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:Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.
Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.
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这些结果表明 PGD2 及其信号轴在 LUAD 中发挥重要的抑瘤和抗炎作用,在预后管理和治疗决策中具有潜在应用价值。
肿瘤代谢重编程是癌症的一个标志,但代谢物介导的细胞间通讯仍知之甚少。为填补这一空白,我们基于单细胞RNA数据估计并探索了通讯事件,以探究肺腺癌(LUAD)肿瘤微环境(TME)的代谢景观,并识别新的代谢物信号轴。
scRNA-seq数据集使用Seurat包进行降维处理。使用Cell Marker 2.0和既往研究中的典型标记物手动进行细胞注释。使用MEBOCOST推断单细胞代谢物丰度和通讯事件。使用TCGA-LUAD数据集,通过ESTIMATE和ssGSEA算法估计和分析免疫细胞浸润水平和肿瘤热评分。此外,对相关信号轴内的基因进行了生存分析。TCGA-LUAD数据集中的上述所有分析均通过两个Gene Expression Omnibus (GEO)数据集进行验证。PTGDR和PTGDS的表达模式通过RT-qPCR和荧光原位杂交进行验证。
在LUAD的TME中,跨细胞类型鉴定出五个标志性代谢物:前列腺素D2(PGD2)、D-甘露糖、胆碱、L-半胱氨酸和胆固醇。前列腺素D2(PGD2)成为关键角色,主要由成纤维细胞和浆细胞样树突状细胞(pDCs)通过PTGDS基因产生,肥大细胞通过HPGDS基因产生。PGD2信号主要被NK/T细胞上的PGD2受体(PTGDR)接收,并由内皮细胞上的SLCO2A1转运体运输。CX3CR1+ NK/T细胞是突出的细胞毒性群体,作为PGD2自分泌信号轴,参与PGD2自分泌信号传导,而KLRC2+ NK、DNAJB1+ NK细胞和CD8+ MAIT细胞参与PGD2旁分泌信号传导。PGD2还可能通过内皮细胞上的SLCO2A1协助乳酸外排。PGD2信号轴的临床相关性在多个bulk RNA数据集中得到验证,显示其与上述免疫细胞如DNAJB1+ NK细胞的浸润相关,并与LUAD更好的预后相关。此外,我们发现基于该信号轴开发的风险模型可以预测热肿瘤和冷肿瘤对免疫治疗的反应,提示可能使低风险患者获益的潜在药物。这些发现进一步得到RT-qPCR和免疫荧光数据的支持,证实了与正常组织相比,LUAD肿瘤组织中PTGDS和PTGDR的下调。
Tumor metabolism reprogramming is a hallmark of cancer, but metabolite-mediated intercellular communication remains poorly understood. To address this gap, we estimated and explored communication events exploring based on single-cell RNA data, to explore the metabolic landscape of tumor microenvironment (TME) in lung adenocarcinoma (LUAD) and identify novel metabolite signaling axis.
The scRNA-seq dataset was subjected to dimensionality reduction using the Seurat package. Cell annotation was manually performed using typical markers from Cell Marker 2.0 and previous studies. Single-cell metabolite abundance and communication events were inferred using MEBOCOST. The TCGA-LUAD datasets was used to estimate and analyze immune cell infiltration levels and tumor hot score using the ESTIMATE and ssGSEA algorithms. Additionally, survival analysis was conducted on genes within relative signaling axis. All analysis above in TCGA-LUAD dataset was validated by two Gene Expression Omnibus (GEO) datasets. The expression patterns of PTGDR and PTGDS were validated by RT-qPCR and fluorescence in situ hybridisation.
Five landmark metabolites across cell types were identified as prostaglandin D2 (PGD2), D-Mannose, Choline, L-Cysteine, and Cholesterol of TME in LUAD. Prostaglandin D2 (PGD2) emerged as a key player, primarily produced by fibroblasts and plasmacytoid dendritic cells (pDCs) by via the PTGDS gene and by mast cells via the HPGDS gene. PGD2 signaling was shown to primarily be received by the PGD2 receptor ( PTGDR ) on NK/T cells and transported by the SLCO2A1 transporter on endothelial cells. CX3CR1+ NK/T cells, which are prominent cytotoxic populations, as a PGD2 autocrine signaling axis, are involved in PGD2 autocrine signaling, while KLRC2+ NK, DNAJB1+ NK cells and CD8+ MAIT cells participate in PGD2 paracrine signaling. PGD2 may also assist lactate efflux via SLCO2A1 on endothelial cells. The clinical relevance of the PGD2 signaling axis was validated across multiple bulk RNA datasets, showing that it is associated with the infiltration of above immune cells such as DNAJB1+ NK cells, and linked to better prognosis in LUAD. Furthermore, we found that a risk model developed based on this signaling axis could predict responses to immune therapy in hot and cold tumors, suggesting potential drugs that may benefit low-risk patients. These findings were further supported by RT-qPCR and immunofluorescence data, which confirmed the downregulation of PTGDS and PTGDR in LUAD tumor tissues compared to normal tissues.
Collectively, these results suggest that PGD2 and its signaling axis play a significant role in tumor-suppressive and anti-inflammatory effects in LUAD, with potential applications in prognosis management and therapy decision-making.
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