CN114480639B - 新靶点用于诊断和治疗垂体腺瘤 - Google Patents

新靶点用于诊断和治疗垂体腺瘤 Download PDF

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CN114480639B
CN114480639B CN202111604335.0A CN202111604335A CN114480639B CN 114480639 B CN114480639 B CN 114480639B CN 202111604335 A CN202111604335 A CN 202111604335A CN 114480639 B CN114480639 B CN 114480639B
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常梦琪
王子豪
张彦若
高俊
王任直
幸兵
马文斌
王裕
娄继忠
周刚
包新杰
刘芃昊
王月坤
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Peking Union Medical College Hospital Chinese Academy of Medical Sciences
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Abstract

本发明公开了EC和/或CAF细胞在制备诊断垂体腺瘤的产品中的应用。EC和CAF相关marker在垂体腺瘤硬肿瘤中表达显著升高,可以作为肿瘤硬度鉴定的标志物。通过数据库预测和验证实验证明了VEGFR和PDGFR的抑制剂在治疗硬肿瘤中的作用,有望作为临床治疗药物,为解决硬肿瘤切除率低的难题提供了解决办法。

Description

新靶点用于诊断和治疗垂体腺瘤
技术领域
本发明涉及生物医药技术领域,具体涉及新靶点用于诊断和治疗垂体腺瘤。
背景技术
垂体腺瘤(pituitary adenoma,PA)是第二常见的颅内肿瘤,约占原发性肿瘤的15%[1]。在过去的几十年里,经蝶窦手术一直是PA的一线治疗方法,肿瘤全切率是影响患者预后最重要的因素[2-4]。然而,PA患者中只有66-78%的患者能获得完全的切除。有许多肿瘤残余的患者肿瘤反复复发,10年复发率高达7-12%[5,6]。因此,力求术中肿瘤全切除和探索新的靶向药物成为减少复发和治疗PA患者的主要方向。由于PA所在鞍区的解剖结构复杂,视野有限,对于质地坚硬、体积大、海绵窦浸润的垂体肿瘤,很难将其完全切除。随着内镜手术系统的迅速发展,肿瘤硬度已成为影响手术切除率的关键因素[7,8]。对于软肿瘤,即使体积较大且侵犯海绵窦,也可以很容易地通过吸力刮除,通常有较好的手术预后。对于质地坚硬、体积大、海绵窦浸润的垂体肿瘤,单纯手术治疗难以将其完全切除。目前的治疗方法无法改变肿瘤的硬度,提高肿瘤全切率。
因此,更好地了解肿瘤硬化的潜在机制,并探索改善肿瘤硬度的药物,对于提高PA患者的预后非常重要。
相关文献如下,
1.Ostrom,Q.T.et al.CBTRUS statistical report:primary brain andcentral nervous system tumors diagnosed in the United States in 2007-2011.Neuro Oncol 16Suppl 4,iv1-63(2014).
2.Molitch,M.E.Diagnosis and Treatment of Pituitary Adenomas:AReview.Jama 317,516-524(2017).
3.Almutairi,R.D.et al.Gross total resection of pituitary adenomasafter endoscopic vs.microscopic transsphenoidal surgery:a meta-analysis.ActaNeurochir(Wien)160,1005-1021(2018).
4.Tabaee,A.et al.Endoscopic pituitary surgery:a systematic review andmeta-analysis.J Neurosurg 111,545-54(2009).
5.Salomon,M.P.et al.The epigenomic landscape of pituitary adenomasreveals specific alterations and differentiates among acromegaly,cushing'sdisease and endocrine-inactive subtypes.Clin Cancer Res 24,4126-4136(2018).
6.Reddy,R.et al.Can we ever stop imaging in surgically treated andradiotherapy-naive patients with non-functioning pituitary adenoma?EurJEndocrinol 165,739-44(2011).
7.Zhao,B.et al.Extended transsphenoidal approach for pituitaryadenomas invading the anterior cranial base,cavernous sinus,and clivus:asingle-center experience with 126consecutive cases.J Neurosurg 112,108-17(2010).
