Novel microvascular invasion-based prognostic nomograms to predict survival outcomes in patients after R0 resection for hepatocellular carcinoma. J Cancer Res Clin Oncol. 2017;143:293-303. [PMID: 27743138 DOI: 10.1007/s00432-016-2286-1]

Dual-energy computed tomography iodine quantification combined with laboratory data for predicting microvascular invasion in hepatocellular carcinoma: a two-centre study

OBJECTIVES

Microvascular invasion (MVI) is a recognized biomarker associated with poorer prognosis in patients with hepatocellular carcinoma. Dual-energy computed tomography (DECT) is a highly sensitive technique that can determine the iodine concentration (IC) in tumour and provide an indirect evaluation of internal microcirculatory perfusion. This study aimed to assess whether the combination of DECT with laboratory data can improve preoperative MVI prediction.

METHODS

This retrospective study enrolled 119 patients who underwent DECT liver angiography at 2 medical centres preoperatively. To compare DECT parameters and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied across MVI groups. Finally, a general linear classifier was used to assess the classification ability of each PC score.

RESULTS

Significant differences were noted (P < .05) in alpha-fetoprotein (AFP) level, normalized arterial phase IC, and normalized portal phase IC between the MVI groups in the primary and validation datasets. The PC1-PC4 accounted for 67.9% of the variance in the primary dataset, with loadings of 24.1%, 16%, 15.4%, and 12.4%, respectively. In both primary and validation datasets, PC3 and PC4 were significantly different across MVI groups, with area under the curve values of 0.8410 and 0.8373, respectively.

CONCLUSIONS

The recombination of DECT IC and laboratory features based on varying factor loadings can well predict MVI preoperatively.

ADVANCES IN KNOWLEDGE

Utilizing PCA, the amalgamation of DECT IC and laboratory features, considering diverse factor loadings, showed substantial promise in accurately classifying MVI. There have been limited endeavours to establish such a combination, offering a novel paradigm for comprehending data in related research endeavours.

Predictive values of sarcopenia and systemic inflammation-based markers in advanced hepatocellular carcinoma after hepatectomy

BACKGROUND

Sarcopenia accompanied by systemic inflammation is associated with poor prognosis in patients with advanced hepatocellular carcinoma (HCC). However, the effect of sarcopenia combined with systemic inflammation on the prognosis of patients with advanced HCC who underwent hepatectomy is unclear. This study aimed to evaluate the effect of sarcopenia and inflammation on the prognosis of patients with advanced HCC.

METHODS

This retrospective study included 151 patients recruited between July 2010 and December 2022. We defined advanced HCC as that presenting with vascular invasion or tumor size ≥2 cm or multiple tumors. Sarcopenia was assessed using the psoas muscle index. Preoperative inflammatory markers were used by calculating the prognostic nutritional index, albumin-globulin ratio (AGR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio. Cox regression analysis was performed to determine the prognostic factors for overall survival.

RESULTS

Of 151 patients, sarcopenia occurred in 84 (55.6 %). Sarcopenia was significantly associated with male sex, older age, body mass index (<25 kg/m2), and a higher NLR. In the multivariate analysis, AGR <1.25 (hazard ratio [HR], 2.504; 95% confidence interval [CI]: 1.325-4.820; p < 0.05); alpha-fetoprotein levels ≥25 ng/mL (HR, 1.891; 95% CI: 1.016-3.480; p = 0.04); and sarcopenia (HR, 1.908; 95% CI: 1.009-3.776; p < 0.05) were independent predictors of overall survival. The sarcopenia and low AGR groups had significantly worse overall survival than either the non-sarcopenia and high AGR or sarcopenia and low AGR groups.

CONCLUSION

Sarcopenia and AGR are independent prognostic factors in patients with advanced HCC. Thus, sarcopenia may achieve a better prognostic value when combined with AGR.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing

BACKGROUND

As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted.

METHODS

We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining.

RESULTS

Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55).

CONCLUSIONS

TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

Deep learning-based accurate diagnosis and quantitative evaluation of microvascular invasion in hepatocellular carcinoma on whole-slide histopathology images

BACKGROUND

Microvascular invasion (MVI) is an independent prognostic factor that is associated with early recurrence and poor survival after resection of hepatocellular carcinoma (HCC). However, the traditional pathology approach is relatively subjective, time-consuming, and heterogeneous in the diagnosis of MVI. The aim of this study was to develop a deep-learning model that could significantly improve the efficiency and accuracy of MVI diagnosis.

MATERIALS AND METHODS

We collected H&E-stained slides from 753 patients with HCC at the First Affiliated Hospital of Zhejiang University. An external validation set with 358 patients was selected from The Cancer Genome Atlas database. The deep-learning model was trained by simulating the method used by pathologists to diagnose MVI. Model performance was evaluated with accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve.

RESULTS

We successfully developed a MVI artificial intelligence diagnostic model (MVI-AIDM) which achieved an accuracy of 94.25% in the independent external validation set. The MVI positive detection rate of MVI-AIDM was significantly higher than the results of pathologists. Visualization results demonstrated the recognition of micro MVIs that were difficult to differentiate by the traditional pathology. Additionally, the model provided automatic quantification of the number of cancer cells and spatial information regarding MVI.

CONCLUSIONS

We developed a deep learning diagnostic model, which performed well and improved the efficiency and accuracy of MVI diagnosis. The model provided spatial information of MVI that was essential to accurately predict HCC recurrence after surgery.

Comparative effectiveness of several adjuvant therapies after hepatectomy for hepatocellular carcinoma patients with microvascular invasion

BACKGROUND

For resectable hepatocellular carcinoma (HCC), radical hepatectomy is commonly used as a curative treatment. However, postoperative recurrence significantly diminishes the overall survival (OS) of HCC patients, especially with microvascular invasion (MVI) as an independent high-risk factor for recurrence. While some studies suggest that postoperative adjuvant therapy may decrease the risk of recurrence following liver resection in HCC patients, the specific role of adjuvant therapies in those with MVI remains unclear.

AIM

To conduct a network meta-analysis (NMA) to evaluate the efficacy of various adjuvant therapies and determine the optimal adjuvant regimen.

METHODS

A systematic literature search was conducted on PubMed, EMBASE, and Web of Science until April 6, 2023. Studies comparing different adjuvant therapies or comparing adjuvant therapy with hepatectomy alone were included. Hazard ratios (HRs) with 95% confidence intervals were used to combine data on recurrence free survival and OS in both pairwise meta-analyses and NMA.

RESULTS

Fourteen eligible trials (2268 patients) reporting five different therapies were included. In terms of reducing the risk of recurrence, radiotherapy (RT) [HR = 0.34 (0.23, 0.5); surface under the cumulative ranking curve (SUCRA) = 97.7%] was found to be the most effective adjuvant therapy, followed by hepatic artery infusion chemotherapy [HR = 0.52 (0.35, 0.76); SUCRA = 65.1%]. Regarding OS improvement, RT [HR: 0.35 (0.2, 0.61); SUCRA = 93.1%] demonstrated the highest effectiveness, followed by sorafenib [HR = 0.48 (0.32, 0.69); SUCRA = 70.9%].

CONCLUSION

Adjuvant therapy following hepatectomy may reduce the risk of recurrence and provide a survival benefit for HCC patients with MVI. RT appears to be the most effective adjuvant regimen.

Novel nomograms based on microvascular invasion grade for early-stage hepatocellular carcinoma after curative hepatectomy

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.

A Grading System of Microvascular Invasion for Patients with Hepatocellular Carcinoma Undergoing Liver Resection with Curative Intent: A Multicenter Study

Background

Microvascular invasion (MVI) is closely correlated with poor clinical outcomes in patients with hepatocellular carcinoma (HCC). A grading system of MVI is needed to assist in the management of HCC patient.

Methods

Multicenter data of HCC patients who underwent liver resection with curative intent was analyzed. This grading system was established by detected number and distance from tumor boundary of MVI. Survival outcomes were compared among patients in each group. This system was verified by time-receiver operating characteristic curve, time-area under the curve, calibration curve, and decision curve analyses. Cox regression analysis was performed to study the associated factors of prognosis. Logistic analysis was used to study the predictive factors of MVI.

Results

All patients were classified into 4 groups: M0: no MVI; M1: 1~5 proximal MVIs (≤1 cm from tumor boundary); M2a: >5 proximal MVIs (≤1 cm from tumor boundary); M2b: ≥1 distal MVIs (>1 cm from tumor boundary). The recurrence-free survival (RFS), overall survival (OS), and early RFS rates among all the individual groups were significantly different. Based on the number of proximal MVI (0~5 vs >5), patients in the M2b group were further divided into two subgroups which also showed different prognosis. Multiple methods showed this grading system to be significantly better than the MVI two-tiered system in prognostic evaluation. Four multivariate models for RFS, OS, early RFS, late RFS, and a predictive model of MVI were then established and were shown to satisfactorily evaluate prognosis and have a great discriminatory power, respectively.

Conclusion

This MVI grading system could precisely evaluate prognosis of HCC patients after liver resection with curative intent and it could be employed in routine pathological reports. The severity of MVI from both adjacent and distant from tumor boundary should be stated. A hypothesis about two occurrence modes of distal MVI was proposed.

Characterization of Microvascular Invasion in Hepatocellular Carcinoma Using Computational Modeling of Interstitial Fluid Pressure and Velocity

BACKGROUND

Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue.

PURPOSE

To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model.

STUDY TYPE

Retrospective.

POPULATION

A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI.

FIELD STRENGTH/SEQUENCE

A 3-T, three-dimensional spoiled gradient-recalled echo.

ASSESSMENT

MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired.

