Volatile organic compounds for detecting cell dysplasia and genetic alterations associated with lung cancer
The present invention provides methods of identifying a genetic abnormality such as mutation in EGFR or KRAS or ALK which is associated with the management of lung cancer or diagnosing, prognosing or monitoring the treatment of pre-cancerous conditions of the lung, such as bronchial dysplasia or atypical alveolar hyperplasia (AAH), through the detection of at least one volatile organic compound indicative of these states.
1. A method of differentiating between a test subject having lung cancer associated with a mutation in Epidermal Growth Factor Receptor (EGFR) and subjects having lung cancer associated with a genetic alteration selected from a mutation in KRAS, an ALK-ELM4 translocation and CMET amplification, the method comprising the steps of:
a) obtaining a breath sample from the test subject;
b) determining a level of at least one volatile organic compound associated with lung cancer in the breath sample; and
c) comparing the level of the at least one volatile organic compound from the breath sample with the level of said at least one volatile organic compound in a negative control sample of cells not having a mutation in EGFR, whereby a significantly different level of said at least one volatile organic compound in the breath sample as compared to the level of said compound in the negative control sample is indicative of the presence of mutation in EGFR.
2. The method according to claim 1 , wherein the at least one volatile organic compound associated with lung cancer is selected from the group consisting of 4-methyl-1-heptanol, acetic acid octyl ester, decane, 3-methyl-decane, octanal, pentadecanenitrile, and tetradecene; or selected from the group consisting of 4-methyl-1-heptanol, 6-methyl-1-heptanol, 2-ethyl-1-hexanol, acetic acid octyl ester, benzaldehyde, decane, 3-methyl-dodecane, tetrahydrofuran, isopropyl myristate, octanal, pentadecanenitrile, 2,2,4-trimethyl-pentanenitrile, 2,2,4-trimethyl-3-carboxyisopropyl-isobutyl ester pentanoic acid, phenol, styrene, tetradecane, 4-methyl-tetradecane, toluene, tridecane, 6-methyl-tridecane, and undecane; or selected from the group consisting of triethylamine, 2-hydroxy benzaldehyde, and decanal; or selected from the group consisting of triethylamine, toluene, styrene, benzaldehyde, 2-hydroxy benzaldehyde, decanal, phenol and 2-ethyl-1-hexanol.
3. The method according to claim 1 , wherein the step of determining the level of at least one volatile organic compound in the breath sample comprises the use of at least one technique selected from the group consisting of an olfactory system, Gas-Chromatography (GC), GC-lined Mass-Spectrometry (GC-MS), Proton Transfer Reaction Mass-Spectrometry (PTR-MS), and Quartz Crystal Microbalance (QCM).
4. The method according to claim 1 , wherein the level of the at least one volatile organic compound in the breath sample is increased as compared with the level of said compound in the control sample; or wherein the level of the at least one volatile organic compound in the breath sample is decreased as compared with the level of said compound in the control sample.
5. The method according to claim 1 , wherein the at least one volatile organic compound in the breath sample is a plurality of volatile organic compounds, and wherein a combination of levels of each of the plurality of volatile organic compounds in the breath sample a pattern which is significantly different from a pattern of the combination of levels of each of the plurality of volatile organic compounds in the negative control sample.
6. The method according to claim 5 , wherein the pattern is analyzed with a pattern recognition analyzer.
7. The method according to claim 6 , wherein the pattern recognition analyzer comprises at least one algorithm selected from the group consisting of principal component analysis (PCA), artificial neural network algorithms, multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.
8. The method according to claim 1 , wherein the test subject is a mammal.
9. The method according to claim 1 , wherein the at least one volatile organic compound associated with lung cancer is selected from the group consisting of triethylamine, toluene, styrene, decanal, phenol and 2-ethyl-1-hexanol.