8.Sughrue,et al.Excess mortality for patients with residual diseasefollowing resection of pituitary adenomas.Pituitary 14,276-83(2011).
发明内容
为了解决上述技术问题,本发明的目的在于提供一种鉴别区分垂体腺瘤硬肿瘤和软肿瘤的标志物,用于制备鉴别区分硬肿瘤的产品。
本发明另一目的在于提供一种治疗垂体腺瘤的药物或改善垂体腺瘤肿瘤硬度的药物,所述药物包括抑制VEGF、PDGF和/或FGF通路的化合物。
为实现上述目的,本发明具体技术方案如下:
本发明通过Illumina二代测序技术高通量获取垂体腺瘤硬肿瘤和软肿瘤组织的差异表达谱,通过ssGSEA量化分析发现,EC和CAF细胞含量在垂体腺瘤硬肿瘤中显著升高,可作为硬肿瘤或肿瘤硬度的标志物。进一步发明人通过免疫荧光染色发现垂体腺瘤硬肿瘤中EC和CAF细胞相关标志的表达水平升高。进一步,通过基因共表达网络分析,将相似性最高的特征基因进行聚类,进而通过Pearson相关性分析筛选与肿瘤硬度关联最大的特征基因模块。利用特征基因,通过cMAP分析查询肿瘤硬度相关的潜在靶向药物,利用细胞系和大鼠成瘤模型进行验证,证明根据肿瘤硬度相关基因预测得到的小分子抑制剂具有逆转肿瘤硬化的作用。
基于此,本发明第一方面提供了EC和/或CAF细胞在制备诊断垂体腺瘤的产品中的应用。
优选地,所述诊断包括用EC和/或CAF细胞鉴别区分软肿瘤和硬肿瘤。
与软肿瘤相比,所述EC或CAF的细胞含量在硬肿瘤中升高。
优选地,所述EC细胞的检测标志物包括αSMA和S100A4;所述CAF细胞的检测标志物包括CD31和VWF。
第二方面,本发明提供了一种鉴别区分垂体腺瘤硬肿瘤和软肿瘤的试剂盒,所述试剂盒包括定量检测EC和/或CAF细胞含量的鉴定试剂。
优选地,所述定量检测EC细胞的鉴定试剂包括定量检测αSMA和/或S100A4表达的试剂;所述定量检测CAF含量的鉴定试剂包括定量检测CD31和/或VWF表达的试剂。
优选地,定量检测αSMA、S100A4、CD31和VWF表达的试剂包括引物、探针和/或抗体;优选地,抗体。
优选地,本发明通过免疫荧光染色检测来自受试者样品中肿瘤硬度相关标志,包括αSMA、S100A4、CD31和VWF的表达水平;与软肿瘤相比,肿瘤硬度相关标志的表达水平上调,确定受试者肿瘤质地为硬肿瘤。
第三方面,本发明提供了药物干预靶点在治疗垂体腺瘤的药物中的应用,所述药物干预靶点包括VEGF、PDGF和/或FGF通路。
优选地,所述药物包括基因敲除技术对所述VEGF、PDGF或FGF通路进行阻断干预或通过VEGF、PDGF和/或FGF的抑制剂进行阻断干预的药物。
优选地,所述VEGF、PDGF和/或FGF的抑制剂包括阿西替尼、帕佐帕尼、索拉非尼和舒尼替尼。
第四方面,本发明提供了一种改善垂体腺瘤肿瘤硬度的药物组合物,所述药物组合物包括抑制VEGF、PDGF和/或FGF的化合物;优选地,所述化合物包括小分子抑制剂。
基于上述技术方案,本发明具有以下有益效果:
本发明通过实验发现,EC和CAF相关marker在垂体腺瘤硬肿瘤中表达显著升高,可以作为肿瘤硬度鉴定的标志物,并用于制备诊断垂体腺瘤的产品。通过数据库预测和验证实验证明了靶向VEGFR和PDGFR的抑制剂在治疗硬肿瘤中的作用,有望作为临床治疗药物,为解决硬肿瘤切除率低的难题提供了解决办法。
附图说明
图1肿瘤硬度相关的细胞检测。软肿瘤和硬肿瘤的内皮细胞、淋巴内皮细胞、微血管内皮细胞和CAF的比较。
