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Protein profiling of cerebrospinal fluid from patients undergoing vestibular schwannoma surgery and clinical significance
Biomedicine & Pharmacotherapy 116 (2019) 108985
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Protein profiling of cerebrospinal fluid from patients undergoing vestibular schwannoma surgery and clinical significance
T
Xiang Huanga,1, Jian Xua,1, Yiwen Shena, Lei Zhangb, Ming Xua, Mingyu Chena, Junwei Rena, ⁎⁎ ⁎ Liangfu Zhoua, Hui Gongb, , Ping Zhonga, a b
Department of Neurosurgery, Huashan Hospital, Fudan University, China Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, China
ARTICLE INFO
ABSTRACT
Keywords: Vestibular schwannoma Proteomic analysis Cerebrospinal fluid Recurrence iTRAQ
Vestibular schwannoma (VS) is a common disease in the region of the cerebellopontine angle in the posterior cranial fossa. Large VS and its surgical management usually lead to severe cranial nerve dysfunction and affect the patient’s quality of life. We aimed to find some possible progression markers of VS. Here, we sought to characterize the cerebrospinal fluid (CSF) proteome of patients with different VS grades and recurrence to identify biomarkers predictive of VS growth or recurrence. CSF was collected intraoperatively prior to removal of untreated VS, including grade I–V and recurrence. Isobaric tags for relative and absolute quantitation–based proteomic analysis of CSF from 43 VS patients and 3 control patients was used to identify candidate proteins. Ninety-three overlapping proteins were found to display differential expression in grade I, II, III, IV, and V VS patients compared with the control group. Nine proteins were chosen for validation with enzyme-linked immunosorbent assay. VS was distinguished from control patients based on the expression patterns of six proteins (ATP-binding cassette subfamily A member 3 [ABCA3], secretogranin-1 [SCG1], Krueppel-like factor 11 [KLF11], voltage-dependent calcium channel subunit alpha-2/delta-1 [CA2D1], brain acid soluble protein 1 [BASP1], and peroxiredoxin-2 [PRDX2]. ABCA3 and KLF11 were positively correlated with the size of earlyphase of VS, while BASP1 and PRDX2 showed a negative correlation. ABCA3, CA2D1, and KLF11 were upregulated, while BASP1 and PRDX2 were downregulated in the CSF from VS recurrence. But SCG1 was increased only at early-phase. These data suggest that increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 in CSF are associated with VS growth at the early phase or recurrence.
1. Introduction Vestibular schwannoma (VS), accounting for 8%–10% of all intracranial tumors, [1–3] is a common disease that develops in the cerebellopontine angle in the posterior cranial fossa. VS often grows slowly and is commonly treated with surgery. However, surgical treatment may lead to severe cranial nerve dysfunction and affect the patient’s quality of life. Hence, conservative management, such as “wait and see,” is often used for VS. As such, characterizing molecular
markers for tumor growth monitoring and tumor control could be critical to this disease management. The composition of cerebrospinal fluid (CSF) reflects molecules actively transported from the blood as well as secretions from intracranial tumors and brain. Therefore, CSF serves as a potential source of diagnostic and therapeutic targets. Differential proteomic analyses of CSF have yielded biomarkers for several brain tumors [4–7]. However, few studies have concentrated on the proteomic profile of VS to investigate potential biomarkers in CSF associated with VS growth
Abbreviations: ABCA3, ATP-binding cassette sub-family A member 3; AML, acute myeloid leukemia; APOA1, Apolipoprotein A–I; ATII, alveolar epithelial type II; BASP1, brain acid soluble protein 1; CA2D1, voltage-dependent calcium channel subunit alpha-2/delta-1; CCS, copper chaperone for superoxide dismutase; CHGB, chromogranin B; CSF, cerebrospinal fluid; ELISA, enzyme-linked immunosorbent assay; GBP, gabapentin; iTRAQ, isobaric tags for relative and absolute quantitation; KLF11, Krueppel-like factor 11; LBs, lamellar bodies; MS, multiple sclerosis; OPCM, opioid-binding protein; PRDX2, peroxiredoxin-2; SCG1, secretogranin-1; Sp1/ KLF, Sp1/Krüppel-like factor; TGF-β, transforming growth factor-β; VS, vestibular schwannoma ⁎ Corresponding author at: Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, China. ⁎⁎ Corresponding author at: Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China. E-mail addresses: [email protected] (H. Gong), [email protected] (P. Zhong). 1 These authors contribute equally. https://doi.org/10.1016/j.biopha.2019.108985 Received 30 March 2019; Received in revised form 24 April 2019; Accepted 13 May 2019 0753-3322/ © 2019 The Authors. Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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physiology at the molecular level [8,9]. Here, using 43 CSF samples of VS, we applied Isobaric tags for relative and absolute quantitation (iTRAQ)–based proteomics analysis to identify proteins that are differentially expressed in CSF from different grades or recurrence of VS compared with the control group. Enzymelinked immunosorbent assay (ELISA) was subsequently used to verify the results in 87 CSF samples of VS. We aimed to elucidate novel biomarkers related to the growth and recurrence of VS that may serve as potential therapeutic targets for VS treatment.
collected (15 ml per patient) before tumor exposure via dura incisions, filtered (0.22 μm), and stored at −80 °C before analysis. The institutional review board of Huashan Hospital, Fudan University, approved the study protocol. Informed consent was obtained for all samples. 2.3. iTRAQ-based proteomics analysis The CSF from patients were analyzed to explore differential protein expression by iTRAQ-based proteomics technique as described previously [11]. In brief, total protein was concentrated and extracted from the CSF of patients with VS. The protein concentration was determined using the Bradford assay kit (Bio-Rad). Equal amounts of protein were labeled with iTRAQ reagent. Each labeled sample included a mixture of 2 to 10 protein samples from the same group. The labeled samples were combined and dried in vacuo for liquid chromatography tandem mass spectrometry (MS/MS) analysis. The analysis was repeated twice. To identify and quantify the protein, MS/MS data were analyzed with the ProteinPilot 2.0 software (Applied Biosytems). An iTRAQ ratio ≥1.2 or ≤0.83 was considered as up- or downregulation [12,13], respectively.
2. Materials and methods 2.1. Materials Bradford assay kits were obtained from Bio-Rad (USA). Human secretogranin-1 (SCG1), voltage-dependent calcium channel subunit alpha-2/delta-1 (CA2D1), brain acid soluble protein 1 (BASP1), peroxiredoxin-2 (PRDX2), ATP-binding cassette subfamily A member 3 (ABCA3), and Krueppel-like factor 11 (KLF11) ELISA kits were purchased from FUSHENG (Shanghai, China). 2.2. Clinical and patient sample information
2.4. ELISA
Our study included CSF samples for iTRAQ-based proteomics (43 samples) and ELISA analysis (87 samples) from VS patients who were undergoing surgery for sporadic VS from January 2014 and December 2016 in Huashan Hospital. Patients with prior meningitis or demyelinating disease were excluded. These VS patients were grouped by grade I to V and recurrence. Tumor size was categorized according to the international criteria using the largest extrameatal tumor diameter on the postcontrast axial magnetic resonance image (MRI) [10]. Grade I to V were grouped by the size of tumor according to international grading of VS size [10] (group I: < 1 cm; group II: 1–2 cm; group III: 2–3 cm; group IV: 3–4 cm; group V: 4–5 cm) (Fig. 1). The recurrence group included patients undergoing a second surgery for recurrent VS. Among the 98 CSF specimens, 43 specimens were examined by iTRAQ-based proteomics analysis, while 87 specimens were subsequently validated by ELISA. There were 32 overlapping cases in two groups. The control CSF was from 3 normal adults without brain tumor, meningitis, or demyelinating disease via lumbar punctures. CSF from all patients was
Protein expression levels characterized by proteomic analysis in CSF were validated by ELISA. In brief, CSF samples, which we collected from patients, were centrifuged at 4 °C for 20 min, and then the supernatant was collected and stored at −80 °C. An ELISA kit (FUSHENG, Shanghai, China) was used for measuring these protein levels mentioned above in CSF according to the manufacturer’s protocols. 2.5. Statistical analysis Data are expressed as mean ± SEM. Student’s t-test was applied to two-group comparisons. One-way ANOVA with Bonferroni post hoc test was used to multiple group comparisons. Statistical analyses and correlation analysis were carried out using Prism 5. Values of p < 0.05 were considered statistically significant.
Fig. 1. VS tumor size grade on postcontrast axial MRI according to international grading of the size of VS. (A) Group I: < 1 cm. (B) Group II: 1–2 cm. (C) Group III: 2–3 cm. (D) Group IV: 3–4 cm. (E) Group V: 4–5 cm. 2
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Table 1 Baseline characteristics of control and patients with VS, and analysis of CSF with iTRAQ-based proteomics.* Variable
Male/female Age (years) Tumor size (cm) Preoperative Hearing SBP (mmHg) DBP (mmHg) AST (u/L) ALT (u/L) Creatinine (μmol/L) Medical history Shock Hypertension Diabetes mellitus Proteins Dysregulated (n)
Control
AC Hearing classa
Up Down
VS I
II
III
IV
V
Recurrence
3/0 34.0 ± 8.5 – – – 127 ± 6.6 87.3 ± 11.0 48.0 ± 26.6 32.7 ± 17.0 69.0 ± 12.1
1/0 68 0.9 75 3 118 80 13 13 75
2/3 44.8 ± 12.0 1.7 ± 0.1 56.5 ± 35.2 2.3 ± 1.0 123.2 ± 6.4 77.4 ± 5.6 18.0 ± 5.7 21.4 ± 12.1 62.6 ± 10.2
3/6 46.4 ± 15.2 2.6 ± 0.3 71.0 ± 26.0 3.1 ± 1.0 129.7 ± 10.1 84.1 ± 5.2 15.9 ± 3.4 20.1 ± 1.0 66.3 ± 14.0
4/10 48.6 ± 13.1 3.2 ± 0.2 63.0 ± 19.2 2.9 ± 0.8 125.3 ± 12.0 78.9 ± 5.9 18.4 ± 4.9 22.9 ± 11.9 65.6 ± 12.9
5/8 46.1 ± 14.8 4.4 ± 0.5 62.0 ± 25.3 3.1 ± 0.9 122.3 ± 9.1 77.5 ± 6.3 20.4 ± 9.0 28.2 ± 20.0 73.5 ± 18.7
1/0 38 3.5 – 4 110 70 21 26 67
0 0 0 – –
0 0 0 58 124
0 1 0 39 161
0 1 0 55 195
0 3 0 64 204
0 0 0 39 162
0 0 0 44 147
Abbreviations: VS vestibular schwannoma; AC air conduction; SBP systolic pressure; DBP diastolic pressure; AST aspartate aminotransferase; ALT alanine aminotransferase. * VS patients were grouped with I–V, and recurrence. a The criteria used for the preoperative hearing evaluations were provided by the classification method of the American Institute of Otolaryngology–Head and Neck Surgery (AAO-HNS), 1995.
constituent, and immunoglobulin binding in line with these pathways mentioned above (Fig. 2C).
3. Results 3.1. Differentially expressed proteins were identified in CSF from patients with VS
3.3. Nine proteins in CSF correlate with the size of VS
To explore which proteins or factors in CSF affect the growth rate of VS, we analyzed differentially expressed proteins in CSF between control group and patients with VS (including grade I, II, III, IV, V, and recurrence) by iTRAQ-based proteomics analysis. Table 1 summarizes the basic characteristics of the 43 VS patients aged 21–69 years and in groups I–V and recurrence. iTRAQ ratio > 1.2 or ratio < 0.83 and p values < 0.05 were considered as upregulation or downregulation, respectively. We compared the control group to VS grade I, II, III, IV, or recurrence. Of the 431 proteins detected, 58 proteins were upregulated in grade I, 39 proteins in grade II, 55 proteins in grade III, 64 proteins in grade IV, 39 proteins in grade V, and 44 proteins in recurrence. A total of 124 proteins were found to be downregulated in grade I, 161 proteins in grade II, 195 proteins in grade III, 204 proteins in grade IV, 162 proteins in grade V, and 147 proteins in recurrence compared with the control group.
