Search

Biliary atresia (BA) is characterized by a progressive, sclerosing, inflammatory process that leads to cirrhosis in infancy. Although it is the most common indication for liver transplantation in early childhood, little is known about its etiopathogenesis. To elucidate factors involved in this process, we performed comprehensive genome-wide gene expression analysis using complementary DNA (cDNA) microarrays. We compared messenger RNA expression levels of approximately 18,000 human genes from normal, diseased control, and end-stage BA livers. Reverse-transcription polymerase chain reaction (RT-PCR) and Northern blot analysis were performed to confirm changes in gene expression. Cluster and principal component analysis showed that all BA samples clustered together, forming a distinct group well separated from normal and diseased controls. We further identified 35 genes and ESTs whose expression differentiated BA from normal and diseased controls. Most of these genes are known to be associated with cell signaling, transcription regulation, hepatic development, morphogenesis, and fibrogenesis. In conclusion, this study serves to delineate processes that are involved in the pathogenesis of BA.

The use of DNA microarrays for the analysis of complex biological samples is becoming a mainstream part of biomedical research. One of the most commonly used methods compares the relative abundance of mRNA in two different samples by probing a single DNA microarray simultaneously. The simplicity of this concept sometimes masks the complexity of capturing and processing microarray data. On the basis of the analysis of many of our microarray experiments, we identified the major causes of distortion of the microarray data and the sources of noise. In this study, we provide a systematic statistical approach for extraction of true expression ratios from raw microarray data, which we describe as an unfolding process. The results of this analysis are presented in the form of a model describing the relationship between the measured fluorescent intensities and the concentrations of mRNA transcripts. We developed and tested several algorithms for inference of the model parameters for the microarray data. Special emphasis is given to the statistical robustness of these algorithms, in particular resistance to outliers. We also provide methods for measurement of noise and reproducibility of the microarray experiments.

The lack of reliable early detection of ovarian cancer and the absence of specific symptoms result in diagnosis of ovarian cancer at advanced stage in the majority of the patients. Through gene expression profiling we can identify important genes that may help understand the evolution from normal ovarian tissue to ovarian cancer. The gene expression profiles of 7 normal ovaries and 26 ovaries with serous epithelial ovarian cancer (SEOC) were examined by cDNA microarrays using supervised and unsupervised analysis, with sequential significance filtering. Real-time RT-PCR was used to measure and compare the expression levels of 5 selected genes: WAP four-disulfide core domain protein HE4 (WAP, up-regulated), secreted phosphoprotein 1 (SPP1, osteopontin; up-regulated), activin A receptor, type I (ACVR1, up-regulated), tumor necrosis factor (TNF superfamily, member 2; TNF, up-regulated) and decorin (DCN, down-regulated) in 4 epithelial scrapings and in 6 bulk-extracted normal ovaries. The gene expression profile of SEOC was not dependent on the stage of the disease at diagnosis. A supervised microarray data analysis identified a subset of 329 genes showing significant differential expression between SEOC samples and bulk normal ovarian tissue and ovarian surface scrapings, including several new genes such as TNFalpha and activin A receptor type I. The real-time RT-PCR for the up-regulated genes did not differ significantly between normal ovarian epithelial scrapings and bulk-extracted ovaries. However, decorin showed a statistically significant difference (P=0.0073) in expression between epithelial scrapings and bulk-extracted ovaries. Previously uncharacterized genes are associated with the malignant phenotype of SEOC. Bulk normal ovarian tissue may serve as control for SEOC tissue in gene expression profiling. Gene expression profiling and sequential statistical analyses of gene subsets can identify new genes and molecular pathways affecting development of SEOC. The genes of interest can be potential targets for future research of SEOC.