STATISTICAL TESTS

Wilcoxon signed-ranks tests, histogram analysis, Mann-Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini-Hochberg correction. A P value <0.05 was considered statistically significant.

RESULTS

The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI-positive and MVI-negative groups, except for tumor size. Nine IFP histogram analysis-derived parameters and seven IFV histogram analysis-derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%).

DATA CONCLUSION

A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP- and IFV-derived parameters exhibited significant association with the MVI status.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 2.

Novel Prognostic Nomogram to Predict Progression-Free Survival of Patients with Hepatocellular Carcinoma After Transarterial Chemoembolization

Purpose

A retrospective analysis of hepatocellular carcinoma (HCC) patients treated with transarterial chemoembolization (TACE) to identify risk factors was conducted, and a novel predictive nomogram model was constructed.

Patients and Methods

A total of 346 HCC patients who underwent TACE as initial treatment were retrospectively included, of which 208 were randomly allocated to the derivation cohort and 138 were allocated to the validation cohort. Progression-free survival (PFS) was used as the follow-up endpoint according to mRECIST. Kaplan‒Meier analysis and the Cox regression model screened out some indicators associated with short-term prognosis, and R language was further used to construct a nomogram model. The nomogram was compared with the classical BCLC staging system.

Results

The independent predictors affecting PFS in HCC patients undergoing TACE included the following: 1. Baseline indicators: age (P=0.013), albumin-bilirubin (ALBI) grade (grade 2 vs grade 1, P=0.029; grade 3 vs grade 1, P<0.001), and portal vein tumour thrombus (PVTT, P<0.001); 2. Indicators at the 1-month follow-up: Neutrophil To Lymphocyte Ratio (NLR, P=0.032) and changes in alpha-fetoprotein (AFP, P<0.05) and des-γ-carboxy prothrombin (DCP, P<0.001); and 3. Cumulative treatment numbers of TACE in 6 months (P=0.007). In the derivation cohort, the calibration curve of the nomogram showed a high consistency between the predicted and actual PFS probability, and the nomogram outperformed the BCLC staging system (P=0.004). This result was also confirmed in the validation cohort (P=0.012).

Conclusion

The constructed nomogram was suggested to have good predictive efficacy and could be used as a complementary assessment to predict the survival and prognosis of HCC patients treated with TACE.

Perfusion parameters of triphasic computed tomography hold preoperative prediction value for microvascular invasion in hepatocellular carcinoma

The purpose of this study was to evaluate perfusion parameters of triphasic computed tomography (CT) scans in predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC). All patients were pathologically diagnosed as HCC and underwent triple-phase enhanced CT imaging, which was used to calculate the blood perfusion parameters of hepatic arterial supply perfusion (HAP), portal vein blood supply perfusion (PVP), hepatic artery perfusion Index (HPI), and arterial enhancement fraction (AEF). Receiver operating characteristic (ROC) curve was used to evaluate the performance. The mean values of PVP(Min), AEF(Min), the difference in PVP, HPI and AEF related parameters, the relative PVP(Min) and AEF(Min) in MVI negative group were significantly higher than those in MVI positive group, while for the difference in HPI(Max), the relative HPI(Max) and AEF(Max), the value of MVI positive group significantly higher than that of negative group. The combination of PVP, HPI and AEF had the highest diagnostic efficacy. The two parameters related to HPI had the highest sensitivity, while the combination of PVP related parameters had higher specificity. A combination of perfusion parameters in patients with HCC derived from traditional triphasic CT scans can be used as a preoperative biomarker for predicting MVI.

Adjuvant TACE may not improve recurrence-free or overall survival in HCC patients with low risk of recurrence after hepatectomy

Background

To identify whether adjuvant transarterial chemoembolization (TACE) can improve prognosis in HCC patients with a low risk of recurrence (tumor size ≤ 5 cm, single nodule, no satellites, and no microvascular or macrovascular invasions) after hepatectomy.

Methods

The data of 489 HCC patients with a low risk of recurrence after hepatectomy from Shanghai Cancer Center (SHCC) and Eastern Hepatobiliary Surgery Hospital (EHBH) were retrospectively reviewed. Recurrence-free survival (RFS) and overall survival (OS) were analyzed with Kaplan-Meier curves and Cox proportional hazards regression models. The effects of selection bias and confounding factors were balanced using propensity score matching (PSM).

Results

In the SHCC cohort, 40 patients (19.9%, 40/201) received adjuvant TACE, and in the EHBH cohort, 113 patients (46.2%, 133/288) received adjuvant TACE. Compared to the patients without adjuvant TACE after hepatectomy, patients receiving adjuvant TACE had significantly shorter RFS (P=0.022; P=0.014) in both cohorts before PSM. However, no significant difference existed in OS (P=0.568; P=0.082). Multivariate analysis revealed that serum alkaline phosphatase and adjuvant TACE were independent prognostic factors for recurrence in both cohorts. Furthermore, significant differences existed in tumor size between the adjuvant TACE and non-adjuvant TACE groups in the SHCC cohort. There were differences in transfusion, Barcelona Clinic Liver Cancer stage and tumor-node-metastasis stage in the EHBH cohort. These factors were balanced by PSM. After PSM, patients with adjuvant TACE after hepatectomy still had significantly shorter RFS than those without (P=0.035; P=0.035) in both cohorts, but there was no difference in OS (P=0.638; P=0.159). Adjuvant TACE was the only independent prognostic factor for recurrence in multivariate analysis, with hazard ratios of 1.95 and 1.57.

Conclusions

Adjuvant TACE may not improve long-term survival and might promote postoperative recurrence in HCC patients with a low risk of recurrence after hepatectomy.

Understanding the causes of recurrent HCC after liver resection and radiofrequency ablation

INTRODUCTION

Surgical resection and radiofrequency ablation are preferred options for early-stage disease, with 5-year recurrence rates as high as 70% when patients are treated according to guidelines. With increasing availability of therapeutic options, including but not limited to, immune-checkpoint inhibitors (ICI), tyrosine kinase inhibitors, antiangiogenics, and adoptive cell therapies, understanding the causes of recurrence and identifying its predictors should be priorities in the hepatocellular carcinoma (HCC) research agenda.

AREAS COVERED

Current knowledge of HCC predictors of recurrence is reviewed, and recent insights about its underlying mechanisms are presented. In addition, results from recent clinical trials investigating treatment combinations are critically appraised.

EXPERT OPINION

HCC recurrence is either due to progressive growth of microscopic residual disease, or to de novo cancer development in the context of a diseased liver, each occurring in an early (<2years) vs. late (≥2 years) fashion. Collectively, morphological, proteomic, and transcriptomic data suggest vascular invasion and angiogenesis as key drivers of HCC recurrence. Agents aimed at blocking either of these two hallmarks should be prioritized at the moment of early-stage HCC clinical trial design. Emerging results from clinical trials testing ICI in early-stage HCC underscore the importance of defining the best treatment sequence and the most appropriate combination strategies. Lastly, as different responses to systemic therapies are increasingly defined according to the HCC etiology, patient enrolment into clinical trials should take into account the biological characteristics of their inherent disease.

A novel nomogram predicting the early recurrence of hepatocellular carcinoma patients after R0 resection

Background

Early tumor recurrence is one of the most significant poor prognostic factors for patients with HCC after R0 resection. The aim of this study is to identify risk factors of early recurrence, in addition, to develop a nomogram model predicting early recurrence of HCC patients.

Methods

A total of 481 HCC patients after R0 resection were enrolled and divided into a training cohort (n = 337) and a validation cohort (n = 144). Risk factors for early recurrence were determined based on Cox regression analysis in the training cohort. A nomogram incorporating independent risk predictors was established and validated.

Results

Early recurrence occurred in 37.8% of the 481 patients who underwent curative liver resection of HCC. AFP ≥ 400 ng/mL (HR: 1.662; P = 0.008), VEGF-A among 127.8 to 240.3 pg/mL (HR: 1.781, P = 0.012), VEGF-A > 240.3 pg/mL (HR: 2.552, P < 0.001), M1 subgroup of MVI (HR: 2.221, P = 0.002), M2 subgroup of MVI (HR: 3.120, P < 0.001), intratumor necrosis (HR: 1.666, P = 0.011), surgical margin among 5.0 to 10.0 mm (HR: 1.601, P = 0.043) and surgical margin < 5.0 mm (HR: 1.790, P = 0.012) were found to be independent risk factors for recurrence-free survival in the training cohort and were used for constructing the nomogram. The nomogram indicated good predictive performance with an AUC of 0.781 (95% CI: 0.729-0.832) and 0.808 (95% CI: 0.731-0.886) in the training and validation cohorts, respectively.

Conclusions

Elevated serum concentrations of AFP and VEGF-A, microvascular invasion, intratumor necrosis, surgical margin were independent risk factors of early intrahepatic recurrence. A reliable nomogram model which incorporated blood biomarkers and pathological variables was established and validated. The nomogram achieved desirable effectiveness in predicting early recurrence in HCC patients.

Prognostic significance of three-tiered pathological classification for microvascular invasion in patients with combined hepatocellular-cholangiocarcinoma following hepatic resection

BACKGROUND AND OBJECTIVES

Previous studies have reported that the microvascular invasion three-tiered grading (MiVI-TTG) scheme is a better prognostic predictor than the two-tiered microvascular invasion (MiVI) grading scheme in hepatocellular carcinoma. This study aims to explore the prognostic significance of MiVI-TTG in patients undergoing liver resection for combined hepatocellular-cholangiocarcinoma (cHCC) and to explore the risk factors for MiVI in cHCC.

