Survival prediction of stage I lung adenocarcinomas by expression of 10 genes
| Autor: | Fabrizio Bianchi, Laura Tizzoni, Francesco Nicassio, Lara Felicioni, Antonio Marchetti, Pier Paolo Di Fiore, Paolo Nuciforo, Fiamma Buttitta, Manuela Vecchi, Loris Bernard |
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| Rok vydání: | 2007 |
| Předmět: |
Oncology
medicine.medical_specialty Lung Neoplasms Biology Adenocarcinoma Bioinformatics Predictive Value of Tests Internal medicine medicine Biomarkers Tumor Humans Lung cancer Survival analysis Neoplasm Staging Oligonucleotide Array Sequence Analysis Lung Gene Expression Profiling Cancer Reproducibility of Results General Medicine medicine.disease Prognosis Survival Analysis Gene expression profiling Gene Expression Regulation Neoplastic medicine.anatomical_structure Predictive value of tests Cohort Research Article |
| Zdroj: | The Journal of clinical investigation. 117(11) |
| ISSN: | 0021-9738 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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