E Zhang1, F Dai2, Y Mao3, W He3, F Liu3, W Ma4, Y Qiao4. 1. School of Life Sciences, Lanzhou University, No. 222 Tianshui South Road, Lanzhou, 730000, Gansu, People's Republic of China. zhanged15@lzu.edu.cn. 2. School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China. 3. Lanzhou University Second Hospital, Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China. 4. Lanzhou University First Hospital, Lanzhou University, Lanzhou, 730000, Gansu, People's Republic of China.
Abstract
BACKGROUND: Over the past few decades, immunological checkpoint therapy has been an increasingly prominent strategy in the treatment of tumors, including prostate cancer (PC). There are few systematic studies of the phenotypic of tumor-infiltrating immune cells in PC tissues. METHODS: CIBERSORT is an analytical tool for estimating the abundance of member cell types in mixed cell population by gene expression data. Herein, we analyzed different levels of tumor-infiltrating immunity cells in normal tissue compared with PC using CIBERSORT. RESULTS: The results showed that proportion of M1 macrophages and resting mast cells presented significant differences in prostate tumor than these normal tissues. A higher proportion of resting mast cells was associated with a worse outcome and M1 macrophages was associated with a favorable outcome. Moreover, the radiotherapy and targeted molecular therapy can affect the immune infiltration of M1 macrophages and resting mast cells. CONCLUSIONS: Resting mast cells and M1 macrophages has an important role in the prognosis of prostate cancer. Our data provides valuable information about the future treatment of PC.
BACKGROUND: Over the past few decades, immunological checkpoint therapy has been an increasingly prominent strategy in the treatment of tumors, including prostate cancer (PC). There are few systematic studies of the phenotypic of tumor-infiltrating immune cells in PC tissues. METHODS: CIBERSORT is an analytical tool for estimating the abundance of member cell types in mixed cell population by gene expression data. Herein, we analyzed different levels of tumor-infiltrating immunity cells in normal tissue compared with PC using CIBERSORT. RESULTS: The results showed that proportion of M1 macrophages and resting mast cells presented significant differences in prostate tumor than these normal tissues. A higher proportion of resting mast cells was associated with a worse outcome and M1 macrophages was associated with a favorable outcome. Moreover, the radiotherapy and targeted molecular therapy can affect the immune infiltration of M1 macrophages and resting mast cells. CONCLUSIONS: Resting mast cells and M1 macrophages has an important role in the prognosis of prostate cancer. Our data provides valuable information about the future treatment of PC.
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