肺動(dòng)脈高壓時(shí)肺血管內(nèi)皮間質(zhì)轉(zhuǎn)化相關(guān)miRNAs網(wǎng)絡(luò)調(diào)控的生物信息學(xué)分析

張衛(wèi)芳，熊愛珍，吳衛(wèi)華，祝田田，鄒小舟，劉　汀，胡長(zhǎng)平

(1.南昌大學(xué)第二附屬醫(yī)院藥學(xué)部，江西 南昌　330006；2. 中南大學(xué)藥學(xué)院藥理學(xué)系，湖南 長(zhǎng)沙　410078；3.湖南醫(yī)藥學(xué)院藥理學(xué)教研室，湖南 懷化　418000)

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肺動(dòng)脈高壓時(shí)肺血管內(nèi)皮間質(zhì)轉(zhuǎn)化相關(guān)miRNAs網(wǎng)絡(luò)調(diào)控的生物信息學(xué)分析

張衛(wèi)芳1,2，熊愛珍1，吳衛(wèi)華3，祝田田2，鄒小舟2，劉汀2，胡長(zhǎng)平2

(1.南昌大學(xué)第二附屬醫(yī)院藥學(xué)部，江西 南昌330006；2. 中南大學(xué)藥學(xué)院藥理學(xué)系，湖南 長(zhǎng)沙410078；3.湖南醫(yī)藥學(xué)院藥理學(xué)教研室，湖南 懷化418000)

目的探索肺動(dòng)脈高壓(pulmonary hypertension，PH)時(shí)肺血管內(nèi)皮間質(zhì)轉(zhuǎn)化(EndMT)相關(guān)miRNAs及其下游靶點(diǎn)的網(wǎng)絡(luò)調(diào)控。方法利用文獻(xiàn)挖掘PH相關(guān)基因及EndMT/EMT相關(guān)miRNAs。利用Biological General Repository for Interaction Datasets(BioGRID)數(shù)據(jù)庫(kù)得到基因相互作用關(guān)系。利用生物信息學(xué)(DIANA3、Miranda4、PicTar5、TargetScan6、miRDB7和microT-CDS8)預(yù)測(cè)相應(yīng)miRNAs的靶基因關(guān)系，超幾何分析預(yù)測(cè)與肺動(dòng)脈高壓EndMT相關(guān)miRNAs，通過對(duì)miRNAs參與功能分區(qū)中的情況篩選評(píng)分最高的miRNAs并選擇部分進(jìn)行實(shí)驗(yàn)驗(yàn)證，利用Cytocape 3軟件構(gòu)建miRNAs與其下游靶點(diǎn)的相互作用網(wǎng)絡(luò)。結(jié)果根據(jù)文獻(xiàn)挖掘出與PH有關(guān)的基因230個(gè)，與EndMT/EMT相關(guān)miRNAs共189個(gè)，對(duì)應(yīng)成熟體322個(gè)。其中98個(gè)miRNAs可能與PH時(shí)EndMT有關(guān)。其中，僅有22個(gè)miRNAs同時(shí)參與了TGF-β/BMP、低氧和炎癥3個(gè)功能通路，評(píng)分最高，分別為miR-let-7家族、miR-124、miR-130家族、miR-135、miR-144、miR-149、miR-155、miR-16-1、miR-17、miR-181家族、miR-182、miR-200家族、miR-204、miR-205、miR-21、miR-224、miR-27、miR-29家族、miR-301a、miR-31、miR-361和miR-375。對(duì)let-7g、miR-21、miR-124及miR-130家族進(jìn)行實(shí)時(shí)熒光定量PCR驗(yàn)證發(fā)現(xiàn)其在低氧誘導(dǎo)PH大鼠肺動(dòng)脈中表達(dá)均明顯變化。結(jié)論利用生物學(xué)信息技術(shù)從大量miRNAs中篩選得到的22個(gè)miRNAs同時(shí)參與TGF-β/BMP、低氧和炎癥信號(hào)通路，可能與PH時(shí)EndMT相關(guān)，為后續(xù)深入研究PH時(shí)EndMT提供了重要的理論依據(jù)。

