■越来越多的研究证实,肿瘤相关巨噬细胞(TAMs)对肿瘤发生有重大影响,programming,和远处转移,代表了各种癌症的新靶标。然而,在结直肠癌(CRC)中,TAMs与肿瘤细胞之间潜在的动态变化和相互作用在很大程度上仍然难以捉摸.
■我们使用sing-cellRNA-seq数据和提取的TAM分化相关基因描绘了巨噬细胞的动态变化。接下来,我们利用加权基因共表达网络分析(WGCNA),利用大量RNA-seq数据获得CMS相关模块基因.最后,我们利用单变量Cox和LassoCox回归分析来鉴定TAM分化相关生物标志物,并建立了新的风险特征模型.我们对CRC组织样品采用定量实时聚合酶链反应(qRT-PCR),并使用HPA数据库中的免疫组织化学(IHC)数据来验证预后基因的mRNA和蛋白质表达。在细胞水平上分析TAM与每个共有分子亚型(CMS)亚群的相互作用。
■总共获得了来自单细胞数据集的47,285个细胞和来自批量数据集的1197个CRC患者。其中,将6400个骨髓细胞重新聚类并注释。RNASE1,F13A1,DAPK1,CLEC10A,将RPN2、REG4和RGS19鉴定为预后基因,并基于上述基因建立风险特征模型。qRT-PCR分析表明RNASE1和DAPK1在CRC肿瘤组织中表达显著上调。细胞-细胞通讯分析证明了TAM和CMS恶性细胞亚群之间的复杂相互作用。
■这项研究对肿瘤微环境中TAM的动态特征进行了深入剖析,并为CRC提供了有希望的治疗靶标。
UNASSIGNED: Accumulating research substantiated that tumor-associated macrophages (TAMs) have a significant impact on the tumorigenesis, progression, and distant metastasis, representing a novel target for various cancers. However, the underlying dynamic changes and interactions between TAMs and tumor cells remain largely elusive in colorectal cancer (CRC).
UNASSIGNED: We depicted the dynamic changes of macrophages using sing-cell RNA-seq data and extracted TAM differentiation-related genes. Next, we utilized the weighted gene co-expression network analysis (WGCNA) to acquire CMS-related modular genes using bulk RNA-seq data. Finally, we utilized univariate Cox and Lasso Cox regression analyses to identify TAM differentiation-related biomarkers and established a novel risk signature model. We employed quantitative real-time polymerase chain reaction (qRT-PCR) on CRC tissue samples and used immunohistochemistry (IHC) data frome the HPA database to validate the mRNA and protein expression of prognostic genes. The interaction of TAMs and each
consensus molecular subtype (CMS) subpopulation was analyzed at the cellular level.
UNASSIGNED: A total of 47,285 cells from single-cell dataset and 1197 CRC patients from bulk dataset were obtained. Among those, 6400 myeloid cells were re-clustered and annotated. RNASE1, F13A1, DAPK1, CLEC10A, RPN2, REG4 and RGS19 were identified as prognostic genes and the risk signature model was established based on the above genes. The qRT-PCR analysis indicated that the expression of RNASE1 and DAPK1 were significantly up-regulated in CRC tumor tissues. The cell-cell communication analysis demonstrated complex interactions between TAMs and CMS malignant cell subpopulations.
UNASSIGNED: This study presents an in-depth dissection of the dynamic features of TAMs in the tumor microenvironment and provides promising therapeutic targets for CRC.