Blood-Based Gene Expression Signatures in Non―Small Cell Lung Cancer

Blood-based surrogate markers would be attractive biomarkers for early detection, diagnosis, prognosis, and prediction of therapeutic outcome in cancer. Disease-associated gene expression signatures in peripheral blood mononuclear cells (PBMC) have been described for several cancer types. However, R...

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Veröffentlicht in:Clinical cancer research 2011-05, Vol.17 (10), p.3360-3367
Hauptverfasser: ZANDER, Thomas, HOFMANN, Andrea, GATHOF, Birgit, MAUCH, Cornelia, DELANK, Karl-Stefan, ENGEL-RIEDEL, Walburga, WICHMANN, H.-Erich, STOELBEN, Erich, SCHULTZE, Joachim L, WOLF, Jürgen, STARATSCHEK-JOX, Andrea, CLASSEN, Sabine, DEBEY-PASCHER, Svenja, MAISEL, Daniela, ANSEN, Sascha, HAHN, Moritz, BEYER, Marc, THOMAS, Roman K
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Sprache:eng
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Zusammenfassung:Blood-based surrogate markers would be attractive biomarkers for early detection, diagnosis, prognosis, and prediction of therapeutic outcome in cancer. Disease-associated gene expression signatures in peripheral blood mononuclear cells (PBMC) have been described for several cancer types. However, RNA-stabilized whole blood-based technologies would be clinically more applicable and robust. We evaluated the applicability of whole blood-based gene expression profiling for the detection of non-small cell lung cancer (NSCLC). Expression profiles were generated from PAXgene-stabilized blood samples from three independent groups consisting of NSCLC cases and controls (n = 77, 54, and 102), using the Illumina WG6-VS2 system. Several genes are consistently differentially expressed in whole blood of NSCLC patients and controls. These expression profiles were used to build a diagnostic classifier for NSCLC, which was validated in an independent validation set of NSCLC patients (stages I-IV) and hospital-based controls. The area under the receiver operator curve was calculated to be 0.824 (P < 0.001). In a further independent dataset of stage I NSCLC patients and healthy controls the AUC was 0.977 (P < 0.001). Specificity of the classifier was validated by permutation analysis in both validation cohorts. Genes within the classifier are enriched in immune-associated genes and show specificity for NSCLC. Our results show that gene expression profiles of whole blood allow for detection of manifest NSCLC. These results prompt further development of gene expression-based biomarker tests in peripheral blood for the diagnosis and early detection of NSCLC.
ISSN:1078-0432
1557-3265
DOI:10.1158/1078-0432.CCR-10-0533