肺動(dòng)脈高壓；miRNAs；內(nèi)皮間質(zhì)轉(zhuǎn)化；網(wǎng)絡(luò)調(diào)控；生物信息學(xué)；網(wǎng)絡(luò)藥理；相互作用

肺動(dòng)脈高壓(pulmonary hypertension，PH)主要特征為肺動(dòng)脈阻塞引起肺血管阻力及肺動(dòng)脈壓力漸進(jìn)性升高，伴隨不可逆的肺血管重構(gòu)，最終導(dǎo)致右心衰竭而死亡[1]。PH時(shí)肺血管重構(gòu)主要表現(xiàn)為內(nèi)膜增生、中膜肥厚、外膜增生、原位血栓、不同程度的炎癥以及叢狀動(dòng)脈樣改變[2-3]。PH時(shí)重構(gòu)的肺血管內(nèi)膜中α-SMA標(biāo)記的細(xì)胞明顯增加[1]。傳統(tǒng)的觀念認(rèn)為靜止的肺動(dòng)脈平滑肌細(xì)胞(pulmonary arterial smooth muscle cell，PASMCs)自身增殖是這些細(xì)胞的唯一來源。近期有學(xué)者在PH動(dòng)物模型和患者病變肺血管中發(fā)現(xiàn)了內(nèi)皮細(xì)胞間質(zhì)轉(zhuǎn)化(endothelial-mesenchymal transition, EndMT)的存在，并通過體外實(shí)驗(yàn)證實(shí)雷帕霉素可抑制各種因素誘導(dǎo)的肺血管EndMT[4-5]。提示，肺血管EndMT是肺血管重構(gòu)時(shí)α-SMA樣細(xì)胞的另一重要來源。進(jìn)一步探索PH時(shí)肺血管EndMT的病理機(jī)制，為尋找防治PH的新靶點(diǎn)和藥物具有重要意義。

微小非編碼RNA(microRNA，miRNA)是一類存在于真核生物中具有調(diào)控功能的非編碼小分子單鏈RNA，大約長(zhǎng)度為21～25 nt。大量研究表明其參與生命過程中一系列的重要進(jìn)程，包括個(gè)體發(fā)育、器官形成以及細(xì)胞增殖、死亡與分化等[6]。眾所周知，一個(gè)miRNA有多個(gè)靶點(diǎn)，一個(gè)基因又可被多個(gè)miRNAs調(diào)控，他們之間往往形成復(fù)雜的網(wǎng)絡(luò)調(diào)控機(jī)制參與疾病發(fā)生發(fā)展。因此，通過網(wǎng)絡(luò)藥理學(xué)技術(shù)探索相互作用網(wǎng)絡(luò)，而不是單一的研究某個(gè)miRNA或基因的功能，能更好地解釋miRNA或基因在疾病中的整體作用。

目前研究雖然提示miRNAs在PH的病理生理過程中扮演著重要的角色。但僅發(fā)現(xiàn)了少部分miRNAs在PH中起重要作用，且對(duì)于這類疾病分子機(jī)制的整體功能研究也尚在起步階段。鑒于PH時(shí)肺血管EndMT的機(jī)制尚不明確，本文擬運(yùn)用網(wǎng)絡(luò)藥理學(xué)方法探索與PH時(shí)肺血管EndMT相關(guān)miRNAs及其相關(guān)下游靶點(diǎn)的相互作用機(jī)制，為后續(xù)研究PH時(shí)肺血管EndMT的分子機(jī)制提供明確的方向及策略。

1　方法

1.1相關(guān)文獻(xiàn)篩查通過Medline(PubMed)搜索“pulmonary hypertension”，通過此我們尋找到與PH疾病相關(guān)的基因，我們稱為PH模塊。通過進(jìn)一步切換關(guān)鍵詞，包含“pulmonary hypertension”、“microRNA”、“miRNA”、“endothelial to mesenchymal transition”、“epithelial-mesenchymal transition”。搜索得到與PH時(shí)EMT/EndMT相關(guān)的miRNAs及EMT/EndMT相關(guān)的miRNAs。

