Phase II study evaluating 2 dosing schedules of oral foretinib (GSK1363089), cMET/VEGFR2 inhibitor, in patients with metastatic gastric cancer
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Background: T-cell infiltration in primary colon tumors is associated with improved patient survival. Preliminary data supports a similar association in colorectal liver metastases (CRLM), and we previously identified increased CRLM expression of the immunostimulatory cytokine LIGHT (TNFSF14) to be related to improved patient prognosis. Therefore, mechanisms to augment the T-cell response in CRLM may be a promising treatment modality, however, the tumor immune microenvironment and LIGHT expression in CRLM remains to be characterized.

Methods: Utilizing a syngeneic and immunocompetent model of CRLM, the immune microenvironment was characterized for lymphocyte phenotype, function, and location utilizing flow cytometry, immunoassays, and immunofluorescence microscopy.

Results: CD3+ and CD4+ lymphocytes were decreased, and CD8+ cells were increased in CRLM compared to control liver. When present, greater populations of tumor infiltrating lymphocytes (TIL) were found peritumoral than intratumoral. The TIL expressed significantly higher levels of CD69 and CD107a, but lower levels of LIGHT. Cytokine expression profiles revealed increased levels of the T-helper 1 (Th1) cytokines IFN gamma, IL-12, IL-1b, and IL-8 in CRLM compared to control liver tissue. There was no difference in T-helper 2 (Th2) cytokines between the groups.

Conclusions: Characterization of the tumor microenvironment of CRLM revealed that although a limited number of activated T-cells infiltrate the tumor and initiate an immune response, the number of LIGHT + T cells infiltrating the tumor were very low. Techniques to decrease suppressive influences or augment the cytotoxic T-cell response are needed and may be possible through mechanisms that can increase intratumoral TIL LIGHT expression.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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