Early detection and prognosis evaluation for hepatocellular carcinoma by circulating tumour DNA methylation: A multicentre cohort study.

BACKGROUND: Early diagnosis of hepatocellular carcinoma (HCC) can significantly improve patient survival. We aimed to develop a blood-based assay to aid in the diagnosis, detection and prognostic evaluation of HCC. METHODS: A three-phase multicentre study was conducted to screen, optimise and validate HCC-specific differentially methylated regions (DMRs) using next-generation sequencing and quantitative methylation-specific PCR (qMSP). RESULTS: Genome-wide methylation profiling was conducted to identify DMRs distinguishing HCC tumours from peritumoural tissues and healthy plasmas. The twenty most effective DMRs were verified and incorporated into a multilocus qMSP assay (HepaAiQ). The HepaAiQ model was trained to separate 293 HCC patients (Barcelona Clinic Liver Cancer (BCLC) stage 0/A, 224) from 266 controls including chronic hepatitis B (CHB) or liver cirrhosis (LC) (CHB/LC, 96), benign hepatic lesions (BHL, 23), and healthy controls (HC, 147). The model achieved an area under the curve (AUC) of 0.944 with a sensitivity of 86.0% in HCC and a specificity of 92.1% in controls. Blind validation of the HepaAiQ model in a cohort of 523 participants resulted in an AUC of 0.940 with a sensitivity of 84.4% in 205 HCC cases (BCLC stage 0/A, 167) and a specificity of 90.3% in 318 controls (CHB/LC, 100; BHL, 102; HC, 116). When evaluated in an independent test set, the HepaAiQ model exhibited a sensitivity of 70.8% in 65 HCC patients at BCLC stage 0/A and a specificity of 89.5% in 124 patients with CHB/LC. Moreover, HepaAiQ model was assessed in paired pre- and postoperative plasma samples from 103 HCC patients and correlated with 2-year patient outcomes. Patients with high postoperative HepaAiQ score showed a higher recurrence risk (Hazard ratio, 3.33, p < .001). CONCLUSIONS: HepaAiQ, a noninvasive qMSP assay, was developed to accurately measure HCC-specific DMRs and shows great potential for the diagnosis, detection and prognosis of HCC, benefiting at-risk populations.

Serial circulating tumor DNA profiling predicts tumor recurrence after liver transplantation for liver cancer.

BACKGROUND: Minimal residual disease (MRD) is proposed to be responsible for tumor recurrence. The role of circulating tumor DNA (ctDNA) to detect MRD, monitor recurrence, and predict prognosis in liver cancer patients undergoing liver transplantation (LT) remains unrevealed. METHODS: Serial blood samples were collected to profile ctDNA mutational changes. Baseline ctDNA mutational profiles were compared with those of matched tumor tissues. Correlations between ctDNA status and recurrence rate (RR) and recurrence-free survival (RFS) were analyzed, respectively. Dynamic change of ctDNA was monitored to predict tumor recurrence. RESULTS: Baseline mutational profiles of ctDNA were highly concordant with those of tumor tissues (median, 89.85%; range 46.2-100%) in the 74 patients. Before LT, positive ctDNA status was associated with higher RR (31.7% vs 11.5%; p = 0.001) and shorter RFS than negative ctDNA status (17.8 vs 19.4 months; p = 0.019). After LT, the percentage of ctDNA positivity decreased (17.6% vs 47.0%; p < 0.001) and patients with positive ctDNA status had higher RR (46.2% vs 21.3%; p < 0.001) and shorter RFS (17.2 vs 19.2 months; p = 0.010). Serial ctDNA profiling demonstrated patients with decreased or constant negative ctDNA status had lower RR (33.3% vs 50.0%; p = 0.015) and favorable RFS (18.2 vs 15.0 months, p = 0.003) than those with increased or constant positive ctDNA status. Serial ctDNA profiling predicted recurrence months ahead of imaging evidence and serum tumor biomarkers. CONCLUSIONS: ctDNA could effectively detect MRD and predict tumor recurrence in liver cancer patients undergone LT.

