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Results for “Expression profiling”

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PubMed2003

Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors.

PURPOSE: The purpose of this study was to determine whether comprehensive transcriptional profiles (TPs) can be obtained from single-passage fine-needle aspirations (FNAs) of breast cancer and to explore whether profiles capture routine clinicopathological parameters. EXPERIMENTAL DESIGN: Expression profiles were available on 38 patients with stage I-III breast cancer who underwent FNA at the time of diagnosis. [(33)P]dCTP-labeled cDNA probes were generated and hybridized to cDNA membrane microarrays that contained 30,000 human sequence clones, including 10,890 expressed sequence tags. RESULTS: The median total RNA yield from the biopsies was 2 micro g (range, 1-25 micro g). The cellular composition of each biopsy was examined and, on average, 79% of the cells were cancer cells. TP was successfully performed on all 38 of the biopsies. Unsupervised complete-linkage hierarchical clustering with all of the biopsies revealed an association between estrogen receptor (ER) status and gene expression profiles. There was a strong correlation between ER status determined by TP and measured by routine immunohistochemistry (P = 0.001). A similar strong correlation was seen with HER-2 status determined by fluorescent in situ hybridization (P = 0.0002). Using the first 18 cases as the discovery set, we established a cutoff of 2.0 and 18.0 for ER and HER-2 mRNA levels, respectively, to distinguish clinically-negative from -positive cases. We also identified 105 genes (excluding the ER gene) the expression of which correlated highly with clinical ER status. Twenty tumors were used for prospective validation. HER-2 status was correctly identified in all 20 of the cases, based on HER-2 mRNA content detected by TP. ER status was correctly identified in 19 of 20 cases. When the marker set of 105 genes was used to prospectively predict ER status, TP-based classification correctly identified 9 of 10 of the ER-positive and 7 of 10 of the ER-negative tumors. We also explored supervised cluster analysis using various functional categories of genes, and we observed a clear separation between ER-negative and ER-positive tumors when genes involved in signal transduction were used for clustering. CONCLUSIONS: These results demonstrate that comprehensive TP can be performed on FNA biopsies. TPs reliably measure conventional single-gene prognostic markers such as ER and HER-2. A complex pattern of genes (not including ER) can also be used to predict clinical ER status. These results demonstrate that needle biopsy-based diagnostic microarray tests may be developed that could capture conventional prognostic information but may also contain additional clinical information that cannot currently be measured with other methods.

Adult↗

PubMed2003

Gene-expression profiles of human tumor xenografts in nude mice treated orally with the EGFR tyrosine kinase inhibitor ZD1839.

To date, no single or multiple molecular markers have been successful in predicting sensitivity of individual patients to anti-cancer drugs. As the nature of a specific cancer is considered to be defined by the proteins being expressed in the tumor cells, systematic analysis of gene-expression profiles may provide information reflecting sensitivity of a given tumor to certain drugs. Recent progress in genome technology has enabled us to examine expression profiles of thousands of genes in a single experiment. We used this approach to examine 13 xenografts of human tumors implanted into nude mice for sensitivity to an orally active, selective epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), ZD1839 (Iressa). To identify genes that might be associated with sensitivity to this drug we used a cDNA microarray representing 23,040 genes to analyze expression profiles of the 13 xenografts and identified 114 genes whose expression levels correlated significantly with sensitivity of the tumors to ZD1839. We then investigated alteration of expression profiles in response to the ZD1839 treatment in four non-small cell lung cancer (NSCLC) xenografts, of which two (LC6 and LC11) were sensitive and the other two (Lu116 and L27) were resistant to this EGFR-TKI. Systematic analysis of expression at various time points during oral treatment for 14 days, compared with corresponding untreated samples, identified a set of genes whose expression levels changed in the two sensitive tumors but not in the two resistant tumors. The data obtained here should provide useful information on the molecular mechanism underlying clinical responses to EGFR-TKIs, aid the development of novel therapies for lung cancer, and potentially identify predictive molecular markers for sensitivity to ZD1839.

Administration, Oral↗

PubMed2001

Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification.

