Hepatocellular Carcinoma Recurrence-free Survival Research Articles

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

Risk of hepatocellular carcinoma after curative treatment when switching from tenofovir disoproxil fumarate or entecavir to tenofovir alafenamide: A real-world multicenter cohort study.

Antiviral treatment reduces the risk of developing hepatocellular carcinoma (HCC) in patients with chronic hepatitis B. However, there is a lack of high-quality evidence regarding the preventive effects of tenofovir alafenamide (TAF) on HCC. We evaluated the impact of TAF use after curative treatment on HCC recurrence. Patients who underwent surgery or radiofrequency ablation as a curative treatment for HCC were selected. Those patients who continued antiviral treatment with nucleos(t)ide analogs (NAs; entecavir [ETV] or tenofovir disoproxil fumarate [TDF]) or switched to TAF were included. The primary outcome was HCC recurrence, and the time-varying effect of NA use on HCC recurrence was analyzed using various statistical methods. Among 2794 consecutive patients with chronic hepatitis B who received curative treatment for HCC, 199 subsequently switched from ETV or TDF to TAF. After a median of 3.0years, 1303 patients (46.6%) experienced HCC recurrence. After propensity score matching (ratio 1:10), switching to TAF was not associated with an increased HCC recurrence (HR 1.00, 95% CI 0.68-1.47; p=1.00) by time-varying Cox analysis. Switching to TAF was not associated with HCC recurrence in subgroups of NA (HR 1.06, 95% CI 0.67-1.67; p=0.81 for TDF, and HR 1.09, 95% CI 0.51-2.33; p=0.82 for ETV). Kaplan-Meier analysis showed comparable HCC recurrence-free survival between patients who switched to TAF and those who continued with their NA (p=0.08). Time-varying Cox analyses in various subgroups confirmed the primary findings. TAF is as effective as TDF and ETV in preventing HCC recurrence after curative treatment.

Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma.

The metastatic vascular patterns of hepatocellular carcinoma (HCC) are mainly microvascular invasion (MVI) and vessels encapsulating tumor clusters (VETC). However, most existing VETC-related radiological studies still focus on the prediction of VETC status. This study aimed to build and compare VETC-MVI related models (clinical, radiomics, and deep learning) associated with recurrence-free survival of HCC patients. Retrospective. 398 HCC patients (349 male, 49 female; median age 51.7 years, and age range: 22-80 years) who underwent resection from five hospitals in China. The patients were randomly divided into training cohort (n = 358) and test cohort (n = 40). 3-T, pre-contrast T1-weighted imaging spoiled gradient recalled echo (T1WI SPGR), T2-weighted imaging fast spin echo (T2WI FSE), and contrast enhanced arterial phase (AP), delay phase (DP). Two radiologists performed the segmentation of HCC on T1WI, T2WI, AP, and DP images, from which radiomic features were extracted. The RFS related clinical characteristics (VETC, MVI, Barcelona stage, tumor maximum diameter, and alpha fetoprotein) and radiomic features were used to build the clinical model, clinical-radiomic (CR) nomogram, deep learning model. The follow-up process was done 1 month after resection, and every 3 months subsequently. The RFS was defined as the date of resection to the date of recurrence confirmed by radiology or the last follow-up. Patients were followed up until December 31, 2022. Univariate COX regression, least absolute shrinkage and selection operator (LASSO), Kaplan-Meier curves, log-rank test, C-index, and area under the curve (AUC). P < 0.05 was considered statistically significant. The C-index of deep learning model achieved 0.830 in test cohort compared with CR nomogram (0.731), radiomic signature (0.707), and clinical model (0.702). The average RFS of the overall patients was 26.77 months (range 1-80 months). MR deep learning model based on VETC and MVI provides a potential tool for survival assessment. 3 TECHNICAL EFFICACY: Stage 3.