METHODS

This research included 208 patients graded as M0, M1, or M2 using the MiVI-TTG scheme. Predictive performance was assessed by Cox regression analysis, Kaplan-Meier curve with Log rank test, Harrell's c-index, and time-dependent areas under the receiver operating characteristic curve (tdAUC). The clinical utility of the two schemes was evaluated by decision cure analysis (DCA). The risk factors for MiVI were evaluated using logistic regression analysis.

RESULTS

Among 208 cHCC patients, the proportions of M0, M1 and M2 were 38.9%, 36.5%, and 24.5%, respectively. Patients with severe MiVI status had worse recurrence-free survival and overall survival (OS) based on Kaplan-Meier analysis. M1, M2, and MiVI-positive were independent risk factors for early recurrence, while M2 and MiVI-positive were associated with overall survival (OS). MiVI-TTG had a larger c-index, tdAUC, and net benefit rate than the two-tiered MiVI grading scheme for predicting recurrence free survival and OS. AFP≥400 ng/ml was the independent risk factor for MiVI, and satellite nodules were independent risk factors for M2.

CONCLUSIONS

MiVI-TTG has a greater prognostic value than the two-tiered MiVI grading scheme in patients undergoing hepatic resection for cHCC.

Subcentimeter Nodules with Diagnostic Hallmarks of Hepatocellular Carcinoma: Comparison of Pathological Features and Survival Outcomes with Nodules Measuring 1-2 cm

Objective

To compare the pathologic diagnosis and survival of patients with subcentimeter and 1-2 cm nodules that present with diagnostic hallmarks of hepatocellular carcinoma (HCC).

Methods

Diagnostic hallmarks of HCC were defined as hyperintensity on T2 weighted imaging, restricted diffusion, arterial phase hyperenhancement, washout on portal venous phase, and hypointensity on hepatobiliary phase. We retrospectively included 139 patients undergoing curative resection with single nodules ≤2 cm that present imaging features described above on gadoxetic acid-enhanced MRI. The final diagnosis was confirmed by histopathological assessment. Recurrence-free survival (RFS) was compared using Kaplan-Meier analysis with the Log-rank test. Factors associated with overall and early recurrence were identified using Cox regression analysis.

Results

Among 139 nodules (49 nodules <1 cm), there was no significant difference in the percentage of HCC between subcentimeter and 1-2 cm nodules (94.0% vs 94.4%, P > 0.999). Microvascular invasion (MVI) was less common in subcentimeter HCC (4.3% vs 17.6%, P = 0.032). There were 27 recurrences during a median follow-up time of 46.7 months. Patients with subcentimeter HCC achieved less recurrence, with a 5-year RFS rate of 87.3%. The MVI-positive patients had more early and overall recurrence. A tumor size <1 cm was associated with lower overall recurrence (HR, 0.336; P = 0.047). No factors were independently associated with early recurrence.

Conclusion

Subcentimeter nodules with diagnostic hallmarks of HCC are highly associated with HCC diagnosis and achieve less tumor recurrence after resection. Early diagnosis and treatment of subcentimeter HCC may be more appropriate.

Postoperative adjuvant therapy for hepatocellular carcinoma with microvascular invasion

Hepatocellular carcinoma (HCC) is one of the most lethal tumors in the world. Liver resection (LR) and liver transplantation (LT) are widely considered as radical treatments for early HCC. However, the recurrence rates after curative treatment are still high and overall survival is unsatisfactory. Microvascular invasion (MVI) is considered to be one of the important prognostic factors affecting postoperative recurrence and long-term survival. Unfortunately, whether HCC patients with MVI should receive postoperative adjuvant therapy remains unknown. In this review, we summarize the therapeutic effects of transcatheter arterial chemoembolization, hepatic arterial infusion chemotherapy, tyrosine protein kinase inhibitor-based targeted therapy, and immune checkpoint inhibitors in patients with MVI after LR or LT, aiming to provide a reference for the best adjuvant treatment strategy for HCC patients with MVI after LT or LR.

Pre- to postoperative alpha-fetoprotein ratio-based nomogram to predict tumor recurrence in patients with hepatocellular carcinoma

Background

This study aimed to investigate the role of the alpha fetoprotein (AFP) ratio before and after curative resection in the prognosis of patients with hepatocellular carcinoma (HCC) and to develop a novel pre- to postoperative AFP ratio nomogram to predict recurrence free survival (RFS) for HCC patients after curative resection.

Methods

A total of 485 pathologically confirmed HCC patients who underwent radical hepatectomy from January 2010 to December 2018 were retrospectively analyzed. The independent prognostic factors of hepatocellular carcinoma were identified by multivariate COX proportional model analysis, and the nomogram model was constructed. The receiver operating characteristic and the C-index were used to evaluate the accuracy and efficacy of the model prediction, the correction curve was used to assess the calibration of the prediction model, and decision curve analysis was used to evaluate the clinical application value of the nomogram model.

Results

A total of 485 HCC patients were divided into the training cohort (n = 340) and the validation cohort (n = 145) by random sampling at a ratio of 7:3. Using X-tile software, it was found that the optimal cut-off value of the AFP ratio in the training cohort was 0.8. In both cohorts, the relapse-free survival of patients with an AFP ratio <0.8 (high-risk group) was significantly shorter than in those with an AFP ratio ≥0.8 (low-risk group) (P < 0.05). An AFP ratio <0.8 was an independent risk factor for recurrence of HCC after curative resection. Based on the AFP ratio, BCLC stage and cirrhosis diagnosis, a satisfactory nomogram was developed. The AUC of our nomogram for predicting 1-, 3-, and 5-year RFS was 0.719, 0.690, and 0.708 in the training cohort and 0.721, 0.682, and 0.681 in the validation cohort, respectively. Furthermore, our model demonstrated excellent stratification as well as clinical applicability.

Conclusion

The AFP ratio was a reliable biomarker for tumor recurrence. This easy-to-use AFP ratio-based nomogram precisely predicted tumor recurrence in HCC patients after curative resection.

Prognostic Analysis of Single Large Hepatocellular Carcinoma Following Radical Resection: A Single-Center Study

Objective

To investigate the survival and independent prognostic factors for single large hepatocellular carcinoma (SLHCC) after surgical resection.

Methods

Patients with SLHCC who underwent radical resection from January 2013 to December 2017 were retrospectively analyzed. The Kaplan-Meier method was used to analyze the overall survival (OS) rate and recurrence-free survival (RFS) rates. Cox forward stepwise regression was performed to analyze the independent prognostic factors.

Results

A total of 485 cases were included. The average age was 51.2±11.2 years, 88.9% had a history of hepatitis B virus infection, and most patients had normal liver function. The average tumor diameter was 8.8±3.0 cm. The 1-, 3-, and 5-year OS and RFS rates were 76.8%, 56.7%, and 45.7%, and 61.0%, 46.2%, and 34.7%, respectively. Multivariate analysis showed that liver cirrhosis (HR=1.456, P=0.004), total bilirubin (TB) ≥17.1 μmol/L (HR=1.437, P=0.011), glutamyl transferase (GGT) >60 U/L (HR=1.438, P=0.020), lactate dehydrogenase (LDH) >225 U/L (HR=1.442, P=0.007), blood loss ≥400 mL (HR=1.339, P=0.027), microvascular invasion (MVI) (HR=1.492, P=0.004), satellite lesions (HR=1.859, P<0.0001) and Edmondson-Steiner grade III+IV (HR=1.740, P=0.018) were independent risk factors for reduced OS in SLHCC patients. Sex (HR=1.763, P=0.003), liver cirrhosis (HR=1.382, P=0.007), GGT >60 U/L (HR=1.512, P=0.003), LDH >225 U/L (HR=1.480, P=0.002), MVI (HR=1.545, P=0.001), and satellite lesions (HR=1.564, P=0.001) were independent risk factors for reduced RFS. OS and RFS nomograms were constructed using risk factors with C-index values of 0.692 (95% CI: 0.659-0.724) and 0.659 (95% CI: 0.623-0.693), respectively. The Hosmer-Leme test demonstrated the good fit of both nomograms.

Conclusion

Surgical resection is the standard and effective treatment for SLHCC patients. Sex, liver cirrhosis, TB≥17.1 μmol/L, GGT>60 U/L, LDH>225 U/L, blood loss≥400 mL, MVI, Edmondson-Steiner grade III+IV, and satellite lesions were found to be independent prognostic factors in SLHCC patients following radical resection. The OS and RFS nomograms accurately predicted the prognosis of SLHCC patients.

A new prognostic model predicting hepatocellular carcinoma early recurrence in patients with microvascular invasion who received postoperative adjuvant transcatheter arterial chemoembolization

BACKGROUD

In this study, we aimed to develop a prognostic model to predict HCC early recurrence (within 1-year) in patients with microvascular invasion who received postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE).

METHODS

A total of 148 HCC patients with MVI who received PA-TACE were included in this study. The modes were verified in an internal validation cohort (n = 112) and an external cohort (n = 36). Univariate and multivariate Cox regression analyses were performed to identify the independent prognostic factors relevant to early recurrence. A clinical nomogram prognostic model was established, and nomogram performance was assessed via internal validation and calibration curve statistics.

RESULTS

After data dimensionality reduction and element selection, multivariate Cox regression analysis indicated that alpha fetoprotein level, systemic inflammation response index, alanine aminotransferase, tumour diameter and portal vein tumour thrombus were independent prognostic factors of HCC early recurrence in patients with MVI who underwent PA-TACE. Nomogram with independent factors was established and achieved a better concordance index of 0.765 (95% CI: 0.691-0.839) and 0.740 (95% CI: 0.583-0.898) for predicting early recurrence in training cohort and validation cohort, respectively. Time-dependent AUC indicated comparative stability and adequate discriminative ability of the model. The DCA revealed that the nomogram could augment net benefits and exhibited a wider range of threshold probabilities than AJCC T stage.

