Correction: A DNA microarray survey of gene expression in normal human tissues
Ontology highlight
ABSTRACT:
SUBMITTER: Shyamsundar R
PROVIDER: S-EPMC1242207 | biostudies-literature | 2005 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundNumerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes.ResultsHere we describe a systematic survey of gene expression in 115 human tissue samples representing 35 different tissue types, using cDNA microarrays representing approximately 26,000 different human genes. Unsupervised hierarchical cluster analysis of the gene-expression patterns in these tissues identified clusters of genes with related biological functions and grouped the tissue specimens in a pattern that reflected their anatomic locations, cellular compositions or physiologic functions. In unsupervised and supervised analyses, tissue-specific patterns of gene expression were readily discernable. By comparative hybridization to normal genomic DNA, we were also able to estimate transcript abundances for expressed genes.ConclusionsOur dataset provides a baseline for comparison to diseased tissues, and will aid in the identification of tissue-specific functions. In addition, our analysis identifies potential molecular markers for detection of injury to specific organs and tissues, and provides a foundation for selection of potential targets for selective anticancer therapy.
| S-EPMC1088941 | biostudies-literature
Project description:Array hybridizations profiling diverse human tissues; for each array the human tissue RNA is hybridized against a universal reference RNA. Series_type: Logical set Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: other. This dataset is part of the TransQST collection.
2005-02-21 | E-GEOD-2193 | biostudies-arrayexpress
Project description:BackgroundTumor protein 63 (p63) is a transcription factor of the p53 gene family involved in differentiation of several tissues including squamous epithelium. p63 immunohistochemistry is broadly used for tumor classification but published data on its expression in cancer is conflicting.MethodsTo comprehensively catalogue p63 expression, tissue microarrays (TMAs) containing 12,620 tissue samples from 115 tumor entities and 76 normal tissue types were analyzed.Resultsp63 expression was seen in various normal tissues including squamous epithelium and urothelium. At least occasional weak p63 positivity could be detected in 61 (53%) of 115 different tumor types. The frequencies of p63 positivity was highest in squamous cell carcinomas irrespective of their origin (96-100%), thymic tumors (100%), urothelial carcinomas (81-100%), basal type tumors such as basal cell carcinomas (100%), and various salivary gland neoplasias (81-100%). As a rule, p63 was mostly expressed in cancers derived from p63 positive normal tissues and mostly not detectable in tumors derived from p63 negative cancers. However, exceptions from this rule occurred. A positive p63 immunostaining in cancers derived from p63 negative tissues was unrelated to aggressive phenotype in 422 pancreatic cancers, 160 endometrium cancers and 374 ovarian cancers and might be caused by aberrant squamous differentiation or represent stem cell properties. In 355 gastric cancers, aberrant p63 expression occurred in 4% and was linked to lymph node metastasis (p = 0.0208). Loss of p63 in urothelial carcinomas - derived from p63 positive urothelium - was significantly linked to advanced stage, high grade (p < 0.0001 each) and poor survival (p < 0.0001) and might reflect clinically relevant tumor dedifferentiation.ConclusionThe high prevalence of p63 expression in specific tumor types makes p63 immunohistochemistry a suitable diagnostic tool. Loss of p63 expression might constitute a feature of aggressive cancers.
| S-EPMC7830855 | biostudies-literature
Project description:Human brain aging has received special attention in part because of the elevated risks of neurodegenerative disorders such as Alzheimer's disease in seniors. Recent technological advances enable us to investigate whether similar mechanisms underlie aging and neurodegeneration, by quantifying the similarities and differences in their genome-wide gene expression profiles.We have developed a computational method for assessing an individual's "physiological brain age" by comparing global mRNA expression datasets across a range of normal human brain samples. Application of this method to brains samples from select regions in two diseases--Alzheimer's disease (AD, superior frontal gyrus), frontotemporal lobar degeneration (FTLD, in rostral aspect of frontal cortex ?BA10)--showed that while control cohorts exhibited no significant difference between physiological and chronological ages, FTLD and AD exhibited prematurely aged expression profiles.This study establishes a quantitative scale for measuring premature aging in neurodegenerative disease cohorts, and it identifies specific physiological mechanisms common to aging and some forms of neurodegeneration. In addition, accelerated expression profiles associated with AD and FTLD suggest some common mechanisms underlying the risk of developing these diseases.
