Li Shuang, Zou Dawei, Liu Zhaoqian
Hunan Key Laboratory of Pharmacogenetics, Department of Clinical Pharmacology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
Institute of Clinical Pharmacology, Central South University, Changsha, China.
Front Pharmacol. 2023 Mar 9;14:1127557. doi: 10.3389/fphar.2023.1127557. eCollection 2023.
Immunotherapy has limited effectiveness in ovarian cancer (OC) patients, highlighting the need for reliable biomarkers to predict the effectiveness of these treatments. The C-X-C motif chemokine ligands (CXCLs) have been shown to be associated with survival outcomes and immunotherapy efficacy in cancer patients. In this study, we aimed to evaluate the predictive value of 16 CXCLs in OC patients. We analyzed RNA-seq data from The Cancer Genome Atlas, Gene Expression Omnibus, and UCSC Xena database and conducted survival analysis. Consensus cluster analysis was used to group patients into distinct clusters based on their expression patterns. Biological pathway alterations and immune infiltration patterns were examined across these clusters using gene set variation analysis and single-sample gene set enrichment analysis. We also developed a CXCL scoring model using principal component analysis and evaluated its effectiveness in predicting immunotherapy response by assessing tumor microenvironment cell infiltration, tumor mutational burden estimation, PD-L1/CTLA4 expression, and immunophenoscore analysis (IPS). Most CXCL family genes were overexpressed in OC tissues compared to normal ovarian tissues. Patients were grouped into three distinct CXCL clusters based on their CXCL expression pattern. Additionally, using differentially expressed genes among the CXCL clusters, patients could also be grouped into three gene clusters. The CXCL and gene subtypes effectively predicted survival and immune cell infiltration levels for OC patients. Furthermore, patients with high CXCL scores had significantly better survival outcomes, higher levels of immune cell infiltration, higher IPS, and higher expression of PD-L1/CTLA4 than those with low CXCL scores. The CXCL score has the potential to be a promising biomarker to guide immunotherapy in individual OC patients and predict their clinical outcomes and immunotherapy responses.
免疫疗法在卵巢癌（OC）患者中的有效性有限，这凸显了需要可靠的生物标志物来预测这些治疗的有效性。C-X-C基序趋化因子配体（CXCLs）已被证明与癌症患者的生存结果和免疫疗法疗效相关。在本研究中，我们旨在评估16种CXCLs在OC患者中的预测价值。我们分析了来自癌症基因组图谱、基因表达综合数据库和加州大学圣克鲁兹分校Xena数据库的RNA测序数据，并进行了生存分析。共识聚类分析用于根据患者的表达模式将其分组为不同的簇。使用基因集变异分析和单样本基因集富集分析来检查这些簇中的生物通路改变和免疫浸润模式。我们还使用主成分分析开发了一种CXCL评分模型，并通过评估肿瘤微环境细胞浸润、肿瘤突变负担估计、PD-L1/CTLA4表达和免疫表型评分分析（IPS）来评估其预测免疫疗法反应的有效性。与正常卵巢组织相比，大多数CXCL家族基因在OC组织中过表达。根据CXCL表达模式，患者被分为三个不同的CXCL簇。此外，利用CXCL簇之间的差异表达基因，患者也可以被分为三个基因簇。CXCL和基因亚型有效地预测了OC患者的生存和免疫细胞浸润水平。此外，CXCL评分高的患者比CXCL评分低的患者具有显著更好的生存结果、更高的免疫细胞浸润水平、更高的IPS以及更高的PD-L1/CTLA4表达。CXCL评分有可能成为指导个体OC患者免疫疗法并预测其临床结果和免疫疗法反应的有前景的生物标志物。