1.2PH模塊網(wǎng)絡(luò)屬性評(píng)價(jià)從Medline(PubMed)基因數(shù)據(jù)庫(kù)中隨機(jī)選取與PH模塊個(gè)數(shù)相同的蛋白編碼基因，作為隨機(jī)網(wǎng)絡(luò)模塊。隨機(jī)網(wǎng)絡(luò)模塊重復(fù)選取3次。同時(shí)將PH模塊及隨機(jī)網(wǎng)絡(luò)模塊中的基因分別通過蛋白質(zhì)-蛋白質(zhì)相互作用軟件數(shù)據(jù)庫(kù)BioGRID(Biological General Repository for Interaction Datasets)數(shù)據(jù)庫(kù)得到各自模塊基因相互作用關(guān)系，并計(jì)算各自網(wǎng)絡(luò)的最大連接組件的“節(jié)點(diǎn)數(shù)”(largest connected component，LCC)和直接相互作用的“邊”(edges)。用Cytocape 3軟件做相互作用網(wǎng)絡(luò)圖，孤立的節(jié)點(diǎn)不在圖上畫出。

1.3miRNAs相關(guān)靶點(diǎn)分析通過生物信息數(shù)據(jù)庫(kù)(DIANA3、Miranda4、PicTar5、TargetScan6、miRDB7和microT-CDS8)進(jìn)行搜索得到相應(yīng)miRNAs靶基因關(guān)系。

1.4miRNAs富集分析及評(píng)分通過miRNAtap9工具包超幾何分析列表中每個(gè)miRNA的靶基因在PH模塊中的富集效應(yīng)。具體方法為選擇PH模塊中的230個(gè)基因作為基因集合，每個(gè)miRNAs預(yù)測(cè)得到的所有miRNAs為基因列表，以在2個(gè)或以上不同靶基因預(yù)測(cè)數(shù)據(jù)源中出現(xiàn)過的基因?yàn)槿炕虮尘埃穆?lián)表卡方分析，采用蒙特卡洛模擬方法計(jì)算確切顯著性概率值P值。對(duì)于在基因集合中出現(xiàn)基因列表中的基因的比例小于隨機(jī)概率的，P值賦予0.95，即直接認(rèn)定富集不顯著。校正P值計(jì)算用到BH(Benjamini Hochberg)方法。通過設(shè)定篩選條件[校正P值<0.05, 靶基因在基因集合中富集的基因個(gè)數(shù)(setsize)≥5]得出與PH時(shí)肺血管EndMT相關(guān)miRNAs。將參與PH疾病的功能通路主要分為TGF-β、低氧和炎癥，通過miRNAs基因靶點(diǎn)所屬功能類別進(jìn)一步對(duì)miRNAs進(jìn)行功能分類評(píng)分，篩選出評(píng)分較高的miRNAs，并用Cytocape 3軟件構(gòu)建miRNAs-靶點(diǎn)相互作用網(wǎng)絡(luò)圖。

1.5低氧大鼠PH模型建立清潔級(jí)Sprague-Dawley(SD)♂大鼠20只，合格號(hào)為scxk(湘)2009-0004，體質(zhì)量180～200 g，適應(yīng)性喂養(yǎng)1周后稱量體質(zhì)量、標(biāo)號(hào)；按體質(zhì)量隨機(jī)分為對(duì)照組(n=10)和低氧模型組(n=10)。對(duì)照組常氧下(21% O2)飼養(yǎng)；低氧模型組于低氧倉(cāng)中(10% O2，放有無水氯化鈣和鈉石灰分別用來吸收水分和CO2)飼養(yǎng)，兩組大鼠自由飲水、進(jìn)食。3周后頸靜脈插管分別檢測(cè)右心室收縮壓(right ventricular systolic pressure,RVSP)及肺動(dòng)脈平均壓(mean pulmonary artery pressure, mPAP)以確定造模是否成功。

1.6實(shí)時(shí)熒光定量PCR肺動(dòng)脈用液氮磨碎后加TRIzol。根據(jù)逆轉(zhuǎn)錄試劑盒(TaKaRa)說明書逆轉(zhuǎn)錄為cDNA。cDNA經(jīng)適當(dāng)稀釋后，用SYBR Premix Ex TaqⅡ試劑盒(TaKaRa)進(jìn)行實(shí)時(shí)熒光定量PCR。PCR反應(yīng)條件：95℃ 30 s，(95℃ 5 s，60℃ 31 s)40個(gè)循環(huán)。內(nèi)參選用U6，內(nèi)參及目的miRNAs引物由廣州銳博生物有限公司提供。

