Eight-year longitudinal study of whole blood gene expression profiles in individuals undergoing long-term medical follow-up.

Blood circulates throughout the body via the peripheral tissues, contributes to host homeostasis and maintains normal physiological functions, in addition to responding to lesions. Previously, we revealed that gene expression analysis of peripheral blood cells is a useful approach for assessing diseases such as diabetes mellitus and cancer because the altered gene expression profiles of peripheral blood cells can reflect the presence and state of diseases. However, no chronological assessment of whole gene expression profiles has been conducted. In the present study, we collected whole blood RNA from 61 individuals (average age at registration, 50 years) every 4 years for 8 years and analyzed gene expression profiles using a complementary DNA microarray to examine whether these profiles were stable or changed over time. We found that the genes with very stable expression were related mostly to immune system pathways, including antigen cell presentation and interferon-related signaling. Genes whose expression was altered over the 8-year study period were principally involved in cellular machinery pathways, including development, signal transduction, cell cycle, apoptosis, and survival. Thus, this chronological examination study showed that the gene expression profiles of whole blood can reveal unmanifested physiological changes.

Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study.

BACKGROUND: According to EULAR recommendations, biologic DMARDs (bDMARDs) such as tumor necrosis factor inhibitor, tocilizumab (TCZ), and abatacept (ABT) are in parallel when prescribing to rheumatoid arthritis (RA) patients who have shown insufficient response to conventional synthetic DMARDs. However, most prediction studies of therapeutic response to bDMARDs using gene expression profiles were focused on a single bDMARD, and consideration of the results from the perspective of RA pathophysiology was insufficient. The aim of this study was to identify the specific molecular biological features predicting the therapeutic outcomes of three bDMARDs (infliximab [IFX], TCZ, and ABT) by studying blood gene expression signatures of patients before biologic treatment in a unified test platform. METHODS: RA patients who responded inadequately to methotrexate and were later commenced on any one of IFX (n = 140), TCZ (n = 38), or ABT (n = 31) as their first biologic between May 2007 and November 2011 were enrolled. Whole-blood gene expression data were obtained before biologic administration. Patients were categorized into remission (REM) and nonremission (NON-REM) groups according to CDAI at 6 months of biologic therapy. We employed Gene Set Enrichment Analysis (GSEA) to identify functional gene sets differentially expressed between these two groups for each biologic. Then, we compiled "signature scores" for these gene sets, and the prediction performances were assessed. RESULTS: GSEA showed that inflammasome genes were significantly upregulated with IFX in the NON-REM group compared with the REM group. With TCZ in the REM group, B-cell-specifically expressed genes were upregulated. RNA elongation, apoptosis-related, and NK-cell-specifically expressed genes were upregulated with ABT in the NON-REM group. Logistic regression analyses showed that "signature scores" of inflammasomes, B-cell-specifically expressed, and NK-cell-specifically expressed genes were significant, independently predictive factors for treatment outcome with IFX, TCZ, and ABT, respectively. The AUCs of ROC curves of these signature scores were 0.637, 0.796, and 0.768 for IFX, TCZ, and ABT, respectively. CONCLUSIONS: We have identified original gene expression predictive signatures uniquely underlying the therapeutic effects of IFX, TCZ, and ABT. This is, to our knowledge, the first attempt to predict therapeutic effects of three drugs concomitantly using a unified gene expression test platform.

Large-scale East-Asian eQTL mapping reveals novel candidate genes for LD mapping and the genomic landscape of transcriptional effects of sequence variants.

