| Literature DB >> 23516489 |
Bo Li1, Feng Li, Lingyi Chi, Liangwen Zhang, Shugan Zhu.
Abstract
OBJECTIVE: SPARC is a key determinant of invasion and metastasis in some tumors, such as gliomas, melanomas and prostate tumors. SPARC can change the composition and structure of the matrix and promote angiogenesis; these effects are closely related to clinical stage and the prognosis of tumors such as meningiomas. However, little is known about the expression of SPARC in intracranial aneurysms. The goal of this study was to establish the role of SPARC in human intracranial aneurysms.Entities:
Mesh:
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Year: 2013 PMID: 23516489 PMCID: PMC3597740 DOI: 10.1371/journal.pone.0058490
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Patient and aneurysm characteristics.
| Patient | Age | Sex | Risk factors | Aneurysm site | Aneurysm size | Hunt-Hessgrade | SPARC staining | MMP 2 staining | MMP 9 staining |
| 1 | 31 | F | None | Aa | 3×5×3 | 0 | + + | +++ | + + |
| 2 | 29 | F | None | Ta | 1×1×1 | 0 | + + + | + + | + + |
| 3 | 50 | M | None | Aa | 3×2.5×3.5 | 0 | + + | + + + | + + |
| 4 | 50 | F | None | Aica | 2×2×2 | 0 | + + | + + | + + |
| 5 | 25 | F | previous SAH | Acom | 4×4×3.5 | VI | + + | + + | + + + |
| 6 | 70 | M | previous SAH | Acom | 2×1.2×0.8 | II | + + + | + + + | + + |
| 7 | 51 | F | previous SAH | Acom | 4×4×5 | III | + + | + + | + + |
| 8 | 56 | M | HTN,previous SAH | Pcom | 2.5×2×2 | II | + + + | + + | + + + |
| 9 | 50 | F | previous SAH | Acom | 2×2.5×2 | IV | + + | + + + | + + + |
| 10 | 39 | M | previous SAH | Mca | 1.2×1×0.4 | II | + + | + + | + + |
| 11 | 39 | F | previous SAH | Mca | 0.5×0.8×0.2 | II | + + + | + + | + + + |
| 12 | 46 | F | previous SAH | Mca | 1.5×2.5×1.5 | II | + + + | + + + | + + |
| 13 | 60 | F | previous SAH | Mca | 4×3×3.5 | IV | + + + | + + + | + + + |
| 14 | 35 | F | previous SAH | Acom | 1×0.8×0.5 | II | + + | + + + | + + |
| 15 | 54 | M | previous SAH | Pcom | 1.5×1×1 | III | + + + | + + + | + + |
| 16 | 18 | M | previous SAH | Pca | 1.5×0.5×1.5 | III | + + + | + + + | + + + |
| 17 | 60 | F | previous SAH | Mca | 1.5×0.8×0.5 | II | + + | + + | + + |
| 18 | 19 | F | previous SAH | Acom | 1×1×0.7 | II | + + + | + + | + + + |
| 19 | 43 | M | previous SAH | Acom | 0.6×0.7×1 | I | + + + | + + | + + + |
| 20 | 50 | M | HTN, previous SAH | Acom | 2×2×1 | II | + + + | + + + | + + |
| 21 | 52 | M | previous SAH | Va | 3×4×4 | II | + + + | + + | + + + |
| 22 | 57 | F | previous SAH | Ia | 3×2×1 | I | + + | + + | + + + |
| 23 | 48 | F | previous SAH | Mca | 0.3×0.2×0.2 | IV | + + | + + + | + + |
| 24 | 31 | M | previous SAH | Mca | 4×3×1.5 | II | + + + | + + | + + + |
| 25 | 46 | F | previous SAH | Aa | 0.7×0.6×0.2 | I | + + + | + + + | + + |
| 26 | 51 | F | previous SAH | Acom | 1×0.5×0.8 | III | + + + | + + + | + + + |
| 27 | 49 | M | Smoker, | Acom | 2×3×1 | II | + + + | + + + | + + + |
| previous SAH | |||||||||
| 28 | 19 | F | previous SAH | Acom | 2×2×1 | III | + + | + + + | + + |
| 29 | 63 | F | previous SAH | Aa | 1×1×0.5 | I | + + + | + + | + + + |
| 30 | 55 | M | previous SAH | Pcom | 3×3×5 | II | + + + | + + + | + + |
| 31 | 34 | M | previous SAH | Mca | 0.6×0.5×0.5 | III | + + + | + + + | + + + |
HTN, hypertension; SAH, subarachnoid haemorrhage; F, female; M, male; pcom, posterior communicating artery aneurysm; acom, anterior communicating artery.
aneurysm; mca, middle cerebral artery aneurysm; ba, basilar artery aneurysm; pca, posterior cerebral artery aneurysm; va, vertebral artery aneurysm; ia, internal carotid artery; aa, anterior cerebral aneurysm; ta, temporal artery aneurysm; aica, anterior inferior cerebellar artery aneurysm.
