טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
Ph.D Thesis
Ph.D StudentOrna Barash
SubjectVolatile Signature of Genetic Mutations in Lung Cancer
DepartmentDepartment of Chemical Engineering
Supervisor Full Professor Haick Hossam
Full Thesis textFull thesis text - English Version


Abstract

Lung cancer (LC) development is associated with multiple genetic and epigenetic alterations, involving tumor suppressor genes (e.g. TP53) and specific oncogenes (e.g. EGFR, KRAS, EML4-ALK fusion). Nowadays, the most available approach for studying the molecular specification and for profiling LC lesions is based on genomics and proteomics; however these techniques suffer from several obstacles like limited and variable sample material along with sample degradation, high costs and extended analysis time. In this thesis, we present a new approach for LC genetic mapping that is based on analysis through volatile organic compounds (VOCs). For this purpose, we have analyzed VOCs from isolated LC cell lines and found a correlation between their volatolomic (VOC) signatures and the cells' metabolic activity (i.e. genetic mutation) using two independent approaches. The first approach is based on chemical analysis by gas chromatography linked with mass spectrometry (GC-MS) for the identification and quantification of the variety of breath VOCs exist in each studied group. The second method is based on cross-reactive nanoarrays in combination with pattern recognition methods. This approach provides collective VOC patterns rather than specific VOC identification and quantification. The results showed the feasibility to sense secondary metabolic expressions for fine genetic alterations such as mutation in KRAS, P53, EGFR and EML4-ALK from the cells headspace.  Some of the alterations were associated with general carcinogenesis while the other part predicts response to targeted therapy. These findings indicate that volatolomics might have the potential one day to help guiding doctors in making medical decisions at the time of diagnosis and also monitoring the progression/regression of the disease during treatment for reassessment of clinical approach in a rapid, cheap and accurate manner.