Transthyretin Stimulates Tumor Growth through Regulation of Tumor, Immune, and Endothelial Cells.
Chih-Chun LeeXinchun DingTing ZhaoLingyan WuSusan PerkinsHong DuCong YanPublished in: Journal of immunology (Baltimore, Md. : 1950) (2018)
Early detection of lung cancer offers an important opportunity to decrease mortality while it is still treatable and curable. Thirteen secretory proteins that are Stat3 downstream gene products were identified as a panel of biomarkers for lung cancer detection in human sera. This panel of biomarkers potentially differentiates different types of lung cancer for classification. Among them, the transthyretin (TTR) concentration was highly increased in human serum of lung cancer patients. TTR concentration was also induced in the serum, bronchoalveolar lavage fluid, alveolar type II epithelial cells, and alveolar myeloid cells of the CCSP-rtTA/(tetO)7-Stat3C lung tumor mouse model. Recombinant TTR stimulated lung tumor cell proliferation and growth, which were mediated by activation of mitogenic and oncogenic molecules. TTR possesses cytokine functions to stimulate myeloid cell differentiation, which are known to play roles in tumor environment. Further analyses showed that TTR treatment enhanced the reactive oxygen species production in myeloid cells and enabled them to become functional myeloid-derived suppressive cells. TTR demonstrated a great influence on a wide spectrum of endothelial cell functions to control tumor and immune cell migration and infiltration. TTR-treated endothelial cells suppressed T cell proliferation. Taken together, these 13 Stat3 downstream inducible secretory protein biomarkers potentially can be used for lung cancer diagnosis, classification, and as clinical targets for lung cancer personalized treatment if their expression levels are increased in a given lung cancer patient in the blood.
Keyphrases
- endothelial cells
- cell proliferation
- induced apoptosis
- high glucose
- cell cycle arrest
- dendritic cells
- bone marrow
- mouse model
- cell migration
- machine learning
- reactive oxygen species
- acute myeloid leukemia
- cell cycle
- cardiovascular disease
- poor prognosis
- gene expression
- small molecule
- binding protein
- immune response
- dna methylation
- induced pluripotent stem cells
- combination therapy
- protein protein
- quantum dots
- newly diagnosed
- replacement therapy
- sensitive detection
- wild type