Control Circle of Willis arteries.
| Control artery | Age | Sex | Risk factors | SPARC staining | MMP 2 staining | MMP 9 staining |
| 1 | 54 | F | Smoker | + | + | + |
| 2 | 21 | F | None | + | + | + |
| 3 | 22 | M | None | − | + | − |
| 4 | 56 | M | HTN | + | − | − |
| 5 | 30 | M | None | − | + | − |
| 6 | 71 | M | None | + | + | + |
| 7 | 67 | M | HTN | ++ | − | − |
| 8 | 17 | M | None | + | − | − |
| 9 | 34 | M | Obese | − | + | + |
| 10 | 24 | M | None | + | − | − |
HTN, hypertension; F, female; M, male;
Figure 1Normal human placenta (positive control) immunostained for SPARC, MMP 2, and MMP 9.
A: SPARC: intense immunostaining of syncytial cells (arrow) ×400. B: MMP 2: intense immunostaining of syncytial cells (arrow) ×400. C: MMP 9: intense immunostaining of syncytial cells (arrow) ×400.
Figure 2Normal cerebral artery immunostained for SPARC, MMP 2, and MMP 9.
A: SPARC: minimal background immunostaining of adventitia (arrow) ×400. B: MMP 2: minimal background immunostaining of intima, media and adventitia (arrow) ×400. C: MMP 9: minimal background immunostaining of intima, media and adventitia (arrow) ×400. D: Negative control: no immunostaining evident ×400.
Figure 3Intracranial aneurysms immunostained for SPARC, MMP 2, and MMP 9.
A: SPARC: intense immunostaining of medial (arrow) smooth muscle cells ×400. B: MMP 2: intense immunostaining of medial (arrow) smooth muscle cells ×400. C: MMP 9: intense immunostaining of medial (arrow) smooth muscle cells ×400. D: Negative control: no immunostaining of medial smooth muscle cells ×400.
Spearman rank correlation analysis between SPARC staining and MMP 2 staining.
| MMP 2 staining | |||
| Spearman’s rho | SPARC staining | Correlation Coefficient | .625 |
| Sig. (2-tailed) | .000 | ||
| N | 41 | ||
Correlation is significant at the 0.01 level (2-tailed).
Spearman rank correlation analysis between SPARC staining and MMP 9 staining.
| MMP 9 staining | |||
| Spearman’s rho | SPARC staining | Correlation Coefficient | .742 |
| Sig. (2-tailed) | .000 | ||
| N | 41 | ||
Correlation is significant at the 0.01 level (2-tailed).
Table 3 and 4 describe that the SPARC staining have rank correlation with MMP 2 and MMP 9 staining (P<0.001), the difference was statistically significant.
Influencing Factors of SPARC staining.
| Coefficients | ||||||
| Standardized Coefficients | df | F | Sig. | |||
| Beta | Std. Error | |||||
| Age | −.705 | .163 | 2 | 18.752 | .000 | |
| Sex | −.106 | .130 | 1 | .671 | .420 | |
| Risk Factor | .910 | .161 | 2 | 31.726 | .000 | |
Dependent Variable: SPARC staining.
Assignment situation: Aged (years): 10–19 = 1, 20–29 = 2, 30–39 = 3, 40–49 = 4, 50–59 = 5 60–69 = 60 70–79 = 7; Gender: 1 = Male, 2 = Female; Risk factors: the existence of risk factors = 1, non-existent risk factors = 0.
Optimal scaling regression analysis between SPARC and Hunt-hess grade.
| SPARC staining | MMP 2 staining | MMP 9 staining | ||
| Hunt-Hess grade | Pearson Correlation Coefficients | −0.013 | 0.273 | 0.279 |
| Sig.(2-tailed) | 0.945 | 0.137 | 0.128 |
Figure 4Western blot of SPARC, MMP 2 and MMP 9.