Recurrence of Hepatocellular Carcinoma After Liver Transplantation: A Single-Center Experience

Hedgehog components are overexpressed in a series of liver cancer cases

Liver cancers, including hepatocellular carcinoma (HCC), are the sixth most common cancer and the third leading cause of cancer-related death worldwide, representing a global public health problem. This study evaluated nine patients with HCC. Six of the cases involved hepatic explants, and three involved hepatic segmentectomy for tumor resection. Eight out of nine tumors were HCC, with one being a combined hepatocellular-cholangiocarcinoma tumor. Conventional markers of hepatocellular differentiation (Hep Par-1, arginase, pCEA, and glutamine synthetase) were positive in all patients, while markers of hepatic precursor cells (CK19, CK7, EpCAM, and CD56) were negative in most patients, and when positive, they were detected in small, isolated foci. Based on in silico analysis of HCC tumors from The Cancer Genome Atlas database, we found that Hedgehog (HH) pathway components (GLI1, GLI2, GLI3 and GAS1) have high connectivity values (module membership > 0.7) and are strongly correlated with each other and with other genes in biologically relevant modules for HCC. We further validated this finding by analyzing the gene expression of HH components (PTCH1, GLI1, GLI2 and GLI3) in our samples through qPCR, as well as by immunohistochemical analysis. Additionally, we conducted a chemosensitivity analysis using primary HCC cultures treated with a panel of 18 drugs that affect the HH pathway and/or HCC. Most HCC samples were sensitive to sunitinib. Our results offer a comprehensive view of the molecular landscape of HCC, highlighting the significance of the HH pathway and providing insight into focused treatments for HCC.

Prediction of early recurrence of hepatocellular carcinoma after liver transplantation based on computed tomography radiomics nomogram

BACKGROUND

Early recurrence results in poor prognosis of patients with hepatocellular carcinoma (HCC) after liver transplantation (LT). This study aimed to explore the value of computed tomography (CT)-based radiomics nomogram in predicting early recurrence of patients with HCC after LT.

METHODS

A cohort of 151 patients with HCC who underwent LT between December 2013 and July 2019 were retrospectively enrolled. A total of 1218 features were extracted from enhanced CT images. The least absolute shrinkage and selection operator algorithm (LASSO) logistic regression was used for dimension reduction and radiomics signature building. The clinical model was constructed after the analysis of clinical factors, and the nomogram was constructed by introducing the radiomics signature into the clinical model. The predictive performance and clinical usefulness of the three models were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA), respectively. Calibration curves were plotted to assess the calibration of the nomogram.

RESULTS

There were significant differences in radiomics signature among early recurrence patients and non-early recurrence patients in the training cohort (P < 0.001) and validation cohort (P < 0.001). The nomogram showed the best predictive performance, with the largest area under the ROC curve in the training (0.882) and validation (0.917) cohorts. Hosmer-Lemeshow testing confirmed that the nomogram showed good calibration in the training (P = 0.138) and validation (P = 0.396) cohorts. DCA showed if the threshold probability is within 0.06-1, the nomogram had better clinical usefulness than the clinical model.

CONCLUSIONS

Our CT-based radiomics nomogram can preoperatively predict the risk of early recurrence in patients with HCC after LT.

T2 Hepatocellular Carcinoma Exception Policies That Prolong Waiting Time Improve the Use of Evidence-based Treatment Practices

Supplemental Digital Content is available in the text.

Background.

A United Network for Organ Sharing policy change in 2015 created a 6-mo delay in the receipt of T2 hepatocellular carcinoma exception points. It was hypothesized that the policy changed locoregional therapy (LRT) practices and explant findings because of longer expected waiting time.

Methods.

Patients transplanted with a first T2 hepatocellular carcinoma exception application between January 1, 2010 and December 31, 2014 (prepolicy; N = 6562), and those between August 10, 2015 and December 2, 2019 (postpolicy; N = 2345), were descriptively compared using data from United Network for Organ Sharing.

Results.

Median time from first application to transplantation was more homogenous across the US postpolicy, due to greater absolute increases in Regions 3, 6, 10, and 11 (>120 d). During waitlisting, postpolicy candidates received more LRT overall (P < 0.001), with more notable increases in previously short-wait regions. Postpolicy explants were overall more likely to have ≥1 tumor with complete necrosis (23.9 versus 18.4%; P < 0.001) and less likely have ≥1 tumor with no necrosis (32.6% versus 38.5%; P < 0.001). Significant geographic variability in explant treatment response was observed prepolicy with recipients in previously short-wait regions having more frequent tumor viability at transplant. Postpolicy, there were no differences in the prevalence of recipients with ≥1 tumor with 100% or 0% necrosis across regions (P = 0.9 and 0.2, respectively).

Conclusions.

The 2015 T2 exception policy has led to reduced geographic variability in the use of pretransplant LRT and in less frequent tumor viability on explant for recipients in previously short-waiting times.