CONCLUSIONS

The nomogram prognostic model showed adequate discriminative ability and high predictive accuracy.

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensus is urgently needed. Recently, artificial intelligence has emerged as an important tool for improving the clinical management of hepatocellular carcinoma. Many studies about microvascular invasion currently focus on preoperative and prognosis prediction of microvascular invasion using artificial intelligence. In this paper, we review the definition and staging of microvascular invasion, especially the diagnosis of it by using artificial intelligence. In preoperative prediction, deep learning based on multimodal data modeling of radiomics-screened features, clinical features, and medical images is currently the most effective means. In prognostic prediction, pathology is the gold standard, and the techniques used should more effectively utilize the global features of the pathology images.

A Practical Risk Classification of Early Recurrence in Hepatocellular Carcinoma Patients with Microvascular invasion after Hepatectomy: A Decision Tree Analysis

PURPOSE

This study was designed to establish risk classifications for early recurrence in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) after hepatectomy.

METHODS

The data of 563 HCC patients with MVI after hepatectomy from two hospitals were retrospectively reviewed. Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse early recurrence. The risk classification for early recurrence was established by using classification and regression tree (CART) analysis and validated by using two independent validation cohorts from two hospitals.

RESULTS

Multivariate analysis revealed that four indices, namely, infection of chronic viral hepatitis, MVI classification, tumour size, and serum alpha-fetoprotein (AFP), were independent prognostic factors for early recurrence in HCC patients with MVI. By CART analysis, MVI classification and serum AFP became the nodes of a decision tree and 3-stratification classifications that satisfactorily determined the risk of early recurrence were established. The area under the time-dependent receiver operating characteristic curve (AUC) values of the classification for early recurrence at 0.5, 1.0, and 2.0 years were 0.75, 0.73, and 0.71, respectively, which were all significantly higher than three common classic HCC stages (BCLC stage, Chinese stage, and TNM stage). The calibration curves showed good agreement between predictions by classification for early recurrence and actual survival outcomes. These prediction results also were confirmed in the independent internal and external validation cohorts.

CONCLUSIONS

The 3 stratification classifications enabled satisfactory risk evaluation of early recurrence in HCC patients with MVI after hepatectomy.

Prediction for Aggressiveness and Postoperative Recurrence of Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

To investigate the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and to evaluate their association with postoperative recurrence of HCC.

MATERIALS AND METHODS

This retrospective study included 147 patients with surgically confirmed HCCs who underwent gadoxetic-enhanced MRI. The lesions were evaluated quantitatively in terms of the relative enhancement ratio (RER), and qualitatively based on imaging features and clinical parameters. Logistic regression analyses were performed to investigate the value of these parameters in predicting the pathologic grade, MVI, and CK19 in HCC. Predictive factors for postoperative recurrence were determined using a Cox proportional hazards model.

RESULTS

Peritumoral enhancement (odds ratio [OR], 3.396; p = 0.025) was an independent predictor of high pathologic grades. Serum protein induced by vitamin K absence or antagonist (PIVKA) level > 40 mAU/mL (OR, 3.763; p = 0.018) and peritumoral hypointensity (OR, 4.343; p = 0.003) were independent predictors of MVI. Predictors of CK19 included serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 4.576; p = 0.005), rim enhancement (OR, 5.493; p = 0.024), and lower RER (OR, 0.013; p = 0.011). Peritumoral hypointensity (hazard ratio [HR], 1.957; p = 0.027) and poor pathologic grades (HR, 2.339; p = 0.043) were independent predictors of recurrence.

CONCLUSION

We demonstrated the value of preoperative gadoxetic-enhanced MRI in predicting aggressive pathological features of HCC. Poor pathologic grades and peritumoral hypointensity may independently predict the recurrence of HCC.

Accurate prediction of microvascular invasion occurrence and effective prognostic estimation for patients with hepatocellular carcinoma after radical surgical treatment

Background

Hepatocellular carcinoma (HCC) is the third most common cause of cancer death worldwide, with an overall 5-year survival rate of less than 18%, which may be related to tumor microvascular invasion (MVI). This study aimed to compare the clinical prognosis of HCC patients with or without MVI after radical surgical treatment, and further analyze the preoperative risk factors related to MVI to promote the development of a new treatment strategy for HCC.

Methods

According to the postoperative pathological diagnosis of MVI, 160 study patients undergoing radical hepatectomy were divided into an MVI-negative group (n = 68) and an MVI-positive group (n = 92). The clinical outcomes and prognosis were compared between the two groups, and then the parameters were analyzed by multivariate logistic regression to construct an MVI prediction model. Then, the practicability and validity of the model were evaluated, and the clinical prognosis of different MVI risk groups was subsequently compared.

Result

There were no significant differences between the MVI-negative and MVI-positive groups in clinical baseline, hematological, or imaging data. Additionally, the clinical outcome comparison between the two groups presented no significant differences except for the pathological grading (P = 0.002) and survival and recurrence rates after surgery (P < 0.001). The MVI prediction model, based on preoperative AFP, tumor diameter, and TNM stage, presented superior predictive efficacy (AUC = 0.7997) and good practicability (high H-L goodness of fit, P = 0.231). Compared with the MVI high-risk group, the patients in the MVI low-risk group had a higher survival rate (P = 0.002) and a lower recurrence rate (P = 0.004).

Conclusion

MVI is an independent risk factor for a poor prognosis after radical resection of HCC. The MVI prediction model, consisting of AFP, tumor diameter, and TNM stage, exhibits superior predictive efficacy and strong clinical practicability for MVI prediction and prognostication, which provides a new therapeutic strategy for the standardized treatment of HCC patients.

Novel postoperative nomograms for predicting individual prognoses of hepatitis B-related hepatocellular carcinoma with cirrhosis

Background

Liver cirrhosis is a well-known risk factor for carcinogenesis of hepatocellular carcinoma (HCC). The aim of the present study was to construct individual prognostic models for HCC with cirrhosis.

Methods

The clinical differences between HCC patients with and without cirrhosis were compared using a large cohort of 1003 cases. The patients with cirrhosis were randomly divided into a training cohort and a validation cohort in a ratio of 2:1. Univariate and multivariate analyses were performed to reveal the independent risk factors for recurrence-free survival (RFS) and overall survival (OS) in HCC patients with cirrhosis. These factors were subsequently used to construct nomograms.

Results

Multivariate analyses revealed that five clinical variables (hepatitis B e antigen (HBeAg) positivity, alpha-fetoprotein (AFP) level, tumour diameter, microvascular invasion (MVI), and satellite lesions) and seven variables (HBeAg positivity, AFP level, tumour diameter, MVI, satellite lesions, gamma-glutamyl transpeptidase level, and histological differentiation) were significantly associated with RFS and OS, respectively. The C-indices of the nomograms for RFS and OS were 0.739 (P < 0.001) and 0.789 (P < 0.001), respectively, in the training cohort, and 0.752 (P < 0.001) and 0.813 (P < 0.001), respectively, in the validation cohort. The C-indices of the nomograms were significantly higher than those of conventional staging systems (P < 0.001). The calibration plots showed optimal consistence between the nomogram-predicted and observed prognoses.

Conclusions

The nomograms developed in the present study showed good performance in predicting the prognoses of HCC patients with hepatitis B virus-associated cirrhosis.

A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy

INTRODUCTION

Microvascular invasion (MVI) is a known risk factor for prognosis after R0 liver resection for hepatocellular carcinoma (HCC). The aim of this study was to develop a deep learning prognostic prediction model by incorporating a new factor of MVI area to the other independent risk factors.

METHODS

Consecutive patients with HCC who underwent R0 liver resection from January to December 2016 at the Eastern Hepatobiliary Surgery Hospital were included in this retrospective study. For patients with MVI detected on resected specimens, they were divided into two groups according to the size of the maximal MVI area: the small-MVI group and the large-MVI group.

RESULTS

Of 193 patients who had MVI in the 337 HCC patients, 130 patients formed the training cohort and 63 patients formed the validation cohort. The large-MVI group of patients had worse overall survival (OS) when compared with the small-MVI group (p = 0.009). A deep learning model was developed based on the following independent risk factors found in this study: MVI stage, maximal MVI area, presence/absence of cirrhosis, and maximal tumor diameter. The areas under the receiver operating characteristic of the deep learning model for the 1-, 3-, and 5-year predictions of OS were 80.65, 74.04, and 79.44, respectively, which outperformed the traditional COX proportional hazards model.

CONCLUSION

The deep learning model, by incorporating the maximal MVI area as an additional prognostic factor to the other previously known independent risk factors, predicted more accurately postoperative long-term OS for HCC patients with MVI after R0 liver resection.

Radiomic analysis based on multi-phase magnetic resonance imaging to predict preoperatively microvascular invasion in hepatocellular carcinoma

BACKGROUND

The prognosis of hepatocellular carcinoma (HCC) remains poor and relapse occurs in more than half of patients within 2 years after hepatectomy. In terms of recent studies, microvascular invasion (MVI) is one of the potential predictors of recurrence. Accurate preoperative prediction of MVI is potentially beneficial to the optimization of treatment planning.

AIM

To develop a radiomic analysis model based on pre-operative magnetic resonance imaging (MRI) data to predict MVI in HCC.

