TY - JOUR
T1 - Endovascular Biopsy
T2 - In Vivo Cerebral Aneurysm Endothelial Cell Sampling and Gene Expression Analysis
AU - Cooke, Daniel L.
AU - McCoy, David B.
AU - Halbach, Van V.
AU - Hetts, Steven W.
AU - Amans, Matthew R.
AU - Dowd, Christopher F.
AU - Higashida, Randall T.
AU - Lawson, Devon
AU - Nelson, Jeffrey
AU - Wang, Chih Yang
AU - Kim, Helen
AU - Werb, Zena
AU - McCulloch, Charles
AU - Hashimoto, Tomoki
AU - Su, Hua
AU - Sun, Zhengda
N1 - Funding Information:
Acknowledgements The authors would like to thank the UCSF Neurointerventional Radiology service, particularly its fellows, for their help in the sample collection. Sources of Funding The project was funded in part by the Society for Neurointerventional Surgery, the UCSF Department of Radiology, and by a grant from the National Cancer Institute R01 CA056721 to Z.W.
Funding Information:
The authors would like to thank the UCSF Neurointerventional Radiology service, particularly its fellows, for their help in the sample collection. The project was funded in part by the Society for Neurointerventional Surgery, the UCSF Department of Radiology, and by a grant from the National Cancer Institute R01 CA056721 to Z.W. The authors declare that they have no conflict of interest.
Publisher Copyright:
© 2017, Springer Science+Business Media, LLC.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - There is limited data describing endothelial cell (EC) gene expression between aneurysms and arteries partly because of risks associated with surgical tissue collection. Endovascular biopsy (EB) is a lower risk alternative to conventional surgical methods, though no such efforts have been attempted for aneurysms. We sought (1) to establish the feasibility of EB to isolate viable ECs by fluorescence-activated cell sorting (FACS), (2) to characterize the differences in gene expression by anatomic location and rupture status using single-cell qPCR, and (3) to demonstrate the utility of unsupervised clustering algorithms to identify cell subpopulations. EB was performed in 10 patients (5 ruptured, 5 non-ruptured). FACS was used to isolate the ECs and single-cell qPCR was used to quantify the expression of 48 genes. Linear mixed models and exploratory multilevel component analysis (MCA) and self-organizing maps (SOMs) were performed to identify possible subpopulations of cells. ECs were collected from all aneurysms and there were no adverse events. A total of 437 ECs was collected, 94 (22%) of which were aneurysmal cells and 319 (73%) demonstrated EC-specific gene expression. Ruptured aneurysm cells, relative controls, yielded a median p value of 0.40 with five genes (10%) with p values < 0.05. The five genes (TIE1, ENG, VEGFA, MMP2, and VWF) demonstrated uniformly reduced expression relative the remaining ECs. MCA and SOM analyses identified a population of outlying cells characterized by cell marker gene expression profiles different from endothelial cells. After removal of these cells, no cell clustering based on genetic co-expressivity was found to differentiate aneurysm cells from control cells. Endovascular sampling is a reliable method for cell collection for brain aneurysm gene analysis and may serve as a technique to further vascular molecular research. There is utility in combining mixed and clustering methods, despite no specific subpopulation identified in this trial.
AB - There is limited data describing endothelial cell (EC) gene expression between aneurysms and arteries partly because of risks associated with surgical tissue collection. Endovascular biopsy (EB) is a lower risk alternative to conventional surgical methods, though no such efforts have been attempted for aneurysms. We sought (1) to establish the feasibility of EB to isolate viable ECs by fluorescence-activated cell sorting (FACS), (2) to characterize the differences in gene expression by anatomic location and rupture status using single-cell qPCR, and (3) to demonstrate the utility of unsupervised clustering algorithms to identify cell subpopulations. EB was performed in 10 patients (5 ruptured, 5 non-ruptured). FACS was used to isolate the ECs and single-cell qPCR was used to quantify the expression of 48 genes. Linear mixed models and exploratory multilevel component analysis (MCA) and self-organizing maps (SOMs) were performed to identify possible subpopulations of cells. ECs were collected from all aneurysms and there were no adverse events. A total of 437 ECs was collected, 94 (22%) of which were aneurysmal cells and 319 (73%) demonstrated EC-specific gene expression. Ruptured aneurysm cells, relative controls, yielded a median p value of 0.40 with five genes (10%) with p values < 0.05. The five genes (TIE1, ENG, VEGFA, MMP2, and VWF) demonstrated uniformly reduced expression relative the remaining ECs. MCA and SOM analyses identified a population of outlying cells characterized by cell marker gene expression profiles different from endothelial cells. After removal of these cells, no cell clustering based on genetic co-expressivity was found to differentiate aneurysm cells from control cells. Endovascular sampling is a reliable method for cell collection for brain aneurysm gene analysis and may serve as a technique to further vascular molecular research. There is utility in combining mixed and clustering methods, despite no specific subpopulation identified in this trial.
KW - Cerebral aneurysm
KW - Cerebrovascular procedures
KW - Endothelium
KW - Gene expression
KW - Vascular biology
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UR - http://www.scopus.com/inward/citedby.url?scp=85029146015&partnerID=8YFLogxK
U2 - 10.1007/s12975-017-0560-4
DO - 10.1007/s12975-017-0560-4
M3 - Article
C2 - 28900857
AN - SCOPUS:85029146015
SN - 1868-4483
VL - 9
SP - 20
EP - 33
JO - Translational Stroke Research
JF - Translational Stroke Research
IS - 1
ER -