Profiles of sequence variants that influence gene transcription are very important for understanding mechanisms that affect phenotypic variation and disease susceptibility. Using genotypes at 1.4 million SNPs and a comprehensive transcriptional profile of 15,454 coding genes and 6,113 lincRNA genes obtained from peripheral blood cells of 298 Japanese individuals, we mapped expression quantitative trait loci (eQTLs). We identified 3,804 cis-eQTLs (within 500 kb from target genes) and 165 trans-eQTLs (>500 kb away or on different chromosomes). Cis-eQTLs were often located in transcribed or adjacent regions of genes; among these regions, 5' untranslated regions and 5' flanking regions had the largest effects. Epigenetic evidence for regulatory potential accumulated in public databases explained the magnitude of the effects of our eQTLs. Cis-eQTLs were often located near the respective target genes, if not within genes. Large effect sizes were observed with eQTLs near target genes, and effect sizes were obviously attenuated as the eQTL distance from the gene increased. Using a very stringent significance threshold, we identified 165 large-effect trans-eQTLs. We used our eQTL map to assess 8,069 disease-associated SNPs identified in 1,436 genome-wide association studies (GWAS). We identified genes that might be truly causative, but GWAS might have failed to identify for 148 out of the GWAS-identified SNPs; for example, TUFM (P = 3.3E-48) was identified for inflammatory bowel disease (early onset); ZFP90 (P = 4.4E-34) for ulcerative colitis; and IDUA (P = 2.2E-11) for Parkinson's disease. We identified four genes (P<2.0E-14) that might be related to three diseases and two hematological traits; each expression is regulated by trans-eQTLs on a different chromosome than the gene.

Gene expression levels of S100 protein family in blood cells are associated with insulin resistance and inflammation (Peripheral blood S100 mRNAs and metabolic syndrome).

OBJECTIVE: Visceral fat obesity is located upstream of metabolic syndrome and atherosclerotic diseases. Accumulating evidences indicate that several immunocytes including macrophages infiltrate into adipose tissue and induce chronic low-grade inflammation. We recently analyzed the association between visceral fat adiposity and the gene expression profile in peripheral blood cells in human subjects and demonstrated the close relationship of visceral fat adiposity and disturbance of circadian rhythm in peripheral blood cells. In a series of studies, we herein investigated the association of visceral fat adiposity and mRNA levels relating to inflammatory genes in peripheral blood cells. APPROACH AND RESULTS: Microarray analysis was performed in peripheral blood cells from 28 obese subjects. Reverse transcription-polymerase chain reaction (RT-PCR) was conducted by using blood cells from 57 obese subjects. Obesity was defined as body mass index (BMI) greater than 25 kg/m2 according to the Japanese criteria. Gene expression profile analysis was carried out with Agilent whole human genome 4×44K oligo-DNA microarray. Gene ontology (GO) analysis showed that 14 genes were significantly associated with visceral fat adiposity among 239 genes relating to inflammation. Among 14 genes, RT-PCR demonstrated that S100A8, S100A9, and S100A12 positively correlated with visceral fat adiposity in 57 subjects. Stepwise multiple regression analysis showed that S100A8 and S100A12 mRNA levels were closely associated with HOMA-IR and S100A9 mRNA was significantly related to adiponectin and CRP. CONCLUSIONS: Peripheral blood mRNA levels of S100 family were closely associated with insulin resistance and inflammation.

Prediction of the response to chemotherapy in advanced esophageal cancer by gene expression profiling of biopsy samples.

To improve the prognosis of advanced esophageal cancer, neoadjuvant chemotherapy (NACT) followed by surgery is a promising treatment strategy. NACT has been shown to improve the prognosis of responders. However, non-responders not only suffer from side-effects, but they also lose precious time to take advantage of other possible treatments. Therefore, it is crucial to establish a reliable method that allows prediction of response before chemotherapy. A biopsy sample can provide valuable information on the biological characteristics of an individual esophageal cancer, which can affect chemosensitivity. Comprehensive gene expression profiling (GEP) using oligonucleotide microarray covering 30,000 human probes was performed in 50 pretreatment endoscopic biopsy samples from 25 patients with esophageal squamous cell cancer (ESCC) who underwent cisplatin-based chemotherapy (two samples per patient). Chemotherapeutic responses were evaluated by the reduction rate of the tumor area on CT scans. Responders were defined as patients with reduction rates of ≥50% and non-responders were defined as patients with <50% decrease. The diagnostic system, that predicts responses to chemotherapy, was constructed with the 199 most informative genes, and showed 82% of accuracy. Furthermore, the predictive performance of this system was confirmed using an additional ten samples with an accuracy of 80%. This study shows that GEP of pretreatment ESCC biopsy samples has the potential to predict responses to chemotherapy.

Gene expression profile prospectively predicts peritoneal relapse after curative surgery of gastric cancer.