After performing Ingenuity Pathway Analysis (IPA) analysis, the expression of nine proteins was found to be associated with the grade of VS. Among these proteins, Apolipoprotein A–I (APOA1) and ABCA3 were upregulated in CSF in a size-dependent manner. APOA1 levels in CSF reached peaked at grade IV, while ABCA3 levels in CSF were highest in grade III. This suggests that increased expression of these two factors may positively relate to the growth of VS. KLF11 and SCG1 showed a sharp increase in CSF from the grade I and II groups, but KLF increased less and SCG1 revealed no increase in CSF from the grade III–V groups compared with control group. CA2D1 and opioid-binding protein (OPCM) were increased greatly in CSF from the grade I group but then began to decrease in the grade II group. This may indicate that an increase in CA2D1 and OPCM levels are related to the early stages of VS. Copper chaperone for superoxide dismutase (CCS) levels in CSF were the highest in the grade II group. Although levels decreased in CSF in the grade III group, they remained 20-fold higher than in the control group (Fig. 3A). Two proteins (BASP1 and PRDX2) were greatly downregulated in the CSF of VS compared with the control group (Fig. 3B). The protein-protein interactions among the 9 proteins were analyzed by FunRich_V3. The result indicated that SCG1 could indirectly interact with APOA1 via proteins such as LBP, CP, and others. There were no direct interactions among the other 7 proteins (Fig. 3C).
3.2. Function and pathway analysis of differentiated protein in grade I–V VS patients Ninety-three proteins showed overlapping expression patterns in VS patients with grade I, II, III, IV, and V compared with the control group. Eleven proteins were upregulated while 82 proteins were downregulated in CSF from patients with grade I–V compared with the control group (Fig. 2A). We then analyzed the functions and pathways in which these proteins were involved using FunRich_V3. These proteins were mapped to several pathways. The top six enriched pathways (p < 0.001) were the immune system pathway, hemostasis pathway, integrin family interaction, complement cascade, superoxide radicals degradation, and glypican pathway (Fig. 2B). We also performed functional enrichment analysis on the differentially expressed proteins. Protease inhibitor activity was identified as the most enriched biological process. The other top 7 significantly enriched functions were complement activity, calcium ion binding, transporter activity, metal ion binding, peroxidase activity, extracellular matrix structural
3.4. ELISA analysis identified 6 proteins in CSF associated with the growth of VS We then performed an ELISA test in CSF from 87 VS patients aged 19–69 years (46.3 ± 13.5 years). Of these 87 patients, 83 (95.4%) were untreated VS, 4 (4.6%) were recurrent VS, and 32 patients overlapped with patients by iTRAQ analysis. The clinical characteristics of VS patients are summarized in Table 2. Compared with the control group, ABCA3 levels increased in CSF from grade II–V and were highest in group III. KLF11 and CA2D1 levels increased in CSF from grades I–V and reached a maximum in grade II and grade I, respectively. SCG1 3
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Fig. 2. Proteomic analysis of CSF from VS grade I–V patients and control subjects. (A) Heatmap of down-regulated (green) (fold change < 0.83) and up-regulated (red) (fold change > 1.2) CSF proteins in patients VS grade I–V vs control subjects. (B) Top six pathways and (C) top seven functions in which differentially expressed proteins were involved were analyzed by FunRich_V3 Software.
increased in CSF from grade I and II, but it showed no alteration in grades III–V (Fig. 4A). BASP1 and PRDX2 decreased in CSF from grades II–V (Fig. 4B). These data coincide with the results observed in
proteomic analysis. However, there was no difference in these factors between female and male patients (Supplementary Table 1). Moreover, APOA1, OPCM, and CCS showed no change between grades I–V and the 4
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Fig. 3. Nine proteins associated with growth of VS were screened out by iTRAQ-based proteomics analysis. (A) iTRAQ ratio of ABCA3, SCG1, KLF11, CA2D1, APOA1, OPCM, and CCS in CSF from VS grade I–V compared with the control group. (B) iTRAQ ratio of BASP1 and PRDX2 in CSF from VS grade I–V compared with the control group. (C) The protein-protein interactions among the 9 proteins mentioned in A and B were analyzed by FunRich_V3 Software.
control group (Fig. 4C). Next, we analyzed the correlation of tumor size with these proteins. This analysis revealed that ABCA3 and KLF11 were positively correlated with size, while BASP1 and PRDX2 were negatively correlated with the tumor size under grade III (Table 3). These data suggest that the increased levels SCG1, KLF11, and CA2D1 may serve as early biomarkers of VS.
3.5. Identification of 5 proteins in CSF associated with the recurrence of VS In CSF, 10 overlapping proteins were upregulated and 76 overlapping proteins were downregulated in grade II and recurrence patients compared with the control group (Fig. 5A). Clinical characteristics of VS recurrence patients are summarized in Table 1. Proteomic analysis revealed that ABCA3 (iTRAQ ratio: 9.10), SCG1 (iTRAQ ratio: 3.28), KLF11 (iTRAQ ratio: 9.39), and CA2D19 (iTRAQ ratio: 8.96)
Table 2 Baseline characteristics of control and patients with VS, and analysis of CSF with ELISA.*. Variable
Male/female Age (years) Tumor size (cm) Preoperative Hearing SBP (mmHg) DBP (mmHg) AST (u/L) ALT (u/L) Creatinine (μmol/L) Medical history Shock Hypertension Diabetes mellitus
Control
AC Hearing classa
VS I
II
III
IV
V
Recurrence
3/0 34.0 ± 8.5 – – – 127 ± 6.6 87.3 ± 11.0 48.0 ± 26.6 32.7 ± 17.0 69.0 ± 12.1
2/1 55.0 ± 18.4 0.9 ± 0 55.0 ± 28.3 2.5 ± 0.7 124.5 ± 9.2 84.5 ± 6.4 15.0 ± 2.8 16.0 ± 4.2 63.0 ± 17.0
2/5 46.7 ± 13.1 1.8 ± 0.1 49.7 ± 29.6 2.0 ± 1.0 128.0 ± 8.4 82.9 ± 7.6 23.0 ± 8.4 32.1 ± 20.5 58.7 ± 11.9
10/20 45.7 ± 11.4 2.6 ± 0.3 53.6 ± 28.5 2.8 ± 1.1 124.2 ± 14.2 80.0 ± 8.2 20.2 ± 12.6 23.5 ± 13.7 61.9 ± 16.1
7/13 48.6 ± 14.4 3.4 ± 0.3 62.3 ± 19.8 3.1 ± 0.7 127.5 ± 10.8 79.2 ± 6.5 22.8 ± 10.1 25.9 ± 13.6 63.1 ± 15.0
9/14 44.1 ± 16.2 4.5 ± 0.5 62.8 ± 25.1 3.3 ± 0.9 121.2 ± 10.2 79.1 ± 6.6 20.3 ± 8.4 26.5 ± 18.6 67.7 ± 15.4
3/1 47.5 ± 8.8 3.4 ± 0.8 – 4.0 ± 0 129.5 ± 15.4 79.5 ± 14.1 20.8 ± 8.8 27.8 ± 12.9 65.3 ± 4.9
0 0 0
0 0 0
0 1 0
0 7 1
0 4 1
0 1 1
0 2 1
Abbreviations: VS: vestibular schwannoma; AC: air conduction; SBP: systolic pressure; DBP: diastolic pressure; AST: aspartate aminotransferase; ALT: alanine aminotransferase. * VS patients were grouped with I, II, III, IV, V, and recurrence. a The criteria used for the preoperative hearing evaluations were provided by the classification method of the American Institute of Otolaryngology–Head and Neck Surgery (AAO-HNS), 1995. 5
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Fig. 4. ELISA verification of the 9 proteins associated with the growth of VS. (A) The concentrations of ABCA3, SCG1, KLF11, and CA2D1 in CSF were from VS grade I–V and the control group. (B) The concentrations of BASP1 and PRDX2 in CSF were from VS grade I–V and the control group. (C) The concentrations of APOA1, OPCM, and CCS in CSF were from VS grade I–V and the control group. Control: n = 3; grade I: n = 3; grade II: n = 7; grade III, n = 30; grade IV, n = 20; grade V, n = 23. *p < 0.05 vs control group; **p < 0.01 vs control group.
were upregulated while BASP1 (iTRAQ ratio: 0.23) and PRDX2 (iTRAQ ratio: 0.63) were downregulated in CSF from VS recurrence (p < 0.05) as in VS grade II patients (Table 4). ELISA analysis was performed in CSF from VS recurrence and grade II patients (Table 2). The data revealed that ABCA3, CA2D1, and KLF11 increased (Fig. 5B) while BASP1 and PDRX2 decreased (Fig. 5C) significantly in recurrence and grade III in comparison with the control group. SCG1 did not change in
recurrence, although it increased in grade III compared with the control group (Fig. 5B). OPCM, CCS, and APOA1 revealed no alteration in recurrence or grade III in comparison with the control group (Fig. 5D). These data suggest that upregulation of ABCA3, CA2D1, and KLF11 and the downregulation of BASP1 and PDRX2 may be associated with the recurrence of VS. 6
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control and monitoring. Proteomic analysis of CSF is a useful method for investigating protein expression during the pathogenesis of brain tumors [4,5]. However, there have been few studies examining the protein composition of the CSF of VS. Using CSF samples from 6 patients, Kazemizadeh et al. [9] detected 237 proteins and identified 26 candidate VS CSF biomarkers, including 6 upregulated proteins, 7 downregulated proteins, and 13 dysregulation proteins. We detected 431 proteins in CSF and found that 39 to 58 proteins were upregulated, while 124 to 204 proteins were downregulated in grade I–V VS patients, respectively. Of the upregulated proteins reported by Kazemizadeh et al, 2 proteins overlapped the upregulated proteins, 1 protein overlapped the downregulated proteins, and 10 proteins overlapped the dysregulation proteins. Of these downregulated proteins, 7 proteins overlapped the downregulated proteins and 1 protein overlapped the dysregulated proteins. However, in their study, the sample size was small, and the patients were not divided into different grades. The control group in their study consisted of children with acute leukemia, which may contribute to the differences between our results and theirs. Seo et al [8] found 29 proteins showing significant changes in the expression level between VS tissue and normal nerve tissue, 7 of which were related to apoptosis, but they did not identify any proteins related to the growth of VS. In these proteins, only 1 protein (Annexin A2) could be detected but showed no alteration in VS CSF in our study, although they reported it was upregulated in VS tissue. The difference in samples may be the main cause of the different results between our study and theirs. Analysis of the differential protein in present study showed that the top enriched pathway and function are the immune system pathway and complement activity, respectively. Inflammation and angiogenesis play a pivotal role in the volumetric growth of VS [16,17]. Lewis D et al recently provided in vivo imaging evidence that increased inflammation correlates with growing VS [18]. Complement activation in inflammatory conditions is thought to contribute significantly to end organ damage [19], which may be related to hearing loss induced by
Table 3 Correlation of tumor size with protein levels in CSF.a Protein
Pearson r
p value
Correlation significance
R2
ABCA3 SCG1 KLF11 CA2D1 APOA1 OPCM CCS BASP1 PRDX2
0.8542 −0.4135 0.6065 0.1072 0.0546 −0,2707 −0.0836 −0.7207 −0.5024
< 0.0001 0.0065 < 0.0001 0.4993 0.7380 0.0829 0.5988 < 0.0001 0.0007
Yes Yes Yes No No No No Yes Yes
0.7297 0.1710 0.3679 0.0115 0.0003 0.0733 0.0070 0.5195 0.2525
a The samples included CSF from VS grade I-III and the control group as in Table 2.
