Showing papers by "Rork Kuick published in 2003"

Distinct Transcriptional Profiles of Adrenocortical Tumors Uncovered by DNA Microarray Analysis

Abstract: Comprehensive expression profiling of tumors using DNA microarrays has been used recently for molecular classification and biomarker discovery, as well as a tool to identify and investigate genes involved in tumorigenesis. Application of this approach to a cohort of benign and malignant adrenocortical tissues would be potentially informative in all of these aspects. In this study, we generated transcriptional profiles of 11 adrenocortical carcinomas (ACCs), 4 adrenocortical adenomas (ACAs), 3 normal adrenal cortices (NCs), and 1 macronodular hyperplasia (MNH) using Affymetrix HGU95Av2 oligonucleotide arrays representing 10,500 unique genes. The expression data set was used for unsupervised hierarchical cluster analysis as well as principal component analysis to visually represent the expression data. An analysis of variance on the three classes (NC, ACA plus MNH, and ACC) revealed 91 genes that displayed at least threefold differential expression between the ACC cohort and both the NC and ACA cohorts at a significance level of P < 0.01. Included in these 91 genes were those known to be up-regulated in adrenocortical tumors, such as insulin-like growth factor (IGF2), as well as novel differentially expressed genes such as osteopontin (SPP) and serine threonine kinase 15 (STK15). Increased expression of IGF2 was identified in 10 of 11 ACCs (90.9%) and was verified by quantitative reverse transcriptase-polymerase chain reaction. Select proliferation-related genes (TOP2A and Ki-67) were validated at the protein level using immunohistochemistry and adrenocortical tissue microarrays. Our results demonstrated significant and consistent gene expression changes in ACCs compared to benign adrenocortical lesions. Moreover, we identified several genes that represent potential diagnostic markers and may play a role in the pathogenesis of ACC. (Am J Pathol 2003, 162:521–531) Adrenocortical carcinoma (ACC) is a rare but highly lethal cancer with an annual incidence of 0.5 to 2 patients

Characterization of gene expression profiles associated with glioma progression using oligonucleotide-based microarray analysis and real-time reverse transcription-polymerase chain reaction.

Abstract: Diffuse astrocytoma of World Health Organization (WHO) grade II has an inherent tendency to spontaneously progress to anaplastic astrocytoma (WHO grade III) and/or glioblastoma (WHO grade IV). The molecular basis of astrocytoma progression is still poorly understood, in particular with respect to the progression-associated changes at the mRNA level. Therefore, we compared the transcriptional profile of approximately 6800 genes in primary WHO grade II gliomas and corresponding recurrent high-grade (WHO grade III or IV) gliomas from eight patients using oligonucleotide-based microarray analysis. We identified 66 genes whose mRNA levels differed significantly (P < 0.01, ≥2-fold change) between the primary and recurrent tumors. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of 12 selected genes, including 7 genes with increased expression and 5 genes with reduced expression on progression. In addition, the expression of these 12 genes was determined in an independent series of 43 astrocytic gliomas (9 diffuse astrocytomas, 10 anaplastic astrocytomas, 17 primary, and 7 secondary glioblastomas). These analyses confirmed that the transcript levels of nine of the selected genes (COL4A2, FOXM1, MGP, TOP2A, CENPF, IGFBP4, VEGFA, ADD3, and CAMK2G) differed significantly in WHO grade II astrocytomas as compared to anaplastic astrocytomas and/or glioblastomas. Thus, we identified and validated a set of interesting candidate genes whose differential expression likely plays a role in astrocytoma progression.

