Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.
Ratio of the interferon-γ signature to the immunosuppression signature predicts anti-PD-1 therapy response in melanoma.
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干扰素-γ 特征与免疫抑制特征的比率可预测黑色素瘤中的抗 PD-1 治疗反应
DOI：
10.1038/s41525-021-00169-w
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发表时间：
2021-02-04
影响因子：
5.3
通讯作者：
Kong Y
中科院分区：
文献类型：
--
作者：
Cui C;Xu C;Yang W;Chi Z;Sheng X;Si L;Xie Y;Yu J;Wang S;Yu R;Guo J;Kong Y
免疫检查点抑制剂(ICI)治疗在许多患者中产生了临床益处。然而，仍然需要更好的ICI预测生物标志物来帮助个体患者与最有可能受益的治疗相匹配。现有的基于基因表达谱(GEP)的ICI生物标志物主要集中在测量T细胞炎症的肿瘤微环境，这对ICI的反应有积极作用。在这里，我们通过分析来自三个公开可用的黑色素瘤数据集的联合发现队列(n= 120)的rna测序数据来识别免疫抑制特征(Ims)。与来自新生成的内部验证队列(n= 55)的9个已发表的GEP签名的集合、用抗PD-1(n= 54)和抗CTLA-4(n= 42)治疗的转移性黑色素瘤的3个已发表的数据集以及用抗PD-1(n= 45)治疗的胃癌患者相比，使用已建立的干扰素-CTLA签名和免疫球蛋白的比率一致地更好地预测ICI治疗的结果，表明免疫球蛋白作为免疫治疗的现有GEP签名的补充的预测生物标记物的潜在用途。
Immune checkpoint inhibitor (ICI) treatments produce clinical benefit in many patients. However, better pretreatment predictive biomarkers for ICI are still needed to help match individual patients to the treatment most likely to be of benefit. Existing gene expression profiling (GEP)-based biomarkers for ICI are primarily focused on measuring a T cell-inflamed tumor microenvironment that contributes positively to the response to ICI. Here, we identified an immunosuppression signature (IMS) through analyzing RNA sequencing data from a combined discovery cohort (n= 120) consisting of three publicly available melanoma datasets. Using the ratio of an established IFN-γsignature and IMS led to consistently better prediction of the ICI therapy outcome compared to a collection of nine published GEP signatures from the literature on a newly generated internal validation cohort (n= 55) and three published datasets of metastatic melanoma treated with anti-PD-1 (n= 54) and anti-CTLA-4 (n= 42), as well as in patients with gastric cancer treated with anti-PD-1 (n= 45), demonstrating the potential utility of IMS as a predictive biomarker that complements existing GEP signatures for immunotherapy.
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DOI：
10.1056/nejmoa1003466
发表时间：
2010-08-19
期刊：
The New England journal of medicine
影响因子：
--
作者：
Hodi FS;O'Day SJ;McDermott DF;Weber RW;Sosman JA;Haanen JB;Gonzalez R;Robert C;Schadendorf D;Hassel JC;Akerley W;van den Eertwegh AJ;Lutzky J;Lorigan P;Vaubel JM;Linette GP;Hogg D;Ottensmeier CH;Lebbé C;Peschel C;Quirt I;Clark JI;Wolchok JD;Weber JS;Tian J;Yellin MJ;Nichol GM;Hoos A;Urba WJ
通讯作者：
Urba WJ
影响因子：
2.7
作者：
Dheda, K;Huggett, JF;Zumla, A
通讯作者：
Zumla, A
DOI：
10.1073/pnas.1320318110
发表时间：
2013-12-10
影响因子：
11.1
作者：
Feig, Christine;Jones, James O.;Fearon, Douglas T.
通讯作者：
Fearon, Douglas T.
影响因子：
50.3
作者：
Costa, Ana;Kieffer, Yann;Mechta-Grigoriou, Fatima
通讯作者：
Mechta-Grigoriou, Fatima
影响因子：
82.9
作者：
Auslander N;Zhang G;Lee JS;Frederick DT;Miao B;Moll T;Tian T;Wei Z;Madan S;Sullivan RJ;Boland G;Flaherty K;Herlyn M;Ruppin E
通讯作者：
Ruppin E