| S-EPMC2947518 | biostudies-literature
Project description:Adenomatous colorectal polyps are the precursors of the majority of colorectal cancers. Investigation into the gene expression changes in the progression of colorectal adenoma may offer potential targets for the development of novel diagnostic strategies. Previous gene expression studies have generally been based on a limited number of cases or only focused on a single or a few genes. The present study aimed to identify molecular characteristics of colorectal adenoma through analysis of pathways and gene ontology. The study identified 808 upregulated and 857 downregulated genes. Among the 40 pathways enriched with differentially-expressed genes, the Staphylococcus aureus infection pathway and the intestinal immune network for immunoglobulin A production pathway were identified as the most statistically noteworthy pathways at the early stage for colorectal tumorigenesis (P<0.05). These results provide new understanding of colorectal adenoma pathogenesis, with the hope of offering theoretical support for future therapeutic studies.
| S-EPMC4186588 | biostudies-literature
Project description:Long non-coding RNAs (lncRNAs) are a large class of gene transcripts that do not code proteins; however, their functions are largely unknown and many new lncRNAs are yet to be discovered. Taking advantage of our previously developed, super-fast, novel lncRNA discovery pipeline, UClncR, and rich resources of GTEx RNA-seq data, we performed systematic novel lincRNA discovery for over 8000 samples across 30 tissue types. We conducted novel detection for each major tissue type first and then consolidated the novel discoveries from all tissue types. These novel lincRNs were profiled and analyzed along with known genes to identify tissue-specific genes in 30 major human tissue types. Thirteen sub-brain regions were also analyzed in a similar manner. Our analysis revealed thousands to tens of thousands of novel lincRNAs for each tissue type. These lincRNAs could define each tissue type's identity and demonstrated their reliability and tissue-specific expression. Tissue-specific genes were identified for each major tissue type and sub-brain region. The tissue-specific genes clearly defined each respective tissue's unique function and could be used to expand the interpretation of non-coding SNPs from genome-wide association (GWAS) studies.
| S-EPMC8143134 | biostudies-literature
Project description:The aim of the present study was to compare the gene expression profiles in aortic dissection (AD) and healthy human aortic tissue samples by DNA microarray analysis in order to screen the differential genes. In total, five AD and four healthy aortic specimens were selected; the total RNA was extracted and reverse transcribed into cDNA and in vitro transcribed into aRNA, followed by microarray hybridization for analysis. Thereafter, the transcription levels of six differential genes, myosin light chain kinase (MYLK), polycystin 1, transient receptor potential channel interacting (PKD-1), myosin heavy chain 11 (MYH11), superoxide dismutase 3, extracellular (SOD3), filamin A (FLNA), and transgelin (TAGLN), screened from the expression profiles were quantitatively verified. Compared with the healthy aortic specimens, a total of 1,661 genes in the AD group demonstrated more than 2-fold differential expression, of which 997 genes were upregulated and 664 genes were downregulated. Thereafter, six AD-associated genes that showed downregulation in the microarray assay were selected for quantitatively verifying the gene transcription level using reverse transcription-quantitative polymerase chain reaction (RT-qPCR), which confirmed their downregulation compared with the healthy aortic tissue genes; of the six genes, the expression levels of MYLK, PKD-1, MYH11, SOD3 and TAGLN were significantly downregulated (P<0.05), while the expression of FLNA was not significantly downregulated (P>0.05). Thus, whole genome microarray may be used to screen differentially expressed genes between AD and healthy aortic tissues. When used in combination with RT-qPCR validation, this method may provide novel strategies for investigating AD.
