Expression signatures of TP53 mutations in serous ovarian cancers.

Abstract

BACKGROUND: Mutations in the TP53 gene are extremely common and occur very early in the progression of serous ovarian cancers. Gene expression patterns that relate to mutational status may provide insight into the etiology and biology of the disease. METHODS: The TP53 coding region was sequenced in 89 frozen serous ovarian cancers, 40 early stage (I/II) and 49 advanced stage (III/IV). Affymetrix U133A expression data was used to define gene expression patterns by mutation, type of mutation, and cancer stage. RESULTS: Missense or chain terminating (null) mutations in TP53 were found in 59/89 (66%) ovarian cancers. Early stage cancers had a significantly higher rate of null mutations than late stage disease (38% vs. 8%, p < 0.03). In advanced stage cases, mutations were more prevalent in short term survivors than long term survivors (81% vs. 30%, p = 0.0004). Gene expression patterns had a robust ability to predict TP53 status within training data. By using early versus late stage disease for out of sample predictions, the signature derived from early stage cancers could accurately (86%) predict mutation status of late stage cancers. CONCLUSIONS: This represents the first attempt to define a genomic signature of TP53 mutation in ovarian cancer. Patterns of gene expression characteristic of TP53 mutation could be discerned and included several genes that are known p53 targets or have been described in the context of expression signatures of TP53 mutation in breast cancer.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1186/1471-2407-10-237

Publication Info

Bernardini, Marcus Q, Tsukasa Baba, Paula S Lee, Jason C Barnett, Gregory P Sfakianos, Angeles Alvarez Secord, Susan K Murphy, Edwin Iversen, et al. (2010). Expression signatures of TP53 mutations in serous ovarian cancers. BMC Cancer, 10. p. 237. 10.1186/1471-2407-10-237 Retrieved from https://hdl.handle.net/10161/4356.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Secord

Angeles Alvarez Secord

Professor of Obstetrics and Gynecology

My primary research interest has focused on on novel therapeutics, biomarkers and clinical trial development for ovarian and endometrial cancer. My fundamental goal is to develop a strong translational research program at Duke University in the Gynecologic Oncology Division, where knowledge we glean from our basic science research can be incorporated into our clinical trial program. Specifically, my focus is on biologic therapy and molecular biomarkers to direct therapy in patients with ovarian and endometrial cancers to determine if a strategy that incorporates both clinical and genomic information can improve clinical outcome, minimize unnecessary toxicity, and impact positively on quality of life.

In addition I am interested in robotic-assisted laparoscopic surgery for women with endometrial, ovarian and cervical cancers, as well as for benign gynecologic conditions.

Iversen

Edwin Severin Iversen

Research Professor of Statistical Science

Bayesian statistical modeling with application to problems in genetic
epidemiology and cancer research; models for epidemiological risk
assessment, including hierarchical methods for combining related
epidemiological studies; ascertainment corrections for high risk
family data; analysis of high-throughput genomic data sets.


Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.