Sub-classification of Advanced-Stage Hepatocellular Carcinoma: A Cohort Study Including 612 Patients Treated with Sorafenib

A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma

PURPOSE

Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treatment.

EXPERIMENTAL DESIGN

We recruited 2,626 patients with BCLC-C HCC from multiple centers, comprising training/test (n = 1,693) and validation cohorts (n = 933). The XGBoost model was chosen for maximum performance among the machine learning (ML) models. Patients were categorized into low-, intermediate-, high-, and very high-risk subgroups based on the estimated prognosis, and this subclassification was named the CLAssification via Machine learning of BCLC-C (CLAM-C).

RESULTS

The areas under the receiver operating characteristic curve of the CLAM-C for predicting the 6-, 12-, and 24-month survival of patients with BCLC-C were 0.800, 0.831, and 0.715, respectively-significantly higher than those of the conventional models, which were consistent in the validation cohort. The four subgroups had significantly different median overall survivals, and this difference was maintained among various patient subgroups and treatment modalities. Immune-checkpoint inhibitors and transarterial therapies were associated with significantly better survival than tyrosine kinase inhibitors (TKI) in the low- and intermediate-risk subgroups. In cases with first-line systemic therapy, the CLAM-C identified atezolizumab-bevacizumab as the best therapy, particularly in the high-risk group. In cases with later-line systemic therapy, nivolumab had better survival than TKIs in the low-to-intermediate-risk subgroup, whereas TKIs had better survival in the high- to very high-risk subgroup.

CONCLUSIONS

ML modeling effectively subclassified patients with BCLC-C HCC, potentially aiding treatment allocation. Our study underscores the potential utilization of ML modeling in terms of prognostication and treatment allocation in patients with BCLC-C HCC.

Development of a Multivariate Prognostic Model for Lenvatinib Treatment in Hepatocellular Carcinoma

BACKGROUND

Lenvatinib is a first-line agent for advanced hepatocellular carcinoma (HCC), but individual responses to treatment are highly heterogeneous. The aim of this study was to investigate the clinical parameters that influence the efficacy of Lenvatinib and to develop a prognostic model.

METHODS

We retrospectively enrolled 333 Lenvatinib-treated patients with HCC with a median age of 57 years. Two hundred nd sixty-three of these patients had BCLC (2022) stage C. The median overall survival (mOS) time within the cohort was 12.1 months, and the median progression-free survival (mPFS) time was 4.7 months. Univariate Cox regression, best subset regression, and Lasso regression were used to screen primary variables for possible contribution to OS, multivariate Cox analysis was used to fit selected models, and the final model was selected using the maximum area under the curve (AUC) and minimum AIC. Receiver operating curves (ROC), calibration curves, and decision curve analysis were plotted to assess model performance, and 5-fold cross-validation was performed for internal validation. X-tile software was used to select the best cutoff points and to divide the study cohort into 3 different risk groups.

RESULTS

Seven variables were included in the final model: BCLC stage, prior transarterial chemoembolization and immunotherapy history, tumor number, prognostic nutritional index, log (alpha-fetoprotein), and log (platelet-to-lymphocyte ratio). We named this final model the "multivariate prognostic model for Lenvatinib" (MPML), and a nomogram was constructed to predict the probability of survival at 6, 9, and 12 months. The MPML had good discrimination, calibration, and applicability. Cross-validation showed mean AUC values of 0.7779, 0.7738, and 0.7871 at 6, 9, and 12 months, respectively. According to nomogram points, mOS time was 21.57, 8.70, and 5.37 months in the low, medium, and high-risk groups, respectively (P < .001), and these differences were also observed in the PFS survival curve (P < .001).

CONCLUSIONS

The MPML stratified patients according to baseline clinical characteristics had a strong performance in predicting Lenvatinib efficacy and has the potential for use as an auxiliary clinical tool for individualized decision-making.