4. Discussion In this study, we used iTARQ-based proteomics analysis and ELISA verification to analyze the CSF of VS patients, which identified SCG1, KLF11, and CA2D1 as early biomarkers of VS. The increased ABCA3 and KLF11 and the decreased BASP1 and PRDX2 were associated with the growth of VS in the early phase. The upregulation of ABCA3, CA2D1, and KLF11 and the downregulation of BASP1 and PRDX2 correlated with the recurrence of VS. In the restricted, compact area of the cerebellopontine angle, where there are multiple vascular and neural structures, growing VS oppresses and shifts most cranial nerves or even the brain stem in the posterior cranial fossa, causing severe clinical symptoms [14]. Although surgery could remove the tumor, it would affect the function of such structures as mentioned above during treatment, leading to many complications [2,3,15]. Moreover, most VS tumors show slow-growing characteristics, and the wait-and-see approach is often used for treatment, during which tumor growth is monitored regularly. Therefore, identification of molecular markers indicative of tumor growth is necessary for tumor
Fig. 5. iTRAQ-based proteomic analysis and ELISA verification of the 9 proteins in CSF from VS recurrence. (A) Heatmap of overlapping down-regulated (green) (fold change < 0.83) and up-regulated (red) (fold change > 1.2) CSF proteins in patients with VS recurrence and grade II vs control subjects. (B) ELISA analysis of ABCA3, SCG1, KLF11, and CA2D1 concentration in CSF from VS recurrence, grade II, and control group. (C) ELISA analysis of BASP1 and PRDX2 concentration in CSF from VS recurrence, grade II, and control group. (D) ELISA analysis of APOA1, OPCM, and CCS concentration in CSF from VS recurrence, grade II, and control group. Control: n = 3; grade II: n = 7; recurrence: n = 4. *p < 0.05 vs control group; **p < 0.01 vs control group. 7
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Table 4 iTRAQ ratio and p value of proteins in CSF form VS recurrence patients. Identified Protein
Accession Number
Entrez ID
iTRAQ ratio
p
ATP-binding cassette sub-family A member 3 Secretogranin-1 Krueppel-like factor 11 Voltage-dependent calcium channel subunit alpha-2/delta-1 Apolipoprotein A-I Opioid-binding protein/cell adhesion molecule Copper chaperone for superoxide dismutase Brain acid soluble protein 1 Peroxiredoxin-2
ABCA3_HUMAN SCG1_HUMAN KLF11_HUMAN CA2D1_HUMAN APOA1_HUMAN OPCM_HUMAN CCS_HUMAN BASP1_HUMAN PRDX2_HUMAN
21 1114 8462 781 335 4978 9973 10409 7001
9.10 3.28 9.39 8.96 73.74 1.27 60.44 0.23 0.63
0.0251 0.0405 0.0232 0.0121 0.3100 0.7125 0.4221 0.0053 0.0058
affinity binding site for gabapentin (GBP); and GBP treatment may be associated with improvement of epilepsy, postherpetic neuralgic pain, and sleep disorders [38,42]. In this study, CA2D1 increased in CSF from VS grade I–V and recurrence. The detailed molecular mechanisms need further study. BASP1, belonging to the group of growth-associated proteins, is upregulated during neuritogenesis and axonal regeneration [43,44]. However, recent studies have revealed that BASP1 is downregulated in multiple tumors, including hepatocellular carcinomas and several leukemias, by gene methylation [45,46], suggesting it is a significant tumor suppressor. PRDX2 is a neuronal-specific peroxiredoxin [47] that participates in cerebral antioxidant responses [48] in multiple neurodegenerative diseases, including Parkinson’s disease [49]. PRDX2 deficiency exaggerated ischemic neuronal injury by directly modulating the redox-sensitive signaling [50]. The present study revealed that BASP1 and PRDX2 were downregulated in CSF from VS grade I–V and recurrence, suggesting these may promote the growth of VS, which is evidenced by the negative correlation between BSAP2 or PRDX2 level in CSF and the size of VS. The reduced expression of PRDX2 in CSF from VS grade I–V and recurrence may increase accessibility to acoustic nerve damage in response to oxidative stress. One limitation of this study is the use of only three CSF control samples and one CSF sample of a grade I VS patient for iTRAQ analysis. In the present study, the CSF samples of the control group came from patients with acute brain trauma. Most CSF samples from acute brain trauma patients are mixed with blood. To ensure the quality of the experiment, we carefully selected the CSF samples from the control group to ensure they were pure and without any blood. We also excluded other diseases such as other cancers or cardiovascular diseases. This greatly limited the number of patients enrolled into our study as controls. According to the guidelines of VS treatment, patients with small tumors less than 2 cm are recommended for gamma knife treatment, unless they insist on tumor removal surgery. Thus, many patients with small VS prefer gamma knife treatment to surgery. Hence, we had only one case of grade I for iTRAQ analysis, but we collected more CSF samples for verification using ELISA analysis. The other limitation of this study is the need for further experiments to clarify whether increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 promote the growth of VS.
VS. These findings suggest that the inhibition of the inflammatory process or complement activation may be considered as novel therapeutic targets for VS. Our data first identified six proteins (ABCA3, KLF11, SCG1, CA2D1, BASP1, and PRDX2) in CSF related to VS growth, five of which were associated with recurrence of VS. ABCA3 is highly expressed in the lungs, followed by brain, pancreas, skeletal muscle, and heart. In lung tissue, it localizes to the limiting membrane of lamellar bodies (LBs) in alveolar epithelial type II (ATII) cells [20]. It contributes to the biogenesis of LBs or protection of ATII cells by lipid transport, particularly in phosphatidylcholine and phosphatidylglycerol trafficking [21,22]. In brain tissue, ABCA3 is expressed in total in all cell types including oligodendrocytes, neurons, astrocytes, and microglia [23,24], but the role of ABCA3 in the brain is currently unclear. High ABCA3 expression in non–small-cell lung cancer has been correlated with a poor prognosis [25]. In addition, ABCA3 is also overexpressed in childhood acute myeloid leukemia (AML), which results in multidrug resistance and poor outcome of chemotherapy in AML [26,27]. In this study, we observed that ABCA3 increased in CSF from grade II–V VS and recurrence, and ABCA3 was positively correlated with the size of the tumor in grade III VS. Detailed examination of the role of ABCA3 in VS cells will provide further insight into the relationship between ABCA3 and the growth and recurrence of VS. KLF11 belongs to the Sp1/Krüppel-like factor zinc finger transcription factor (Sp1/KLF) family [28] and is widely expressed in many tissues. It inhibits the growth of tumor cells, suppresses the angiogenesis of tumor tissue, and enhanced the apoptosis of tumor cells in vitro and in vivo [29] by inhibition of the transforming growth factor-β (TGFβ) signaling pathway [30]. The reduced expression of KLF11 in several types of cancer [31] is associated with tumorigenesis and tumor development. The data presented here show that the KLF11 level in CSF is increased in VS grade I and further increased in VS grade II, whereas it begins to decrease in VS grade III compared with the control group. Considering the role of TGF-β in VS cell replication [32], increased KLF11 may contribute to the slow growth of VS via regulation of TGF-β. SCG1, also known as chromogranin B (CHGB), a member of the chromogranin gene family, is expressed in secretory granules of neuroendocrine cells and neurons [33]. It is a high-capacity, low-affinity calcium-binding protein [34] and has been proposed as a candidate gene related to the risk of schizophrenia [35] as well as a biomarker for pancreatic neuroendocrine tumors in Japanese patients [36]. The increase in SCG1 in CSF has been found in patients in the early stages of multiple sclerosis [37]. This study revealed that SCG1 was increased in CSF with VS grade I and II but showed no alteration in patients with VS grade III–V or recurrence. In VS patients, it was negatively correlated with the growth of VS. It may be one of the early biomarkers of VS, but the level is not related to the growth of VS. Further studies are needed to elucidate its role in the early phases of VS pathogenesis and its potential as a biomarker for VS. CA2D1 is highly expressed in the brain, heart, skeletal system, and smooth muscle [38]. The upregulation of CA2D1 was observed in response to spinal injury and neuropathic pain [39–41]. It has a high-
5. Conclusion In this study, we identified a pattern of CSF-secreted proteins by iTRAQ analysis that might discriminate patients with VS from controls and particularly those with recurrence from controls. Using ELISA to validate these findings, our study first revealed that SCG1, KLF11, and CA2D1 are early biomarkers of VS, and increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 in CSF are associated with VS growth in the early phase. CA2D1, ABCA3, KLF11, BASP1 and PRDX2 are also related to VS recurrence. It is crucial to characterize early biomarkers or effective therapeutic targets for VS to improve patients’ quality of life. 8
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Funding [13]
This work was supported by Shanghai Science and Technology Commission, China (grant 134119a4700), “Yang Fan” project (grant 15YF1401500), “China Spark Program” supported by the Ministry of Science and Technology, China (grant S2013C000013) and Natural Science Foundation of Shanghai(grant 17ZR1403800).
[14] [15]
Ethics approval and consent to participate
[16]
This study was approved by the Research Ethics Committee of Huashan Hospital, Fudan University. Informed consent was obtained from all patients in the study. The privacy rights of human subjects was always observed.
[17] [18]
Availability of data and material The data sets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
[19]
Conflict of interest
[20]
There is no conflict of interest to be disclosed.
[21]
Acknowledgements
[22]
Not applicable.
[23]
Appendix A. Supplementary data
[24]
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.biopha.2019.108985.