AFP-L3 and DCP strongly predict early hepatocellular carcinoma recurrence after liver transplantation

Alpha-fetoprotein (AFP) predicts hepatocellular carcinoma (HCC) recurrence after liver transplant (LT) but remains an imperfect biomarker. The role of DCP (des-gamma-carboxyprothrombin) and AFP-L3 (AFP bound to Lens culinaris agglutinin) in predicting HCC recurrence remains incompletely characterized. AFP-L3 and DCP could identify patients at high risk of post-transplant HCC recurrence and serve as liver transplant exclusion criteria to defer transplant until patients receive additional risk-reducing pre-transplant locoregional therapy. This prospective cohort study included consecutive patients with HCC who underwent LT (within or down-staged to Milan criteria) between 2017 and 2022. Pre-transplant AFP, AFP-L3, and DCP measurements were obtained. The primary endpoint was the ability of biomarkers to predict HCC recurrence-free survival. This cohort included 285 patients with a median age of 67 (IQR 63-71). At LT, median biomarker values were AFP 5.0ng/ml (IQR 3.0-12.1), AFP-L3 6.7% (0.5-13.2), and DCP 1.0ng/ml (0.3-2.8). Most (94.7%) patients received pre-LT locoregional therapy. After a median post-LT follow-up of 3.1 years, HCC recurrence was observed in 18 (6.3%) patients. AFP-L3 and DCP outperformed AFP with C-statistics of 0.81 and 0.86 respectively, compared with 0.74 for AFP. A dual-biomarker combination of AFP-L3 ≥15% and DCP ≥7.5 predicted 61.1% of HCC recurrences, whereas HCC only recurred in 7 of 265 (2.6%) patients not meeting this threshold. The Kaplan-Meier recurrence-free survival rate at 3 years post-LT was 43.7% for patients with dual-positive biomarkers compared to 97.0% for all others (p <0.001). Dual-positivity for AFP-L3 ≥15% and DCP ≥7.5 strongly predicted post-LT HCC recurrence. This model could refine LT selection criteria and identify high-risk patients who require additional locoregional therapy prior to LT. Alpha-fetoprotein (AFP) is used to predict hepatocellular carcinoma (HCC) recurrence after liver transplant, but it remains an imperfect biomarker. In this prospective study, the biomarkers DCP (des-gamma-carboxyprothrombin) and AFP-L3 (AFP bound to Lens culinaris agglutinin) strongly predicted early HCC recurrence and outperformed AFP. A dual-biomarker combination of AFP-L3 ≥15% and DCP ≥7.5 predicted the majority of recurrences and could be used to further refine liver transplant eligibility criteria.

A radiomics-based model can predict recurrence-free survival of hepatocellular carcinoma after curative ablation

BackgroundPrediction of early recurrence (ER) of HCC after radical treatment is of great significance for follow-up and subsequent treatment, and there is a lot of unmet needs. Here, our goal is to develop and validate a radiomics nomogram that can predict ER after curative ablation. ObjectiveThe aim of this study was to evaluate the efficacy and safety of regorafenib after disease progression with sorafenib in Chinese patients with advanced HCC through this retrospective analysis. Methods149 HCC patients treated between November 2008 and February 2018 were enrolled and randomly divided into training cohort (n = 105) and validation cohort (n = 44). The survival endpoint was recurrence-free survival (RFS). A total of 16908 radiomics features were extracted from the contrast-enhanced MR images of each patient. The minimum redundancy maximum relevance algorithm (mRMR) and random survival forest (RSF) were used for feature selection. Twelve kinds of support vector machine (SVM) models, a Cox regression model (Cox PH), a random survival forest (RSF) model and a gradient boosting model (GBoost) were used to build a radiomics signature. These models were trained after adjusting the model parameters using 5-fold cross-validation. The best models were selected according to the C-index. ResultsUsing the machine learning (ML) framework, 40 features were identified that demonstrated good prediction of HCC recurrence across all cohorts. The random survival forest (RSF) model showed higher prognostic value, with a C-index of 0.733–0.801 and an integrated Brier score of 0.147–0.165, compared with other SVM models, Cox regression models, etc. (all P < 0.05). Time-dependent receiver operating characteristic (ROC) curve analysis, survival analysis, and decision curve analysis (DCA) were used to verify the performance of the RSF model in predicting tumor recurrence. ConclusionWe successfully built a radiomics-based RSF model with integrated radiomics and clinicopathological features that can potentially be used to predict ER after curative ablation in HCC patients.

