侵袭性垂体腺瘤中lncRNA-mRNA的共表达网络

蒋国庆; 邓兴力; 李晓娟; 钱源

doi:10.12259/j.issn.2095-610X.S20201214

侵袭性垂体腺瘤中lncRNA-mRNA的共表达网络

doi: 10.12259/j.issn.2095-610X.S20201214

蒋国庆¹,
邓兴力²,
李晓娟¹,
钱源^{3, 4, 5, ,}

1.
昆明医科大学第一附属医院产科
2.
神经外科
3.
检验科
4.
云南省检验医学重点实验室
5.
临床检验诊断云南省创新团队，云南昆明　650032

基金项目: 国家自然科学基金资助项目（81760273）；云南省卫生科技计划基金资助项目（2018NS0112）；省部共建云南生物资源保护与利用国家重点实验室开放课题计划基金资助项目（2018KF006）；昆明市科技计划基金资助项目（2019-1-S-25318000001501）

详细信息

作者简介:
蒋国庆（1994～），男，安徽六安人，在读硕士研究生，主要从事产科妊娠相关疾病研究工作

通讯作者:
钱源，E-mail： yuanqian2x@hotmail.com

中图分类号: R736.4
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出版历程
- 收稿日期: 2020-03-14
- 刊出日期: 2019-12-26

Analysis of lncRNA-mRNA Co-expression Network in Invasive Pituitary Adenomas

1.
Dept. of Obstetrics
2.
Dept. of Neurosurgery
3.
Dept. of Clinical Laboratory，The 1st Affiliated Hospital of Kunming Medical University
4.
Yunnan Provincial Key laboratory of Laboratory Medicine
5.
Yunnan Innovation Team of Clinical Laboratory and Diagnosis，Kunming Yunnan 650032，China

摘要

摘要: 目的利用二代测序技术筛选侵袭性垂体腺瘤组织中差异表达的lncRNA，分析其在侵袭性垂体腺瘤发病机制中可能发挥的潜在作用。方法通过RNA测序分析4例侵袭性垂体腺瘤患者和3例非侵袭性垂体腺瘤患者的lncRNA和mRNA的表达情况，筛选出差异表达的lncRNA和mRNA。据此，构建lncRNA-mRNA共表达网络，并进行GO和KEGG通路分析。结果对侵袭性和非侵袭性垂体瘤的lncRNA和mRNA差异表达分析，共获得35个差异表达的lncRNA和463个差异表达的mRNA。共表达网络显示FAM66A、TPTEP1、AC017116.11、RP11-1114A5.4和RP11-246K15.1在网络中处于关键位置。结论 lncRNA-mRNA共表达网络的建立，发现一些差异表达的lncRNA可能在侵袭性垂体腺瘤的发病机制中发挥关键作用，可能成为侵袭性垂体腺瘤新的诊断标志物和治疗靶点。
- 侵袭性垂体腺瘤 /
- 长链非编码（lncRNA） /
- RNA测序 /
- lncRNA-mRNA共表达
Abstract: Objective To screen differentially expressed lncRNAs in invasive pituitary adenomas by second-generation sequencing, and to explore their potential role in the pathogenesis of invasive pituitary adenomas. Methods The expressions of lncRNA and mRNA in 4 patients with invasive pituitary adenoma and 3 patients with non-invasive pituitary adenoma were analyzed by RNA sequencing to single out the differentially expressed lncRNA and mRNA. Accordingly, lncrNA-mRNA co-expression networks were constructed and GO and KEGG pathways were analyzed. Results A total of 35 differentially expressed lncRNAs and 463 differentially expressed mRNAs were obtained by analyzing the differentially expressed lncRNAs and mRNAs in both invasive and non-invasive pituitary tumors. The co-expression network showed that FAM66A, TPTEP1, AC017116.11, RP11-1114A5.4 and RP11-246K15.1 were in a key position in the network. Conclusion Through the establishment of co-expression network of lncRNA-mRNA, we found that some new lncRNA may play a key role in the pathogenesis of invasive pituitary adenomas and may be used as novel biomarkers of invasive pituitary adenomas.
- Invasive pituitary adenoma /
- long noncoding RNA /
- RNA sequencing /
- lncRNA-mRNA co-expression network

HTML全文

图 1 差异表达基因的聚类热图（红色代表高表达，蓝色代表低表达）

A：为差异表达的lncRNA热图；B：为差异表达的mRNA热图。

Figure 1. Cluster heat map of differentially expressed genes（Red represents high expression and blue represents low expression）