2　結(jié)果

2.1PH模塊建立通過Medline(PubMed)搜索pulmonary hypertension(2016年2月14日)，共50 307篇文獻(xiàn)，尋找到與PH疾病相關(guān)的基因共230個(gè)，我們將其稱為PH模塊。將這230個(gè)基因通過22個(gè)不同功能進(jìn)行分類并做相互作用關(guān)系圖(Fig 1A)。圖中每個(gè)節(jié)點(diǎn)表示一個(gè)基因，顏色為該基因?qū)?yīng)的功能；字體大小表示該節(jié)點(diǎn)的度的大小，度越大節(jié)點(diǎn)字體越大；每條邊的粗細(xì)表示該兩兩基因作用的研究報(bào)道支撐多寡，線條越粗則該兩兩作用在不同研究中報(bào)道的次數(shù)越多。分別計(jì)算PH模塊及隨機(jī)網(wǎng)絡(luò)模塊的網(wǎng)絡(luò)屬性得到PH模塊共有195個(gè)節(jié)點(diǎn)，LCC為76，Edges為727；隨機(jī)模塊LCC為3.7±3，Edges為36.7±3.5。PH模塊LCC及Edges顯著高于隨機(jī)網(wǎng)絡(luò)模塊(Fig 1B～C，P<0.01)。表明PH模塊具有巨大而稠密的相互關(guān)聯(lián)，是作為篩選相關(guān)miRNAs的理想模塊。

2.2與PH時(shí)EndMT相關(guān)的miRNAs通過Medline(PubMed)搜索得到PH時(shí)EndMT相關(guān)的文獻(xiàn)23篇；PH時(shí)EndMT相關(guān)miRNAs文獻(xiàn)0篇；EndMT/EMT有關(guān)的miRNAs文獻(xiàn)56篇(2016年2月14日)。通過閱讀摘要，必要時(shí)閱讀全文，得到相關(guān)miRNAs189個(gè)，對(duì)應(yīng)成熟體322個(gè)。通過富集分析發(fā)現(xiàn)可能與PH時(shí)EndMT相關(guān)的miRNAs共98個(gè)，將其稱為“目標(biāo)miRNAs”(Tab 1)。

Fig 1　The PH-network

2.3對(duì)目標(biāo)miRNAs進(jìn)行功能分類評(píng)分并進(jìn)行miRNAs-靶點(diǎn)網(wǎng)絡(luò)構(gòu)建由于“目標(biāo)miRNAs”數(shù)目較多，為了篩選評(píng)分最高的miRNAs，將參與PH疾病的功能通路主要分為TGF-β、低氧和炎癥并對(duì)得到的目標(biāo)miRNAs進(jìn)行功能分類。其中有22個(gè)miRNAs同時(shí)參與了TGF-β、低氧和炎癥3個(gè)功能通路，評(píng)分最高，它們分別是miR-let-7家族、miR-124、miR-130家族、miR-135、miR-144、miR-149、miR-155、miR-16-1、miR-17、miR-181家族、miR-182、miR-200家族、miR-204、miR-205、miR-21、miR-224、miR-27、miR-29家族、miR-301a、miR-31、miR-361和miR-375(Fig 2)。

Fig 2　A subset of miRNAs previously associated with hypoxia,inflammation and TGF-β is predicted to target PH network

