Skip to main navigation Skip to search Skip to main content

A breast cancer prognostic signature predicts clinical outcomes in multiple tumor types

  • Ying Wooi Wan
  • , Yong Qian
  • , Shruti Rathnagiriswaran
  • , Vincent Castranova
  • , Nancy Lan Guo

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Epidemiological studies indicate an increased risk of subsequent primary ovarian cancer from women with breast cancer. We have recently identified a 28-gene expression signature that predicts, with high accuracy, the clinical course in a large population of breast cancer patients. This prognostic gene signature also accurately predicts response to chemotherapy commonly used for treating breast cancer, including CMF, Tamoxifen, Paclitaxel, Docetaxel and Doxorubicin (Adriamycin), in a panel of 60 cancer cell lines of nine different tissue origins. This prompted us to investigate whether this prognostic gene signature could also predict clinical outcome in other cancer types of epithelial origins, including ovarian cancer (n=124), colon tumors (n=74) and lung adenocarcinomas (n=442). The results show that the gene expression signature contributes significantly more accurate (P<0.05; compared with random prediction) prognostic information in multiple cancer types independent of established clinical parameters. Furthermore, the functional pathway analysis with curated database delineated a biological network with tight connections between the signature genes and numerous well established cancer hallmarks, indicating important roles of this prognostic gene signature in tumor genesis and progression.

Original languageEnglish
Pages (from-to)489-494
Number of pages6
JournalOncology Reports
Volume24
Issue number2
DOIs
StatePublished - Aug 2010

Keywords

  • Breast cancer
  • Colon cancer
  • Lung adenocarcinoma
  • Ovarian cancer
  • Prognostic gene signature

Fingerprint

Dive into the research topics of 'A breast cancer prognostic signature predicts clinical outcomes in multiple tumor types'. Together they form a unique fingerprint.

Cite this