色谱 ›› 2021, Vol. 39 ›› Issue (11): 1191-1202.DOI: 10.3724/SP.J.1123.2021.04009
收稿日期:
2021-04-08
出版日期:
2021-11-08
发布日期:
2021-10-22
通讯作者:
王彦,阎超
作者简介:
Tel:(021)38953588,E-mail: chaoyan@sjtu.edu.cn(阎超).基金资助:
YANG Kaige, WANG Weiwei, WANG Yan*(), YAN Chao*()
Received:
2021-04-08
Online:
2021-11-08
Published:
2021-10-22
Contact:
WANG Yan,YAN Chao
Supported by:
摘要:
外泌体是由各种类型细胞在正常或非正常生理情况下分泌释放至细胞外且携带多种生物活性分子的细胞外囊泡,在细胞间通讯和免疫应答等生物过程中发挥着重要作用。肝内胆管癌是一种胆道上皮恶性肿瘤,早期无明显临床症状且生存率较低,目前常用的诊断手段包括依赖于影像设备的诊断方式和灵敏度及特异性较低的诊断标志物等,这些手段的不足对发展新的特异性标志物提出了需求。该文对血清中的外泌体进行了分离和表征,并采用液相色谱-质谱技术针对健康组与肝内胆管癌患者组的血清样本和血清外泌体样本进行了无标记定量蛋白质组学分析,分别从两种类型样本中鉴定并筛选到271和430种可信蛋白质。基于血清样本和血清外泌体样本的可信蛋白质定量表达值进行多维统计分析都能将健康组与肝内胆管癌患者组良好地区分开。对血清样本中鉴定到的蛋白质进行差异蛋白质筛选,肝内胆管癌患者组相对于健康组有15个上调和8个下调蛋白质;对血清外泌体样本中鉴定到的蛋白质进行差异蛋白质筛选,肝内胆管癌患者组相对于健康组有33个上调和18个下调蛋白质;基于两种样本筛选到的差异蛋白质中仅有4个是重复的,且基于血清外泌体样本的51个差异蛋白质中有35个蛋白质属于外泌体蛋白质数据库。针对差异蛋白质进行生物学信息分析,与差异蛋白质相关的分子功能、生物过程和信号通路主要涉及天然免疫反应、炎症反应和凝血等过程。该研究为发现肝内胆管癌的潜在生物标志物和探究肝内胆管癌的发生、发展和转移等过程提供了参考和借鉴价值。此外,通过比较研究发现血清外泌体样本能够获得较多的差异蛋白质和生物学信息,证明了外泌体作为组学分析样本的价值和应用潜力。
中图分类号:
杨凯歌, 王薇薇, 王彦, 阎超. 血清和血清外泌体的蛋白质组分析及其在肝内胆管癌中的应用[J]. 色谱, 2021, 39(11): 1191-1202.
YANG Kaige, WANG Weiwei, WANG Yan, YAN Chao. Proteomic analysis of serum and serum exosomes, and their application in intrahepatic cholangiocarcinoma[J]. Chinese Journal of Chromatography, 2021, 39(11): 1191-1202.
图1 血清外泌体的表征
Fig. 1 Characterization of serum exosomes a. size range of healthy control (HC) serum exosomes measured using nanoparticle tracking analysis (NTA). b. size range of intrahepatic cholangiocarcinoma (iCCA) serum exosomes measured using NTA. c. Western blotting analysis of CD81, CD63 and CD9 in the serum exosomes and serum (HC and iCCA). d. TEM image of HC serum exosomes. e. TEM image of iCCA serum exosomes. White arrow: vesicle.
图2 血清外泌体的蛋白质组分析
Fig. 2 Proteome analysis of serum exosomes a. SDS-PAGE analysis of proteins of the serum exosomes and serum (HC and iCCA). b. Venn diagram of the identified proteins of the serum exosomes by LC-MS and ExoCarta database.
图3 可信蛋白质定量表达值数据标准化处理(a)前、 (b)后的箱线图
Fig. 3 Boxplots of quantitative expression data of credible proteins (a) before and (b)after normalization IQR: interquartile range.
