Lung cancer is one of the most common and deadly types of cancer. Mouse models of lung cancer recapitulate many features of the human disease and have provided new insight about cancer development, progression and treatment. Now, a new study published by Cell Press in the September 13th issue of the journal Cancer Cell identifies protein signatures in mouse blood samples that reflect lung cancer biology in humans.
The research may lead to better monitoring of tumor progression as well as blood based early detection strategies for human lung cancer that could have a substantial impact on disease prognosis.
"In our study, we applied a comparative strategy of genetically engineered mouse models of cancer and integrated data at the genome and protein levels to uncover lung cancer signatures in blood samples that reflect different types of lung cancer, or that reflect signaling pathways driving tumor development," says senior study author, Dr. Samir M. Hanash, from the Fred Hutchinson Cancer Research Center in Seattle. In order to identify blood protein signatures common to lung cancer, Dr. Hanash and colleagues looked at the proteins in the blood plasma of several different mouse lung tumor models and compared the proteins with those in models of other types of tumors.
The researchers identified individual protein signatures for molecularly distinct types of lung cancer and discovered that the networks of proteins provided insight into the genes that drive tumor development. Further, they identified proteins which were restricted to the blood samples from the lung cancer models and were not previously linked with lung cancer.
The authors went on to demonstrate the relevance of the protein signatures identified in the mouse models to human lung cancer. "We obtained evidence for concordant findings in human lung cancer cell lines and in plasmas collected from subjects with lung cancer at the time of diagnosis and in blood samples collected from asymptomatic subjects prior to diagnosis. These findings point to the power of integrating multiple types of studies and data to uncover lung cancer markers and may lead to early detection strategies for humans as well as strategies for monitoring tumor status in patients with the disease," says Dr. Hanash.
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