Zhang Xueli, Zhang Hong, Shen Bairong, Sun Xiao-Feng
School of Medicine, Institute of Medical Sciences, Örebro University, SE-70182 Örebro, Sweden.
Centre for Systems Biology, Soochow University, Suzhou 215006, China.
Cancers (Basel). 2020 Feb 3;12(2):341. doi: 10.3390/cancers12020341.
Colorectal cancer (CRC) is one of the major causes of cancer death worldwide. In general, early diagnosis for CRC and individual therapy have led to better survival for the cancer patients. Accumulating studies concerning biomarkers have provided positive evidence to improve cancer early diagnosis and better therapy. It is, however, still necessary to further investigate the precise biomarkers for cancer early diagnosis and precision therapy and predicting prognosis. In this study, AI-assisted systems with bioinformatics algorithm integrated with microarray and RNA sequencing (RNA-seq) gene expression (GE) data has been approached to predict microRNA (miRNA) biomarkers for early diagnosis of CRC based on the miRNA-messenger RNA (mRNA) interaction network. The relationships between the predicted miRNA biomarkers and other biological components were further analyzed on biological networks. Bayesian meta-analysis of diagnostic test was utilized to verify the diagnostic value of the miRNA candidate biomarkers and the combined multiple biomarkers. Biological function analysis was performed to detect the relationship of candidate miRNA biomarkers and identified biomarkers in pathways. Text mining was used to analyze the relationships of predicted miRNAs and their target genes with 5-fluorouracil (5-FU). Survival analyses were conducted to evaluate the prognostic values of these miRNAs in CRC. According to the number of miRNAs single regulated mRNAs (NSR) and the number of their regulated transcription factor gene percentage (TFP) on the miRNA-mRNA network, there were 12 promising miRNA biomarkers were selected. There were five potential candidate miRNAs (miRNA-186-5p, miRNA-10b-5, miRNA-30e-5p, miRNA-21 and miRNA-30e) were confirmed as CRC diagnostic biomarkers, and two of them (miRNA-21 and miRNA-30e) were previously reported. Furthermore, the combinations of the five candidate miRNAs biomarkers showed better prediction accuracy for CRC early diagnosis than the single miRNA biomarkers. miRNA-10b-5p and miRNA-30e-5p were associated with the 5-FU therapy resistance by targeting the related genes. These miRNAs biomarkers were not statistically associated with CRC prognosis.
结直肠癌（CRC）是全球癌症死亡的主要原因之一。一般来说，CRC的早期诊断和个体化治疗使癌症患者的生存率更高。越来越多关于生物标志物的研究为改善癌症早期诊断和更好的治疗提供了积极证据。然而，仍有必要进一步研究用于癌症早期诊断、精准治疗和预测预后的精确生物标志物。在本研究中，已采用将生物信息学算法与微阵列和RNA测序（RNA-seq）基因表达（GE）数据相结合的人工智能辅助系统，基于miRNA-信使RNA（mRNA）相互作用网络预测用于CRC早期诊断的微小RNA（miRNA）生物标志物。在生物网络上进一步分析了预测的miRNA生物标志物与其他生物成分之间的关系。利用诊断试验的贝叶斯荟萃分析来验证miRNA候选生物标志物和组合的多个生物标志物的诊断价值。进行生物学功能分析以检测候选miRNA生物标志物与通路中已鉴定生物标志物的关系。文本挖掘用于分析预测的miRNA及其靶基因与5-氟尿嘧啶（5-FU）的关系。进行生存分析以评估这些miRNA在CRC中的预后价值。根据miRNA-mRNA网络上单个miRNA调控的mRNA数量（NSR）及其调控的转录因子基因百分比（TFP），选择了12个有前景的miRNA生物标志物。有5个潜在的候选miRNA（miRNA-186-5p、miRNA-10b-5、miRNA-30e-5p、miRNA-21和miRNA-30e）被确认为CRC诊断生物标志物，其中两个（miRNA-21和miRNA-30e）此前已有报道。此外，这5个候选miRNA生物标志物的组合对CRC早期诊断的预测准确性优于单个miRNA生物标志物。miRNA-10b-5p和miRNA-30e-5p通过靶向相关基因与5-FU治疗耐药性相关。这些miRNA生物标志物与CRC预后无统计学关联。