Prognosis of spontaneously ruptured hepatocellular carcinoma: a propensity score matching study.

PURPOSE: Spontaneous rupture is a fatal complication of hepatocellular carcinoma (HCC). This study compared the prognosis of spontaneously ruptured HCC (srHCC) with that of non-ruptured HCC (nrHCC). METHODS: A total of 185 srHCC patients and 1085 nrHCC patients treated by hepatectomy between February 2005 and December 2017 at Zhongshan Hospital were retrospectively reviewed and enrolled. The overall survival (OS) and time to recurrence (TTR) were evaluated. A 1:2 propensity score matching (PSM) analysis was performed using the nearest neighbor matching with a caliper of 0.2. RESULTS: Before PSM, patients with srHCC who underwent hepatectomy (n = 185) had a poorer prognosis than those with nrHCC (n = 1085; 5-year OS, 39.1% vs 59.2%, P < 0.001; 5-year TTR, 83.8% vs 54.9%, P < 0.001). After PSM, patients with srHCC (n = 156) had higher 5-year TTR (83.2% vs 69.0%, P < 0.001) but comparable 5-year OS with those with nrHCC (n = 312, 44.0% vs 46.0%, P = 0.600). Univariate and multivariate analyses demonstrated spontaneous rupture as an independent risk factor for TTR (hazard ratio [HR], 1.681; 95% confidence interval [CI] 1.326-2.132; P < 0.001), but not for OS (HR: 1.074; 95% CI 0.823-1.401; P = 0.600). Further analysis revealed that srHCC was not appropriate to be assigned as T4 stage in American Joint Committee on Cancer classification. CONCLUSION: Spontaneous rupture of HCC is not a risk factor for survival. If resected eventually, srHCC may achieve comparable survival with nrHCC.

Circulating immune index predicting the prognosis of patients with hepatocellular carcinoma treated with lenvatinib and immunotherapy.

Background: Immune checkpoint inhibitor (ICI)-based combination therapy has opened a new avenue for the treatment of multiple malignancies including hepatocellular carcinoma (HCC). However, considering the unsatisfactory efficacy, biomarkers are urgently needed to identify the patients most likely to benefit from ICI-based combination therapy. Methods: A total of 194 patients undergoing ICI-based combination therapy for unresectable HCC were retrospectively enrolled and divided into a training cohort (n = 129) and a validation cohort (n = 65) randomly. A novel circulating immune index (CII) defined as the ratio of white blood cell count (×109/L) to lymphocyte proportion (%) was constructed and its prognostic value was determined and validated. Results: Patients with CII ≤ 43.1 reported prolonged overall survival (OS) compared to those with CII > 43.1 (median OS: 24.7 vs 15.1 months; 6-, 12-, 18-month OS: 94.2%, 76.7%, 66.1% vs 86.4%, 68.2%, 22.8%, P = 0.019), and CII was identified as an independent prognostic factor for OS (hazard ratio, 2.24; 95% confidence interval, 1.17-4.31; P = 0.015). These results were subsequently verified in the validation cohort. Additionally, patients with low CII levels had improved best radiological tumor response (complete response, partial response, stable disease, progressive disease: 3%, 36%, 50%, 11% vs 0%, 27%, 46%, 27%; P = 0.037) and disease control rate (89% vs 73%; P = 0.031) in the pooled cohort and better pathologic response (pathologic complete response, major pathologic response, partial pathologic response, no pathologic response: 20%, 44%, 28%, 8% vs 0%, 0%, 40%, 60%; P = 0.005) in the neoadjuvant cohort. Detection of lymphocyte subsets revealed that an elevated proportion of CD4+ T cells was related to better OS, while the proportion of CD8+ T cells was not. Conclusions: We constructed a novel circulating immune biomarker that was capable of predicting OS and therapeutic efficacy for HCC patients undergoing ICI and lenvatinib combination therapy.

Prognostic model for predicting outcome and guiding treatment decision for unresectable hepatocellular carcinoma treated with lenvatinib monotherapy or lenvatinib plus immunotherapy.

