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PubMed2002

Gene expression profile of human bone marrow stromal cells: high-throughput expressed sequence tag sequencing analysis.

Human bone marrow stromal cells (HBMSC) are pluripotent cells with the potential to differentiate into osteoblasts, chondrocytes, myelosupportive stroma, and marrow adipocytes. We used high-throughput DNA sequencing analysis to generate 4258 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' (97) and 3' (4161) ends of human cDNA clones from a HBMSC cDNA library. Our goal was to obtain tag sequences from the maximum number of possible genes and to deposit them in the publicly accessible database for ESTs (dbEST of the National Center for Biotechnology Information). Comparisons of our EST sequencing data with nonredundant human mRNA and protein databases showed that the ESTs represent 1860 gene clusters. The EST sequencing data analysis showed 60 novel genes found only in this cDNA library after BLAST analysis against 3.0 million ESTs in NCBI's dbEST database. The BLAST search also showed the identified ESTs that have close homology to known genes, which suggests that these may be newly recognized members of known gene families. The gene expression profile of this cell type is revealed by analyzing both the frequency with which a message is encountered and the functional categorization of expressed sequences. Comparing an EST sequence with the human genomic sequence database enables assignment of an EST to a specific chromosomal region (a process called digital gene localization) and often enables immediate partial determination of intron/exon boundaries within the genomic structure. It is expected that high-throughput EST sequencing and data mining analysis will greatly promote our understanding of gene expression in these cells and of growth and development of the skeleton.

Bone Marrow Cells↗

PubMed2003

Local Context Finder (LCF) reveals multidimensional relationships among mRNA expression profiles of Arabidopsis responding to pathogen infection.

A major task in computational analysis of mRNA expression profiles is definition of relationships among profiles on the basis of similarities among them. This is generally achieved by pattern recognition in the distribution of data points representing each profile in a high-dimensional space. Some drawbacks of commonly used pattern recognition algorithms stem from their use of a globally linear space and/or limited degrees of freedom. A pattern recognition method called Local Context Finder (LCF) is described here. LCF uses nonlinear dimensionality reduction for pattern recognition. Then it builds a network of profiles based on the nonlinear dimensionality reduction results. LCF was used to analyze mRNA expression profiles of the plant host Arabidopsis interacting with the bacterial pathogen Pseudomonas syringae. In one case, LCF revealed two dimensions essential to explain the effects of the NahG transgene and the ndr1 mutation on resistant and susceptible responses. In another case, plant mutants deficient in responses to pathogen infection were classified on the basis of LCF analysis of their profiles. The classification by LCF was consistent with the results of biological characterization of the mutants. Thus, LCF is a powerful method for extracting information from expression profile data.

Arabidopsis↗

PubMed2002

Gene expression profile of native human retinal pigment epithelium.

PURPOSE: To generate a profile of genes expressed in the native human retinal pigment epithelium and identify candidate genes for retinal and macular diseases. METHODS: Two cDNA libraries (one amplified, the other unamplified) were constructed using RNA isolated from native human RPE sheets. The sequence from the 5' end was obtained for randomly selected clones from the two libraries. Of these, more than 2000 expressed sequence tags (ESTs) were analyzed for similarity to sequences and gene clusters in public databases. RESULTS: EST analysis revealed several known RPE-expressed genes and more than 500 genes that have been characterized previously but were not known to be expressed in the RPE. Transthyretin and 90-kDa heat shock protein represent the most abundant transcripts identified in these RPE libraries. More than 200 novel ESTs and putative proteins were identified. An additional 344 sequences matched only the human genomic sequence. CONCLUSIONS: High-complexity cDNA libraries were generated from native human RPE. Analysis of ESTs generated from these libraries has yielded a profile of genes expressed in the native RPE. Several of the identified genes are known to play a significant role in the RPE. Novel ESTs, putative proteins, and genomic hits may represent as yet unidentified RPE-expressed genes and many of these, mapping in the region of retinal disease loci, may serve as candidate genes. In addition, the nonredundant set of more than 1100 genes and ESTs described herein will be a valuable resource for generating gene microarrays, which can assist in delineating RPE expression profiles during human disease pathogenesis.

Child↗

PubMed2003

Total RNA yield and microarray gene expression profiles from fine-needle aspiration biopsy and core-needle biopsy samples of breast carcinoma.