图4 基于标准化定量蛋白质组的多维统计分析
Fig. 4 Multidimensional statistical analysis based on the normalized quantitative proteome a. principal components analysis (PCA) based on the normalized quantitative proteome of HC and iCCA serum; R2X[1]=0.24, R2X[2]=0.17. b. PCA based on the normalized quantitative proteome of HC and iCCA serum exosomes; R2X[1]=0.26, R2X[2]=0.17. c. orthogonal partial least-squares discrimination analysis (OPLS-DA) based on the normalized quantitative proteome of HC and iCCA serum; R2X[1]=0.40, R2Xo[1]=0.11. d. OPLS-DA based on the normalized quantitative proteome of HC and iCCA serum exosomes; R2X[1]=0.45, R2Xo[1]=0.10. Ellipse: Hotelling’s T2 (95%).
Sample type | A | R2X(cum) | R2Y(cum) | Q2(cum) |
---|---|---|---|---|
Serum | 1P+1O | 0.509 | 0.999 | 0.969 |
Exosome | 1P+1O | 0.547 | 0.999 | 0.984 |
表1 基于血清和血清外泌体标准化定量蛋白质组的 OPLS-DA模型参数
Table 1 Parameters of OPLS-DA models based on the normalized quantitative proteome of serum and serum exosomes
Sample type | A | R2X(cum) | R2Y(cum) | Q2(cum) |
---|---|---|---|---|
Serum | 1P+1O | 0.509 | 0.999 | 0.969 |
Exosome | 1P+1O | 0.547 | 0.999 | 0.984 |
Serum | Exosome | |||||||
---|---|---|---|---|---|---|---|---|
Accession | Gene symbol | FC(iCCA/HC) | P-value | Accession | Gene symbol | FC(iCCA/HC) | P-value | |
P00450 | CP | 2.2429 | 0.0053 | P04275 | VWF | 2.1460 | 0.0383 | |
P06681 | C2 | 2.2294 | 0.0001 | P01009 | SERPINA1 | 2.4817 | 0.0001 | |
P01833 | PIGR | 12.4548 | 0.0091 | P01877 | IGHA2 | +∞ | 0.0019 | |
Q06033 | ITIH3 | 2.5237 | 0.0086 | P01833 | PIGR | 9.5927 | 0.0048 | |
P36980 | CFHR2 | 3.9305 | 0.0371 | P20742 | PZP | 3.7771 | 0.0034 | |
P00742 | F10 | 2.2807 | 0.0001 | P36980 | CFHR2 | 2.1296 | 0.0109 | |
Q04756 | HGFAC | 2.5523 | 0.0024 | P01011 | SERPINA3 | 2.3901 | 0.0002 | |
P05362 | ICAM1 | +∞ | 0.0004 | P02763 | ORM1 | 2.3329 | 0.0028 | |
Q9BYE9 | CDHR2 | +∞ | 0.0005 | P15144 | ANPEP | 2.0323 | 0.0167 | |
A0A0A0MRZ9 | IGLV5-52 | 2.1752 | 0.0147 | P68133 | ACTA1 | 2.1930 | 0.0357 | |
P19320 | VCAM1 | 3.1375 | 0.0206 | P02775 | PPBP | 2.0735 | 0.0422 | |
P13473 | LAMP2 | 2.1709 | 0.0220 | Q04695 | KRT17 | +∞ | 0.0016 | |
Q9BT22 | ALG1 | 2.0182 | 0.0281 | Q14766 | LTBP1 | 2.0226 | 0.0274 | |
Q8NFU5 | IPMK | 12.1589 | 0.0006 | Q6UWP8 | SBSN | 4.0805 | 0.0177 | |
A2VCL2 | CCDC162 | 2.4897 | 0.0018 | P07327 | ADH1A | +∞ | 0.0052 | |
P06727 | APOA4 | 0.4316 | 0.0030 | P22792 | CPN2 | 2.8882 | 0.0049 | |
P07996 | THBS1 | 0.4055 | 0.0021 | P35555 | FBN1 | 2.4629 | 0.0282 | |
A0A075B6S6 | IGKV2D-30 | 0.0000 | 0.0288 | P02750 | LRG1 | 2.4234 | 0.0016 | |
P01602 | IGKV1-5 | 0.0000 | 0.0006 | P20930 | FLG | +∞ | 0.0165 | |
P13647 | KRT5 | 0.3018 | 0.0392 | P08571 | CD14 | 3.7509 | 0.0234 | |
Q7Z794 | KRT77 | 0.3075 | 0.0094 | Q9UEW3 | MARCO | 2.4943 | 0.0434 | |