Subclassification of advanced-stage hepatocellular carcinoma with macrovascular invasion: combined transarterial chemoembolization and radiotherapy as an alternative first-line treatment

Background/Aim

The Barcelona Clinic Liver Cancer (BCLC) guidelines recommend systemic therapy as the only first-line treatment for patients with BCLC stage C hepatocellular carcinoma (HCC) despite its heterogeneity of disease extent. We aimed to identify patients who might benefit from combined transarterial chemoembolization (TACE) and radiation therapy (RT) by subclassifying BCLC stage C.

Methods

A total of 1,419 treatment-naïve BCLC stage C patients with macrovascular invasion (MVI) who were treated with combined TACE and RT (n=1,115) or systemic treatment (n=304) were analyzed. The primary outcome was overall survival (OS). Factors associated with OS were identified and assigned points by the Cox model. The patients were subclassified into three groups based on these points.

Results

The mean age was 55.4 years, and 87.8% were male. The median OS was 8.3 months. Multivariate analysis revealed a significant association of Child-Pugh B, infiltrative-type tumor or tumor size ≥10 cm, main or bilateral portal vein invasion, and extrahepatic metastasis with poor OS. The sub-classification was categorized into low (point ≤1), intermediate (point=2), and high (point ≥3) risks based on the sum of points (range, 0-4). The OS in the low, intermediate, and high-risk groups was 22.6, 8.2, and 3.8 months, respectively. In the low and intermediate-risk groups, patients treated with combined TACE and RT exhibited significantly longer OS (24.2 and 9.5 months, respectively) than those who received systemic treatment (6.4 and 5.1 months, respectively; P<0.0001).

Conclusions

Combined TACE and RT may be considered as a first-line treatment option for HCC patients with MVI when classified into low- and intermediate-risk groups.

Prognostic value of a nomogram based on peripheral blood immune parameters in unresectable hepatocellular carcinoma after intensity-modulated radiotherapy

BACKGROUND

For patients with unresectable hepatocellular carcinoma (uHCC), intensity-modulated radiotherapy (IMRT) has become one of the options for clinical local treatment. Immune parameters, including platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and systemic immune inflammatory (SII), predict survival in various cancers. This study aimed to determine whether peripheral immune parameters can predict survival in patients with uHCC undergoing IMRT and establish a clinically useful prognostic nomogram for survival prediction.

METHODS

The clinical data of 309 HCC patients were retrospectively analyzed and randomly divided into training (n = 216) and validation (n = 93) cohorts. PLR, NLR and SII were collected before and after IMRT. Univariate and multivariate Cox analyses were performed to identify independent prognostic factors affecting survival, which were used to generate a nomogram.

RESULTS

The median survival was 16.3 months, and significant increases in PLR, NLR, and SII were observed after IMRT (P < 0.001). High levels of immune parameters were associated with poor prognosis (P < 0.001); enlarged spleen, Barcelona clinic liver cancer stage (B and C), post-SII, and delta-NLR were independent risk factors for survival and were included in the nomogram, which accurately predicted 3- and 5-year survival. The nomogram was well verified in the validation cohort.

CONCLUSIONS

High levels of immune parameters are associated with poor prognosis in uHCC patients receiving IMRT. Our nomogram accurately predicts the survival of patients with uHCC receiving IMRT.

Identification and validation of a prognostic model of necroptosis-related lncRNAs in hepatocellular carcinoma

Background: The study focused on establishing a prognostic survival model with six necroptosis-related lncRNAs to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC).

Methods: The data of gene expression and clinical information of HCC patients were obtained from The Cancer Genome Atlas (TCGA). Cox regression with LASSO was used for constructing a necroptosis-related lncRNA survival model, which we further validated with qRT-PCR in vitro. The relative bioinformatics analysis and consensus cluster analysis were performed based on six differentially expressed lncRNAs.

Results: The survival prognostic model was constructed by using data from TCGA. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. GSEA showed that several signaling pathways were related to HCC progression. Immune-related functional analysis showed that aDCs, macrophages, Th2 cells, and Tregs have stronger correlation with the high-risk group. The consensus cluster analysis further validated the 6-lncRNA prognostic model.