[25]
References
[26]
[1] L.G. Bian, W. Tirakotai, Q.F. Sun, W.G. Zhao, J.K. Shen, Q.Z. Luo, Molecular genetics alterations and tumor behavior of sporadic vestibular schwannoma from the People’s Republic of China, J. Neurooncol. 73 (3) (2005) 253–260. [2] X. Huang, M. Xu, J. Xu, L. Zhou, P. Zhong, M. Chen, K. Ji, H. Chen, Y. M, Complications and management of large intracranial vestibular schwannomas via the retrosigmoid approach, World Neurosurg. 99 (2017) 326–335. [3] X. Huang, J. Xu, M. Xu, M. Chen, K. Ji, J. Ren, P. Zhong, Functional outcome and complications after the microsurgical removal of giant vestibular schwannomas via the retrosigmoid approach: a retrospective review of 16-year experience in a single hospital, BMC Neurol. 17 (1) (2017) 18. [4] S. Roy, S.A. Josephson, J. Fridlyand, J. Karch, C. Kadoch, J. Karrim, L. Damon, P. Treseler, S. Kunwar, M.A. Shuman, T. Jones, C.H. Becker, H. Schulman, J.L. Rubenstein, Protein biomarker identification in the CSF of patients with CNS lymphoma, J. Clin. Oncol. 26 (1) (2008) 96–105. [5] F.W. Khwaja, M.S. Reed, J.J. Olson, B.J. Schmotzer, G.Y. Gillespie, A. Guha, M.D. Groves, S. Kesari, J. Pohl, E.G. Van Meir, Proteomic identification of biomarkers in the cerebrospinal fluid (CSF) of astrocytoma patients, J. Proteome Res. 6 (2) (2007) 559–570. [6] M.U. Rajagopal, Y. Hathout, T.J. Macdonald, M.W. Kieran, S. Gururangan, S.M. Blaney, P. Phillips, R. Packer, H. Gordish-Dressman, B.R. Rood, Proteomic profiling of cerebrospinal fluid identifies prostaglandin D2 synthase as a putative biomarker for pediatric medulloblastoma: a pediatric brain tumor consortium study, Proteomics 11 (5) (2011) 935–943. [7] F. Shen, Y. Zhang, Y. Yao, W. Hua, H.S. Zhang, J.S. Wu, P. Zhong, L.F. Zhou, Proteomic analysis of cerebrospinal fluid: toward the identification of biomarkers for gliomas, Neurosurg. Rev. 37 (3) (2014) 367–380 discussion 80. [8] J.H. Seo, K.H. Park, E.J. Jeon, K.H. Chang, H. Lee, W. Lee, Y.S. Park, Proteomic analysis of vestibular schwannoma: conflicting role of apoptosis on the pathophysiology of sporadic vestibular schwannoma, Otol. Neurotol. 36 (4) (2015) 714–719. [9] M.A. Kazemizadeh Gol, T.C. Lund, S.C. Levine, M.E. Adams, Quantitative proteomics of vestibular schwannoma cerebrospinal fluid: a pilot study, Otolaryngol. Head. Neck Surg. 154 (5) (2016) 902–906. [10] J. Kanzaki, M. Tos, M. Sanna, D.A. Moffat, E.M. Monsell, K.I. Berliner, New and modified reporting systems from the consensus meeting on systems for reporting results in vestibular schwannoma, Otol. Neurotol. 24 (4) (2003) 642–648 discussion 8–9. [11] M. Gilar, P. Olivova, A.E. Daly, J.C. Gebler, Two-dimensional separation of peptides using RP-RP-HPLC system with different pH in first and second separation dimensions, J. Sep. Sci. 28 (14) (2005) 1694–1703. [12] X. Yang, V. Dondeti, R. Dezube, D.M. Maynard, L.Y. Geer, J. Epstein, X. Chen,
[27]
[28]
[29]
[30] [31] [32] [33]
[34] [35] [36]
[37]
9
S.P. Markey, J.A. Kowalak, DBParser: web-based software for shotgun proteomic data analyses, J. Proteome Res. 3 (5) (2004) 1002–1008. J. Peng, J.E. Elias, C.C. Thoreen, L.J. Licklider, S.P. Gygi, Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/ MS) for large-scale protein analysis: the yeast proteome, J. Proteome Res. 2 (1) (2003) 43–50. X. Huang, J. Xu, M. Xu, L.F. Zhou, R. Zhang, L. Lang, Q. Xu, P. Zhong, M. Chen, Y. Wang, Z. Zhang, Clinical features of intracranial vestibular schwannomas, Oncol. Lett. 5 (1) (2013) 57–62. M.K. Turel, S. Thakar, V. Rajshekhar, Quality of life following surgery for large and giant vestibular schwannomas: a prospective study, J. Neurosurg. 122 (2) (2015) 303–311. M. De Vries, P.C. Hogendoorn, I. Briaire-De Bruyn, M.J. Malessy, A.G. Van Der Mey, Intratumoral hemorrhage, vessel density, and the inflammatory reaction contribute to volume increase of sporadic vestibular schwannomas, Virchows Arch.: Int. J. Pathol. 460 (6) (2012) 629–636. M. De Vries, I. Briaire-De Bruijn, M.J. Malessy, S.F. De Bruine, A.G. Van Der Mey, P.C. Hogendoorn, Tumor-associated macrophages are related to volumetric growth of vestibular schwannomas, Otol. Neurotol. 34 (2) (2013) 347–352. D. Lewis, F. Roncaroli, E. Agushi, D. Mosses, R. Williams, K.L. Li, X. Zhu, R. Hinz, R. Atkinson, A. Wadeson, S. Hulme, H. Mayers, E. Stapleton, S.K.L. Lloyd, S.R. Freeman, S.A. Rutherford, C. Hammerbeck-Ward, D.G. Evans, O. Pathmanaban, A. Jackson, A.T. King, D. Coope, Inflammation and vascular permeability correlate with growth in sporadic vestibular schwannoma, Neurooncology 21 (3) (2019) 314–325. W.C. Song, Membrane complement regulatory proteins in autoimmune and inflammatory tissue injury, Curr. Dir. Autoimmun. 7 (2004) 181–199. G. Yamano, H. Funahashi, O. Kawanami, L.X. Zhao, N. Ban, Y. Uchida, T. Morohoshi, J. Ogawa, S. Shioda, N. Inagaki, ABCA3 is a lamellar body membrane protein in human lung alveolar type II cells, FEBS Lett. 508 (2) (2001) 221–225. Y. Matsumura, H. Sakai, M. Sasaki, N. Ban, N. Inagaki, ABCA3-mediated cholinephospholipids uptake into intracellular vesicles in A549 cells, FEBS Lett. 581 (17) (2007) 3139–3144. A.B. Chai, A.J. Ammit, I.C. Gelissen, Examining the role of ABC lipid transporters in pulmonary lipid homeostasis and inflammation, Respir. Res. 18 (1) (2017) 41. W.S. Kim, G.J. Guillemin, E.N. Glaros, C.K. Lim, B. Garner, Quantitation of ATPbinding cassette subfamily-A transporter gene expression in primary human brain cells, Neuroreport 17 (9) (2006) 891–896. M.L. Fitzgerald, R. Xavier, K.J. Haley, R. Welti, J.L. Goss, C.E. Brown, D.Z. Zhuang, S.A. Bell, N. Lu, M. Mckee, B. Seed, M.W. Freeman, ABCA3 inactivation in mice causes respiratory failure, loss of pulmonary surfactant, and depletion of lung phosphatidylglycerol, J. Lipid Res. 48 (3) (2007) 621–632. T.R. Overbeck, J. Arnemann, R. Waldmann-Beushausen, L. Trumper, F.A. Schondube, K. Reuter-Jessen, B.C. Danner, ABCA3 phenotype in non-small cell lung cancer indicates poor outcome, Oncology 93 (4) (2017) 270–278. D. Steinbach, J.P. Gillet, A. Sauerbrey, B. Gruhn, K. Dawczynski, V. Bertholet, F. De Longueville, F. Zintl, J. Remacle, T. Efferth, ABCA3 as a possible cause of drug resistance in childhood acute myeloid leukemia, Clin. Cancer Res. 12 (14 Pt 1) (2006) 4357–4363. N. Aberuyi, S. Rahgozar, Z. Khosravi Dehaghi, A. Moafi, A. Masotti, A. Paolini, The translational expression of ABCA2 and ABCA3 is a strong prognostic biomarker for multidrug resistance in pediatric acute lymphoblastic leukemia, Onco. Ther. 10 (2017) 3373–3380. E. Kuroda, Y. Horikawa, M. Enya, N. Oda, E. Suzuki, K. Iizuka, J. Takeda, Identification of minimal promoter and genetic variants of Kruppel-like factor 11 gene and association analysis with type 2 diabetes in Japanese, Endocr. J. 56 (2) (2009) 275–286. M.E. Fernandez-Zapico, G.A. Lomberk, S. Tsuji, C.J. Demars, M.R. Bardsley, Y.H. Lin, L.L. Almada, J.J. Han, D. Mukhopadhyay, T. Ordog, N.S. Buttar, R. Urrutia, A functional family-wide screening of SP/KLF proteins identifies a subset of suppressors of KRAS-mediated cell growth, Biochem. J. 435 (2) (2011) 529–537. B. Spittau, K. Krieglstein, Klf10 and Klf11 as mediators of TGF-beta superfamily signaling, Cell Tissue Res. 347 (1) (2012) 65–72. C. Bureau, N. Hanoun, J. Torrisani, J.P. Vinel, L. Buscail, P. Cordelier, Expression and function of Kruppel Like-Factors (KLF) in carcinogenesis, Curr. Genom. 10 (5) (2009) 353–360. M. Bizzarri, R. Filipo, M.G. Valente, D. Bernardeschi, F. Ronchetti, S. Monini, I. Chiappini, M. Barbara, Release of transforming growth factor beta-1 in a vestibular schwannoma cell line, Acta Otolaryngol. 122 (7) (2002) 785–787. C. Nowakowski, W.A. Kaufmann, C. Adlassnig, H. Maier, K. Salimi, K.A. Jellinger, J. Marksteiner, Reduction of chromogranin B-like immunoreactivity in distinct subregions of the hippocampus from individuals with schizophrenia, Schizophr. Res. 58 (1) (2002) 43–53. L. Taupenot, K.L. Harper, D.T. O’connor, The chromogranin-secretogranin family, N. Engl. J. Med. 348 (12) (2003) 1134–1149. J.G. Shin, J.H. Kim, C.S. Park, B.J. Kim, J.W. Kim, I.G. Choi, J. Hwang, H.D. Shin, S.I. Woo, Gender-specific associations between CHGB genetic variants and schizophrenia in a Korean population, Yonsei Med. J. 58 (3) (2017) 619–625. M. Miki, T. Ito, M. Hijioka, L. Lee, K. Yasunaga, K. Ueda, T. Fujiyama, Y. Tachibana, K. Kawabe, R.T. Jensen, Y. Ogawa, Utility of chromogranin B compared with chromogranin A as a biomarker in Japanese patients with pancreatic neuroendocrine tumors, Jpn. J. Clin. Oncol. 47 (6) (2017) 520–528. A.C. Kroksveen, J.D. Jaffe, E. Aasebo, H. Barsnes, Y. Bjorlykke, D. Franciotta, H. Keshishian, K.M. Myhr, J.A. Opsahl, V. Van Pesch, C.E. Teunissen, O. Torkildsen, R.J. Ulvik, H. Vethe, S.A. Carr, F.S. Berven, Quantitative proteomics suggests decrease in the secretogranin-1 cerebrospinal fluid levels during the disease course of
Biomedicine & Pharmacotherapy 116 (2019) 108985
X. Huang, et al. multiple sclerosis, Proteomics 15 (19) (2015) 3361–3369. [38] H.C. Gong, J. Hang, W. Kohler, L. Li, T.Z. Su, Tissue-specific expression and gabapentin-binding properties of calcium channel alpha2delta subunit subtypes, J. Membr. Biol. 184 (1) (2001) 35–43. [39] R.A. Newton, S. Bingham, P.C. Case, G.J. Sanger, S.N. Lawson, Dorsal root ganglion neurons show increased expression of the calcium channel alpha2delta-1 subunit following partial sciatic nerve injury, Brain Res. Mol. Brain Res. 95 (1–2) (2001) 1–8. [40] T.L. Yaksh, Calcium channels as therapeutic targets in neuropathic pain, J. Pain 7 (1 Suppl. 1) (2006) S13–30. [41] M. Katsura, Y. Mohri, K. Shuto, Y. Hai-Du, T. Amano, A. Tsujimura, M. Sasa, S. Ohkuma, Up-regulation of L-type voltage-dependent calcium channels after long term exposure to nicotine in cerebral cortical neurons, J. Biol. Chem. 277 (10) (2002) 7979–7988. [42] G. Chouinard, The search for new off-label indications for antidepressant, antianxiety, antipsychotic and anticonvulsant drugs, J. Psychiatry Neurosci. 31 (3) (2006) 168–176. [43] H.M. Bomze, K.R. Bulsara, B.J. Iskandar, P. Caroni, J.H. Skene, Spinal axon regeneration evoked by replacing two growth cone proteins in adult neurons, Nat. Neurosci. 4 (1) (2001) 38–43. [44] M.R. Mason, A.R. Lieberman, G. Grenningloh, P.N. Anderson, Transcriptional upregulation of SCG10 and CAP-23 is correlated with regeneration of the axons of peripheral and central neurons in vivo, Mol. Cell. Neurosci. 20 (4) (2002) 595–615.
[45] E.J. Yeoh, M.E. Ross, S.A. Shurtleff, W.K. Williams, D. Patel, R. Mahfouz, F.G. Behm, S.C. Raimondi, M.V. Relling, A. Patel, C. Cheng, D. Campana, D. Wilkins, X. Zhou, J. Li, H. Liu, C.H. Pui, W.E. Evans, C. Naeve, L. Wong, J.R. Downing, Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling, Cancer Cell 1 (2) (2002) 133–143. [46] T. Moribe, N. Iizuka, T. Miura, M. Stark, S. Tamatsukuri, H. Ishitsuka, Y. Hamamoto, K. Sakamoto, T. Tamesa, M. Oka, Identification of novel aberrant methylation of BASP1 and SRD5A2 for early diagnosis of hepatocellular carcinoma by genome-wide search, Int. J. Oncol. 33 (5) (2008) 949–958. [47] M.L. Aon-Bertolino, J.I. Romero, P. Galeano, M. Holubiec, M.S. Badorrey, G.E. Saraceno, E.M. Hanschmann, C.H. Lillig, F. Capani, Thioredoxin and glutaredoxin system proteins-immunolocalization in the rat central nervous system, Biochim. Biophys. Acta 1810 (1) (2011) 93–110. [48] Y. Gan, X. Ji, X. Hu, Y. Luo, L. Zhang, P. Li, X. Liu, F. Yan, P. Vosler, Y. Gao, R.A. Stetler, J. Chen, Transgenic overexpression of peroxiredoxin-2 attenuates ischemic neuronal injury via suppression of a redox-sensitive pro-death signaling pathway, Antioxid. Redox Signal. 17 (5) (2012) 719–732. [49] A. Patenaude, M.R. Murthy, M.E. Mirault, Emerging roles of thioredoxin cycle enzymes in the central nervous system, Cell. Mol. Life Sci. 62 (10) (2005) 1063–1080. [50] T.H. Lee, S.U. Kim, S.L. Yu, S.H. Kim, D.S. Park, H.B. Moon, S.H. Dho, K.S. Kwon, H.J. Kwon, Y.H. Han, S. Jeong, S.W. Kang, H.S. Shin, K.K. Lee, S.G. Rhee, D.Y. Yu, Peroxiredoxin II is essential for sustaining life span of erythrocytes in mice, Blood 101 (12) (2003) 5033–5038.