211.3: Effect of Preoperative Adjuvant Therapy on the Efficacy of Hepatocellular Carcinoma With Portal Vein Tumor Thrombus After Liver Transplantation

Introduction: Hepatocellular carcinoma (HCC) had a high incidence of portal vein tumor thrombus (PVTT), and the occurrence of PVTT usually indicated a poor prognosis. In recent years, liver transplantation has been recommended as an alternative treatment for HCC with PVTT, however the efficacy is still controversial. Preoperative adjuvant therapy had a certain effect in hepatectomy for HCC with PVTT, but its role in liver transplantation has not been reported. Therefore, the purpose of this study is to explore the effect of preoperative adjuvant therapy on the efficacy of HCC with PVTT after liver transplantation. Methods: The clinical data of 22 patients with hepatocellular carcinoma with portal vein tumor thrombus (HCC + PVTT) undergoing liver transplantation from one center from 2010 to 2017 were analyzed retrospectively. 22 patients with hepatocellular carcinoma without portal vein tumor thrombus (HCC) were matched according to their age, tumor size and tumor number. The overall survival(OS) rate and recurrence-free survival(RFS) rate were compared between the two groups. At the same time, the OS and RFS of 22 patients with HCC+PVTT undergoing liver transplantation with preoperative adjuvant therapy and without preoperative adjuvant therapy were compared. Univariate and multivariate Cox regression analysis were used to explore the independent risk factors of recurrence. Results: The 1- and 3-year OS in HCC + PVTT group were 63.64% and 30.69%, respectively, which were significantly lower than HCC group (81.57% and 52.78%, P = 0.0391, respectively). The 1- and 3-year RFS in HCC + PVTT group were 51.71% and 40.22%, respectively, which were significantly lower than HCC group (74.46% and 68.73%, P = 0.0407). In HCC + PVTT group, the 1- and 3-year OS in preoperative adjuvant therapy group were 70% and 40%, respectively, higher than non preoperative adjuvant therapy group (58.33% and 16.67%, P = 0.179), and the 1- and 3-year RFS in preoperative adjuvant therapy group were 88.89% and 63.49%, respectively, which were significantly higher than non preoperative adjuvant therapy group (20.37% and 20.37%, P = 0.0336). Univariate and multivariate Cox regression analysis showed that preoperative adjuvant therapy was an independent factor affecting recurrence after liver transplantation in HCC + PVTT group (P = 0.010 and P = 0.023). Conclusion: This study was the first to explore the effect of preoperative adjuvant therapy on the efficacy of hepatocellular carcinoma with portal vein tumor thrombus after liver transplantation. In this study, the prognosis of patients with HCC + PVTT was poor. Preoperative adjuvant therapy can improve the prognosis of HCC + PVTT patients after liver transplantation and reduce the risk of recurrence. This study had certain clinical significance for exploring the preoperative treatment and operation timing of HCC with PVTT for liver transplantation. However, due to the small sample size of this study, which still need to be further verified by multi center large sample size research.

Liver transplantation in hepatocellular carcinoma – should we perform downstaging?

AimTo compare the long-term outcomes between liver transplant (LT) recipients with hepatocellular carcinoma (HCC) who were downstaged with transarterial-chemoembolization (TACE) to the Milan criteria (MC) and those initially meeting the MC.MethodsThis retrospective study enrolled 198 patients with HCC: 38 were downstaged and 160 patients initially met the MC. Post-LT survival and HCC recurrence-free survival were evaluated. We assessed the association of death and HCC recurrence with TACE, baseline (age, sex, disease etiology, Model of End-stage Liver Disease, tumor number and the sum of maximum tumor diameters, waiting time, alpha-fetoprotein level) and explant characteristics (tumor number and the sum of maximum tumor diameters, micro- and macrovascular invasion).ResultsThe recipient survival rates one, three, and five years after LT were 88.2%, 80.1%, and 75.9%, respectively. HCC recurrence-free probabilities were 92.3%, 87.9%, and 85%, respectively. The outcomes were comparable between the groups. In multivariate analysis, the number of tumors on the explant, age, and tumor recurrence were independent risk factors for death. Only the sum of maximum tumor diameters on the explant was an independent risk factor for HCC recurrence.ConclusionsPatients successfully downstaged with TACE to the MC can achieve post-LT recipient and HCC recurrence-free survival comparable with patients initially within the MC. Good response to TACE as a criterion for LT may be a method of selecting patients with favorable biological characteristics.

