Gene-expression profiles predict survival of patients with lung adenocarcinoma.
Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy.
Beer
David G
DG
Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA. dgbeer@umich.edu
Kardia
Sharon L R
SL
Huang
Chiang-Ching
CC
Giordano
Thomas J
TJ
Levin
Albert M
AM
Misek
David E
DE
Lin
Lin
L
Chen
Guoan
G
Gharib
Tarek G
TG
Thomas
Dafydd G
DG
Lizyness
Michelle L
ML
Kuick
Rork
R
Hayasaka
Satoru
S
Taylor
Jeremy M G
JM
Iannettoni
Mark D
MD
Orringer
Mark B
MB
Hanash
Samir
S
D000230:Adenocarcinoma / Q000145:classification / Q000235:genetics* / Q000401:mortality* / Q000473:pathology; D015331:Cohort Studies; D020869:Gene Expression Profiling; D006801:Humans; D008175:Lung Neoplasms / Q000145:classification / Q000235:genetics* / Q000401:mortality* / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D015996:Survival Rate