Tumor recurrence following liver transplantation for hepatocellular carcinoma: role of tumor proliferation status

MRI-based clinical-radiomics nomogram model for predicting microvascular invasion in hepatocellular carcinoma

BACKGROUND

Preoperative microvascular invasion (MVI) of liver cancer is an effective method to reduce the recurrence rate of liver cancer. Hepatectomy with extended resection and additional adjuvant or targeted therapy can significantly improve the survival rate of MVI+ patients by eradicating micrometastasis. Preoperative prediction of MVI status is of great clinical significance for surgical decision-making and the selection of other adjuvant therapy strategies to improve the prognosis of patients.

PURPOSE

Established a radiomics machine learning model based on multimodal MRI and clinical data, and analyzed the preoperative prediction value of this model for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

METHOD

The preoperative liver MRI data and clinical information of 130 HCC patients who were pathologically confirmed to be pathologically confirmed were retrospectively studied. These patients were divided into MVI-positive group (MVI+) and MVI-negative group (MVI-) based on postoperative pathology. After a series of dimensionality reduction analysis, six radiomic features were finally selected. Then, linear support vector machine (linear SVM), support vector machine with rbf kernel function (rbf-SVM), logistic regression (LR), Random forest (RF) and XGBoost (XGB) algorithms were used to establish the MVI prediction model for preoperative HCC patients. Then, rbf-SVM with the best predictive performance was selected to construct the radiomics score (R-score). Finally, we combined R-score and clinical-pathology-image independent predictors to establish a combined nomogram model and corresponding individual models. The predictive performance of individual models and combined nomogram was evaluated and compared by receiver operating characteristic curve (ROC).

RESULT

Alpha-fetoprotein concentration, peritumor enhancement, maximum tumor diameter, smooth tumor margins, tumor growth pattern, presence of intratumor hemorrhage, and RVI were independent predictors of MVI. Compared with individual models, the final combined nomogram model (AUC: 0.968, 95% CI: 0.920-1.000) constructed by radiometry score (R-score) combined with clinicopathological parameters and apparent imaging features showed the optimal predictive performance.

CONCLUSION

This multi-parameter combined nomogram model had a good performance in predicting MVI of HCC, and had certain auxiliary value for the formulation of surgical plan and evaluation of prognosis.

Machine Learning Pipeline for the Automated Prediction of MicrovascularInvasion in HepatocellularCarcinomas

Background: Microvascular invasion (MVI) is a necessary step in the metastatic evolution of hepatocellular carcinoma liver tumors. Predicting the onset of MVI in the initial stages of the tumors could improve patient survival and the quality of life. In this study, the possibility of using radiomic features to predict the presence/absence of MVI was evaluated. Methods: Multiphase contrast-enhanced computed tomography (CECT) images were collected from 49 patients, and the radiomic features were extracted from the tumor region and the zone of transition. The most-relevant features were selected; the dataset was balanced, and the presence/absence of MVI was classified. The dataset was split into training and test sets in three ways using cross-validation: the first applied feature selection and dataset balancing outside cross-validation; the second applied dataset balancing outside and feature selection inside; the third applied the entire pipeline inside the cross-validation procedure. Results: The features from the tumor areas on CECT showed both the portal and the arterial phases to be the most predictive. The three pipelines showed receiver operating characteristic area under the curve (ROC AUC) scores of 0.89, 0.84, and 0.61, respectively. Conclusions: The results obtained confirmed the efficiency of multiphase CECT and the ZOT in detecting MVI. The results showed a significant difference in the performance of the three pipelines, highlighting that a non-rigorous pipeline design could lead to model performance and generalization capabilities that are too optimistic.

MCM2 in human cancer: functions, mechanisms, and clinical significance

Background

Aberrant DNA replication is the main source of genomic instability that leads to tumorigenesis and progression. MCM2, a core subunit of eukaryotic helicase, plays a vital role in DNA replication. The dysfunction of MCM2 results in the occurrence and progression of multiple cancers through impairing DNA replication and cell proliferation.

Conclusions

MCM2 is a vital regulator in DNA replication. The overexpression of MCM2 was detected in multiple types of cancers, and the dysfunction of MCM2 was correlated with the progression and poor prognoses of malignant tumors. According to the altered expression of MCM2 and its correlation with clinicopathological features of cancer patients, MCM2 was thought to be a sensitive biomarker for cancer diagnosis, prognosis, and chemotherapy response. The anti-tumor effect induced by MCM2 inhibition implies the potential of MCM2 to be a novel therapeutic target for cancer treatment. Since DNA replication stress, which may stimulate anti-tumor immunity, frequently occurs in MCM2 deficient cells, it also proposes the possibility that MCM2 targeting improves the effect of tumor immunotherapy.

