Pan-cancer analysis reveals CCL5/CSF2 as potential predictive biomarkers for immune checkpoint inhibitors

IF 5.3 2区 医学 Q1 ONCOLOGY Cancer Cell International Pub Date : 2024-09-10 DOI:10.1186/s12935-024-03496-x
Yi-Chao Chen, Wei-Zhong Zheng, Chun-Peng Liu, Yong-Qiang Zhao, Jun-Wei Li, Ze-Sen Du, Tian-Tian Zhai, Hao-Yu Lin, Wen-Qi Shi, Shan-Qing Cai, Feng Pan, Si-Qi Qiu
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Abstract

Currently, there are no optimal biomarkers available for distinguishing patients who will respond to immune checkpoint inhibitors (ICIs) therapies. Consequently, the exploration of novel biomarkers that can predict responsiveness to ICIs is crucial in the field of immunotherapy. We estimated the proportions of 22 immune cell components in 10 cancer types (6,128 tumors) using the CIBERSORT algorithm, and further classified patients based on their tumor immune cell proportions in a pan-cancer setting using k-means clustering. Differentially expressed immune genes between the patient subgroups were identified, and potential predictive biomarkers for ICIs were explored. Finally, the predictive value of the identified biomarkers was verified in patients with urothelial carcinoma (UC) and esophageal squamous cell carcinoma (ESCC) who received ICIs. Our study identified two subgroups of patients with distinct immune infiltrating phenotypes and differing clinical outcomes. The patient subgroup with improved outcomes displayed tumors enriched with genes related to immune response regulation and pathway activation. Furthermore, CCL5 and CSF2 were identified as immune-related hub-genes and were found to be prognostic in a pan-cancer setting. Importantly, UC and ESCC patients with high expression of CCL5 and low expression of CSF2 responded better to ICIs. We demonstrated CCL5 and CSF2 as potential novel biomarkers for predicting the response to ICIs in patients with UC and ESCC. The predictive value of these biomarkers in other cancer types warrants further evaluation in future studies.
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泛癌症分析发现 CCL5/CSF2 是免疫检查点抑制剂的潜在预测性生物标记物
目前,还没有最佳的生物标志物来区分哪些患者会对免疫检查点抑制剂(ICIs)疗法产生反应。因此,探索能预测对 ICIs 反应性的新型生物标记物在免疫疗法领域至关重要。我们使用CIBERSORT算法估算了10种癌症类型(6128个肿瘤)中22种免疫细胞成分的比例,并在泛癌症环境中使用k-means聚类方法根据肿瘤免疫细胞比例对患者进行了进一步分类。确定了患者亚组之间表达不同的免疫基因,并探索了 ICIs 的潜在预测生物标志物。最后,在接受 ICIs 治疗的尿路上皮癌(UC)和食管鳞状细胞癌(ESCC)患者中验证了所发现的生物标志物的预测价值。我们的研究发现了两个具有不同免疫浸润表型和不同临床结果的患者亚组。预后较好的患者亚群的肿瘤富含与免疫反应调节和通路激活相关的基因。此外,CCL5和CSF2被确定为免疫相关的枢纽基因,并被发现在泛癌症环境中具有预后作用。重要的是,CCL5 高表达和 CSF2 低表达的 UC 和 ESCC 患者对 ICIs 的反应更好。我们证明了 CCL5 和 CSF2 是预测 UC 和 ESCC 患者对 ICIs 反应的潜在新型生物标记物。这些生物标志物在其他癌症类型中的预测价值值得在未来的研究中进一步评估。
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来源期刊
CiteScore
10.90
自引率
1.70%
发文量
360
审稿时长
1 months
期刊介绍: Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.
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