Prognostic gene signatures for non-small-cell lung cancer

Resectable non-small-cell lung cancer (NSCLC) patients have poor prognosis, with 30-50% relapsing within 5 years. Current staging criteria do not fully capture the complexity of this disease. Survival could be improved by identification of those early-stage patients who are most likely to benefit fr...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2009-02, Vol.106 (8), p.2824-2828
Main Authors: Boutros, Paul C, Lau, Suzanne K, Pintilie, Melania, Liu, Ni, Shepherd, Frances A, Der, Sandy D, Tsao, Ming-Sound, Penn, Linda Z, Jurisica, Igor
Format: Article
Language:English
Subjects:
Adenocarcinoma
Adjuvant therapy
Adjuvants
Biological Sciences
Carcinoma, Non-Small-Cell Lung - genetics
Cells
Classification
Datasets
Gene expression
Gene Expression Profiling
Humans
Lung cancer
Lung neoplasms
Lung Neoplasms - genetics
Medical prognosis
Non small cell lung carcinoma
Polymerase chain reaction
Prognosis
Reverse Transcriptase Polymerase Chain Reaction
Ribonucleic acid
RNA
RNA, Messenger - genetics
Signatures
Squamous cell carcinoma
Statistical significance
Statistics
Survival
Tumors
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Summary:Resectable non-small-cell lung cancer (NSCLC) patients have poor prognosis, with 30-50% relapsing within 5 years. Current staging criteria do not fully capture the complexity of this disease. Survival could be improved by identification of those early-stage patients who are most likely to benefit from adjuvant therapy. Molecular classification by using mRNA expression profiles has led to multiple, poorly overlapping signatures. We hypothesized that differing statistical methodologies contribute to this lack of overlap. To test this hypothesis, we analyzed our previously published quantitative RT-PCR dataset with a semisupervised method. A 6-gene signature was identified and validated in 4 independent public microarray datasets that represent a range of tumor histologies and stages. This result demonstrated that at least 2 prognostic signatures can be derived from this single dataset. We next estimated the total number of prognostic signatures in this dataset with a 10-million-signature permutation study. Our 6-gene signature was among the top 0.02% of signatures with maximum verifiability, reaffirming its efficacy. Importantly, this analysis identified 1,789 unique signatures, implying that our dataset contains >500,000 verifiable prognostic signatures for NSCLC. This result appears to rationalize the observed lack of overlap among reported NSCLC prognostic signatures.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.0809444106