Protein profiles associated with survival in lung adenocarcinoma

Abstract: Morphologic assessment of lung tumors is informative but insufficient to adequately predict patient outcome. We previously identified transcriptional profiles that predict patient survival, and here we identify proteins associated with patient survival in lung adenocarcinoma. A total of 682 individual protein spots were quantified in 90 lung adenocarcinomas by using quantitative two-dimensional polyacrylamide gel electrophoresis analysis. A leave-one-out cross-validation procedure using the top 20 survival-associated proteins identified by Cox modeling indicated that protein profiles as a whole can predict survival in stage I tumor patients (P = 0.01). Thirty-three of 46 survival-associated proteins were identified by using mass spectrometry. Expression of 12 candidate proteins was confirmed as tumor-derived with immunohistochemical analysis and tissue microarrays. Oligonucleotide microarray results from both the same tumors and from an independent study showed mRNAs associated with survival for 11 of 27 encoded genes. Combined analysis of protein and mRNA data revealed 11 components of the glycolysis pathway as associated with poor survival. Among these candidates, phosphoglycerate kinase 1 was associated with survival in the protein study, in both mRNA studies and in an independent validation set of 117 adenocarcinomas and squamous lung tumors using tissue microarrays. Elevated levels of phosphoglycerate kinase 1 in the serum were also significantly correlated with poor outcome in a validation set of 107 patients with lung adenocarcinomas using ELISA analysis. These studies identify new prognostic biomarkers and indicate that protein expression profiles can predict the outcome of patients with early-stage lung cancer.

Novel Candidate Targets of β-Catenin/T-cell Factor Signaling Identified by Gene Expression Profiling of Ovarian Endometrioid Adenocarcinomas

Abstract: The activity of beta-catenin (beta-cat), a key component of the Wnt signaling pathway, is deregulated in about 40% of ovarian endometrioid adenocarcinomas (OEAs), usually as a result of CTNNB1 gene mutations. The function of beta-cat in neoplastic transformation is dependent on T-cell factor (TCF) transcription factors, but specific genes activated by the interaction of beta-cat with TCFs in OEAs and other cancers with Wnt pathway defects are largely unclear. As a strategy to identify beta-cat/TCF transcriptional targets likely to contribute to OEA pathogenesis, we used oligonucleotide microarrays to compare gene expression in primary OEAs with mutational defects in beta-cat regulation (n = 11) to OEAs with intact regulation of beta-cat activity (n = 17). Both hierarchical clustering and principal component analysis based on global gene expression distinguished beta-cat-defective tumors from those with intact beta-cat regulation. We identified 81 potential beta-cat/TCF targets by selecting genes with at least 2-fold increased expression in beta-cat-defective versus beta-cat regulation-intact tumors and significance in a t test (P < 0.05). Seven of the 81 genes have been previously reported as Wnt/beta-cat pathway targets (i.e., BMP4, CCND1, CD44, FGF9, EPHB3, MMP7, and MSX2). Differential expression of several known and candidate target genes in the OEAs was confirmed. For the candidate target genes CST1 and EDN3, reporter and chromatin immunoprecipitation assays directly implicated beta-cat and TCF in their regulation. Analysis of presumptive regulatory elements in 67 of the 81 candidate genes for which complete genomic sequence data were available revealed an apparent difference in the location and abundance of consensus TCF-binding sites compared with the patterns seen in control genes. Our findings imply that analysis of gene expression profiling data from primary tumor samples annotated with detailed molecular information may be a powerful approach to identify key downstream targets of signaling pathways defective in cancer cells.

Molecular profiling of the immune response in colon cancer using protein microarrays: occurrence of autoantibodies to ubiquitin C-terminal hydrolase L3.

Abstract: We implemented a protein microarray approach to identify proteins that induce a humoral response in colon cancer. Solubilized proteins from the LoVo colon adenocarcinoma cell line were separated into 1760 fractions, arrayed onto nitrocellulose-coated slides, and hybridized with individual sera from 15 newly diagnosed patients with colon cancer, 15 with lung cancer, and 15 healthy subjects. 39/1760 fractions showed enhanced reactivity with sera from patients with colon cancer (p < 0.01) relative to healthy controls. A distinct pattern of reactivity was observed with sera from colon cancer relative to lung cancer. One fraction that exhibited reactivity with 9/15 colon cancer sera was subjected to mass spectrometry leading to the identification of ubiquitin C-terminal hydrolase isozyme 3 (UCH-L3) as a constituent. To validate the occurrence of autoantibodies to UCH-L3, independent analysis was done by means of Western blots. UCH-L3 antibodies were detected in 19/43 sera from patients with colon cancer, and in 0/54 sera from subjects with lung cancer (24), colon adenoma (15) or otherwise healthy (15). Our findings indicate the occurrence of an immune response to a broad set of antigens in colon cancer and the feasibility of identifying the antigenic targets using a combination of protein microarrays and mass spectrometry.

Pancreatic gene expression during the initiation of acute pancreatitis: identification of EGR-1 as a key regulator

Abstract: We hypothesized that genes expressed in pancreatic acinar cells during the initiation of acute pancreatitis determine the severity of the disease. Therefore, we utilized microarrays to identify tho...

