DataSheet_1_The CXCL Family Contributes to Immunosuppressive Microenvironment in Gliomas and Assists in Gliomas Chemotherapy.pdf

Gliomas are a type of malignant central nervous system tumor with poor prognosis. Molecular biomarkers of gliomas can predict glioma patient’s clinical outcome, but their limitations are also emerging. C-X-C motif chemokine ligand family plays a critical role in shaping tumor immune landscape and modulating tumor progression, but its role in gliomas is elusive. In this work, samples of TCGA were treated as the training cohort, and as for validation cohort, two CGGA datasets, four datasets from GEO database, and our own clinical samples were enrolled. Consensus clustering analysis was first introduced to classify samples based on CXCL expression profile, and the support vector machine was applied to construct the cluster model in validation cohort based on training cohort. Next, the elastic net analysis was applied to calculate the risk score of each sample based on CXCL expression. High-risk samples associated with more malignant clinical features, worse survival outcome, and more complicated immune landscape than low-risk samples. Besides, higher immune checkpoint gene expression was also noticed in high-risk samples, suggesting CXCL may participate in tumor evasion from immune surveillance. Notably, high-risk samples also manifested higher chemotherapy resistance than low-risk samples. Therefore, we predicted potential compounds that target high-risk samples. Two novel drugs, LCL-161 and ADZ5582, were firstly identified as gliomas’ potential compounds, and five compounds from PubChem database were filtered out. Taken together, we constructed a prognostic model based on CXCL expression, and predicted that CXCL may affect tumor progression by modulating tumor immune landscape and tumor immune escape. Novel potential compounds were also proposed, which may improve malignant glioma prognosis.

胶质瘤(Gliomas)是一类预后不良的恶性中枢神经系统肿瘤。胶质瘤的分子生物标志物可用于预测患者的临床结局，但其局限性也逐渐显现。C-X-C基序趋化因子配体(C-X-C motif chemokine ligand, CXCL)家族在塑造肿瘤免疫微环境、调控肿瘤进展中发挥关键作用，但其在胶质瘤中的作用尚不清楚。本研究以癌症基因组图谱(TCGA)的样本作为训练集，验证集则纳入两份中国胶质瘤基因组图谱(CGGA)数据集、四份来自基因表达综合数据库(GEO)的数据集以及本课题组的临床样本。本研究首先采用共识聚类分析，基于CXCL表达谱对样本进行分类；随后基于训练集的分类结果，利用支持向量机在验证集中构建聚类模型。接下来，通过弹性网分析，基于CXCL表达计算每个样本的风险评分。相较于低风险样本，高风险样本呈现出更恶性的临床特征、更差的生存结局以及更为复杂的免疫微环境。此外，高风险样本中的免疫检查点基因表达水平更高，提示CXCL家族可能参与肿瘤的免疫逃逸过程。值得注意的是，高风险样本的化疗耐药性也显著高于低风险样本。因此，本研究筛选出了靶向高风险样本的潜在化合物。本研究首次鉴定出LCL-161与ADZ5582两种新型药物作为胶质瘤的潜在治疗化合物，并从PubChem数据库中筛选出另外五种化合物。综上，本研究构建了基于CXCL表达的预后模型，并预测CXCL家族可通过调控肿瘤免疫微环境与肿瘤免疫逃逸来影响肿瘤进展；本研究同时提出的新型潜在化合物，有望改善恶性胶质瘤患者的预后。