Conclusion: A novel 6-lncRNA (AL606489.1, NRAV, LINC02870, DUXAP8, “ZFPM2-AS1,” and AL031985.3) prognostic model had an accurately predictive power in HCC prognosis, which might be worthy of clinical application.

Prognostic models for outcome prediction in patients with advanced hepatocellular carcinoma treated by systemic therapy: a systematic review and critical appraisal

Objective

To describe and analyze the predictive models of the prognosis of patients with hepatocellular carcinoma (HCC) undergoing systemic treatment.

Design

Systematic review.

Data sources

PubMed and Embase until December 2020 and manually searched references from eligible articles.

Eligibility criteria for study selection

The development, validation, or updating of prognostic models of patients with HCC after systemic treatment.

Results

The systematic search yielded 42 eligible articles: 28 articles described the development of 28 prognostic models of patients with HCC treated with systemic therapy, and 14 articles described the external validation of 32 existing prognostic models of patients with HCC undergoing systemic treatment. Among the 28 prognostic models, six were developed based on genes, of which five were expressed in full equations; the other 22 prognostic models were developed based on common clinical factors. Of the 28 prognostic models, 11 were validated both internally and externally, nine were validated only internally, two were validated only externally, and the remaining six models did not undergo any type of validation. Among the 28 prognostic models, the most common systemic treatment was sorafenib (n = 19); the most prevalent endpoint was overall survival (n = 28); and the most commonly used predictors were alpha-fetoprotein (n = 15), bilirubin (n = 8), albumin (n = 8), Child–Pugh score (n = 8), extrahepatic metastasis (n = 7), and tumor size (n = 7). Further, among 32 externally validated prognostic models, 12 were externally validated > 3 times.

Conclusions

This study describes and analyzes the prognostic models developed and validated for patients with HCC who have undergone systemic treatment. The results show that there are some methodological flaws in the model development process, and that external validation is rarely performed. Future research should focus on validating and updating existing models, and evaluating the effects of these models in clinical practice.

Systematic review registration

PROSPERO CRD42020200187.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09841-5.

Identification and Validation of a Prognostic Prediction Model of m6A Regulator-Related LncRNAs in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly invasive malignancy prone to recurrence, and patients with HCC have a low 5-year survival rate. Long non-coding RNAs (lncRNAs) play a vital role in the occurrence and development of HCC. N6-methyladenosine methylation (m6A) is the most common modification influencing cancer development. Here, we used the transcriptome of m6A regulators and lncRNAs, along with the complete corresponding clinical HCC patient information obtained from The Cancer Genome Atlas (TCGA), to explore the role of m6A regulator-related lncRNA (m6ARlnc) as a prognostic biomarker in patients with HCC. The prognostic m6ARlnc was selected using Pearson correlation and univariate Cox regression analyses. Moreover, three clusters were obtained via consensus clustering analysis and further investigated for differences in immune infiltration, immune microenvironment, and prognosis. Subsequently, nine m6ARlncs were identified with Lasso-Cox regression analysis to construct the prognostic signature m6A-9LPS for patients with HCC in the training cohort (n = 226). Based on m6A-9LPS, the risk score for each case was calculated. Patients were then divided into high- and low-risk subgroups based on the cutoff value set by the X-tile software. m6A-9LPS showed a strong prognosis prediction ability in the validation cohort (n = 116), the whole cohort (n = 342), and even clinicopathological stratified survival analysis. Combining the risk score and clinical characteristics, we established a nomogram for predicting the overall survival (OS) of patients. To further understand the mechanism underlying the m6A-9LPS-based classification of prognosis differences, KEGG and GO enrichment analyses, competitive endogenous RNA (ceRNA) network, chemotherapeutic agent sensibility, and immune checkpoint expression level were assessed. Taken together, m6A-9LPS could be used as a precise prediction model for the prognosis of patients with HCC, which will help in individualized treatment of HCC.

