Biomarker panel for detecting lung cancer
A method and a kit for assessing risk of lung cancer versus benign disease in a subject are provided. The method includes obtaining a biological sample from the subject and determining a measurement for a panel of biomarkers in the biological sample. The panel includes at least two biomarkers selected from the group consisting of IL-6, IL-1ra, IL-10, SDF-1α+β, TNF-α, MIP-1α, sIL-2Rα, CA-125, sE-Selectin, Eotaxin, sEGFR, MMP-2, OPN, MCP-1, CRP, sICAM-1 and CYFRA 21.1. The method further includes comparing the measurement to a reference profile for the panel of biomarkers, sorting the subject into a group and determining whether the subject is at risk for lung cancer based on the group.
1. A method of measuring a panel of biomarkers in a subject suspected of having non-small cell lung cancer, the method comprising:
obtaining a biological sample from the subject;
determining a measurement for the panel of biomarkers in the biological sample, the panel consisting of IL-6, IL-1ra, IL-10, SDF-1α+β, TNF-α, and MIP-1α, wherein the measurement comprises measuring a level of each biomarker in the panel.
2. The method according to claim 1 , comprising determining the measurement for the panel of biomarkers wherein the panel further comprises sIL-2Rα.
3. The method according to claim 1 , wherein the measurement is obtained after detection of an indeterminate nodule is found by low-dose computed tomography (LDCT) detection.
4. The method according to claim 1 , wherein the measurement is a primary screen.
5. The method according to claim 1 , wherein the subject is a “high risk” subject for lung cancer.
6. The method according to claim 1 , comprising using a learning statistical classifier system to analyze the measurement of the panel of biomarkers.
7. The method according to claim 6 , wherein the learning statistical classifier system is a Random Forest system.
8. The method according to claim 7 , wherein the panel has a misclassification error of less than 20%.
9. The method according to claim 6 , wherein the Random Forest system comprises 1000 cross-validated classification trees.
10. The method according to claim 1 , wherein the biological sample comprises plasma sample or serum sample.