Accurate molecular classification of human cancers based on gene expression using a simple classifier with a pathological tree-based framework.

Abstract: Recent studies suggest accurate prediction of tissue of origin for human cancers can be achieved by applying sophisticated statistical learning procedures to gene expression data obtained from DNA microarrays. We have pursued the hypothesis that a more straightforward and equally accurate strategy for classifying human tumors is to use a simple algorithm that considers gene expression levels within a tree-based framework that encodes limited information about pathology and tissue ontogeny. By considering gene expression data within this framework, we found only a small number of genes were required to achieve a relatively high accuracy level in tumor classification. Using as few as 45 genes we were able to classify 157 of 190 human malignant tumors correctly, which is comparable to previous results obtained with sophisticated classifiers using thousands of genes. Our simple classifier accurately predicted the origin of metastatic tumors even when the classifier was trained using only primary tumors, and the classifier produced accurate predictions when trained and tested on expression data from different labs, and from different microarray platforms. Our findings suggest that accurate and robust cancer diagnosis from gene expression profiles can be achieved by mimicking the classification strategies routinely used by surgical pathologists.

Amplification and Overexpression of the L-MYC Proto-Oncogene in Ovarian Carcinomas

Abstract: Gene amplification is an important mechanism of oncogene activation in various human cancers, including ovarian carcinomas (OvCas). We used restriction landmark genomic scanning (RLGS) to detect amplified DNA fragments in the genomes of 47 primary OvCas. Visual analysis of the RLGS gel images revealed several OvCa samples with spots of greater intensity than corresponding spots from normal tissues, indicating possible DNA amplification in specific tumors. Two primary tumors (E1 and S12) shared four high-intensity spots. A recently developed informatics tool termed Virtual Genome Scans was used to compare the RLGS patterns in these tumors with patterns predicted from the human genome sequence. Virtual Genome Scans determined that three of the four fragments localized to chromosome 1p34-35, a region containing the proto-oncogene L-MYC. Sixty-eight primary OvCas, including 40 analyzed by RLGS, were screened by quantitative polymerase chain reaction (PCR) for possible amplification of L-MYC. Ten tumors with increased L-MYC copy number were identified, including tumor E1, which showed an ∼24-fold increase in copy number compared to normal DNA. Southern analysis of several tumors confirmed the quantitative PCR results. Using sequence tagged site (STS) markers flanking L-MYC, increased DNA copy number in tumor E1 was found to span the region flanking L-MYC between D1S432 and D1S463 (≈3.1 Mb). Other tumors showed amplification only at the L-MYC locus. Using oligonucleotide microarrays, L-MYC was found to be more frequently overexpressed in OvCas than either c-MYC or N-MYC relative to ovarian surface epithelium. Quantitative reverse transcriptase-PCR analysis confirmed elevated L-MYC expression in a substantial fraction of OvCas, including nine of nine tumors with increased L-MYC copy number. The data implicate L-MYC gene amplification and/or overexpression in human OvCa pathogenesis.

Profiling of pathway-specific changes in gene expression following growth of human cancer cell lines transplanted into mice

Abstract: Background Tumor cells cultured in vitro are widely used to investigate the molecular biology of cancers and to evaluate responses to drugs and other agents. The full extent to which gene expression in cancer cells is modulated by extrinsic factors and by the microenvironment in which the cancer cells reside remains to be determined. Two cancer cell lines (A549 lung adenocarcinoma and U118 glioblastoma) were transplanted subcutaneously into immunodeficient mice to form tumors. Global gene-expression profiles of the tumors were determined, based on analysis of expression of human genes, and compared with expression profiles of the cell lines grown in culture.