下载: 全尺寸图片幻灯片

图 2 lncRNA-mRNA共表达网络

菱形代表lncRNA，圆形代表mRNA；红色表示上调，绿色表示下调，图形的大小代表Degree。

Figure 2. lncRNA-mRNA co-expression network

下载: 全尺寸图片幻灯片

图 3 GO富集分析结果

A：BP、CC和MF富集排名前十的柱状图；B：BP、CC和MF富集排名前十的气泡图。

Figure 3. GO enrichment analysis results

下载: 全尺寸图片幻灯片

图 4 KEGG富集分析结果

A：KEGG富集排名前十的柱状图；B：富集排名前十的气泡图。

Figure 4. KEGG enrichment analysis results

下载: 全尺寸图片幻灯片

表 1 差异表达的lncRNA

Table 1. Differentially expressed lncRNAs

基因名	Log2（Foldchange）	P	异常表达情况
RP11-252P19.2	7.110230855	0.025594461	上调
LINC00473	6.892052835	0.000316802	上调
STXBP5-AS1	5.640589233	0.007878966	上调
RP11-71H17.7	5.221628067	0.017764884	上调
TPTEP1	4.89206949	0.003097546	上调
RP11-262H14.3	3.952787834	0.03606433	上调
RP11-12O16.1	2.807343125	0.011324588	上调
RP11-111M22.3	2.28836899	0.002792906	上调
RP11-250B2.3	1.906609127	0.035774432	上调
FAM66A	1.848133787	0.002209197	上调
RP11-262H14.4	1.813382724	0.009868508	上调
CTD-3193K9.4	1.721455664	0.001307362	上调
MAFG-AS1	1.536359193	0.044840975	上调
SNHG8	1.461730762	0.049804872	上调
AC139100.4	1.448409941	0.045905713	上调
FAM27C	1.415494365	0.029287703	上调
AC005062.2	1.349936987	0.033475711	上调
RP11-646I6.5	1.272730756	0.046225249	上调
RN7SL674P	1.260917811	0.008860604	上调
RP11-662M24.2	1.188403274	0.037409712	上调
LRRC75A-AS1	1.042079322	0.002182732	上调
ZFAS1	−1.030295183	0.02204746	下调
TP53TG1	−1.093552638	0.027463784	下调
CTB-129O4.1	−1.167587296	0.041920971	下调
RP11-1020A11.1	−1.227419109	0.025518005	下调
AP006621.5	−1.265098387	0.004293786	下调
C5orf66	−1.323699343	0.024003471	下调
RP11-1114A5.4	−1.346165585	0.036015113	下调
AC017116.11	−1.355620383	0.018311217	下调
AC019181.2	−1.556768999	0.031834266	下调
UMAD1	−2.049223764	0.026775377	下调
AC005618.6	−2.103056949	0.012754031	下调
SOCS2-AS1	−2.450904018	0.010320293	下调
RP11-246K15.1	−3.394395932	0.006322703	下调
ARMCX5-GPRASP2	−3.509890448	0.042606052	下调

下载: 导出CSV

表 2 排名前20的差异表达的mRNA

Table 2. The top 20 differentially expressed mRNA

mRNAs基因名	Log2（Foldchange）	P	异常表达情况
SLC4A3	3.130642688	0.000067700	上调
ZNF444	1.555389418	0.000111993	上调
HDAC4	2.871048277	0.000146683	上调
MRO	−3.344017691	0.000209461	下调
ECHDC1	10.92744203	0.000217674	上调
KIAA1958	−1.739496332	0.000224985	下调
TBC1D5	22.81214317	0.000254824	上调
NCALD	2.281098096	0.000325798	上调
LAMTOR5	−4.230692295	0.000366157	下调
TMPRSS6	7.265115275	0.000399492	上调
RPL26	−4.965389762	0.000462772	下调
RPSA	2.332207622	0.000464748	上调
CTSC	1.469599612	0.000464889	上调
MYO10	4.166108193	0.000472723	上调
ATP6AP2	3.197467642	0.000514505	上调
EPHX2	2.326018659	0.000616419	上调
PARP11	−1.579039067	0.000625344	下调
AGTRAP	1.045079801	0.000845595	上调
MXRA7	−1.391168544	0.000967649	下调
SLC29A2	−9.596231979	0.001050552	下调

下载: 导出CSV

表 3 Degree排名前五的lncRNA

Table 3. The top 5 lncRNAs in Degree

基因名	Degree
FAM66A	52
TPTEP1	42
AC017116.11	33
RP11-1114A5.4	29
RP11-246K15.1	28

下载: 导出CSV

参考文献(15)

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