To better understand the molecular mechanisms that underlie the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC), we studied the gene expression profiles of 29 ccRCC tumors obtained from patients with diverse clinical outcomes by using 21,632 cDNA microarrays. We identified gene expression alterations that were both common to most of the ccRCC studied and unique to clinical subsets. There was a significant distinction in gene expression profile between patients with a relatively nonaggressive form of the disease [100% survival after 5 years with the majority (15/17 or 88%) having no clinical evidence of metastasis] versus patients with a relatively aggressive form of the disease (average survival time 25.4 months with a 0% 5-year survival rate). Approximately 40 genes most accurately make this distinction, some of which have previously been implicated in tumorigenesis and metastasis. To test the robustness and potential clinical usefulness of this molecular distinction, we simulated its use as a prognostic tool in the clinical setting. In 96% of the ccRCC cases tested, the prediction was compatible with the clinical outcome, exceeding the accuracy of prediction by staging. These results suggest that two molecularly distinct forms of ccRCC exist and that the integration of expression profile data with clinical parameters could serve to enhance the diagnosis and prognosis of ccRCC. Moreover, the identified genes provide insight into the molecular mechanisms of aggressive ccRCC and suggest intervention strategies.

Adenocarcinoma, Clear Cell↗

PubMed2003

DNA microarrays for comparison of gene expression profiles between diagnosis and relapse in precursor-B acute lymphoblastic leukemia: choice of technique and purification influence the identification of potential diagnostic markers.

Microarrays for gene expression profiling are rapidly becoming important research tools for the identification of novel markers, for example, for novel classification of leukemias and lymphomas. Here, we review the considerations and infrastructure for microarray experiments. These considerations are illustrated via a microarray-based comparison of gene expression profiles of paired diagnosis-relapse samples from patients with precursor-B acute lymphoblastic leukemia (ALL), who relapsed during therapy or after completion of treatment. Initial experiments showed that several seemingly differentially expressed genes were actually derived from contaminating non-leukemic cells, particularly myeloid cells and T-lymphocytes. Therefore, we purified the ALL cells of the diagnosis and relapse samples if their frequency was lower than 95%. Furthermore, we observed in earlier studies that extra RNA amplification leads to skewing of particular gene transcripts. Sufficient (non-amplified) RNA of purified and paired diagnosis-relapse samples was obtained from only seven cases. The gene expression profiles were evaluated with Affymetrix U95A chips containing 12 600 human genes. These diagnosis-relapse comparisons revealed only a small number of genes (n=6) that differed significantly in expression: mostly signaling molecules and transcription factors involved in cell proliferation and cell survival were highly upregulated at relapse, but we did not observe any increase in drug-resistance markers. This finding fits with the observation that tumors with a high proliferation index have a poor prognosis. The genes that changed between diagnosis and relapse are currently not in use as diagnostic or disease progression markers, but represent potential new markers for such applications. Leukemia (2003) 17, 1324-1332. doi:10.1038/sj.leu.2402974

Biomarkers↗

PubMed2002

Adaptive quality-based clustering of gene expression profiles.

MOTIVATION: Microarray experiments generate a considerable amount of data, which analyzed properly help us gain a huge amount of biologically relevant information about the global cellular behaviour. Clustering (grouping genes with similar expression profiles) is one of the first steps in data analysis of high-throughput expression measurements. A number of clustering algorithms have proved useful to make sense of such data. These classical algorithms, though useful, suffer from several drawbacks (e.g. they require the predefinition of arbitrary parameters like the number of clusters; they force every gene into a cluster despite a low correlation with other cluster members). In the following we describe a novel adaptive quality-based clustering algorithm that tackles some of these drawbacks. RESULTS: We propose a heuristic iterative two-step algorithm: First, we find in the high-dimensional representation of the data a sphere where the "density" of expression profiles is locally maximal (based on a preliminary estimate of the radius of the cluster-quality-based approach). In a second step, we derive an optimal radius of the cluster (adaptive approach) so that only the significantly coexpressed genes are included in the cluster. This estimation is achieved by fitting a model to the data using an EM-algorithm. By inferring the radius from the data itself, the biologist is freed from finding an optimal value for this radius by trial-and-error. The computational complexity of this method is approximately linear in the number of gene expression profiles in the data set. Finally, our method is successfully validated using existing data sets. AVAILABILITY: http://www.esat.kuleuven.ac.be/~thijs/Work/Clustering.html

Algorithms↗

PubMed2003

Systematic expression profiling of the mouse transcriptome using RIKEN cDNA microarrays.

