The Radiosensitivity Index Gene Signature Identifies Distinct Tumor Immune Microenvironment Characteristics Associated With Susceptibility to Radiation Therapy.
The Radiosensitivity Index Gene Signature Identifies Distinct Tumor Immune Microenvironment Characteristics Associated With Susceptibility to Radiation Therapy.
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放射敏感性指数基因特征描述与放射治疗敏感性相关的独特肿瘤免疫微环境特征。
DOI：
10.1016/j.ijrobp.2022.03.006
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发表时间：
2022-07-01
影响因子：
7
通讯作者：
Torres-Roca, Javier F.
中科院分区：
文献类型：
--
作者：
Grass, G. Daniel;Alfonso, Juan C. L.;Welsh, Eric;Ahmed, Kamran A.;Teer, Jamie K.;Pilon-Thomas, Shari;Harrison, Louis B.;Cleveland, John L.;Mule, James J.;Eschrich, Steven A.;Enderling, Heiko;Torres-Roca, Javier F.
放射治疗（RT）是癌症治疗的支柱，越来越多的证据表明与免疫反应组分协同作用的潜力。然而，很少有数据描述肿瘤免疫结构与RT敏感性的关系。为了应对这一挑战，我们采用辐射敏感性指数（RSI）基因特征来估计> 10，000个原发性肿瘤的RT敏感性，并表征其与RSI相关的免疫微环境。我们分析了前瞻性组织收集方案中10，469例原发性肿瘤（31种类型）的基因表达谱。通过RSI估计每个肿瘤的RT敏感性，并表征各自的分布。采用差异表达基因（DEG）结合单样本基因集富集分析（ssGSEA）评价RSI测量的肿瘤生物学。评估免疫调节分子表达的差异，并使用去卷积算法估计与RSI相关的免疫细胞浸润。一个肿瘤子集（n= 2，368）进行DNA测序，以表征突变频率。我们在各种肿瘤类型内和之间鉴定了广泛的RSI值，其中几种显示出非单峰分布（例如结肠、肾、肺、前列腺、食管、胰腺和PAM 50乳腺亚型; p <0.05）。在所有肿瘤类型中，在肿瘤类型特异性中位数处对RSI进行分层，识别出7，148个DEG，其中146个在方向上协调。网络拓扑分析表明RSI测量了协调的STAT 1，IRF 1和CCL 4/MIP-1β转录网络。具有估计的对RT的高敏感性的肿瘤表现出干扰素相关信号传导途径和免疫细胞浸润（例如，CD 8 + T细胞、活化的自然杀伤细胞、M1-巨噬细胞; q < 0.05）的明显富集，这是在各种免疫调节分子的不同表达模式的背景下。该分析描述了与RSI基因表达特征相关的患者肿瘤的免疫微环境。
Radiotherapy (RT) is a mainstay of cancer care and accumulating evidence suggests the potential for synergism with components of the immune response. However, little data describes the tumor immune contexture in relation to RT-sensitivity. To address this challenge, we employed the radiation sensitivity index (RSI) gene signature to estimate the RT-sensitivity of >10,000 primary tumors and characterized their immune microenvironments in relation to the RSI. We analyzed gene expression profiles of 10,469 primary tumors (31 types) within a prospective tissue collection protocol. The RT-sensitivity of each tumor was estimated by the RSI and respective distributions were characterized. The tumor biology measured by the RSI was evaluated by differentially expressed genes (DEGs) combined with single sample gene set enrichment analysis (ssGSEA). Differences in the expression of immune regulatory molecules were assessed and deconvolution algorithms were used to estimate immune cell infiltrates in relation to the RSI. A subset (n=2,368) of tumors underwent DNA sequencing for mutational frequency characterization. We identified a wide range of RSI values within and across various tumor types, with several demonstrating non-unimodal distributions (e.g. colon, renal, lung, prostate, esophagus, pancreas and PAM50 breast subtypes; p <0.05). Across all tumors types, stratifying RSI at a tumor type-specific median, identified 7,148 DEGs, of which 146 were coordinate in direction. Network topology analysis demonstrates RSI measures a coordinated STAT1, IRF1, and CCL4/MIP-1β transcriptional network. Tumors with an estimated high sensitivity to RT demonstrated distinct enrichment of interferon-associated signaling pathways and immune cell infiltrates (e.g. CD8+ T cells, activated natural killer cells, M1-macrophages; q < 0.05), which was in the context of diverse expression patterns of various immunoregulatory molecules. This analysis describes the immune microenvironments of patient tumors in relation to the RSI gene expression signature.
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影响因子：
5.8
作者：
Gu, Zuguang;Eils, Roland;Schlesner, Matthias
通讯作者：
Schlesner, Matthias
DOI：
10.1097/ppo.0b013e318238216e
发表时间：
2011-11
期刊：
Cancer journal (Sudbury, Mass.)
影响因子：
--
作者：
Fenstermacher DA;Wenham RM;Rollison DE;Dalton WS
通讯作者：
Dalton WS
影响因子：
64.5
作者：
Benci JL;Xu B;Qiu Y;Wu TJ;Dada H;Twyman-Saint Victor C;Cucolo L;Lee DSM;Pauken KE;Huang AC;Gangadhar TC;Amaravadi RK;Schuchter LM;Feldman MD;Ishwaran H;Vonderheide RH;Maity A;Wherry EJ;Minn AJ
通讯作者：
Minn AJ
影响因子：
11.2
作者：
Burnette BC;Liang H;Lee Y;Chlewicki L;Khodarev NN;Weichselbaum RR;Fu YX;Auh SL
通讯作者：
Auh SL
放射敏性指数是用于放射疗法和免疫疗法的潜在生物标志物。
影响因子：
5.3
作者：
Dai YH;Wang YF;Shen PC;Lo CH;Yang JF;Lin CS;Chao HL;Huang WY
通讯作者：
Huang WY