BACKGROUND: Gene expression profiling should be applicable to needle biopsy samples if microarray technology is to become practically useful for clinical research or management of breast carcinoma. This study compared gene expression profiles derived from fine-needle aspiration biopsy (FNAB) and from core needle biopsy (CBX). METHODS: Total RNA was extracted from single FNAB and CBX samples. Corresponding pairs of FNAB and CBX were analyzed for similarity of gene expression profiles using cDNA microarrays that contain 30721 human sequences. A subset of genes that distinguished CBX samples from FNAB samples was evaluated in a larger group of needle biopsy samples and in a published genomic database derived from 78 sporadic breast carcinomas with known clinical outcome. RESULTS: Sixty-eight patients with newly diagnosed breast carcinoma were included in the current study. Sixty-five patients underwent FNAB (17 had both FNAB and CBX) and 3 underwent CBX only. Extracted RNA was of suitable quality for hybridization in 46 (71%) FNABs and 15 (75%) CBXs. Total RNA yield in those samples was similar for single-pass FNAB (mean = 3.6 microg and median = 2.2 microg; n = 46) and CBX (mean = 2.8 microg and median = 2.0 microg; n = 15), with 1 microg or more of total RNA in all cases. Transcriptional profiling was performed successfully in all cases when it was attempted, in a total of 50 samples (38 FNABs and 12 CBXs), including matched FNAB and CBX samples from 10 patients. There were differences in gene expression profiles in 10 matched FNAB and CBX sample pairs. Genes that were expressed differently in CBX samples, compared with FNAB samples, were recognized as being predominantly from the endothelium, fibroblasts, myofibroblasts or smooth muscle, and histiocytes. Corresponding microscopic cell counts from FNABs demonstrated means of 80% tumor cells, 15% lymphocytes, and 5% stromal cells, whereas CBXs contained 50% tumor cells, 20% lymphocytes, and 30% stromal cells. Considering that CBXs are approximately six-fold richer in nonlymphoid stromal cells than FNABs and that CBXs differentially express a set of recognized stromal genes, the authors used these biopsies to define a transcriptional profile of breast carcinoma stroma. A set of 120 genes differentially expressed in CBXs was assessed independently in a published breast carcinoma genomic database to classify breast carcinomas based on stromal gene expression. Subgroups of tumors with low or high stromal signal were identified, but there was no correlation with the development of systemic metastases within 5 years. CONCLUSIONS: Both FNAB and CBX yield a similar quality and quantity of total RNA and are suitable for cDNA microarray analyses in approximately 70-75% of single-pass samples. Transcriptional profiles from FNAB and CBX of the same tumor generally are similar and are driven by the tumor cell population. The authors concluded that each technique has relative advantages. The FNABs provide transcriptional profiles that are a purer representation of the tumor cell population, whereas transcriptional profiles from CBXs include more representation from nonlymphoid stromal elements. Selection of the preferred needle biopsy sampling technique for genomic studies of breast carcinomas should depend on whether variable stromal gene expression is desirable in the samples.

Adult↗

PubMed2006

Gene expression profiling of primary cutaneous melanoma and clinical outcome.

BACKGROUND: Gene expression profiling data for human primary cutaneous melanomas are scarce because of the lack of retrospective collections of frozen tumors. To identify differentially expressed genes that may be involved in melanoma progression and prognosis, we investigated the relationship between gene expression profiles and clinical outcome in a cohort of patients with primary melanoma. METHODS: Labeled complementary RNA (cRNA) from each tissue sample was hybridized to a pangenomic 44K 60-mer oligonucleotide microarray. Class comparison and class prediction analyses were performed to identify genes whose expression in primary melanomas was associated with 4-year distant metastasis-free survival among 58 patients with at least 4 years of follow-up, distant metastasis, or death. Results were validated immunohistochemically at the protein level in 176 independent primary melanomas from patients with a median clinical follow-up of 8.5 years. Survival was analyzed with a Cox multivariable model and stratified log-rank test. All statistical tests were two-sided. RESULTS: We identified 254 genes that were associated with distant metastasis-free survival of patients with primary melanoma. These 254 genes include genes involved in activating DNA replication origins, such as minichromosome maintenance genes and geminin. Twenty-three of these genes were studied at the protein level; expression of five (MCM4, P = .002; MCM3, P = .030; MCM6, P = .004; KPNA2, P = .021; and geminin, P = .004) was statistically significantly associated with overall survival in the validation set. In a multivariable Cox model adjusted for tumor thickness, ulceration, age, and sex, expression of MCM4 (hazard ratio [HR] of death = 4.04, 95% confidence interval [CI] = 1.39 to 11.76; P = .010) and MCM6 (HR of death = 7.42, 95% CI = 1.99 to 27.64; P = .003) proteins was still statistically significantly associated with overall survival. CONCLUSION: We identified 254 genes whose expression was associated with metastatic dissemination of cutaneous melanomas. These genes may shed light on the molecular mechanisms underlying poor prognosis in melanoma patients.