Inducible Expression of Macrophage Receptor Marco by Dendritic Cells Following Phagocytic Uptake of Dead Cells Uncovered by Oligonucleotide Arrays

Abstract: The efficient Ag presenting and immunostimulatory capacity of dendritic cells (DCs) has led to the use of tumor Ag-pulsed DCs in treatment regimens for cancer. Although vaccine studies involving tumor lysate-pulsed DCs have been performed, little, if any, information is available on the effects of phagocytic uptake of tumor lysate on DC biology and function. We have investigated gene expression pattern differences between unpulsed DCs and tumor lysate-pulsed-DCs, using Affymetrix MG-U74Av2 oligonucleotide arrays, which contain ∼12,000 genes and expressed sequence tags. Upon 24 h tumor lysate pulsing, the levels of 87 transcripts increased at least 3-fold while the levels of 121 transcripts were reduced by one-third or more, with accompanying p values <0.01. Most of these genes encoded proteins important for DC effector functions including cytokines, chemokines, and receptors, such as IL-12p40, macrophage inflammatory protein-2, and IL-6; Ag presentation, such as carboxypeptidase D and H2-DM; cell adhesion (e.g., EGF-like module containing, mucin-like, hormone receptor-like sequence 1, rhoB); and T cell activation. Interestingly, we observed a high level of expression of a novel member of the class A scavenger receptor family, macrophage receptor with collagenous structure (Marco). Marco is thought to play an important role in the immune response by mediating binding and phagocytosis, but also in the formation of lamellipodia-like structures and of dendritic processes. Therefore, we have identified a repertoire of genes that likely play a role in DC function.

Expression profile of lung cancer

Abstract: The present invention relates to compositions and methods for cancer diagnostics, including but not limited to, cancer markers. In particular, the present invention provides gene expression profiles associated with lung cancers. Genes identified as cancer markers find use in the diagnosis and characterization of lung cancer. In addition, the genes provide targets for cancer drug screens and therapeutic applications.

Molecular profiling of pancreatic adenocarcinoma and chronic pancreatitis identifies multiple genes differentially regulated in pancreatic cancer (Cancer Research (2003) (2649-2657))

Abstract: The molecular basis of pancreatic cancer is not understood. Previous attempts to determine the specific genes expressed in pancreatic cancer have been hampered by similarities between adenocarcinoma and chronic pancreatitis. In the current study, microarrays (Affymetrix) were used to profile gene expression in pancreatic adenocarcinoma (10), pancreatic cancer cell lines (7), chronic pancreatitis (5), and normal pancreas (5). Molecular profiling indicated a large number of genes differentially expressed between pancreatic cancer and normal pancreas but many fewer differences between pancreatic cancer and chronic pancreatitis, likely because of the shared stromal influences in the two diseases. To specifically identify genes expressed in neoplastic epithelium, we selected genes more highly expressed (>2-fold, p < 0.01) in adenocarcinoma compared with both normal pancreas and chronic pancreatitis and which were also highly expressed in pancreatic cancer cell lines. This strategy yielded 158 genes, of which 124 were not previously associated with pancreatic cancer. Quantitative-reverse transcription-PCR for two molecules, S100P and 14-3-3sigma, validated the microarray data. Support for the success of the neoplastic cell gene expression identification strategy was obtained by immunocytochemical localization of four representative genes, 14-3-3sigma, S100P, S100A6, and beta4 integrin, to neoplastic cells in pancreatic tumors. Thus, comparisons between pancreatic adenocarcinoma, pancreatic cancer cell lines, normal pancreas, and chronic pancreatitis have identified genes that are selectively expressed in the neoplastic epithelium of pancreatic adenocarcinoma. These data provide new insights into the molecular pathology of pancreatic cancer that may be useful for detection, diagnosis, and treatment.

Proteomic analysis of eIF-5A in lung adenocarcinomas

Abstract: We examined the eIF-5A protein expression in 93 lung adenocarcinomas and 10 uninvolved lung samples using quantitative two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) analysis with identification by mass spectrometry and 2-D Western blots. The same tissue samples were examined for the eIF-5A mRNA expression using oligonucleotide microarrays, and the cellular localization of the eIF-5A protein was examined using immunohistochemical analysis on tissue arrays. Higher eIF-5A protein expression was present in tumors showing poor differentiation, 12/13(th) codon K-ras mutations, p53 nuclear accumulation, and tumors with positive lymphocytic response. The eIF-5A mRNA was also significantly increased in lung adenocarcinomas compared to normal lung, but the eIF-5A protein expression was not correlated to its mRNA levels indicating that the increase in the eIF-5A protein expression in lung tumors is post-transcriptionally/translationally/post-translationally regulated. Patients having a higher eIF-5A protein expression showed a relatively poorer survival suggesting the use of eIF-5A as prognostic marker in lung adenocarcinoma. Moreover, the investigation on agents that inhibit eIF-5A function is encouraged.