ARTICLE pubs.acs.org/jpr
Combined Serum and Tissue Proteomic Study Applied to a c-Myc Transgenic Mouse Model of Hepatocellular Carcinoma Identified Novel Disease Regulated Proteins Suitable for Diagnosis and Therapeutic Intervention Strategies Maria Stella Ritorto† and J€urgen Borlak*,†,‡ † ‡
Department of Molecular Medicine and Medical Biotechnology, Fraunhofer ITEM, Hanover, Germany Centre of Pharmacology and Toxicology, Hanover Medical School, Hanover, Germany
bS Supporting Information ABSTRACT: Hepatocellular carcinoma (HCC) is the third leading cause of cancer death in the U.S. Notably, most HCCs display c-Myc hyperactivity but this transcription factor participates in the regulation of as many as 15-20% of genes of the human genome. To better understand its oncogenic activity, a mass spectrometry-based proteomic approach was employed to search for disease-regulated proteins in liver tissue and serum of c-Myc transgenic mice that specifically developed HCC. Overall, a total of 90 differentially expressed proteins were identified with retinol binding protein 4, transthyretin, major urinary protein family, apolipoprotein E, and glutathione peroxidase being regulated in common in tissue and serum of HCC mice. Importantly, this study identified n = 22 novel tumor tissue-regulated proteins to function in cell cycle and proliferation, nucleotide and ribosomal biogenesis, oxidative stress, and GSH metabolism, while bioinformatics revealed the coding sequences of regulated proteins to enharbour c-Myc binding sites. Translation of the findings to human disease was achieved by Western immunoblotting of serum proteins and by immunohistochemistry of human HCC. Taken collectively, our study helps to define a c-Myc proteome suitable for diagnostic and possible therapeutic intervention strategies. KEYWORDS: proteomics, hepatocellular carcinoma, c-Myc, transgenic mice, translational research, biomarkers
1. INTRODUCTION Hepatocellular carcinoma (HCC) is on the rise and estimated to be the fifth most common cause of cancer and the third leading cause of cancer-related deaths in men and women.1 Early detection of disease significantly improves survival and prognosis but remains a finding by chance, as most patients are asymptomatic until the disease has progressed considerably. As of today, only a few serum biomarkers are available for disease diagnosis and therapeutic-monitoring, notably alpha-fetoprotein (AFP). Unfortunately, serum AFP levels are within normal range in about 40% of patients with hepatocellular carcinoma of less than 2 cm in diameter while in patients with tumors of 2-5 cm in diameter nearly 30% have normal AFP serum levels.3,2 Moreover, not all hepatocellular carcinomas secrete AFP, and this biomarker was shown to be elevated in pregnancy, by other tumors of gonadal origin, and in acute or chronic viral Hepatitis without a tumor.4-6 Because of its aggressive nature, the median survival following diagnosis is approximately 6-20 months.8,7 Consequently, early detection of the disease is a priority task but necessitates research for an identification and validation of better disease diagnostics. r 2011 American Chemical Society
In this regard, several serum biomarkers for diagnosis of HCC have been introduced and were recently evaluated for their clinical utility that included a comparison of AFP-L3 and desgamma-carboxy prothrombin (DCP) with DCP being a more robust and reliable marker as discussed in detail elsewhere.9 Additional candidates that function in metabolism, calcium homeostasis, cytoskeleton dynamics, tumor suppression, and apoptosis were also explored. Owing to the complexity of the disease, such candidate biomarkers need to be validated for specificity and accuracy in the diagnosis and the monitoring of disease progression. Indeed, at the molecular level, genetic analyses had revealed c-Myc to be frequently overexpressed, that is, in up to 70% of human viral and alcohol-related HCC10 while tissue microarray analysis had demonstrated c-Myc to be hyperactive and to be an important driver of HCC particularly in chronic liver diseases.11 Moreover, studies on Hepatitis B virus infected HCC patients had demonstrated strong activation of Received: December 2, 2010 Published: February 11, 2011 3012
dx.doi.org/10.1021/pr101207t | J. Proteome Res. 2011, 10, 3012–3030
Journal of Proteome Research c-Myc by the HBx protein and such activation of c-Myc accelerated the HBx oncogenic potential, therefore evidencing a central role of c-Myc in HCC promotion and progression. Given the importance of c-Myc in HCC, it is not surprising that it is an attractive target for novel therapies, as recently reviewed by Henriksson et al.12 In the present study, an integrated serum and tissue proteomic approach was applied to a c-Myc transgenic mouse model that specifically developed HCC. By use of the alpha-1 antitrypsin (AAT) promoter, targeted overexpression of c-Myc to the liver was achieved, as originally reported by Dalemans et al.13 Here, two-dimensional electrophoresis (2-DE) coupled with MALDI mass spectrometry (MS) enabled the study of the liver and serum proteome with the aim to identify novel c-Myc regulated proteins in HCC. Furthermore, commonly regulated proteins in serum and tissue of HCC were identified while the relevance of the findings for human disease was established by Western immunoblotting of serum proteins and by immunohistochemistry of human HCC, respectively. Taken collectively, our findings help to define a c-Myc proteome to facilitate diagnostic and therapeutic intervention strategies.
