Recurrent somatic mutations as predictors of immunotherapy response.
Recurrent somatic mutations as predictors of immunotherapy response.
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DOI：
10.1038/s41467-022-31055-3
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发表时间：
2022-07-08
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
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作者：
免疫检查点阻断（ICB）已经改变了转移性癌症的治疗方法，但受到不同反应率的阻碍。一个关键的未满足需求是识别预测治疗反应的生物标志物。为了解决这个问题，我们分析了六个具有匹配疾病结果的全外显子组测序队列，以确定预测 ICB 反应的基因和途径。为了提高检测能力，我们重点关注在表观遗传、复制时间和基于序列的协变量校正后发生显着突变的基因和通路。利用这项技术，我们确定了几个基因（BCLAF1、KRAS、BRAF 和 TP53）和通路（MAPK 信号传导、p53 相关和免疫调节）作为 ICB 反应的预测因子，并开发了癌症免疫治疗反应 CLassifiEr (CIRCLE)。与单独的肿瘤突变负荷相比，CIRCLE 可以更好地预测 ICB 反应，敏感性提高 10.5%，特异性提高 11%。我们预计，CIRCLE 以及更广泛地对经常突变的癌症基因的分析将为更好的癌症免疫治疗预后工具铺平道路。用于癌症免疫治疗的遗传生物标志物很少。在这里，作者识别了与治疗反应相关的反复突变基因和通路，并使用肿瘤全外显子组测序和临床特征开发了一个分类器。
Immune checkpoint blockade (ICB) has transformed the treatment of metastatic cancer but is hindered by variable response rates. A key unmet need is the identification of biomarkers that predict treatment response. To address this, we analyzed six whole exome sequencing cohorts with matched disease outcomes to identify genes and pathways predictive of ICB response. To increase detection power, we focus on genes and pathways that are significantly mutated following correction for epigenetic, replication timing, and sequence-based covariates. Using this technique, we identify several genes (BCLAF1, KRAS, BRAF, and TP53) and pathways (MAPK signaling, p53 associated, and immunomodulatory) as predictors of ICB response and develop the Cancer Immunotherapy Response CLassifiEr (CIRCLE). Compared to tumor mutational burden alone, CIRCLE led to superior prediction of ICB response with a 10.5% increase in sensitivity and a 11% increase in specificity. We envision that CIRCLE and more broadly the analysis of recurrently mutated cancer genes will pave the way for better prognostic tools for cancer immunotherapy. Few genetic biomarkers are known for cancer immunotherapy. Here the authors identify recurrently-mutated genes and pathways associated with treatment response and develop a classifier using tumour whole exome sequencing and clinical features.
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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
影响因子：
50.3
作者：
Hellmann MD;Callahan MK;Awad MM;Calvo E;Ascierto PA;Atmaca A;Rizvi NA;Hirsch FR;Selvaggi G;Szustakowski JD;Sasson A;Golhar R;Vitazka P;Chang H;Geese WJ;Antonia SJ
通讯作者：
Antonia SJ
影响因子：
3.5
作者：
Degenhardt, Frauke;Niklowitz, Petra;Onur, Simone
通讯作者：
Onur, Simone
影响因子：
1.2
作者：
Cingolani, Pablo;Platts, Adrian;Ruden, Douglas M.
通讯作者：
Ruden, Douglas M.
插入和缺失针对人类癌症中的谱系定义基因。
影响因子：
64.5
作者：
Imielinski M;Guo G;Meyerson M
通讯作者：
Meyerson M