METHODS

A total of 113 patients recruited to this study have been diagnosed as having HCC with histological confirmation, among whom 73 were found to have MVI and 40 were not. All the patients received preoperative examination by Gd-enhanced MRI and then curative hepatectomy. We manually delineated the tumor lesion on the largest cross-sectional area of the tumor and the adjacent two images on MRI, namely, the regions of interest. Quantitative analyses included most discriminant factors (MDFs) developed using linear discriminant analysis algorithm and histogram analysis with MaZda software. Independent significant variables of clinical and radiological features and MDFs for the prediction of MVI were estimated and a discriminant model was established by univariate and multivariate logistic regression analysis. Prediction ability of the above-mentioned parameters or model was then evaluated by receiver operating characteristic (ROC) curve analysis. Five-fold cross-validation was also applied via R software.

RESULTS

The area under the ROC curve (AUC) of the MDF (0.77-0.85) outperformed that of histogram parameters (0.51-0.74). After multivariate analysis, MDF values of the arterial and portal venous phase, and peritumoral hypointensity in the hepatobiliary phase were identified to be independent predictors of MVI (P < 0.05). The AUC value of the model was 0.939 [95% confidence interval (CI): 0.893-0.984, standard error: 0.023]. The result of internal five-fold cross-validation (AUC: 0.912, 95%CI: 0.841-0.959, standard error: 0.0298) also showed favorable predictive efficacy.

CONCLUSION

Noninvasive MRI radiomic model based on MDF values and imaging biomarkers may be useful to make preoperative prediction of MVI in patients with primary HCC.

Efficacy of Postoperative Adjuvant Transcatheter Arterial Chemoembolization in Hepatocellular Carcinoma Patients With Microscopic Portal Vein Invasion

Background

Microscopic portal vein invasion (MPVI) strongly predicts poor prognosis in patients with hepatocellular carcinoma (HCC). This study aims to investigate the impact of MPVI on the efficacy of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE).

Methods

From April 2014 to July 2019, a total of 512 HCC patients who underwent curative liver resection (LR) with microscopic vascular invasion (MVI) confirmed by histopathological examination were enrolled and divided into LR alone and PA-TACE groups. They were subsequently stratified into subgroups according to the presence of MPVI. Recurrence-free survival (RFS) and overall survival (OS) were compared using Kaplan–Meier curves and the log-rank test. The efficacy of PA-TACE was tested using univariate and multivariate Cox regression analyses. Sensitivity analysis was conducted after propensity score matching (PSM).

Results

Among all patients, 165 (32.3%) patients underwent PA-TACE, and 196 (38.2%) patients presented MPVI. In the entire cohort, PA-TACE and the presence of MPVI were identified as independent predictors for RFS and OS (all p<0.05). In the subgroup analysis, patients without MPVI who received PA-TACE had significantly better outcomes than those who underwent LR alone before and after PSM (all p<0.05). For patients with MPVI, PA-TACE displayed no significant benefit in terms of improving either RFS or OS, which was consistent with the results from the PSM cohort.

Conclusion

Among the HCC patients without MPVI who underwent curative liver resection, those who received PA-TACE had better RFS and OS outcomes than those who underwent LR alone. For patients with MPVI, PA-TACE had no significant effect on either RFS or OS outcomes.

Deep-learning-based analysis of preoperative MRI predicts microvascular invasion and outcome in hepatocellular carcinoma

Background

Preoperative prediction of microvascular invasion (MVI) is critical for treatment strategy making in patients with hepatocellular carcinoma (HCC). We aimed to develop a deep learning (DL) model based on preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict the MVI status and clinical outcomes in patients with HCC.

Methods

We retrospectively included a total of 321 HCC patients with pathologically confirmed MVI status. Preoperative DCE-MRI of these patients were collected, annotated, and further analyzed by DL in this study. A predictive model for MVI integrating DL-predicted MVI status (DL-MVI) and clinical parameters was constructed with multivariate logistic regression.

Results

Of 321 HCC patients, 136 patients were pathologically MVI absent and 185 patients were MVI present. Recurrence-free survival (RFS) and overall survival (OS) were significantly different between the DL-predicted MVI-absent and MVI-present. Among all clinical variables, only DL-predicted MVI status and a-fetoprotein (AFP) were independently associated with MVI: DL-MVI (odds ratio [OR] = 35.738; 95% confidence interval [CI] 14.027–91.056; p < 0.001), AFP (OR = 4.634, 95% CI 2.576–8.336; p < 0.001). To predict the presence of MVI, DL-MVI combined with AFP achieved an area under the curve (AUC) of 0.824.

Conclusions

Our predictive model combining DL-MVI and AFP achieved good performance for predicting MVI and clinical outcomes in patients with HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02645-8.

Pyroptosis-Related Patterns Predict Tumor Immune Landscape and Immunotherapy Response in Bladder Cancer

Background: Bladder cancer (BC) is a leading cause of death from malignancy, with significant heterogeneity in the immunotherapeutic responsiveness of advanced status. Pyroptosis, a newly discovered inflammatory programmed cell death, is confirmed to play an indispensable role in tumorigenesis and anti-tumor activity. However, the effect of pyroptosis on the tumor-immune landscape remodeling and immunotherapy in BC remains elusive.

Methods: We comprehensively evaluated the mRNA expression and genomic alterations of 33 pyroptosis-related genes (PRGs) in BC and evaluated the patterns of pyroptosis in publicly available BC datasets. An unsupervised clustering method was used to classify patients into distinct patterns. Then, we established a pyroptosis-related signature score (PS-score) model to quantify the pyroptosis-related patterns of individual BC patients using principal component analysis. Furthermore, we correlated the patterns with the immune landscape and response efficacy of immunotherapy.

Results: Two pyroptosis-related patterns were identified in BC, and distinct patterns showed various immune characteristics. Patterns with a high expression level of PRGs exhibited a survival advantage and showed higher infiltration of cytotoxic lymphocytes. Tumors with a low PS-score were characterized by high tumor-infiltrating lymphocytes and considered “hot.” Further analysis revealed that the PS-score was an independent prognostic factor and could predict the response to immunotherapy for patients with advanced BC. We found a significant positive association between AHNAK2, AHNAK nucleoprotein 2, expression, and PS-score. Functional assays showed that AHNAK2 knockdown was correlated with attenuated invasive ability.

Conclusion: This work comprehensively demonstrated the potential function of pyroptosis-related patterns in the bladder tumor-immune landscape and identified their therapeutic liability in immunotherapy. Our study enhanced our understanding of the immune landscape and provided a new approach toward more effective immunotherapy strategies.

Preoperative Prediction of Microvascular Invasion Risk Grades in Hepatocellular Carcinoma Based on Tumor and Peritumor Dual-Region Radiomics Signatures

Objective

To predict preoperative microvascular invasion (MVI) risk grade by analyzing the radiomics signatures of tumors and peritumors on enhanced magnetic resonance imaging (MRI) images of hepatocellular carcinoma (HCC).

Methods

A total of 501 HCC patients (training cohort n = 402, testing cohort n = 99) who underwent preoperative Gd-EOB-DTPA-enhanced MRI and curative liver resection within a month were studied retrospectively. Radiomics signatures were selected using the least absolute shrinkage and selection operator (Lasso) algorithm. Unimodal radiomics models based on tumors and peritumors (10mm or 20mm) were established using the Logistic algorithm, using plain T1WI, arterial phase (AP), portal venous phase (PVP), and hepatobiliary phase (HBP) images. Multimodal radiomics models based on different regions of interest (ROIs) were established using a combinatorial modeling approach. Moreover, we merged radiomics signatures and clinico-radiological features to build unimodal and multimodal clinical radiomics models.

Results

In the testing cohort, the AUC of the dual-region (tumor & peritumor 20 mm)radiomics model and single-region (tumor) radiomics model were 0.741 vs 0.694, 0.733 vs 0.725, 0.667 vs 0.710, and 0.559 vs 0.677, respectively, according to AP, PVP, T1WI, and HBP images. The AUC of the final clinical radiomics model based on tumor and peritumoral 20mm incorporating radiomics features in AP&PVP&T1WI images for predicting MVI classification in the training and testing cohorts were 0.962 and 0.852, respectively.

Conclusion

The radiomics signatures of the dual regions for tumor and peritumor on AP and PVP images are of significance to predict MVI.

New Insights Into a Classification-Based Microvascular Invasion Prediction Model in Hepatocellular Carcinoma: A Multicenter Study

Background and Aims

Most microvascular invasion (MVI)-predicting models have not considered MVI classification, and thus do not reflect true MVI effects on prognosis of patients with hepatocellular carcinoma (HCC). We aimed to develop a novel MVI-predicting model focused on MVI classification, hoping to provide useful information for clinical treatment strategy decision-making.

Methods

A retrospective study was conducted with data from two Chinese medical centers for 800 consecutive patients with HCC (derivation cohort) and 250 matched patients (external validation cohort). MVI-associated variables were identified by ordinal logistic regression. Predictive models were constructed based on multivariate analysis results and validated internally and externally. The models' discriminative ability and calibration ability were examined.

Results

Four factors associated independently with MVI: tumor diameter, tumor number, serum lactate dehydrogenase (LDH) ≥ 176.58 U/L, and γ-glutamyl transpeptidase (γ-GGT). Area under the curve (AUC)s for our M2, M1, and M0 nomograms were 0.864, 0.648, and 0.782. Internal validation of all three models was confirmed with AUC analyses in D-sets (development datasets) and V-sets (validation datasets) and C-indices for each cohort. GiViTI calibration belt plots and Hosmer-Lemeshow (HL) chi-squared calibration values demonstrated good consistency between observed frequencies and predicted probabilities for the M2 and M0 nomograms. Although the M1 nomogram was well calibrated, its discrimination was poor.