Application of circulating tumor DNA for prediction and surveillance of tumor recurrence after liver transplantation: A pilot study.

e16149 Background: Emerging data suggest that circulating tumor DNA (ctDNA) could detect minimal residual disease (MRD) and reflect tumor recurrence after radical resection in hepatocellular carcinoma (HCC). However, most reported ctDNA measurements are based on hotspot mutations and their predictive value in liver transplantation (LT) are still undetermined. We conducted a pilot study investigate ctDNA fingerprint as the detection marker of MRD in HCC patients undergoing LT. Methods: We enrolled 74 patients in HCC and monitored their ctDNA changes along the course of treatment at both pre- and post-operation by serial sampling of peripheral blood. All of the patents were treated by LT, and their ctDNA variations were used to assess the recurrence. We analyzed the correlation between ctDNA levels and recurrence-free survival (RFS) of the patients. Results: We monitored the ctDNA value of each patient before and after LT and found that the ctDNA-positive group was associated with higher recurrence rate (31.7% vs 11.5%), and has a shorter RFS than that of the ctDNA-negative group at baseline (preopreation) (HR, 3.25; CI 95% 1.18-8.97; p = 0.019). The conclusion also stands in patients at first timepoint follow-up after LT (postoperation) (recurrence rate, 46.2% vs 21.3%; HR, 4.26; CI 95% 1.62-11.2; p = 0.010). Moreover, changes of ctDNA were associated with RFS during the course after LT, both the ctDNA-decreased group and ctDNA-negative group have favorable clinical benefit than ctDNA-increased group. Conclusions: This study confirming the association between baseline levels of ctDNA and RFS in HCC undergoing LT. More importantly, it suggests the change of ctDNA level in plasma is a promising biomarker of MRD detection and patient prognosis in early HCC.

Development of nomogram models of inflammatory markers based on clinical database to predict prognosis for hepatocellular carcinoma after surgical resection

BackgroundInflammation plays a significant role in tumour development, progression, and metastasis. In this study, we focused on comparing the predictive potential of inflammatory markers for overall survival (OS), recurrence-free survival (RFS), and 1- and 2-year RFS in hepatocellular carcinoma (HCC) patients.MethodsA total of 360 HCC patients were included in this study. A LASSO regression analysis model was used for data dimensionality reduction and element selection. Univariate and multivariate Cox regression analyses were performed to identify the independent risk factors for HCC prognosis. Nomogram prediction models were established and decision curve analysis (DCA) was conducted to determine the clinical utility of the nomogram model.ResultsMultivariate Cox regression analysis indicated that the prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) were independent prognostic factors of OS, and aspartate aminotransferase-to-platelet ratio (APRI) was a common independent prognostic factor among RFS, 1-year RFS, and 2-year RFS. The systemic inflammation response index (SIRI) was an independent prognostic factor for 1-year RFS in HCC patients after curative resection. Nomograms established and achieved a better concordance index of 0.772(95% CI: 0.730-0.814), 0.774(95% CI: 0.734-0.815), 0.809(95% CI: 0.766-0.852), and 0.756(95% CI: 0.696-0.816) in predicting OS, RFS, 1-year RFS, and 2-year RFS respectively. The risk scores calculated by nomogram models divided HCC patients into high-, moderate- and low-risk groups (P < 0.05). DCA analysis revealed that the nomogram models could augment net benefits and exhibited a wider range of threshold probabilities in the prediction of HCC prognosis.ConclusionsThe nomograms showed high predictive accuracy for OS, RFS, 1-year RFS, and 2-year RFS in HCC patients after surgical resection. The nomograms could be useful clinical tools to guide a rational and personalized treatment approach and prognosis judgement.

MiR-500a-3p is a Potential Prognostic Biomarker in Hepatocellular Carcinoma.