Automatically Extracted Machine Learning Features from Preoperative CT to Early Predict Microvascular Invasion in HCC: The Role of the Zone of Transition (ZOT)

Background: Microvascular invasion (MVI) is a consolidated predictor of hepatocellular carcinoma (HCC) recurrence after treatments. No reliable radiological imaging findings are available for preoperatively diagnosing MVI, despite some progresses of radiomic analysis. Furthermore, current MVI radiomic studies have not been designed for small HCC nodules, for which a plethora of treatments exists. This study aimed to identify radiomic MVI predictors in nodules ≤3.0 cm by analysing the zone of transition (ZOT), crossing tumour and peritumour, automatically detected to face the uncertainties of radiologist’s tumour segmentation. Methods: The study considered 117 patients imaged by contrast-enhanced computed tomography; 78 patients were finally enrolled in the radiomic analysis. Radiomic features were extracted from the tumour and the ZOT, detected using an adaptive procedure based on local image contrast variations. After data oversampling, a support vector machine classifier was developed and validated. Classifier performance was assessed using receiver operating characteristic (ROC) curve analysis and related metrics. Results: The original 89 HCC nodules (32 MVI+ and 57 MVI−) became 169 (62 MVI+ and 107 MVI−) after oversampling. Of the four features within the signature, three are ZOT heterogeneity measures regarding both arterial and venous phases. On the test set (19MVI+ and 33MVI−), the classifier predicts MVI+ with area under the curve of 0.86 (95%CI (0.70–0.93), p∼10−5), sensitivity = 79% and specificity = 82%. The classifier showed negative and positive predictive values of 87% and 71%, respectively. Conclusions: The classifier showed the highest diagnostic performance in the literature, disclosing the role of ZOT heterogeneity in predicting the MVI+ status.

Recurrence of hepatocellular carcinoma following deceased donor liver transplantation: case series

Aim

We aimed to study the clinical and pathological characteristics of liver transplant recipients with hepatocellular carcinoma recurrence.

Methods

We reviewed the data for 26 patients who had tumor recurrence after deceased donor liver transplant for hepatocellular carcinoma at the Johns Hopkins Hospital from January 2005 to December 2015.

Results

In total, 88% of recipients were males. The mean age was 59 years. On explant, poor differentiation was detected in 43%, while 73% had microvascular invasion. Overall, 62% were diagnosed to be outside of Milan criteria. Out of these, 15% met the criteria for downstaging. Twenty (77%) patients had pre-transplant alpha fetoprotein levels ≥ 20 ng/mL. In 54% of patients, the location of hepatocellular carcinoma (HCC) recurrence was extrahepatic, followed by intrahepatic in 31% and both intra- and extrahepatic in 15%. The post-transplant tumor recurrence was diagnosed at a mean of 427 days (range 34-1502). Fifty percent of HCC recurrences were diagnosed within one year following liver transplant. Twenty (77%) patients received treatment for their recurrent HCC: external radiation (n = 10), surgical resections (n = 8; brain 4, spine 2, bone 1, and Whipple surgery 1), sorafenib (n = 7), locoregional therapy (n = 5). Overall, 24 out of 26 (92%) recipients died within four years after the transplant.

Conclusion

HCC recurrence after liver transplant is infrequent. More than fifty percent of HCC recurrences following liver transplant are extrahepatic. Despite better recipient selection for liver transplant, the curative options are limited in recurrent cases and associated with extremely poor outcomes.

Direct Comparison of Four Presurgical Stratifying Schemes for Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Gadoxetic Acid-Enhanced MRI

BACKGROUND

Microvascular invasion (MVI) is implicated in the poor prognosis of hepatocellular carcinoma (HCC). Presurgical stratifying schemes have been proposed for HCC-MVI but lack external validation.

PURPOSE

To perform external validation and comparison of four presurgical stratifying schemes for the prediction of MVI using gadoxetic acid-based MRI in a cohort of HCC patients.

STUDY TYPE

Retrospective.

SUBJECTS

Included were 183 surgically resected HCCs from patients who underwent pretreatment MRI.