miRNAtargetCntsetSizePvaluePadjustedlet-7a-3p2067450.00010.0021miR-130a-3p1677410.00010.0021miR-130b-3p1680420.00010.0021miR-139-5p401150.00010.0021miR-148a-5p1750400.00010.0021miR-181a-5p1286350.00010.0021miR-181b-5p1259340.00010.0021miR-181c-5p1285350.00010.0021miR-224-5p1476350.00010.0021miR-27a-3p2406490.00010.0021miR-338-5p2368570.00010.0021miR-33a-3p2386540.00010.0021miR-374a-3p1076290.00010.0021miR-42993351510.00010.0021miR-44887641480.00010.0021miR-56885281480.00010.0021miR-589-3p1693390.00010.0021miR-9-3p1819400.00010.0021miR-124-3p2340470.00020.0032miR-144-3p1627370.00020.0032miR-301a-3p1700410.00020.0032miR-320a2574530.00020.0032miR-129-5p2453500.00030.0039miR-135a-5p1497360.00030.0039miR-149-5p1783380.00030.0039miR-302a-5p1797390.00030.0039let-7b-3p2118440.00040.0044miR-106a-3p1086270.00040.0044miR-150-5p1470330.00040.0044miR-106a-5p2273460.00060.0059miR-200b-3p1928400.00060.0059miR-200c-3p1980410.00060.0059miR-33b-5p1032250.00060.0059miR-93-5p1178280.00070.0064miR-148a-3p1460320.00080.0066miR-199a-3p728190.00080.0066miR-506-3p2367460.00080.0066let-7g-3p1960400.00100.0075miR-590-3p4122710.00100.0075miR-126-5p2071410.00120.0084miR-200b-5p811210.00120.0084miR-490-5p442140.00120.0084miR-183-5p1134260.00130.0088let-7f-2-3p891220.00150.0096miR-186-5p3049550.00150.0096miR-17-5p1195270.00170.0106miR-200a-5p875220.00190.0113miR-29c-3p1704350.00200.0117miR-1371465310.00220.0123miR-20b-5p1199270.00220.0123miR-29b-3p1709350.00220.0123miR-19b-1-5p14270.00230.0128miR-29a-3p1703350.00250.0133miR-589-5p984230.00250.0133miR-16-1-3p461140.00260.0135miR-335-3p3510610.00260.0135

續(xù)表

miRNAtargetCntsetSizePvaluePadjustedmiR-3751357290.00260.0135miR-103a-3p2346440.00270.0136miR-6123297580.00270.0136miR-205-3p1004230.00310.0151miR-222-3p984220.00390.0178miR-374a-5p2011390.00390.0178miR-185-5p1674330.00430.0192miR-221-3p976220.00450.0196miR-92a-3p1504310.00450.0196miR-2061654330.00460.0197miR-26b-5p1740340.00460.0197miR-155-5p1225260.00470.0200miR-27a-5p736180.00490.0204miR-361-5p1307270.00500.0207miR-204-5p857200.00530.0216miR-9-5p2265420.00550.0222miR-491-5p872200.00570.0229miR-26a-5p1770340.00630.0249miR-34b-5p1307270.00630.0249miR-218-5p995220.00700.0271miR-409-3p726170.00750.0279miR-182-3p389110.00800.0294miR-205-5p1715330.00800.0294miR-1072650470.00810.0296miR-31-3p542140.00820.0297miR-127-5p1684320.00840.0303miR-155-3p557140.00930.0321miR-19b-3p1795340.00930.0321miR-21-5p788180.00930.0321let-7f-1-3p1305260.01050.0352miR-19a-3p1806340.01050.0352miR-204-3p1815340.01070.0353miR-21-3p1169240.01070.0353miR-29a-5p628150.01080.0353miR-590-5p987210.01080.0353let-7a-2-3p796180.01120.0358miR-34c-3p1337260.01320.0415miR-424-5p2959500.01390.0432miR-136-3p648150.01460.0444miR-382-5p1063220.01490.0451miR-424-3p25780.01650.0491

target Cnt: the number of all predicted targets;set size：the number of all predicted targets in PH model

2.4低氧PH模型大鼠構(gòu)建為進(jìn)一步驗(yàn)證生物信息學(xué)分析所得miRNAs，我們構(gòu)建了低氧誘導(dǎo)PH大鼠模型，探討miRNAs在肺動(dòng)脈中的表達(dá)變化。結(jié)果顯示，低氧模型組大鼠的RVSP及mPAP均顯著高于對(duì)照組(Fig 3，P<0.01)。提示：低氧PH模型大鼠構(gòu)建成功。