P67936 | TPM4 | 0.0000 | 0.0110 | P02792 | FTL | +∞ | 0.0000 | |
O60229 | KALRN | 0.4881 | 0.0039 | P21333 | FLNA | 2.0853 | 0.0431 | |
P28066 | PSMA5 | +∞ | 0.0000 | |||||
P12814 | ACTN1 | 3.5309 | 0.0364 | |||||
Q9UGM3 | DMBT1 | 2.4154 | 0.0404 | |||||
Q9H4G4 | GLIPR2 | 3.8794 | 0.0397 | |||||
P78509 | RELN | 2.6213 | 0.0149 | |||||
Q15063 | POSTN | +∞ | 0.0000 | |||||
P30101 | PDIA3 | +∞ | 0.0070 | |||||
O14818 | PSMA7 | 2.2647 | 0.0024 | |||||
Q7Z398 | ZNF550 | 2.8163 | 0.0197 | |||||
O95810 | CAVIN2 | +∞ | 0.0001 | |||||
P01861 | IGHG4 | 0.3768 | 0.0009 | |||||
P06396 | GSN | 0.4789 | 0.0032 | |||||
P06727 | APOA4 | 0.2324 | 0.0000 | |||||
Q16610 | ECM1 | 0.2677 | 0.0001 | |||||
P04070 | PROC | 0.2334 | 0.0437 | |||||
P35443 | THBS4 | 0.3062 | 0.0060 | |||||
A0A075B6R2 | IGHV4-4 | 0.3530 | 0.0112 | |||||
P22105 | TNXB | 0.3142 | 0.0009 | |||||
A0A0B4J2H0 | IGHV1-69D | 0.1628 | 0.0016 | |||||
Q04756 | HGFAC | 0.3811 | 0.0005 | |||||
Q14532 | KRT32 | 0.0000 | 0.0007 | |||||
A0A0G2JMI3 | IGHV1-69-2 | 0.3718 | 0.0104 | |||||
A0A087WSZ0 | IGKV1D-8 | 0.0000 | 0.0002 | |||||
P12109 | COL6A1 | 0.4603 | 0.0094 | |||||
Q68EA5 | ZNF57 | 0.4689 | 0.0425 | |||||
Q96MV8 | ZDHHC15 | 0.3387 | 0.0171 | |||||
Q13939 | CCIN | 0.3101 | 0.0093 | |||||
Q9BS31 | ZNF649 | 0.0000 | 0.0021 |
表2 基于血清和血清外泌体样本的HC与iCCA组的差异蛋白质
Table 2 Differential proteins between HC and iCCA groups based on the serum and serum exosome samples
Serum | Exosome | |||||||
---|---|---|---|---|---|---|---|---|
Accession | Gene symbol | FC(iCCA/HC) | P-value | Accession | Gene symbol | FC(iCCA/HC) | P-value | |
P00450 | CP | 2.2429 | 0.0053 | P04275 | VWF | 2.1460 | 0.0383 | |
P06681 | C2 | 2.2294 | 0.0001 | P01009 | SERPINA1 | 2.4817 | 0.0001 | |
P01833 | PIGR | 12.4548 | 0.0091 | P01877 | IGHA2 | +∞ | 0.0019 | |
Q06033 | ITIH3 | 2.5237 | 0.0086 | P01833 | PIGR | 9.5927 | 0.0048 | |
P36980 | CFHR2 | 3.9305 | 0.0371 | P20742 | PZP | 3.7771 | 0.0034 | |
P00742 | F10 | 2.2807 | 0.0001 | P36980 | CFHR2 | 2.1296 | 0.0109 | |
Q04756 | HGFAC | 2.5523 | 0.0024 | P01011 | SERPINA3 | 2.3901 | 0.0002 | |
P05362 | ICAM1 | +∞ | 0.0004 | P02763 | ORM1 | 2.3329 | 0.0028 | |
Q9BYE9 | CDHR2 | +∞ | 0.0005 | P15144 | ANPEP | 2.0323 | 0.0167 | |
A0A0A0MRZ9 | IGLV5-52 | 2.1752 | 0.0147 | P68133 | ACTA1 | 2.1930 | 0.0357 | |
P19320 | VCAM1 | 3.1375 | 0.0206 | P02775 | PPBP | 2.0735 | 0.0422 | |
P13473 | LAMP2 | 2.1709 | 0.0220 | Q04695 | KRT17 | +∞ | 0.0016 | |
Q9BT22 | ALG1 | 2.0182 | 0.0281 | Q14766 | LTBP1 | 2.0226 | 0.0274 | |
Q8NFU5 | IPMK | 12.1589 | 0.0006 | Q6UWP8 | SBSN | 4.0805 | 0.0177 | |
A2VCL2 | CCDC162 | 2.4897 | 0.0018 | P07327 | ADH1A | +∞ | 0.0052 | |
P06727 | APOA4 | 0.4316 | 0.0030 | P22792 | CPN2 | 2.8882 | 0.0049 | |
P07996 | THBS1 | 0.4055 | 0.0021 | P35555 | FBN1 | 2.4629 | 0.0282 | |
