Literature DB >> 19410283

Analysis of gene expression in stage I serous tumors identifies critical pathways altered in ovarian cancer.

Jeremy Chien1, Jian-Bing Fan, Debra A Bell, Craig April, Brandy Klotzle, Takayo Ota, Wilma L Lingle, Jesus Gonzalez Bosquet, Viji Shridhar, Lynn C Hartmann.   

Abstract

OBJECTIVE: Despite recent advances in the conceptual understanding of the pathogenesis of ovarian cancer, it remains the foremost cause of death from gynecologic malignancies in developed countries. The main reason for such a high rate of mortality is the lack of sensitive and specific biomarkers and imaging techniques for early detection of ovarian cancer. Additional biological insights into early-stage ovarian carcinogenesis are needed to help speed the development of markers for early detection of ovarian cancer. The objective of this study was to characterize differentially expressed genes in high-grade stage I serous carcinoma of the ovary.
METHODS: We analyzed gene expression in macrodissected formalin-fixed, paraffin-embedded samples from 5 high-grade stage I serous carcinomas and 5 stage I borderline tumors of the ovary using the Illumina Whole Genome DASL assay (cDNA-mediated annealing, selection, extension, and ligation) corresponding to 24,000 genes. Significance Analysis of Microarrays was performed to determine differentially expressed genes in stage I serous carcinoma, and class prediction analysis was performed to determine the predictive value of differentially expressed gene sets to correctly classify serous carcinoma from borderline tumors in 3 independent data sets. Altered transcription factor pathways and biological pathways unique to stage I serous carcinoma were identified through class comparison of differentially expressed genes.
RESULTS: Unsupervised cluster analysis of gene expression correctly classified stage I serous carcinomas from serous borderline tumors. Supervised analysis identified several known, as well as novel, genes differentially expressed in stage I ovarian cancer. Using a differentially expressed gene set, class comparison prediction analysis correctly identified serous carcinomas from serous borderline tumors in 3 independent data sets at over 80% accuracy, sensitivity, and specificity. Pathway analysis demonstrated the significance of p53 and E2F pathways in serous carcinogenesis and significant involvements of cell cycle and immune response pathways in stage I serous epithelial ovarian cancer.
CONCLUSION: We have identified differentially expressed genes associated with the carcinogenesis of high-grade stage I serous EOC. Furthermore, integrative analysis of biological and transcription pathway data contributed to the confirmation of important biological pathways and discovery of additional unique genes and pathways that may have potential importance in ovarian pathogenesis and biomarker development.

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Year:  2009        PMID: 19410283     DOI: 10.1016/j.ygyno.2009.04.002

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  22 in total

1.  Minichromosome maintenance protein 7 as a potential prognostic factor for progression-free survival in high-grade serous carcinomas of the ovary.

Authors:  Takayo Ota; Amy C Clayton; Douglas M Minot; Viji Shridhar; Lynn C Hartmann; C Blake Gilks; Jeremy R Chien
Journal:  Mod Pathol       Date:  2010-11-12       Impact factor: 7.842

2.  Sorbitol dehydrogenase overexpression and other aspects of dysregulated protein expression in human precancerous colorectal neoplasms: a quantitative proteomics study.

Authors:  Anuli Uzozie; Paolo Nanni; Teresa Staiano; Jonas Grossmann; Simon Barkow-Oesterreicher; Jerry W Shay; Amit Tiwari; Federico Buffoli; Endre Laczko; Giancarlo Marra
Journal:  Mol Cell Proteomics       Date:  2014-02-24       Impact factor: 5.911

3.  Validation of ovarian cancer gene expression signatures for survival and subtype in formalin fixed paraffin embedded tissues.

Authors:  Gregory P Sfakianos; Edwin S Iversen; Regina Whitaker; Liudmila Akushevich; Joellen M Schildkraut; Susan K Murphy; Jeffrey R Marks; Andrew Berchuck
Journal:  Gynecol Oncol       Date:  2012-12-26       Impact factor: 5.482

4.  Whole-genome gene expression profiling of formalin-fixed, paraffin-embedded tissue samples.

Authors:  Craig April; Brandy Klotzle; Thomas Royce; Eliza Wickham-Garcia; Tanya Boyaniwsky; John Izzo; Donald Cox; Wendell Jones; Renee Rubio; Kristina Holton; Ursula Matulonis; John Quackenbush; Jian-Bing Fan
Journal:  PLoS One       Date:  2009-12-03       Impact factor: 3.240

Review 5.  Emerging regulatory paradigms in glutathione metabolism.

Authors:  Yilin Liu; Annastasia S Hyde; Melanie A Simpson; Joseph J Barycki
Journal:  Adv Cancer Res       Date:  2014       Impact factor: 6.242

6.  Gene expression analysis of matched ovarian primary tumors and peritoneal metastasis.

Authors:  Joel A Malek; Alejandra Martinez; Eliane Mery; Gwenael Ferron; Ruby Huang; Christophe Raynaud; Eva Jouve; Jean-Paul Thiery; Denis Querleu; Arash Rafii
Journal:  J Transl Med       Date:  2012-06-11       Impact factor: 5.531

7.  Loss-of-heterozygosity on chromosome 19q in early-stage serous ovarian cancer is associated with recurrent disease.

Authors:  Ingiridur Skirnisdottir; Markus Mayrhofer; Maria Rydåker; Helena Akerud; Anders Isaksson
Journal:  BMC Cancer       Date:  2012-09-12       Impact factor: 4.430

8.  High-prevalence and broad spectrum of Cell Adhesion and Extracellular Matrix gene pathway mutations in epithelial ovarian cancer.

Authors:  Arash Rafii; Najeeb M Halabi; Joel A Malek
Journal:  J Clin Bioinforma       Date:  2012-09-24

9.  An inferential framework for biological network hypothesis tests.

Authors:  Phillip D Yates; Nitai D Mukhopadhyay
Journal:  BMC Bioinformatics       Date:  2013-03-14       Impact factor: 3.169

10.  Non-steroidal anti-inflammatory drugs decrease E2F1 expression and inhibit cell growth in ovarian cancer cells.

Authors:  Blanca L Valle; Theresa D'Souza; Kevin G Becker; William H Wood; Yongqing Zhang; Robert P Wersto; Patrice J Morin
Journal:  PLoS One       Date:  2013-04-24       Impact factor: 3.240

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