Integrated genomic analysis identifies a genetic mutation model predicting response to immune checkpoint inhibitors in melanoma.
Integrated genomic analysis identifies a genetic mutation model predicting response to immune checkpoint inhibitors in melanoma.
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综合基因组分析确定了预测黑色素瘤免疫检查点抑制剂反应的基因突变模型。
DOI：
10.1002/cam4.3481
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发表时间：
2020-11
期刊：
影响因子：
4
通讯作者：
Teng L
中科院分区：
文献类型：
--
作者：
Jiang J;Ding Y;Wu M;Chen Y;Lyu X;Lu J;Wang H;Teng L
已经开发了几种生物标志物，例如肿瘤突变负荷（TMB）、新抗原负荷（NAL）、程序性细胞死亡受体1配体（PD-L1）表达和乳酸脱氢酶（LDH），用于预测对免疫检查点抑制剂（ICI）的反应黑色素瘤。然而，由于其临界值不明确、测试平台的一致性差、预测可靠性差等局限性，限制了其在临床上的广泛应用。为了鉴定临床上可操作的生物标志物并探索有效的预测策略，我们基于来自先前研究的全外显子组测序数据，开发了一种名为免疫治疗评分（ITS）的遗传突变模型，用于预测黑色素瘤对ICI治疗的反应。我们在三个独立队列和荟萃队列中观察到，高ITS患者的持久临床获益和生存结局优于低ITS患者。值得注意的是，ITS的预测能力比TMB的更稳健。值得注意的是，ITS不仅是ICIs治疗的独立预测因子，而且与TMB或LDH组合比任何单一生物标志物更好地预测对ICIs的反应。此外，高ITS患者具有免疫治疗敏感性特征，包括高TMB和NAL、紫外线损伤、DNA损伤修复途径受损、细胞周期信号传导阻滞以及NF 1和SERPINB3/4频繁突变。总的来说，这些发现值得在未来进行前瞻性研究，并可能有助于指导黑色素瘤患者的ICIs治疗的临床决策。本研究提供的证据表明，基因突变模型（命名为ITS）确定了一个黑色素瘤人群具有多种遗传模式的敏感性，ICI，谁可能受益于ICI治疗。来自三个独立队列的初步数据强烈表明，高ITS黑色素瘤患者的ICI治疗效果更好。值得注意的是，与任何单一生物标志物相比，ITS和TMB或LDH的组合策略显示出更好的预测功效。
Several biomarkers such as tumor mutation burden (TMB), neoantigen load (NAL), programmed cell‐death receptor 1 ligand (PD‐L1) expression, and lactate dehydrogenase (LDH) have been developed for predicting response to immune checkpoint inhibitors (ICIs) in melanoma. However, some limitations including the undefined cut‐off value, poor uniformity of test platform, and weak reliability of prediction have restricted the broad application in clinical practice. In order to identify a clinically actionable biomarker and explore an effective strategy for prediction, we developed a genetic mutation model named as immunotherapy score (ITS) for predicting response to ICIs therapy in melanoma, based on whole‐exome sequencing data from previous studies. We observed that patients with high ITS had better durable clinical benefit and survival outcomes than patients with low ITS in three independent cohorts, as well as in the meta‐cohort. Notably, the prediction capability of ITS was more robust than that of TMB. Remarkably, ITS was not only an independent predictor of ICIs therapy, but also combined with TMB or LDH to better predict response to ICIs than any single biomarker. Moreover, patients with high ITS harbored the immunotherapy‐sensitive characteristics including high TMB and NAL, ultraviolet light damage, impaired DNA damage repair pathway, arrested cell cycle signaling, and frequent mutations in NF1 and SERPINB3/4. Overall, these findings deserve prospective investigation in the future and may help guide clinical decisions on ICIs therapy for patients with melanoma. This study provided evidences that the genetic mutation model (named as ITS) identified a melanoma population with multiple genetic patterns of sensitivity to ICIs, who might potentially benefit from ICIs therapy. Preliminary data from three independent cohorts strongly suggested better treatment outcomes from ICIs therapy in melanoma patients with high ITS. Remarkably, the combination strategy of ITS and TMB or LDH showed better prediction efficacy compared with any single biomarker.
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影响因子：
5.8
作者：
Gu, Zuguang;Eils, Roland;Schlesner, Matthias
通讯作者：
Schlesner, Matthias
影响因子：
10.1
作者：
Johnson DB;Frampton GM;Rioth MJ;Yusko E;Xu Y;Guo X;Ennis RC;Fabrizio D;Chalmers ZR;Greenbowe J;Ali SM;Balasubramanian S;Sun JX;He Y;Frederick DT;Puzanov I;Balko JM;Cates JM;Ross JS;Sanders C;Robins H;Shyr Y;Miller VA;Stephens PJ;Sullivan RJ;Sosman JA;Lovly CM
通讯作者：
Lovly CM
DOI：
10.1158/1078-0432.ccr-15-1125
发表时间：
2016-03-15
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
--
作者：
Loi S;Dushyanthen S;Beavis PA;Salgado R;Denkert C;Savas P;Combs S;Rimm DL;Giltnane JM;Estrada MV;Sánchez V;Sanders ME;Cook RS;Pilkinton MA;Mallal SA;Wang K;Miller VA;Stephens PJ;Yelensky R;Doimi FD;Gómez H;Ryzhov SV;Darcy PK;Arteaga CL;Balko JM
通讯作者：
Balko JM
影响因子：
8.4
作者：
Eisenhauer, E. A.;Therasse, P.;Verweij, J.
通讯作者：
Verweij, J.
影响因子：
30.8
作者：
Krauthammer, Michael;Kong, Yong;Ha, Byung Hak;Evans, Perry;Bacchiocchi, Antonella;McCusker, James P.;Cheng, Elaine;Davis, Matthew J.;Goh, Gerald;Choi, Murim;Ariyan, Stephan;Narayan, Deepak;Dutton-Regester, Ken;Capatana, Ana;Holman, Edna C.;Bosenberg, Marcus;Sznol, Mario;Kluger, Harriet M.;Brash, Douglas E.;Stern, David F.;Materin, Miguel A.;Lo, Roger S.;Mane, Shrikant;Ma, Shuangge;Kidd, Kenneth K.;Hayward, Nicholas K.;Lifton, Richard P.;Schlessinger, Joseph;Boggon, Titus J.;Halaban, Ruth
通讯作者：
Halaban, Ruth