Conclusion

We developed and validated MVI prediction models in patients with HCC that differentiate MVI classification and may provide useful guidance for treatment planning.

Image-matching digital macro-slide-a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma

Background

Microvascular invasion (MVI) is a prominent risk factor of postoperative recurrence for hepatocellular carcinoma (HCC). The MVI detection rate of conventional pathological examination approaches is relatively low and unsatisfactory.

Methods

By integrating pathological macro-slide with whole-mount slide imaging, we first created a novel pathological examination method called image-matching digital macro-slide (IDS). Surgical samples from eligible patients were collected to make IDS. The MVI detection rates, tumor recurrence rates and recurrence-free survival were compared among conventional 3-Point and 7-Point baseline sampling protocols and IDS. Additionally, biomarkers to recognize MVI false negative patients were probed via combining conventional pathological sampling protocols and IDS. Receiver operating characteristic curve (ROC) analysis was used to obtain the optimal cutoff of biomarkers to distinguish MVI false negative patients.

Results

The MVI detection rates were 21.98%, 32.97% and 63.74%, respectively, in 3-Point, 7-Point baseline sampling protocols and IDS (p < 0.001). Tumor recurrence rate of patients with MVI negative status in IDS (6.06%) was relatively lower than that of patients with MVI negative status in 3-Point (16.90%) and 7-Point (16.39%) sampling protocols. Alpha-fetoprotein (AFP) and protein induced by vitamin K absence or antagonist-II (PIVKA-II) were selected as potential biomarkers to distinguish MVI false negative patients.

Conclusions

Our study demonstrated that IDS can help enhance the detection rate of MVI in HCC and refine the prediction of HCC prognosis. Alpha-fetoprotein is identified as a suitable and robust biomarker to recognize MVI false-negative patients in conventional pathological protocols.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12072-022-10307-w.

Dynamic Contrast-Enhanced Ultrasonography with Sonazoid for Diagnosis of Microvascular Invasion in Hepatocellular Carcinoma

The aim of the present study was to investigate the imaging features observed in pre-operative Sonazoid contrast-enhanced ultrasound (SZ-CEUS) and the correlations with the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) patients. In this single-center retrospective study, 31 patients with surgically and histopathologically confirmed HCC lesions were included. Patients were classified according to the presence of MVI into the MVI-positive group (n = 15) and MVI-negative group (n = 16). The CEUS examinations were performed within 2 or 3 d before surgery. Features, including tumor necrosis and ultrasound contrast agent (UCA) distribution characteristics in the arterial phase (AP), tumor types (single nodular [SN] or non-single nodular [non-SN]) in the post-vascular phase (PVP), wash-in time, wash-in slope, time to peak (TTP) and peak intensity (PI), were assessed. Univariate analysis revealed statistically significant differences between the two groups with respect to tumor necrosis (p = 0.002), inhomogeneous distribution of contrast agent in the AP (p = 0.001) and non-SN type in the PVP (p < 0.001). There was no significant difference in the quantitative parameters. Multivariate analysis revealed that non-SN type in the PVP was a significant independent risk factor for MVI of HCC (odds ratio = 30.51, 95% confidence interval [CI]: 2.335-398.731, p = 0.009). The area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 0.873, 93.3%, 81.3%, 82.4% and 92.9%, respectively. Thus, SZ-CEUS can provide useful information for the diagnosis of MVI in HCC.

Cancer Genomic Alterations Can Be Potential Biomarkers Predicting Microvascular Invasion and Early Recurrence of Hepatocellular Carcinoma

Background

High recurrence incidence and poor survival after hepatectomy are enormous threats to hepatocellular carcinoma (HCC) patients, which can be caused by microvascular invasion (MVI). However, it is difficult to predict preoperative MVI status. In this study, we focus on cancer genomic alterations to comprehensively explore potential MVI and early recurrence biomarkers and provide clues to the mechanisms of HCC invasion and metastasis.

Methods

Forty-one patients with initially suspected HCC who were undergoing hepatectomy were finally enrolled. High-throughput targeted sequencing was performed on genomic alterations in their preoperative plasma and surgical fresh tumor tissues utilizing the 1,021-gene panel.

Results

HCC patients without MVI had longer RFS than MVI ones (p < 0.0001). The mutant incidence of genes like KEAP1, TP53, HIST1H3D, NFKBIA, PIK3CB, and WRN was higher in both MVI and early-recurrence patients than their counterparts. Besides, the alteration rates of Rap1 and Ras signaling pathways were significantly higher in MVI patients than NMVI ones (p < 0.05), and a similar trend of differences was also found in early-recurrence/non-recurrence comparison. The maximal variant allele frequency (VAF) of circulating tumor DNA (ctDNA) was statistically higher in MVI patients than NMVI ones (0.038 vs. 0.012, p = 0.0048). With the cutoff value of 0.018, ctDNA maximal VAF could potentially predict the presence of MVI with an AUC of 0.85 (95% CI 0.693–0.998, p = 0.0062).

Conclusion

The integration of a panel containing specific mutated genes and ctDNA maximal VAF for predicting MVI and early recurrence of HCC may achieve better performance.

MR Elastography-Based Shear Strain Mapping for Assessment of Microvascular Invasion in Hepatocellular Carcinoma

OBJECTIVES

To evaluate the potential of MR elastography (MRE)-based shear strain mapping to noninvasively predict the presence of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

METHODS

Fifty-nine histopathology-proven HCC patients with conventional 60-Hz MRE examinations (+/-MVI, n = 34/25) were enrolled retrospectively between December 2016 and October 2019, with one subgroup comprising 29/59 patients (+/-MVI, n = 16/13) who also underwent 40- and 30-Hz MRE examinations. Octahedral shear strain (OSS) maps were calculated, and the percentage of peritumoral interface length with low shear strain (i.e., a low-shear-strain length, pLSL, %) was recorded. For OSS-pLSL, differences between the MVI (+) and MVI (-) groups and diagnostic performance at different MRE frequencies were analyzed using the Mann-Whitney test and area under the receiver operating characteristic curve (AUC), respectively.

RESULTS

The peritumor OSS-pLSL was significantly higher in the MVI (+) group than in the MVI (-) group at the three frequencies (all p < 0.01). The AUC of peritumor OSS-pLSL for predicting MVI was good/excellent in all frequency groups (60-Hz: 0.73 (n = 59)/0.80 (n = 29); 40-Hz: 0.84; 30-Hz: 0.90). On further analysis of the 29 cases with all frequencies, the AUCs were not significantly different. As the frequency decreased from 60-Hz, the specificity of OSS increased at 40-Hz (53.8-61.5%) and further increased at 30-Hz (53.8-76.9%), and the sensitivity remained high at lower frequencies (100.0-93.8%) (all p > 0.05).

CONCLUSIONS

MRE-based shear strain mapping is a promising technique for noninvasively predicting the presence of MVI in patients with HCC, and the most recommended frequency for OSS is 30-Hz.

KEY POINTS

• MR elastography (MRE)-based shear strain mapping has the potential to predict the presence of microvascular invasion (MVI) in hepatocellular carcinoma preoperatively. • The low interface shear strain identified at tumor-liver boundaries was highly correlated with the presence of MVI.

Prognostic Impact of Surgical Margin in Hepatectomy on Patients With Hepatocellular Carcinoma: A Meta-Analysis of Observational Studies

Objective

This study aims to comprehensively evaluate the prognostic impact of the surgical margin in hepatectomy on patients diagnosed with hepatocellular carcinoma (HCC).

Methods

A comprehensive and systematic search for eligible articles published in English before July 2021 was conducted across PubMed, Cochrane Library, Web of Science, and Embase electronic databases. The overall survival (OS) and disease-free survival (DFS) were the primary endpoints.

Results

In total, 37 observational studies with 12,295 cases were included in this meta-analysis. The results revealed that a wide surgical margin (≥1 cm) was associated with better OS (hazard ration (HR), 0.70; 95% confidence interval (CI), 0.63–0.77) and DFS (HR, 0.66; 95% CI, 0.61–0.71) compared to a narrow surgical margin (<1 cm). Subgroup analyses were conducted based on median follow-up time, gender, country, hepatitis B surface antigen (HBsAg) status, tumor number, and liver cirrhosis. The prognostic benefit of a wide surgical margin was consistent in most subgroups, however, analysis of studies from Western countries showed that margin width was not associated with prognosis.

Conclusion

In summary, a surgical margin wider than 1 cm prolongs the long-term prognosis of HCC patients compared to a surgical margin narrower than 1 cm.

A novel classification in predicting prognosis and guiding postoperative management after R0 liver resection for patients with hepatocellular carcinoma and microvascular invasion

BACKGROUND

Microvascular invasion (MVI) is a significant risk factor affecting survival outcomes of patients after R0 liver resection (LR) for hepatocellular carcinoma (HCC). The current classification of MVI is not refined enough to prognosticate long-term survival of these patients, and a new MVI classification is needed.

METHODS

Patients with HCC who underwent R0 LR at the Eastern Hepatobiliary Surgery Hospital from January 2013 to December 2013 and with resected specimens showing MVI were included in this study with an aim to establish a novel MVI classification. The classification which was developed using multivariate cox regression analysis was externally validated.

RESULTS

There were 180 patients in the derivation cohort and 131 patients in the external validation cohort. The following factors were used for scoring: α-fetoprotein level (AFP), liver cirrhosis, tumor number, tumor diameter, MVI number, and distance between MVI and HCC. Three classes of patients could be distinguished by using the total score: class A, ≤3 points; class B, 3.5-5 points and class C, >5 points with distinct long-term survival outcomes (median recurrence free survival (mRFS), 22.6, 10.2, and 1.9 months, P < 0.001). The predictive accuracy of this classification was more accurate than the other commonly used classifications for HCC patients with MVI. In addition, the mRFS of class C patients was significantly prolonged (1.9 months vs. 6.2 months, P < 0.001) after adjuvant transcatheter arterial chemoembolization (TACE).