图2肿瘤硬度相关标志物验证。左图:软肿瘤和硬肿瘤中CAF标记物(αSMA和S100A4)和EC标记物(CD31和VWF)的免疫荧光染色(绿色)。细胞核DAPI染色(蓝色)。比例尺:50μm。右图:4种细胞标记物荧光强度的定量分析。a.u任意单位。*P<0.05,**P<0.01,***P<0.001。
图3鉴定与垂体腺瘤肿瘤硬度高度相关的基因。(A)火山图显示硬肿瘤和软肿瘤之间的差异基因。虚线右侧代表硬肿瘤中上调基因,虚线左侧代表下调基因。(B)簇状树状图表示差异基因的聚类分析。上面部分:每个分支代表一个基因。下面部分:每个色块代表一个共表达模块。(C)热图显示每个基因模块与PA患者临床特征的相关性。绿松石(turquoise)模块是最为关键的模块,该模块基因表达与硬度、一般内皮细胞、淋巴内皮细胞、微血管内皮细胞和CAF含量呈正相关。
图4垂体腺瘤硬肿瘤靶向治疗药物的预测。(A)基于SRG的cMap分析可用于降低肿瘤硬度的候选药物和分子途径的探索。(B)软肿瘤和硬肿瘤中VEGF、PDGF、FGF和RTK信号通路ssGSEA富集评分比较。(C)比较阿西替尼、帕佐帕尼、索拉非尼和舒尼替尼在软肿瘤和硬肿瘤中治疗的IC50值。
图5舒尼替尼在体外和体内抑制了PA的生长,并降低了垂体腺瘤动物模型的肿瘤硬度。(A)舒尼替尼或DMSO处理2天的GH3细胞的细胞活力检测。***P<0.001。均值±标准差。(B)连续12天给药过程中的肿瘤体积。(C)舒尼替尼或对照剂治疗大鼠肿瘤重量。**P<0.01.(D)肿瘤取材的照片。比例尺:1厘米。(E)连续12天测定大鼠体重。“NS”表示组间无显著差异。(F&G)统计直方图显示舒尼替治疗组(F)和对照组(G)肿瘤组织的所有记录点的杨氏模量。舒尼替治疗组0.85±0.34kPa;对照组的0.90±0.03kPa。E(kPa)表示每个样品中痕量的杨氏模量。
具体实施方式
以下实施例用于说明本发明,但不用来限制本发明的范围。若未特别指明,实施例中所用的技术手段为本领域技术人员所熟知的常规手段。
下述实施例所使用的实验方法如无特殊说明,均为常规方法。
下述实施例中所有的材料、试剂等,如无特殊说明,均可从商业途径获得。
实施例1组织总RNA提取及质量监控
收集垂体腺瘤临床标本,包括11例软肿瘤和11例硬肿瘤。标本于2017年-2018年收集,来自北京协和医院神经外科。将适当大小的垂体腺瘤组织放入Ep管中,加200μl Trizol试剂,使用电动组织研磨器充分研磨组织。之后添加800μl Trizol,震荡混合均匀,置于旋转摇床上20-40r/min孵育10min。加入200μl氯仿,混合均匀,冰上孵育10min,4℃离心15min。小心吸取上层清液约500μl至新的EP管中,加500μl异丙醇,混匀,-80℃沉淀。13,300rpm 4℃离心30min,去除上清;加入1ml 75%的乙醇,吹打沉淀至飘浮,13,300rpm 4℃离心5min,去除上清。重复该步骤一次。将Eppendorf管置于含有滤纸的干燥盒里室温放置干燥8min,加20-30μl RNase free water溶解。使用NanoPhotometer检测浓度,根据260/230和260/280判断RNA纯度。用1%琼脂糖凝胶电泳检测RNA的完整性。
实施例2基因测序及细胞成分分析
测序:采用Illumina二代测序技术高通量检测垂体腺瘤硬肿瘤和软肿瘤组织的RNA。获取差异表达谱,并进行RNA表达数据的处理分析。
