Title |
Tumor-infiltrating CD4+ T cells in patients with gastric cancer
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Published in |
Cancer Cell International, December 2017
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DOI | 10.1186/s12935-017-0489-4 |
Pubmed ID | |
Authors |
Long Yuan, Benling Xu, Peng Yuan, Jinxue Zhou, Peng Qin, Lu Han, Guangyu Chen, Zhenlei Wang, Zengci Run, Peng Zhao, Quanli Gao |
Abstract |
T lymphocytes play an indispensably important role in clearing virus and tumor antigen. There is little knowledge about impacts of inhibitory molecules with cytokine on tumor-infiltrating CD4+ T-cells in the presence of gastric cancer (GC). This study investigated the distribution of tumor-infiltrating T-cells subset and the differentiation as well as inhibitory phenotype of T-cells from blood and tissues of GC patients. Patients with GC diagnosed on the basis of pre-operative staging and laparotomy findings were approached for enrollment between 2014 and 2015 at the Affiliated Cancer Hospital of Zhengzhou University, China. Phenotypic analysis based on isolation of tumor-infiltrating lymphocytes and intracellular IFN-γ staining assay is conducted. Statistical analysis is performed to show significance. The results showed that the percentage of CD4+ T-cells among CD3+ cells in tumors was significantly higher than that in the matched paraneoplastic tissue. CD4+ CD25high CD127low regulatory T-cells (Tregs), PD-1+, Tim-3+, and PD-1+ Tim-3+ cells were up-regulated on tumor infiltrating T-cells from patients with GC compared to their expressions on corresponding peripheral blood and peritumoral T-cells. Blockades of PD-1+ and Tim-3+ were effective in restoring tumor infiltrating T-cells' production of interferon-gamma (IFN-γ). Combined PD-1+ and Tim-3+ inhibition had a synergistic effect on IFN-γ secretion by CD4+ T-cells. The results suggested that the composition, inhibitors, and location of the immune infiltrate should be considered when evaluating antitumor immunotherapy. A new insight into the mechanisms underlying T cell dysfunction is provided. |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
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Unknown | 23 | 100% |
Demographic breakdown
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Student > Ph. D. Student | 5 | 22% |
Researcher | 5 | 22% |
Student > Bachelor | 3 | 13% |
Other | 2 | 9% |
Student > Master | 2 | 9% |
Other | 2 | 9% |
Unknown | 4 | 17% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 5 | 22% |
Immunology and Microbiology | 5 | 22% |
Biochemistry, Genetics and Molecular Biology | 3 | 13% |
Agricultural and Biological Sciences | 2 | 9% |
Engineering | 2 | 9% |
Other | 1 | 4% |
Unknown | 5 | 22% |