Background: Lenvatinib monotherapy and combination therapy with immune checkpoint inhibitors (ICI) were widely applied for unresectable hepatocellular carcinoma (uHCC). However, many patients failed to benefit from the treatments. A prognostic model was needed to predict the treatment outcomes and guide clinical decisions. Methods: 304 patients receiving lenvatinib monotherapy or lenvatinib plus ICI for uHCC were retrospectively included. The risk factors derived from the multivariate analysis were used to construct the predictive model. The C-index and area under the receiver-operating characteristic curve (AUC) were calculated to assess the predictive efficiency. Results: Multivariate analysis revealed that protein induced by vitamin K absence or antagonist-II (PIVKA-II) (HR, 2.05; P=0.001) and metastasis (HR, 2.07; P<0.001) were independent risk factors of overall survival (OS) in the training cohort. Herein, we constructed a prognostic model called PIMET score and stratified patients into the PIMET-low group (without metastasis and PIVKA-II<600 mAU/mL), PIMET-int group (with metastasis or PIVKA-II>600 mAU/mL) and PIMET-high group (with metastasis and PIVKA-II>600 mAU/mL). The C-index of PIMET score for the survival prediction was 0.63 and 0.67 in the training and validation cohort, respectively. In the training cohort, the AUC of 12-, 18-, and 24-month OS was 0.661, 0.682, and 0.744, respectively. The prognostic performances of the model were subsequently validated. The AUC of 12-, 18-, and 24-month OS was 0.724, 0.726, and 0.762 in the validation cohort. Subgroup analyses showed consistent predictive value for patients receiving lenvatinib monotherapy and patients receiving lenvatinib plus ICI. The PIMET score could also distinguish patients with different treatment responses. Notably, the combination of lenvatinib and ICI conferred survival benefits to patients with PIMET-int or PIMET-high, instead of patients with PIMET-low. Conclusion: The PIMET score comprising metastasis and PIVKA-II could serve as a helpful prognostic model for uHCC receiving lenvatinib monotherapy or lenvatinib plus ICI. The PIMET score could guide the treatment decision and facilitate precision medicine for uHCC patients.

Efficacy and safety of lenvatinib for preventing tumor recurrence after liver transplantation in hepatocellular carcinoma beyond the Milan criteria.

Background: Lenvatinib is one of the first-line treatments for unresectable hepatocellular carcinoma (HCC). However, data are lacking on lenvatinib in the postoperative setting. Methods: This retrospective analysis enrolled 242 patients with HCC who underwent liver transplantation (LTx). Eligible patients were divided into 2 groups according to their use of adjuvant lenvatinib following LTx (lenvatinib, n=42; control, n=200). The primary outcome measures were overall survival (OS), time to recurrence (TTR), and safety. Kaplan-Meier analysis was applied to calculate the OS, while a competing risk model was used to estimate the cumulative incidence of recurrence. Results: The lenvatinib group showed more advanced tumors and a higher proportion of HCC beyond the Milan criteria (P<0.001) than the control group. There were no significant differences in both the OS and TTR between the 2 groups. After focusing on the patients with HCC beyond the Milan criteria, baseline characteristics were similar in the lenvatinib group (n=38) and the control group (n=102). Competing risk analysis showed lenvatinib significantly prolonged TTR after LTx versus the control group [sub-hazard ratio (sHR), 0.40; 95% confidence interval (CI): 0.17 to 0.93; P=0.031]. In the multivariate competing risk model, adjuvant lenvatinib was an independent protective factor for tumor recurrence after LTx in patients with HCC beyond the Milan criteria (sHR, 0.33; 95% CI: 0.13 to 0.83; P=0.018). The rate of early recurrence within t2 years after LTx was also significantly decreased in the lenvatinib group (15.8% vs. 33.3%, P=0.041). However, the lenvatinib group exhibited comparable OS with the control group in patients with HCC beyond the Milan criteria. Treatment-related adverse events (TRAEs) and Grade ≥3 TRAEs occurred in 40 (95.2%) and 13 (31%) patients who received adjuvant lenvatinib, respectively. No treatment-related death was reported. Conclusions: Postoperative lenvatinib administration may provide clinical benefits and is well tolerated in patients with HCC beyond the Milan criteria who undergo LTx.