The number of known mRNA transcripts in the mouse has been greatly expanded by the RIKEN Mouse Gene Encyclopedia project. Validation of their reproducible expression in a tissue is an important contribution to the study of functional genomics. In this report, we determine the expression profile of 57,931 clones on 20 mouse tissues using cDNA microarrays. Of these 57,931 clones, 22,928 clones correspond to the FANTOM2 clone set. The set represents 20,234 transcriptional units (TUs) out of 33,409 TUs in the FANTOM2 set. We identified 7206 separate clones that satisfied stringent criteria for tissue-specific expression. Gene Ontology terms were assigned for these 7206 clones, and the proportion of 'molecular function' ontology for each tissue-specific clone was examined. These data will provide insights into the function of each tissue. Tissue-specific gene expression profiles obtained using our cDNA microarrays were also compared with the data extracted from the GNF Expression Atlas based on Affymetrix microarrays. One major outcome of the RIKEN transcriptome analysis is the identification of numerous nonprotein-coding mRNAs. The expression profile was also used to obtain evidence of expression for putative noncoding RNAs. In addition, 1926 clones (70%) of 2768 clones that were categorized as "unknown EST," and 1969 (58%) clones of 3388 clones that were categorized as "unclassifiable" were also shown to be reproducibly expressed.

Animals↗

PubMed2003

Rules for gene usage inferred from a comparison of large-scale gene expression profiles of T and B lymphocyte development.

Ribonucleic acid expression profiles of seven consecutive stages of mouse thymocyte development were generated on high density oligonucleotide arrays. Previously known expression patterns of several genes were confirmed. Ten percent (1,304 of more than 13,000) of the monitored genes were found with 99% confidence to be differentially expressed across all T cell developmental stages. When compared with 1,204 genes differentially expressed in five consecutive B lineage developmental stages of bone marrow, >40% (546 genes) appeared to be shared by both lineages. However, when four pools of functionally distinct cell stages were compared between B and T cell development, DJ-rearranged precursor cells and resting immature precursor cells before and after surface Ag receptor expression shared less than 10%, mature resting lymphocytes between 15 and 20%, and only cycling precursors responding to precursor lymphocyte receptor deposition shared >50% of these differentially expressed genes. Three general rules emerge from these results: 1) proliferation of cells at comparable stages is in majority executed by the same genes; 2) intracellular signaling and intercellular communication are effected largely by different genes; and 3) most genes are not used strictly at comparable, but rather at several, stages, possibly in different functional contexts.

Animals↗

PubMed2003

RNA expression profiles and data mining of sugarcane response to low temperature.

Tropical and subtropical plants are generally sensitive to cold and can show appreciable variation in their response to cold stress when exposed to low positive temperatures. Using nylon filter arrays, we analyzed the expression profile of 1,536 expressed sequence tags (ESTs) of sugarcane (Saccharum sp. cv SP80-3280) exposed to cold for 3 to 48 h. Thirty-four cold-inducible ESTs were identified, of which 20 were novel cold-responsive genes that had not previously been reported as being cold inducible, including cellulose synthase, ABI3-interacting protein 2, a negative transcription regulator, phosphate transporter, and others, as well as several unknown genes. In addition, 25 ESTs were identified as being down-regulated during cold exposure. Using a database of cold-regulated proteins reported for other plants, we searched for homologs in the sugarcane EST project database (SUCEST), which contains 263,000 ESTs. Thirty-three homologous putative cold-regulated proteins were identified in the SUCEST database. On the basis of the expression profiles of the cold-inducible genes and the data-mining results, we propose a molecular model for the sugarcane response to low temperature.

Cold Temperature↗

PubMed1997

The significance of digital gene expression profiles.

Genes differentially expressed in different tissues, during development, or during specific pathologies are of foremost interest to both basic and pharmaceutical research. "Transcript profiles" or "digital Northerns" are generated routinely by partially sequencing thousands of randomly selected clones from relevant cDNA libraries. Differentially expressed genes can then be detected from variations in the counts of their cognate sequence tags. Here we present the first systematic study on the influence of random fluctuations and sampling size on the reliability of this kind of data. We establish a rigorous significance test and demonstrate its use on publicly available transcript profiles. The theory links the threshold of selection of putatively regulated genes (e.g., the number of pharmaceutical leads) to the fraction of false positive clones one is willing to risk. Our results delineate more precisely and extend the limits within which digital Northern data can be used.

Actins↗

PubMed2002

Gene expression profile analysis of rheumatoid synovial fibroblast cultures revealing the overexpression of genes responsible for tumor-like growth of rheumatoid synovium.