Administration of doxorubicin has been shown to prolong survival of patients with hepatocellular carcinoma (HCC). However, treatment regimen is often complicated by the emergence of drug resistance. The goal of our study is to enhance our understanding on the genetic changes that confer cellular chemoresistance to doxorubicin. To model this insensitive response, we established five doxorubicin-resistant (DOR) sublines through repeated exposure of escalating doses of doxorubicin to HCC cell lines (HKCI-2, -3, -4, -C1 and -C2). The DOR sublines developed displayed an average approximately 17-fold higher IC(50) value than their sensitive parental cell lines. The resistant phenotype displayed was investigated by the genome-wide analyses of comparative genomic hybridization (CGH) and complementary DNA microarray for the affected genomic anomalies and deregulated genes expressed, respectively. Over-representations of regional chr. 7q11-q21, 8q22-q23 and 10p13-pter were indicated in the DOR sublines from CGH analysis. Of particular interest was the finding of amplicon augmentations from regional or whole chromosome gains during the clonal expansion of resistant sublines. Most notably, recurring amplicon 7q11.2-q21 identified coincided with the location of the multi-drug-resistant gene, MDR1. The potential involvement of MDR1 was examined by quantitative reverse transcription-polymerase chain reaction RT-PCR (qRT-PCR), which indicated an upregulation in all DOR sublines (P=0.015). Consistent overexpression of the translated MDR1 gene, P-glycoprotein, in all five DOR sublines was further confirmed in Western blot analysis. Two distinct cluster dendrograms were achieved between the DOR sublines and their sensitive parental counterparts in expression profiling. Within the doxorubicin-resistant group, distinct features of candidate genes overexpressions including ABC transporting proteins, solute carriers and TOP2A were suggested. Further assessment of TOP2A messenger RNA levels by qRT-PCR confirmed array findings and pinpointed to a common up-regulation of TOP2A in DOR sublines. Our present study highlighted areas of genomic imbalances and candidate genes in the acquired doxorubicin-resistance behavior of HCC cells.

Treatment with IFN-alpha therapy has been shown to exhibit antitumor effects on patients with hepatocellular carcinoma (HCC). However, individual responses remained unpredictable because of the frequent presence of intrinsic or acquired IFN-alpha resistance. Hence, delineation of molecular targets implicated in the resistant pathway holds value in refining the therapeutic benefits of IFN-alpha.The current study analyzed the effect of IFN-alpha in human HCC cells. Three hepatitis C virus (HCV)-related, five hepatitis B virus (HBV)-related and two non-B non-C-related cell lines were subjected to IFN-alpha treatment and the cytotoxic effect on cell viability was measured. Further analysis by cDNA microarray and quantitative reverse transcription-PCR were conducted to examine the gene expression changes that mediated the IFN-alpha resistance observed.According to the IC(50) values determined, HCV-related cell lines indicated distinct resistance (IC(50), 389-1468 units/mL) compared with the HBV-related (IC(50), 11-77 units/mL) and non-B non-C-related cell lines (IC(50), 24-108 units/mL). Unsupervised hierarchical clustering on array data indicated three HCV-related cell lines to cluster independently from the sensitive cell lines, suggesting discrete features in association with IFN-alpha tolerance. Moreover, Significance Analysis of Microarrays analysis indicated the differential expression of 149 expressed sequence tags that represented 51 up-regulated and 98 down-regulated genes in the resistant cell lines. Comparing the temporal pattern of gene expression between 6- and 24-hour treatments, candidate genes that were considerably induced with time were further highlighted in the tolerant HCV-related cell lines. These candidates were verified by quantitative reverse transcription-PCR, which confirmed the down-regulation of UBA2, ZNF185, and FOXF1 and up-regulation of UBE4B in the drug-tolerant cells.Our present study showed that the insensitivity to IFN-alpha therapy in HCC cells is associated with drug-inducible transcriptional alterations. Furthermore, our investigation highlighted potential candidate genes in conferring an anti-apoptotic effect toward IFN-alpha treatment.

