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结直肠癌中与铜死亡相关的 miRNA 特征及免疫浸润特征。

Cuproptosis-related miRNAs signature and immune infiltration characteristics in colorectal cancer.

机构信息

Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, PR China.

Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, PR China.

出版信息

Cancer Med. 2023 Aug;12(15):16661-16678. doi: 10.1002/cam4.6270. Epub 2023 Jun 19.

DOI:10.1002/cam4.6270
PMID:37334893
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10469834/
Abstract

BACKGROUND

A novel form of cell death termed cuproptosis was proposed recently. miRNAs play important roles in colorectal cancer (CRC). However, their relationships have not been reported.

METHODS

miRNAs that negatively regulate 16 cuproptosis regulators were predicted using Targetscan database. The univariate Cox, LASSO, and multivariate Cox regression analyses were performed to select cuproptosis-related miRNAs. GSEA and ssGSEA analysis was carried out for functional enrichment analysis. The immune cell proportion score (IPS) and the efficiencies of multiple chemotherapy drugs were compared between different risk groups. The CCK8, cell colony, edu, and flow cytometry assays were performed to validate the roles of miRNA. Luciferase reporter assay confirmed the regulatory mechanism of miRNA on cuproptosis.

RESULTS

Six cuproptosis-related miRNAs (hsa-miR-653, hsa-miR-216a, hsa-miR-3684, hsa-miR-4437, hsa-miR-641, and hsa-miR-552) were screened out for model construction. The risk score could act as an independent prognostic indicator in CRC (p < 0.001, 95% HR = 1.243 (1.129-1.369)). The nomogram could efficiently predict the overall survival rate (AUC = 0.836). Then, the level of immunosuppressive pathways, immunosuppressive cells, stromal-activated genes, and stromal score was higher in the high-risk group. The IPS analysis showed a better response to immunotherapy in the low-risk group. Also, the risk score was closely correlated with efficiencies of multiple chemotherapy drugs. Furthermore, miR-653 was highly expressed in CRC tissues (p < 0.001), closely correlated with T stage (p < 0.001), metastasis (p < 0.001), and tumor stage (p < 0.001). High expression of miR-653 predicted a shorter overall survival (p = 0.0282) and disease-free survival (p = 0.0056). In addition, miR-653 promoted cell proliferation, inhibited apoptosis, and negatively regulated the expression of DLD through directly binding to the 3'-UTR of DLD mRNA.

CONCLUSION

We constructed a cuproptosis-related miRNA signature for the prediction of CRC patient survival and immunotherapy sensitivity. miR-653 was highly expressed in CRC tissues, promoted cell proliferation, and inhibited apoptosis by negatively regulating the expression of DLD.

摘要

背景

最近提出了一种称为铜死亡的新型细胞死亡形式。miRNA 在结直肠癌(CRC)中发挥重要作用。然而,它们之间的关系尚未被报道。

方法

使用 Targetscan 数据库预测负调控 16 种铜死亡调节剂的 miRNA。进行单变量 Cox、LASSO 和多变量 Cox 回归分析以选择与铜死亡相关的 miRNA。进行 GSEA 和 ssGSEA 分析以进行功能富集分析。比较不同风险组之间的免疫细胞比例评分(IPS)和多种化疗药物的效率。通过 CCK8、细胞集落、edu 和流式细胞术测定验证 miRNA 的作用。荧光素酶报告实验证实 miRNA 对铜死亡的调控机制。

结果

筛选出 6 个与铜死亡相关的 miRNA(hsa-miR-653、hsa-miR-216a、hsa-miR-3684、hsa-miR-4437、hsa-miR-641 和 hsa-miR-552)用于模型构建。风险评分可作为 CRC 的独立预后指标(p<0.001,95%HR=1.243(1.129-1.369))。列线图可以有效地预测总生存率(AUC=0.836)。然后,高危组中免疫抑制途径、免疫抑制细胞、基质激活基因和基质评分水平较高。IPS 分析表明低危组对免疫治疗的反应更好。此外,风险评分与多种化疗药物的效率密切相关。此外,miR-653 在 CRC 组织中高表达(p<0.001),与 T 分期(p<0.001)、转移(p<0.001)和肿瘤分期(p<0.001)密切相关。miR-653 高表达预测总生存期较短(p=0.0282)和无病生存期较短(p=0.0056)。此外,miR-653 通过直接结合 DLD mRNA 的 3'-UTR 促进细胞增殖,抑制细胞凋亡,并负调控 DLD 的表达。

结论

我们构建了一个与 CRC 患者生存和免疫治疗敏感性相关的铜死亡相关 miRNA 特征。miR-653 在 CRC 组织中高表达,通过负调控 DLD 的表达促进细胞增殖和抑制细胞凋亡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/a6868c0a9ecf/CAM4-12-16661-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/75ca1469ed27/CAM4-12-16661-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/00a3a0fbe3d6/CAM4-12-16661-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/04d1debbaa93/CAM4-12-16661-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/5ba29ceafcad/CAM4-12-16661-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/01ad4fe797e2/CAM4-12-16661-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/a6868c0a9ecf/CAM4-12-16661-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/75ca1469ed27/CAM4-12-16661-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/901c5503d838/CAM4-12-16661-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/eb3ea2be2f81/CAM4-12-16661-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/00a3a0fbe3d6/CAM4-12-16661-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/04d1debbaa93/CAM4-12-16661-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/5ba29ceafcad/CAM4-12-16661-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/01ad4fe797e2/CAM4-12-16661-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8717/10469834/a6868c0a9ecf/CAM4-12-16661-g005.jpg

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