Siddique Farzana, Shehata Mohamed, Ghazal Mohammed, Contractor Sohail, El-Baz Ayman
Department of Bioengineering, University of Louisville, Louisville, KY 40292, USA.
Electrical, Computer, and Biomedical Engineering Department, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates.
Cancers (Basel). 2024 Jul 25;16(15):2643. doi: 10.3390/cancers16152643.
As of 2022, lung cancer is the most commonly diagnosed cancer worldwide, with the highest mortality rate. There are three main histological types of lung cancer, and it is more important than ever to accurately identify the subtypes since the development of personalized, type-specific targeted therapies that have improved mortality rates. Traditionally, the gold standard for the confirmation of histological subtyping is tissue biopsy and histopathology. This, however, comes with its own challenges, which call for newer sampling techniques and adjunctive tools to assist in and improve upon the existing diagnostic workflow. This review aims to list and describe studies from the last decade (n = 47) that investigate three such potential omics techniques-namely (1) transcriptomics, (2) proteomics, and (3) metabolomics, as well as immunohistochemistry, a tool that has already been adopted as a diagnostic adjunct. The novelty of this review compared to similar comprehensive studies lies with its detailed description of each adjunctive technique exclusively in the context of lung cancer subtyping. Similarities between studies evaluating individual techniques and markers are drawn, and any discrepancies are addressed. The findings of this study indicate that there is promising evidence that supports the successful use of omics methods as adjuncts to the subtyping of lung cancer, thereby directing clinician practice in an economical and less invasive manner.
截至2022年，肺癌是全球最常被诊断出的癌症，死亡率最高。肺癌主要有三种组织学类型，自从个性化、针对特定类型的靶向治疗出现并提高了死亡率以来，准确识别这些亚型比以往任何时候都更加重要。传统上，确认组织学亚型的金标准是组织活检和组织病理学。然而，这也带来了自身的挑战，需要更新的采样技术和辅助工具来协助并改进现有的诊断流程。本综述旨在列出并描述过去十年（n = 47）中研究三种此类组学技术的研究，即（1）转录组学、（2）蛋白质组学和（3）代谢组学，以及免疫组织化学，这是一种已被用作诊断辅助工具的技术。与类似的综合研究相比，本综述的新颖之处在于它专门在肺癌亚型分类的背景下详细描述了每种辅助技术。对评估个体技术和标志物的研究之间的相似性进行了总结，并解决了任何差异。本研究的结果表明，有令人鼓舞的证据支持将组学方法成功用作肺癌亚型分类的辅助手段，从而以经济且侵入性较小的方式指导临床医生的实践。