Chromosomal rearrangements unraveled by spectral karyotyping (SKY) indicated frequent chromosome 19 translocations in hepatocellular carcinoma (HCC). In an effort to characterize the aberrant 19 rearrangements in HCC, we performed positional mapping by fluorescence in-situ hybridization (FISH) in 10 HCC cell lines. SKY analysis indicated structural rearrangements of chromosome 19 in 6 cell lines, 4 of which demonstrated recurring 19p translocations with different partner chromosomes. Using fluorescence-labeled BAC probes, physical mapping indicated a breakpoint cluster between 19p13.12 and 19p12. A corresponding transcriptional mapping by cDNA array on 19p suggested the differential expression of a single downregulated gene ACP5 (tartrate-resistant acid phosphatase type 5). Quantitative RT-PCR confirmed the reduced expression of ACP5 and indicated a strong correlation of its repressed expression only in cell lines that contain a 19p rearrangement (p = 0.004). We further examined the expression of ACP5 in a cohort of 82 primary tumors and 74 matching nonmalignant liver tissues. In the primary HCC examined, a reduction of ACP5 transcripts by 2 to as much as 1,000-fold was suggested in 67% of tumors (55/82 cases). When compared to adjacent nonmalignant tissues, 46% of tumors (34/74 cases) demonstrated a lower expression level (p = 0.015). On closer examination, a high significance of ACP5 repression was suggested in the cirrhotic HCC subgroup that was derived from chronic hepatitis B infected patients (55%; 30/54 cases; p = 0.001). Functional examination of ACP5 ectopic expression in HCC cells further demonstrated a significant growth inhibitory effect of ACP5 on tumor cell survival (p < 0.001). In our study, the novel finding of common ACP5 downregulation in HCC may provide basis for further investigations on the role of acid phosphatase in hepatocarcinogenesis.

Despite a prolongation of patient survival, the overall response of doxorubicin (DX) treatment on patients with hepatocellular carcinoma (HCC) remains modest. This is largely attributed to the development of tumor drug resistance either at the onset or during the course of treatment. To investigate the genetic changes associated with DX chemo-resistance, we examined the cytotoxic effect of DX on a panel of 9 HCC cell lines (HepG2, Hep3B, PLC/PRF/5, and six in-house established, HKCI-1, 2, 3 and 4, C1 and C2). The karyotypic abnormalities were examined by spectral karyotyping (SKY) and the chromosome loci defined were investigated for underlying deregulated genes by positional expression profiling. Quantitative RT-PCR was employed to verify the profiling findings, and also used to examine a number of drug resistance-related candidate genes (MDR1, MRP1, MGMT, PTEN, BCL2, BAX, TP53 and P21). Our results indicated that the cytotoxic effect of DX in cell lines exhibited IC50 values that ranged from sensitive to resistant (0.07 to 3.55 microM). While the overall chromosome aneuploidy did not correlate with DX resistance, aberrations on chromosome 10 demonstrated significant correlation with increasing IC50 (p=0.007). Positional profiling further suggested the consistent down-regulation of CGI-18 and ECHS1 on chromosome 10q. The array findings were substantiated by quantitative RT-PCR, which further pointed to a repressed ECHS1 expression in correlation with DX resistance (p=0.021). Among the candidate genes studied, an inverse relationship of P21 (p=0.034) and BAX (p=0.002) expression with DX resistance was also indicated. Our present study highlights the usefulness of multimodality approaches in identifying genetic markers, and further describes the novel finding of ECHS1 down-regulation in the DX chemo-resistance of HCC.

Genome-wide monitoring of gene expression using DNA microarrays represents one of the latest breakthroughs in experimental molecular biology and provides unprecedented opportunity to explore the biological processes underlying human diseases by providing a comprehensive survey of a cell's transcriptional landscape. In the cancer field, this revolutionary technology allows the simultaneous assessment of the transcription of tens of thousands of genes, and of their relative expression between normal cells and malignant cells. As microarray analysis emerges from its infancy, there is widespread hope that microarrays will significantly impact on our ability to explore the genetic changes associated with cancer etiology and development, and ultimately lead to the discovery of new biomarkers for disease diagnosis and prognosis prediction, and of new therapeutic tools. This review provides an overview of microarray technology, specifically in the context of cancer research and describes some of its recent applications to the study of cancer. In addition, the challenges of translating microarray findings into molecular cancer diagnosis and prognosis tools, with the potential of altering clinical practice through individualized cancer care and ultimately of contributing to the battle against cancer, are discussed.