Adolescent↗

PubMed2006

From microarray to biological networks: Analysis of gene expression profiles.

Powerful new methods, such as expression profiles using cDNA arrays, have been used to monitor changes in gene expression levels as a result of a variety of metabolic, xenobiotic, or pathogenic challenges. This potentially vast quantity of data enables, in principle, the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. Here we present a general approach to developing dynamic models for analyzing time series of whole-genome expression. The parameters in the model show the influence of one gene expression level on another and are calculated using singular value decomposition as a means of inverting noisy and near-singular matrices. Correlative networks can then be generated based on these parameters with a simple threshold approach. We also demonstrate how dynamic models can be used in conjunction with cluster analysis to analyze microarray time series. Using the parameters from the dynamic model as a metric, two-way hierarchical clustering could be performed to visualize how influencing genes affect the expression levels of responding genes. Application of these approaches is demonstrated using gene expression data in yeast cell cycle.

Computational Biology↗

PubMed2005

Gene expression profiling of progressive papillary noninvasive carcinomas of the urinary bladder.

PURPOSE: The aim of the present study was to define gene expression profiles of noninvasive and invasive bladder cancer, to identify potential therapeutic or screening targets in bladder cancer, and to define genetic changes relevant for tumor progression of recurrent papillary bladder cancer (pTa). EXPERIMENTAL DESIGN: Overall, 67 bladder neoplasms (46 pTa, 3 pTis, 10 pT1, and 8 pT2) and eight normal bladder specimens were investigated by a combination of laser microdissection and gene expression profiling. Eight of 16 patients with recurrent noninvasive papillary bladder tumors developed carcinoma in situ (pTis) or invasive bladder cancer (> or = pT1G2) in the course of time. RNA expression results of the putative progression marker cathepsin E (CTSE) were confirmed by immunohistochemistry using high-throughput tissue microarray analysis (n = 776). Univariate analysis of factors regarding overall survival, progression-free survival, and recurrence-free survival in patients with urothelial bladder cancer was done. RESULTS: Hierarchical cluster analyses revealed no differences between pTaG1 and pTaG2 tumors. However, distinct groups of invasive cancers with different gene expression profiles in papillary and solid tumors were found. Progression-associated gene profiles could be defined (e.g., FABP4 and CTSE) and were already present in the preceding noninvasive papillary tumors. CTSE expression (P = 0.003) and a high Ki-67 labeling index of at least 5% (P = 0.01) were the only factors that correlated significantly with progression-free survival of pTa tumors in our gene expression approach. CONCLUSIONS: Gene expression profiling revealed novel genes with potential clinical utility to select patients that are more likely to develop aggressive disease.

Aged↗

PubMed2006

A multiplex branched DNA assay for parallel quantitative gene expression profiling.

We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.

Alternative Splicing↗

PubMed2003

Partitioning large-sample microarray-based gene expression profiles using principal components analysis.

Principal components analysis (PCA) is useful for reproducing the total variation among hundreds or thousands of continuously-scaled variables with a much smaller number of unobservable variables called 'latent factors'. The CLUSFAVOR computer program was used to implement PCA for identifying groups of genes with similar expression profiles from a large number of genes used on DNA microarrays. This paper describes the principal components solution to the factor model of the correlation matrix R, calculation of eigenvalues and eigenvectors of R, extraction of factors, and calculation of factor loadings and identification of genes with similar loading patterns to construct groups of genes with similar expression profiles. With regard to extraction of factors, it was found that more than 90% of the total variance in input data could be accounted for by extracting factors whose eigenvalues exceed unity. Bipolar factors containing strong positive and negative loadings can also be used for identifying two unique groups of genes, since expression profiles of genes that load positive are unlike expression profiles of genes that load negative on the same factor. While PCA does not provide the absolute answer to a multidimensional problem, it nevertheless can provide a heuristic with which natural groupings of genes with similar expression profiles can be assembled. While cluster analysis essentially generates a single dendogram (tree branch) containing every gene in the input data, PCA can be used to assemble gene expression profiles that strongly correlate with the latent factors accounting for a majority of total variance. Example results for CLUSFAVOR computer program runs are provided.

