Sun Desheng, Zhong Jieyu, Wei Wei, Liu Li, Liu Jun, Lin Xiaona
Department of Ultrasonography, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P.R. China.
Department of Breast Surgery, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P.R. China.
Oncol Lett. 2020 Nov;20(5):188. doi: 10.3892/ol.2020.12050. Epub 2020 Sep 3.
Long non-coding RNAs (lncRNAs) participate in various biological processed involved in tumorigenesis, metastasis and proliferation. The aim of the present study was to identify candidate long non-coding RNAs (lncRNAs) involved in sentinel lymph node (SLN) metastasis in breast cancer. Specimens of SLNs were collected from patients with SLN metastasis via punch biopsy. Total RNA was extracted and RNA sequencing (RNA-seq) was conducted. Differential expression profiles of mRNAs and lncRNAs were obtained via bioinformatics analysis, and Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on differentially expressed mRNAs. The expression levels of lncRNAs were analyzed via reverse transcription-quantitative PCR (RT-qPCR), and the regulation network of the lncRNAs to downstream microRNAs (miRs) and mRNAs was predicted. Based on RNA-seq results, six differentially expressed candidate lncRNAs were identified in patients with and without SLN metastasis: lnc-ANGPTL1-3:3, lnc-GJA10-12:1, lnc-ACAN-2:1, lnc-ZPBP2-4:1, lnc-GATA3-16:1 and lnc-ACOX3-5:1. KEGG and GO analysis identified that the mitogen-activated protein kinase (MAPK) and PI3K/Akt signaling pathways were the most enriched pathways. After RT-qPCR analysis, lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 exhibited expression patterns that were consistent with those from RNA-seq. Moreover, receiver operating characteristic curve analysis demonstrated that lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 expression levels had high sensitivity and specificity in the diagnosis of SLN metastasis, and that their expression levels were upregulated in patients with axillary lymph node metastasis. Further analysis revealed that lnc-GJA10-12:1 and lnc-ANGPTL1-3:3 were commonly involved in regulating the miR-302 family, including miR-302d-3p and miR-302c-3p, which together targeted AKT1. Additionally, lnc-ANGPTL1-3:3 was predicted to target miR-520b to regulate MAP3K2 expression. lnc-GJA10-12:1 was also predicted to target miR-34a-5p to regulate MAP2K1 and MAP3K9 expression levels, as well as miR-449a to regulate MAP2K1 expression. The results of the present study suggested that lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 may potentially serve a role in SLN metastasis of breast cancer by regulating the PI3K/Akt and MAPK signaling pathways via targeting the miR-302 family, miR-520a-3p, miR-34a-5p and miR-449a. Thus, lnc-ANGPTL1-3:3 and lnc-GJA10-12:1 in SLN may serve as potential markers of breast cancer metastasis.
长链非编码RNA(lncRNAs)参与肿瘤发生、转移和增殖过程中的各种生物学过程。本研究旨在鉴定参与乳腺癌前哨淋巴结(SLN)转移的候选长链非编码RNA(lncRNAs)。通过穿刺活检从发生SLN转移的患者中收集SLN标本。提取总RNA并进行RNA测序(RNA-seq)。通过生物信息学分析获得mRNA和lncRNA的差异表达谱,并对差异表达的mRNA进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析。通过逆转录定量PCR(RT-qPCR)分析lncRNAs的表达水平,并预测lncRNAs对下游微小RNA(miRs)和mRNA的调控网络。基于RNA-seq结果,在有和没有SLN转移的患者中鉴定出6种差异表达的候选lncRNAs:lnc-ANGPTL1-3:3、lnc-GJA10-12:1、lnc-ACAN-2:1、lnc-ZPBP2-4:1、lnc-GATA3-16:1和lnc-ACOX3-5:1。KEGG和GO分析确定丝裂原活化蛋白激酶(MAPK)和PI3K/Akt信号通路是最富集的通路。RT-qPCR分析后,lnc-ANGPTL1-3:3和lnc-GJA1-12:1表现出与RNA-seq一致的表达模式。此外,受试者工作特征曲线分析表明,lnc-ANGPTL1-3:3和lnc-GJA10-12:1的表达水平在SLN转移诊断中具有高敏感性和特异性,且其表达水平在腋窝淋巴结转移患者中上调。进一步分析显示,lnc-GJA10-12:1和lnc-ANGPTL1-3:3共同参与调控miR-302家族,包括miR-302d-3p和miR-302c-3p,它们共同靶向AKT1。此外,预测lnc-ANGPTL1-3:3靶向miR-520b以调控MAP3K2表达。lnc-GJA10-12:1还被预测靶向miR-34a-5p以调控MAP2K1和MAP3K9表达水平,以及靶向miR-449a以调控MAP2K1表达。本研究结果表明,lnc-ANGPTL1-3:3和lnc-GJA10-12:1可能通过靶向miR-302家族、miR-520a-3p、miR-34a-5p和miR-449a调控PI3K/Akt和MAPK信号通路,从而在乳腺癌SLN转移中发挥作用。因此,SLN中的lnc-ANGPTL1-3:3和lnc-GJA10-12:1可能作为乳腺癌转移的潜在标志物。