Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung Cancer.
Development of an Immune-Pathology Informed Radiomics Model for Non-Small Cell Lung Cancer.
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DOI：
10.1038/s41598-018-20471-5
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发表时间：
2018-01-31
影响因子：
4.6
通讯作者：
Koay EJ
中科院分区：
文献类型：
--
作者：
Tang C;Hobbs B;Amer A;Li X;Behrens C;Canales JR;Cuentas EP;Villalobos P;Fried D;Chang JY;Hong DS;Welsh JW;Sepesi B;Court L;Wistuba II;Koay EJ
随着免疫治疗剂的使用越来越多，用于识别应答者和无应答者的预处理策略对于适当的治疗分配是有用的。我们假设NSCLC的局部免疫微环境与患者结局相关，并且这些局部免疫特征表现出可通过定量成像指标识别的独特放射学特征。我们收集了两组接受明确手术切除治疗的NSCLC患者，并从治疗前CT成像中提取定量参数。然后利用免疫组织化学和自动细胞计数对切除的原发性肿瘤的肿瘤PDL 1表达百分比和肿瘤浸润淋巴细胞的密度（通过CD 3计数）进行定量。将这些治疗前放射组学参数与肿瘤免疫参数相关联，我们开发了免疫病理学知情模型（IPIM），该模型利用4个放射组学特征将患者分为4个聚类（指定为A-D）。IPIM指定与两种训练中的总生存率显著相关，（5年OS：聚类A-D分别为61%、41%、50%和91%，P = 0.04）和验证（5年OS：A-D组分别为55%、72%、75%和86%，P = 0.002）队列和免疫病理学（均P < 0.05）。具体而言，我们确定了一个有利的结果组，其特征是低CT强度和高异质性，表现出低PDL 1和高CD 3浸润，提示有利的免疫激活状态。我们基于免疫微环境和患者结局开发了NSCLC放射组学特征。该手稿演示了独立队列中的模型创建和验证。
With increasing use of immunotherapy agents, pretreatment strategies for identifying responders and non-responders is useful for appropriate treatment assignment. We hypothesize that the local immune micro-environment of NSCLC is associated with patient outcomes and that these local immune features exhibit distinct radiologic characteristics discernible by quantitative imaging metrics. We assembled two cohorts of NSCLC patients treated with definitive surgical resection and extracted quantitative parameters from pretreatment CT imaging. The excised primary tumors were then quantified for percent tumor PDL1 expression and density of tumor-infiltrating lymphocyte (via CD3 count) utilizing immunohistochemistry and automated cell counting. Associating these pretreatment radiomics parameters with tumor immune parameters, we developed an immune pathology-informed model (IPIM) that separated patients into 4 clusters (designated A-D) utilizing 4 radiomics features. The IPIM designation was significantly associated with overall survival in both training (5 year OS: 61%, 41%, 50%, and 91%, for clusters A-D, respectively, P = 0.04) and validation (5 year OS: 55%, 72%, 75%, and 86%, for clusters A-D, respectively, P = 0.002) cohorts and immune pathology (all P < 0.05). Specifically, we identified a favorable outcome group characterized by low CT intensity and high heterogeneity that exhibited low PDL1 and high CD3 infiltration, suggestive of a favorable immune activated state. We have developed a NSCLC radiomics signature based on the immune micro-environment and patient outcomes. This manuscript demonstrates model creation and validation in independent cohorts.
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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：
3.7
作者：
Grove O;Berglund AE;Schabath MB;Aerts HJ;Dekker A;Wang H;Velazquez ER;Lambin P;Gu Y;Balagurunathan Y;Eikman E;Gatenby RA;Eschrich S;Gillies RJ
通讯作者：
Gillies RJ
DOI：
10.1097/jto.0b013e318282def7
发表时间：
2013-03
期刊：
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
影响因子：
--
作者：
Guo C;Shao R;Correa AM;Behrens C;Johnson FM;Raso MG;Prudkin L;Solis LM;Nunez MI;Fang B;Roth JA;Wistuba II;Swisher SG;Lin T;Pataer A
通讯作者：
Pataer A
DOI：
10.1007/s00259-011-1934-6
发表时间：
2012-01-01
影响因子：
9.1
作者：
Liao, Shengri;Penney, Bill C.;Pu, Yonglin
通讯作者：
Pu, Yonglin
影响因子：
28.2
作者：
Kim ES;Herbst RS;Wistuba II;Lee JJ;Blumenschein GR Jr;Tsao A;Stewart DJ;Hicks ME;Erasmus J Jr;Gupta S;Alden CM;Liu S;Tang X;Khuri FR;Tran HT;Johnson BE;Heymach JV;Mao L;Fossella F;Kies MS;Papadimitrakopoulou V;Davis SE;Lippman SM;Hong WK
通讯作者：
Hong WK