Predicting prognosis of breast cancer with gene signatures: Are we lost in a sea of data?

Takayuki Iwamoto, Lajos Pusztai

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

A large number of prognostic and predictive signatures have been proposed for breast cancer and a few ofthese are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes.

Original languageEnglish
Article number81
JournalGenome Medicine
Volume2
Issue number11
DOIs
Publication statusPublished - Nov 12 2010
Externally publishedYes

Fingerprint

Neoplasm Genes
Breast Neoplasms
Genes
Gene Expression
Molecular Pathology
Validation Studies
Routine Diagnostic Tests
History
Research Personnel
Phenotype

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics
  • Molecular Biology
  • Molecular Medicine

Cite this

Predicting prognosis of breast cancer with gene signatures : Are we lost in a sea of data? / Iwamoto, Takayuki; Pusztai, Lajos.

In: Genome Medicine, Vol. 2, No. 11, 81, 12.11.2010.

Research output: Contribution to journalArticle

@article{9ba2cfcea7cb4b4eb9a6020d066b785c,
title = "Predicting prognosis of breast cancer with gene signatures: Are we lost in a sea of data?",
abstract = "A large number of prognostic and predictive signatures have been proposed for breast cancer and a few ofthese are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes.",
author = "Takayuki Iwamoto and Lajos Pusztai",
year = "2010",
month = "11",
day = "12",
doi = "10.1186/gm202",
language = "English",
volume = "2",
journal = "Genome Medicine",
issn = "1756-994X",
publisher = "BioMed Central",
number = "11",

}

TY - JOUR

T1 - Predicting prognosis of breast cancer with gene signatures

T2 - Are we lost in a sea of data?

AU - Iwamoto, Takayuki

AU - Pusztai, Lajos

PY - 2010/11/12

Y1 - 2010/11/12

N2 - A large number of prognostic and predictive signatures have been proposed for breast cancer and a few ofthese are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes.

AB - A large number of prognostic and predictive signatures have been proposed for breast cancer and a few ofthese are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes.

UR - http://www.scopus.com/inward/record.url?scp=78751696635&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78751696635&partnerID=8YFLogxK

U2 - 10.1186/gm202

DO - 10.1186/gm202

M3 - Article

C2 - 21092148

AN - SCOPUS:78751696635

VL - 2

JO - Genome Medicine

JF - Genome Medicine

SN - 1756-994X

IS - 11

M1 - 81

ER -