Compositions, methods and kits for diagnosis of lung cancer
The present invention provides methods for identifying biomarker proteins that exhibit differential expression in subjects with a first lung condition versus healthy subjects or subjects with a second lung condition. The present invention also provides compositions comprising these biomarker proteins and methods of using these biomarker proteins or panels thereof to diagnose, classify, and monitor various lung conditions. The methods and compositions provided herein may be used to diagnose or classify a subject as having lung cancer or a non-cancerous condition, and to distinguish between different types of cancer (e.g., malignant versus benign, SCLC versus NSCLC).
1. A method of determining the likelihood that a pulmonary nodule in a subject is not lung cancer, comprising:
(a) contacting a blood sample obtained from the subject with a proteolytic enzyme to produce peptide fragments from a panel of proteins present in the blood sample, wherein the panel comprises ALDOA_HUMAN, FRIL_HUMAN, LG3BP_HUMAN, TSP1_HUMAN, COIA1_HUMAN, PEDF_HUMAN, MASP1_HUMAN, GELS_HUMAN, LUM_HUMAN, C163A_HUMAN and PTPRJ_HUMAN;
(b) combining the produced peptide fragments from the panel from step (a) with labeled, synthetic peptide fragments which correspond to the produced peptide fragments from the panel;
(c) performing selected reaction monitoring mass spectrometry to measure the abundance of the peptide fragments from step (b);
(d) calculating a probability of lung cancer score based on the peptide fragment measurements of step (c) and one protein-protein interaction comprising peptide fragments produced from FRIL_HUMAN and COIA1_HUMAN;
(e) ruling out lung cancer for the subject if the score in step (d) is lower than a pre-determined score; and
(f) performing image monitoring on the subject for at least a one year period if the pulmonary nodule is determined not to be lung cancer.
2. The method of claim 1 , wherein the pulmonary nodule is 30 mm or less.
3. The method of claim 2 , wherein the pulmonary nodule is between 8-30 mm.
4. The method of claim 1 , wherein the subject is a human.
5. The method of claim 1 , wherein the synthetic peptide fragments have an isotopic label attached.
6. The method of claim 1 , wherein a transition for each of the peptide fragments is determined.
7. The method of claim 1 , wherein said score is determined as P s =1/[1+exp(−α−Σ i=1 5 β i *{hacek over (I)} i,s −γ*{hacek over (I)} COIA1 *{hacek over (I)} FRIL )], where {hacek over (I)} is Box-Cox transformed and normalized intensity of transition i in said sample (s), βi is the corresponding logistic regression coefficient, α is a panel-specific constant, and γ is a coefficient for the interaction term.
8. The method of claim 1 , wherein the predetermined lung cancer score is obtained from a reference population comprising at least 100 subjects with a lung condition and wherein each subject in the reference population has been assigned a score based on the abundance of peptide fragments produced from at least each of ALDOA_HUMAN, FRIL_HUMAN, LG3BP_HUMAN, TSP1_HUMAN and COIA1_HUMAN obtained from a blood sample.
9. The method of claim 1 , wherein lung cancer is ruled out in a subject if the probability of lung cancer score is 15% or less in comparison to a reference population.
10. The method of claim 9 , wherein lung cancer is ruled out in the subject if the probability of lung cancer score is 10% or less in comparison to a reference population.
11. The method of claim 10 , wherein lung cancer is ruled out in the subject if the probability of lung cancer score is 5% or less in comparison to a reference population.
12. The method of claim 1 , wherein the image monitoring comprises chest computed tomography.
13. The method of claim 1 , wherein at least one step is performed on a computer system.
14. The method of claim 1 , wherein the proteolytic enzyme is trypsin.