通过ssGSEA量化分析发现,在所有PA样本的细胞成分中,内皮细胞(EndothelialCell,EC)和肿瘤相关成纤维细胞(Cancer-associated Fibroblast,CAF)在硬肿瘤中的含量明显高于软肿瘤,其中所述EC包括普通EC、淋巴EC、微血管EC(图1)。这些结果表明,基质细胞,特别是EC和CAF可能在促进PA的硬化中起关键作用。
实施例3免疫荧光检测肿瘤硬度相关的基因
本实施例中使用的一抗体如下:
anti-smooth muscle actin-α(αSMA)(Bioss bs-3759R);anti-S100A4(Proteintech 60188-1-IG);anti-CD31(Abcam ab28364);anti-von Willebrand factor(VWF)(Bioss bs-10048R)。
本发明进行了CAF标记物(αSMA和S100A4)和EC标记物(CD31和VWF)的免疫荧光染色(图2左),并统计了两组间蛋白表达的差异(图2右)。结果如图2所示,在硬肿瘤中αSMA、S100A4、CD31和VWF的蛋白表达水平明显高于软肿瘤,提示硬肿瘤中有更多的CAF和EC。
所述免疫荧光染色方法:对肿瘤组织进行福尔马林固定石蜡包埋(FFPE)切片免疫荧光(IF)染色。首先,FFPE组织被切成4μm的切片,然后用二甲苯和乙醇脱烃和复水。接下来,将载玻片在亚沸点温度下置于EDTA抗原回收缓冲液中孵育,然后放入阻断液(CSA IIKit;丹麦Glostrup Dako)室温下烤30分钟。载玻片与一抗anti-CD31、anti-vonWillebrand factor、anti-smooth muscle actin-α和anti-S100A4抗体孵育,然后与带有荧光的二抗在室温下孵育50分钟。DAPI染细胞核。使用Ortho荧光显微镜拍照。所有图像采用NIH ImageJ 1.51s分析软件定量,每个图像使用相同的阈值。
实施例4肿瘤硬度相关基因鉴定
本发明通过Illumina二代测序技术高通量共鉴定了1288个软肿瘤和硬肿瘤之间的差异表达基因(DEG),然后为了确定DEG的表型相关性,发明人使用WGCNA分析来确定与肿瘤硬度相关的关键的基因模块,进而对模块与临床性状的相关性进行分析筛选与肿瘤硬度最相关的基因模块。
具体的,用R中的WGCNA工具包构建DEG的共表达网络。首先进行样本聚类,检测离群点。采用pickSoftThreshold方法选择一个合适的软阈值(功率)来实现scale-freetopology fit index>0.85,保持最佳的平均连通性。然后将邻接矩阵转化为拓扑重叠矩阵(TOM),定义基因共表达相似性,并对基于TOM的相似性进行基因层次聚类,得到层次聚类树状图。利用Dynamic Tree Cut软件包对最小基因大小为50的模块进行识别,计算模块特征基因(MEs)的相似性后,将相似性的cut off值设为0.75,合并模块,代表每个模块的总体表达谱。采用Pearson相关分析确定各模块MEs之间的邻接关系。
结果显示,本发明鉴定了1288个软肿瘤和硬肿瘤之间的差异表达基因(DEG),其中硬肿瘤中有759个上调基因和529个下调基因(图3A)。之后得到一个层次聚类树状图,生成12个基因模块(图3B)。其中,131个基因组成的绿松石(turquoise)模块与肿瘤硬度(R=0.84,P=1×10-05)、普通EC(R=0.90,P=2×10-07)、淋巴EC(R=0.94,P=4×10-10)、微血管EC(R=0.94,P=2×10-09)、CAF(R=0.70,P=0.003)呈正相关(图3C)。绿松石模块基因与肿瘤硬度、EC和CAF的高度相关性,表明绿松石模块基因在肿瘤硬度调控中的重要性。因此,这131个绿松石模块代表的基因被定义为肿瘤硬度相关基因(Stiffness RelatedGene,SRG)。
