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:Bulk and single-cell RNA sequencing identify prognostic signatures related to FGFBP2(+) NK cell in hepatocellular carcinoma.
Bulk and single-cell RNA sequencing identify prognostic signatures related to FGFBP2(+) NK cell in hepatocellular carcinoma.
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本研究在 HCC 中识别出八个与 FGFBP2 + NK 细胞相关的预后基因特征,这些特征可能作为 HCC 的潜在治疗靶点。
肝细胞癌(HCC)是一种高度侵袭性的恶性肿瘤。作为一种特定的免疫细胞亚群,FGFBP2+ NK 细胞在 HCC 进展的免疫监视中发挥关键作用。本研究旨在识别与 HCC 中 FGFBP2+ NK 细胞相关的预后特征。
Bulk和scRNA-seq数据来自公共数据库。通过"Seurat"包描绘了HCC的单细胞图谱和自然杀伤(NK)细胞的异质性。通过"Monocle2"包构建了FGFBP2 + NK细胞的拟时序轨迹。通过"CellChat"包分析细胞间相互作用。筛选预后特征以开发RiskScore模型,并验证了预测稳健性。评估了不同风险组之间的免疫细胞浸润和免疫治疗反应。通过"oncoPredict"包预测药物敏感性。利用HCC细胞通过体外实验检测了预后基因特征的表达。通过EdU实验、伤口愈合和Transwell实验评估了关键基因对HCC细胞增殖、迁移和侵袭能力的影响。
HCC样本中NK细胞的比例明显低于健康样本。NK细胞进一步分为三个细胞亚群,其中FGFBP2 + NK细胞与HCC患者的预后相关。FGFBP2 + NK细胞的拟时序轨迹分析揭示了两个差异表达基因簇。FGFBP2 + NK细胞在HCC中表现出广泛的细胞间通讯。此外,还鉴定了八个预后特征,包括六个“风险”基因(UBE2F、AHSA1、PTP4A2、CDKN2D、FTL、RGS2)和两个“保护”基因(KLF2、GZMH)。建立了具有良好预后预测性能的RiskScore模型。与低风险组相比,高风险组预后更差,免疫细胞浸润更低,TIDE评分更高。此外,16种药物与RiskScore显示出显著相关性。另外,在HCC细胞中GZMH的表达下调,而FTL、PTP4A2、UBE2F、CDKN2D、RGS2和AHSA1的表达上调。沉默FTL和PTP4A2可抑制HCC细胞的增殖、迁移和侵袭能力。
Hepatocellular carcinoma (HCC) is a highly aggressive malignancy. As a specific immune cell subpopulation, FGFBP2 + NK cells play a crucial part in immune surveillance of HCC progression. This study set out to identify prognostic signature related to FGFBP2 + NK cell in HCC.
Bulk and scRNA-seq data were derived from the public databases. The single cell atlas of HCC and heterogeneity of natural killer (NK) cells were delineated by "Seurat" package. Pseudo-time trajectory of FGFBP2 + NK cell was constructed by "Monocle2" package. Cell-cell interactions were analyzed by "CellChat" package. Prognostic signature was screened to develop a RiskScore model, and the prediction robustness was verified. Immune cell infiltration and immunotherapy response were assessed between different risk groups. Drug sensitivity was predicted by "oncoPredict" package. The expressions of the prognosis gene signature were detected by in vitro test utilizing HCC cells. The effects of key genes on the proliferative, migratory and invasive capacity of HCC cells were assessed by EdU assay, wound healing and Transwell assay.
The proportion of NK cell in HCC samples was markedly decreased than that in healthy samples. NK cell was further divided into three cell subpopulations, and FGFBP2 + NK cell was associated with the prognosis of HCC patients. Pseudo-time trajectory analysis of FGFBP2 + NK cell revealed two differential expression gene clusters. FGFBP2 + NK cell exhibited extensive intercellular communication in HCC. Further, eight prognostic signatures were identified, including six "risk" genes ( UBE2F , AHSA1 , PTP4A2 , CDKN2D , FTL , RGS2 ) and two "protective" genes ( KLF2 , GZMH ). RiskScore model was established with good prognostic prediction performance. In comparison to low-risk group, high-risk group had poorer prognosis, lower immune cell infiltration, and higher TIDE score. Moreover, 16 drugs showed significant correlation with RiskScore. Additionally, the expressions of GZMH was downregulated while FTL , PTP4A2 , UBE2F , CDKN2D , RGS2 , and AHSA1 were up-regulated in HCC cells. FTL and PTP4A2 silencing could suppress the proliferation, migration and invasion abilities of HCC cells.
This study identified eight prognostic gene signatures related to FGFBP2 + NK cell in HCC, which may serve as potential therapeutic targets for HCC.
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