2.5實(shí)時(shí)熒光定量PCR驗(yàn)證隨機(jī)挑選在EMT和PH中作用均肯定的miRNAs 2個(gè)(miR-21、miR-124)、只在EMT中作用肯定的miRNAs 1個(gè)(let-7g)及只在PH中作用肯定的miRNAs 1個(gè)(miR-130家族)進(jìn)行實(shí)時(shí)熒光定量PCR初步驗(yàn)證。結(jié)果發(fā)現(xiàn)與對(duì)照組相比，低氧誘導(dǎo)PH大鼠肺動(dòng)脈中l(wèi)et-7g和miR-124表達(dá)明顯下調(diào)，miR-21、miR-130家族表達(dá)明顯上調(diào)(Fig 4，P<0.05)。進(jìn)一步提示通過生物信息學(xué)預(yù)測(cè)得到的let-7g、miR-21、miR-124、miR-130家族可能與低氧PH時(shí)EndMT有關(guān)。

Fig 3　Homodynamic index for hypoxia-induced PH rats(n=10)

**P<0.01vsControl

Fig 4　Change of miRNAs in pulmonary artery

*P<0.05,**P<0.01vsControl

2.6miRNAs-靶點(diǎn)網(wǎng)絡(luò)構(gòu)建對(duì)這22個(gè)miRNAs進(jìn)行miRNAs-靶點(diǎn)(PH網(wǎng)絡(luò)中的)網(wǎng)絡(luò)構(gòu)建，以直觀觀察該22個(gè)miRNAs在PH內(nèi)皮間質(zhì)轉(zhuǎn)化中可能發(fā)揮的整體作用(Fig 5)。

Fig 5　Predicted target network of 22 miRNA groups

3　討論

EndMT即在外界刺激及體內(nèi)微環(huán)境的影響下，單層內(nèi)皮細(xì)胞間固有的聯(lián)系遭到破壞，內(nèi)皮細(xì)胞失去原有的表型，獲得狹長(zhǎng)的間質(zhì)樣及肌成纖維細(xì)胞樣表型[7]。在EndMT過程中，內(nèi)皮細(xì)胞標(biāo)志蛋白(VE-cadherin, Tie-1/2, VEGFR1/2, PECAM/CD31)表達(dá)明顯下調(diào)，肌成纖維細(xì)胞和平滑肌細(xì)胞標(biāo)志蛋白波形蛋白(vimentin)和α-平滑肌肌動(dòng)蛋白(α-smooth muscle actin, α-SMA)表達(dá)增加。實(shí)驗(yàn)證據(jù)提示[8]，EndMT在心血管發(fā)育(包括肺動(dòng)脈發(fā)育)、各種血管疾病(如動(dòng)脈粥樣硬化和血管再狹窄時(shí)內(nèi)膜增生)以及傷口愈合中發(fā)揮重要作用。有學(xué)者發(fā)現(xiàn)在PH患者的肺動(dòng)脈內(nèi)膜中，同時(shí)存在著內(nèi)皮細(xì)胞和多功能間質(zhì)祖細(xì)胞，其中肌成纖維細(xì)胞在肺動(dòng)脈內(nèi)膜增生中發(fā)揮重要作用[9]；PH患者肺動(dòng)脈內(nèi)皮細(xì)胞形態(tài)發(fā)生改變，并且通過標(biāo)志蛋白的表達(dá)檢測(cè)發(fā)現(xiàn)有平滑肌樣細(xì)胞(即α-SMA標(biāo)記細(xì)胞)和小部分移行細(xì)胞(即內(nèi)皮樣細(xì)胞標(biāo)志蛋白和平滑肌樣細(xì)胞標(biāo)志蛋白同時(shí)出現(xiàn)的細(xì)胞)的存在[10]。提示EndMT可促進(jìn)α-SMA樣細(xì)胞在病變血管部位聚集從而參與PH時(shí)肺血管重構(gòu)。但PH時(shí)肺血管EndMT發(fā)生的機(jī)制尚不明確。