Clinical Characteristics of Long-Term Survivors After Sorafenib Treatment for Unresectable Hepatocellular Carcinoma: A Korean National Multicenter Retrospective Cohort Study

Background/Aim

Sorafenib is the first systemic therapy for the treatment of advanced-stage hepatocellular carcinoma (HCC) and progressive HCC after locoregional therapy. The aim of this study was to evaluate the prognostic factors of long-term survivors after sorafenib treatment.

Methods

This multicenter, retrospective, cohort study included 1,566 unresectable HCC patients who received sorafenib treatment between 2007 and 2014 in nine tertiary centers in Korea. The patients were classified into a long-term survivor group (survival more than two years, n = 257) or a control group (n = 1309). The primary outcomes were the prognostic factors affecting long-term survival. Secondary endpoints included time-to-progression and other safety profiles.

Results

The patients were predominantly men (83.8%) with chronic hepatitis B (77.3%) and Barcelona clinic of liver cancer-stage C (BCLC-C) (78.3%). The median overall survival was 9.0 months. After treatment, eight patients (0.4%) achieved complete response and 139 patients (8.8%) achieved partial response according to the mRECIST criteria. The prognostic factors predicting long-term survival were metformin use (adjusted hazard ratio [aHR] = 3.464; P < 0.001), hand-foot skin reaction (aHR = 1.688; P = 0.003), and concomitant treatment with chemoembolization or radiotherapy (aHR = 2.766; P < 0.001). Poor prognostic factors of long-term survival were a Child-Pugh score of B (HR = 0.422; P < 0.001), the presence of extrahepatic metastasis (HR = 0.639; P = 0.005), main portal vein invasion (HR = 0.502; P = 0.001), and elevated alpha-fetoprotein (>1,000 ng/mL; HR = 0.361; P < 0.001).

Conclusion

This large, multicenter, retrospective study showed an objective response rate of 9.1% and a proportion of long-term survivors of 16.4% in Korean patients. The prognostic factors derived in our study can be used in clinical practice during sorafenib treatment.

A Nomogram-Based Prognostic Model for Advanced Hepatocellular Carcinoma Patients Treated with Sorafenib: A Multicenter Study

Among scores and staging systems used for HCC, none showed a good prognostic ability in patients with advanced HCC treated with Sorafenib. We aimed to evaluate predictive factors of overall survival (OS) and drug response in HCC patients undergoing Sorafenib included in the Italian Liver Cancer (ITA.LI.CA.) multicenter cohort. Patients in the ITA.LI.CA database treated with Sorafenib and updated on 30 June 2019 were included. Demographic and clinical data before starting Sorafenib treatment were considered. For the evaluation of predictive factors for OS, a time-dependent Cox proportional hazard model was used. A total of 1107 patients were included in our analysis. The mean age was 64.3 years and 81.7% were male. Most patients were staged as BCLC B (205, 18.9%) or C (706, 65.1%). The median time of Sorafenib administration was 4 months (interquartile range (IQR) 2-12), and the median OS was 10 months (IQR: 4-20). A total of 263 patients (33.8%) out of 780 with available evaluation experienced objective tumoral response to Sorafenib. The Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) (hazard ratio (HR) 1.284), maximum tumoral diameter (HR 1.100), plasma total bilirubin (HR 1.119), aspartate amino transferase assessed as multiple of the upper normal value (HR 1.032), alpha-fetoprotein ≥200 ng/mL (HR 1.342), hemoglobin (HR 0.903) and platelet count (HR 1.002) were associated with OS at multivariate Cox regression analysis. Drug response was predicted by maximum tumoral diameter and platelet count. A novel prognostic nomogram for patients undergoing Sorafenib is hereby proposed. The novelty introduced is the comprehensive patient's assessment using common markers of patient's general status, liver damage and function and HCC biology. Further studies are required to test its accuracy and provide external validation.

Prognostic significance of systemic immune-inflammation index-based nomogram for early stage hepatocellular carcinoma after radiofrequency ablation

BACKGROUND

Radiofrequency ablation (RFA) is the recommended treatment for early stage hepatocellular carcinoma (HCC), and the prognostic value of systemic immune-inflammation index (SII) in early stage HCC is not discussed. Therefore, the purpose of the study is to explore the prognostic value of SII based on lymphocyte, neutrophil, and platelet counts in patients with HCC after RFA.

