Enhancer RNA SLIT2 Inhibits Bone Metastasis of Breast Cancer Through Regulating P38 MAPK/c-Fos Signaling Pathway.

Enhancer RNA SLIT2 Inhibits Bone Metastasis of Breast Cancer Through Regulating P38 MAPK/c-Fos Signaling Pathway.
复制标题

DOI:
10.3389/fonc.2021.743840
复制
发表时间:
2021
影响因子:
4.7
通讯作者:
Lin H
Lin H
中科院分区:
医学3区
文献类型:
--
作者:
Li P;Lin Z;Liu Q;Chen S;Gao X;Guo W;Gong F;Wei J;Lin H

文献摘要

参考文献

被引文献

相似文献

乳腺癌(BRCA)是女性最常见的癌症,而骨骼是最常见的转移部位之一。虽然新的诊断方法或放射或化学疗法和靶向疗法取得了巨大的进步,但骨转移的发生也与较差的生存率有关。增强子RNA(eRNA)已被证明参与肿瘤发生和转移的进展。然而,eRNA在BRCA骨转移中的作用仍不清楚。从癌症基因组图谱(TCGA)数据库中检索1,211例原发性BRCA和17例骨转移样本的基因表达谱,并通过考克斯回归和最小绝对收缩和选择算子(LASSO)回归确定具有显著预后意义的eRNA。受试者工作特征(ROC)和校准曲线表明诺模图具有可接受的准确性和区分度。然后利用eRNA靶基因、CIBERSORT分析免疫细胞百分比、单样本基因集富集分析(ssGSEA)免疫基因、基因集变异分析(GSVA)肿瘤信号通路标志和反相蛋白芯片(RPPA)构建共表达调控网络,鉴定BRCA骨转移关键eRNA。最后,使用细胞计数试剂盒-8(CCK-8)测定、细胞周期测定和transwell测定来研究细胞增殖、迁移和侵袭力的变化。采用免疫沉淀法和Western blotting法研究了它们之间的相互作用及其调控信号通路。选择27个hub eRNA,并构建具有相对高准确性的生存相关线性风险评估模型(曲线下面积(AUC):0.726)。此外,通过LASSO和多变量考克斯回归和CIBERSORT分析,进一步证实了7种免疫相关eRNA(SLIT 2、CLEC 3B、LBPL 1、FRY、RASGEF 1B、DST和ITIH 5)作为BRCA骨转移的预后标志。最后,体外试验证明SLIT 2的过表达降低了BRCA细胞的增殖和转移。利用高通量共表达调控网络,我们发现SLIT 2可能通过调控P38 MAPK/c-Fos信号通路促进肿瘤转移。基于BRCA骨转移的共表达网络,我们筛选关键eRNA,通过生物信息学分析探索预测骨转移的预后模型。此外,我们还发现SLIT 2在BRCA骨转移中的潜在调控信号通路,这为BRCA骨转移的治疗提供了一个有希望的策略。
Breast cancer (BRCA) is the most common cancer in women, while the bones are one of the most common sites of metastasis. Although new diagnostic methods or radiation or chemotherapies and targeted therapies have made huge advances, the occurrence of bone metastasis is also linked with poorer survival. Enhancer RNAs (eRNAs) have been demonstrated to participate in the progression of tumorigenesis and metastasis. However, the role of eRNAs in BRCA bone metastasis remains largely unclear. Gene expression profiling of 1,211 primary BRCA and 17 bone metastases samples were retrieved from The Cancer Genome Atlas (TCGA) database, and the significant prognostic eRNAs were identified by Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The acceptable accuracy and discrimination of the nomogram were indicated by the receiver operating characteristic (ROC) and the calibration curves. Then target genes of eRNA, immune cell percentage by CIBERSORT analysis, immune genes by single-sample gene set enrichment analysis (ssGSEA), hallmark of cancer signaling pathway by gene set variation analysis (GSVA), and reverse phase protein array (RPPA) protein chip were used to build a co-expression regulation network and identified the key eRNAs in bone metastasis of BRCA. Finally, Cell Counting Kit-8 (CCK8) assay, cell cycle assay, and transwell assay were used to study changes in cell proliferation, migration, and invasiveness. Immunoprecipitation assay and Western blotting were used to test the interaction and the regulation signaling pathways. The 27 hub eRNAs were selected, and a survival-related linear risk assessment model with a relatively high accuracy (area under curve (AUC): 0.726) was constructed. In addition, seven immune-related eRNAs (SLIT2, CLEC3B, LBPL1, FRY, RASGEF1B, DST, and ITIH5) as prognostic signatures for bone metastasis of BRCA were further confirmed by LASSO and multivariate Cox regression and CIBERSORT analysis. Finally, in vitro assay demonstrated that overexpression of SLIT2 reduced proliferation and metastasis in BRCA cells. Using high-throughput co-expression regulation network, we identified that SLIT2 may regulating P38 MAPK/c-Fos signaling pathway to promote the effects of metastasis. Based on the co-expression network for bone metastasis of BRCA, we screened key eRNAs to explore a prognostic model in predicting the bone metastasis by bioinformatics analysis. Besides, we identified the potential regulatory signaling pathway of SLIT2 in BRCA bone metastasis, which provides a promising therapeutic strategy for metastasis of BRCA.
SETDB1通过表观遗传学沉默p21表达促进结直肠癌的进展
DOI: 10.1038/s41419-020-2561-6
发表时间: 2020-05-11
影响因子: 9
作者:
Cao, Nan;Yu, Yali;Ye, Mei
通讯作者: Ye, Mei
DOI: 10.1007/s12253-019-00600-9
发表时间: 2019-07-01
影响因子: 2.8
作者:
Mohamed, Ghada;Talima, Soha;Murray, Paul G.
通讯作者: Murray, Paul G.
DOI: 10.1016/j.molcel.2015.06.002
发表时间: 2015-07-16
期刊: Molecular cell
影响因子: 16
作者:
Li W;Hu Y;Oh S;Ma Q;Merkurjev D;Song X;Zhou X;Liu Z;Tanasa B;He X;Chen AY;Ohgi K;Zhang J;Liu W;Rosenfeld MG
通讯作者: Rosenfeld MG
DOI: 10.1038/s41586-020-2774-y
发表时间: 2020-10
期刊: Nature
影响因子: 64.8
作者:
Tavora B;Mederer T;Wessel KJ;Ruffing S;Sadjadi M;Missmahl M;Ostendorf BN;Liu X;Kim JY;Olsen O;Welm AL;Goodarzi H;Tavazoie SF
通讯作者: Tavazoie SF
DOI: 10.1096/fj.01-0813com
发表时间: 2002-09-01
期刊: FASEB JOURNAL
影响因子: 4.8
作者:
Udagawa, T;Fernandez, A;D'Amato, RJ
通讯作者: D'Amato, RJ