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Protein profiling of cerebrospinal fluid from patients undergoing vestibular schwannoma surgery and clinical significance
T
Xiang Huanga,1, Jian Xua,1, Yiwen Shena, Lei Zhangb, Ming Xua, Mingyu Chena, Junwei Rena, ⁎⁎ ⁎ Liangfu Zhoua, Hui Gongb, , Ping Zhonga, a b
Department of Neurosurgery, Huashan Hospital, Fudan University, China Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, China
ARTICLE INFO
ABSTRACT
Keywords: Vestibular schwannoma Proteomic analysis Cerebrospinal fluid Recurrence iTRAQ
Vestibular schwannoma (VS) is a common disease in the region of the cerebellopontine angle in the posterior cranial fossa. Large VS and its surgical management usually lead to severe cranial nerve dysfunction and affect the patient’s quality of life. We aimed to find some possible progression markers of VS. Here, we sought to characterize the cerebrospinal fluid (CSF) proteome of patients with different VS grades and recurrence to identify biomarkers predictive of VS growth or recurrence. CSF was collected intraoperatively prior to removal of untreated VS, including grade I–V and recurrence. Isobaric tags for relative and absolute quantitation–based proteomic analysis of CSF from 43 VS patients and 3 control patients was used to identify candidate proteins. Ninety-three overlapping proteins were found to display differential expression in grade I, II, III, IV, and V VS patients compared with the control group. Nine proteins were chosen for validation with enzyme-linked immunosorbent assay. VS was distinguished from control patients based on the expression patterns of six proteins (ATP-binding cassette subfamily A member 3 [ABCA3], secretogranin-1 [SCG1], Krueppel-like factor 11 [KLF11], voltage-dependent calcium channel subunit alpha-2/delta-1 [CA2D1], brain acid soluble protein 1 [BASP1], and peroxiredoxin-2 [PRDX2]. ABCA3 and KLF11 were positively correlated with the size of earlyphase of VS, while BASP1 and PRDX2 showed a negative correlation. ABCA3, CA2D1, and KLF11 were upregulated, while BASP1 and PRDX2 were downregulated in the CSF from VS recurrence. But SCG1 was increased only at early-phase. These data suggest that increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 in CSF are associated with VS growth at the early phase or recurrence.
1. Introduction Vestibular schwannoma (VS), accounting for 8%–10% of all intracranial tumors, [1–3] is a common disease that develops in the cerebellopontine angle in the posterior cranial fossa. VS often grows slowly and is commonly treated with surgery. However, surgical treatment may lead to severe cranial nerve dysfunction and affect the patient’s quality of life. Hence, conservative management, such as “wait and see,” is often used for VS. As such, characterizing molecular
markers for tumor growth monitoring and tumor control could be critical to this disease management. The composition of cerebrospinal fluid (CSF) reflects molecules actively transported from the blood as well as secretions from intracranial tumors and brain. Therefore, CSF serves as a potential source of diagnostic and therapeutic targets. Differential proteomic analyses of CSF have yielded biomarkers for several brain tumors [4–7]. However, few studies have concentrated on the proteomic profile of VS to investigate potential biomarkers in CSF associated with VS growth
Abbreviations: ABCA3, ATP-binding cassette sub-family A member 3; AML, acute myeloid leukemia; APOA1, Apolipoprotein A–I; ATII, alveolar epithelial type II; BASP1, brain acid soluble protein 1; CA2D1, voltage-dependent calcium channel subunit alpha-2/delta-1; CCS, copper chaperone for superoxide dismutase; CHGB, chromogranin B; CSF, cerebrospinal fluid; ELISA, enzyme-linked immunosorbent assay; GBP, gabapentin; iTRAQ, isobaric tags for relative and absolute quantitation; KLF11, Krueppel-like factor 11; LBs, lamellar bodies; MS, multiple sclerosis; OPCM, opioid-binding protein; PRDX2, peroxiredoxin-2; SCG1, secretogranin-1; Sp1/ KLF, Sp1/Krüppel-like factor; TGF-β, transforming growth factor-β; VS, vestibular schwannoma ⁎ Corresponding author at: Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, China. ⁎⁎ Corresponding author at: Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China. E-mail addresses: [email protected] (H. Gong), [email protected] (P. Zhong). 1 These authors contribute equally. https://doi.org/10.1016/j.biopha.2019.108985 Received 30 March 2019; Received in revised form 24 April 2019; Accepted 13 May 2019 0753-3322/ © 2019 The Authors. Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
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physiology at the molecular level [8,9]. Here, using 43 CSF samples of VS, we applied Isobaric tags for relative and absolute quantitation (iTRAQ)–based proteomics analysis to identify proteins that are differentially expressed in CSF from different grades or recurrence of VS compared with the control group. Enzymelinked immunosorbent assay (ELISA) was subsequently used to verify the results in 87 CSF samples of VS. We aimed to elucidate novel biomarkers related to the growth and recurrence of VS that may serve as potential therapeutic targets for VS treatment.
collected (15 ml per patient) before tumor exposure via dura incisions, filtered (0.22 μm), and stored at −80 °C before analysis. The institutional review board of Huashan Hospital, Fudan University, approved the study protocol. Informed consent was obtained for all samples. 2.3. iTRAQ-based proteomics analysis The CSF from patients were analyzed to explore differential protein expression by iTRAQ-based proteomics technique as described previously [11]. In brief, total protein was concentrated and extracted from the CSF of patients with VS. The protein concentration was determined using the Bradford assay kit (Bio-Rad). Equal amounts of protein were labeled with iTRAQ reagent. Each labeled sample included a mixture of 2 to 10 protein samples from the same group. The labeled samples were combined and dried in vacuo for liquid chromatography tandem mass spectrometry (MS/MS) analysis. The analysis was repeated twice. To identify and quantify the protein, MS/MS data were analyzed with the ProteinPilot 2.0 software (Applied Biosytems). An iTRAQ ratio ≥1.2 or ≤0.83 was considered as up- or downregulation [12,13], respectively.
2. Materials and methods 2.1. Materials Bradford assay kits were obtained from Bio-Rad (USA). Human secretogranin-1 (SCG1), voltage-dependent calcium channel subunit alpha-2/delta-1 (CA2D1), brain acid soluble protein 1 (BASP1), peroxiredoxin-2 (PRDX2), ATP-binding cassette subfamily A member 3 (ABCA3), and Krueppel-like factor 11 (KLF11) ELISA kits were purchased from FUSHENG (Shanghai, China). 2.2. Clinical and patient sample information
2.4. ELISA
Our study included CSF samples for iTRAQ-based proteomics (43 samples) and ELISA analysis (87 samples) from VS patients who were undergoing surgery for sporadic VS from January 2014 and December 2016 in Huashan Hospital. Patients with prior meningitis or demyelinating disease were excluded. These VS patients were grouped by grade I to V and recurrence. Tumor size was categorized according to the international criteria using the largest extrameatal tumor diameter on the postcontrast axial magnetic resonance image (MRI) [10]. Grade I to V were grouped by the size of tumor according to international grading of VS size [10] (group I: < 1 cm; group II: 1–2 cm; group III: 2–3 cm; group IV: 3–4 cm; group V: 4–5 cm) (Fig. 1). The recurrence group included patients undergoing a second surgery for recurrent VS. Among the 98 CSF specimens, 43 specimens were examined by iTRAQ-based proteomics analysis, while 87 specimens were subsequently validated by ELISA. There were 32 overlapping cases in two groups. The control CSF was from 3 normal adults without brain tumor, meningitis, or demyelinating disease via lumbar punctures. CSF from all patients was
Protein expression levels characterized by proteomic analysis in CSF were validated by ELISA. In brief, CSF samples, which we collected from patients, were centrifuged at 4 °C for 20 min, and then the supernatant was collected and stored at −80 °C. An ELISA kit (FUSHENG, Shanghai, China) was used for measuring these protein levels mentioned above in CSF according to the manufacturer’s protocols. 2.5. Statistical analysis Data are expressed as mean ± SEM. Student’s t-test was applied to two-group comparisons. One-way ANOVA with Bonferroni post hoc test was used to multiple group comparisons. Statistical analyses and correlation analysis were carried out using Prism 5. Values of p < 0.05 were considered statistically significant.
Fig. 1. VS tumor size grade on postcontrast axial MRI according to international grading of the size of VS. (A) Group I: < 1 cm. (B) Group II: 1–2 cm. (C) Group III: 2–3 cm. (D) Group IV: 3–4 cm. (E) Group V: 4–5 cm. 2
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Table 1 Baseline characteristics of control and patients with VS, and analysis of CSF with iTRAQ-based proteomics.* Variable
Male/female Age (years) Tumor size (cm) Preoperative Hearing SBP (mmHg) DBP (mmHg) AST (u/L) ALT (u/L) Creatinine (μmol/L) Medical history Shock Hypertension Diabetes mellitus Proteins Dysregulated (n)
Control
AC Hearing classa
Up Down
VS I
II
III
IV
V
Recurrence
3/0 34.0 ± 8.5 – – – 127 ± 6.6 87.3 ± 11.0 48.0 ± 26.6 32.7 ± 17.0 69.0 ± 12.1
1/0 68 0.9 75 3 118 80 13 13 75
2/3 44.8 ± 12.0 1.7 ± 0.1 56.5 ± 35.2 2.3 ± 1.0 123.2 ± 6.4 77.4 ± 5.6 18.0 ± 5.7 21.4 ± 12.1 62.6 ± 10.2
3/6 46.4 ± 15.2 2.6 ± 0.3 71.0 ± 26.0 3.1 ± 1.0 129.7 ± 10.1 84.1 ± 5.2 15.9 ± 3.4 20.1 ± 1.0 66.3 ± 14.0
4/10 48.6 ± 13.1 3.2 ± 0.2 63.0 ± 19.2 2.9 ± 0.8 125.3 ± 12.0 78.9 ± 5.9 18.4 ± 4.9 22.9 ± 11.9 65.6 ± 12.9
5/8 46.1 ± 14.8 4.4 ± 0.5 62.0 ± 25.3 3.1 ± 0.9 122.3 ± 9.1 77.5 ± 6.3 20.4 ± 9.0 28.2 ± 20.0 73.5 ± 18.7
1/0 38 3.5 – 4 110 70 21 26 67
0 0 0 – –
0 0 0 58 124
0 1 0 39 161
0 1 0 55 195
0 3 0 64 204
0 0 0 39 162
0 0 0 44 147
Abbreviations: VS vestibular schwannoma; AC air conduction; SBP systolic pressure; DBP diastolic pressure; AST aspartate aminotransferase; ALT alanine aminotransferase. * VS patients were grouped with I–V, and recurrence. a The criteria used for the preoperative hearing evaluations were provided by the classification method of the American Institute of Otolaryngology–Head and Neck Surgery (AAO-HNS), 1995.
constituent, and immunoglobulin binding in line with these pathways mentioned above (Fig. 2C).
3. Results 3.1. Differentially expressed proteins were identified in CSF from patients with VS
3.3. Nine proteins in CSF correlate with the size of VS
To explore which proteins or factors in CSF affect the growth rate of VS, we analyzed differentially expressed proteins in CSF between control group and patients with VS (including grade I, II, III, IV, V, and recurrence) by iTRAQ-based proteomics analysis. Table 1 summarizes the basic characteristics of the 43 VS patients aged 21–69 years and in groups I–V and recurrence. iTRAQ ratio > 1.2 or ratio < 0.83 and p values < 0.05 were considered as upregulation or downregulation, respectively. We compared the control group to VS grade I, II, III, IV, or recurrence. Of the 431 proteins detected, 58 proteins were upregulated in grade I, 39 proteins in grade II, 55 proteins in grade III, 64 proteins in grade IV, 39 proteins in grade V, and 44 proteins in recurrence. A total of 124 proteins were found to be downregulated in grade I, 161 proteins in grade II, 195 proteins in grade III, 204 proteins in grade IV, 162 proteins in grade V, and 147 proteins in recurrence compared with the control group.