自2007年英國(guó)藥理學(xué)家Hopkins[11]率先提出“網(wǎng)絡(luò)藥理學(xué)”概念后，由于該方法成本較低，并可有效地幫助科研工作者從大數(shù)據(jù)中縮小范圍尋找靶標(biāo)，顯示出重要的理論和實(shí)際應(yīng)用價(jià)值。目前被迅速應(yīng)用于眾多領(lǐng)域的研究中，以探索miRNAs和基因在人類疾病中的整體作用。早在2012年便有學(xué)者運(yùn)用網(wǎng)絡(luò)藥理學(xué)的方法探索了與PH相關(guān)的miRNAs，并最終通過實(shí)驗(yàn)證實(shí)了miR-21在多種PH模型中表達(dá)上調(diào)并可通過抑制其靶點(diǎn)RhoB改善PH肺血管重構(gòu)，延緩病情的發(fā)展[12]。本文首次運(yùn)用網(wǎng)絡(luò)藥理學(xué)方法探索與PH時(shí)肺血管EndMT相關(guān)miRNAs及其相關(guān)下游靶點(diǎn)的相互作用機(jī)制，并通過實(shí)驗(yàn)對(duì)部分miRNAs進(jìn)行實(shí)驗(yàn)驗(yàn)證。其中l(wèi)et-7家族屬于腫瘤抑制因子，可通過HMGA2抑制多種腫瘤細(xì)胞的EMT[13]；miR-130可促進(jìn)多種類型的PH肺血管重構(gòu)[14]；miR-124及miR-21已確證參與了PH的發(fā)生發(fā)展，且參與了多種細(xì)胞的EndMT/EMT。PH時(shí)，miRNA124在肺動(dòng)脈外膜及肺組織中均表達(dá)下調(diào)，通過多個(gè)靶點(diǎn)(NFATc1、CAMTA1、PTBP1)抑制PASMCs的增殖和表型轉(zhuǎn)化及肺動(dòng)脈成纖維細(xì)胞的增殖、遷移和炎癥[15-16]。miR-124還可通過多個(gè)靶點(diǎn)(CDH2、RHOG)抑制TGF-β或低氧誘導(dǎo)的肺癌細(xì)胞[17]及視網(wǎng)膜色素上皮細(xì)胞[18]EMT。與其他學(xué)者結(jié)果一致，我們驗(yàn)證時(shí)發(fā)現(xiàn)低氧PH時(shí)let-7g下調(diào)而miR-130上調(diào)，這從側(cè)面反映了低氧PH時(shí)可能發(fā)生了EndMT。而miR-124在低氧誘導(dǎo)的肺動(dòng)脈中表達(dá)下調(diào)，提示其可能在PH時(shí)具有抑制肺血管EndMT的作用?？傊?，網(wǎng)絡(luò)藥理學(xué)方法不僅可通過生物信息學(xué)預(yù)測(cè)從而為后續(xù)的研究提供方向和策略，還可通過探究信號(hào)分子在疾病中的整體作用而解釋表面看似矛盾的結(jié)果。

對(duì)于本研究的實(shí)驗(yàn)驗(yàn)證，尚存在以下不足。首先，我們通過分子生物學(xué)實(shí)驗(yàn)驗(yàn)證了部分miRNAs在低氧PH大鼠肺動(dòng)脈中的表達(dá)變化，對(duì)于其它miRNAs如何改變未做探討；其次，我們僅在低氧誘導(dǎo)的PH模型中進(jìn)行了miRNAs驗(yàn)證而未涉及其他動(dòng)物模型如野百合堿誘導(dǎo)PH模型，而兩種模型代表的PH病理過程有差異；再次，肺動(dòng)脈由肺動(dòng)脈內(nèi)皮細(xì)胞、平滑肌細(xì)胞及成纖維細(xì)胞等多種細(xì)胞組成，我們僅檢測(cè)了miRNAs在肺動(dòng)脈中的表達(dá)變化，故這不足以說明其參與了PH時(shí)肺血管EndMT。因此，后續(xù)還需在多種動(dòng)物模型及細(xì)胞水平進(jìn)一步驗(yàn)證這些miRNAs在PH時(shí)肺血管EndMT的整體作用及機(jī)制。

