Ding Ran, Wang Yuhan, Fan Jinyan, Tian Ziyue, Wang Shuang, Qin Xiujuan, Su Wei, Wang Yanbo
Changchun University of Chinese Medicine, Changchun, Jilin, China.
Anhui University of Chinese Medicine, Hefei, Anhui, China.
Front Oncol. 2023 Jun 12;13:1108472. doi: 10.3389/fonc.2023.1108472. eCollection 2023.
Immune checkpoint blockade (ICB) therapy has transformed the treatment of triple-negative breast cancer (TNBC) in recent years. However, some TNBC patients with high programmed death-ligand 1 (PD-L1) expression levels develop immune checkpoint resistance. Hence, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to construct prognostic models of patient survival outcomes in order to understand biological mechanisms operating within the tumor microenvironment.
RNA sequence (RNA-seq) data from 303 TNBC samples were analyzed using an unsupervised cluster analysis approach to reveal distinctive cellular gene expression patterns within the TNBC tumor microenvironment (TME). A panel of T cell exhaustion signatures, immunosuppressive cell subtypes and clinical features were correlated with the immunotherapeutic response, as assessed according to gene expression patterns. The test dataset was then used to confirm the occurrence of immune depletion status and prognostic features and to formulate clinical treatment recommendations. Concurrently, a reliable risk prediction model and clinical treatment strategy were proposed based on TME immunosuppressive signature differences between TNBC patients with good versus poor survival status and other clinical prognostic factors.
Significantly enriched TNBC microenvironment T cell depletion signatures were detected in the analyzed RNA-seq data. A high proportion of certain immunosuppressive cell subtypes, 9 inhibitory checkpoints and enhanced anti-inflammatory cytokine expression profiles were noted in 21.4% of TNBC patients that led to the designation of this group of immunosuppressed patients as the immune depletion class (IDC). Although IDC group TNBC samples contained tumor-infiltrating lymphocytes present at high densities, IDC patient prognosis was poor. Notably, PD-L1 expression was relatively elevated in IDC patients that indicated their cancers were resistant to ICB treatment. Based on these findings, a set of gene expression signatures predicting IDC group PD-L1 resistance was identified then used to develop risk models for use in predicting clinical therapeutic outcomes.
A novel TNBC immunosuppressive tumor microenvironment subtype associated with strong PD-L1 expression and possible resistance to ICB treatment was identified. This comprehensive gene expression pattern may provide fresh insights into drug resistance mechanisms for use in optimizing immunotherapeutic approaches for TNBC patients.
近年来，免疫检查点阻断（ICB）疗法改变了三阴性乳腺癌（TNBC）的治疗方式。然而，一些程序性死亡配体1（PD-L1）表达水平高的TNBC患者会产生免疫检查点抗性。因此，迫切需要对免疫抑制性肿瘤微环境进行表征，并确定生物标志物以构建患者生存结果的预后模型，从而了解肿瘤微环境中起作用的生物学机制。
使用无监督聚类分析方法分析来自303个TNBC样本的RNA序列（RNA-seq）数据，以揭示TNBC肿瘤微环境（TME）中独特的细胞基因表达模式。根据基因表达模式评估，一组T细胞耗竭特征、免疫抑制细胞亚型和临床特征与免疫治疗反应相关。然后使用测试数据集来确认免疫耗竭状态和预后特征的存在，并制定临床治疗建议。同时，基于生存状态良好与生存状态较差的TNBC患者之间的TME免疫抑制特征差异以及其他临床预后因素，提出了可靠的风险预测模型和临床治疗策略。
在分析的RNA-seq数据中检测到显著富集的TNBC微环境T细胞耗竭特征。在21.4%的TNBC患者中发现了高比例的某些免疫抑制细胞亚型、9种抑制性检查点和增强的抗炎细胞因子表达谱，这导致这组免疫抑制患者被指定为免疫耗竭类（IDC）。尽管IDC组TNBC样本中含有高密度的肿瘤浸润淋巴细胞，但IDC患者的预后较差。值得注意的是，IDC患者中PD-L1表达相对升高，表明其癌症对ICB治疗具有抗性。基于这些发现，确定了一组预测IDC组PD-L1抗性的基因表达特征，然后用于开发预测临床治疗结果的风险模型。
确定了一种与强PD-L1表达和可能对ICB治疗耐药相关的新型TNBC免疫抑制性肿瘤微环境亚型。这种全面的基因表达模式可能为耐药机制提供新的见解，以优化TNBC患者的免疫治疗方法。
