify patients into two distinct prognostic subgroups (all p < 0.05). CONCLUSION: The present study proposed two nomogram models integrating presurgical CTC counts and clinicopathological risks and showed relatively good predictive performance of EHR, which may be beneficial to the clinical practice of HCC recurrence. Further multicenter studies are needed to assess its general applicability.

Prognostic factors and an innovative nomogram model for patients with hepatocellular carcinoma treated with postoperative adjuvant transarterial chemoembolization.

PURPOSE: The purpose of this study was to estimate the clinical efficacy and identify the best beneficiaries of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in hepatocellular carcinoma (HCC). PATIENTS AND METHODS: A total of 749 HCC patients who underwent surgical resection (380 underwent PA-TACE, 369 had resection only) with a high risk of recurrence were reviewed retrospectively. Patients receiving PA-TACE were randomly split into development and validation cohorts. Univariate and multivariate analyses were performed in the development cohort. A novel model for PA-TACE-insensitivity prediction was built based on univariate and multivariate analysis and was multi-dimensionally validated in the validation set and all samples. RESULTS: After propensity score matching (PSM), in the early-recurrence group, no significant improvement in RFS was achieved with PA-TACE compared to radical hepatic resection alone. PA-TACE insensitive patients were considered as the PA-TACE non-benefit population and were associated with six clinicopathological factors: AFP, node number, tumor capsule, Ki-67 index, MVI, and complications in the development cohort. These factors were incorporated into a nomogram model, which reliably predicted PA-TACE insensitivity, with concordance indices of 0.874 and 0.897 for the development and validation cohort, respectively. In the overall sample, PA-TACE did not significantly improve patients' RFS and OS in the high-score group, while the low-score group had statistical significance. Recurrence pattern diversity was also found to be a factor leading to PA-TACE insensitivity. CONCLUSION: We constructed a new PA-TACE-insensitivity prediction model with potential clinical value. The good predictive performance and availability would allow this model to effectively screen PA-TACE beneficiaries.KEY MESSAGESThe independent influencing factors of PA-TACE insensitivity in patients who received PA-TACE were analyzed to construct a predictive model and its clinical application performance was verified with multi-dimensional methods.PA-TACE treatment should be avoided for patients with high scores according to this model, while it should be cautiously recommended for patients with low scores after multiple considerations.Compared with other related models, this model has obvious advantages in versatility and effectiveness. It can effectively screen the best benefit population of PA-TACE and provide a reliable reference for the selection of precise treatment plans for patients after radical resection of hepatocellular carcinoma.