Micro RNA Expression Profiles as Adjunctive Data to Assess the Risk of Hepatocellular Carcinoma Recurrence After Liver Transplantation

Article (PDF Available)inAmerican Journal of Transplantation 12(2):428-37 · February 2012with47 Reads
DOI: 10.1111/j.1600-6143.2011.03788.x · Source: PubMed
Donor livers are precious resources and it is, therefore, ethically imperative that we employ optimally sensitive and specific transplant selection criteria. Current selection criteria, the Milan criteria, for liver transplant candidates with hepatocellular carcinoma (HCC) are primarily based on radiographic characteristics of the tumor. Although the Milan criteria result in reasonably high survival and low-recurrence rates, they do not assess an individual patient's tumor biology and recurrence risk. Consequently, it is difficult to predict on an individual basis the risk for recurrent disease. To address this, we employed microarray profiling of microRNA (miRNA) expression from formalin fixed paraffin embedded tissues to define a biomarker that distinguishes between patients with and without HCC recurrence after liver transplant. In our cohort of 64 patients, this biomarker outperforms the Milan criteria in that it identifies patients outside of Milan who did not have recurrent disease and patients within Milan who had recurrence. We also describe a method to account for multifocal tumors in biomarker signature discovery.

Full-text (PDF)

Available from: Mary D'Souza, Jul 30, 2014
    • "For patients with multifocal disease this implies that not all foci are equally responsible for recurrence. Previous approaches either analyzed only one sample per patient [9][10][11][12]or used summarized sample-level information from multifocal patients [6], whereas our approach uses both sample-level and patientlevel information to predict recurrence. This has implications for patients with highly heterogeneous microRNA expression profiles. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: Liver cancer, of which hepatocellular carcinoma (HCC) is by far the most common type, is the second most deadly cancer (746,000 deaths in 2012). Currently, the only curative treatment for HCC is surgery to remove the malignancy (resection) or to remove the entire diseased liver followed by transplantation of healthy liver tissue. Given the shortage of healthy livers, it is crucial to provide transplants to patients that have the best chance of long-term survival. Currently, transplantation is determined via the Milan criteria-patients within Milan (single tumor < 5 cm or 2-3 tumors < 3 cm with no extrahepatic spread nor intrahepatic vascular invasion) are typically eligible for transplantation. However, combining microRNA expression profiling with the Milan criteria can improve prediction of recurrence. HCC often presents with multiple distinct tumor foci arising from local spread of a primary tumor or from the oncogenic predisposition of the diseased liver. Substantial genomic heterogeneity between tumor foci within a single patient has been reported; therefore, biomarker development must account for the possibility of highly heterogeneous genomic profiles from the same individual. Methods: MicroRNA profiling was performed on 180 HCC tumor samples from 89 patients who underwent liver transplantation at the University of Rochester Medical Center. The primary outcome was recurrence-free survival time, and patients were observed for 3 years post-transplantation. Results: MicroRNA expression profiles were used to develop a biomarker that distinguishes HCC patients at greater risk of recurrence post-transplantation. Unsupervised clustering uncovered two distinct subgroups with vast differences in standard transplantation selection criteria and recurrence-free survival times. These subgroups were subsequently used to identify microRNAs strongly associated with HCC recurrence. Our results show that reduced expression of five specific microRNAs is significantly associated with HCC recurrence post-transplantation. Conclusions: MicroRNA profiling of distinct tumor foci, coupled with methods that address within-subject tumor heterogeneity, has the potential to significantly improve prediction of HCC recurrence post-transplantation. The development of a clinically applicable HCC biomarker would inform treatment options for patients and contribute to liver transplant selection criteria for practitioners.
    Full-text · Article · Dec 2016