BACKGROUND: Peritoneal relapse is the most common pattern of tumor progression in advanced gastric cancer. Clinicopathological findings are sometimes inadequate for predicting peritoneal relapse. The aim of this study was to identify patients at high risk of peritoneal relapse in a prospective study based on molecular prediction. METHODS: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly, we constructed a molecular prediction system and validated its robustness and prognostic validity by 500 times multiple validation by repeated random sampling in a retrospective set of 56 (38 relapse-free and 18 peritoneal-relapse) patients. Secondly, we applied this prediction to 85 patients of the prospective set to assess predictive accuracy and prognostic validity. RESULTS: In the retrospective phase, repeated random validation yielded approximately 68% predictive accuracy and a 22-gene expression profile associated with peritoneal relapse was identified. The prediction system identified patients with poor prognosis. In the prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan-Meier analysis of peritoneal-relapse-free survival showed a significant difference between the "good signature group" and "poor signature group" (log-rank p = 0.0017). Multivariate analysis by Cox regression hazards model identified the molecular prediction as the only independent prognostic factor for peritoneal relapse. CONCLUSIONS: Gene expression profile inherent to primary gastric cancer tissues can be useful in prospective prediction of peritoneal relapse after curative surgery, potentially allowing individualized postoperative management to improve the prognosis of patients with advanced gastric cancer.

Differential transcriptome patterns for acute cellular rejection in recipients with recurrent hepatitis C after liver transplantation.

Histopathological evaluation of the liver via biopsy remains the standard procedure for the diagnosis of both acute cellular rejection (ACR) and recurrent hepatitis C (RHC) after liver transplantation. Nevertheless, it is often difficult to diagnose ACR in hepatitis C virus-positive recipients because of changes in common and overlapping with RHC. The aim of this study was to identify potential target genes for ACR in recipients with RHC. We analyzed 22 liver biopsy samples obtained from 21 hepatitis C virus-positive recipients. The clinicopathological diagnosis based on biopsy examination was ACR-predominant with superimposed RHC in 9 samples (ACR group) and RHC without ACR (non-ACR group) in 13. Using oligonucleotide microarrays, we compared the transcriptional changes in the 2 groups and selected 2206 genes that were significantly modulated in ACR. We analyzed the regulatory networks in ACR with Ingenuity Pathway Analysis software, and we confirmed with quantitative real-time polymerase chain reaction the reproducibility of caspase 8, apoptosis-related cysteine peptidase and bone morphogenetic protein 2 up-regulation in another group of validation samples, representing 2 genes from the core network as the target genes for ACR. Our results demonstrated novel transcriptome patterns for ACR with concurrent RHC that were distinct from those of recipients with only RHC, suggesting that gene expression profiling may be useful in the diagnosis of ACR in recipients with hepatitis C.

The feasibility of using biopsy samples from esophageal cancer for comprehensive gene expression profiling.

Advanced esophageal cancer has been recently treated by multimodal therapy including preoperative chemotherapy or chemoradiotherapy and surgery. A biopsy sample provides a valuable specimen for understanding the biological characteristics of individual esophageal cancer. Pretreatment prediction of the response to chemotherapy or radiotherapy based on biological characteristics using biopsy samples is a desirable goal. In using biopsy samples for molecular analysis, there are two problems; the proportion of cancer cells and the intratumor heterogeneity. This study was conducted to investigate the feasibility of using endoscopic biopsy samples of esophageal squamous cell cancer (ESCC) for comprehensive gene expression profiling (GEP). Comprehensive GEP was performed in 40 bulky ESCC specimens and 10 normal esophageal epithelial specimens from patients who underwent esophageal resection and 52 endoscopic ESCC biopsy samples from 26 patients (two samples per one patient). Unsupervised hierarchical cluster analysis showed distinct profiles between the bulky ESCC specimens and normal epithelial specimens. Also, unsupervised hierarchical cluster analysis revealed distinct profiles between the biopsy ESCC samples and normal epithelial specimens. Moreover, a couple of biopsy samples taken from different locations of the same tumor were closely clustered together. That is, biopsy ESCC samples were distinguished from normal esophageal epithelial specimens and the intratumor heterogeneity of GEP was smaller than intertumor heterogeneity. GEP using biopsy ESCC samples is feasible and has the potential to represent the biological properties.