METHODS

We retrospectively evaluated the prognostic value of the SII in training and validation cohorts, and then established an effective nomogram for HCC after RFA based on SII. The C-index, and area under the time-dependent receiver operating characteristic curve (t-AUC) were used to evaluate the discrimination and calibration value of the nomogram.

RESULTS

An optimal cut-off value for the SII of 324.55×109 stratified the patients with HCC into high- and low-SII groups. Univariate and multivariate analyses revealed that SII was an independent predictor for overall survival (OS) and recurrence-free survival (RFS). Moreover, SII was an independent prognostic factor for early-stage HCC with normal alpha-fetoprotein (AFP) levels. The t-AUC of the SII was higher for OS and RFS than for neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR). A high preoperative SII was associated with multiple tumors, larger tumors, and higher levels of AFP. A well-discriminated and calibrated nomogram was constructed to predict the probability of 1-, 2-, 3-, and 5-year RFS with C-indexes of 0.80, which was significantly higher than that obtained with other prognostic clinical indexes.

CONCLUSIONS

The SII is an independent prognostic factor affecting the survival outcomes of patients with early-stage HCC. The comprehensive nomogram based on SII presented in this study is a promising model for predicting RFS in HCC patients after RFA.

Construction and validation of an N6-methyladenosine-associated prognostic signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is among the most common types of cancer that threat the public health worldwide. N6-methyladenosine (m6A) RNA methylation is associated with cancer initiation and progression, and is dynamically regulated by m6A RNA methylation-associated genes. However, little is known about the expression status and the prognostic value of m6A-associated genes in HCC. The present study aimed to identify the expression profiling pattern and clinical significance of m6A-associated genes in HCC. Consensus clustering analysis was performed to identify the clusters of HCC with different clinical outcomes. A prognostic signature built by the least absolute shrinkage and selection operator Cox regression model was utilized to discover subtypes associated with different clinical outcomes of patients with HCC in the discovery cohort from The Cancer Genome Atlas. The differences between subgroups were characterized in terms of epigenetic dysregulation and somatic mutation frequencies. The International Cancer Genome Consortium cohort and two independent cohorts from the meta-Gene Expression Omnibus database were used for external validation. Most of the m6A-associated genes were upregulated and involved in the prognosis and malignancy of HCC. A four-gene prognostic signature revealed two HCC subtypes (namely, high- and low-risk group) that was associated with different clinical outcomes. Patients in the high-risk group were accompanied with increased epigenetic silencing and significant mutations in TP53 and FLG, while ALB was frequently mutated in the low-risk group. In conclusion, an m6A-based signature was constructed to predict the prognosis of patients with HCC, which may provide a tool for reliable prognosis assessment for clinicians, and aid clinical treatment decision-making.

Improved survival prediction and comparison of prognostic models for patients with hepatocellular carcinoma treated with sorafenib

BACKGROUND

The 'Prediction Of Survival in Advanced Sorafenib-treated HCC' (PROSASH) model addressed the heterogeneous survival of patients with hepatocellular carcinoma (HCC) treated with sorafenib in clinical trials but requires validation in daily clinical practice. This study aimed to validate, compare and optimize this model for survival prediction.

METHODS

Patients treated with sorafenib for HCC at five tertiary European centres were retrospectively staged according to the PROSASH model. In addition, the optimized PROSASH-II model was developed using the data of four centres (training set) and tested in an independent dataset. These models for overall survival (OS) were then compared with existing prognostic models.

RESULTS

The PROSASH model was validated in 445 patients, showing clear differences between the four risk groups (OS 16.9-4.6 months). A total of 920 patients (n = 615 in training set, n = 305 in validation set) were available to develop PROSASH-II. This optimized model incorporated fewer and less subjective parameters: the serum albumin, bilirubin and alpha-foetoprotein, and macrovascular invasion, extrahepatic spread and largest tumour size on imaging. Both PROSASH and PROSASH-II showed improved discrimination (C-index 0.62 and 0.63, respectively) compared with existing prognostic scores (C-index ≤0.59).

