Zhao Na, Xing Yujuan, Hu Yanfang, Chang Hao
Department of Gynecology, Dongying People's Hospital, Dongying, China.
Department of Cancer Research, Hanyu Biomed Center Beijing, Beijing, China.
Front Oncol. 2022 Jul 8;12:916251. doi: 10.3389/fonc.2022.916251. eCollection 2022.
Increasing evidence indicates that immune cell infiltration (ICI) affects the prognosis of multiple cancers. This study aims to explore the immunotypes and ICI-related biomarkers in ovarian cancer.
The ICI levels were quantified with the CIBERSORT and ESTIMATE algorithms. The unsupervised consensus clustering method determined immunotypes based on the ICI profiles. Characteristic genes were identified with the Boruta algorithm. Then, the ICI score, a novel prognostic marker, was generated with the principal component analysis of the characteristic genes. The relationships between the ICI scores and clinical features were revealed. Further, an ICI signature was integrated after the univariate Cox, lasso, and stepwise regression analyses. The accuracy and robustness of the model were tested by three independent cohorts. The roles of the model in the immunophenoscores (IPS), tumor immune dysfunction and exclusion (TIDE) scores, and immunotherapy responses were also explored. Finally, risk genes (GBP1P1, TGFBI, PLA2G2D) and immune cell marker genes (CD11B, NOS2, CD206, CD8A) were tested by qRT-PCR in clinical tissues.
Three immunotypes were identified, and ICI scores were generated based on the 75 characteristic genes. CD8 TCR pathways, chemokine-related pathways, and lymphocyte activation were critical to immunophenotyping. Higher ICI scores contributed to better prognoses. An independent prognostic factor, a three-gene signature, was integrated to calculate patients' risk scores. Higher TIDE scores, lower ICI scores, lower IPS, lower immunotherapy responses, and worse prognoses were revealed in high-risk patients. Macrophage polarization and CD8 T cell infiltration were indicated to play potentially important roles in the development of ovarian cancer in the clinical validation cohort.
Our study characterized the immunotyping landscape and provided novel immune infiltration-related prognostic markers in ovarian cancer.
越来越多的证据表明，免疫细胞浸润（ICI）会影响多种癌症的预后。本研究旨在探索卵巢癌的免疫亚型和ICI相关生物标志物。
使用CIBERSORT和ESTIMATE算法对ICI水平进行量化。采用无监督一致性聚类方法，根据ICI图谱确定免疫亚型。用Boruta算法识别特征基因。然后，通过对特征基因进行主成分分析，生成一种新的预后标志物——ICI评分。揭示了ICI评分与临床特征之间的关系。此外，在单因素Cox、套索和逐步回归分析后，整合了一个ICI特征。通过三个独立队列测试了该模型的准确性和稳健性。还探讨了该模型在免疫表型评分（IPS）、肿瘤免疫功能障碍与排除（TIDE）评分以及免疫治疗反应中的作用。最后，通过qRT-PCR在临床组织中检测了风险基因（GBP1P1、TGFBI、PLA2G2D）和免疫细胞标志物基因（CD11B、NOS2、CD206、CD8A）。
确定了三种免疫亚型，并基于75个特征基因生成了ICI评分。CD8 TCR通路、趋化因子相关通路和淋巴细胞活化对免疫表型分型至关重要。较高的ICI评分有助于更好的预后。整合了一个独立的预后因素——三基因特征，以计算患者的风险评分。高危患者显示出较高的TIDE评分、较低的ICI评分、较低的IPS、较低的免疫治疗反应和较差的预后。在临床验证队列中，巨噬细胞极化和CD8 T细胞浸润在卵巢癌的发生发展中可能发挥重要作用。
我们的研究对免疫分型情况进行了表征，并为卵巢癌提供了新的免疫浸润相关预后标志物。
