Lung cancer is a complex disease, with a wide range of genetic alterations and clinical presentations. Understanding the natural and clinical history of the disease is crucial for developing effective diagnostic and treatment strategies. Omics approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools for understanding the molecular mechanisms underlying lung cancer and for identifying novel biomarkers and therapeutic targets. These approaches enable researchers to examine the entire genome, transcriptome, proteome, or metabolome of a cell or tissue, providing a comprehensive view of the biological processes involved in lung cancer development and progression. Targeted therapies that address specific genetic mutations and pathways hold promise for improving the diagnosis and treatment of this disease.
Micheletti, C., Dhuli, K., Donato, K., Gadler, M., Benedetti, S., Guerri, G., et al. (2023). Omics sciences and precision medicine in lung cancer. LA CLINICA TERAPEUTICA, 174(Suppl. 2(6)), 37-45 [10.7417/CT.2023.2470].
Omics sciences and precision medicine in lung cancer
Micheletti, C
;Bernini, A;Bertelli, M
2023-01-01
Abstract
Lung cancer is a complex disease, with a wide range of genetic alterations and clinical presentations. Understanding the natural and clinical history of the disease is crucial for developing effective diagnostic and treatment strategies. Omics approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools for understanding the molecular mechanisms underlying lung cancer and for identifying novel biomarkers and therapeutic targets. These approaches enable researchers to examine the entire genome, transcriptome, proteome, or metabolome of a cell or tissue, providing a comprehensive view of the biological processes involved in lung cancer development and progression. Targeted therapies that address specific genetic mutations and pathways hold promise for improving the diagnosis and treatment of this disease.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1261118