PurposemiR-500a-3p has been extensively reported to be implicated in the development and progression in several human cancer types. This study aimed to investigate the diagnostic and prognostic significance of miR-500a-3p as a biomarker in hepatocellular carcinoma (HCC).MethodsmiR-500a-3p expression was evaluated by in situ hybridization (ISH) and real-time PCR in 10 adjacent normal tissues (ANT), 21 liver fibrosis tissues, and 110 HCC tissues. Statistical analysis was used to investigate the correlation of miR-500a-3p expression with clinicopathological features in HCC patients. Kaplan–Meier survival analysis was performed to evaluate the prognostic significance of miR-500a-3p in overall survival and recurrence-free survival in HCC patients.ResultsIn this study, we found that expression levels of miR-500a-3p were enhanced in HCC tissues. High miR-500a-3p levels were positively correlated with multiple clinicopathological features, including advanced clinical stage, distant metastatic status, increased AFP levels and poor tumor differentiation degree. More importantly, high miR-500a-3p levels predicted poor overall survival and early recurrence in HCC patients. Finally, a strong and positive correlation of miR-500a-3p mRNA expression with ISH staining scores was observed in clinical HCC tissues.ConclusionOur findings suggest that miR-500a-3p might be used as a novel biomarker to facilitate early diagnosis and predict prognosis in HCC patients.

What Is the Optimal Bridging Therapy for Patients with Hepatitis C-associated Hepatocellular Carcinoma Awaiting Liver Transplant? An Analysis of the United States HCC Liver Transplantation Consortium

Introduction: Patients with hepatitis C (HCV)-associated hepatocellular carcinoma (HCC) often receive bridging therapy in the form of liver-directed therapy (LDT) while awaiting liver transplant (LT). The optimal modality of LDT, with respect to both cancer outcomes and response to direct-acting antiviral (DAA) therapy, remains unknown. Methods: The United States HCC Liver Transplantation Consortium was queried for patients with primary HCV-associated HCC within Milan criteria who completed DAA therapy and underwent LT. Primary outcomes were HCC recurrence-free survival (RFS) and overall survival (OS). Secondary outcome was sustained virologic response (SVR) as indicator of efficacy of DAA therapy. Results: Of 857 patients, 753 met inclusion criteria. LDT consisted of radiofrequency ablation (RFA,13.3%,N=100), transarterial chemoembolization (TACE,44.1%,N=332), yttrium-90 (Y90,4.8%,N=36), and stereotactic body radiation therapy (SBRT,2.9%,N=22). Eighty-one(10.8%) patients received no LDT and 182(24.2%) received multiple modalities. SBRT patients had the highest 5-year RFS(100%) followed by those receiving TACE(94%), Y90(91.4%), RFA(89.9%), and multiple therapies(88.2%) (p=0.048, Figure 1A). OS was higher among patients who received SBRT, but not statistically significant (p=0.685, Figure 1B). SVR rate was lower among radiation-based therapy groups (Y90 73.5%, SBRT 78.9%, others≥88%; p=0.046). Conclusions: In a homogeneous population of HCV-associated HCC patients within Milan criteria who received bridging therapy while awaiting LT, SBRT was associated with increased RFS and trended towards increased OS. However, radiation-based therapy was associated with decreased efficacy of DAA as measured by lower SVR rates. The optimal choice of bridging therapy to liver transplant must balance oncologic and virologic outcomes, but these findings seem to favor SBRT.

An Integrated Fibrosis Signature for Predicting Survival and Immunotherapy Efficacy of Patients With Hepatocellular Carcinoma

Introduction: Fibrosis, a primary cause of hepatocellular carcinoma (HCC), is intimately associated with inflammation, the tumor microenvironment (TME), and multiple carcinogenic pathways. Currently, due to widespread inter- and intra-tumoral heterogeneity of HCC, the efficacy of immunotherapy is limited. Seeking a stable and novel tool to predict prognosis and immunotherapy response is imperative. Methods: Using stepwise Cox regression, least absolute shrinkage and selection operator (LASSO), and random survival forest algorithms, the fibrosis-associated signature (FAIS) was developed and further validated. Subsequently, comprehensive exploration was conducted to identify distinct genomic alterations, clinical features, biological functions, and immune landscapes of HCC patients. Results: The FAIS was an independent prognostic predictor of overall survival and recurrence-free survival in HCC. In parallel, the FAIS exhibited stable and accurate performance at predicting prognosis based on the evaluation of Kaplan–Meier survival curves, receiver operator characteristic curves, decision curve analysis, and Harrell’s C-index. Further investigation elucidated that the high-risk group presented an inferior prognosis with advanced clinical traits and a high mutation frequency of TP53, whereas the low-risk group was characterized by superior CD8+ T cell infiltration, a higher TIS score, and a lower TIDE score. Additionally, patients in the low-risk group might yield more benefits from immunotherapy. Conclusion: The FAIS was an excellent scoring system that could stratify HCC patients and might serve as a promising tool to guide surveillance, improve prognosis, and facilitate clinical management.