Molecular diagnostics is a rapidly advancing field in which insights into disease mechanisms are being elucidated by use of new gene-based biomarkers. Until recently, diagnostic and prognostic assessment of diseased tissues and tumors relied heavily on indirect indicators that permitted only general classifications into broad histologic or morphologic subtypes and did not take into account the alterations in individual gene expression. Global expression analysis using microarrays now allows for simultaneous interrogation of the expression of thousands of genes in a high-throughput fashion and offers unprecedented opportunities to obtain molecular signatures of the state of activity of diseased cells and patient samples. Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments and ultimately may lead to improved early diagnosis and innovative therapeutic approaches for cancer.

Analysis of ovarian carcinomas has shown that karyotypes are often highly abnormal and cannot be identified with certainty by conventional cytogenetic methods. In this study, 17 tumors derived from 13 patients were analyzed by a combination of spectral karyotyping (SKY), comparative genomic hybridization (CGH), and expression microarrays. Within the study group, a total of 396 chromosomal rearrangements could be identified by SKY and CGH analysis. When the distribution of aberrations was normalized with respect to relative genomic length, chromosomes 3, 8, 11, 17, and 21 had the highest frequencies. Parallel microarray expression studies of 1718 human cDNAs were used to analyze expression profiles and to determine whether correlating gene expression with chromosomal rearrangement would identify smaller subsets of differentially expressed genes. Within the entire set of samples, microarray expression analysis grouped together poorly differentiated tumors irrespective of histological subtype. For three patients, a comparison between genomic alterations and gene expression pattern was performed on samples of primary and metastatic tumors. Their common origin was demonstrated by the close relationship of both the SKY and CGH karyotypes and the observed profiles of gene expression. In agreement with the pattern of genomic imbalance observed for chromosome 3 in ovarian cancer, the relative expression profile with respect to a normal ovary exhibited a contiguous pattern of reduced expression of genes mapping to the 3p25.5-3p21.31 and increased expression of genes from 3q13.33-3q28. This study demonstrates that SKY, CGH, and microarray analysis can in combination identify significantly smaller subsets of differentially expressed genes for future studies.

Array comparative genomic hybridization (aCGH) and microarray expression profiling were used to subclassify DNA and RNA alterations associated with differential response to chemotherapy in ovarian cancer. Two to 4 Mb interval arrays were used to map genomic imbalances in 26 sporadic serous ovarian tumors. Cytobands 1p36, iq42-44, 6p22.1-p21.2, 7q32.1-q34 9q33.3-q34.3, 11p15.2, 13q12.2-q13.1, 13q21.31, 17q11.2, 17q24.2-q25.3, 18q12.2, and 21q21.2-q21.3 were found to be statistically associated with chemotherapy response, and novel regions of loss at 15g11.2q15.1 and 17q21.32-q21.33 were identified. Gene expression profiles were obtained from a subset of these tumors and identified a group of genes whose differential expression was significantly associated with drug resistance. Within this group, five genes (GAPD, HMGB2, HSC70, GRP58, and HMGB1), previously shown to form a nuclear complex associated with resistance to DNA conformation-altering chemotherapeutic drugs in in vitro systems, may represent a novel class of genes associated with in vivo drug response in ovarian cancer patients. Although RNA expression change indicated only weak DNA copy number dependence, these data illustrate the value of molecular profiling at both the RNA and DNA levels to identify small genomic regions and gene subsets that could be associated with differential chemotherapy response in ovarian cancer.