Induction of Wnt-inducible signaling protein-1 correlates with invasive breast cancer oncogenesis and reduced type 1 cell-mediated cytotoxic immunity: a retrospective study.
Induction of Wnt-inducible signaling protein-1 correlates with invasive breast cancer oncogenesis and reduced type 1 cell-mediated cytotoxic immunity: a retrospective study.
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DOI：
10.1371/journal.pcbi.1003409
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发表时间：
2014-01
影响因子：
4.3
通讯作者：
Klinke DJ 2nd
中科院分区：
文献类型：
--
作者：
Klinke DJ 2nd
先天性和1型细胞介导的细胞毒性免疫功能作为维持细胞内稳态的重要细胞外控制机制。白细胞介素-12（IL-12）是一种重要的细胞因子，其将先天免疫与1型细胞介导的细胞毒性免疫联系起来。我们最近在体外观察到肿瘤源性Wnt诱导信号蛋白-1（WISP 1）发挥旁分泌作用来抑制IL 12信号传导。这项回顾性研究的目的有三个：1）确定与1型细胞介导的细胞毒性免疫相关的基因特征是否与总生存期相关，2）确定浸润性乳腺癌中WISP 1表达是否增加，3）确定与IL 12信号传导抑制一致的基因特征是否与WISP 1表达相关。与抗肿瘤免疫相关的基因的临床信息和mRNA表达从癌症基因组图谱研究的侵袭性乳腺癌分支获得。使用分层聚类确定患者队列。使用基于模型的免疫极化推断来解释与患者队列相关的免疫特征。使用反相蛋白质阵列、组织微阵列和定量流式细胞术在乳腺癌细胞系中验证所观察到的基因表达差异。我们发现1型细胞介导的细胞毒性免疫与浸润性乳腺癌患者生存率的增加相关，尤其是浸润性三阴性乳腺癌患者。浸润性乳腺癌的致癌性转化与WISP 1的增加有关。浸润性乳腺癌中的基因表达特征与WISP 1通过抑制IL 12信号传导和促进2型免疫而作为1型细胞介导的免疫的旁分泌抑制剂一致。此外，基于模型的推理有助于识别适当的免疫特征，这些免疫特征可用作遗传工程设计乳腺癌更好的临床前模型的设计约束。有效的抗肿瘤免疫与进入肿瘤微环境的免疫细胞的数量和细胞毒性活性成比例。癌症免疫治疗的最新进展源于通过抑制免疫检查点或过继性T细胞治疗来增加肿瘤浸润免疫细胞的数量。在这里，我们使用计算方法来确定肿瘤微环境中存在的限制抗肿瘤免疫效力的潜在机制。具体而言，我们发现致癌转化与肿瘤衍生的生化信号（即Wnt诱导的信号蛋白-1）的诱导有关，后者局部抑制抗肿瘤免疫。此外，我们使用基于模型的推断来证明与有效的1型细胞介导的细胞毒性免疫一致的基因特征是独立于分子病理学的总生存率的预测因子。有趣的是，三阴性乳腺癌患者在与1型细胞介导的免疫相关的队列中更丰富。由于这种免疫基因特征在目前的乳腺癌基因工程小鼠模型中不存在，因此这些结果有助于确定设计限制，以设计更好的乳腺癌临床前模型。在临床前动物模型中证明疗效是将改进的癌症免疫疗法引入临床的先决条件。
Innate and type 1 cell-mediated cytotoxic immunity function as important extracellular control mechanisms that maintain cellular homeostasis. Interleukin-12 (IL12) is an important cytokine that links innate immunity with type 1 cell-mediated cytotoxic immunity. We recently observed in vitro that tumor-derived Wnt-inducible signaling protein-1 (WISP1) exerts paracrine action to suppress IL12 signaling. The objective of this retrospective study was three fold: 1) to determine whether a gene signature associated with type 1 cell-mediated cytotoxic immunity was correlated with overall survival, 2) to determine whether WISP1 expression is increased in invasive breast cancer, and 3) to determine whether a gene signature consistent with inhibition of IL12 signaling correlates with WISP1 expression. Clinical information and mRNA expression for genes associated with anti-tumor immunity were obtained from the invasive breast cancer arm of the Cancer Genome Atlas study. Patient cohorts were identified using hierarchical clustering. The immune signatures associated with the patient cohorts were interpreted using model-based inference of immune polarization. Reverse phase protein array, tissue microarray, and quantitative flow cytometry in breast cancer cell lines were used to validate observed differences in gene expression. We found that type 1 cell-mediated cytotoxic immunity was correlated with increased survival in patients with invasive breast cancer, especially in patients with invasive triple negative breast cancer. Oncogenic transformation in invasive breast cancer was associated with an increase in WISP1. The gene expression signature in invasive breast cancer was consistent with WISP1 as a paracrine inhibitor of type 1 cell-mediated immunity through inhibiting IL12 signaling and promoting type 2 immunity. Moreover, model-based inference helped identify appropriate