Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer.

By J. Welsh, P. Zarrinkar, L. Sapinoso, S. Kern, C. Behling, B. Monk, D. Lockhart, R. Burger, G. Hampton. Proceedings of the National Academy of Sciences of the United States of America, 2001

681 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/272da24e76e492afd62a64552a4fdc56ac6fb1b3

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Citations in the corpus

The HE4 (WFDC2) protein is a biomarker for ovarian carcinoma. (2003, methodology): “The latter was applied to identify two genes, WFDC2 and MSLN, which are amplified in ovarian carcinomas but not in normal tissues (13, 14).”
Minimum redundancy feature selection from microarray gene expression data (2003, methodology): “Simple methods based on mutual information [4], statistical tests (t-test, F-test) have been shown to be effective [10] [6] [8] [18] [24].”
Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer. (2001, methodology): “Differential expression of genes in benign and malignant prostate tissues was estimated using an algorithm (9) based on equally weighted contributions from the difference of hybridization intensities ( Tumor– Normal), the quotient of hybridization intensities ( Tumor/ Normal), and the result of an u”
Candidate-gene approaches for studying complex genetic traits: practical considerations (2002, background): “For example, by examining expression studies of tumour tissue, investigators have identified genes that might be important in the pathology of certain cancer”
c-Myc can induce DNA damage, increase reactive oxygen species, and mitigate p53 function: a mechanism for oncogene-induced genetic instability. (2002, neutral): “(Welsh et al., 2001).”
Gene expression patterns in human liver cancers. (2002, background): “The phenotypic diversity of cancer is accompanied by a corresponding diversity in gene expression patterns (Perou et al., 1999; Alizadeh et al., 2000; Perou et al., 2000; Ross et al., 2000; Welsh et al., 2001).”
ONCOMINE: a cancer microarray database and integrated data-mining platform. (2004, background): “[23], which had profiled 27 primary ovarian carcinomas.”
Strategies for discovering novel cancer biomarkers through utilization of emerging technologies (2008, background): “When complementary DNA microarrays were used to identify overexpressed genes in ovarian carcinoma, 101 transcripts were shown to be overexpressed in ovarian cancers compared with normal tissues”
Coexpression analysis of human genes across many microarray data sets. (2004, neutral): “2001) 88 1952 19868 (Welsh et al. 2001) 49 5418 52459 (Khatua et al.”
Molecular classification of human carcinomas by use of gene expression signatures. (2001, methodology): “As an example, we chose 28 of the genes that were 92% predictive of serous papillary carcinomas of the ovary and compared the expression levels of these genes in an expanded set of 24 ovarian tumor samples against 5 samples of normal ovary, 2 of which were highly enriched for surface ovarian epithel”
A comparative study of feature selection and multiclass classification methods for tissue classification based on gene expression (2004, background): “However, while binary classification and clustering are heavily studied, (see, e.g. Alizadeh et al., 2000; Ben-Dor et al., 2000; Brown et al., 2000; Der et al., 1998; Eisen et al., 1998; Friedman et al., 2000; Raychaudhuri et al., 2002; Tamayo et al., 1999; Welsh et al., 2001), only a small amount o”