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通过批量和单细胞RNA测序探索细胞焦亡在塑造结直肠癌肿瘤微环境中的作用。

Exploring the role of pyroptosis in shaping the tumor microenvironment of colorectal cancer by bulk and single-cell RNA sequencing.

作者信息

Ding Chengsheng, Yang Xiao, Li Shuchun, Zhang Enkui, Fan Xiaodong, Huang Ling, He Zirui, Sun Jing, Ma Junjun, Zang Lu, Zheng Minhua

机构信息

Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, Shanghai, 200025, China.

Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.

出版信息

Cancer Cell Int. 2023 May 18;23(1):95. doi: 10.1186/s12935-023-02897-8.

DOI:10.1186/s12935-023-02897-8
PMID:37198617
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10193704/
Abstract

BACKGROUND

Emerging studies have shown that pyroptosis plays a non-negligible role in the development and treatment of tumors. However, the mechanism of pyroptosis in colorectal cancer (CRC) remains still unclear. Therefore, this study investigated the role of pyroptosis in CRC.

METHODS

A pyroptosis-related risk model was developed using univariate Cox regression and LASSO Cox regression analyses. Based on this model, pyroptosis-related risk scores (PRS) of CRC samples with OS time > 0 from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database were calculated. The abundance of immune cells in CRC tumor microenvironment (TME) was predicted by single-sample gene-set enrichment analysis (ssGSEA). Then, the responses to chemotherapy and immunotherapy were predicted by pRRophetic algorithm, the tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms, respectively. Moreover, the Cancer Therapeutics Response Portal (CTRP) and PRISM Repurposing dataset (PRISM) were used to explore novel drug treatment strategies of CRC. Finally, we investigated pyroptosis-related genes in the level of single-cell and validated the expression levels of these genes between normal and CRC cell lines by RT-qPCR.

RESULTS

Survival analysis showed that CRC samples with low PRS had better overall survival (OS) and progression-free survival (PFS). CRC samples with low PRS had higher immune-related gene expression and immune cell infiltration than those with high PRS. Besides, CRC samples with low PRS were more likely to benefit from 5-fluorouracil based chemotherapy and anti-PD-1 immunotherapy. In novel drug prediction, some compounds such as C6-ceramide and noretynodrel, were inferred as potential drugs for CRC with different PRS. Single-cell analysis revealed pyroptosis-related genes were highly expressed in tumor cells. RT-qPCR also demonstrated different expression levels of these genes between normal and CRC cell lines.

CONCLUSIONS

Taken together, this study provides a comprehensive investigation of the role of pyroptosis in CRC at the bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) levels, advances our understanding of CRC characteristics, and guides more effective treatment regimens.

摘要

背景

新兴研究表明,细胞焦亡在肿瘤的发生发展及治疗中发挥着不可忽视的作用。然而,细胞焦亡在结直肠癌(CRC)中的机制仍不清楚。因此,本研究探讨了细胞焦亡在CRC中的作用。

方法

使用单因素Cox回归和LASSO Cox回归分析建立细胞焦亡相关风险模型。基于该模型,计算来自基因表达综合数据库(GEO)和癌症基因组图谱(TCGA)数据库中OS时间>0的CRC样本的细胞焦亡相关风险评分(PRS)。通过单样本基因集富集分析(ssGSEA)预测CRC肿瘤微环境(TME)中免疫细胞的丰度。然后,分别通过pRRophetic算法、肿瘤免疫功能障碍与排除(TIDE)算法和SubMap算法预测对化疗和免疫治疗的反应。此外,利用癌症治疗反应门户(CTRP)和PRISM重新利用数据集(PRISM)探索CRC的新型药物治疗策略。最后,我们在单细胞水平研究细胞焦亡相关基因,并通过RT-qPCR验证这些基因在正常细胞系和CRC细胞系之间的表达水平。

结果

生存分析表明,低PRS的CRC样本具有更好的总生存期(OS)和无进展生存期(PFS)。低PRS的CRC样本比高PRS的样本具有更高的免疫相关基因表达和免疫细胞浸润。此外,低PRS的CRC样本更有可能从基于5-氟尿嘧啶的化疗和抗PD-1免疫治疗中获益。在新型药物预测中,一些化合物如C6-神经酰胺和炔诺酮被推断为不同PRS的CRC的潜在药物。单细胞分析显示细胞焦亡相关基因在肿瘤细胞中高表达。RT-qPCR也证实了这些基因在正常细胞系和CRC细胞系之间的表达水平不同。

结论

综上所述,本研究在批量RNA测序(RNA-seq)和单细胞RNA测序(scRNA-seq)水平上全面研究了细胞焦亡在CRC中的作用,增进了我们对CRC特征的理解,并指导了更有效的治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/50cd99f57aeb/12935_2023_2897_Fig9_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/e0b8dc3b1c79/12935_2023_2897_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/71041a54d962/12935_2023_2897_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/c54ccce580f8/12935_2023_2897_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/70e335564e67/12935_2023_2897_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/b59f2f0a4006/12935_2023_2897_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/ab2edda806f3/12935_2023_2897_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9394/10193704/50cd99f57aeb/12935_2023_2897_Fig9_HTML.jpg

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