FIELD STRENGTH/SEQUENCE

This includes 1.5-3.0 T with T₂ , T₁ , diffusion-weighted imaging (DWI), and dynamic gadoxetic acid contrast-enhancement imaging sequences.

ASSESSMENT

A two-trait predictor of venous invasion (TTPVI), Lei model, Lee model, and Xu model were compared. We relied on preoperative characteristics and imaging findings via four independent radiologists who were blinded to histologic results, as required by the tested tools.

STATISTICAL TEST

Tests of accuracy between predicted and observed HCC-MVI rates using receiver operating characteristic (ROC) curve and decision curve analysis. The intraclass correlation coefficient (ICC) and Cronbach's alpha statistics were used to evaluate reproducibility.

RESULTS

HCC-MVI was identified in 52 patients (28.4%). The average ROC curves (AUCs) for HCC-MVI predictions were 0.709-0.880, 0.714-0.828, and 0.588-0.750 for the Xu model, Lei model, and Lee model, respectively. The rates of accuracy were 60.7-81.4%, 69.9-75.9%, and 65.6-73.8%, respectively. Decision curve analyses indicated a higher benefit for the Xu and Lei models compared to the Lee model. The ICC and Cronbach's alpha index were highest in the Lei model (0.896/0.943), followed by the Xu model (0.882/0.804), and the Lee model (0.769/0.715). The TTPVI resulted in a Cronbach's alpha index of 0.606 with a sensitivity of 34.6-61.5% and a specificity of 76.3-91.6%.

DATA CONCLUSION

Stratifying schemes relying on gadoxetic acid-enhanced MRI provide an additional insight into the presence of preoperative MVI. The Xu model outperformed the other models in terms of accuracy when performed by an experienced radiologist. Conversely, the Lei model outperformed the other models in terms of reproducibility.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:433-447.

Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma

BACKGROUND & AIMS

Microvascular invasion (MVI) impairs surgical outcomes in patients with hepatocellular carcinoma (HCC). As there is no single highly reliable factor to preoperatively predict MVI, we developed a computational approach integrating large-scale clinical and imaging modalities, especially radiomic features from contrast-enhanced CT, to predict MVI and clinical outcomes in patients with HCC.

METHODS

In total, 495 surgically resected patients were retrospectively included. MVI-related radiomic scores (R-scores) were built from 7,260 radiomic features in 6 target volumes. Six R-scores, 15 clinical factors, and 12 radiographic scores were integrated into a predictive model, the radiographic-radiomic (RR) model, with multivariate logistic regression.

RESULTS

Radiomics related to tumor size and intratumoral heterogeneity were the top-ranked MVI predicting features. The related R-scores showed significant differences according to MVI status (p <0.001). Regression analysis identified 8 MVI risk factors, including 5 radiographic features and an R-score. The R-score (odds ratio [OR] 2.34) was less important than tumor capsule (OR 5.12), tumor margin (OR4.20), and peritumoral enhancement (OR 3.03). The RR model using these predictors achieved an area under the curve (AUC) of 0.909 in training/validation and 0.889 in the test set. Progression-free survival (PFS) and overall survival (OS) were significantly different between the RR-predicted MVI-absent and MVI-present groups (median PFS: 49.5 vs. 12.9 months; median OS: 76.3 vs. 47.3 months). RR-computed MVI probability, histologic MVI, tumor size, and Edmondson-Steiner grade were independently associated with disease-specific recurrence and mortality.

CONCLUSIONS

The computational approach, integrating large-scale clinico-radiologic and radiomic features, demonstrates good performance for predicting MVI and clinical outcomes. However, radiomics with current CT imaging analysis protocols do not provide statistically significant added value to radiographic scores.

LAY SUMMARY

The most effective treatment for hepatocellular carcinoma (HCC) is surgical removal of the tumor but often recurrence occurs, partly due to the presence of microvascular invasion (MVI). Lacking a single highly reliable factor able to preoperatively predict MVI, we developed a computational approach to predict MVI and the long-term clinical outcome of patients with HCC. In particular, the added value of radiomics, a newly emerging form of radiography, was comprehensively investigated. This computational method can enhance the communication with the patient about the likely success of the treatment and guide clinical management, with the aim of finding drugs that reduce the risk of recurrence.

Clinicopathological Distinction of Low-AFP-Secreting vs. High-AFP-Secreting Hepatocellular Carcinomas

Ilntroduction and aims. We aimed to investigate the clinical and pathological differences between low-AFP-secreting (AFP < 20 ng/mL) and high-AFP-secreting (AFP ≥ 20 ng/mL) hepatocellular carcinomas in patients who undergo liver transplant (LT).