Prediction of efficacy of anti-TNF biologic agent, infliximab, for rheumatoid arthritis patients using a comprehensive transcriptome analysis of white blood cells.

Introduction of biologics, such as infliximab, to the therapy of rheumatoid arthritis (RA) patients has revolutionized the treatment of this disease. However, biomarkers for predicting the efficacy of the drug at an early phase of treatment for selecting real responders have not been found. We here present predictive markers based on a thorough transcriptome analysis of white blood cells from RA patients. RNA from whole blood cells of consecutive 42 patients before the first infusion was analyzed with microarrays for training studies. Samples from the subsequent 26 consecutive patients were used for a prospective study. We categorized the results into no inflammation and residual inflammation groups using the serum C-reactive protein (CRP) level at 14weeks after the first infusion. The accuracy of prediction in our study was 65.4%.

Interactions among type I and type II interferon, tumor necrosis factor, and beta-estradiol in the regulation of immune response-related gene expressions in systemic lupus erythematosus.

INTRODUCTION: Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease characterized by various clinical manifestations. Several cytokines interact and play pathological roles in SLE, although the etiopathology is still obscure. In the present study we investigated the network of immune response-related molecules expressed in the peripheral blood of SLE patients, and the effects of cytokine interactions on the regulation of these molecules. METHODS: Gene expression profiles of peripheral blood from SLE patients and from healthy women were analyzed using DNA microarray analysis. Differentially expressed genes classified into the immune response category were selected and analyzed using bioinformatics tools. Since interactions among TNF, IFNgamma, beta-estradiol (E2), and IFNalpha may regulate the expression of interferon-inducible (IFI) genes, stimulating and co-stimulating experiments were carried out on peripheral blood mononuclear cells followed by analysis using quantitative RT-PCR. RESULTS: Thirty-eight downregulated genes and 68 upregulated genes were identified in the functional category of immune response. Overexpressed IFI genes were confirmed in SLE patient peripheral bloods. Using network-based analysis on these genes, several networks including cytokines--such as TNF and IFNgamma--and E2 were constructed. TNF-regulated genes were dominant in these networks, but in vitro TNF stimulation on peripheral blood mononuclear cells showed no differences in the above gene expressions between SLE and healthy individuals. Co-stimulating with IFNalpha and one of TNF, IFNgamma, or E2 revealed that TNF has repressive effects while IFNgamma essentially has synergistic effects on IFI gene expressions in vitro. E2 showed variable effects on IFI gene expressions among three individuals. CONCLUSIONS: TNF may repress the abnormal regulation by IFNalpha in SLE while IFNgamma may have a synergistic effect. Interactions between IFNalpha and one of TNF, IFNgamma, or E2 appear to be involved in the pathogenesis of SLE.

Molecular prediction of early recurrence after resection of hepatocellular carcinoma.

The prognosis of hepatocellular carcinoma (HCC) remains poor. Vascular invasion, tumour multiplicity and large tumour size are the conventional poor prognostic indicators related to early recurrence. However, it is difficult to predict prognosis of each HCC in the absence of these indicators. The purpose of this study is to predict early recurrence of HCC after radical resection based on whole human gene expression profiling. Microarray analyses were performed in 139 HCC primary tumours. A total of 88 cases lacking the conventional poor prognostic indicators were analysed to establish a molecular prediction system characteristic for early recurrence in 42 training cases with two polarised prognoses, and to test its predictive performance in 46 independent cases (group C). Subsequently, this system was applied to another 51 independent cases with some poor prognostic indicators (group D). The molecular prediction system accurately differentiated HCC cases into poor and good prognoses in both the independent group C (disease-free survival [DFS]: p=0.029, overall survival [OS]: p=0.0043) and independent group D (DFS: p=0.0011, OS, p=0.035). Multivariate Cox regression analysis indicated that the clinical value of molecular prediction system was an independent prognostic factor (p<0.0001, hazard ratio=3.29). Gene expression pattern related to early intrahepatic recurrence inherited in the primary HCC tumour can be useful for the prediction of prognosis.

Screening of potential molecular targets for colorectal cancer therapy.

