RNF43 p.G659fs 通过 PI3K/AKT/mTOR 信号通路和 HLA-E 上调导致 MSI-high 结直肠癌中 NK 细胞功能障碍
RNF43 p.G659fs leads to natural killer cell dysfunction in MSI-high colorectal cancer through PI3K/AKT/mTOR signaling and HLA-E up-regulation.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Efferocytosis signatures as prognostic markers for revealing immune landscape and predicting immunotherapy response in hepatocellular carcinoma.
Efferocytosis signatures as prognostic markers for revealing immune landscape and predicting immunotherapy response in hepatocellular carcinoma.
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肝细胞癌(HCC)是一种高度致命的肝癌,诊断时多已处于晚期;因此,识别新的早期生物标志物可能有助于降低死亡率。胞葬作用(efferocytosis)是指一个细胞吞噬另一个细胞的过程,包括巨噬细胞、树突状细胞、NK细胞等,在肿瘤发生中发挥复杂作用,有时促进、有时抑制肿瘤发展。然而,胞葬作用相关基因(ERGs)在HCC进展中的作用研究甚少,其在HCC免疫治疗和药物靶向中的调控作用尚未见报道。
我们从Genecards数据库下载胞葬作用相关基因,筛选在HCC与正常组织之间表达显著变化且与HCC预后相关的ERGs。采用机器学习算法研究预后基因特征。使用CIBERSORT和pRRophetic R包评估HCC亚型的免疫环境并预测治疗反应。在HCC细胞上进行CCK-8实验,以评估药物敏感性预测的可靠性。
我们构建了一个由六个基因组成的预后预测模型,ROC曲线显示该风险模型具有良好的预测准确性。此外,HCC中两个ERGs相关亚组在肿瘤免疫景观、免疫反应和预后分层方面表现出显著差异。在HCC细胞上进行的CCK-8实验证实了药物敏感性预测的可靠性。
我们的研究强调了胞葬作用在HCC进展中的重要性。我们研究中基于胞葬作用相关基因构建的风险模型为HCC患者提供了一种新的精准医学方法,使临床医生能够根据患者独特的特征定制治疗方案。我们的研究结果对于开发涉及免疫治疗和化疗的个体化治疗方法具有重要意义,从而可能有助于实现HCC的个性化且更有效的治疗干预。
Background: Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with late diagnosis; therefore, the identification of new early biomarkers could help reduce mortality. Efferocytosis, a process in which one cell engulfs another cell, including macrophages, dendritic cells, NK cells, etc. , plays a complex role in tumorigenesis, sometimes promoting and sometimes inhibiting tumor development.
However, the role of efferocytosis-related genes (ERGs) in HCC progression has been poorly studied, and their regulatory effects in HCC immunotherapy and drug targeting have not been reported. Methods: We downloaded efferocytosis-related genes from the Genecards database and screened for ERGs that showed significant expression changes between HCC and normal tissues and were associated with HCC prognosis.
Machine learning algorithms were used to study prognostic gene features. CIBERSORT and pRRophetic R packages were used to evaluate the immune environment of HCC subtypes and predict treatment response. CCK-8 experiments conducted on HCC cells were used to assess the reliability of drug sensitivity prediction. Results: We constructed a prognostic prediction model composed of six genes, and the ROC curve showed good predictive accuracy of the risk model.
In addition, two ERG-related subgroups in HCC showed significant differences in tumor immune landscape, immune response, and prognostic stratification. The CCK-8 experiment conducted on HCC cells confirmed the reliability of drug sensitivity prediction. Conclusion: Our study emphasizes the importance of efferocytosis in HCC progression.
The risk model based on efferocytosis-related genes developed in our study provides a novel precision medicine approach for HCC patients, allowing clinicians to customize treatment plans based on unique patient characteristics. The results of our investigation carry noteworthy implications for the development of individualized treatment approaches involving immunotherapy and chemotherapy, thereby potentially facilitating the realization of personalized and more efficacious therapeutic interventions for HCC.
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