After performing Ingenuity Pathway Analysis (IPA) analysis, the expression of nine proteins was found to be associated with the grade of VS. Among these proteins, Apolipoprotein A–I (APOA1) and ABCA3 were upregulated in CSF in a size-dependent manner. APOA1 levels in CSF reached peaked at grade IV, while ABCA3 levels in CSF were highest in grade III. This suggests that increased expression of these two factors may positively relate to the growth of VS. KLF11 and SCG1 showed a sharp increase in CSF from the grade I and II groups, but KLF increased less and SCG1 revealed no increase in CSF from the grade III–V groups compared with control group. CA2D1 and opioid-binding protein (OPCM) were increased greatly in CSF from the grade I group but then began to decrease in the grade II group. This may indicate that an increase in CA2D1 and OPCM levels are related to the early stages of VS. Copper chaperone for superoxide dismutase (CCS) levels in CSF were the highest in the grade II group. Although levels decreased in CSF in the grade III group, they remained 20-fold higher than in the control group (Fig. 3A). Two proteins (BASP1 and PRDX2) were greatly downregulated in the CSF of VS compared with the control group (Fig. 3B). The protein-protein interactions among the 9 proteins were analyzed by FunRich_V3. The result indicated that SCG1 could indirectly interact with APOA1 via proteins such as LBP, CP, and others. There were no direct interactions among the other 7 proteins (Fig. 3C).
3.2. Function and pathway analysis of differentiated protein in grade I–V VS patients Ninety-three proteins showed overlapping expression patterns in VS patients with grade I, II, III, IV, and V compared with the control group. Eleven proteins were upregulated while 82 proteins were downregulated in CSF from patients with grade I–V compared with the control group (Fig. 2A). We then analyzed the functions and pathways in which these proteins were involved using FunRich_V3. These proteins were mapped to several pathways. The top six enriched pathways (p < 0.001) were the immune system pathway, hemostasis pathway, integrin family interaction, complement cascade, superoxide radicals degradation, and glypican pathway (Fig. 2B). We also performed functional enrichment analysis on the differentially expressed proteins. Protease inhibitor activity was identified as the most enriched biological process. The other top 7 significantly enriched functions were complement activity, calcium ion binding, transporter activity, metal ion binding, peroxidase activity, extracellular matrix structural
3.4. ELISA analysis identified 6 proteins in CSF associated with the growth of VS We then performed an ELISA test in CSF from 87 VS patients aged 19–69 years (46.3 ± 13.5 years). Of these 87 patients, 83 (95.4%) were untreated VS, 4 (4.6%) were recurrent VS, and 32 patients overlapped with patients by iTRAQ analysis. The clinical characteristics of VS patients are summarized in Table 2. Compared with the control group, ABCA3 levels increased in CSF from grade II–V and were highest in group III. KLF11 and CA2D1 levels increased in CSF from grades I–V and reached a maximum in grade II and grade I, respectively. SCG1 3
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Fig. 2. Proteomic analysis of CSF from VS grade I–V patients and control subjects. (A) Heatmap of down-regulated (green) (fold change < 0.83) and up-regulated (red) (fold change > 1.2) CSF proteins in patients VS grade I–V vs control subjects. (B) Top six pathways and (C) top seven functions in which differentially expressed proteins were involved were analyzed by FunRich_V3 Software.
increased in CSF from grade I and II, but it showed no alteration in grades III–V (Fig. 4A). BASP1 and PRDX2 decreased in CSF from grades II–V (Fig. 4B). These data coincide with the results observed in
proteomic analysis. However, there was no difference in these factors between female and male patients (Supplementary Table 1). Moreover, APOA1, OPCM, and CCS showed no change between grades I–V and the 4
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Fig. 3. Nine proteins associated with growth of VS were screened out by iTRAQ-based proteomics analysis. (A) iTRAQ ratio of ABCA3, SCG1, KLF11, CA2D1, APOA1, OPCM, and CCS in CSF from VS grade I–V compared with the control group. (B) iTRAQ ratio of BASP1 and PRDX2 in CSF from VS grade I–V compared with the control group. (C) The protein-protein interactions among the 9 proteins mentioned in A and B were analyzed by FunRich_V3 Software.
control group (Fig. 4C). Next, we analyzed the correlation of tumor size with these proteins. This analysis revealed that ABCA3 and KLF11 were positively correlated with size, while BASP1 and PRDX2 were negatively correlated with the tumor size under grade III (Table 3). These data suggest that the increased levels SCG1, KLF11, and CA2D1 may serve as early biomarkers of VS.
3.5. Identification of 5 proteins in CSF associated with the recurrence of VS In CSF, 10 overlapping proteins were upregulated and 76 overlapping proteins were downregulated in grade II and recurrence patients compared with the control group (Fig. 5A). Clinical characteristics of VS recurrence patients are summarized in Table 1. Proteomic analysis revealed that ABCA3 (iTRAQ ratio: 9.10), SCG1 (iTRAQ ratio: 3.28), KLF11 (iTRAQ ratio: 9.39), and CA2D19 (iTRAQ ratio: 8.96)
Table 2 Baseline characteristics of control and patients with VS, and analysis of CSF with ELISA.*. Variable
Male/female Age (years) Tumor size (cm) Preoperative Hearing SBP (mmHg) DBP (mmHg) AST (u/L) ALT (u/L) Creatinine (μmol/L) Medical history Shock Hypertension Diabetes mellitus
Control
AC Hearing classa
VS I
II
III
IV
V
Recurrence
3/0 34.0 ± 8.5 – – – 127 ± 6.6 87.3 ± 11.0 48.0 ± 26.6 32.7 ± 17.0 69.0 ± 12.1
2/1 55.0 ± 18.4 0.9 ± 0 55.0 ± 28.3 2.5 ± 0.7 124.5 ± 9.2 84.5 ± 6.4 15.0 ± 2.8 16.0 ± 4.2 63.0 ± 17.0
2/5 46.7 ± 13.1 1.8 ± 0.1 49.7 ± 29.6 2.0 ± 1.0 128.0 ± 8.4 82.9 ± 7.6 23.0 ± 8.4 32.1 ± 20.5 58.7 ± 11.9
10/20 45.7 ± 11.4 2.6 ± 0.3 53.6 ± 28.5 2.8 ± 1.1 124.2 ± 14.2 80.0 ± 8.2 20.2 ± 12.6 23.5 ± 13.7 61.9 ± 16.1
7/13 48.6 ± 14.4 3.4 ± 0.3 62.3 ± 19.8 3.1 ± 0.7 127.5 ± 10.8 79.2 ± 6.5 22.8 ± 10.1 25.9 ± 13.6 63.1 ± 15.0
9/14 44.1 ± 16.2 4.5 ± 0.5 62.8 ± 25.1 3.3 ± 0.9 121.2 ± 10.2 79.1 ± 6.6 20.3 ± 8.4 26.5 ± 18.6 67.7 ± 15.4
3/1 47.5 ± 8.8 3.4 ± 0.8 – 4.0 ± 0 129.5 ± 15.4 79.5 ± 14.1 20.8 ± 8.8 27.8 ± 12.9 65.3 ± 4.9
0 0 0
0 0 0
0 1 0
0 7 1
0 4 1
0 1 1
0 2 1
Abbreviations: VS: vestibular schwannoma; AC: air conduction; SBP: systolic pressure; DBP: diastolic pressure; AST: aspartate aminotransferase; ALT: alanine aminotransferase. * VS patients were grouped with I, II, III, IV, V, and recurrence. a The criteria used for the preoperative hearing evaluations were provided by the classification method of the American Institute of Otolaryngology–Head and Neck Surgery (AAO-HNS), 1995. 5
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Fig. 4. ELISA verification of the 9 proteins associated with the growth of VS. (A) The concentrations of ABCA3, SCG1, KLF11, and CA2D1 in CSF were from VS grade I–V and the control group. (B) The concentrations of BASP1 and PRDX2 in CSF were from VS grade I–V and the control group. (C) The concentrations of APOA1, OPCM, and CCS in CSF were from VS grade I–V and the control group. Control: n = 3; grade I: n = 3; grade II: n = 7; grade III, n = 30; grade IV, n = 20; grade V, n = 23. *p < 0.05 vs control group; **p < 0.01 vs control group.
were upregulated while BASP1 (iTRAQ ratio: 0.23) and PRDX2 (iTRAQ ratio: 0.63) were downregulated in CSF from VS recurrence (p < 0.05) as in VS grade II patients (Table 4). ELISA analysis was performed in CSF from VS recurrence and grade II patients (Table 2). The data revealed that ABCA3, CA2D1, and KLF11 increased (Fig. 5B) while BASP1 and PDRX2 decreased (Fig. 5C) significantly in recurrence and grade III in comparison with the control group. SCG1 did not change in
recurrence, although it increased in grade III compared with the control group (Fig. 5B). OPCM, CCS, and APOA1 revealed no alteration in recurrence or grade III in comparison with the control group (Fig. 5D). These data suggest that upregulation of ABCA3, CA2D1, and KLF11 and the downregulation of BASP1 and PDRX2 may be associated with the recurrence of VS. 6
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control and monitoring. Proteomic analysis of CSF is a useful method for investigating protein expression during the pathogenesis of brain tumors [4,5]. However, there have been few studies examining the protein composition of the CSF of VS. Using CSF samples from 6 patients, Kazemizadeh et al. [9] detected 237 proteins and identified 26 candidate VS CSF biomarkers, including 6 upregulated proteins, 7 downregulated proteins, and 13 dysregulation proteins. We detected 431 proteins in CSF and found that 39 to 58 proteins were upregulated, while 124 to 204 proteins were downregulated in grade I–V VS patients, respectively. Of the upregulated proteins reported by Kazemizadeh et al, 2 proteins overlapped the upregulated proteins, 1 protein overlapped the downregulated proteins, and 10 proteins overlapped the dysregulation proteins. Of these downregulated proteins, 7 proteins overlapped the downregulated proteins and 1 protein overlapped the dysregulated proteins. However, in their study, the sample size was small, and the patients were not divided into different grades. The control group in their study consisted of children with acute leukemia, which may contribute to the differences between our results and theirs. Seo et al [8] found 29 proteins showing significant changes in the expression level between VS tissue and normal nerve tissue, 7 of which were related to apoptosis, but they did not identify any proteins related to the growth of VS. In these proteins, only 1 protein (Annexin A2) could be detected but showed no alteration in VS CSF in our study, although they reported it was upregulated in VS tissue. The difference in samples may be the main cause of the different results between our study and theirs. Analysis of the differential protein in present study showed that the top enriched pathway and function are the immune system pathway and complement activity, respectively. Inflammation and angiogenesis play a pivotal role in the volumetric growth of VS [16,17]. Lewis D et al recently provided in vivo imaging evidence that increased inflammation correlates with growing VS [18]. Complement activation in inflammatory conditions is thought to contribute significantly to end organ damage [19], which may be related to hearing loss induced by
Table 3 Correlation of tumor size with protein levels in CSF.a Protein
Pearson r
p value
Correlation significance
R2
ABCA3 SCG1 KLF11 CA2D1 APOA1 OPCM CCS BASP1 PRDX2
0.8542 −0.4135 0.6065 0.1072 0.0546 −0,2707 −0.0836 −0.7207 −0.5024
< 0.0001 0.0065 < 0.0001 0.4993 0.7380 0.0829 0.5988 < 0.0001 0.0007
Yes Yes Yes No No No No Yes Yes
0.7297 0.1710 0.3679 0.0115 0.0003 0.0733 0.0070 0.5195 0.2525
a The samples included CSF from VS grade I-III and the control group as in Table 2.