Metagenomic Next-Generation Sequencing Versus Traditional Laboratory Methods for the Diagnosis and Treatment of Infection in Liver Transplantation.

Background: Metagenomic next-generation sequencing (mNGS) has emerged as an effective method for the noninvasive and precise detection of infectious pathogens. However, data are lacking on whether mNGS analyses could be used for the diagnosis and treatment of infection during the perioperative period in patients undergoing liver transplantation (LT). Methods: From February 2018 to October 2018, we conducted an exploratory study using mNGS and traditional laboratory methods (TMs), including culture, serologic assays, and nucleic acid testing, for pathogen detection in 42 pairs of cadaveric liver donors and their corresponding recipients. Method performance in determining the presence of perioperative infection and guiding subsequent clinical decisions was compared between mNGS and TMs. Results: The percentage of liver donors with mNGS-positive pathogen results (64.3%, 27/42) was significantly higher than that using TMs (28.6%, 12/42; P<0.05). The percentage of co-infection detected by mNGS in liver donors was 23.8% (10/42) significantly higher than 0.0% (0/42) by TMs (P<0.01). Forty-three pathogens were detected using mNGS, while only 12 pathogens were identified using TMs. The results of the mNGS analyses were consistent with results of the TM analyses in 91.7% (11/12) of donor samples at the species level, while mNGS could be used to detect pathogens in 66.7% (20/30) of donors deemed pathogen-negative using TMs. Identical pathogens were detected in 6 cases of donors and recipients by mNGS, among which 4 cases were finally confirmed as donor-derived infections (DDIs). For TMs, identical pathogens were detected in only 2 cases. Furthermore, 8 recipients developed early symptoms of infection (<7 days) after LT; we adjusted the type of antibiotics and/or discontinued immunosuppressants according to the mNGS results. Of the 8 patients with infections, 7 recipients recovered, and 1 patient died of severe sepsis. Conclusions: Our preliminary results show that mNGS analyses can provide rapid and precise pathogen detection compared with TMs in a variety of clinical samples from patients undergoing LT. Combined with symptoms of clinical infection, mNGS showed superior advantages over TMs for the early identification and assistance in clinical decision-making for DDIs. mNGS results were critical for the management of perioperative infection in patients undergoing LT.

Integration of Inflammation-Immune Factors to Build Prognostic Model Predictive of Prognosis and Minimal Residual Disease for Hepatocellular Carcinoma.

Background: Tumor recurrence after hepatectomy is high for hepatocellular carcinoma (HCC), and minimal residual disease (MRD) could be the underlying mechanism. A predictive model for recurrence and presence of MRD is needed. Methods: Common inflammation-immune factors were reviewed and selected to construct novel models. The model consisting of preoperative aspartate aminotransferase, C-reactive protein, and lymphocyte count, named ACLR, was selected and evaluated for clinical significance. Results: Among the nine novel inflammation-immune models, ACLR showed the highest accuracy for overall survival (OS) and time to recurrence (TTR). At the optimal cutoff value of 80, patients with high ACLR (> 80) had larger tumor size, higher Edmondson's grade, more vascular invasion, advanced tumor stage, and poorer survival than those with low ACLR (≤ 80) in the training cohort (5-year OS: 43.3% vs. 80.1%, P < 0.0001; 5-year TTR: 74.9% vs. 45.3%, P < 0.0001). Multivariate Cox analysis identified ACLR as an independent risk factor for OS [hazard ratio (HR) = 2.22, P < 0.001] and TTR (HR = 2.36, P < 0.001). Such clinical significance and prognostic value were verified in validation cohort. ACLR outperformed extant models, showing the highest area under receiver operating characteristics curve for 1-, 3-, and 5-year OS (0.737, 0.719, and 0.708) and 1-, 3-, and 5-year TTR (0.696, 0.650, and 0.629). High ACLR correlated with early recurrence (P < 0.001) and extremely early recurrence (P < 0.001). In patients with high ACLR, wide resection margin might confer survival benefit by decreasing recurrence (median TTR, 25.5 vs. 11.4 months; P = 0.037). Conclusions: The novel inflammation-immune model, ACLR, could effectively predict prognosis, and the presence of MRD before hepatectomy and might guide the decision on resection margin for patients with HCC.