实施例5鉴定治疗垂体腺瘤的潜在药物
通过对SRG和相关分子路径的cMAP数据库分析,探索可能用于处理硬PA的化合物。
设定cut off值enrichment scores<-95,P<0.05,筛选获得富集的通路(mode ofaction,以下简称MoA)揭示靶向硬肿瘤的化合物及其所在的分子通路,发现在硬肿瘤中36种化合物靶向的35个分子通路(图4A)。发明人筛选了富集程度高和关键的MoA,包括作为PDGFR抑制剂的14种化合物组成的MoA,作为PDGFR抑制剂的7种化合物组成的MoA和作为FGFR的抑制剂的3种化合物组成的MoA,其中PDGFR抑制剂的14种化合物组成的MoA是富集程度最高和最关键的MoA。因此,VEGF、PDGF和FGF信号通路可能成为硬肿瘤的潜在治疗靶点。如图4B,硬肿瘤中VEGF、PDGF和FGF信号通路的表达水平明显高于软肿瘤,表明这些分子通路的在硬肿瘤中被激活,表示他们在肿瘤硬化中的重要性。此外,基于肿瘤药敏多组学数据库(GDSC)数据,发明人评估了硬肿瘤对阿西替尼、帕佐帕尼、索拉非尼和舒尼替尼四种VEGFR/PDGFR的抑制剂的治疗反应。通过整合细胞系和PA样本的基因表达谱,发明人使用回归分析估算四种药物在每个PA患者中的IC50值。舒尼替尼估计的IC50值在硬肿瘤组明显低于软肿瘤组(P=0.003),表明VEGFR/PDGFR抑制剂中,硬肿瘤患者对舒尼替尼的治疗更敏感(图4C)。
实施例6细胞和动物水平验证舒尼替尼对肿瘤硬度的作用
为了进一步研究肿瘤对舒尼替尼处理的敏感性,发明人比较了对照和不同浓度舒尼替尼处理的GH3细胞系的细胞活力,舒尼替尼处理的GH3细胞活性受到明显的抑制作用,半抑制浓度(IC50)为41.81μM(图5A)。随后,为了评估舒尼替尼在对大鼠细胞成瘤模型的影响,发明人通过将GH3细胞皮下注射到Wistar Furth大鼠的侧翼,建立了成瘤模型。给药处理后,舒尼替尼组相对于对照组肿瘤体积(59%抑制,P<0.05)和肿瘤重量(37%抑制,P<0.05)显著减少(图5B-D)。此外,舒尼替尼治疗对大鼠体重的影响很小,表明其安全性(图5E)。然后,进一步应用原子力显微镜(AFM)检测对照组和舒尼替尼组肿瘤标本的硬度(图5F&G)。舒尼替尼治疗组(0.85±0.34kPa,图5F)相对于对照组(0.90±0.03kPa,图5G)的肿瘤硬度显著降低(P<0.0001)。以上结果表明,舒尼替尼可以抑制垂体腺瘤的生长,降低肿瘤的硬度,可以作为垂体腺瘤治疗的潜在药物。
虽然,上文中已经用一般性说明及具体实施方案对本发明作了详尽的描述,但在本发明基础上,可以对之作一些修改或改进,这对本领域技术人员而言是显而易见的。因此,在不偏离本发明精神的基础上所做的这些修改或改进,均属于本发明要求保护的范围。

Claims (1)

1.检测垂体腺瘤组织中αSMA、S100A4、CD31和VWF蛋白表达水平的试剂在制备区分垂体腺瘤硬肿瘤和软肿瘤的试剂中的应用,其特征在于,硬肿瘤中αSMA、S100A4、CD31和VWF的蛋白表达水平显著高于软肿瘤。
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