Colorectal cancer is a leading cause of cancer death worldwide. To identify molecular targets for colorectal cancer therapy, we tested small interfering RNAs (siRNAs) against 97 genes whose expression was elevated in human colorectal cancer tissues for the ability to promote apoptosis of human colorectal cancer cells (HT-29 cells). The results indicate that the downregulation of PSMA7 (proteasome subunit, alpha-type, 7) and RAN (ras-related nuclear protein) most efficiently induced apoptosis of HT-29 cells. PSMA7 and RAN were highly expressed in colorectal cancer cell lines compared with normal colon tissues. Furthermore, PSMA7 and RAN were overexpressed in not only colon tumor tissues but also the other tumor tissues. Moreover, in vivo delivery of PSMA7 siRNA and RAN siRNA markedly induced apoptosis in HT-29 xenograft tumors in mice. Thus, silencing of PSMA7 and RAN induces cancer cells to undergo apoptosis, and PSMA7 and RAN might be promising new molecular targets for drug and RNA interference-based therapeutics against colorectal cancer.

A comparative analysis of the transcriptome and signal pathways in hepatic differentiation of human adipose mesenchymal stem cells.

The specific features of the plasticity of adult stem cells are largely unknown. Recently, we demonstrated the hepatic differentiation of human adipose tissue-derived mesenchymal stem cells (AT-MSCs). To identify the genes responsible for hepatic differentiation, we examined the gene expression profiles of AT-MSC-derived hepatocytes (AT-MSC-Hepa) using several microarray methods. The resulting sets of differentially expressed genes (1639 clones) were comprehensively analyzed to identify the pathways expressed in AT-MSC-Hepa. Clustering analysis revealed a striking similarity of gene clusters between AT-MSC-Hepa and the whole liver, indicating that AT-MSC-Hepa were similar to liver with regard to gene expression. Further analysis showed that enriched categories of genes and signaling pathways such as complementary activation and the blood clotting cascade in the AT-MSC-Hepa were relevant to liver-specific functions. Notably, decreases in Twist and Snail expression indicated that mesenchymal-to-epithelial transition occurred in the differentiation of AT-MSCs into hepatocytes. Our data show a similarity between AT-MSC-Hepa and the liver, suggesting that AT-MSCs are modulated by their environmental conditions, and that AT-MSC-Hepa may be useful in basic studies of liver function as well as in the development of stem cell-based therapy.

Molecular mapping of human hepatocellular carcinoma provides deeper biological insight from genomic data.

DNA microarray analysis of human cancer has resulted in considerable accumulation of global gene profiles. However, extraction and understanding the underlying biology of cancer progression remains a significant challenge. This study applied a novel integrative computational and analytical approach to this challenge in human hepatocellular carcinoma (HCC) with the aim of identifying potential molecular markers or novel therapeutic targets. We analysed 100 HCC tissue samples by human 30K DNA microarray. The gene expression data were uploaded into the network analysis tool, and the biological networks were displayed graphically. We identified several activated 'hotspot' regions harbouring a concentration of upregulated genes. Several 'hotspot' regions revealed integrin and Akt/NF-kappaB signalling. We identified key members linked to these signalling pathways including osteopontin (SPP1), glypican-3 (GPC3), annexin 2 (ANXA2), S100A10 and vimentin (VIM). Our integrative approach should significantly enhance the power of microarray data in identifying novel potential targets in human cancer.

Gene expression of colorectal cancer: preoperative genetic diagnosis using endoscopic biopsies.

In colorectal cancer, to predict the response to chemo- and/or radio-therapy or the existence of lymph node metastasis preoperatively, a more competent diagnostic system is required, in addition to conventional diagnosis based on morphology and pathology. The application of gene expression profiling to preoperative cancer diagnosis using endoscopic biopsies could enable the selection of a more appropriate therapy for patients. In this study, we evaluated the feasibility of gene expression profiling using preoperative biopsies of colorectal tumors in a clinical setting, by investigating the influence of intra-tumor heterogeneity on the profiles and testing the prediction ability of tumor malignancy. Under endoscopic examination, two biopsies were sampled from each of 10 colorectal cancers and 10 adenomas, and their gene expression data were obtained using cDNA microarrays. The intra- and inter-tumor heterogeneities of the profiles were compared with unsupervised clustering analysis. Molecular prediction of tumor malignancy using biopsies was performed with the supervised classification algorithm. In clustering analysis, almost all paired biopsies from the same tumors joined each other. Pearson's correlation coefficients of the profiles between biopsies from the same tumors (mean, 0.83) were significantly greater than those of the profiles between biopsies from other cancers (mean, 0.58) (p<0.0001). In the supervised classification method, malignancy was correctly predicted in 39 out of 40 biopsies with 8-71 informative genes. Gene expression profiling using endoscopic biopsies of colorectal tumors revealed that the intra-tumor heterogeneity was smaller than the inter-tumor heterogeneity and tumor malignancy was correctly predicted. Our findings suggest that the technique of gene expression profiling accurately represents the biological properties of colorectal cancer and could help the preoperative diagnosis of this disease.