MATERIAL AND METHODS

We evaluated 145 patients who underwent deceased donor LT for HCC from January 1, 2005 until August 1, 2015 at the Johns Hopkins Hospital.

RESULTS

Median pre-LT AFP in the entire cohort was 13 ng/mL (IQR 6-59). Using serum AFP cutoff of 20 ng/mL, 61 (42%) patients had high-AFP-secreting tumors and 84 (58%) had low-AFP-secreting tumors. Patients with high-AFP-secreting tumors had larger lesions (3 cm vs. 2.4 cm, p = 0.024), and were more likely to have microvascular-invasion (36.1% vs. 20.2%, p = 0.02) and poor-differentiation (18% vs. 4.8%, p = 0.01), and tumor recurrence following LT (28% vs. 6%, p < 0.001). The 1-year, 3-year, and 5-year recurrence-free survival for patients in the low-AFP-secreting group compared to the high-AFP-secreting group were 100%, 92%, 92% vs. 81.3%, 71.3%, 68.5% respectively (p = 0.0003).

CONCLUSION

AFP is a suboptimal predictor of tumor recurrence following liver transplant in HCC patients. However, it can have some value in distinguishing more aggressive forms of HCC (high-AFP-secreting) that are associated with higher tumor recurrence. Novel tumor biomarkers are needed that can enhance predicting tumor recurrence following LT based on tumor biology.

Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

AIM

To discover methylated-differentially expressed genes (MDEGs) in hepatocellular carcinoma (HCC) and to explore relevant hub genes and potential pathways.

METHODS

The data of expression profiling GSE25097 and methylation profiling GSE57956 were gained from GEO Datasets. We analyzed the differentially methylated genes and differentially expressed genes online using GEO2R. Functional and enrichment analyses of MDEGs were conducted using the DAVID database. A protein-protein interaction (PPI) network was performed by STRING and then visualized in Cytoscape. Hub genes were ranked by cytoHubba, and a module analysis of the PPI network was conducted by MCODE in Cytoscape software.

RESULTS

In total, we categorized 266 genes as hypermethylated, lowly expressed genes (Hyper-LGs) referring to endogenous and hormone stimulus, cell surface receptor linked signal transduction and behavior. In addition, 161 genes were labelled as hypomethylated, highly expressed genes (Hypo-HGs) referring to DNA replication and metabolic process, cell cycle and division. Pathway analysis illustrated that Hyper-LGs were enriched in cancer, Wnt, and chemokine signalling pathways, while Hypo-HGs were related to cell cycle and steroid hormone biosynthesis pathways. Based on PPI networks, PTGS2, PIK3CD, CXCL1, ESR1, and MMP2 were identified as hub genes for Hyper-LGs, and CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10 were hub genes for Hypo-HGs by combining six ranked methods of cytoHubba.

CONCLUSION

In the study, we disclose numerous novel genetic and epigenetic regulations and offer a vital molecular groundwork to understand the pathogenesis of HCC. Hub genes, including PTGS2, PIK3CD, CXCL1, ESR1, MMP2, CDC45, DTL, AURKB, CDKN3, MCM2, and MCM10, can be used as biomarkers based on aberrant methylation for the accurate diagnosis and treatment of HCC.

Meta-analysis of gene expression profiles identifies differential biomarkers for hepatocellular carcinoma and cholangiocarcinoma

Hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) are the members of hepatobiliary diseases. Both types of cancer often exert high levels of similarity in terms of phenotypic characteristics, thus leading to difficulties in HCC and CCA differential diagnoses. In this study, a transcriptome meta-analysis was performed on HCC and CCA microarray data to identify differential transcriptome networks and potential biomarkers for HCC and CCA. Raw data from nine gene expression profiling datasets, consisting of 1,185 samples in total, were methodologically compiled and analyzed. To evaluate differentially expressed (DE) genes in HCC and CCA, the levels of gene expression were compared between cancer and its normal counterparts (i.e., HCC versus normal liver and CCA versus normal bile duct) using t test (P < 0.05) and k-fold validation. A total of 226 DE genes were specific to HCC, 249 DE genes specific to CCA, and 41 DE genes in both HCC and CCA. Gene ontology and pathway enrichment analyses revealed different patterns between functional transcriptome networks of HCC and CCA. Cell cycle and glycolysis/gluconeogenesis pathways were exclusively dysregulated in HCC whereas complement and coagulation cascades as well as glycine, serine, and threonine metabolism were prodominantly differentially expressed in CCA. Our meta-analysis revealed distinct dysregulation in transcriptome networks between HCC and CCA. Certain genes in these networks were discussed in the context of HCC and CCA transition, unique characteristics of HCC and CCA, and their potentials as HCC and CCA differential biomarkers.

