单细胞和多组学整合揭示了胆固醇生物合成与HER2在侵袭性乳腺癌中的协同作用。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-04-24 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.04.030
Tzu-Yang Tseng, Chiao-Hui Hsieh, Jie-Yu Liu, Hsuan-Cheng Huang, Hsueh-Fen Juan
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引用次数: 0

摘要

乳腺癌是影响妇女的最普遍的恶性肿瘤之一。癌细胞分子通路的改变代表了驱动恶性肿瘤的关键调控中断,影响癌细胞的存活、增殖,并可能调节治疗反应。因此,通过系统的计算方法解码复杂的分子机制并确定新的治疗靶点是推进有效乳腺癌治疗的重要步骤。在这项研究中,我们开发了一个综合计算框架,结合单细胞RNA测序(scRNA-seq)和多组学分析来描绘乳腺癌患者恶性细胞亚群的功能特征。我们的分析揭示了恶性乳腺癌细胞中胆固醇生物合成与HER2表达之间的显著相关性,这得到了蛋白质组学数据、基因表达谱、药物治疗评分和细胞表面HER2强度测量的支持。鉴于先前的证据将胆固醇生物合成与HER2膜动力学联系起来,我们提出了一种针对这两种途径的组合策略。通过克隆性和活力分析的实验验证表明,同时抑制胆固醇生物合成(通过他汀类药物)和HER2(通过Neratinib)可以协同减少恶性乳腺癌细胞,即使在HER2阴性的情况下也是如此。通过scRNA-seq和多组学数据的系统分析,我们的研究通过计算和实验验证了胆固醇生物合成和HER2作为乳腺癌新的联合治疗靶点。这种数据驱动的方法强调了利用多种分子分析技术来发现以前未探索的治疗策略的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-cell and multi-omics integration reveals cholesterol biosynthesis as a synergistic target with HER2 in aggressive breast cancer.

Breast cancer stands as one of the most prevalent malignancies affecting women. Alterations in molecular pathways in cancer cells represent key regulatory disruptions that drive malignancy, influencing cancer cell survival, proliferation, and potentially modulating therapeutic responsiveness. Therefore, decoding the intricate molecular mechanisms and identifying novel therapeutic targets through systematic computational approaches are essential steps toward advancing effective breast cancer treatments. In this study, we developed an integrative computational framework that combines single-cell RNA sequencing (scRNA-seq) and multi-omics analyses to delineate the functional characteristics of malignant cell subsets in breast cancer patients. Our analyses revealed a significant correlation between cholesterol biosynthesis and HER2 expression in malignant breast cancer cells, supported by proteomics data, gene expression profiles, drug treatment scores, and cell-surface HER2 intensity measurements. Given previous evidence linking cholesterol biosynthesis to HER2 membrane dynamics, we proposed a combinatorial strategy targeting both pathways. Experimental validation through clonogenic and viability assays demonstrated that simultaneous inhibition of cholesterol biosynthesis (via statins) and HER2 (via Neratinib) synergistically reduced malignant breast cancer cells, even in HER2-negative contexts. Through systematic analysis of scRNA-seq and multi-omics data, our study computationally identified and experimentally validated cholesterol biosynthesis and HER2 as novel combinatorial therapeutic targets in breast cancer. This data-driven approach highlights the potential of leveraging multiple molecular profiling techniques to uncover previously unexplored treatment strategies.

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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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