The treatment strategy and outcome for spontaneously ruptured hepatocellular carcinoma: a single-center experience in 239 patients.

PURPOSE: There exist no treatment guidelines for spontaneously ruptured hepatocellular carcinoma (srHCC) and its prognosis remains controversial. METHODS: Patients were retrospectively enrolled and grouped based on hemodynamics and tumor resectability. The 30-day mortality, 5-year overall survival (OS), progression-free survival (PFS), peritoneal metastasis (PM) and intrahepatic metastasis (IM) rates were compared. RESULTS: In general, 239 patients were classified into four groups: patients with stable hemodynamics underwent semi-elective hepatectomy (n = 119), and those with unstable hemodynamics received emergent hepatectomy (n = 17), sequential hemostatic-transcatheter arterial chemoembolization (TACE)/-laparotomy with late hepatectomy (n = 49), or TACE only (n = 54). Hepatectomy was safer and provided better OS and PFS than TACE both before and after propensity score matching. Emergent hepatectomy was associated with higher 30-day mortality (6.2%, P < 0.05) and poorer prognosis whereas semi-elective hepatectomy and sequential treatment had comparable mortality (both 0%) and survival (36.3% vs 45.2%, P > 0.05). Compared with hemostatic TACE in the sequential treatment group, early surgical intervention (semi-elective hepatectomy, emergent hepatectomy, and sequential laparotomy with late hepatectomy) decreased PM (13.6% vs 34.2%, P = 0.003) whereas had higher IM (68.0% vs 50.0%, P = 0.039), but neither procedure had affected OS. In srHCC patients with high risk of recurrence (multiple tumors, micro- and macro-vascular invasion), postoperative adjuvant TACE improved OS. CONCLUSION: Hepatectomy could provide better prognosis than TACE for srHCC patients while semi-elective hepatectomy and sequential hemostatic-TACE with staged hepatectomy are viable options for srHCCs with stable and unstable hemodynamics, respectively.

Development of an Eight-gene Prognostic Model for Overall Survival Prediction in Patients with Hepatocellular Carcinoma.

BACKGROUND AND AIMS: The overall survival (OS) of hepatocellular carcinoma (HCC) remains dismal. Bioinformatic analysis of transcriptome data could identify patients with poor OS and may facilitate clinical decision. This study aimed to develop a prognostic gene model for HCC. METHODS: GSE14520 was retrieved as a training set to identify differential expressed genes (DEGs) between tumor and adjacent liver tissues in HCC patients with different OS. A DEG-based prognostic model was then constructed and the TCGA-LIHC and ICGC-LIRI datasets were used to validate the model. The area under the receiver operating characteristic curve (AUC) and hazard ratio (HR) of the model for OS were calculated. A model-based nomogram was established and verified. RESULTS: In the training set, differential expression analysis identified 80 genes dysregulated in oxidation-reduction and metabolism regulation. After univariate Cox and LASSO regression, eight genes (LPCAT1, DHRS1, SORBS2, ALDH5A1, SULT1C2, SPP1, HEY1 and GOLM1) were selected to build the prognostic model. The AUC for 1-, 3- and 5-year OS were 0.779, 0.736, 0.754 in training set and 0.693, 0.689, 0.693 in the TCGA-LIHC validation set, respectively. The AUC for 1- and 3-year OS were 0.767 and 0.705 in the ICGC-LIRI validation set. Multivariate analysis confirmed the model was an independent prognostic factor (training set: HR=4.422, p<0.001; TCGA-LIHC validation set: HR=2.561, p<0.001; ICGC-LIRI validation set: HR=3.931, p<0.001). Furthermore, a nomogram combining the model and AJCC stage was established and validated, showing increased OS predictive efficacy compared with the prognostic model (p=0.035) or AJCC stage (p<0.001). CONCLUSIONS: Our eight-gene prognostic model and the related nomogram represent as reliable prognostic tools for OS prediction in HCC patients.

