Novel genomic signature predictive of response to immune checkpoint blockade: A pan-cancer analysis from project Genomics Evidence Neo-plasia Information Exchange (GENIE),Cancer Genetics

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Novel genomic signature predictive of response to immune checkpoint blockade: A pan-cancer analysis from project Genomics Evidence Neo-plasia Information Exchange (GENIE)
Cancer Genetics ( IF 1.4 ) Pub Date : 2021-08-28 , DOI: 10.1016/j.cancergen.2021.08.004
Nishwant Swami ₁ , William L Hwang ₂ , Jimmy A Guo ₃ , Hannah Hoffman ₄ , Matthew C Abramowitz ₅ , Ziad Elbakouny ₆ , Himisha Beltran ₆ , Fallon Chipidza ₆ , Toni Choueiri ₆ , Alan Dal Pra ₅ , Franklin Huang ₇ , Salma Kaochar ₈ , Philip Kantoff ₉ , Daniel W Kim ₆ , Amar U Kishan ₁₀ , Erin Kobetz ₅ , Catherine Marinac ₆ , Lorelei A Mucci ₁₁ , Vinayak Muralidhar ₆ , Alan Pollack ₅ , Nina N Sanford ₁₂ , Edward M Schaeffer ₁₃ , Daniel E Spratt ₁₄ , Shuang G Zhao ₁₄ , Timothy R Rebbeck ₁₅ , Paul L Nguyen ₆ , Felix Y Feng ₇ , Brandon A Mahal ₅ , Mohammed Alshalalfa ₁₆

Affiliation

University of Massachusetts Medical School, Worcester, MA, USA.
Massachusetts General Hospital, Boston, MA, USA; Broad Institute, Cambridge MA, USA.
Massachusetts General Hospital, Boston, MA, USA; Broad Institute, Cambridge MA, USA; University of California at San Francisco, San Francisco, CA, USA.
Massachusetts General Hospital, Boston, MA, USA.
University of Miami Miller School of Medicine, Sylvester Comprehensive Cancer Center, USA.
Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA, USA.
University of California at San Francisco, San Francisco, CA, USA.
Baylor College of Medicine, Houston, TX, USA.
Memorial Sloan Kettering Cancer Center, New York, NY, USA.
University of California Los Angeles, Los Angeles, CA, USA.
Harvard T. H. Chan School of Public Health, Boston, MA, USA.
University of Texas Southwestern Medical Center, Dallas, TX, USA.
Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
University of Michigan, Ann Arbor, MI, USA.
Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA, USA; Harvard T. H. Chan School of Public Health, Boston, MA, USA.
University of California at San Francisco, San Francisco, CA, USA; Dana-Farber Cancer Institute and Brigham and Women's Hospital, Boston, MA, USA.

Background: High tumor mutation burden (TMB) and total mutation count (TMC) can be predictive of better response to immune checkpoint blockade (ICB). Nevertheless, TMB and TMC are limited by variation across cancers and inconsistent definitions due to different profiling methods (targeted vs whole genome sequencing). Our objective was to identify genomic alterations (GAs) associated with ICB response and builds a novel genomic signature predictive of ICB response, independent of TMB/TMC.

Methods: This was a pan-cancer next generation sequencing (NGS)-association study using January 2014-May 2016 data from AACR Project Genomics Evidence Neo-plasia Information Exchange (GENIE). Participants included 6619 patients with metastatic or un-resectable cancer across 9 cancer types (including 1572 ICB-treated patients). GA data was collected using next-generation sequencing (NGS) assays and downloaded from cbioportal.org. Predictive analyses for ICB response were performed to develop the signature (ImmGA).

Results: GAs in 16 genes were associated with improved OS in ICB-treated patients (p < 0.005). 13 GAs were associated with an OS benefit in ICB-treated patients (P_interaction < 0.05); these genes composed the ImmGA signature. High ImmGA score (≥2 alterations out of 13 predictive GAs) was associated with better OS in ICB-treated patients (AHR:0.67, 95%CI [0.6–0.75], p = 1.4e⁻¹²), even after accounting for TMC (P_interaction = 8e⁻¹⁶). High ImmGA was associated with better OS in ICB-treated patients across most cancers and across different ICB treatment modalities.

Conclusion: A novel signature predictive of ICB response (ImmGA) was developed from 13 GAs. Further investigation of the utility of ImmGA for treatment and trial selection is warranted.

中文翻译：

预测免疫检查点阻断反应的新基因组特征：来自基因组学证据肿瘤信息交换 (GENIE) 项目的泛癌分析

背景：高肿瘤突变负荷 (TMB) 和总突变计数 (TMC) 可以预测对免疫检查点阻断 (ICB) 的更好反应。然而，由于不同的分析方法（靶向与全基因组测序），TMB 和 TMC 受到癌症之间的差异和不一致的定义的限制。我们的目标是确定与 ICB 反应相关的基因组改变 (GA)，并建立一个预测 ICB 反应的新基因组特征，独立于 TMB/TMC。

方法：这是一项泛癌下一代测序 (NGS) 关联研究，使用来自 AACR 项目基因组学证据肿瘤信息交换 (GENIE) 的 2014 年 1 月至 2016 年 5 月的数据。参与者包括 9 种癌症类型的 6619 名转移性或不可切除的癌症患者（包括 1572 名接受 ICB 治疗的患者）。GA 数据使用新一代测序 (NGS) 分析收集并从 cbioportal.org 下载。对 ICB 反应进行预测分析以开发特征 (ImmGA)。

结果：16 个基因中的 GA 与 ICB 治疗患者的 OS 改善相关（p < 0.005）。13 种 GA 与 ICB 治疗患者的 OS 获益相关（P_交互作用 < 0.05）；这些基因组成了 ImmGA 特征。高 ImmGA 评分（13 个预测性 GA 中的≥2 个改变）与 ICB 治疗患者的更好 OS 相关（AHR：0.67，95%CI [0.6–0.75]，p = 1.4e ^-12），即使在考虑 TMC 之后（P_相互作用 = 8e ^-16）。在大多数癌症和不同的 ICB 治疗方式中，高 ImmGA 与 ICB 治疗的患者更好的 OS 相关。

结论：从 13 种 GA 中开发出一种新的 ICB 反应预测特征 (ImmGA)。有必要进一步研究 ImmGA 在治疗和试验选择方面的效用。

更新日期：2021-09-20

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