The Immunology of Hepatocellular Carcinoma.

Liver cancer is the third leading cause of cancer death worldwide. Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver. Liver resection or transplantation offer the only potentially curative options for HCC; however, many patients are not candidates for surgical resection, either due to presentation at advanced stages or poor liver function and portal hypertension. Liver transplantation is also limited to patients with certain characteristics, such as those that meet the Milan criteria (one tumor ≤ 5 cm, or up to three tumors no larger than 3 cm, along with the absence of gross vascular invasion or extrahepatic spread). Locoregional therapies, such as ablation (radiofrequency, ethanol, cryoablation, microwave), trans-arterial therapies like chemoembolization (TACE) or radioembolization (TARE), and external beam radiation therapy, have been used mainly as palliative measures with poor prognosis. Therefore, emerging novel systemic treatments, such as immunotherapy, have increasingly become popular. HCC is immunogenic, containing infiltrating tumor-specific T-cell lymphocytes and other immune cells. Immunotherapy may provide a more effective and discriminatory targeting of tumor cells through induction of a tumor-specific immune response in cancer cells and can improve post-surgical recurrence-free survival in HCC. We herein review evidence supporting different immunomodulating cell-based technology relative to cancer therapy in vaccines and targeted therapies, such as immune checkpoint inhibitors, in the management of hepatocellular carcinoma among patients with advanced disease.

A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma

BackgroundThe mechanistic basis for relapsed hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on the association between lncRNAs and HCC relapse.MethodsDifferentially expressed lncRNAs and mRNAs between a primary HCC group and relapsed HCC group were identified using the edge R package to analyze the GSE101432 dataset. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA–mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology (GO) enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and expression in the clinical samples was verified by qRT-PCR. Thereafter, we inputted the genes from the two groups into the HCC TNM stage and tumor grade database from TCGA. Finally, we performed Kaplan–Meier survival analysis on the lncRNAs related to relapsed HCC.ResultsIn this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to this. The GO terms in the yellow and black modules were related to cell proliferation, differentiation, and survival, as well as some transcription-related biological processes. Through qRT-PCR, we found that the expression levels of LINC00941 and LINC00668 in relapsed HCC were higher than those in primary HCC. Further, mRNA levels of LOX, OTX1, MICB, NDUFA4L2, BAIAP2L2, and KCTD17 were changed in relapsed HCC compared to levels in primary HCC. In addition, we verified that these genes could predict the overall survival and recurrence-free survival of HCC. Moreover, we found that LINC00668 and LINC00941 could affect tumor grade and TNM stages. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.ConclusionIn summary, we identified the key gene modules and central genes associated with relapsed HCC and constructed lncRNA–mRNA networks related to this. These genes are likely to have potential prognostic value for relapsed HCC and might shed new light on novel biomarkers or diagnostic targets for relapsed HCC.

Ablative Volume of Radiofrequency Ablation Related to Intrahepatic Recurrence-Free Survival of Hepatocellular Carcinoma

Abstract Purpose The aim of this study was to evaluate intrahepatic recurrence-free survival of hepatocellular carcinoma (HCC) after Radiofrequency ablation (RFA) Methods A retrospective cohort study of single HCC treated by RFA between 2015 and 2017. Fifty patients were enrolled in the study. Tumor volume and ablative volume were measured by using Syngo.via application (Siemen Healthineers, United States). Ablative volume classified into small and large ablative volumes. Ablative margin was evaluated by visual comparison between pre- and post-RFA images and classified into two groups: closed ablative margin (&lt;0.5cm) and large ablative margin (&gt;0.5 cm). The recurrence tumor was classified as local tumor progression (LTP) and intrahepatic distant recurrence (IDR). The recurrence-free survival rate and independent risk for tumor recurrence were analyzed. Results Recurrence-free survival rate at the first, second, third, and fourth year after RFA was 83, 56, 44, and 44%, respectively. The average recurrence-free survival time in large ablative volume group was significantly longer than small ablative volume group (31.57 vs. 8.50 months, p = 0.003). A significant independent risk factor for tumor recurrence was large ablative volume (hazard ratio = 0.12, 95% confidence interval = 0.02–0.84, p = 0.033). The IDR group had ratio of actual ablative volume by ideal ablative volume (ablative ratio) higher than LTP group and nonrecurrent group. Conclusion The large ablative volume prevented tumor recurrence and increased recurrence-free survival rate. But aggressive ablation with high ablative volume ratio could increase risk of IDR.

