再分化使能的 TSHRCART 细胞克服侵袭性甲状腺癌中的抗原丢失
Redifferentiation-enabled TSHRCART cells overcome antigen loss in aggressive thyroid cancers.
这些发现确立了肿瘤再分化作为一种可推广的策略,用于克服抗原丢失并增强 CAR-T 细胞疗法在甲状腺癌以及可能其他实体瘤中的疗效。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Identification of signature genes and immune infiltration analysis in thyroid cancer based on PANoptosis related genes.
Identification of signature genes and immune infiltration analysis in thyroid cancer based on PANoptosis related genes.
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我们的研究表明,PANoptosis 可能通过调节巨噬细胞、CD4+ T 细胞、活化 T 细胞和 B 细胞以及 TNF 信号通路,参与甲状腺癌的免疫失调。本研究提示了甲状腺癌发生的潜在靶点和机制。
甲状腺癌是内分泌系统最常见的恶性肿瘤。PANoptosis是一种特定的炎症性细胞死亡形式,主要包括焦亡、凋亡和坏死性凋亡。越来越多的证据表明,PANoptosis在肿瘤发生发展中起着至关重要的作用。然而,甲状腺癌中与PANoptosis相关的致病机制尚未被阐明。
基于目前已鉴定的PANoptosis基因,对来自GEO数据库的甲状腺癌患者数据集进行了分析。筛选甲状腺癌与PANoptosis的共有差异表达基因。分析PANoptosis相关基因(PRGs)的功能特征并筛选关键表达通路。通过LASSO回归建立预后模型并鉴定关键基因。基于CIBERSORT算法评估hub基因与免疫细胞之间的关联。通过验证数据集对预测模型进行验证,并探索免疫组化以及药物-基因相互作用。
结果显示,八个关键基因(NUAK2、TNFRSF10B、TNFRSF10C、TNFRSF12A、UNC5B 和 PMAIP1)在区分甲状腺癌患者和对照者方面表现出良好的诊断性能。这些关键基因与巨噬细胞、CD4+ T 细胞和中性粒细胞相关。此外,PRGs 主要富集于免疫调节通路和 TNF 信号通路。该模型的预测性能在验证数据集中得到确认。DGIdb 数据库揭示了 36 种针对甲状腺癌的潜在治疗靶点药物。
Thyroid cancer is the most common malignancy of the endocrine system. PANoptosis is a specific form of inflammatory cell death. It mainly includes pyroptosis, apoptosis and necrotic apoptosis. There is increasing evidence that PANoptosis plays a crucial role in tumour development. However, no pathogenic mechanism associated with PANoptosis in thyroid cancer has been identified.
Based on the currently identified PANoptosis genes, a dataset of thyroid cancer patients from the GEO database was analysed. To screen the common differentially expressed genes of thyroid cancer and PANoptosis. To analyse the functional characteristics of PANoptosis-related genes (PRGs) and screen key expression pathways. The prognostic model was established by LASSO regression and key genes were identified. The association between hub genes and immune cells was evaluated based on the CIBERSORT algorithm. Predictive models were validated by validation datasets, immunohistochemistry as well as drug-gene interactions were explored.
The results showed that eight key genes (NUAK2, TNFRSF10B, TNFRSF10C, TNFRSF12A, UNC5B, and PMAIP1) exhibited good diagnostic performance in differentiating between thyroid cancer patients and controls. These key genes were associated with macrophages, CD4+ T cells and neutrophils. In addition, PRGs were mainly enriched in the immunomodulatory pathway and TNF signalling pathway. The predictive performance of the model was confirmed in the validation dataset. The DGIdb database reveals 36 potential therapeutic target drugs for thyroid cancer.
Our study suggests that PANoptosis may be involved in immune dysregulation in thyroid cancer by regulating macrophages, CD4+ T cells and activated T and B cells and TNF signalling pathways. This study suggests potential targets and mechanisms for thyroid cancer development.
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