A New Method for Constructing Macrophage-Associated Predictors of Treatment Efficacy Based on Single-Cell Sequencing Analysis.

IF 3.2 4区 医学 Q3 IMMUNOLOGY
Journal of Immunotherapy Pub Date : 2024-02-01 Epub Date: 2023-11-20 DOI:10.1097/CJI.0000000000000497
Jianxiu Lin, Yang Ran, Tengfei Wu, Zishan Wang, Jinjin Zhao, Yun Tian
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引用次数: 0

Abstract

Tumor-associated macrophages (TAMs) are highly infiltrated in the tumor microenvironment (TME) of colorectal cancer (CRC) and play a vital role in CRC's development as well as prognosis. The required data were obtained from the Gene Expression Omnibus database and The Cancer Genome Atlas. Univariate Cox regression and least absolute shrinkage operator analyses were executed for model construction. TME assessment and immune prediction were performed using the ESTIMATE software package and the single sample genome enrichment analysis algorithm. The results show patients with low a TAMs risk score (TRS) had a better prognosis in both The Cancer Genome Atlas and Gene Expression Omnibus cohorts. Patients with low TRS were more sensitive to 3 chemotherapeutic agents: oxaliplatin, paclitaxel, and cisplatin ( P <0.05). TME assessment showed that the low TRS group had less infiltration of M2 macrophages and regulatory T cells, but CD4 + T cells, NK cells, and dendritic cells occupy a greater proportion of TME. Low TRS group patients have a low StromalScore and ImmuneScore but have high TumorPurity. The immune checkpoint TIM-3 gene HAVCR2 expression was significantly higher in the high TRS group. Finally, we created a nomogram including TRS for forecasting survival, and TRS was significantly associated with the clinical stage of the patients. In conclusion, the TRS serves as a reliable prognostic indicator of CRC; it predicts patient outcomes to immunotherapy and chemotherapy and provides genomic evidence for the subsequent development of modulated TAMs for treating CRC.

基于单细胞测序分析构建巨噬细胞相关治疗效果预测因子的新方法
肿瘤相关巨噬细胞(tumor -associated macrophages, tam)高度浸润于结直肠癌(CRC)的肿瘤微环境(tumor microenvironment, TME)中,在结直肠癌的发生发展和预后中起着至关重要的作用。所需数据来自基因表达综合数据库和癌症基因组图谱。单变量Cox回归和最小绝对收缩算子分析用于模型构建。采用ESTIMATE软件包和单样本基因组富集分析算法进行TME评估和免疫预测。结果显示,在The Cancer Genome Atlas和Gene Expression Omnibus队列中,TAMs风险评分(TRS)较低的患者预后较好。低TRS患者对奥沙利铂、紫杉醇和顺铂3种化疗药物更敏感(P
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Immunotherapy
Journal of Immunotherapy 医学-免疫学
CiteScore
6.90
自引率
0.00%
发文量
79
审稿时长
6-12 weeks
期刊介绍: Journal of Immunotherapy features rapid publication of articles on immunomodulators, lymphokines, antibodies, cells, and cell products in cancer biology and therapy. Laboratory and preclinical studies, as well as investigative clinical reports, are presented. The journal emphasizes basic mechanisms and methods for the rapid transfer of technology from the laboratory to the clinic. JIT contains full-length articles, review articles, and short communications.
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