Profiling Expression Patterns and Isolating Differentially Expressed Genes by cDNA Microarray System with Colorimetry Detection

Chen, Jeremy J.W.; Wu, Reen; Yang, Pan‐Chyr; Huang, Jui Chien; Sher, Yuh Pyng; Han, Meng; Kao, Wei Chen; Lee, Pei Jung; Chiu, Trai Fu; Chang, Fu; Chu, Yi; Wu, Cheng Wen; Peck, Konan

doi:10.1006/geno.1998.5354

Cited by 214 publications

(138 citation statements)

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“…It is important at this point to keep in mind that published expression pro®ling work with microarrays or oligonucleotide chips uses microgram amounts of poly(A) + RNA for probe preparation (Schena et al, 1996;Lockhart et al, 1996), or resorts to probe ampli®cation methods that may skew relative abundance values. Further miniaturization using Nylon microarrays (Chen et al, 1998) and radioactive probes (with a very high-resolution detection system) can bring down sample requirements by a large factor (Bertucci et al, in preparation), but in the implementation described here, the method is already able to provide signi®cant information in clinically relevant situations.…”

Section: Resultsmentioning

confidence: 99%

“…The most productive implementation uses hybridization of complex probes prepared from cell or tissue RNA to`macroarrays' of cDNA inserts on Nylon membranes (Bernard et al, 1996;Tsou et al, 1998), miniaturized`microarrays' constructed on glass slides (Schena et al, 1995;DeRisi et al, 1996;Shalon et al, 1996) or on Nylon membranes (Chen et al, 1998), or`DNA chips' carrying oligonucleotides (Lockhart et al, 1996;Wodicka et al, 1997). In all cases, hybridization intensity can be used to derive expression data for each gene represented on the array.…”

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confidence: 99%

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Expression scanning of an array of growth control genes in human tumor cell lines

et al. 1999

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Analysis of gene expression on a medium-or large-scale is an increasingly recognized method for functional and clinical investigations based on the now extensive catalog of known or partially sequenced genes. The accessibility of this approach can be enhanced by using readily available technology (macroarrays on Nylon, radioactive detection) and the IMAGE resource to assemble sets of targets. We have set up such a medium-scale,¯exible system and validated it by the study of quantitative expression levels for 120 genes in six cell lines, including three mammary carcinoma cell lines. A number of important parameters are identi®ed as necessary for the assembly of a valid set and the obtention of goodquality quantitative data. The extensive data assembled in this survey identi®ed potential targets of carcinogenesis, for example the CRABP2 and GATA3 transcription factor genes. We also demonstrate the feasibility of this procedure for relatively small tumor samples, without recourse to probe ampli®cation methods.Keywords: cancer; breast cancer; gene expression; cDNA; gene array Recent studies have addressed the problem of alterations in human cancers in a global way, enumerating all genomic alterations, such as ampli®cations (Courjal et al

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Section: Resultsmentioning

confidence: 99%

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confidence: 99%

Expression scanning of an array of growth control genes in human tumor cell lines

et al. 1999

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“…2-4,6 -8,22 In addition, transcriptional silencing by methylation of CpG islands in the 5Ј promoter region of the caveolin-1 gene was once found in two human breast cancer cell lines that failed to express the caveolin-1 protein. 23 Our previous microarray data from the comparison of genes differentially expressed in cell lines with varying invasive capability suggested a possible reciprocal transcriptional regulation between caveolin-1 and HEK2, TNF-R, or protein kinase C during lung cell transformation, 20 although further experimentation is needed to confirm this guess.…”

Section: Discussionmentioning

confidence: 99%

“…20 Briefly, mRNA was extracted from each CL cell line and reverse-transcribed into cDNA labeled with biotin. The biotin-labeled cDNA was used as probes and hybridized with the membranes that contained 9600 nonredundant expressed sequence tag clones selected from human cDNA libraries.…”

Section: Microarray Analysismentioning

confidence: 99%

Up-Regulated Caveolin-1 Accentuates the Metastasis Capability of Lung Adenocarcinoma by Inducing Filopodia Formation