CONCLUSIONS

In HCC patients treated with sorafenib, individualized prediction of survival and risk group stratification using baseline prognostic and predictive parameters with the PROSASH model was validated. The refined PROSASH-II model performed at least as good with fewer and more objective parameters. PROSASH-II can be used as a tool for tailored treatment of HCC in daily practice and to define pre-planned subgroups for future studies.

A novel prognostic score model based on combining systemic and hepatic inflammation markers in the prognosis of HBV-associated hepatocellular carcinoma patients

Objectives: The study aimed to evaluate the prognostic value of systemic inflammation markers [neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Prognostic Nutritional Index (PNI)] and hepatic inflammation markers [aspartate aminotransferase-to-platelet ratio index (APRI), γ-glutamyl transferase (γ-GT)/alanine aminotransferase (ALT)] in patients with hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) and further to develop a novel prognostic score model. Methods: A total of 401 cases with HBV-associated HCC who underwent hepatectomy as initial therapy were included in the analysis. Kaplan-Meier was performed to construct survival curves and receiver operating characteristic (ROC) analysis was used to detect the optimal cut-off value of markers. The prognostic score model was constructed using significant inflammation markers in the Cox model. Each factor was given a score of 1 and patients were stratified according to the scores. Results: In the Cox model, α-fetoprotein (AFP), ALT, tumour differentiation, maximum size of tumours, TNM stage, PNI and γ-GT/ALT were independently prognostic factors. We established a preoperative inflammation-based prognostic scoring model combining PNI and γ-GT/ALT. The novel preoperative inflammation-based prognostic score was superior (area under the curve [AUC], 0.659) to 7^th tumour-node-metastasis (TNM) stage (AUC, 0.600) despite no statistical significance (p = .1036). Conclusion: PNI and γ-GT/ALT are independent predictors for prognosis. The novel prognostic score model based on systemic and hepatic inflammation markers is suitable for the prognosis evaluation in patients with HBV-associated HCC.

Combined transarterial chemoembolization and radiotherapy as a first-line treatment for hepatocellular carcinoma with macroscopic vascular invasion: Necessity to subclassify Barcelona Clinic Liver Cancer stage C

BACKGROUND AND PURPOSE

Systemic therapy such as sorafenib is the standard for Barcelona Clinic Liver Cancer (BCLC) stage C hepatocellular carcinoma (HCC); however, the survival benefits are modest especially for HCC with macroscopic vascular invasion (MVI). Transarterial chemoembolization (TACE) plus external beam radiotherapy (RT) is an alternative treatment to sorafenib, with favorable clinical results. We evaluated the outcomes of respiratory-gated RT and TACE in treatment-naïve BCLC stage C HCC patients with MVI and proposed a subclassification model.

METHODS

In this study, 639 patients received TACE plus RT for HCC with MVI as a first-line treatment between January 2010 and December 2015.

RESULTS

Main/bilateral portal vein and/or inferior vena cava tumor thrombus was observed in 353 (55.2%) patients. The median radiation dose was 39 Gy (range 24-50) with a 2.5-Gy (2-5) median fraction size. The median overall survival was 10.7 months, with 1- and 2-year survival rates of 46.5% and 23.9%, respectively. In the multivariate analysis, Child-Pugh classification B, tumor size >10 cm, infiltrative/diffuse type, presence of extrahepatic metastasis, alpha-fetoprotein >150,000 ng/mL, and radiation dose ≤40 Gy were significant predictors for poor overall survival. Subclassification of patients into very low, low, intermediate, and high-risk groups showed median survivals of 84.8, 14.7, 10.3, and 5.7 months, respectively (p < 0.001).

CONCLUSION

TACE plus RT is an effective and safe treatment for HCC with MVI and could be considered a first-line treatment option. The subclassification scheme accurately predicted the prognosis of these patients and may be useful for tailored treatment.