2. MATERIALS AND METHODS 2.1. Patient Characteristics and Human Tissue and Serum Samples
The Ethical committee of the Medical School of Hanover had approved the use of human samples. Patient characteristics are given in Supporting Information 1 (SI1). Human tumor tissue blocks from patients group A (IHC analysis) were provided by Dr. Ferdinand Hofst€adter, Institute of Pathology, University of Regensburg (Germany). Tissue blocks were sectioned and processed as described below (see 2.5.2). Characteristics of patient group B. Sera of HCC patients were obtained from Dr. Arndt Vogel, Hanover Medical School, and used for WB analyses. Here individuals were chosen according to their tumor staging (i.e., T3/T4, no regional lymph node involvement -N0- and no distant metastasis -M0-). 2.2. c-Myc Transgenic Mouse Model of HCC
All animal work followed strictly the Public Health Service (PHS) Policy of the NIH (USA) on Human Care and Use of Laboratory Animals. Formal approval to carry out animal studies was granted by the ethical review board of the city of Hanover (Germany). Transgenic mice were the kind gift of Dr. Dalemans.13 They were maintained as hemozygotes in the C57/Bl6 blackground. The transgene was verified by PCR using the forward primer: 50 -CACTGCGAGGGGTTCTGGAGAGGC-30 and the reverse primer: 50 -ATCGTCGTGGCTGTCTGCTGG-30 ; the following assay conditions were employed: 15 min 95 °C, 1 min 60 °C, 1 min 70 °C, 1 min 95 °C, 31 cycles. A total of n = 6 healthy nontransgenic (C57BL6) and n = 6 HCC bearing mice aged between 10 and 12 months were studied. Moreover, the sera of n = 3 transgenic mice devoid of cancer (5-6 months) have been analyzed by Western immunoblotting and the data were compared to nontransgenic controls and tumor bearing transgenic mice. The animals were kept individually and food and water were given ab libitum. 2.3. Gene Expression Analysis
2.3.1. Extraction of Total RNA. RNA from n = 3 control mice, n = 3 AAT-c-myc transgenic mice at the age of 2, n = 3 AAT-c-myc transgenic mice at the age of 6 and n = 3 HCC mice
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aged 12 months was isolated with the RNeasy Mini Kit (RNeasy MidiKit Qiagen, Santa Clarita, CA) according to the manufacturer’s instruction and quantified with the NanoDrop ND-1000 system (NanoDrop software, version 3.0.0, ThermoFisher, Wilmington, MA). 2.3.2. Sample Preparation for Analysis with Affymetrix GeneChip System. Total RNA (5 μg) was used to generate biotin-labeled cRNA (10 μg) by means of GeneChip One-Cycle cDNA Synthesis Kit and GeneChip IVT Labeling Kit (Affymetrix, Inc., Santa Clara, CA). Quality control of cRNA was checked with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA) and labeled cRNA of each sample was hybridized to Affymetrix GeneChip Mouse Genome -430 2.0 arrays in a Affymetrix 640 GeneChip Hybridization Oven. The arrays were scanned using the GeneChip Scanner 3000 (Affymetrix, Inc., Santa Clara, CA). 2.3.3. Statistical Analysis. Scaling or per-chip normalization was used. The Scale factor (SF) was according to the Affymetrix recommended setting SF = 1 and the TGT value was 500. A t test analysis was performed using the software Data Mining Tool (DMT, 3.0, Affymetrix). Only data, which exhibit a 100% concordance in the change direction with a p-value
