Adenocarcinoma is the predominant histological subtype of lung cancer, the leading cause of cancer deaths in the world. At stage I, the tumor is cured by surgery alone in about 60% of cases. Markers are needed to stratify patients by prognostic outcomes and may help in devising more effective therapies for poor prognosis patients. To achieve this goal, we used an integrated strategy combining meta-analysis of published lung cancer microarray data with expression profiling from an experimental model. The resulting 80-gene model was tested on an independent cohort of patients using RT-PCR, resulting in a 10-gene predictive model that exhibited a prognostic accuracy of approximately 75% in stage I lung adenocarcinoma when tested on 2 additional independent cohorts. Thus, we have identified a predictive signature of limited size that can be analyzed by RT-PCR, a technology that is easy to implement in clinical laboratories.

Survival prediction of stage I lung adenocarcinomas by expression of 10 genes / F. Bianchi, P. Nuciforo, M. Vecchi, L. Bernard, L. Tizzoni, A. Marchetti, F. Buttitta, L. Felicioni, F. Nicassio, P.P. Di Fiore. - In: THE JOURNAL OF CLINICAL INVESTIGATION. - ISSN 0021-9738. - 117:11(2007 Nov), pp. 3436-3444. [10.1172/JCI32007]

Survival prediction of stage I lung adenocarcinomas by expression of 10 genes

P.P. Di Fiore
Ultimo
2007

Abstract

Adenocarcinoma is the predominant histological subtype of lung cancer, the leading cause of cancer deaths in the world. At stage I, the tumor is cured by surgery alone in about 60% of cases. Markers are needed to stratify patients by prognostic outcomes and may help in devising more effective therapies for poor prognosis patients. To achieve this goal, we used an integrated strategy combining meta-analysis of published lung cancer microarray data with expression profiling from an experimental model. The resulting 80-gene model was tested on an independent cohort of patients using RT-PCR, resulting in a 10-gene predictive model that exhibited a prognostic accuracy of approximately 75% in stage I lung adenocarcinoma when tested on 2 additional independent cohorts. Thus, we have identified a predictive signature of limited size that can be analyzed by RT-PCR, a technology that is easy to implement in clinical laboratories.
Settore MED/04 - Patologia Generale
http://www.jci.org/cgi/reprint/117/11/3436?
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/33726
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