Plasma MicroRNA Panel Predicts Early Tumor Recurrence in Patients with Hepatocellular Carcinoma after Liver Transplantation.

Background: This study aimed to evaluate the role of plasma microRNA panel (miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801) for prediction and surveillance of early tumor recurrence in hepatocellular carcinoma (HCC) patients who had undergone liver transplantation (LT). Methods: The expression of plasma microRNA panel was assayed in 193 HCC patients (training cohort, n =151; validation cohort, n = 42). Sensitivity and specificity for detecting post-transplant HCC recurrence, and the relationship of microRNA panel expression with clinical characteristics were analyzed accordingly. The prognostic value of microRNA panel was compared with that of AFP (alpha-fetoprotein) and DCP (Des-gamma-carboxyprothrombin). Cox regression analyses were used to evaluate independent prognostic factors. Results: In the training cohort, the rate of positive plasma microRNA panel status at 7-14 days after LT (late phase; 44.2%) decreased than that before (76.2%, P < 0.001) and 1-6 days after LT (early phase; 78.5%, P < 0.001). At late phase, positive microRNA panel status correlated with higher early tumor recurrence rate (one year after LT) than negative status (45.9% vs 10.7%; P < 0.001). Patients with persistent positive microRNA panel status both before and after LT had the highest early tumor recurrence rate in this cohort (54.9%, P < 0.001). The results were consistent in the validation cohort. Cox regression analysis found that positive plasma microRNA panel status at late phase was the only independent risk factor for early recurrence (HR: 4.903, 95% CI = 2.195 - 10.951; P < 0.001). Dynamic monitoring demonstrated plasma microRNA panel status changed from negative to positive earlier than AFP and DCP upon recurrence, and the median time between positivity of plasma microRNA and imaging evidence of recurrence was 2.4 (0.5-10.0) months. Conclusions: Plasma microRNA panel could be a noninvasive biomarker for prediction and surveillance of early tumor recurrence in HCC patients who have undergone LT.

A novel preoperative predictive model of 90-day mortality after liver resection for huge hepatocellular carcinoma.

BACKGROUND: Hepatectomy for huge hepatocellular carcinoma (HCC) (diameter ≥10 cm) is characterized by high mortality. This study aimed to establish a preoperative model to evaluate the risk of postoperative 90-day mortality for huge HCC patients. METHODS: We retrospectively enrolled 1,127 consecutive patients and prospectively enrolled 93 patients with huge HCC who underwent hepatectomy (training cohort, n=798; validation cohort, n=329; prospective cohort, n=93) in our institute. Based on independent preoperative predictors of 90-day mortality, we established a logistic regression model and visualized the model by nomogram. RESULTS: The 90-day mortality rates were 9.6%, 9.2%, and 10.9% in the training, validation, and prospective cohort. The α-fetoprotein (AFP) level, the prealbumin levels, and the presence of portal vein tumor thrombosis (PVTT) were preoperative independent predictors of 90-day mortality. A logistic regression model, AFP-prealbumin-PVTT score (APP score), was subsequently established and showed good performance in predicting 90-day mortality (training cohort, AUC =0.87; validation cohort, AUC =0.91; prospective cohort, AUC =0.93). Using a cut-off of -1.96, the model could stratify patients into low risk (≤-1.96) and high risk (>-1.96) with different 90-day mortality rates (~30% vs. ~2%). Furthermore, the predictive performance for 90-day mortality and overall survival was significantly superior to the Child-Pugh score, the model of end-stage liver disease (MELD) score, and the albumin-bilirubin (ALBI) score. CONCLUSIONS: The APP score can precisely predict postoperative 90-day mortality as well as long-term survival for patients with huge HCC, assisting physician selection of suitable candidates for liver resection and improving the safety and efficacy of surgical treatment.