表征外泌体mirna在癌症转移中的泛癌作用。

IF 4.1 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Computational and structural biotechnology journal Pub Date : 2025-01-01 Epub Date: 2024-12-26 DOI:10.1016/j.csbj.2024.12.025
Piyush Agrawal , Gulden Olgun , Arashdeep Singh , Vishaka Gopalan , Sridhar Hannenhalli
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引用次数: 0

摘要

外泌体microRNAs (exomiRs)在细胞间通讯中起着关键作用,特别是在癌症中,它们调节增殖、血管生成和转移等关键细胞过程,突出了它们作为潜在诊断和治疗靶点的重要性。在这里,我们的目的是表征来自七种癌症类型(四种细胞系和三种肿瘤)的exomir在影响转移前生态位(PMN)中的作用。在每种癌症类型中,我们提取了高置信度的外显子irs(外显体中LogFC >= 2,相对于对照组),它们的实验验证靶点,以及这些靶点之间的富集途径。然后,我们根据它们在富集通路中的出现频率选择了前100个高置信度目标。我们观察到相对于基因组背景,外显子的GC含量明显较高。基因本体论分析既揭示了一般的癌症过程,如伤口愈合和上皮细胞增殖,也揭示了癌症特异性过程,如肾脏的“血管生成”和肺的“骨化”。与正常相比,ExomiR靶点在癌症特异性肿瘤抑制基因中富集,在肺中形成的PMN中下调。基序分析显示,外显子序列中富集的基序具有较高的癌间相似性。我们的分析总结了与M2巨噬细胞分化和化疗耐药相关的外显子,如miR-21和miR-222-3p,调节PTEN/PI3/Akt, NF-kB等信号通路。此外,TCGA的Cox回归分析表明,exomiR靶点与患者更好的总生存期显著相关。最后,使用exomiR靶向基因表达的支持向量机模型对治疗的应答者和无应答者进行了分类,AUROC范围为0.72至0.96,高于之前报道的基因特征。
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Characterizing the pan-cancer role of exosomal miRNAs in metastasis across cancers
Exosomal microRNAs (exomiRs) play a critical role in intercellular communication, especially in cancer, where they regulate key cellular processes like proliferation, angiogenesis, and metastasis, highlighting their significance as potential diagnostic and therapeutic targets. Here, we aimed to characterize the role of exomiRs, derived from seven cancer types (four cell lines and three tumors), in influencing the pre-metastatic niche (PMN). In each cancer type we extracted high confidence exomiRs (LogFC >= 2 in exosomes relative to control), their experimentally validated targets, and the enriched pathways among those targets. We then selected the top100 high-confidence targets based on their frequency of appearance in the enriched pathways. We observed significantly higher GC content in exomiRs relative to genomic background. Gene Ontology analysis revealed both general cancer processes, such as wound healing and epithelial cell proliferation, as well as cancer-specific processes, such as “angiogenesis” in the kidney and “ossification” in the lung. ExomiR targets were enriched for cancer-specific tumor suppressor genes and downregulated in PMN formed in lungs compared to normal. Motif analysis showed high inter-cancer similarity among motifs enriched in exomiRs. Our analysis recapitulated exomiRs associated with M2 macrophage differentiation and chemoresistance, such as miR-21 and miR-222–3p, regulating signaling pathways like PTEN/PI3/Akt, NF-kB, etc. Additionally, Cox regression analysis in TCGA indicated that exomiR targets are significantly associated with better overall survival of patients. Lastly, support vector machine model using exomiR targets gene expression classified responders and non-responders to therapy with an AUROC ranging from 0.72 to 0.96, higher than previously reported gene signatures.
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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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