10. The method according to claim 1 , wherein the test subject is human.
11. The method according to claim 1 , wherein the mutation in EGFR is a T790M EGFR mutation.
12. A method for treating lung cancer, comprising:
(i) determining that a patient has a lung cancer associated with a mutation in Epidermal Growth Factor Receptor (EGFR), as differentiated from patients having lung cancer associated with a genetic alteration selected from a mutation in KRAS, an ALK-ELM4 translocation and CMET amplification, by a method comprising the steps of:
a) obtaining a breath sample from the patient;
b) determining a level of at least one volatile organic compound associated with lung cancer in the breath sample; and
c) comparing the level of the at least one volatile organic compound from the breath sample with the level of said at least one volatile organic compound in a negative control sample of cells not having a mutation in EGFR, whereby a significantly different level of said at least one volatile organic compound in the breath sample as compared to the level of said compound in the negative control sample is indicative of the presence of mutation in EGFR in the patient, and
(ii) administering a tyrosine kinase modulator to the patient having a lung cancer associated with the mutation in EGFR.
13. The method according to claim 12 , wherein the tyrosine kinase modulator is selected from the group consisting of Axitinib, Bosutinib, Cediranib, Crizotinib, Dasatinib, Erlotinib, Gefitinib, Imatinib, Lapatinib, Lestaurtinib, Nilotinib, Semaxanib, Sunitinib, and Vandetanib.
14. The method according to claim 12 , wherein the at least one volatile organic compound associated with lung cancer is selected from the group consisting of 4-methyl-1-heptanol, acetic acid octyl ester, decane, 3-methyl-decane, octanal, pentadecanenitrile, and tetradecene; or selected from the group consisting of 4-methyl-1-heptanol, 6-methyl-1-heptanol, 2-ethyl-1-hexanol, acetic acid octyl ester, benzaldehyde, decane, 3-methyl-dodecane, tetrahydrofuran, isopropyl myristate, octanal, pentadecanenitrile, 2,2,4-trimethyl-pentanenitrile, 2,2,4-trimethyl-3-carboxyisopropyl-isobutyl ester pentanoic acid, phenol, styrene, tetradecane, 4-methyl-tetradecane, toluene, tridecane, 6-methyl-tridecane, and undecane; or selected from the group consisting of triethylamine, 2-hydroxy benzaldehyde, and decanal; or selected from the group consisting of triethylamine, toluene, styrene, benzaldehyde, 2-hydroxy benzaldehyde, decanal, phenol and 2-ethyl-1-hexanol.
15. The method according to claim 12 , wherein the at least one volatile organic compound associated with lung cancer is selected from the group consisting of triethylamine, toluene, styrene, decanal, phenol and 2-ethyl-1-hexanol.
16. The method according to claim 12 , wherein the step of determining the level of at least one volatile organic compound in the breath sample comprises the use of at least one technique selected from the group consisting of an olfactory system, Gas-Chromatography (GC), GC-lined Mass-Spectrometry (GC-MS), Proton Transfer Reaction Mass-Spectrometry (PTR-MS), and Quartz Crystal Microbalance (QCM).
17. The method according to claim 12 , wherein the level of the at least one volatile organic compound in the breath sample is increased as compared with the level of said compound in the control sample; or wherein the level of the at least one volatile organic compound in the breath sample is decreased as compared with the level of said compound in the control sample.
18. The method according to claim 12 , wherein the at least one volatile organic compound in the breath sample is a plurality of volatile organic compounds, and wherein a combination of levels of each of the plurality of volatile organic compounds in the breath sample forms a pattern which is significantly different from a pattern of the combination of levels of each of the plurality of volatile organic compounds in the negative control sample.
19. The method according to claim 18 , wherein the pattern is analyzed with a pattern recognition analyzer.
20. The method according to claim 19 , wherein the pattern recognition analyzer comprises at least one algorithm selected from the group consisting of principal component analysis (PCA), artificial neural network algorithms, multi-layer perception (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), radial bias function (RBF), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA), linear discriminant analysis (LDA), cluster analysis, and nearest neighbor.