Liver transplantation for advanced hepatocellular carcinoma: how far can we go?

Liver transplantation is one of the most effective treatment options for hepatocellular carcinoma. Although the Milan criteria have been widely used to identify suitable candidates for liver transplant with a good prognosis, many transplant centers have developed and actually used more expanded criteria. Living donor liver transplant (LDLT) is at the center of expansion of criteria because it is based on the personal relationship between a recipient and a donor. Asian LDLT centers have developed various expanded criteria for LDLT using tumor biologic markers as well as the size and number of the tumors. However, there is no consensus on the limit of the expansion of criteria. Here, we present our experience and opinion on LDLT for advanced hepatocellular carcinoma.

Impact of model for end-stage liver disease score on long-term survival following liver transplantation for hepatocellular carcinoma

BACKGROUND AND AIMS

Survival rates after orthotopic liver transplantation (OLT) for hepatocellular carcinoma (HCC) have significantly increased after Milan criteria and Model for End-Stage Liver Disease (MELD) score implementation. However, few studies have reported this survival in countries with organ donor shortages over a period of 10 years and long waiting lists.

METHODS

This retrospective analysis of clinical data from 93 consecutive HCC patients who underwent OLT from June 2001 to September 2011 excluded 22 who underwent living donor liver transplantation (LDLT). Seventy-one deceased donor liver transplantations (DDLT) were evaluated before and after the MELD era. Kaplan-Meier analysis was used to plot survival rates. The follow-up was 2 months to 10 years.

RESULTS

The overall survival and recurrence rates at 10 years were 67% and 12.2%, respectively. After MELD, patient survival at 5 years decreased from 70% to 64% and the recurrence rate decreased from 15.3% to 12.5%. The most frequent recurrence sites were lung and liver.

CONCLUSION

In our center MELD score implementation had a small impact on long-term survival post OLT for HCC.

Hepatocellular cancer and liver transplantation: a Western experience

Orthotopic liver transplantation is the preferred treatment option in patients with hepatocellular carcinoma developing in chronic liver disease. Unfortunately, based on classical transplantation criteria (Milan criteria), only a minority of patients with hepatocellular carcinoma are candidate to orthotopic liver transplantation. Major improvements in treatment strategy and surgical technique including the use of neoadjuvant locoregional therapies and progresses of post-transplant immunosuppressive treatment have contributed to safely expand transplantation criteria preserving acceptable surgical morbidity-mortality and good oncologic outcome. Further extension of transplantation criteria may have advantages including an increase in the number of transplant candidates and improvement of the prognosis of the disease and also disadvantages including an increase of surgical morbidity and deterioration of global oncologic outcome of orthotopic liver transplantation in hepatocellular carcinoma. In the future, identification of imaging or molecular prognostic markers could help to better define transplantation criteria.

Hepatectomy for hepatocellular carcinoma patients with macronodular cirrhosis

OBJECTIVE

Patients with hepatocellular carcinoma (HCC) presenting with nonmicronodular or micronodular cirrhosis are usually treated by hepatectomy. The value of resection for patients with hepatitis B virus-related macronodular cirrhosis, however, remains unknown because of potentially fatal complications of this procedure.

METHODS

Clinicopathological data were analyzed for 85 resected HCC patients with hepatitis B virus-related macronodular cirrhosis. An additional 255 patients with nonmicronodular and micronodular cirrhosis were randomly selected during the same period as the control group.

RESULTS

Compared with nonmicronodular and micronodular cirrhosis patients, macronodular cirrhotic patients exhibited elevated alanine aminotransferase, aspartate aminotransferase, and γ-glutamyltransferase levels, higher Child-Pugh classification, higher indocyanine green retention rate at 15 min (ICG R15), and more number of total complications. No significant differences were observed between the two groups with regard to major complications, mortality, overall survival, and recurrence-free survival. The morbidity rate was relatively low in patients exhibiting low ICG R15 (<10%). Cox analysis identified small tumors (≤ 5 cm) and radical resection as independent prognostic factors that could predict long-term overall survival. Radical resection can result in high recurrence-free survival in macronodular cirrhotic patients.