4. Discussion In this study, we used iTARQ-based proteomics analysis and ELISA verification to analyze the CSF of VS patients, which identified SCG1, KLF11, and CA2D1 as early biomarkers of VS. The increased ABCA3 and KLF11 and the decreased BASP1 and PRDX2 were associated with the growth of VS in the early phase. The upregulation of ABCA3, CA2D1, and KLF11 and the downregulation of BASP1 and PRDX2 correlated with the recurrence of VS. In the restricted, compact area of the cerebellopontine angle, where there are multiple vascular and neural structures, growing VS oppresses and shifts most cranial nerves or even the brain stem in the posterior cranial fossa, causing severe clinical symptoms [14]. Although surgery could remove the tumor, it would affect the function of such structures as mentioned above during treatment, leading to many complications [2,3,15]. Moreover, most VS tumors show slow-growing characteristics, and the wait-and-see approach is often used for treatment, during which tumor growth is monitored regularly. Therefore, identification of molecular markers indicative of tumor growth is necessary for tumor
Fig. 5. iTRAQ-based proteomic analysis and ELISA verification of the 9 proteins in CSF from VS recurrence. (A) Heatmap of overlapping down-regulated (green) (fold change < 0.83) and up-regulated (red) (fold change > 1.2) CSF proteins in patients with VS recurrence and grade II vs control subjects. (B) ELISA analysis of ABCA3, SCG1, KLF11, and CA2D1 concentration in CSF from VS recurrence, grade II, and control group. (C) ELISA analysis of BASP1 and PRDX2 concentration in CSF from VS recurrence, grade II, and control group. (D) ELISA analysis of APOA1, OPCM, and CCS concentration in CSF from VS recurrence, grade II, and control group. Control: n = 3; grade II: n = 7; recurrence: n = 4. *p < 0.05 vs control group; **p < 0.01 vs control group. 7
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Table 4 iTRAQ ratio and p value of proteins in CSF form VS recurrence patients. Identified Protein
Accession Number
Entrez ID
iTRAQ ratio
p
ATP-binding cassette sub-family A member 3 Secretogranin-1 Krueppel-like factor 11 Voltage-dependent calcium channel subunit alpha-2/delta-1 Apolipoprotein A-I Opioid-binding protein/cell adhesion molecule Copper chaperone for superoxide dismutase Brain acid soluble protein 1 Peroxiredoxin-2
ABCA3_HUMAN SCG1_HUMAN KLF11_HUMAN CA2D1_HUMAN APOA1_HUMAN OPCM_HUMAN CCS_HUMAN BASP1_HUMAN PRDX2_HUMAN
21 1114 8462 781 335 4978 9973 10409 7001
9.10 3.28 9.39 8.96 73.74 1.27 60.44 0.23 0.63
0.0251 0.0405 0.0232 0.0121 0.3100 0.7125 0.4221 0.0053 0.0058
affinity binding site for gabapentin (GBP); and GBP treatment may be associated with improvement of epilepsy, postherpetic neuralgic pain, and sleep disorders [38,42]. In this study, CA2D1 increased in CSF from VS grade I–V and recurrence. The detailed molecular mechanisms need further study. BASP1, belonging to the group of growth-associated proteins, is upregulated during neuritogenesis and axonal regeneration [43,44]. However, recent studies have revealed that BASP1 is downregulated in multiple tumors, including hepatocellular carcinomas and several leukemias, by gene methylation [45,46], suggesting it is a significant tumor suppressor. PRDX2 is a neuronal-specific peroxiredoxin [47] that participates in cerebral antioxidant responses [48] in multiple neurodegenerative diseases, including Parkinson’s disease [49]. PRDX2 deficiency exaggerated ischemic neuronal injury by directly modulating the redox-sensitive signaling [50]. The present study revealed that BASP1 and PRDX2 were downregulated in CSF from VS grade I–V and recurrence, suggesting these may promote the growth of VS, which is evidenced by the negative correlation between BSAP2 or PRDX2 level in CSF and the size of VS. The reduced expression of PRDX2 in CSF from VS grade I–V and recurrence may increase accessibility to acoustic nerve damage in response to oxidative stress. One limitation of this study is the use of only three CSF control samples and one CSF sample of a grade I VS patient for iTRAQ analysis. In the present study, the CSF samples of the control group came from patients with acute brain trauma. Most CSF samples from acute brain trauma patients are mixed with blood. To ensure the quality of the experiment, we carefully selected the CSF samples from the control group to ensure they were pure and without any blood. We also excluded other diseases such as other cancers or cardiovascular diseases. This greatly limited the number of patients enrolled into our study as controls. According to the guidelines of VS treatment, patients with small tumors less than 2 cm are recommended for gamma knife treatment, unless they insist on tumor removal surgery. Thus, many patients with small VS prefer gamma knife treatment to surgery. Hence, we had only one case of grade I for iTRAQ analysis, but we collected more CSF samples for verification using ELISA analysis. The other limitation of this study is the need for further experiments to clarify whether increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 promote the growth of VS.
VS. These findings suggest that the inhibition of the inflammatory process or complement activation may be considered as novel therapeutic targets for VS. Our data first identified six proteins (ABCA3, KLF11, SCG1, CA2D1, BASP1, and PRDX2) in CSF related to VS growth, five of which were associated with recurrence of VS. ABCA3 is highly expressed in the lungs, followed by brain, pancreas, skeletal muscle, and heart. In lung tissue, it localizes to the limiting membrane of lamellar bodies (LBs) in alveolar epithelial type II (ATII) cells [20]. It contributes to the biogenesis of LBs or protection of ATII cells by lipid transport, particularly in phosphatidylcholine and phosphatidylglycerol trafficking [21,22]. In brain tissue, ABCA3 is expressed in total in all cell types including oligodendrocytes, neurons, astrocytes, and microglia [23,24], but the role of ABCA3 in the brain is currently unclear. High ABCA3 expression in non–small-cell lung cancer has been correlated with a poor prognosis [25]. In addition, ABCA3 is also overexpressed in childhood acute myeloid leukemia (AML), which results in multidrug resistance and poor outcome of chemotherapy in AML [26,27]. In this study, we observed that ABCA3 increased in CSF from grade II–V VS and recurrence, and ABCA3 was positively correlated with the size of the tumor in grade III VS. Detailed examination of the role of ABCA3 in VS cells will provide further insight into the relationship between ABCA3 and the growth and recurrence of VS. KLF11 belongs to the Sp1/Krüppel-like factor zinc finger transcription factor (Sp1/KLF) family [28] and is widely expressed in many tissues. It inhibits the growth of tumor cells, suppresses the angiogenesis of tumor tissue, and enhanced the apoptosis of tumor cells in vitro and in vivo [29] by inhibition of the transforming growth factor-β (TGFβ) signaling pathway [30]. The reduced expression of KLF11 in several types of cancer [31] is associated with tumorigenesis and tumor development. The data presented here show that the KLF11 level in CSF is increased in VS grade I and further increased in VS grade II, whereas it begins to decrease in VS grade III compared with the control group. Considering the role of TGF-β in VS cell replication [32], increased KLF11 may contribute to the slow growth of VS via regulation of TGF-β. SCG1, also known as chromogranin B (CHGB), a member of the chromogranin gene family, is expressed in secretory granules of neuroendocrine cells and neurons [33]. It is a high-capacity, low-affinity calcium-binding protein [34] and has been proposed as a candidate gene related to the risk of schizophrenia [35] as well as a biomarker for pancreatic neuroendocrine tumors in Japanese patients [36]. The increase in SCG1 in CSF has been found in patients in the early stages of multiple sclerosis [37]. This study revealed that SCG1 was increased in CSF with VS grade I and II but showed no alteration in patients with VS grade III–V or recurrence. In VS patients, it was negatively correlated with the growth of VS. It may be one of the early biomarkers of VS, but the level is not related to the growth of VS. Further studies are needed to elucidate its role in the early phases of VS pathogenesis and its potential as a biomarker for VS. CA2D1 is highly expressed in the brain, heart, skeletal system, and smooth muscle [38]. The upregulation of CA2D1 was observed in response to spinal injury and neuropathic pain [39–41]. It has a high-
5. Conclusion In this study, we identified a pattern of CSF-secreted proteins by iTRAQ analysis that might discriminate patients with VS from controls and particularly those with recurrence from controls. Using ELISA to validate these findings, our study first revealed that SCG1, KLF11, and CA2D1 are early biomarkers of VS, and increased ABCA3 and KLF11 and decreased BASP1 and PRDX2 in CSF are associated with VS growth in the early phase. CA2D1, ABCA3, KLF11, BASP1 and PRDX2 are also related to VS recurrence. It is crucial to characterize early biomarkers or effective therapeutic targets for VS to improve patients’ quality of life. 8
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Funding [13]
This work was supported by Shanghai Science and Technology Commission, China (grant 134119a4700), “Yang Fan” project (grant 15YF1401500), “China Spark Program” supported by the Ministry of Science and Technology, China (grant S2013C000013) and Natural Science Foundation of Shanghai(grant 17ZR1403800).
[14] [15]
Ethics approval and consent to participate
[16]
This study was approved by the Research Ethics Committee of Huashan Hospital, Fudan University. Informed consent was obtained from all patients in the study. The privacy rights of human subjects was always observed.
[17] [18]
Availability of data and material The data sets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
[19]
Conflict of interest
[20]
There is no conflict of interest to be disclosed.
[21]
Acknowledgements
[22]
Not applicable.
[23]
Appendix A. Supplementary data
[24]
Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.biopha.2019.108985.