Sarcopenia and visceral adiposity predict poor overall survival in hepatocellular carcinoma patients after curative hepatic resection.

BackgroundThis study investigated the association of 3 components of body composition (sarcopenia, intramuscular fat deposition and visceral adiposity) with the overall or recurrence-free survival of hepatocellular carcinoma (HCC) patients who underwent curative hepatic resection.MethodsOne hundred sixty newly diagnosed and surgically treated HCC patients were retrospectively enrolled from 2003 to 2011. Three items of body composition were measured using the 3rd lumbar level image of preoperative computed tomography (CT): psoas muscle index (PMI), psoas muscle attenuation (PMA), and visceral adipose tissue index (VATI). Sex-specific optimal cut-off for each item was determined from receiver-operating characteristic curves.ResultsThe HCC patients showed a median age of 55 years, 75% of male, 78% of hepatitis B surface antigen positivity, and 96% of Child-Pugh A. The sarcopenic group (PMI less than the sex-specific cutoff of 3.33 cm2/m2 for men and 2.38 cm2/m2 for women) had 17.5% of the patients with a lower PMA (more fat deposition) but similar VATI compared to the non-sarcopenic group. PMI showed a positive correlation with PMA (ρ=0.493, P<0.001), while there was no significant correlation between PMI and VATI, and between PMA and VATI. On the multivariate analysis, a high PMI and low VATI were independent factors affecting overall survival while PMA was not. Nevertheless, PMI and VATI were not independent factors for recurrence-free survival.ConclusionsIn curatively resected HCC patients, sarcopenia and high visceral adiposity predict poor overall survival but not recurrence-free survival, while PMA did not predict overall survival.

Letter to the Editor: Protein Disulfide Isomerase Family A Member 3 Pseudogene 1 Level Could Predict Recurrence‐Free Survival in Hepatocellular Carcinoma: Reliable?

With great interest, I carefully read with the work(1) by Xie et al. in a recent issue of Hepatology. The authors revealed that higher PDIA3P1 level was related to poorer recurrence-free survival (RFS) in hepatocellular carcinoma (HCC), considering PDIA3P1 as a predictor for shorter RFS. However, the association between PDIA3P1 and RFS in HCC should be interpreted cautiously in consideration of the following comments.

HCC recurrence in HCV-infected patients after liver transplantation: SiLVER Study reveals benefits of sirolimus in combination with CNIs - a post-hoc analysis.

Factors affecting outcomes in liver transplant (LTx) recipients with hepatocellular carcinoma (HCC) and hepatitis C viral (HCV) infection include the choice of immunosuppression. Here, we analyzed the HCV+ subgroup of patients from the randomized controlled, international SiLVER Study. We performed a post hoc analysis of 166 HCV+ SiLVER Study patients regarding HCC outcome after LTx. Control patients (group A: n=88) received mTOR inhibitor (mTORi)-free, calcineurin inhibitor (CNI)-based versus sirolimus-based immunosuppression (group B: n=78). We found no significant difference regarding HCV-RNA titers between group A and B. Since no effect in group B could be due to variable sirolimus dosing, we split group B into patients receiving sirolimus-based immunosuppression+CNIs for >50% (B1; n=44) or <50% (B2; n=34) of the time. While there remained no difference in HCV-RNA titer between groups, HCC recurrence-free survival in group B1 (81.8%) was markedly better versus both group A (62.7%; P=0.0136) and group B2 (64.7%; P=0.0326); Interestingly, further subgroup analysis revealed an increase (P=0.0012) in liver enzyme values in group B2. Taken together, in HCV-infected patients with HCC and LTx, mTORi immunosuppression+CNIs yields excellent outcomes. Unexpectedly, higher levels of liver inflammation and poorer outcomes occur with mTORi monotherapy in the HCV+ subgroup.

