Article
The absence of p53 promotes metastasis in a novel somatic mouse model for hepatocellular carcinoma.
University of Massachusetts Medical School, 364 Plantation St., LRB 521, Worcester, MA 01605, USA.
Molecular and Cellular Biology (impact factor:
5.53).
03/2005;
25(4):1228-37.
DOI:10.1128/MCB.25.4.1228-1237.2005
pp.1228-37
Source: PubMed
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Article: c-myc amplification in hepatocellular carcinoma predicts unfavorable prognosis.
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ABSTRACT: Structural alterations and amplifications of the c-myc oncogene have been implicated in the pathogenesis and progression of several human neoplastic diseases. To study the role of c-myc amplification in human hepatocellular carcinomas (HCC), we analyzed 20 HCC using differential polymerase chain reaction (PCR). DNA used for differential PCR was extracted from formalin-fixed, paraffin-embedded tissue obtained by radiographically directed needle aspiration biopsy. Differential PCR reactions included sets of primers for c-myc and a control gene, dopamine D2 receptor (D2R), which yielded products of 150 bp and 110 bp, respectively. Evaluation of amplification was based on the relative concentration of c-myc and D2R PCR products. The c-myc amplification was detected in 10 of 20 HCC. Cases with c-myc amplification tended to have higher histologic grade and were significantly (P = 0.05) associated with worse prognosis. Amplification was present in none of two Grade 1 tumors, seven of the fourteen Grade 2 tumors, and three of four Grade 3 tumors. The mean survival times (+/- SEM) for patients with and without c-myc amplification were 5.7 (+/- 1.8) and 13.8 (+/- 2.6) months, respectively. These results indicate that c-myc amplification in HCC can be evaluated by differential PCR of needle biopsy specimens, and is an unfavorable prognostic indicator.Modern Pathology 03/1996; 9(2):95-8. · 4.79 Impact Factor -
Article: A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes.
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ABSTRACT: MOTIVATION: DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory due to the lack of a systematic framework that can accommodate noise, variability, and low replication often typical of microarray data. RESULTS: We develop a Bayesian probabilistic framework for microarray data analysis. At the simplest level, we model log-expression values by independent normal distributions, parameterized by corresponding means and variances with hierarchical prior distributions. We derive point estimates for both parameters and hyperparameters, and regularized expressions for the variance of each gene by combining the empirical variance with a local background variance associated with neighboring genes. An additional hyperparameter, inversely related to the number of empirical observations, determines the strength of the background variance. Simulations show that these point estimates, combined with a t -test, provide a systematic inference approach that compares favorably with simple t -test or fold methods, and partly compensate for the lack of replication.Bioinformatics 07/2001; 17(6):509-19. · 5.47 Impact Factor -
Article: A receptor for subgroup A Rous sarcoma virus is related to the low density lipoprotein receptor.
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ABSTRACT: Cellular receptors are required for efficient entry of retroviruses into cells. We previously cloned a chicken gene responsible for susceptibility to the retrovirus subgroup A Rous sarcoma virus (RSV(A)). Here we have isolated the quail homolog and generated two alternatively spliced processed genes encoding cellular receptors for RSV(A). Predicted products of the processed genes appear to be small membrane-associated proteins with identical 83 amino acid extracellular domains but different membrane anchors. Within the extracellular domain is a region closely related to the ligand-binding repeat of the low density lipoprotein receptor (LDLR). Expression of either processed gene renders mammalian cells specifically susceptible to RSV(A). Antibodies directed against the receptor block subgroup A infection of avian cells via endogenous receptors and have no effect on entry of other RSV subgroups. Thus, small LDLR-related proteins are cellular receptors for RSV(A).Cell 10/1993; 74(6):1043-51. · 32.40 Impact Factor
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Keywords
Alb-TVA mice
albumin gene promoter
cathepsin E
Gene expression microarrays
intact p53 gene
magnetic resonance imaging
mice
mouse model
oncogene-bearing avian retroviral vectors
p53 null mice
PyMT mutants
PyMT-expressing viruses
resulting tumors
specific tyrosine residues
tumor cell migration
tumors
Tumors induced
TVA transgenic mice
TVA-positive animals
viral receptor TVA