Immune Microenvironment and Response in Prostate Cancer Using Large Population Cohorts.
Immune Microenvironment and Response in Prostate Cancer Using Large Population Cohorts.
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DOI：
10.3389/fimmu.2021.686809
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发表时间：
2021
影响因子：
7.3
通讯作者：
Qin C
中科院分区：
文献类型：
--
作者：
Ren X;Chen X;Zhang X;Jiang S;Zhang T;Li G;Lu Z;Zhang D;Wang S;Qin C
前列腺癌（PCa）的免疫微环境与疾病进展有关。然而，以前的研究还没有充分探讨PCa免疫微环境。该研究使用ssGSEA算法来探索组合的PCa群组（8个群组; 1，597个样品）中53个免疫术语的表达水平。基于随机森林分析选择前10个免疫术语，并用于免疫相关风险评分（IRS）计算。此外，我们探讨了高IRS组和低IRS组之间临床和基因组特征的差异。基于10个免疫术语的IRS签名显示出对PCa预后的高预测潜力。高IRS组患者的免疫治疗应答因子百分比显著较高，表明IRS可有效预测免疫治疗应答率。此外，进行共识聚类以将人群分成具有不同临床结局的三个IRS聚类。IRScluster 3中的患者预后最差，免疫治疗应答率最高。另一方面，IRScluster 2中的患者显示出更好的预后和低免疫治疗应答率。此外，VGLL 3、ANPEP、CD 38、CCK、DPYS、CST 2、COMP、CRISP 3、NKAIN 1和F5基因在三个IRS簇中差异表达。此外，CMap分析显示，有5种化合物靶向IRS特征，硫利达嗪、三氟拉嗪、0175029-0000、阿司他汀A和氟奋乃静。总之，探索了PCa肿瘤微环境的免疫特征，并基于10个免疫术语构建了IRS签名。分析表明，该签名是预测PCa免疫治疗应答率和预后的有用工具。
Immune microenvironment of prostate cancer (PCa) is implicated in disease progression. However, previous studies have not fully explored PCa immune microenvironment. This study used ssGSEA algorithm to explore expression levels of 53 immune terms in a combined PCa cohort (eight cohorts; 1,597 samples). The top 10 immune terms were selected based on the random forest analysis and used for immune-related risk score (IRS) calculation. Furthermore, we explored differences in clinical and genomic features between high and low IRS groups. An IRS signature based on the 10 immune terms showed high prediction potential for PCa prognosis. Patients in the high IRS group showed significantly higher percentage of immunotherapy response factors, implying that IRS is effective in predicting immunotherapy response rate. Furthermore, consensus clustering was performed to separate the population into three IRSclusters with different clinical outcomes. Patients in IRScluster3 showed the worst prognosis and highest immunotherapy response rate. On the other hand, patients in IRScluster2 showed better prognosis and low immunotherapy response rate. In addition, VGLL3, ANPEP, CD38, CCK, DPYS, CST2, COMP, CRISP3, NKAIN1, and F5 genes were differentially expressed in the three IRSclusters. Furthermore, CMap analysis showed that five compounds targeted IRS signature, thioridazine, trifluoperazine, 0175029-0000, trichostatin A, and fluphenazine. In summary, immune characteristics of PCa tumor microenvironment was explored and an IRS signature was constructed based on 10 immune terms. Analysis showed that this signature is a useful tool for prognosis and prediction of immunotherapy response rate of PCa.
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影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
影响因子：
64.5
作者：
Malta TM;Sokolov A;Gentles AJ;Burzykowski T;Poisson L;Weinstein JN;Kamińska B;Huelsken J;Omberg L;Gevaert O;Colaprico A;Czerwińska P;Mazurek S;Mishra L;Heyn H;Krasnitz A;Godwin AK;Lazar AJ;Cancer Genome Atlas Research Network;Stuart JM;Hoadley KA;Laird PW;Noushmehr H;Wiznerowicz M
通讯作者：
Wiznerowicz M
影响因子：
4.6
作者：
Bonneville R;Krook MA;Kautto EA;Miya J;Wing MR;Chen HZ;Reeser JW;Yu L;Roychowdhury S
通讯作者：
Roychowdhury S
DOI：
10.1164/rccm.201309-1611oc
发表时间：
2014-04-01
影响因子：
24.7
作者：
Germain, Claire;Gnjatic, Sacha;Dieu-Nosjean, Marie-Caroline
通讯作者：
Dieu-Nosjean, Marie-Caroline
影响因子：
23.4
作者：
Humid, Anis A.;Gray, Kathryn P.;Sweeney, Christopher J.
通讯作者：
Sweeney, Christopher J.