Gene Expression Profiling↗

PubMed2006

Partially degraded RNA from bladder washing is a suitable sample for studying gene expression profiles in bladder cancer.

OBJECTIVES: To determine the impact of different levels of RNA degradation on gene expression measurements and to ascertain if the gene expression profile obtained from bladder washing (BW) correlates to that obtained from the related bladder tumour (BT). METHODS: BT and BW RNAs from the same patient were heat shocked to obtain three RNA degradation states, which were compared with intact RNAs from healthy bladders by using complementary DNA (cDNA) microarrays. All samples were amplified by means of a T3N9-based transcription method. In addition, four of the differentially expressed genes in microarrays related to bladder cancer (KRT20, IGF2, GSN, and CCL2) were analyzed in 36 tumoural and 14 control BW samples by quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR). RESULTS: A high percentage of overlapping differentially expressed genes were detected between BT arrays (85-91%) and between BW arrays (78-93%). Furthermore, the similarity between BW and BT arrays was relatively high and independent of the RNA degradation state (52-60%). Finally, expression differences for the four selected genes were confirmed in the vast majority of extended BW samples tested by qRT-PCR. CONCLUSIONS: Our results showed that partially degraded RNA samples analyzed by cDNA microarrays yielded gene expression profiles comparable to those obtained using intact RNA. Moreover, BW RNA exhibited gene expression patterns similar to those identified in the BT, indicating that BW is an appropriate sample for studying gene expression profiles of BT using cDNA microarrays. In addition, qRT-PCR results further support the suitability of BW for gene expression profiling and its potential use for routine diagnostics.

Chemokine CCL2↗

PubMed2006

Characterization of gene expression profiles of normal canine retina and brain using a retinal cDNA microarray.

PURPOSE: Construction of a canine retinal custom cDNA microarray for comprehensive retinal gene expression profiling and application for the identification of genes that are preferentially expressed in the retina and brain lobes using a brain pool reference tissue. METHODS: A cDNA microarray was constructed utilizing clones obtained from a normalized canine retinal expressed sequence tag library. Gene expression profiles were analyzed for normal retina, as well as the cortex of the frontal, occipital, and temporal brain regions. Each sample was studied against a reference sample of pooled brain RNA. Data from a quantified scanned image were normalized using the loess subgrid procedure. Retina-enriched genes were identified using the Significance Analysis of Microarrays (SAM) algorithm, and confirmed by northern blot analyses for selected genes. Differences between biological samples were displayed using principal component analysis (PCA). RESULTS: Expression profiles for each tissue set were analyzed against the common reference of pooled brain. Changes in expression between the sample and the reference were higher in the retina (27.9%) than the individual brain tissues (2-6.6%). Furthermore, all individual retinal samples were clearly separated from any of the hybridizations using brain tissue in the PCA. The accuracy of observed changes in expression has been confirmed by northern blot analysis using five randomly chosen genes that represented a wide range of different expression levels between retina and brain. CONCLUSIONS: We have established an accurate and robust microarray system suitable for the investigation of expression patterns in the retina and brain. Characterization of the gene expression profiles in normal retina will facilitate the understanding of the processes that underline differences between normal and diseased retinas.

Animals↗

PubMed2003

Gene expression profiling in hypertension research: a critical perspective.

Recent advances in molecular biology and technology have made it possible to monitor the expression levels of virtually all genes simultaneously. As the tools for gene expression profiling have become more widely available, the number of investigators applying this technology in hypertension research, as in other fields of biomedical research, has grown rapidly. At the same time, numerous articles have been published that discuss the technical aspects of gene profiling and its promise for advancing research on the pathogenesis and treatment of multiple clinical disorders. However, much of the research carried out with gene expression profiling has been of a correlational or descriptive nature, and the true value of this technology is unclear. Despite the initial wave of enthusiasm for gene expression profiling, its actual utility for studying multifactorial disorders like hypertension remains to be established. In this review, we offer a critical perspective on the use of gene expression profiling in hypertension research and discuss some emerging strategies for taking this technology beyond the limits of correlational and descriptive studies.

