Elshoeibi Amgad Mohamed, Elsayed Basel, Kaleem Muhammad Zain, Elhadary Mohamed Ragab, Abu-Haweeleh Mohannad Natheef, Haithm Yunes, Krzyslak Hubert, Vranic Semir, Pedersen Shona
College of Medicine, QU Health, Qatar University, Doha 2713, Qatar.
Department of Clinical Biochemistry, Aalborg University Hospital, 9000 Aalborg, Denmark.
Cancers (Basel). 2023 Oct 16;15(20):5005. doi: 10.3390/cancers15205005.
The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.
小细胞肺癌（SCLC）的准确诊断至关重要，因为其治疗策略与其他肺癌不同。本系统评价旨在确定与正常肺组织相比，在SCLC中差异表达的蛋白质，评估它们在诊断和预测该疾病方面的潜在效用。此外，该研究还确定了SCLC与大细胞神经内分泌癌（LCNEC）之间差异表达的蛋白质，旨在发现区分这两种神经内分泌肺癌亚型的生物标志物。按照系统评价和Meta分析的首选报告项目（PRISMA）指南，在PubMed/MEDLINE、Scopus、Embase和Web of Science数据库中进行了全面检索。纳入了报告蛋白质组学信息并通过组织病理学和/或细胞病理学检查确认SCLC和/或LCNEC的研究，同时排除了综述文章、非原创文章以及基于动物样本或细胞系的研究。初步检索得到1705篇文章，经过去重和筛选后，16篇文章被认为符合要求。这些研究揭示了与正常肺组织相比，在SCLC中117种显著差异表达的独特蛋白质，以及SCLC与LCNEC之间37种差异表达的独特蛋白质。总之，本综述强调了蛋白质组学技术在识别用于诊断SCLC、预测其预后以及将其与LCNEC区分开来的新型生物标志物方面的潜力。
