Zhou Rongbin, Xie Yuli, Wang Zuheng, Liu Zige, Lu Wenhao, Li Xiao, Wei Chunmeng, Li Xing, Wang Fubo
Collaborative Innovation Centre of Regenerative Medicine and Medical BioResource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Center for Genomic and Personalized Medicine, Guangxi key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, 530021, China.
BMC Cancer. 2025 Mar 18;25(1):498. doi: 10.1186/s12885-025-13901-x.
In recent years, immunotherapy has made significant progress. However, the understanding of the heterogeneity and function of T cells, particularly CD8 + T cells, in cervical cancer (CESC) microenvironment remains insufficient. We aim to characterize the heterogeneity, developmental trajectory, regulatory network, and intercellular communication of CD8 + T cells in cervical squamous cell carcinoma and to construct a prognostic risk model based on the transcriptomic characteristics of CD8 + T cells.
We integrated single-cell RNA sequencing data from CESC tumor samples with bulk transcriptome data from TCGA and GEO databases. We identified CD8 + T cell subsets in the CESC microenvironment, revealing significant interactions between CD8 + T cells and other cell types through intercellular communication analysis. Pseudotime trajectory analysis revealed dynamic transcriptional regulation during CD8 + T cell differentiation and functional acquisition processes. We constructed a transcriptional regulatory network for CESC CD8 + T cells, identifying key transcription factors. Based on CD8 + T cell-related genes, a prognostic risk model comprising eight core genes was developed and validated using machine learning.
We identified four distinct CD8 + T cell subsets, namely progenitor, intermediate, proliferative, and terminally differentiated, each exhibiting unique transcriptomic characteristics and functional properties. CD8 + T cell subsets interact with macrophages through different ligand-receptor networks, including the CCL-CCR signaling pathway and costimulatory molecules. Sorafenib was identified as a potential immunotherapeutic drug through drug screening. Experimental validation demonstrated that sorafenib enhances the cytotoxicity of CD8 + T cells by increasing the secretion of IFN-γ and TNF-α, thereby significantly inhibiting the invasiveness and survival of CESC cells.
Our study provides valuable insights into the heterogeneity and functional diversity of CD8 + T cells in CESC. We demonstrate that a CD8 + T cell-related prognostic signature may serve as a potential tool for risk stratification in patients with CESC. Additionally, our finding suggests that sorafenib could be a promising therapeutic candidate for improving antitumor immunity in this patient population.
近年来，免疫疗法取得了重大进展。然而，对于宫颈癌（CESC）微环境中T细胞，尤其是CD8 + T细胞的异质性和功能的了解仍然不足。我们旨在表征宫颈鳞状细胞癌中CD8 + T细胞的异质性、发育轨迹、调控网络和细胞间通讯，并基于CD8 + T细胞的转录组特征构建预后风险模型。
我们将CESC肿瘤样本的单细胞RNA测序数据与来自TCGA和GEO数据库的批量转录组数据进行整合。我们在CESC微环境中鉴定出CD8 + T细胞亚群，通过细胞间通讯分析揭示了CD8 + T细胞与其他细胞类型之间的显著相互作用。伪时间轨迹分析揭示了CD8 + T细胞分化和功能获得过程中的动态转录调控。我们构建了CESC CD8 + T细胞的转录调控网络，确定了关键转录因子。基于CD8 + T细胞相关基因，开发了一个包含八个核心基因的预后风险模型，并使用机器学习进行了验证。
我们鉴定出四个不同的CD8 + T细胞亚群，即祖细胞、中间细胞、增殖细胞和终末分化细胞，每个亚群都表现出独特的转录组特征和功能特性。CD8 + T细胞亚群通过不同的配体-受体网络与巨噬细胞相互作用，包括CCL-CCR信号通路和共刺激分子。通过药物筛选确定索拉非尼为潜在的免疫治疗药物。实验验证表明，索拉非尼通过增加IFN-γ和TNF-α的分泌来增强CD8 + T细胞的细胞毒性，从而显著抑制CESC细胞的侵袭性和存活率。
我们的研究为CESC中CD8 + T细胞的异质性和功能多样性提供了有价值的见解。我们证明，CD8 + T细胞相关的预后特征可能作为CESC患者风险分层的潜在工具。此外，我们的发现表明索拉非尼可能是改善该患者群体抗肿瘤免疫力的有前景的治疗候选药物。