    • "Studies involving large clinical cohorts within a population-based setting are required. C19MC microRNA cluster Up Tissue Poor clinico-pathological features, recurrence, and shorter overall survival [112] miR-155, miR-15a, miR-432, miR-486-3p, miR-15b, miR-30b Up Tissue Recurrence-free survival [113] miR-19a, miR-886, miR-126, miR-223, miR-24, and miR-147 Signature Tissue Overall survival and recurrent free survival [65] 67 miRs signature Signature Tissue Differentiate recurrence after liver transplantation [114] miR signatures in tumor and non-tumor tissues Signature Tissue Differentiate early and late recurrence [115] miR-326, miR-3677, miR-511-1, miR- 511-2, miR-9-1, and miR-9-2 Signature Tissue Negatively associated with overall survival [116] Predictive Therapeutic Response Markers miR-122 Down Cells, tissue Decreased sensitivity to Doxorubicin [81] miR-122 Down Cells, tissue Decreased sensitivity to Adriamycin, Vincristin [80] miR-122 Down Cells, tissue Suppressed sensitivity to sorafenib [76] miR-146a Up Cells Suppresses sensitivity to interferon-α [71] miR-193a-3p Down Cells, tissue Resistance to 5-FU [84] miR-193b Up Cells, Tissue Sensitivity to cisplatin [117] miR-199a-3p Down Cells, tissue Increased sensitivity to Doxorubicin [82] miR-1247a Down Cells Resistance to sorafenib [118] miR-21 Up Cells, tissue Resistance to interferon-α/5FU in HCC cells [74] miR-34a Down Cells, tissue Resistance to sorafenib [94] 13 microRNA signature Signature Cells, tissue Multidrug resistance [90] "
    [Show abstract] [Hide abstract] ABSTRACT: The discovery of small non-coding RNAs known as microRNAs has refined our view of the complexity of gene expression regulation. In hepatocellular carcinoma (HCC), the fifth most frequent cancer and the third leading cause of cancer death worldwide, dysregulation of microRNAs has been implicated in all aspects of hepatocarcinogenesis. In addition, alterations of microRNA expression have also been reported in non-cancerous liver diseases including chronic hepatitis and liver cirrhosis. MicroRNAs have been proposed as clinically useful diagnostic biomarkers to differentiate HCC from different liver pathologies and healthy controls. Unique patterns of microRNA expression have also been implicated as biomarkers for prognosis as well as to predict and monitor therapeutic responses in HCC. Since dysregulation has been detected in various specimens including primary liver cancer tissues, serum, plasma, and urine, microRNAs represent novel non-invasive markers for HCC screening and predicting therapeutic responses. However, despite a significant number of studies, a consensus on which microRNA panels, sample types, and methodologies for microRNA expression analysis have to be used has not yet been established. This review focuses on potential values, benefits, and limitations of microRNAs as new clinical markers for diagnosis, prognosis, prediction, and therapeutic monitoring in HCC.
    Full-text · Article · Aug 2015
    • "In HCC, a number of miRNAs have been associated with survival or response to chemotherapy such as sorafenib or doxorubicin [5][6][7]. However, the sample size, the numbers of candidate miRNAs or miRNA detection method in previous studies were relatively limited [8][9][10]. TCGA project provides a collection of clinical data, RNA sequence, DNA methylation, DNA copy number variations, and miRNA sequence profiles for LIHC. "
    [Show abstract] [Hide abstract] ABSTRACT: Hepatocellular carcinoma (HCC) is the fifth common cancer. The differential expression of microRNAs (miRNAs) has been associated with the prognosis of various cancers. However, limited information is available regarding genome-wide miRNA expression profiles in HCC to generate a tumor-specific miRNA signature of prognostic values. In this study, the miRNA profiles in 327 HCC patients, including 327 tumor and 43 adjacent non-tumor tissues, from The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) were analyzed. The associations of the differentially expressed miRNAs with patient survival and other clinical characteristics were examined with t-test and Cox proportional regression model. Finally, a tumor-specific miRNA signature was generated and examined with Kaplan–Meier survival, univariate\multivariate Cox regression analyses and KEGG pathway analysis. Results showed that a total of 207 miRNAs were found differentially expressed between tumor and adjacent non-tumor HCC tissues. 78 of them were also discriminatively expressed with gender, race, tumor grade and AJCC tumor stage. Seven miRNAs were significantly associated with survival (P value <0.001). Among the seven significant miRNAs, six (hsa-mir-326, hsa-mir-3677, hsa-mir-511-1, hsa-mir-511-2, hsa-mir-9-1, and hsa-mir-9-2) were negatively associated with overall survival (OS), while the remaining one (hsa-mir-30d) was positively correlated. A tumor-specific 7-miRNAs signature was generated and validated as an independent prognostic predictor. Collectively, we have identified and validated an independent prognostic model based on the expression of seven miRNAs, which can be used to assess patients’ survival. Additional work is needed to translate our model into clinical practice.
    Full-text · Article · Jun 2015
Show more