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:Comprehensive single-cell analysis reveals cellular heterogeneity and immune interactions in colorectal cancer.
Comprehensive single-cell analysis reveals cellular heterogeneity and immune interactions in colorectal cancer.
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结直肠癌(CRC)因其多样的细胞组成和复杂的微环境而面临巨大的治疗挑战。我们的研究对CRC组织进行了单细胞RNA测序(scRNA-seq),检测了18,741个单细胞,将其分为六个主要细胞群体:上皮细胞、成纤维细胞、内皮细胞、T和NK细胞、B细胞和髓系细胞。上皮细胞在基因拷贝数上表现出显著变异。在T_NK细胞中,我们鉴定出四个不同的亚群。CytoTRACE分析表明,C3亚型分化潜能较低,而C0和C1亚型分化潜能较高。一致地,Monocle拟时序轨迹分析将C3细胞定位在分化终末阶段,而C0细胞富集于发育轨迹的早期阶段,提示T/NK亚群之间存在功能异质性。通过GSVA和ssGSEA功能分析,C3亚型显示出最高的炎症相关活性评分。对转录因子的进一步探索确定了T_NK细胞中三个独特的调控簇,揭示了其基因调控网络。
我们利用C3亚型T_NK细胞的标志物结合年龄相关基因开发了一个预后特征,发现其与患者生存结局显著相关。该预后模型被证明能有效对CRC患者进行风险分类。
此外,采用ESTIMATE、CIBERSORT和Xcell算法进行的免疫分析强调了CRC肿瘤内免疫细胞群体的复杂性。对肿瘤突变负荷(TMB)的分析突出了患者组之间的差异模式及其与预后风险水平的关系。
总体而言,这些见解为CRC细胞多样性和免疫动态提供了详细视角,支持靶向和个性化治疗干预的推进。
Colorectal cancer (CRC) presents considerable therapeutic challenges due to its diverse cellular composition and intricate microenvironment.
Our study utilized single-cell RNA sequencing (scRNA-seq) on CRC tissues, examining 18,741 individual cells, which were grouped into six primary cell populations: epithelial, fibroblast, endothelial, T and NK, B, and myeloid. The epithelial cells exhibited notable variations in gene copy numbers. Within T_NK cells, we identified four distinct subsets. CytoTRACE analysis indicated that subtype C3 exhibited lower differentiation potential, whereas subtypes C0 and C1 showed higher differentiation potential.
Consistently, Monocle pseudotime trajectory analysis positioned C3 cells at the terminal stage of differentiation, while C0 cells were enriched at the early stage of the developmental trajectory, suggesting functional heterogeneity among T/NK subpopulations. Through functional analyses with GSVA and ssGSEA, subtype C3 displayed the highest inflammation-associated activity scores.
Further exploration of transcription factors defined three unique regulatory clusters among T_NK cells, illuminating their gene-regulation networks.
We developed a prognostic signature using markers from subtype C3 T_NK cells combined with age-associated genes, revealing a significant correlation with patient survival outcomes. This prognostic model proved effective in categorizing CRC patients according to risk.
Additionally, immune profiling employing ESTIMATE, CIBERSORT, and Xcell algorithms underscored the complexity of immune cell populations within CRC tumors. Analysis of tumor mutational burden (TMB) highlighted differential patterns between patient groups and its relationship to prognostic risk levels. Collectively, these insights provide a detailed perspective on CRC cell diversity and immune dynamics, supporting the advancement of targeted and personalized therapeutic interventions.
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