CONCLUSIONS

A novel MVI classification was established in predicting prognosis of HCC patients with MVI after R0 LR. Adjuvant TACE was useful for class C patients.

A predictive and prognostic model for hepatocellular carcinoma with microvascular invasion based TCGA database genomics

Background

Microvascular invasion (MVI) adversely affects postoperative long-term survival outcomes in patients with hepatocellular carcinoma (HCC). There is no study addressing genetic changes in HCC patients with MVI. We first screened differentially expressed genes (DEGs) in patients with and without MVI based on TCGA data, established a prediction model and explored the prognostic value of DEGs for HCC patients with MVI.

Methods

In this paper, gene expression and clinical data of liver cancer patients were downloaded from the TCGA database. The DEG analysis was conducted using DESeq2. Using the least absolute shrinkage and selection operator, MVI-status-related genes were identified. A Kaplan-Meier survival analysis was performed using these genes. Finally, we validated two genes, HOXD9 and HOXD10, using two sets of HCC tissue microarrays from 260 patients.

Results

Twenty-three MVI-status-related key genes were identified. Based on the key genes, we built a classification model using random forest and time-dependent receiver operating characteristic (ROC), which reached 0.814. Then, we performed a survival analysis and found ten genes had a significant difference in survival time. Simultaneously, using two sets of 260 patients’ HCC tissue microarrays, we validated two key genes, HOXD9 and HOXD10. Our study indicated that HOXD9 and HOXD10 were overexpressed in HCC patients with MVI compared with patients without MVI, and patients with MVI with HOXD9 and 10 overexpression had a poorer prognosis than patients with MVI with low expression of HOXD9 and 10.

Conclusion

We established an accurate TCGA database-based genomics prediction model for preoperative MVI risk and studied the prognostic value of DEGs for HCC patients with MVI. These DEGs that are related to MVI warrant further study regarding the occurrence and development of MVI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09047-1.

[Up-to-date Knowledge on the Pathological Diagnosis of Hepatocellular Carcinoma]

Hepatocellular carcinoma (HCC) has heterogeneous molecular and pathological features and biological behavior. Large-scale genetic studies of HCC were accumulated, and a pathological-molecular classification of HCC was proposed. Approximately 35% of HCCs can be classified into distinct histopathological subtypes according to their molecular characteristics. Among recently identified subtypes, macrotrabecular massive HCC, neutrophil-rich HCC, vessels encapsulating tumor clusters HCC, and progenitor phenotype HCC (HCC with CK19 expression) are associated with a poor prognosis, whereas the lymphocyte-rich HCC subtype is related to a better prognosis. This review provides up-to-date knowledge on the pathological diagnosis of HCC according to the updated World Health Organization Classification of Digestive System Tumors 5th ed.

Innovative Synoptic Reporting With Seven-Point Sampling Protocol to Improve Detection Rate of Microvascular Invasion in Hepatocellular Carcinoma

Pathological MVI diagnosis could help to determine the prognosis and need for adjuvant therapy in hepatocellular carcinoma (HCC). However, narrative reporting (NR) would miss relevant clinical information and non-standardized sampling would underestimate MVI detection. Our objective was to explore the impact of innovative synoptic reporting (SR) and seven-point sampling (SPRING) protocol on microvascular invasion (MVI) rate and patient outcomes. In retrospective cohort, we extracted MVI status from NR in three centers and re-reviewed specimen sections by SR recommended by the College of American Pathologists (CAP) in our center. In prospective cohort, our center implemented the SPRING protocol, and external centers remained traditional pathological examination. MVI rate was compared between our center and external centers in both cohorts. Recurrence-free survival (RFS) before and after implementation was calculated by Kaplan-Meier method and compared by the log-rank test. In retrospective study, we found there was no significant difference in MVI rate between our center and external centers [10.3% (115/1112) vs. 12.4% (35/282), P=0.316]. In our center, SR recommended by CAP improved the MVI detection rate from 10.3 to 38.6% (P<0.001). In prospective study, the MVI rate in our center under SPRING was significantly higher than external centers (53.2 vs. 17%, P<0.001). RFS of MVI (−) patients improved after SPRING in our center (P=0.010), but it remained unchanged in MVI (+) patients (P=0.200). We conclude that the SR recommended by CAP could help to improve MVI detection rate. Our SPRING protocol could help to further improve the MVI rate and optimize prognostic stratification for HCC patients.

An Oxidative Stress-Related Gene Pair (CCNB1/PKD1), Competitive Endogenous RNAs, and Immune-Infiltration Patterns Potentially Regulate Intervertebral Disc Degeneration Development

Oxidative stress (OS) irreversibly affects the pathogenesis of intervertebral disc degeneration (IDD). Certain non-coding RNAs act as competitive endogenous RNAs (ceRNAs) that regulate IDD progression. Analyzing the signatures of oxidative stress-related gene (OSRG) pairs and regulatory ceRNA mechanisms and immune-infiltration patterns associated with IDD may enable researchers to distinguish IDD and reveal the underlying mechanisms. In this study, OSRGs were downloaded and identified using the Gene Expression Omnibus database. Functional-enrichment analysis revealed the involvement of oxidative stress-related pathways and processes, and a ceRNA network was generated. Differentially expressed oxidative stress-related genes (De-OSRGs) were used to construct De-OSRG pairs, which were screened, and candidate De-OSRG pairs were identified. Immune cell-related gene pairs were selected via immune-infiltration analysis. A potential long non-coding RNA-microRNA-mRNA axis was determined, and clinical values were assessed. Eighteen De-OSRGs were identified that were primarily related to intricate signal-transduction pathways, apoptosis-related biological processes, and multiple kinase-related molecular functions. A ceRNA network consisting of 653 long non-coding RNA-microRNA links and 42 mRNA-miRNA links was constructed. Three candidate De-OSRG pairs were screened out from 13 De-OSRG pairs. The abundances of resting memory CD4+ T cells, resting dendritic cells, and CD8+ T cells differed between the control and IDD groups. CD8+ T cell infiltration correlated negatively with cyclin B1 (CCNB1) expression and positively with protein kinase D1 (PKD1) expression. CCNB1-PKD1 was the only pair that was differentially expressed in IDD, was correlated with CD8+ T cells, and displayed better predictive accuracy compared to individual genes. The PKD1-miR-20b-5p-AP000797 and CCNB1-miR-212-3p-AC079834 axes may regulate IDD. Our findings indicate that the OSRG pair CCNB1-PKD1, which regulates oxidative stress during IDD development, is a robust signature for identifying IDD. This OSRG pair and increased infiltration of CD8+ T cells, which play important roles in IDD, were functionally associated. Thus, the OSRG pair CCNB1-PKD1 is promising target for treating IDD.

Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals

BACKGROUND

The accuracy of estimating microvascular invasion (MVI) preoperatively in hepatocellular carcinoma (HCC) by clinical observers is low. Most recent studies constructed MVI predictive models utilizing radiological and/or radiomics features extracted from computed tomography (CT) images. These methods, however, rely heavily on human experiences and require manual tumor contouring. We developed a deep learning-based framework for preoperative MVI prediction by using CT images of arterial phase (AP) with simple tumor labeling and without the need of manual feature extraction. The model was further validated on CT images that were originally scanned at multiple different hospitals.

METHODS

CT images of AP were acquired for 309 patients from China Medical University Hospital (CMUH). Images of 164 patients, who took their CT scanning at 54 different hospitals but were referred to CMUH, were also collected. Deep learning (ResNet-18) and machine learning (support vector machine) models were constructed with AP images and/or patients' clinical factors (CFs), and their performance was compared systematically. All models were independently evaluated on two patient cohorts: validation set (within CMUH) and external set (other hospitals). Subsequently, explainability of the best model was visualized using gradient-weighted class activation map (Grad-CAM).

RESULTS

The ResNet-18 model built with AP images and patients' clinical factors was superior than other models achieving a highest AUC of 0.845. When evaluating on the external set, the model produced an AUC of 0.777, approaching its performance on the validation set. Model interpretation with Grad-CAM revealed that MVI relevant imaging features on CT images were captured and learned by the ResNet-18 model.

CONCLUSIONS

This framework provide evidence showing the generalizability and robustness of ResNet-18 in predicting MVI using CT images of AP scanned at multiple different hospitals. Attention heatmaps obtained from model explainability further confirmed that ResNet-18 focused on imaging features on CT overlapping with the conditions used by radiologists to estimate MVI clinically.

Systematic review and meta-analysis of validated prognostic models for resected hepatocellular carcinoma patients

BACKGROUND

Many prognostic models for Hepatocellular Carcinoma (HCC) have been developed to inform patients and doctors about individual prognosis. Previous reviews of these models were qualitative and did not assess performance at external validation. We assessed the performance of prognostic models for HCC and set a benchmark for biomarker studies.

METHODS

All externally validated models predicting survival for patients with resected HCC were systematically reviewed. After selection, we extracted descriptive statistics and aggregated c-indices using meta-analysis.