A0A075B6S6 | IGKV2D-30 | 0.0000 | 0.0288 | P02750 | LRG1 | 2.4234 | 0.0016 | |
P01602 | IGKV1-5 | 0.0000 | 0.0006 | P20930 | FLG | +∞ | 0.0165 | |
P13647 | KRT5 | 0.3018 | 0.0392 | P08571 | CD14 | 3.7509 | 0.0234 | |
Q7Z794 | KRT77 | 0.3075 | 0.0094 | Q9UEW3 | MARCO | 2.4943 | 0.0434 | |
P67936 | TPM4 | 0.0000 | 0.0110 | P02792 | FTL | +∞ | 0.0000 | |
O60229 | KALRN | 0.4881 | 0.0039 | P21333 | FLNA | 2.0853 | 0.0431 | |
P28066 | PSMA5 | +∞ | 0.0000 | |||||
P12814 | ACTN1 | 3.5309 | 0.0364 | |||||
Q9UGM3 | DMBT1 | 2.4154 | 0.0404 | |||||
Q9H4G4 | GLIPR2 | 3.8794 | 0.0397 | |||||
P78509 | RELN | 2.6213 | 0.0149 | |||||
Q15063 | POSTN | +∞ | 0.0000 | |||||
P30101 | PDIA3 | +∞ | 0.0070 | |||||
O14818 | PSMA7 | 2.2647 | 0.0024 | |||||
Q7Z398 | ZNF550 | 2.8163 | 0.0197 | |||||
O95810 | CAVIN2 | +∞ | 0.0001 | |||||
P01861 | IGHG4 | 0.3768 | 0.0009 | |||||
P06396 | GSN | 0.4789 | 0.0032 | |||||
P06727 | APOA4 | 0.2324 | 0.0000 | |||||
Q16610 | ECM1 | 0.2677 | 0.0001 | |||||
P04070 | PROC | 0.2334 | 0.0437 | |||||
P35443 | THBS4 | 0.3062 | 0.0060 | |||||
A0A075B6R2 | IGHV4-4 | 0.3530 | 0.0112 | |||||
P22105 | TNXB | 0.3142 | 0.0009 | |||||
A0A0B4J2H0 | IGHV1-69D | 0.1628 | 0.0016 | |||||
Q04756 | HGFAC | 0.3811 | 0.0005 | |||||
Q14532 | KRT32 | 0.0000 | 0.0007 | |||||
A0A0G2JMI3 | IGHV1-69-2 | 0.3718 | 0.0104 | |||||
A0A087WSZ0 | IGKV1D-8 | 0.0000 | 0.0002 | |||||
P12109 | COL6A1 | 0.4603 | 0.0094 | |||||
Q68EA5 | ZNF57 | 0.4689 | 0.0425 | |||||
Q96MV8 | ZDHHC15 | 0.3387 | 0.0171 | |||||
Q13939 | CCIN | 0.3101 | 0.0093 | |||||
Q9BS31 | ZNF649 | 0.0000 | 0.0021 |
图5 基于血清和血清外泌体样本的HC与iCCA组的差异蛋白质筛选
Fig. 5 Screening of differential proteins between HC and iCCA groups based on the serum and serum exosome samples a. volcano plots of identified proteins in the HC and iCCA groups, based on the serum samples. b. volcano plots of identified proteins in the HC and iCCA groups based on the serum exosome samples. c. Venn diagram of the differential proteins screened between HC and iCCA groups based on the serum exosome samples and ExoCarta database. d. Venn diagram of the differential proteins screened between HC and iCCA groups based on the serum and serum exosome samples.
图6 基于血清和血清外泌体样本的HC与iCCA组间差异蛋白质的生物信息分析
Fig. 6 Biological information analysis of differential proteins between the HC and iCCA groups based on the serum and serum exosomes samples a. Gene Ontology (GO) analysis of differential proteins based on the serum samples; b. GO analysis of differential proteins based on the serum exosome samples; c. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of differential proteins based on the serum samples; d. KEGG pathways of differential proteins based on the serum exosome samples.
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