[25]
References
[26]
[1] L.G. Bian, W. Tirakotai, Q.F. Sun, W.G. Zhao, J.K. Shen, Q.Z. Luo, Molecular genetics alterations and tumor behavior of sporadic vestibular schwannoma from the People’s Republic of China, J. Neurooncol. 73 (3) (2005) 253–260. [2] X. Huang, M. Xu, J. Xu, L. Zhou, P. Zhong, M. Chen, K. Ji, H. Chen, Y. M, Complications and management of large intracranial vestibular schwannomas via the retrosigmoid approach, World Neurosurg. 99 (2017) 326–335. [3] X. Huang, J. Xu, M. Xu, M. Chen, K. Ji, J. Ren, P. Zhong, Functional outcome and complications after the microsurgical removal of giant vestibular schwannomas via the retrosigmoid approach: a retrospective review of 16-year experience in a single hospital, BMC Neurol. 17 (1) (2017) 18. [4] S. Roy, S.A. Josephson, J. Fridlyand, J. Karch, C. Kadoch, J. Karrim, L. Damon, P. Treseler, S. Kunwar, M.A. Shuman, T. Jones, C.H. Becker, H. Schulman, J.L. Rubenstein, Protein biomarker identification in the CSF of patients with CNS lymphoma, J. Clin. Oncol. 26 (1) (2008) 96–105. [5] F.W. Khwaja, M.S. Reed, J.J. Olson, B.J. Schmotzer, G.Y. Gillespie, A. Guha, M.D. Groves, S. Kesari, J. Pohl, E.G. Van Meir, Proteomic identification of biomarkers in the cerebrospinal fluid (CSF) of astrocytoma patients, J. Proteome Res. 6 (2) (2007) 559–570. [6] M.U. Rajagopal, Y. Hathout, T.J. Macdonald, M.W. Kieran, S. Gururangan, S.M. Blaney, P. Phillips, R. Packer, H. Gordish-Dressman, B.R. Rood, Proteomic profiling of cerebrospinal fluid identifies prostaglandin D2 synthase as a putative biomarker for pediatric medulloblastoma: a pediatric brain tumor consortium study, Proteomics 11 (5) (2011) 935–943. [7] F. Shen, Y. Zhang, Y. Yao, W. Hua, H.S. Zhang, J.S. Wu, P. Zhong, L.F. Zhou, Proteomic analysis of cerebrospinal fluid: toward the identification of biomarkers for gliomas, Neurosurg. Rev. 37 (3) (2014) 367–380 discussion 80. [8] J.H. Seo, K.H. Park, E.J. Jeon, K.H. Chang, H. Lee, W. Lee, Y.S. Park, Proteomic analysis of vestibular schwannoma: conflicting role of apoptosis on the pathophysiology of sporadic vestibular schwannoma, Otol. Neurotol. 36 (4) (2015) 714–719. [9] M.A. Kazemizadeh Gol, T.C. Lund, S.C. Levine, M.E. Adams, Quantitative proteomics of vestibular schwannoma cerebrospinal fluid: a pilot study, Otolaryngol. Head. Neck Surg. 154 (5) (2016) 902–906. [10] J. Kanzaki, M. Tos, M. Sanna, D.A. Moffat, E.M. Monsell, K.I. Berliner, New and modified reporting systems from the consensus meeting on systems for reporting results in vestibular schwannoma, Otol. Neurotol. 24 (4) (2003) 642–648 discussion 8–9. [11] M. Gilar, P. Olivova, A.E. Daly, J.C. Gebler, Two-dimensional separation of peptides using RP-RP-HPLC system with different pH in first and second separation dimensions, J. Sep. Sci. 28 (14) (2005) 1694–1703. [12] X. Yang, V. Dondeti, R. Dezube, D.M. Maynard, L.Y. Geer, J. Epstein, X. Chen,
[27]
[28]
[29]
[30] [31] [32] [33]
[34] [35] [36]
[37]
9
S.P. Markey, J.A. Kowalak, DBParser: web-based software for shotgun proteomic data analyses, J. Proteome Res. 3 (5) (2004) 1002–1008. J. Peng, J.E. Elias, C.C. Thoreen, L.J. Licklider, S.P. Gygi, Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/ MS) for large-scale protein analysis: the yeast proteome, J. Proteome Res. 2 (1) (2003) 43–50. X. Huang, J. Xu, M. Xu, L.F. Zhou, R. Zhang, L. Lang, Q. Xu, P. Zhong, M. Chen, Y. Wang, Z. Zhang, Clinical features of intracranial vestibular schwannomas, Oncol. Lett. 5 (1) (2013) 57–62. M.K. Turel, S. Thakar, V. Rajshekhar, Quality of life following surgery for large and giant vestibular schwannomas: a prospective study, J. Neurosurg. 122 (2) (2015) 303–311. M. De Vries, P.C. Hogendoorn, I. Briaire-De Bruyn, M.J. Malessy, A.G. Van Der Mey, Intratumoral hemorrhage, vessel density, and the inflammatory reaction contribute to volume increase of sporadic vestibular schwannomas, Virchows Arch.: Int. J. Pathol. 460 (6) (2012) 629–636. M. De Vries, I. Briaire-De Bruijn, M.J. Malessy, S.F. De Bruine, A.G. Van Der Mey, P.C. Hogendoorn, Tumor-associated macrophages are related to volumetric growth of vestibular schwannomas, Otol. Neurotol. 34 (2) (2013) 347–352. D. Lewis, F. Roncaroli, E. Agushi, D. Mosses, R. Williams, K.L. Li, X. Zhu, R. Hinz, R. Atkinson, A. Wadeson, S. Hulme, H. Mayers, E. Stapleton, S.K.L. Lloyd, S.R. Freeman, S.A. Rutherford, C. Hammerbeck-Ward, D.G. Evans, O. Pathmanaban, A. Jackson, A.T. King, D. Coope, Inflammation and vascular permeability correlate with growth in sporadic vestibular schwannoma, Neurooncology 21 (3) (2019) 314–325. W.C. Song, Membrane complement regulatory proteins in autoimmune and inflammatory tissue injury, Curr. Dir. Autoimmun. 7 (2004) 181–199. G. Yamano, H. Funahashi, O. Kawanami, L.X. Zhao, N. Ban, Y. Uchida, T. Morohoshi, J. Ogawa, S. Shioda, N. Inagaki, ABCA3 is a lamellar body membrane protein in human lung alveolar type II cells, FEBS Lett. 508 (2) (2001) 221–225. Y. Matsumura, H. Sakai, M. Sasaki, N. Ban, N. Inagaki, ABCA3-mediated cholinephospholipids uptake into intracellular vesicles in A549 cells, FEBS Lett. 581 (17) (2007) 3139–3144. A.B. Chai, A.J. Ammit, I.C. Gelissen, Examining the role of ABC lipid transporters in pulmonary lipid homeostasis and inflammation, Respir. Res. 18 (1) (2017) 41. W.S. Kim, G.J. Guillemin, E.N. Glaros, C.K. Lim, B. Garner, Quantitation of ATPbinding cassette subfamily-A transporter gene expression in primary human brain cells, Neuroreport 17 (9) (2006) 891–896. M.L. Fitzgerald, R. Xavier, K.J. Haley, R. Welti, J.L. Goss, C.E. Brown, D.Z. Zhuang, S.A. Bell, N. Lu, M. Mckee, B. Seed, M.W. Freeman, ABCA3 inactivation in mice causes respiratory failure, loss of pulmonary surfactant, and depletion of lung phosphatidylglycerol, J. Lipid Res. 48 (3) (2007) 621–632. T.R. Overbeck, J. Arnemann, R. Waldmann-Beushausen, L. Trumper, F.A. Schondube, K. Reuter-Jessen, B.C. Danner, ABCA3 phenotype in non-small cell lung cancer indicates poor outcome, Oncology 93 (4) (2017) 270–278. D. Steinbach, J.P. Gillet, A. Sauerbrey, B. Gruhn, K. Dawczynski, V. Bertholet, F. De Longueville, F. Zintl, J. Remacle, T. Efferth, ABCA3 as a possible cause of drug resistance in childhood acute myeloid leukemia, Clin. Cancer Res. 12 (14 Pt 1) (2006) 4357–4363. N. Aberuyi, S. Rahgozar, Z. Khosravi Dehaghi, A. Moafi, A. Masotti, A. Paolini, The translational expression of ABCA2 and ABCA3 is a strong prognostic biomarker for multidrug resistance in pediatric acute lymphoblastic leukemia, Onco. Ther. 10 (2017) 3373–3380. E. Kuroda, Y. Horikawa, M. Enya, N. Oda, E. Suzuki, K. Iizuka, J. Takeda, Identification of minimal promoter and genetic variants of Kruppel-like factor 11 gene and association analysis with type 2 diabetes in Japanese, Endocr. J. 56 (2) (2009) 275–286. M.E. Fernandez-Zapico, G.A. Lomberk, S. Tsuji, C.J. Demars, M.R. Bardsley, Y.H. Lin, L.L. Almada, J.J. Han, D. Mukhopadhyay, T. Ordog, N.S. Buttar, R. Urrutia, A functional family-wide screening of SP/KLF proteins identifies a subset of suppressors of KRAS-mediated cell growth, Biochem. J. 435 (2) (2011) 529–537. B. Spittau, K. Krieglstein, Klf10 and Klf11 as mediators of TGF-beta superfamily signaling, Cell Tissue Res. 347 (1) (2012) 65–72. C. Bureau, N. Hanoun, J. Torrisani, J.P. Vinel, L. Buscail, P. Cordelier, Expression and function of Kruppel Like-Factors (KLF) in carcinogenesis, Curr. Genom. 10 (5) (2009) 353–360. M. Bizzarri, R. Filipo, M.G. Valente, D. Bernardeschi, F. Ronchetti, S. Monini, I. Chiappini, M. Barbara, Release of transforming growth factor beta-1 in a vestibular schwannoma cell line, Acta Otolaryngol. 122 (7) (2002) 785–787. C. Nowakowski, W.A. Kaufmann, C. Adlassnig, H. Maier, K. Salimi, K.A. Jellinger, J. Marksteiner, Reduction of chromogranin B-like immunoreactivity in distinct subregions of the hippocampus from individuals with schizophrenia, Schizophr. Res. 58 (1) (2002) 43–53. L. Taupenot, K.L. Harper, D.T. O’connor, The chromogranin-secretogranin family, N. Engl. J. Med. 348 (12) (2003) 1134–1149. J.G. Shin, J.H. Kim, C.S. Park, B.J. Kim, J.W. Kim, I.G. Choi, J. Hwang, H.D. Shin, S.I. Woo, Gender-specific associations between CHGB genetic variants and schizophrenia in a Korean population, Yonsei Med. J. 58 (3) (2017) 619–625. M. Miki, T. Ito, M. Hijioka, L. Lee, K. Yasunaga, K. Ueda, T. Fujiyama, Y. Tachibana, K. Kawabe, R.T. Jensen, Y. Ogawa, Utility of chromogranin B compared with chromogranin A as a biomarker in Japanese patients with pancreatic neuroendocrine tumors, Jpn. J. Clin. Oncol. 47 (6) (2017) 520–528. A.C. Kroksveen, J.D. Jaffe, E. Aasebo, H. Barsnes, Y. Bjorlykke, D. Franciotta, H. Keshishian, K.M. Myhr, J.A. Opsahl, V. Van Pesch, C.E. Teunissen, O. Torkildsen, R.J. Ulvik, H. Vethe, S.A. Carr, F.S. Berven, Quantitative proteomics suggests decrease in the secretogranin-1 cerebrospinal fluid levels during the disease course of
Biomedicine & Pharmacotherapy 116 (2019) 108985
X. Huang, et al. multiple sclerosis, Proteomics 15 (19) (2015) 3361–3369. [38] H.C. Gong, J. Hang, W. Kohler, L. Li, T.Z. Su, Tissue-specific expression and gabapentin-binding properties of calcium channel alpha2delta subunit subtypes, J. Membr. Biol. 184 (1) (2001) 35–43. [39] R.A. Newton, S. Bingham, P.C. Case, G.J. Sanger, S.N. Lawson, Dorsal root ganglion neurons show increased expression of the calcium channel alpha2delta-1 subunit following partial sciatic nerve injury, Brain Res. Mol. Brain Res. 95 (1–2) (2001) 1–8. [40] T.L. Yaksh, Calcium channels as therapeutic targets in neuropathic pain, J. Pain 7 (1 Suppl. 1) (2006) S13–30. [41] M. Katsura, Y. Mohri, K. Shuto, Y. Hai-Du, T. Amano, A. Tsujimura, M. Sasa, S. Ohkuma, Up-regulation of L-type voltage-dependent calcium channels after long term exposure to nicotine in cerebral cortical neurons, J. Biol. Chem. 277 (10) (2002) 7979–7988. [42] G. Chouinard, The search for new off-label indications for antidepressant, antianxiety, antipsychotic and anticonvulsant drugs, J. Psychiatry Neurosci. 31 (3) (2006) 168–176. [43] H.M. Bomze, K.R. Bulsara, B.J. Iskandar, P. Caroni, J.H. Skene, Spinal axon regeneration evoked by replacing two growth cone proteins in adult neurons, Nat. Neurosci. 4 (1) (2001) 38–43. [44] M.R. Mason, A.R. Lieberman, G. Grenningloh, P.N. Anderson, Transcriptional upregulation of SCG10 and CAP-23 is correlated with regeneration of the axons of peripheral and central neurons in vivo, Mol. Cell. Neurosci. 20 (4) (2002) 595–615.
[45] E.J. Yeoh, M.E. Ross, S.A. Shurtleff, W.K. Williams, D. Patel, R. Mahfouz, F.G. Behm, S.C. Raimondi, M.V. Relling, A. Patel, C. Cheng, D. Campana, D. Wilkins, X. Zhou, J. Li, H. Liu, C.H. Pui, W.E. Evans, C. Naeve, L. Wong, J.R. Downing, Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling, Cancer Cell 1 (2) (2002) 133–143. [46] T. Moribe, N. Iizuka, T. Miura, M. Stark, S. Tamatsukuri, H. Ishitsuka, Y. Hamamoto, K. Sakamoto, T. Tamesa, M. Oka, Identification of novel aberrant methylation of BASP1 and SRD5A2 for early diagnosis of hepatocellular carcinoma by genome-wide search, Int. J. Oncol. 33 (5) (2008) 949–958. [47] M.L. Aon-Bertolino, J.I. Romero, P. Galeano, M. Holubiec, M.S. Badorrey, G.E. Saraceno, E.M. Hanschmann, C.H. Lillig, F. Capani, Thioredoxin and glutaredoxin system proteins-immunolocalization in the rat central nervous system, Biochim. Biophys. Acta 1810 (1) (2011) 93–110. [48] Y. Gan, X. Ji, X. Hu, Y. Luo, L. Zhang, P. Li, X. Liu, F. Yan, P. Vosler, Y. Gao, R.A. Stetler, J. Chen, Transgenic overexpression of peroxiredoxin-2 attenuates ischemic neuronal injury via suppression of a redox-sensitive pro-death signaling pathway, Antioxid. Redox Signal. 17 (5) (2012) 719–732. [49] A. Patenaude, M.R. Murthy, M.E. Mirault, Emerging roles of thioredoxin cycle enzymes in the central nervous system, Cell. Mol. Life Sci. 62 (10) (2005) 1063–1080. [50] T.H. Lee, S.U. Kim, S.L. Yu, S.H. Kim, D.S. Park, H.B. Moon, S.H. Dho, K.S. Kwon, H.J. Kwon, Y.H. Han, S. Jeong, S.W. Kang, H.S. Shin, K.K. Lee, S.G. Rhee, D.Y. Yu, Peroxiredoxin II is essential for sustaining life span of erythrocytes in mice, Blood 101 (12) (2003) 5033–5038.
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