Novel amino linkers enabling efficient labeling and convenient purification of amino-modified oligonucleotides.

We developed new amino linker reagents for an oligonucleotide (ONT) terminus. These reagents consist of an aminoethyl carbamate main linkage and a side-chain residue, which was a naphthylmethoxymethyl, methoxymethyl, or methyl group or a hydrogen atom. The primary amine was protected with a monomethoxytrityl (MMT) group. The chemical properties of ONTs containing these amino-modifications were investigated. The MMT group of these amino-modifications could be quite rapidly removed from the amine under very mild acidic conditions, which are not strong enough for the deprotection of a conventional aliphatic amine. This significant feature enabled the amino-modified ONTs to be conveniently purified with a reverse phase column. Furthermore, the amino-modifications efficiently reacted to active esters, as compared with other amino-modifications. We also found that the pK(a) values of the amino-modifications were lower than that of the aliphatic amine. All of the experimental results showed that these chemical properties are closely related to their structures. We report here the chemical properties and the availability of the new amino linker reagents.

WNT10B functional dualism: beta-catenin/Tcf-dependent growth promotion or independent suppression with deregulated expression in cancer.

We found aberrant DNA methylation of the WNT10B promoter region in 46% of primary hepatocellular carcinoma (HCC) and 15% of colon cancer samples. Three of 10 HCC and one of two colon cancer cell lines demonstrated low or no expression, and 5-aza-2'deoxycytidine reactivated WNT10B expression with the induction of demethylation, indicating that WNT10B is silenced by DNA methylation in some cancers, whereas WNT10B expression is up-regulated in seven of the 10 HCC cell lines and a colon cancer cell line. These results indicate that WNT10B can be deregulated by either overexpression or silencing in cancer. We found that WNT10B up-regulated beta-catenin/Tcf activity. However, WNT10B-overexpressing cells demonstrated a reduced growth rate and anchorage-independent growth that is independent of the beta-catenin/Tcf activation, because mutant beta-catenin-transduced cells did not suppress growth, and dominant-negative hTcf-4 failed to alleviate the growth suppression by WNT10B. Although WNT10B expression alone inhibits cell growth, it acts synergistically with the fibroblast growth factor (FGF) to stimulate cell growth. WNT10B is bifunctional, one function of which is involved in beta-catenin/Tcf activation, and the other function is related to the down-regulation of cell growth through a different mechanism. We suggest that FGF switches WNT10B from a negative to a positive cell growth regulator.

The gene expression profile represents the molecular nature of liver metastasis in colorectal cancer.

The major cause of death in colorectal cancer is related to liver metastasis. Although the metastatic process has been well studied, many aspects of the molecular genetic basis of metastasis remain unclear. Elucidation of the molecular nature of liver metastasis is urgent to improve the outcome of colorectal cancer. We analyzed the chronological gene expression profiles of 104 colorectal samples corresponding to oncogenic development including normal mucosa, localized and metastasized primary tumors, and liver metastatic lesions as fundamental samples using a custom cDNA microarray. The gene expression patterns in 104 samples were classified into four groups closely associated with their metastatic status, and the genes of each group appropriately reflected the metastatic process. To investigate the existence of metastatic potential in primary tumors using metastasis-related genes detected by chronological analysis, we performed a hierarchical cluster and supervised classification analysis of 28 independent primary tumors. Hierarchical cluster analysis segregated the tumors according to their final metastatic status, rather than their clinical stages, and the profile of metastasized primary tumors resembled one of a metastatic lesion apart from a primary lesion rather than one of a non-metastasized primary tumor. Using the supervised classification approach, the expression profile of these genes allowed the classification of tumors diagnosed as localized cancer into two classes, the localized and the metastasized class, according to their final metastatic status. The disease-free survival and overall survival were significantly longer in the localized class than the metastasized class. Chronological analysis of the gene expression profile provides a better understanding of the metastatic process. Our results suggest that the metastatic potential is already encoded in the primary tumor and is detectable by a gene expression profile, which allows the prediction of liver metastasis in patients diagnosed with localized tumors and also the design of new strategies for the treatment and diagnosis of colorectal cancer.