immune signatures that can be used as design constraints in genetically engineering better pre-clinical models of breast cancer. Effective anti-tumor immunity is proportional to the number and to the cytotoxic activity of immune cells that enter the tumor microenvironment. Recent advances in cancer immunotherapy stem from increasing the number of tumor-infiltrating immune cells by inhibiting immune checkpoints or adoptive T cell therapy. Here, we used computational methods to identify potential mechanisms present within the tumor microenvironment that limit the efficacy of anti-tumor immunity. Specifically, we found that oncogenic transformation is associated with the induction of tumor-derived biochemical cues, namely Wnt-inducible signaling protein-1, that locally suppress anti-tumor immunity. Moreover, we used model-based inference to demonstrate that a gene signature consistent with effective type 1 cell-mediated cytotoxic immunity is a predictor of overall survival independent of molecular pathology. Interestingly, patients with triple negative breast cancer were more enriched in the cohort associated with type 1 cell-mediated immunity. As this immune gene signature is not present in current genetically engineered mouse models of breast cancer, the results help identify design constraints for engineering better pre-clinical models of breast cancer. Demonstrating efficacy in pre-clinical animal models is a pre-requisite for bringing improved cancer immunotherapies into the clinic.
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影响因子：
64.8
作者：
Ellis, Matthew J.;Ding, Li;Shen, Dong;Luo, Jingqin;Suman, Vera J.;Wallis, John W.;Van Tine, Brian A.;Hoog, Jeremy;Goiffon, Reece J.;Goldstein, Theodore C.;Ng, Sam;Lin, Li;Crowder, Robert;Snider, Jacqueline;Ballman, Karla;Weber, Jason;Chen, Ken;Koboldt, Daniel C.;Kandoth, Cyriac;Schierding, William S.;McMichael, Joshua F.;Miller, Christopher A.;Lu, Charles;Harris, Christopher C.;McLellan, Michael D.;Wendl, Michael C.;DeSchryver, Katherine;Allred, D. Craig;Esserman, Laura;Unzeitig, Gary;Margenthaler, Julie;Babiera, G. V.;Marcom, P. Kelly;Guenther, J. M.;Leitch, Marilyn;Hunt, Kelly;Olson, John;Tao, Yu;Maher, Christopher A.;Fulton, Lucinda L.;Fulton, Robert S.;Harrison, Michelle;Oberkfell, Ben;Du, Feiyu;Demeter, Ryan;Vickery, Tammi L.;Elhammali, Adnan;Piwnica-Worms, Helen;McDonald, Sandra;Watson, Mark;Dooling, David J.;Ota, David;Chang, Li-Wei;Bose, Ron;Ley, Timothy J.;Piwnica-Worms, David;Stuart, Joshua M.;Wilson, Richard K.;Mardis, Elaine R.
通讯作者：
Mardis, Elaine R.
影响因子：
5.6
作者：
Chou, Jonathan;Provot, Sylvain;Werb, Zena
通讯作者：
Werb, Zena
DOI：
10.1084/jem.20021769
发表时间：
2003-02-17
期刊：
The Journal of experimental medicine
影响因子：
--
作者：
Fieschi C;Dupuis S;Catherinot E;Feinberg J;Bustamante J;Breiman A;Altare F;Baretto R;Le Deist F;Kayal S;Koch H;Richter D;Brezina M;Aksu G;Wood P;Al-Jumaah S;Raspall M;Da Silva Duarte AJ;Tuerlinckx D;Virelizier JL;Fischer A;Enright A;Bernhöft J;Cleary AM;Vermylen C;Rodriguez-Gallego C;Davies G;Blütters-Sawatzki R;Siegrist CA;Ehlayel MS;Novelli V;Haas WH;Levy J;Freihorst J;Al-Hajjar S;Nadal D;De Moraes Vasconcelos D;Jeppsson O;Kutukculer N;Frecerova K;Caragol I;Lammas D;Kumararatne DS;Abel L;Casanova JL
通讯作者：
Casanova JL
影响因子：
64.8
作者：
Greaves, Mel;Maley, Carlo C.
通讯作者：
Maley, Carlo C.
影响因子：
7.3
作者：
Ciampricotti, Metamia;Vrijland, Kim;de Visser, Karin E.
通讯作者：
de Visser, Karin E.