| Metadata |
| datasetIdentifier | PASS00261 |
| datasetType | SRM |
| submitter | Lik Wee Lee <llee@indidx.com> |
| submitter_organization | Integrated Diagnostics |
| lab_head_full_name | Paul Kearney |
| lab_head_email | pkearney@indidx.com |
| lab_head_organization | Integrated Diagnostics |
| lab_head_country | United States |
| datasetTag | LungNoduleBiomarkers |
| datasetTitle | Biomarker discovery for lung nodules |
| publicReleaseDate | 2013-08-28 00:00:00 |
| finalizedDate | |
| summary | Each year millions of pulmonary nodules are discovered by computed tomography and subsequently biopsied. As the majority of these nodules are benign, many patients undergo unnecessary and costly invasive procedures. We present a 13-protein blood-based classifier that differentiates malignant and benign nodules with high confidence, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules. Using a systems biology strategy, 371 protein candidates were identified and a multiple reaction monitoring (MRM) assay was developed for each. The MRM assays were applied in a three-site discovery study (n = 143) on plasma samples from patients with benign and Stage IA cancer matched on nodule size, age, gender and clinical site, producing a 13-protein classifier. The classifier was validated on an independent set of plasma samples (n = 104), exhibiting a high negative predictive value (NPV) of 90%. Validation performance on samples from a non-discovery clinical site showed NPV of 94%, indicating the general effectiveness of the classifier. A pathway analysis demonstrated that the classifier proteins are likely modulated by a few transcription regulators (NF2L2, AHR, MYC, FOS) that are associated with lung cancer, lung inflammation and oxidative stress networks. The classifier score was independent of patient nodule size, smoking history and age, which are risk factors used for clinical management of pulmonary nodules. Thus this molecular test can provide a powerful complementary tool for physicians in lung cancer diagnosis. |
| contributors | Xiao-jun Li, Clive Hayward, Pui-Yee Fong, Michel Dominguez, Stephen W. Hunsucker, Lik Wee Lee, Matthew Mclean, Scott Law, Heather Butler, Michael Schirm, Olivier Gringras, Julie Lamotagne, Rene Allard, Daniel Chelsky, Nathan D. Price, Stephen Lam, Pierre P. Massion, Harvey Pass, William N. Rom, Anil Vachani, Kenneth C. Fang, Leroy Hood, Paul Kerney |
| publication | Science Translational Medicine 5, 207ra142 (2013) |
| growth | |
| treatment | |
| extraction | |
| separation | Immunoaffinity depletion with IgY14-Supermix resin columns (Sigma) |
| digestion | |
| acquisition | Scheduled MRM |
| informatics | |
| instruments | QTrap 5500 |
| species | Human |
| massModifications | none |
