线粒体起源的生物标志物:未来的癌症诊断。

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2022-07-11 DOI:10.1093/intbio/zyac008
Sukanya Gayan, Gargee Joshi, Tuli Dey
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引用次数: 0

摘要

如果没有有效的早期诊断和适当的治疗,癌症是一种高度致命的疾病。除了癌蛋白和肿瘤代谢物外,来自癌细胞的几种细胞器也成为潜在的生物标志物。从癌细胞中分离出的线粒体就是这样一个生物标志物候选者。与正常线粒体相比,癌变线粒体在形态学、基因组学、转录组学、蛋白质组学和代谢方面表现出不同的特征。本文讨论了通过单细胞组学和人工智能(AI)探索潜在生物标志物等特征的可能性。最后,对利用循环肿瘤细胞技术开发基于生物标志物的诊断及其未来应用前景进行了展望。循环肿瘤细胞分离协议和单细胞组学平台的成功联盟可以作为下一代诊断和个性化治疗程序出现。
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Biomarkers of mitochondrial origin: a futuristic cancer diagnostic.

Cancer is a highly fatal disease without effective early-stage diagnosis and proper treatment. Along with the oncoproteins and oncometabolites, several organelles from cancerous cells are also emerging as potential biomarkers. Mitochondria isolated from cancer cells are one such biomarker candidates. Cancerous mitochondria exhibit different profiles compared with normal ones in morphology, genomic, transcriptomic, proteomic and metabolic landscape. Here, the possibilities of exploring such characteristics as potential biomarkers through single-cell omics and Artificial Intelligence (AI) are discussed. Furthermore, the prospects of exploiting the biomarker-based diagnosis and its futuristic utilization through circulatory tumor cell technology are analyzed. A successful alliance of circulatory tumor cell isolation protocols and a single-cell omics platform can emerge as a next-generation diagnosis and personalized treatment procedure.

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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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