Animals↗

PubMed2005

Gene expression profiles in psoriasis: analysis of impact of body site location and clinical severity.

BACKGROUND: Psoriasis is characterized by symmetry of plaques and modulation of multiple genes within those plaques. OBJECTIVES: We compared gene expression profiles of plaques of psoriasis at different anatomical sites for both symmetrical and asymmetrical disease to ascertain whether the same genes were expressed. METHODS: Gene expression profiles were analysed in biopsies from lesional and uninvolved skin from two groups of patients with either predominantly symmetrical or truncal plaques of psoriasis vulgaris, and from normal skin of healthy volunteers. Genomic analyses were performed using cDNA array and kinetically monitored reverse transcriptase-initiated polymerase chain reaction (kRT-PCR) approaches. A cluster of genes upregulated in involved psoriasis skin as compared with normal skin was identified using each of these two technologies. RESULTS: Clustering of patients based on their gene expression profile did not reveal any correlation with family history of psoriasis, age at onset or association of psoriasis with arthritis. There was no difference in gene expression profile between the type (symmetrical vs. truncal) or location (left vs. right side of body) of psoriatic plaques. Gene expression profiles of involved psoriatic skin analysed by kRT-PCR analysis did correlate with both global (Psoriasis Area and Severity Index) and local (erythema, desquamation and plaque elevation) clinical severity. CONCLUSIONS: These results indicate that it may be feasible to analyse the molecular effects of pharmacological agents on psoriatic skin in 'minizone' protocols, that the obtained data can be correlated with clinical severity and that plaques of psoriasis in the same individual express the same genes.

Adult↗

PubMed2002

Integrating cytogenetics and gene expression profiling in the molecular analysis of multiple myeloma.

Multiple Myeloma (MM), is a currently incurable malignancy of a terminally differentiated antibody secreting plasma cell (PC) that can be controlled with high dose therapy and stem cell support. Conventional cytogenetic analysis has revealed a genomic instability that sets MM apart from the other blood cell cancers. In spite of this "genomic chaos" recurrent structural rearrangements and ploidy changes have aided the identification of important molecular mechanisms of disease etiology and that have also proved to be useful clinical landmarks. Yet, abnormal cytogenetics, present in only 30% of cases, combined with other clinical parameters, only account for 20% of the variability in clinical outcome, which can range from 2 months to > 10 years. Thus, the genomic chaos may mask a unifying chromosome abnormality, e.g. Philadelphia chromosome in CML, or may indicate that MM is a broad descriptor of constellation of many distinct clinical and molecular entities. The advent of microarray profiling of global gene expression patterns is providing evidence that both of these possibilities may be true. We will discuss how the integration of conventional and molecular cytogenetics with gene expression profiling has confirmed past observations and, yet fundamentally changed the way we view the disease.

Chromosome Aberrations↗

PubMed2002

Prediction and uncertainty in the analysis of gene expression profiles.

We have developed a complete statistical model for the analysis of tumor specific gene expression profiles. The approach provides investigators with a global overview on large scale gene expression data, indicating aspects of the data that relate to tumor phenotype, but also summarizing the uncertainties inherent in classification of tumor types. We demonstrate the use of this method in the context of a gene expression profiling study of 27 human breast cancers. The study is aimed at defining molecular characteristics of tumors that reflect estrogen receptor tatus. In addition to good predictive performance with respect to pure classification of the expression profiles, the model also uncovers conflicts in the data with respect to the classification of some of the tumors, highlighting them as critical cases for which additional investigations are appropriate.

Bayes Theorem↗

PubMed2003

Targeted disruption of the meprin beta gene in mice leads to underrepresentation of knockout mice and changes in renal gene expression profiles.