(致謝：本文實(shí)驗(yàn)在中南大學(xué)藥學(xué)院藥理學(xué)系心血管藥理研究室完成。湖南醫(yī)藥學(xué)院藥理學(xué)教研室吳衛(wèi)華博士以及中南大學(xué)藥學(xué)院藥理學(xué)系博士生祝田田、鄒小舟、劉汀和碩士生葛曉月參與完成本文實(shí)驗(yàn)，并協(xié)助數(shù)據(jù)分析。)

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MicroRNAs integrates pathogenic signaling to control endothelial-mesenchymal transition in pulmonary hypertension: results of a network bioinformatic approach

ZHANG Wei-fang1,2, XIONG Ai-zhen1, WU Wei-hua3,ZHU Tian-tian2, ZOU Xiao-zhou2, LIU Ting2, HU Chang-ping2

(1.DeptofPharmacy,theSecondAffiliatedHospitalofNanchangUniversity,Nanchang330006,China；2.DeptofPharmacology,SchoolofPharmaceuticalSciences,CentralSouthUniversity,Changsha410078,China;3.DeptofPharmacology,HunanUniversityofMedicine,HuaihuaHunan418000,China)

AimTo explore micro RNAs-integrated pathogenic signaling to control endothelial-mesenchymal transition(EndMT) in pulmonary hypertension(PH) by a network bioinformatic approach.MethodsLiterature-mining method was used to find PH -related genes and EndMT/EMT-related miRNAs. Bioinformatic prediction approach(DIANA3,Miranda4,PicTar5,TargetScan6,miRDB7 and microT-CDS8) was used for miRNA target prediction. Hypergeometric analysis was used to predict miRNAs related to EndMT in PH. The analysis of interactions between PH-relevant genes(PH network) was performed with the use of Biological General Repository for Interaction Datasets(BioGRID). These miRNAs were ranked with the highest probability of substantial overlap among their gene targets in the PH-network, the relationship between their targets and the PH functional categories which include hypoxia, inflammation, and transforming growth factor/BMP signaling. Then, the part of results was validated by animal experiment. Lastly the miRNA-Target network was built using Cytocape 3.ResultsList of 230 genes was compiled that were directly implicated in the development of PH and 189 miRNAs were related to EndMT in PH. Among 189 miRNAs, only 22 microRNAs(miR-let-7 family, miR-124, miR-130 family, miR-135, miR-144, miR-149, miR-155, miR-16-1, miR-17, miR-181 family, miR-182, miR-200 family, miR-204, miR-205, miR-21, miR-224, miR-27, miR-29 family, miR-301a, miR-31, miR-361 and miR-375) were related to hypoxia, inflammation, and transforming growth factor/BMP signaling. Among these miRNAs, the levels of let-7g, miR-21, miR-124 and miR-130 family were significantly changed in the pulmonary artery in hypoxia-induced PH rats.ConclusionsAmong numerous miRNAs，22 of which may be involved in hypoxia, inflammation, and transforming growth factor/BMP signaling and related to EndMT in PH by network bioinformatic approach, which provides a theoretical basis for further investigation of EndMT in PH.

pulmonary hypertension; miRNAs; EndMT; network regulation; bioinformatics; network pharmacology;interaction

2016-05-23,

2016-06-25

國(guó)家自然科學(xué)基金資助項(xiàng)目(No 81273512，81473209，91439105，81460010)；江西省科技廳青年科學(xué)基金(No 20142BAB215035)；南昌大學(xué)第二附屬醫(yī)院院內(nèi)課題(No 20142YNQN12018)

張衛(wèi)芳(1987-)，女，博士，研究方向：心血管藥理學(xué)，E-mail：z_weifang@163.com;

胡長(zhǎng)平(1969-)，男，教授，博士生導(dǎo)師，研究方向：心血管藥理學(xué)，通訊作者，E-mail: huchangping@yahoo.com

10.3969/j.issn.1001-1978.2016.09.021

A

1001-1978(2016)09-1294-07

R322.12；R318.04；R329.2；R342.2；R394.2； R544

網(wǎng)絡(luò)出版時(shí)間：2016-8-23 14:29:00網(wǎng)絡(luò)出版地址：http://www.cnki.net/kcms/detail/34.1086.R.20160823.1429.042.html