Malik Sumaria, Zafar Paracha Rehan, Khalid Maryam, Nisar Maryum, Siddiqa Amnah, Hussain Zamir, Nawaz Raheel, Ali Amjad, Ahmad Jamil
Research Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
School of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, GM459 Geoffrey Manton Building, Manchester, England.
IET Syst Biol. 2019 Apr;13(2):69-76. doi: 10.1049/iet-syb.2018.5040.
Lung adenocarcinoma is one of the major causes of mortality. Current methods of diagnosis can be improved through identification of disease specific biomarkers. MicroRNAs are small non-coding regulators of gene expression, which can be potential biomarkers in various diseases. Thus, the main objective of this study was to gain mechanistic insights into genetic abnormalities occurring in lung adenocarcinoma by implementing an integrative analysis of miRNAs and mRNAs expression profiles in the case of both smokers and non-smokers. Differential expression was analysed by comparing publicly available lung adenocarcinoma samples with controls. Furthermore, weighted gene co-expression network analysis is performed which revealed mRNAs and miRNAs significantly correlated with lung adenocarcinoma. Moreover, an integrative analysis resulted in identification of several miRNA-mRNA pairs which were significantly dysregulated in non-smokers with lung adenocarcinoma. Also two pairs (miR-133b/Protein Kinase C Zeta (PRKCZ) and miR-557/STEAP3) were found specifically dysregulated in smokers. Pathway analysis further revealed their role in important signalling pathways including cell cycle. This analysis has not only increased the authors' understanding about lung adenocarcinoma but also proposed potential biomarkers. However, further wet laboratory studies are required for the validation of these potential biomarkers which can be used to diagnose lung adenocarcinoma.
肺腺癌是主要的致死原因之一。通过识别疾病特异性生物标志物可改进当前的诊断方法。微小RNA是基因表达的小型非编码调节因子，在各种疾病中可能成为生物标志物。因此，本研究的主要目的是通过对吸烟者和非吸烟者的微小RNA和信使核糖核酸表达谱进行综合分析，深入了解肺腺癌中发生的基因异常情况。通过将公开可用的肺腺癌样本与对照进行比较来分析差异表达。此外，进行了加权基因共表达网络分析，结果显示信使核糖核酸和微小RNA与肺腺癌显著相关。而且，综合分析鉴定出了几对在非吸烟肺腺癌患者中显著失调的微小RNA-信使核糖核酸对。另外还发现两对（微小RNA-133b/蛋白激酶C ζ（PRKCZ）和微小RNA-557/STEAP3）在吸烟者中特异性失调。通路分析进一步揭示了它们在包括细胞周期在内的重要信号通路中的作用。该分析不仅增进了作者对肺腺癌的了解，还提出了潜在的生物标志物。然而，需要进一步的湿实验室研究来验证这些可用于诊断肺腺癌的潜在生物标志物。
