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，肺癌是全球诊断率最高、死亡率最高的恶性肿瘤。肺癌主要存在三种组织学类型，随着能够改善死亡率的个性化、类型特异性靶向治疗的发展，准确识别亚型变得比以往任何时候都更为重要。传统上，确认组织学分型的金标准是组织活检和组织病理学检查。然而，这种方法本身存在挑战，因此需要新的采样技术和辅助工具来协助并改进现有的诊断流程。本综述旨在列举并描述过去十年（共47项）的研究，这些研究探讨了三种潜在的组学技术——即（1）转录组学，（2）蛋白质组学，以及（3）代谢组学，以及已被用作诊断辅助工具的免疫组织化学。与类似的综合性研究相比，本综述的创新之处在于其详细描述了每种辅助技术，且专门针对肺癌分型的背景。研究评估了各项技术和标志物之间的相似性，并解决了存在的差异。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分型的辅助手段，从而以经济且微创的方式指导临床实践。
肿瘤(癌症)患者之家