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.
Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA. dgbeer@umich.edu
David G
DG
Beer
Sharon L R
SL
Kardia
Chiang-Ching
CC
Huang
Thomas J
TJ
Giordano
Albert M
AM
Levin
David E
DE
Misek
Lin
L
Lin
Guoan
G
Chen
Tarek G
TG
Gharib
Dafydd G
DG
Thomas
Michelle L
ML
Lizyness
Rork
R
Kuick
Satoru
S
Hayasaka
Jeremy M G
JM
Taylor
Mark D
MD
Iannettoni
Mark B
MB
Orringer
Samir
S
Hanash
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