Project description:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design
Project description:In this study we investigated the miRNA expression profile of Hepatocellular carcinoma (HCC) specimens from radical resection. We developed a unique 20 miRNA signature that could significantly distinguish HCC venous metastasis from metastasis-free HCC. In contrast to HCC staging systems, this signature was capable of predicting survival and recurrence of HCC patients with multinodular or solitary tumors, including those with early-stage disease. Moreover, the signature was an independent and significant predictor of patient prognosis and relapse when compared to other available clinical parameters. Our study suggests that these 20 miRNAs can enable HCC prognosis and may have clinical utility for the advance identification of HCC patients with a propensity towards metastasis/recurrence. Keywords: disease state design Gene expression profiles were conducted in primary HCC and corresponding noncancerous hepatic tissues from 244 Chinese HCC patients. A total of 134 well-defined cases were used as a training group. Among them, 30 had primary HCC lesions accompanied by tumor emboli and 104 had solitary HCC with no metastasis/recurrence found at follow-up (3 yr). We used a testing group of 110 independent cases. The testing cases included 43 multinodular and 67 solitary HCC. In addition, eight normal liver tissues from disease-free patients were included as normal controls. In the analysis of the 244 HCC cases, RNA was isolated in a pairwise fashion from tumor or non-tumor tissue and samples were selected in random order for miRNA analysis to avoid grouping bias.
Project description:In this study, we utilized microRNA expression profiling to assess risk of HCC recurrence after liver resection. We examined microRNA expression profiling in paired tumor and non-tumor liver tissues of 73 HCC patients with mild cirrhosis (Child-Pugh A/B) who satisfy Milan Criteria. We constructed prediction models of recurrence-free survival using Cox proportional hazard model and principal component analysis.
Project description:Background: Liver transplantation (LT) for Hepatocellular carcinoma (HCC) can be offered to patients beyond Milan criteria. However, there are currently no molecular markers that can be used on HCC explant histology to predict recurrence, which arises in up to 20% of LT recipients. The goal of our study was to identify proteins on HCC explant predictive of recurrence post-transplant, thereby guiding surveillance strategies and identifying patients beyond Milan criteria who would fare well following LT. Methods: LT recipients who had been transplanted at the University Health Network for HCC beyond Milan criteria in the context of Hepatitis B cirrhosis were identified. Snap-frozen samples from the dominant tumors of recurrent (N=7) and non-recurrent (N=4) patients were analyzed using LC-MS/MS on a Q-Exactive Plus mass spectrometer to delineate a distinctive proteomic signature. These tumors were also profiled by a Human Gene 2.0 ST microarray platform to identify a transcriptomic signature predictive of recurrence and analyzed with R packages. STRING database was used to characterize the implicated pathways. Kaplan-Meier estimator was used to generate a combined proteomic/transcriptomic signature predictive of HCC recurrence in patients with HCC beyond Milan criteria at time of LT. Significantly predictive proteins were verified and internally validated by immunoblotting or immunohistochemistry. Results: A total of 79 proteins and 636 genes were significantly differentially expressed in recurrent HCC, compared to non-recurrent (p<0.05). Among these, LGALS3, LGALS3BP, HAL, THBS1, and BLMH, were significantly increased in recurrent HCC at the protein and gene expression level. In turn, ALDH1A1 protein and gene expression were significantly decreased in recurrent HCC. Univariate survival analysis depicted ALDH1A1 (HR=0.084, 95%CI 0.01-0.68, p=0.02), LGALS3BP (HR=7.14, 95%CI 1.20-42.96, p=0.03), and LGALS3 (HR=2.89, 95%CI 1.01-8.3, p=0.049) as the key dysregulated proteins and genes in the patients with HCC recurrence versus those with non-recurrence by both proteomic and transcriptomic analysis. Decreased ALDH1A1 and significantly increased LGALS3 protein expression in recurrent HCC was verified by immunoblotting. Increased LGALS3BP protein expression in recurrent HCC was orthogonally verified and validated by immunohistochemistry in 30 independent HCC samples. Conclusion: Protein and gene expression of the cancer stem cell marker ALDH1A1 was protective against cancer recurrence in patients transplanted for HCC beyond Milan criteria. Conversely, increased expression of LGALS3 and LGALS3BP on explant was significantly predictive of post-transplant recurrence. These findings were internally validated, suggesting potential utility in identifying patients with HCC beyond Milan who would clearly benefit from transplant with limited recurrence risk and guiding post-transplant surveillance.
Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.
Project description:Background and aims: Liver transplantation (LT) is the most radical treatment for hepatocellular carcinoma (HCC) with high rates of long-term survival, but tumor recurrence after LT is an unresolved problem. The aim of our study was to identify predictive markers for tumor recurrence after liver transplantation. Methods: In a retrospective single-center study, we included all patients with LT for HCC in our institution (01/2007-12/2012). Beside demographic data, we analyzed course, bridging therapies, Serum-AFP, time point of tumor recurrence, as well as the correlation of imaging and histopathology of our recipients. Additionally, we performed a microarray analysis to identify different miRNA profiles of patients with and without HCC recurrence after LT. Single assay stem-loop real-time PCR (Q-RT-PCR) was used for validation of the results. Results: During the study period, we performed 92 LT in patients with HCC (22 women, 70 men). Twenty-two (23.9%) patients developed a recurrent HCC after LT. Our subgroup with tumor recurrence after LT, presented with a mean disease-free survival of 10 months (3-55 months) and an overall survival of 25.5 months (4-77 months). Milan criteria, AFP levels and pathologic grading had an influence on the tumor recurrence. Performing miRNA analysis, we could identify significant upregulation of 8 miRNAs and downregulation of another 5 miRNAs in patients with tumor recurrence. Consecutively, array data were successfully validated using Q-RT-PCR. Multivariate Cox regression, ROC analysis and Kaplan-Meier showed that a score consisting of two miRNAs and Milan criteria are an independent predictor for tumor recurrence-free survival. Conclusions: Despite careful selection of patients, an early recurrence of HCC after LT cannot be avoided completely. Reliable prognostic markers related to tumor biology are still missing. Analysis and validation of specific miRNAs combined with radiological parameters might lead to a promising strategy for the prediction of tumor recurrence, but prospective studies have to follow. 8 macrodissected hepatocellular carcinoma (recurrent HCC) and 10 macrodissected hepatocellular carcinoma (non-recurrent HCC).
Project description:Background: The presence of vascular invasion (VI) in pathology specimens has been widely described as closely linked to poor outcome in hepatocellular carcinoma (HCC) patients after tumor resection. Previous attempts have been conducted to achieve molecular markers or signatures to predict HCC recurrence in HCC. Here, we aim to develop a diagnostic model combining clinical and genomic variables able to detect the presence of VI prior to surgery and link it to survival estimation. Methods: Seventy-nine HCV related HCC samples from patients that underwent surgical resection as a treatment for HCC were subjected to Genome-wide gene expression profiling and a predictive model of vascular invasion was constructed. The model was tested in an independent-validation set of 153 fixed tissue samples of resected HCC. Quantitative RTPCR and inmunohistochemistry were performed in HCC samples to test a potential biomarker. Results: A 39-gene signature was able to accurately (72%) identify vascular invasion in HCC patients treated with resection. A model including tumor size and the signature is able to predict presence of VI with 85% accuracy in HCV-related HCC patients, and is able to exclude VI in up to 87% cases in HCC from all etiologies. Conclusions: Using the VI gene signature together with tumor size, VI can be successfully detected in HCC patients. The diagnostic model, integrated in a previously reported survival chart is able to provide an estimated survival for selected cases. Clinical implications of this fact are relevant to provide objective data to further apply expanded indication of curative treatments in HCC. Gene-expression profiling was performed using formalin-fixed, paraffin-embedded hepatocellular carcinoma tissues obtained at the time of surgical resection.