| S-EPMC5038499 | biostudies-literature
Project description:BACKGROUND:Some oncogenes such as ERBB2 and EGFR are over-expressed in only a subset of patients. Cancer outlier profile analysis is one of computational approaches to identify outliers in gene expression data. A database with a large sample size would be a great advantage when searching for genes over-expressed in only a subset of patients. DESCRIPTION:GENT (Gene Expression database of Normal and Tumor tissues) is a web-accessible database that provides gene expression patterns across diverse human cancer and normal tissues. More than 40000 samples, profiled by Affymetrix U133A or U133plus2 platforms in many different laboratories across the world, were collected from public resources and combined into two large data sets, helping the identification of cancer outliers that are over-expressed in only a subset of patients. Gene expression patterns in nearly 1000 human cancer cell lines are also provided. In each tissue, users can retrieve gene expression patterns classified by more detailed clinical information. CONCLUSIONS:The large samples size (>24300 for U133plus2 and >16400 for U133A) of GENT provides an advantage in identifying cancer outliers. A cancer cell line gene expression database is useful for target validation by in vitro experiment. We hope GENT will be a useful resource for cancer researchers in many stages from target discovery to target validation. GENT is available at http://medicalgenome.kribb.re.kr/GENT/ or http://genome.kobic.re.kr/GENT/.
| S-EPMC3118449 | biostudies-literature
Project description:BackgroundMeasuring the quantity of miRNAs in tissues of different physiological and pathological conditions is an important first step to investigate the functions of miRNAs. Matched samples from normal state can provide essential baseline references to analyze the variation of miRNA abundance.ResultsWe provided expression data of 345 miRNAs in 40 normal human tissues, which identified universally expressed miRNAs, and several groups of miRNAs expressed exclusively or preferentially in certain tissue types. Many miRNAs with co-regulated expression patterns are located within the same genomic clusters, and candidate transcriptional factors that control the pattern of their expression may be identified by a comparative genomic strategy. Hierarchical clustering of normal tissues by their miRNA expression profiles basically followed the structure, anatomical locations, and physiological functions of the organs, suggesting that functions of a miRNA could be appreciated by linking to the biologies of the tissues in which it is uniquely expressed. Many predicted target genes of miRNAs that had specific reduced expression in brain and peripheral blood mononuclear cells are required for embryonic development of the nervous and hematopoietic systems based on database search.ConclusionWe presented a global view of tissue distribution of miRNAs in relation to their chromosomal locations and genomic structures. We also described evidence from the cis-regulatory elements and the predicted target genes of miRNAs to support their tissue-specific functional roles to regulate the physiologies of the normal tissues in which they are expressed.
| S-EPMC1904203 | biostudies-literature
Project description:Background: Novel aspartic proteinase of the pepsin family A (Napsin A, TAO1/TAO2) is a functional aspartic proteinase which is involved in the maturation of prosurfactant protein B in type II pneumocytes and the lysosomal protein catabolism in renal cells. Napsin A is highly expressed in adenocarcinomas of the lung and is thus commonly used to affirm this diagnosis. However, studies have shown that other tumors can also express Napsin A. Methods: To comprehensively determine Napsin A expression in normal and tumor tissue, 11,957 samples from 115 different tumor types and subtypes as well as 500 samples of 76 different normal tissue types were evaluable by immunohistochemistry on tissue microarrays. Results: Napsin A expression was present in 16 different tumor types. Adenocarcinoma of the lung (85.6%), clear cell adenocarcinoma of the ovary (71.7%), clear cell adenocarcinoma of the endometrium (42.8%), papillary renal cell carcinoma (40.2%), clear cell (tubulo) papillary renal cell carcinoma (16.7%), endometrial serous carcinoma (9.3%), papillary thyroid carcinoma (9.3%) and clear cell renal cell carcinoma (8.2%) were among the tumors with the highest prevalence of Napsin A positivity. In papillary and clear cell renal cell carcinoma, reduced Napsin A expression was linked to adverse clinic-pathological features (p ≤ 0.03). Conclusion: This methodical approach enabled us to identify a ranking order of tumors according to their relative prevalence of Napsin A expression. The data also show that loss of Napsin A is linked to tumor dedifferentiation in renal cell carcinomas.
| S-EPMC8262149 | biostudies-literature