Hye Sook Chon1, Johnathan M Lancaster. 1. Department of Women's Oncology at H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida 33612, USA.
Abstract
BACKGROUND: DNA microarray technology is a powerful genomic tool that has the potential to elucidate the relationship between clinical features of cancers and their underlying biological alterations. METHODS: We performed a systemic search in PubMed and Medline databases for recently published articles. The search terms used included "genome-wide," "microarrays," "ovarian cancer," "prognosis, " "gene expression profiling, " "molecular marker, " and "molecular biomarker. " RESULTS: Genome-wide expression profiling using DNA microarray technology has enhanced our understanding of the genes that influence ovarian cancer development, histopathologic subtype, progression, response to therapy, and overall survival. CONCLUSIONS: Gene expression profiling has demonstrated its utility in ovarian cancer research. It is hoped that with technologic, statistical, and bioinformatic advances, the reliability and reproducibility of this technique will increase, spawning clinical applications that may enhance our understanding of the disease and our ability to care for patients in the future.
BACKGROUND: DNA microarray technology is a powerful genomic tool that has the potential to elucidate the relationship between clinical features of cancers and their underlying biological alterations. METHODS: We performed a systemic search in PubMed and Medline databases for recently published articles. The search terms used included "genome-wide," "microarrays," "ovarian cancer," "prognosis, " "gene expression profiling, " "molecular marker, " and "molecular biomarker. " RESULTS: Genome-wide expression profiling using DNA microarray technology has enhanced our understanding of the genes that influence ovarian cancer development, histopathologic subtype, progression, response to therapy, and overall survival. CONCLUSIONS: Gene expression profiling has demonstrated its utility in ovarian cancer research. It is hoped that with technologic, statistical, and bioinformatic advances, the reliability and reproducibility of this technique will increase, spawning clinical applications that may enhance our understanding of the disease and our ability to care for patients in the future.
Authors: Andrew D Kelly; Katherine E Hill; Mick Correll; Lan Hu; Yaoyu E Wang; Renee Rubio; Shenghua Duan; John Quackenbush; Dimitrios Spentzos Journal: Genomics Date: 2013-04-03 Impact factor: 5.736
Authors: Levi Waldron; Benjamin Haibe-Kains; Aedín C Culhane; Markus Riester; Jie Ding; Xin Victoria Wang; Mahnaz Ahmadifar; Svitlana Tyekucheva; Christoph Bernau; Thomas Risch; Benjamin Frederick Ganzfried; Curtis Huttenhower; Michael Birrer; Giovanni Parmigiani Journal: J Natl Cancer Inst Date: 2014-04-03 Impact factor: 11.816