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基于肿瘤微环境的四种新型结直肠癌免疫治疗分型的识别与验证

英文原题:Identification and validation of immunotherapy for four novel clusters of colorectal cancer based on the tumor microenvironment.

查看英文原题

Identification and validation of immunotherapy for four novel clusters of colorectal cancer based on the tumor microenvironment.

PubMed 2022/10/28(内容时间) Front Immunol Q1 · IF 7(JCR 2025)

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中文摘要

结直肠癌(CRC)的发病率和死亡率逐年上升。对CRC进行准确分型可以实现对患者的个性化精准治疗。肿瘤微环境(TME)在CRC的恶性进展和免疫治疗中发挥重要作用。深入理解基于TME的分型对于发现CRC新的治疗靶点具有重要意义。

我们从The Cancer Genome Atlas(TCGA)、Gene Expression Omnibus(GEO)(四个数据集——GSE14333、GSE17538、GSE38832和GSE39582)、cBioPortal和FireBrowse中提取了CRC数据,包括基因表达谱、DNA甲基化芯片、体细胞突变、临床病理信息和拷贝数变异(CNV)。利用MCPcounter对CRC样本中10种TME细胞的丰度进行定量。基于R中Pheatmap包的Hcluster函数进行聚类重复性分析。应用ESTIMATE包计算CRC患者的免疫评分和基质评分。采用PCA分析去除不同数据集之间的批次效应,并将全基因组DNA甲基化谱转化为TIL(肿瘤浸润淋巴细胞)甲基化(MeTIL)。

我们使用MOVICS、DeconstructSigs和GISTIC包评估了各聚类之间的突变差异。在治疗方面,进行TIDE和SubMap分析以预测各聚类的免疫治疗反应,并基于pRRophetic包评估化疗敏感性。所有结果均在TCGA和GEO数据中得到验证。共鉴定出四个CRC免疫聚类(ImmClust-CS1、ImmClust-CS2、ImmClust-CS3和ImmClust-CS4)。四个ImmClusts表现出不同的TME组成、癌相关成纤维细胞(CAFs)、功能取向和免疫检查点。CS2中观察到最高的免疫、基质和MeTIL评分,而CS4中评分最低。CS1可能对免疫治疗有反应,而CS2可能在抗CAFs治疗后对免疫治疗有反应。在四个ImmClusts中,获得了突变频率最高的前15个标志物,且CS1在焦点水平上的CNA显著低于其他亚型。

此外,CS1和CS2患者的染色体比CS3和CS4更稳定。还发现了这四个ImmClusts中最敏感的化疗药物。IHC结果显示,CD29在癌症样本中染色显著更深,表明其CD29在结肠癌中高表达。这项工作揭示了基于TME的CRC新聚类,这将有助于预测CRC患者的预后、生物学特征和适当的治疗。

展开英文摘要原文

The incidence and mortality of colorectal cancer (CRC) are increasing year by year. The accurate classification of CRC can realize the purpose of personalized and precise treatment for patients. The tumor microenvironment (TME) plays an important role in the malignant progression and immunotherapy of CRC. An in-depth understanding of the clusters based on the TME is of great significance for the discovery of new therapeutic targets for CRC.

We extracted data on CRC, including gene expression profile, DNA methylation array, somatic mutations, clinicopathological information, and copy number variation (CNV), from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) (four datasets-GSE14333, GSE17538, GSE38832, and GSE39582), cBioPortal, and FireBrowse. The MCPcounter was utilized to quantify the abundance of 10 TME cells for CRC samples.

Cluster repetitive analysis was based on the Hcluster function of the Pheatmap package in R. The ESTIMATE package was applied to compute immune and stromal scores for CRC patients. PCA analysis was used to remove batch effects among different datasets and transform genome-wide DNA methylation profiling into methylation of tumor-infiltrating lymphocyte (MeTIL).

We evaluated the mutation differences of the clusters using MOVICS, DeconstructSigs, and GISTIC packages. As for therapy, TIDE and SubMap analyses were carried out to forecast the immunotherapy response of the clusters, and chemotherapeutic sensibility was estimated based on the pRRophetic package. All results were verified in the TCGA and GEO data. Four immune clusters (ImmClust-CS1, ImmClust-CS2, ImmClust-CS3, and ImmClust-CS4) were identified for CRC.

The four ImmClusts exhibited distinct TME compositions, cancer-associated fibroblasts (CAFs), functional orientation, and immune checkpoints. The highest immune, stromal, and MeTIL scores were observed in CS2, in contrast to the lowest scores in CS4. CS1 may respond to immunotherapy, while CS2 may respond to immunotherapy after anti-CAFs. Among the four ImmClusts, the top 15 markers with the highest mutation frequency were acquired, and CS1 had significantly lower CNA on the focal level than other subtypes.

In addition, CS1 and CS2 patients had more stable chromosomes than CS3 and CS4. The most sensitive chemotherapeutic agents in these four ImmClusts were also found. IHC results revealed that CD29 stained significantly darker in the cancer samples, indicating that their CD29 was highly expressed in colon cancer. This work revealed the novel clusters based on TME for CRC, which would guide in predicting the prognosis, biological features, and appropriate treatment for patients with CRC.

论文信息

作者
Zheng X、Ma Y、Bai Y、Huang T、Lv X、Deng J、Wang Z、Lian W
第一作者单位
Department of Digestion, Henan Provincial Third People's Hospital, Zhengzhou, China.China
通讯作者单位
Department of Clinical Laboratory, Henan Provincial Third People's Hospital, Zhengzhou, China.China
文献类型
非美国政府资助研究
期刊
Frontiers in immunology2022
原文标识
PubMed 36389763 · DOI 10.3389/fimmu.2022.984480