RESULTS

Thirty-eight validated prognostic models were included. Models used on average 7 (IQR:4-9) prognostic factors. Tumor size, tumor number, and vascular invasion were almost always included. Alpha-fetoprotein (AFP) was commonly incorporated since 2007. Recently, the more subjective items ascites and encephalopathy have been dropped. Eight established models performed poor to moderate at external validation, with a pooled C-index below 0.7; including the Barcelona Clinic Liver Cancer (BCLC) system, the American Joint Committee on Cancer (AJCC) 7th edition, the Cancer of the Liver Italian (CLIP) Program, and the Japan Integrated Staging (JIS) score. Out of 24 prognostic models predicting OS, only 6 (25%) had good performance at external validation with pooled C-indices above 0.7; the Li-post (0.77), Li-OS (0.74), Yang-pre (0.74), Yang-post (0.76), Shanghai-score (0.70), and Wang-nomogram (0.71). Models improved over time, but overall performance and study quality remained low.

CONCLUSIONS

Six validated prognostic models demonstrated good performance for predicting survival after resection of HCC. These models can guide patients and doctors and are a benchmark for future models incorporating novel biomarkers.

The impact of liver fibrosis on microvascular invasion and prognosis of hepatocellular carcinoma with a solitary nodule: a Surveillance, Epidemiology, and End Results (SEER) database analysis

Background

The pathogenesis of non-cirrhotic hepatocellular carcinoma (HCC) with a high recurrence remains controversial, while microvascular invasion (MVI) is highly suggestive of tumor recurrence. This study aimed to investigate the effects of liver fibrosis on MVI and prognosis in HCC.

Methods

Based on the data of HCC in the Surveillance, Epidemiology, and End Results (SEER) database [2004–2015], multivariate logistic regression was used for correlation analysis. Survival was analyzed by Log-Rank test and Cox regression, and decision curve analysis and receiver operating characteristic curves were established to evaluate alternative diagnostic and prognostic strategies.

Results

The study included 1,492 patients with MVI (17.8%) or without MVI (82.2%) for HCC with a solitary nodule. Liver fibrosis was significantly correlated with the occurrence of MVI, and the risk of MVI in patients with a fibrosis score F5–6 was lower than in those with a score of F0–4 (OR =0.651, 95% CI: 0.492–0.860). Combining liver fibrosis could improve the prediction performance of MVI risk models, but liver fibrosis was less associated with survival outcomes in comparison with other tumor characteristics.

Conclusions

Lower liver fibrosis correlated with a higher risk of MVI in HCC with a solitary nodule and was a good indicator for improving the performance of MVI risk models. However, it was not a prognostic sensitive indicator.

A Novel Ferroptosis-Related Prognostic Signature Reveals Macrophage Infiltration and EMT Status in Bladder Cancer

Bladder cancer (BC) belongs to one of the most common and highly heterogeneous malignancies. Ferroptosis is a newly discovered regulated cell death (RCD), characterized by accumulation of toxic lipid peroxides, and plays a crucial role in tumor progression. Here, we conducted a comprehensive analysis on the transcriptomics data of ferroptosis-related genes in BC based on The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets. In our study, a 6-gene signature was identified based on the potential prognostic ferroptotic regulatory genes. Furthermore, our signature revealed a good independent prognostic ability in BC. Patients with low-risk score exhibited higher FGFR3 mutation rates while high risk score had a positive association with higher RB1 mutation rates. Meanwhile, higher proportions of macrophages were observed in high BC risk group simultaneously with four methods. Unexpectedly, the risk score showed a significant positive correlation with epithelial-mesenchymal transition (EMT) status. Functional assays indicated that CRYAB and SQLE knockdown was associated with attenuated invasion capacity. Our study revealed a ferroptosis-related risk model for predicting prognostic and BC progression. Our results indicate that targeting ferroptosis may be a therapeutic strategy for BC.

Therapeutic efficacy of microwave coagulation versus liver resection for hepatocellular carcinoma within the Milan criteria: A propensity score matching analysis

INTRODUCTION

This study aimed to compare the therapeutic efficacy of resection (RES) and microwave ablation (MWA) for hepatocellular carcinoma (HCC) within the Milan criteria.

MATERIALS AND METHODS

Between 2011 and 2019, 426 HCC patients within the Milan criteria were treated at our institution (RES: n = 291; MWA: n = 135). We compared overall survival (OS), disease-free survival (DFS), complications, and hospital stay in these patients using propensity score matching (PSM) and determined the prognostic factors using multivariate Cox analysis.

RESULTS

Following 1:1 matching using PSM, 121 patients were matched in each group. The 1-, 3-, and 5-year OS rates were 98.3%, 84.7%, and 69.6% for the MWA group and 96.5%, 81.8%, and 78.1% for the RES group (p = 0.667). The corresponding DFS rates for the MWA and RES groups were 81.8%, 54.4%, and 42.3% and 85.4%, 67.8%, and 57.9%, respectively (p = 0.174). The MWA group had less blood loss and shorter hospital stays (both p < 0.001) than the RES group.

CONCLUSION

MWA resulted in survival outcomes that were similar to those of RES for HCC within the Milan criteria. However, it had more favorable hospital stay and blood loss outcomes than RES.

Microvascular invasion may be the determining factor in selecting TACE as the initial treatment in patients with hepatocellular carcinoma

ABSTRACT

The aim of this study was to investigate factors affecting tumor necrosis with transcatheter arterial chemoembolization (TACE). Factors associated with early hepatocellular carcinoma recurrence after curative hepatectomy were also evaluated.Data of 51 patients who underwent surgery after a single session of TACE at a single university hospital were retrospectively analyzed. Factors that might affect tumor necrosis were determined by evaluating the TACE approach and by analyzing computed tomography and TACE findings, pathologic reports, and laboratory findings.In univariate analysis, microvascular invasion (MVI), radiological capsule appearance on the computed tomography, chronic hepatitis B, diabetes mellitus and serum albumin, MVI were significantly associated with tumor necrosis by TACE (P < .02). In multivariate analysis, MVI was the only statistically significant factor in TACE-induced tumor necrosis (P = .001). In univariate and multivariate analysis, MVI was the strongest factor for recurrence-free survival rate within 2 years (P = .008, P = .002).MVI could be a crucial factor in determining TACE as an initial treatment for hepatocellular carcinoma. MVI is also a strong indicator of recurrence within 2 years after curative hepatic resection.

Preoperative nomogram for microvascular invasion prediction based on clinical database in hepatocellular carcinoma

The presence of microvascular invasion (MVI) is a critical determinant of early hepatocellular carcinoma (HCC) recurrence and prognosis. We developed a nomogram model integrating clinical laboratory examinations and radiological imaging results from our clinical database to predict microvascular invasion presence at preoperation in HCC patients. 242 patients with pathologically confirmed HCC at the Ningbo Medical Centre Lihuili Hospital from September 2015 to January 2021 were included in this study. Baseline clinical laboratory examinations and radiological imaging results were collected from our clinical database. LASSO regression analysis model was used to construct data dimensionality reduction and elements selection. Multivariate logistic regression analysis was performed to identify the independent risk factors associated with MVI and finally a nomogram for predicting MVI presence of HCC was established. Nomogram performance was assessed via internal validation and calibration curve statistics. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the nomogram model by quantifying the net benefits along with the increase in threshold probabilities. Survival analysis indicated that the probability of overall survival (OS) and recurrence-free survival (RFS) were significantly different between patients with MVI and without MVI (P < 0.05). Histopathologically identified MVI was found in 117 of 242 patients (48.3%). The preoperative factors associated with MVI were large tumor diameter (OR = 1.271, 95%CI: 1.137–1.420, P < 0.001), AFP level greater than 20 ng/mL (20–400 vs. ≤ 20, OR = 2.025, 95%CI: 1.056–3.885, P = 0.034; > 400 vs. ≤ 20, OR = 3.281, 95%CI: 1.661–6.480, P = 0.001), total bilirubin level greater than 23 umol/l (OR = 2.247, 95%CI: 1.037–4.868, P = 0.040). Incorporating tumor diameter, AFP and TB, the nomogram achieved a better concordance index of 0.725 (95%CI: 0.661–0.788) in predicting MVI presence. Nomogram analysis showed that the total factor score ranged from 0 to 160, and the corresponding risk rate ranged from 0.20 to 0.90. The DCA showed that if the threshold probability was > 5%, using the nomogram to diagnose MVI could acquire much more benefit. And the net benefit of the nomogram model was higher than single variable within 0.3–0.8 of threshold probability. In summary, the presence of MVI is an independent prognostic risk factor for RFS. The nomogram detailed here can preoperatively predict MVI presence in HCC patients. Using the nomogram model may constitute a usefully clinical tool to guide a rational and personalized subsequent therapeutic choice.

Establishment, validation and evaluation of predictive model for early relapse after R0 resection in hepatocellular carcinoma patients with microvascular invasion

Backgrounds

This is the first study to build and evaluate a predictive model for early relapse after R0 resection in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI).

Methods

The consecutive HCC patients with MVI who underwent hepatectomy in Cancer Hospital of Chinese Academy of Medical Science from Jan 2014 to June 2019 were retrospectively enrolled and randomly allocated into a derivation (N = 286) and validation cohort (N = 120) in a ratio of 7:3. Cox regression and Logistic regression analyses were performed and a predictive model for postoperative early-relapse were developed.

Results

A total of 406 HCC patients with MVI were included in our work. Preoperative blood alpha-fetoprotein (AFP) level, hepatitis B e antigen (HBeAg) status, MVI classification, largest tumor diameter, the status of serosal invasion, number of tumors, and the status of satellite nodules were incorporated to construct a model. The concordance index (C-index) was 0.737 and 0.736 in the derivation and validation cohort, respectively. The calibration curves showed a good agreement between actual observation and nomogram prediction. The C-index of the nomogram was obviously higher than those of the two traditional HCC staging systems.

Conclusion

We have developed and validated a prediction model for postoperative early-relapse in HCC patient with MVI after R0 resection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02940-0.