Meprins are multidomain zinc metalloproteases that are highly expressed in mammalian kidney and intestinal brush border membranes and in leukocytes and certain cancer cells. Mature meprins are oligomers of evolutionarily related, separately encoded alpha and/or beta subunits. Homooligomers of meprin alpha are secreted; oligomers containing meprin beta are plasma membrane associated. Meprin substrates include bioactive peptides and extracellular matrix proteins. Meprins have been implicated in cancer and intestinal inflammation. Additionally, meprin beta is a candidate gene for diabetic nephropathy. To elucidate in vivo functions of these metalloproteases, meprin beta null mice were generated by targeted disruption of the meprin beta gene on mouse chromosome 18q12. Analyses of meprin beta knockout mice indicated that (i) 50% fewer null mice are born than the Mendelian distribution predicts, (ii) null mice that survive develop normally and are viable and fertile, (iii) meprin beta knockout mice lack membrane-associated meprin alpha in kidney and intestine, and (iv) null mice have changes in renal gene expression profiles compared to wild-type mice as assessed by microarray analyses. Thus, disruption of the meprin beta allele in mice affects embryonic viability, birth weight, renal gene expression profiles, and the distribution of meprin alpha in kidney and intestine.

Animals↗

PubMed2004

[Gene expression profile of human adenocarcinoma by cDNA microarray and clustering].

OBJECTIVE: To investigate the gene expression profile of human gastric adenocarcinoma by means of cDNA microarray and to analyze its biological significance. METHODS: Paired tumor and non-tumor specimens from 18 cases of advanced gastric adenocarcinoma were studied. Total RNA was isolated and labeled by reverse transcription reaction with cy5 and cy3 for cDNA probe. cDNA microarrays containing 148 genes were hybridized with labeled cDNA probe. Data from cDNA microarray experiments were analyzed by average-linkage hierarchical clustering and significance analysis of microarrays (SAM). RESULTS: Eighteen tumor and non-tumor specimens were clearly divided by clustering analysis. Three features of gene expression profile were found in gastric adenocarcinoma and non-tumor tissues. The profile of differential gene expression in tumor and non-tumor tissues was mainly shown in feature B and feature C. In gastric adenocarcinoma tissues, the expression of genes in feature B was lower and that in feature C was higher. The profile of differential gene expression among gastric adenocarcinoma tissues was found in feature A. In feature A, the profile of similar gene expression was found in paired tumor and non-tumor tissues from 13 patients. SAM analysis showed that 19 genes in feature B and 12 genes in feature C were of significant difference between tumor and non-tumor specimens. The expression levels of genes related to cell cycle, growth factor, cell adhesion, and matrix remodeling were higher or lower in gastric adenocarcinoma tissues. CONCLUSION: Data from cDNA microarray experiments can clearly distinguish gastric adenocarcinoma from non-tumor tissues. The profiles show that gene expression in gastric adenocarcinomas is both homogeneous and heterogeneous. The homogeneous gene expression profile is found in both tumor and non-tumor tissues from 13 patients, suggesting that some gene aberrance is an early event of carcinogenesis of gastric adenocarcinoma. This study provides not only a new molecular basis for understanding biological properties of gastric adenocarcinoma, but also useful resources for future development of diagnostic and prognostic markers for gastric adenocarcinoma.

Adenocarcinoma↗

PubMed2006

[Effects of microRNA miR-181a on gene expression profiles of K562 cells].

OBJECTIVE: To investigate the effect of microRNA on the gene expression profile of human leukemia K562 cells using microarray technique. METHODS: miR-181a RNA duplexes were designed and synthesized according to the mature sequence of miR-181a. Forty-eight hours after transfection of in vitro cultured K562 cells using Oligofectamine, gene expression profiles of the cells were studied and analyzed using Agilent Human 1A Oligo microarray. RESULTS: Totalling 228 differentially expressed genes were identified from the 20,173 screened genes, including 59 up-regulated ones (consisting of metabolism-associated genes, tumor suppressor genes, signal transduction-associated genes, immunity and defense-associated genes etc), and 169 down-regulated ones (consisting of oncogenes, DNA-binding and transcription genes, metabolism-associated genes, signal transduction-associated genes, cell cycle and development-associated genes etc.) in the transfected K562 cells as compared with the control K562 cells. Changes in expressions of CTCF, ZAP70, SEMA4C and RALA were confirmed by semi-quantitative reverse transcription-polymerase chain reaction. CONCLUSIONS: miR-181a transfection for 48 h induces gene expression profile changes in K562 cells, indicating the functionality of the miR-181a. These differentially expressed genes are related to the functions of the microRNA, and may also be the basis of the regulation model of posttranscriptional gene silencing. These findings provide an evidence for further study of the machineries and functions of the microRNA in mammalian cells.

Gene Expression Profiling↗