scholarly journals Gene expression patterns in the histopathological classification of epithelial ovarian cancer

2010 ◽  
Vol 1 (1) ◽  
pp. 187-192 ◽  
Author(s):  
HONGLAN ZHU ◽  
JING JIE YU
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Histopathological Classification

Classification of the images of gene expression patterns using neural networks based on multivalued neurons with the minimal number of inputs

2002 ◽  
Author(s):  
Igor N. Aizenberg ◽  
Constantine Butakoff ◽  
Ekaterina Myasnikova ◽  
Maria Samsonova ◽  
John Reinitz
Keyword(s):  
Gene Expression ◽  
Neural Networks ◽  
Expression Patterns ◽  
Gene Expression Patterns

scholarly journals Automatic Classification of Embryonic Fruit Fly Gene Expression Patterns

2009 ◽  
pp. 415-419 ◽  
Author(s):  
Andreas Heffel ◽  
Sonja J. Prohaska ◽  
Peter F. Stadler ◽  
Gerhard Kauer ◽  
Jens-Peer Kuska
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Fruit Fly ◽  
Automatic Classification ◽  
Gene Expression Patterns

scholarly journals Distinct cholesterogenic and lipidogenic gene expression patterns in ovarian cancer - a new pool of biomarkers

2015 ◽  
Vol 6 (11-12) ◽  
pp. 472-479 ◽  
Author(s):  
Georgios Pampalakis ◽  
Angeliki-Louiza Politi ◽  
Anastasios Papanastasiou ◽  
Georgia Sotiropoulou
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Expression Patterns ◽  
Gene Expression Patterns

IGF axis gene expression patterns are prognostic of survival in epithelial ovarian cancer

2007 ◽  
Vol 14 (3) ◽  
pp. 781-790 ◽  
Author(s):  
Dimitrios Spentzos ◽  
Stephen A Cannistra ◽  
Franck Grall ◽  
Douglas A Levine ◽  
Kamana Pillay ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Signaling Pathway ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Prognostic Models ◽  
Igf I ◽  
Igf Receptor ◽  
Igf Signaling

The IGF axis has documented growth-promoting effects in various malignancies, but its role in epithelial ovarian cancer (EOC) has not been adequately examined. We studied the expression of the IGF axis genes in relation to outcome in EOC. Microarray expression profiles from 64 patients with advanced-stage EOC were used. Two multi-gene subsets were chosen, one upstream of the IGF receptor (‘IGF family’) and the other downstream of the IGF receptor (‘IGF signaling pathway’), and analyzed in relation to survival. In addition, expression patterns of the two gene subsets were analyzed in relation to favorable and unfavorable prognosis categories identified in a previous study by whole-genome expression profiling. In a gene-by-gene analysis, IGF binding protein 4 and IGF-II receptor gene expression was inversely associated with survival. Using hierarchical clustering, the two multi-gene subsets separated the patient cohort into two groups with different median survival (IGF family: 33 vs 63 months, P=0.02 and IGF signaling pathway: 41 vs 63 months, P=0.05). Furthermore, the two multi-gene subsets were differentially expressed between the previously defined favorable and unfavorable prognosis tumors (Kolmogorov–Smirnov permutation: P=0.0005 and 0.003 for the IGF family and signaling pathway respectively), and individual genes (including IGF-I, IGF-I receptor, and several genes downstream of the receptor) were overexpressed in unfavorable prognosis tumors (permutation P<0.05). The expression patterns of several genes in the IGF axis are associated with survival in EOC, and expression changes of these genes may be underlying previously proposed microarray-derived clinical prognostic models. Future studies are needed to more precisely determine the diagnostic and potential therapeutic significance of these findings.

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