To elucidate the aberrant growth properties of rheumatoid synoviocytes, we have examined the gene expression profile of rheumatoid synovial fibroblasts (RSFs) and compared with that of normal synovial fibroblasts (NSF). Gene expression profile analysis was conducted with synoviocyte cultures obtained from five rheumatoid arthritis (RA) patients and five control cases using a commercial cDNA array containing the defined 588 cancer-related genes. The results were confirmed by real-time RT-PCR. Gene expression levels for the platelet-derived growth factor receptor alpha (PDGFRalpha), plasminogen activator inhibitor-1 (PAI-1), and stromal cell derived factor 1A (SDF1A) are constitutively augmented in RSF compared with NSF. The mRNA levels of PDGFRalpha, PAI-1, and SDF1A in RSF over NSF were 4.6-, 14-, and 2.8-fold, respectively, by real-time RT-PCR. In fact, we found that RSFs showed greater sensitivity to the cell proliferative effect of PDGF. T his aberrant gene expression profile suggests that RSF may have retained the premature phenotype of primordial synoviocytes.

Adult↗

PubMed2002

[Gene expression profile of human hepatocellular carcinoma cell lines with different metastatic potentials].

OBJECTIVE: To compare gene expression profile of human hepatocellular carcinoma (HCC) cell lines with different metastatic potentials, so as to screen for metastasis-related genes. METHODS: Gene expression profile of MHCC97-L and HCCLM3, two HCC cell lines with similar genetic background but different in spontaneous metastatic potentials, were studied by cDNA microarray. RESULTS: From 1,626 screened genes, 25 differentially expressed genes were found, 18 showed decreased expression including the decreased expression of cell cycle control genes Rb2, mismatch repair gene hMSH2, and signal transduction gene protein kinase C beta 2 and 7 increased expression including signal transduction gene MAP kinase kinase 6, cell proliferation gene E25, immunity related gene SP40, 40, etc in HCCLM3. CONCLUSION: The genes, being closely associated with cancer metastasis, could be considered as potential markers to predict metastasis and targets for anti-metastasis intervention.

Blotting, Northern↗

PubMed2003

Genetic expression profiling of six odontogenic tumors.

Odontogenic tumors are rare neoplasms arising from the odontogenic apparatus. We aimed to identify molecular characteristics associated with odontogenic tumorigenesis and malignancy. To this end, we investigated the expression level of human genes by using, for the first time in odontogenic tumors, the technique of expression profiling. Gene expression alterations common to all six odontogenic tumors were identified by the use of cDNA microarrays containing 19,000 human cDNAs. Statistical analysis on a subset of 4974 cDNAs present in the biopsies identified 506 distinct genes associated with the tumors (p-value < 0.01). Gene ontology analysis of the cellular processes which were differentially regulated in odontogenic tumors was accomplished by the use of a subset of 1409 annotated genes. Finally, 43 cDNAs differentiated the three malignant odontogenic tumors (ameloblastic carcinoma, clear cell odontogenic tumor, granular cell odontogenic tumor) from the three benign ameloblastoma biopsies (p < 0.01). The identified genes might help us better classify borderline odontogenic tumors.

Ameloblastoma↗

PubMed2001

Expression profile of protein tyrosine kinase genes in human osteoarthritis chondrocytes.

OBJECTIVE: To determine the expression profile of protein kinase (PK) and protein tyrosine kinase (PTK) genes in human primary osteoarthritis (OA) chondrocytes and to compare it with that of immortalized human chondrocytes T/C 28a4 with a view to learning whether T/C 28a4 cells can be used for elucidating signal transduction pathways in human chondrocytes. DESIGN: We used the Atlas Human cDNA Array and a method based on PCR with degenerate primers to analyse the expression profile of protein kinase genes in primary human OA chondrocytes and compared it with that of immortalized human chondrocyte cell line T/C 28a4 using RT-PCR and Western blotting. RESULTS: A total of 21 PTK genes were identified and several of these have never been shown to be expressed in human OA chondrocytes. Comparative expression analysis of some selected kinase genes showed that the mRNA expression pattern of many protein kinase genes in OA chondrocytes was identical to that of T/C 28a4 cells. However, there were differences in the level of protein expression of selected protein kinases in these cells. For example, mRNA expression of the novel kinase HCK was detected in OA chondrocytes and in the cell lines analysed but by Western blotting HCK protein was not detected in OA chondrocytes. In these studies, we also identified a novel mutant form of the discoidin domain receptor 2 (DDR2) transcript from chondrocyte-like cell line HTB-94. CONCLUSIONS: Our results provide novel information about protein kinase gene expression in OA chondrocytes and indicate that the transformed chondrocyte cell line T/C 28a4 may be suitable for elucidating signal transduction pathways in chondrocytes and to investigate how they regulate chondrocyte function in inflammatory and degenerative joint diseases.