Microarray analysis of promoter methylation in lung cancers.

Aberrant DNA methylation is an important event in carcinogenesis. Of the various regions of a gene that can be methylated in cancers, the promoter is the most important for the regulation of gene expression. Here, we describe a microarray analysis of DNA methylation in the promoter regions of genes using a newly developed promoter-associated methylated DNA amplification DNA chip (PMAD). For each sample, methylated Hpa II-resistant DNA fragments and Msp I-cleaved (unmethylated+methylated) DNA fragments were amplified and labeled with Cy3 and Cy5 respectively, then hybridized to a microarray containing the promoters of 288 cancer-related genes. Signals from Hpa II-resistant (methylated) DNA (Cy3) were normalized to signals from Msp I-cleaved (unmethylated+methylated) DNA fragments (Cy5). Normalized signals from lung cancer cell lines were compared to signals from normal lung cells. About 10.9% of the cancer-related genes were hypermethylated in lung cancer cell lines. Notably, HIC1, IRF7, ASC, RIPK3, RASSF1A, FABP3, PRKCDBP, and PAX3 genes were hypermethylated in most lung cancer cell lines examined. The expression profiles of these genes correlated to the methylation profiles of the genes, indicating that the microarray analysis of DNA methylation in the promoter region of the genes is convenient for epigenetic study. Further analysis of primary tumors indicated that the frequency of hypermethylation was high for ASC (82%) and PAX3 (86%) in all tumor types, and high for RIPK3 in small cell carcinoma (57%). This demonstrates that our PMAD method is effective at finding epigenetic changes during cancer.

Methylation silencing of SOCS-3 promotes cell growth and migration by enhancing JAK/STAT and FAK signalings in human hepatocellular carcinoma.

We identified that suppressor of cytokine signaling-3 (SOCS-3) gene was aberrantly methylated in its CpG island in three of 10 human hepatocellular carcinoma (HCC) cell lines. SOCS-3 RNA was undetectable in five of the 10 HCC cell lines including the three methylated cell lines, and a demethylating agent, 5-aza-2'-deoxycytidine, reactivated SOCS-3 expression in three cell lines tested. The DNA region where we found aberrant DNA methylation includes a signal transducers and activators of transcription (STAT) binding consensus sequence. When the DNA region was used as a promoter, DNA methylation markedly reduced promoter activity. SOCS-3 was also aberrantly methylated in six of 18 primary HCC samples. SOCS-3 expression was reduced in three of the three methylated and one of the three unmethylated primary samples examined. Restoration of SOCS-3 in cells lacking SOCS-3 expression suppressed STAT3 phosphorylation and cell growth. We found that IL-6 acted as a growth factor in HCC cells. Inhibition of SOCS-3 expression in cells whose growth was induced by IL-6 enhanced STAT3 phosphorylation and cell growth. In addition, AG490, a chemical JAK2 inhibitor, suppressed cell growth and downregulated STAT3 phosphorylation, but not FAK phosphorylation. We also found that SOCS-3 physically interacted with phosphorylated FAK and Elongin B in HCC cells. Restoration of SOCS-3 decreased FAK phosphorylation as well as FAK protein level. Inhibition of SOCS-3 expression increased FAK phosphorylation, resulting in enhancement of cell migration. These data indicate that SOCS-3 negatively regulates cell growth and cell motility by inhibiting Janus kinase (JAK)/STAT and FAK signalings in HCC cells. Thus, loss of SOCS-3 by the associated DNA methylation confers cells advantage in growth and migration.