Diagnostic and prognostic value of WNT family gene expression in hepatitis B virus‑related hepatocellular carcinoma

The aim of the present study was to investigate the diagnostic and prognostic value of Wingless-type MMTV integration site (WNT) gene family expression in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). The clinical data of the patients and gene expression levels were downloaded from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Receiver operating characteristic curve analysis was used to investigate the diagnostic value of WNT genes. Cox proportional hazard regression analysis and Kaplan-Meier survival analysis were performed to evaluate the association of WNT gene expression level with overall survival (OS) and recurrence-free survival (RFS). A nomogram was constructed for the prediction of prognosis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Diagnostic receiver operating characteristic curve analysis suggested that WNT2 had a high diagnostic value, with an area under the curve (AUC) of >0.800 (P<0.0001, AUC=0.810, 95% CI: 0.767–0.852). Survival analysis indicated that the expression level of WNT1 was significantly associated with OS and RFS (adjusted P=0.033, adjusted HR=0.607, 95% CI: 0.384–0.960; and adjusted P=0.007, adjusted HR=0.592, 95% CI: 0.404–0.868, respectively). In the TCGA validation cohort, we also observed that WNT2 was significantly differentially expressed between HCC tissues and adjacent non-tumor tissues, and WNT1 was associated with both the OS and RFS of HCC. Therefore, through the GSE14520 HBV-related HCC cohort we concluded that WNT2 may serve as a diagnostic biomarker and WNT1 may serve as a prognostic biomarker. These results may also be extended to TCGA HCC verification cohort.

Abstract 1633: Pretreatment prediction of recurrence-free survival in hepatocellular carcinoma after surgical resection by machine-learning based imaging analysis

Abstract In hepatocellular carcinoma (HCC), patients at early stages are recommended to accept surgical resection as primary treatment by internationally endorsed guidelines. Nevertheless, post-surgical recurrence is one of the main threats that lead to death, with 5-year recurrence rate of over 70%. How to select patients at high risk of recurrence is essential to guide systematic follow-up and provide basis for alternative treatment strategy making, thus to prolong overall survival. In this study, we aimed to predict recurrence free survival (RFS) for HCC patients undergoing surgical resection using MR-based radiomics analysis. A cohort of 176 patients diagnosed with HCC was enrolled with complete recurrence follow-ups. A total of 4404 radiomic features including shape and size, intensity, textural, and wavelet features were extracted on the segmented tumor lesion. Mutual correlation among the features were initially assessed to reduce redundant features by Pearson’s correlation analysis. Lasso-cox regression modeling was further applied to select recurrence-related key features and generate the radiomics signature with 10-fold cross validation. In addition, we explored the predictive ability of conventional clinical factors as comparable predictors with radiomics signature by univariate analysis and constructed clinical model by cox proportional hazard regression modeling. The result turned out that 4 T2WI-based radiomic features were identified as most correlated predictors for the recurrence prediction modeling, which were correspondingly gabor10_glszm_SZLGE, gabor12_glcm45_cluster_prominence, W5L5_fos_kurtosis, and W5E5_fos_skewness. The radiomics signature could successfully stratify patients into high-risk and low-risk groups with p-value &amp;lt; 0.001 and of 0.019 in the training and validation cohorts, respectively, by log-rank test. The radiomics-based model yielded C-indexes of 0.761 and 0.719 in the training and validation cohorts, respectively for RFS prediction. Venous invasion and AFP were selected as effective clinical predictors. The clinical model presented with C-index of 0.551 and 0.583 in the training and validation cohorts, respectively for RFS prediction. When adding clinical predictors into radiomics model, it did not show significant improvement for the prediction with Delong-test p-value &amp;gt; 0.05 in both training and validation cohorts. Our study revealed T2WI-based archetypal radiomic features related with RFS and highlighted the radiomics model as an effective noninvasive tool for RFS pretreatment prediction in HCC after surgical resection, which would beyond doubt provide reliable basis for individualized treatment decision making in HCC management. Citation Format: Jingwei Wei, Yuqi Han, Xia Wu, Yushen Jin, Jie Tian. Pretreatment prediction of recurrence-free survival in hepatocellular carcinoma after surgical resection by machine-learning based imaging analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1633.