Blotting, Western↗

PubMed1999

Expression profiling using cDNA microarrays.

cDNA microarrays are capable of profiling gene expression patterns of tens of thousands of genes in a single experiment. DNA targets, in the form of 3' expressed sequence tags (ESTs), are arrayed onto glass slides (or membranes) and probed with fluorescent- or radioactively-labelled cDNAs. Here, we review technical aspects of cDNA microarrays, including the general principles, fabrication of the arrays, target labelling, image analysis and data extraction, management and mining.

Animals↗

PubMed2001

The effect of TGF-beta1 on differential gene expression profiles in human corneal epithelium studied by cDNA expression array.

PURPOSE: TGF-betas regulate cell proliferation and differentiation, and they play important roles in maintenance of corneal epithelium. However, the precise function of TGF-betas in the corneal epithelium remains unclear. In this study, cDNA expression array technology was used to demonstrate the effect of TGF-beta1 on the simultaneous expression of a large number of genes in cultured human corneal epithelial cells (HCECs). The change in protein level expression of the specific genes influenced by TGF-beta1 was also investigated. METHODS: Human cDNA expression array technology was used to study the simultaneous expression of 1176 specific cellular genes in HCECs incubated with TGF-beta1 (10 ng/ml). Moreover, gene-specific semiquantitative reverse transcription-polymerase chain reaction (RT-PCR) was used to confirm the gene expression pattern measured by the cDNA expression array. Western blot analysis was used to examine protein expression of the specific genes in the presence or absence of TGF-beta1. RESULTS: TGF-beta1 significantly upregulated the expression of 19 genes and significantly downregulated ras-related protein, caspase10, and beta4-integrin in the treated HCECs. The expression of 277 genes including alpha3-integrin, PAI-2, transferrin receptor, and cyclin-D1 was studied. Semiquantitative RT-PCR analysis confirmed the TGF-beta1-mediated changes in expression patterns of these genes. Furthermore, Western blot analysis revealed that TGF-beta1 remarkably decreased PAI-2, transferrin receptor, and integrin alpha3, and increased caspase10 on the protein level. CONCLUSIONS: TGF-beta1 regulates the expression of specific types of genes in HCECs. These results strongly suggest that TGF-beta1 is critically involved in the maintenance of the corneal epithelium through the control of a network of various signal-transduction pathways.

Blotting, Western↗

PubMed2003

[Gene expression profiles in the diagnosis and prognosis of cancer].

DNA-microarray technology can be used to assess the expression of several thousands of genes at the same time. The identification of the gene expression profiles may help to better characterize human cancer. These studies may reveal subclasses of tumor types with similar histopathologic profile but different clinical courses.Furthermore,such studies could help to define therapeutic sensitivity and to estimate prognosis of various cancers. Identification of gene expression profiles of cancer can identify new therapeutic targets or cancer susceptibility genes. The DNA-microarray technology may write a new chapter in molecular oncology.

Antineoplastic Agents↗

PubMedDate not supplied

DEPD, a high resolution gene expression profiling technique capable of identifying new drug targets in the central nervous system.

Digital expression pattern display (DEPD) is an open, automated, PCR-based system of gene expression profiling that is capable of resolving as many as 100,000 transcripts from a single brain tissue cDNA sample. It has a detection sensitivity of better than 1 in 750,000 and it can reliably detect differences in RNA expression levels of less than two-fold. Digital expression pattern display presently is the most sensitive and therefore the only expression profiling method available that is capable of monitoring, in a semi-quantitative fashion, the expression of even the rarest of transcripts found in human brain tissue. Biofrontera applies this proprietary technique, together with state-of-the-art bioinformatics, for the purposes of elucidating pathology pathways of major brain diseases, of analysing the target profiles of drugs presently applied or in development, and of identifying novel targets for drug action.

Animals↗

PubMed2002

Expression profiling of the developing mouse lung: insights into the establishment of the extracellular matrix.

We have undertaken a comprehensive gene expression profiling of the entire process of murine lung development using oligonucleotide-based microarrays. Our data reveals the expression pattern of approximately 11,000 genes throughout the morphologic stages of lung development. This includes known genes with unappreciated pulmonary expression and novel genes with undefined functions. Traditional gene expression analysis techniques verify a high degree of confidence in the microarray data. Examination of the data confirms previously known patterns of expression for extracellular matrix genes and provides new information regarding relationships in temporal expression among groups of these genes. Large-scale cluster analysis reveals associations in the expression profile of specific genes with defined developmental processes. For instance, we identify groups of genes, which are coordinately expressed with extracellular matrix genes during lung development. These data should serve as a resource for the pulmonary research community and assist in deciphering the molecular mechanisms governing normal lung development as well as those involved in aberrant developmental pathology.

Animals↗