CONCLUSION

Resection is safe for macronodular cirrhotic HCC patients, and radical resection provides a positive outcome. Small-sized patients are good candidates for hepatectomy. Macronodular cirrhosis should not rule out hepatectomy in patients with low ICG R15.

Survival advantage of primary liver transplantation for hepatocellular carcinoma within the up-to-7 criteria with microvascular invasion

PURPOSE

Microvascular invasion of hepatocellular carcinoma (HCC) is considered a poor prognostic factor of liver resection (LR) and liver transplantation (LT), but its significance for lesions within the up-to-7 criteria is unclear. This study investigated the survival benefit of primary LT against LR for HCC with microvascular invasion and within the up-to-7 criteria.

METHODS

Adult patients who underwent LR or LT as the primary treatment for HCC were included for study. Patients with prior local ablation, neoadjuvant systemic chemotherapy, targeted therapy, positive resection margin, or metastatic spread were excluded.

RESULTS

There were 471 LR patients and 95 LT recipients (70 with living donor, 25 with deceased donor). Seventy-seven (81.1%) LT recipients had HCC within the up-to-7 criteria. Twenty-five (26.3%) LT recipients had HCC with either macrovascular (n = 4) or microvascular (n = 21) invasion. The 5-year survival rate was 85.7% for LT recipients with HCC within the up-to-7 criteria, unaffected by the presence or absence of vascular invasion (88.2 vs. 85.1%). The rate was comparable with that of LR patients with HCC without vascular invasion (81.2%, p 0.227), but far superior to that of LR patients with lesions with vascular invasion (50.0%, p < 0.0001). Overall survivals were compromised by multiple tumors [odds ratio (OR) 1.902, confidence interval (CI) 1.374-2.633, p = 0.0001], vascular invasion (OR 2.678, CI 1.952-3.674, p < 0.0001), blood transfusion (OR 2.046, CI 1.337-3.131, p = 0.001), and being beyond the up-to-7 criteria (OR 1.457, CI 1.041-2.037, p = 0.028). LT was a favorable factor for survival (OR 0.243, CI 0.130-0.454, p < 0.0001).

CONCLUSION

Primary LT for HCC with microvascular invasion and within the up-to-7 criteria doubled the chance of cure as compared with LR.

Molecular classification and clonal differentiation of hepatocellular carcinoma: the step forward for patient selection for liver transplantation

Liver transplantation is a successful treatment for hepatocellular carcinoma (HCC). However, advanced stages are not selected for transplant, based on the United Network for Organ Sharing selection criteria's. Nowadays, molecular biology-based techniques constitute an excellent option to better understand HCC origin differentiation and biological behavior. Moreover, microarray technology is a powerful tool to address a variety of tumor tissues at molecular level and is actively used for the discovery of biomarkers in cancer research. This article will discuss published data in the field of HCC origin differentiation and its potential impact on outcomes following liver transplantation. Although preliminary results are presented, these findings encourage the use of gene-expression profiling microarrays for studying HCC biology and behavior and ultimately optimizing treatment success.

[Liver transplantation in patients with hepatocellular carcinoma]

Hepatocellular carcinoma (HCC) is the third most common malignancy, with a new incidence of more than 11,000 cases per year and the second most common cause of malignancy-related death in Korean males. In Korea, more than 80% of all HCCs have developed from hepatitis B virus (HBV)-related cirrhotic livers. Liver transplantation (LT) is the only treatment that offers a chance of cure for HCC and the underlying liver cirrhosis simultaneously, but the availability of liver grafts and the aggressiveness of tumor recurrence are critical limiting factors of LT for HCC patients. The serious shortage of deceased-donors on strong demand for LT leads to the development of living-donor LT (LDLT) as a practical alternative replacing deceased-donor LT. Considering that HCC recurrence is the most common cause of posttransplant patient death, recipient candidates should be prudently selected through objectively established criteria. Uniquely, some Asian major LDLT centers challenged the Milan criteria, accepting a much higher number of HCC nodules instead of tumor size expansion. The eligibility criteria of LDLT for HCC are likely to be expanded more than before, but it still requires further qualified risk-benefit analyses. The development of new effective treatment modalities for HCC recurrence will reasonably expand the selection criteria further wide without the expense of recurrence rate. This article is mainly focused on the role of LT for HCC and discussed on the validity of currently available indication criteria.