Depicting the role of TP53 in hepatocellular carcinoma progression

COMMENTARY ON:Association of TP53 mutations with stem cell-like gene expression and survival of patients with hepatocellular carcinoma Woo HG, Wang XW, Budhu A, Kim YH, Kwon SM, Tang ZY, Sun Z, Harris CC, Thorgeirsson SS. Gastroenterology. 2011 Mar;140(3):1063–70. Epub 2010 Nov 19. Copyright (2011). Abstract reprinted with permission from the American Gastroenterological Association.http://www.ncbi.nlm.nih.gov/pubmed/21094160AbstractBackground & Aims: Mutations in TP53, a tumor suppressor gene, are associated with prognosis of many cancers. However, the prognostic values of TP53 mutation sites are not known for patients with hepatocellular carcinoma (HCC) because of heterogeneity in their geographic and etiologic backgrounds.MethodsTP53 mutations were investigated in a total of 409 HCC patients, including Chinese (n=336) and white (n=73) patients, using the direct sequencing method.ResultsA total of 125 TP53 mutations were found in Chinese patients with HCC (37.2%). HCC patients with TP53 mutations had a shorter overall survival time compared with patients with wild-type TP53 (hazard ratio [HR], 1.86; 95% confidence interval [CI]: 1.37–2.52; P<.001). The hot spot mutations R249S and V157F were significantly associated with worse prognosis in univariate (HR, 2.11; 95% CI: 1.51–2.94; P<.001) and multivariate analyses (HR, 1.79; 95% CI: 1.29–2.51; P<.001). Gene expression analysis revealed the existence of stem cell-like traits in tumors with TP53 mutations. These findings were validated in breast and lung tumor samples with TP53 mutations.ConclusionsTP53 mutations, particularly the hot spot mutations R249S and V157F, are associated with poor prognosis for patients with HCC. The acquisition of stem cell-like gene expression traits might contribute to the aggressive behavior of tumors with TP53 mutation

Hepatitis C virus-induced hepatocellular carcinoma

Hepatitis C virus (HCV) is a leading etiology of hepatocellular carcinoma (HCC). The interaction of HCV with its human host is complex and multilayered; stemming in part from the fact that HCV is a RNA virus with no ability to integrate in the host's genome. Direct and indirect mechanisms of HCV-induced HCC include activation of multiple host pathways such as liver fibrogenic pathways, cellular and survival pathways, interaction with the immune and metabolic systems. Host factors also play a major role in HCV-induced HCC as evidenced by genomic studies identifying polymorphisms in immune, metabolic, and growth signaling systems associated with increased risk of HCC. Despite highly effective direct-acting antiviral agents, the morbidity and incidence of liver-related complications of HCV, including HCC, is likely to persist in the near future. Clinical markers to selectively identify HCV subjects at higher risk of developing HCC have been reported however they require further validation, especially in subjects who have experienced sustained virological response. Molecular biomarkers allowing further refinement of HCC risk are starting to be implemented in clinical platforms, allowing objective stratification of risk and leading to individualized therapy and surveillance for HCV individuals. Another role for molecular biomarker-based stratification could be enrichment of HCC chemoprevention clinical trials leading to smaller sample size, shorter trial duration, and reduced costs

Average Rank-Based Score to Measure Deregulation of Molecular Pathway Gene Sets

Deregulation of biological pathways has been shown to be involved in the turmorigenesis of a variety of cancers. The co-regulation of pathways in tumor and normal tissues has not been studied in a systematic manner.In this study we propose a novel statistic named AR-score (average rank based score) to measure pathway activities based on microarray gene expression profiles. We calculate and compare the AR-scores of pathways in microarray datasets containing expression profiles for a wide range of cancer types as well as the corresponding normal tissues. We find that many pathways undergo significant activity changes in tumors with respect to normal tissues. AR-scores for a small subset of pathways are capable of distinguishing tumor from normal tissues or classifying tumor subtypes. In normal tissues many pathways are highly correlated in their activities, whereas their correlations reduce significantly in tumors and cancer cell lines. The co-expression of genes in the same pathways was also significantly perturbed in tumors.The co-regulation of genes in the same pathways and co-regulation of different pathways are significantly perturbed in tumors versus normal tissues. Our method provides a useful tool for better understanding the mechanistic changes in tumors, which can also be used for exploring other biological problems

Subclass Mapping: Identifying Common Subtypes in Independent Disease Data Sets

Whole genome expression profiles are widely used to discover molecular subtypes of diseases. A remaining challenge is to identify the correspondence or commonality of subtypes found in multiple, independent data sets generated on various platforms. While model-based supervised learning is often used to make these connections, the models can be biased to the training data set and thus miss inherent, relevant substructure in the test data. Here we describe an unsupervised subclass mapping method (SubMap), which reveals common subtypes between independent data sets. The subtypes within a data set can be determined by unsupervised clustering or given by predetermined phenotypes before applying SubMap. We define a measure of correspondence for subtypes and evaluate its significance building on our previous work on gene set enrichment analysis. The strength of the SubMap method is that it does not impose the structure of one data set upon another, but rather uses a bi-directional approach to highlight the common substructures in both. We show how this method can reveal the correspondence between several cancer-related data sets. Notably, it identifies common subtypes of breast cancer associated with estrogen receptor status, and a subgroup of lymphoma patients who share similar survival patterns, thus improving the accuracy of a clinical outcome predictor