Huang

et al. 2002

The American Journal of Pathology

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Caveolin-1, a 21-to 24-kd protein, is the principal component of caveolae, which are special invaginated microdomains of the plasma membrane present in most mammalian cells. 1 It is well established that caveolin-1 is a tumor suppressor gene. Caveolin-1 mRNA and protein expression are frequently lost in human cancer cell lines. Re-expression of caveolin-1 in oncogenically transformed cell lines inhibits tumor cell growth and reduces tumorigenicity. [2][3][4][5][6] Several mechanisms have been proposed for caveolin-1 to function as a tumor suppressor. Caveolin-1 may exert its tumor-growth inhibition by contact inactivation of signaling molecules such as v-src, Ha-Ras, protein kinase A, PKC, and p42/44 MAP kinase within caveolae. [7][8][9][10] In addition, down-regulation of caveolin-1 in colon carcinoma cells has been shown to prevent the degradation of inducible nitric oxide synthase via the proteosome pathway, which, in turn, increases the local nitric oxide concentration to facilitate tumorigenesis. 11 Caveolin-1 can also function as a tumor metastasispromoting molecule, which is unrelated to its obvious function of cell growth inhibition. 12 Elevated expression of caveolin-1 is found to be associated with progression of prostate, colon, and breast carcinoma. 13,14 Inhibition of c-myc-induced apoptosis by caveolin-1 was recently proposed to promote progression of prostate cancer, 15 and it may serve as a prognostic indicator for these patients. 16 Nonetheless, it still remains unclear whether and how caveolin-1 can potentiate tumor progression in other types of human cancer.In the present study, we investigated the expression pattern of caveolin-1 both in a series of lung carcinoma cell lines (CLs) with varying invasive/metastatic ability 17

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“…Gene activity was measured by a cDNA microarray method with enzyme colorimetry detection (13). The mRNAs of the pulmonary arteries and veins were amplified by using an in vitro transcription method (14) before they were labeled with biotin during the reverse transcription process.…”

Section: Methodsmentioning

confidence: 99%

Matching gene activity with physiological functions

Huang

Sher

Peck

et al. 2002

Proc. Natl. Acad. Sci. U.S.A.

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Matching the activity of the genes with biomechanics and physiology is an effective way to use cDNA microarray technology. Required are data on the change of activities of genes associated with specific physiological functions with respect to a continuous variable such as time. For each pair of data (gene and physiological function) as functions of time, we can compute a coefficient of correlation, R. The correlation is perfect if R is ؉1 or ؊1; it is nonexistent if R ‫؍‬ 0. By evaluating R for every gene in a microarray, we can arrange the genes in the order of the number R, thus learning which genes are best correlated with the mechanical or physiological function. We illustrate this procedure by studying the blood vessels in the lung in response to pulmonary hypoxic hypertension, including the remodeling of vascular morphometry, the elastic moduli, and the zero-stress state of the vessel wall. For each physiological function, we identify the top genes that correlate the best. We found that different genes correlate best with a given function in large and small arteries, and that the genes in pulmonary veins which respond to arterial functions are different from those in pulmonary arteries. We found one set of genes matching the remodeling of arterial wall thickness, but another set of genes whose integral of activity over time best fit the wall thickness change. Our method can be used to study other thought-provoking problems.cDNA microarray ͉ blood vessel morphometric parameters ͉ blood vessel elasticity ͉ blood vessel opening angle at zero-stress state ͉ pulmonary hypertension

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Profiling Expression Patterns and Isolating Differentially Expressed Genes by cDNA Microarray System with Colorimetry Detection

Cited by 214 publications

References 25 publications

Expression scanning of an array of growth control genes in human tumor cell lines

Expression scanning of an array of growth control genes in human tumor cell lines

Up-Regulated Caveolin-1 Accentuates the Metastasis Capability of Lung Adenocarcinoma by Inducing Filopodia Formation

Matching gene activity with physiological functions

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