A Ferroptosis-Related Gene Prognostic Index to Predict Temozolomide Sensitivity and Immune Checkpoint Inhibitor Response for Glioma.
A Ferroptosis-Related Gene Prognostic Index to Predict Temozolomide Sensitivity and Immune Checkpoint Inhibitor Response for Glioma.
复制标题
铁死亡相关基因预后指数可预测神经胶质瘤的替莫唑胺敏感性和免疫检查点抑制剂反应
DOI：
10.3389/fcell.2021.812422
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发表时间：
2021
影响因子：
5.5
通讯作者：
Zhang X
中科院分区：
文献类型：
--
作者：
Cai Y;Liang X;Zhan Z;Zeng Y;Lin J;Xu A;Xue S;Xu W;Chai P;Mao Y;Song Z;Han L;Xiao J;Song Y;Zhang X
背景：胶质瘤是一种高致死性的脑肿瘤。尽管采用手术、放疗、化疗和免疫治疗等多种方式治疗，胶质瘤预后仍然很差。铁凋亡是一种重要的肿瘤抑制机制，已被证明是有效的抗癌治疗。然而，铁凋亡对胶质瘤患者的临床预后、化疗和免疫检查点抑制剂（ICI）治疗的影响仍需阐明。 方法：基于癌症基因组图谱（TCGA）神经胶质瘤数据集（n = 663），共识聚类揭示了两种不同的铁凋亡相关亚型。随后，采用加权基因共表达网络分析（WGCNA）和“stepAIC”算法构建了铁凋亡相关基因预后指数（FRGPI），并在中国胶质瘤基因组图谱（CGGA）数据集（n = 404）上进行了验证。随后，分析临床、分子和免疫特征与FRGPI之间的相关性。接下来，分别使用“pRRophetic”和“TIDE”算法预测神经胶质瘤的替莫唑胺敏感性和ICI反应。最后，使用基于FRGPI的连接性图谱数据库定义候选小分子药物。 结果：建立了基于HMOX 1、TFRC、JUN和SOCS 1基因的FRGPI。FRGPI的分布在不同的铁中毒相关亚型之间差异显着。高FRGPI患者的总体预后比低FRGPI患者差，与CGGA数据集的结果一致。最终结果显示，高FRGPI的特征在于更具侵袭性的表型、高PD-L1表达、高肿瘤突变负荷评分和增强的替莫唑胺敏感性;低FRGPI与侵袭性较低的表型、高微卫星不稳定性评分和对免疫检查点阻断的更强反应相关。此外，记忆静息CD 4 + T细胞、调节性T细胞、M1巨噬细胞、M2巨噬细胞和中性粒细胞的浸润与FRGPI呈正相关。相反，血浆B细胞和初始CD 4 + T细胞呈负相关。共鉴定了15种潜在的小分子化合物（如depactin、毒扁豆碱和非那西丁）。 结论：FRGPI是预测胶质瘤患者预后、免疫特性、替莫唑胺敏感性和ICI反应的一个有前途的基因组。
Background: Gliomas are highly lethal brain tumors. Despite multimodality therapy with surgery, radiotherapy, chemotherapy, and immunotherapy, glioma prognosis remains poor. Ferroptosis is a crucial tumor suppressor mechanism that has been proven to be effective in anticancer therapy. However, the implications of ferroptosis on the clinical prognosis, chemotherapy, and immune checkpoint inhibitor (ICI) therapy for patients with glioma still need elucidation. Methods: Consensus clustering revealed two distinct ferroptosis-related subtypes based on the Cancer Genome Atlas (TCGA) glioma dataset (n = 663). Subsequently, the ferroptosis-related gene prognostic index (FRGPI) was constructed by weighted gene co-expression network analysis (WGCNA) and “stepAIC” algorithms and validated with the Chinese Glioma Genome Atlas (CGGA) dataset (n = 404). Subsequently, the correlation among clinical, molecular, and immune features and FRGPI was analyzed. Next, the temozolomide sensitivity and ICI response for glioma were predicted using the “pRRophetic” and “TIDE” algorithms, respectively. Finally, candidate small molecular drugs were defined using the connectivity map database based on FRGPI. Results: The FRGPI was established based on the HMOX1, TFRC, JUN, and SOCS1 genes. The distribution of FRGPI varied significantly among the different ferroptosis-related subtypes. Patients with high FRGPI had a worse overall prognosis than patients with low FRGPI, consistent with the results in the CGGA dataset. The final results showed that high FRGPI was characterized by more aggressive phenotypes, high PD-L1 expression, high tumor mutational burden score, and enhanced temozolomide sensitivity; low FRGPI was associated with less aggressive phenotypes, high microsatellite instability score, and stronger response to immune checkpoint blockade. In addition, the infiltration of memory resting CD4+ T cells, regulatory T cells, M1 macrophages, M2 macrophages, and neutrophils was positively correlated with FRGPI. In contrast, plasma B cells and naïve CD4+ T cells were negatively correlated. A total of 15 potential small molecule compounds (such as depactin, physostigmine, and phenacetin) were identified. Conclusion: FRGPI is a promising gene panel for predicting the prognosis, immune characteristics, temozolomide sensitivity, and ICI response in patients with glioma.
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影响因子：
9.8
作者：
Bhattacharya S;Dunn P;Thomas CG;Smith B;Schaefer H;Chen J;Hu Z;Zalocusky KA;Shankar RD;Shen-Orr SS;Thomson E;Wiser J;Butte AJ
通讯作者：
Butte AJ
影响因子：
4.6
作者：
Bonneville R;Krook MA;Kautto EA;Miya J;Wing MR;Chen HZ;Reeser JW;Yu L;Roychowdhury S
通讯作者：
Roychowdhury S
影响因子：
15.9
作者：
Anh Nhat Tran;Walker, Kiera;Hjelmeland, Anita B.
通讯作者：
Hjelmeland, Anita B.
影响因子：
158.5
作者：
Hegi, ME;Diserens, A;Stupp, R
通讯作者：
Stupp, R
影响因子：
3.2
作者：
Donson, Andrew M.;Addo-Yobo, Steven O.;Foreman, Nicholas K.
通讯作者：
Foreman, Nicholas K.