The Increasing Burden of Imported Chronic Hepatitis B — United States, 1974–2008

Without intervention, up to 25% of individuals chronically infected with hepatitis B virus (HBV) die of late complications, including cirrhosis and liver cancer. The United States, which in 1991 implemented a strategy to eliminate HBV transmission through universal immunization, is a country of low prevalence. Approximately 3,000-5,000 U.S.-acquired cases of chronic hepatitis B have occurred annually since 2001. Many more chronically infected persons migrate to the United States yearly from countries of higher prevalence. Although early identification of chronic HBV infection can reduce the likelihood of transmission and late complications, immigrants are not routinely screened for HBV infection during or after immigration.To estimate the number of imported cases of chronic hepatitis B, we multiplied country-specific prevalence estimates by the yearly number of immigrants from each country during 1974-2008.During 1974-2008, 27.9 million immigrants entered the U.S. Sixty-three percent were born in countries of intermediate or high chronic hepatitis B prevalence (range 2%-31%). On average, an estimated 53,800 chronic hepatitis B cases were imported to the U.S. yearly from 2004 through 2008. The Philippines, China, and Vietnam contributed the most imported cases (13.4%, 12.5%, and 11.0%, respectively). Imported cases increased from an estimated low of 105,750 during the period 1974-1977 to a high of 268,800 in 2004-2008.Imported chronic hepatitis B cases account for approximately 95% of new U.S. cases. Earlier case identification and management of infected immigrants would strengthen the U.S. strategy to eliminate HBV transmission, and could delay disease progression and prevent some deaths among new Americans

Nearest Template Prediction: A Single-Sample-Based Flexible Class Prediction with Confidence Assessment

Gene-expression signature-based disease classification and clinical outcome prediction has not been widely introduced in clinical medicine as initially expected, mainly due to the lack of extensive validation needed for its clinical deployment. Obstacles include variable measurement in microarray assay, inconsistent assay platform, analytical requirement for comparable pair of training and test datasets, etc. Furthermore, as medical device helping clinical decision making, the prediction needs to be made for each single patient with a measure of its reliability. To address these issues, there is a need for flexible prediction method less sensitive to difference in experimental and analytical conditions, applicable to each single patient, and providing measure of prediction confidence. The nearest template prediction (NTP) method provides a convenient way to make class prediction with assessment of prediction confidence computed in each single patient's gene-expression data using only a list of signature genes and a test dataset. We demonstrate that the method can be flexibly applied to cross-platform, cross-species, and multiclass predictions without any optimization of analysis parameters

Thrombocytosis is associated with worse survival in patients with hepatocellular carcinoma

Background & AimsThrombocytosis is associated with more aggressive tumour biology in many malignancies. There are limited data in patients with hepatocellular carcinoma (HCC), which often occurs in patients with cirrhosis and portal hypertension. We aimed to explore the prognostic value of thrombocytosis in two cohorts of patients with HCC.MethodsWe included 3561 patients from Taiwan and 1145 patients from the USA. Thrombocytopenia was defined as platelet count < 150à 109/L and thrombocytosis as - ¥Â 300 à  109/L at HCC diagnosis. We used multivariable Cox proportional hazard models to identify independent predictors of survival.ResultsThrombocytosis was present in 9.0% and 6.9% of Taiwan and USA patients respectively. Compared to patients with normal platelet counts and those with thrombocytopenia, patients with thrombocytosis had larger tumours, increased vascular invasion and a higher proportion had extrahepatic metastases in both cohorts. In multivariable analysis, thrombocytosis (aHR 1.40, 95% CI 1.23- 1.60) and thrombocytopenia (aHR 1.13, 95% CI 1.04- 1.23) were both associated with worse survival after adjusting for age, gender, liver disease aetiology, Child- Pugh score, maximal tumour size, tumour nodularity, vascular invasion, lymph node or distant metastasis, performance status and alpha- fetoprotein level. Patients with thrombocytosis had a median survival of 6 and 4 months in the Taiwan and USA cohorts, compared to 32 and 14 months for those with normal platelet counts and 38 and 16 months for thrombocytopenic patients.ConclusionThrombocytosis is independently associated with increased tumour burden and worse overall survival among HCC patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162769/2/liv14560.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162769/1/liv14560_am.pd

In vitro modeling of hepatocellular carcinoma molecular subtypes for anti-cancer drug assessment

Tractable experimental model that accounts for inter-tumor molecular heterogeneity is a key element of anti-cancer drug development. Hepatocellular carcinoma is known to exhibit highly heterogeneous molecular aberrations across the tumors, including somatic genetic and epigenetic alterations. Previous studies showed that molecular tumor subtypes determined by transcriptome, as a comprehensive functional readout, are reproducibly observed across global patient populations irrespective of geographic and etiological variations. Here we demonstrate that transcriptomic hepatocellular carcinoma subtypes, S1 and S2, determined by our previous transcriptome meta-analysis of multiple clinical hepatocellular carcinoma cohorts, are presented in a panel of hepatoma cell lines widely used by the research community. Interestingly, cell line that resembles gene expression pattern of S3 subtype, representing less aggressive tumors, was not identified in the panel. MYC pathway-activated S2-like cell lines showed higher sensitivity to a small molecule BET bromodomain inhibitor, (+)-JQ1, which has anti-MYC activity. These results support the use of hepatoma cell lines as models to evaluate molecular subtype-specific drug response, which is expected to lead to development of tailored, precision care of the patients with hepatocellular carcinoma