| Literature DB >> 31138764 |
Qing Yuan1,2, Hong-Qing Cai3,2, Yi Zhong1,2, Min-Jie Zhang1,2, Zhi-Jian Cheng1,2, Jia-Jie Hao2, Ming-Rong Wang2, Jing-Hai Wan4,5.
Abstract
The prognosis of patients with glioblastoma (GBM) is dismal. It has been reported that Insulin-like growth factor (IGF) binding protein 2 (IGFBP2) is associated with the mobility and invasion of tumor cells. We investigated the expression of IGFBP2 mRNA in GBMs and its clinical relevance, using tissue microarrays and RNAscope in situ hybridization in 180 GBMs and 13 normal or edematous tissues. The correlations between the expression and clinical pathological parameters as well as some other biomarkers were analyzed. Overexpression of IGFBP2 mRNA was observed in 23.9% of tumors tested. No expression of IGFBP2 mRNA was detected in normal or edematous tissues. Kaplan-Meier survival analysis showed that the survival time of all the patients with high IGFBP2 tumors had shorter survival than those with low IGFBP2 (P<0.01). Univariate regression and multivariate regression both indicated that the expression of IGFBP2 transcript level was an independent prognostic factor (P=0.008 and 0.007, respectively). Furthermore, expression of IGFBP2 mRNA was related to the occurrence of isocitrate dehydrogenase 1 (IDH1) mutation, high heat shock protein 27 (Hsp27) expression and telomerase reverse transcriptase (TERT) promoter mutation (TERTp+) (P=0.013, 0.015 and 0.016, respectively), and patients with TERTp+/IGFBP2high showed the shortest survival. In conclusion, IGFBP2 mRNA expression status is an independent prognostic biomarker in GBMs, and the combination of IGFBP2 mRNA and TERTp status might serve as a prognostic indicator in patients with GBM.Entities:
Keywords: Glioblastoma; IGFBP2; RNA In situ hybridization (RISH); TERT
Mesh:
Substances:
Year: 2019 PMID: 31138764 PMCID: PMC6567677 DOI: 10.1042/BSR20190045
Source DB: PubMed Journal: Biosci Rep ISSN: 0144-8463 Impact factor: 3.840
Baseline information of 180 GBMs by IGFBP2 mRNA in situ hybridization
| Variables | No | IGFBP2 (high) | IGFBP2 (low) | χ2 | |
|---|---|---|---|---|---|
| Gender | 0.201 | 0.654 | |||
| Male | 112 | 28 (25.0%) | 84 (75.0%) | ||
| Female | 68 | 15 (22.1%) | 53 (77.9%) | ||
| Age (years) | 4.435 | 0.035 | |||
| ≤50 | 88 | 15 (17.0%) | 73 (83.0%) | ||
| >50 | 92 | 28 (30.4%) | 64 (69.6%) | ||
| KPS | 3.464 | 0.063 | |||
| ≤60 | 32 | 9 (28.1%) | 23 (71.9%) | ||
| >60 | 44 | 5 (11.4%) | 39 (88.6%) | ||
| NA | 104 | 29 (27.9%) | 75 (72.1%) | ||
| Radiotherapy | 3.212 | 0.073 | |||
| Yes | 112 | 32 (28.6%) | 80 (71.4%) | ||
| No | 66 | 11 (16.7%) | 55 (83.3%) | ||
| NA | 2 | 0 (0%) | 2 (100%) | ||
| Chemotherapy | 0.054 | 0.816 | |||
| Yes | 151 | 36 (23.8%) | 115 (76.2%) | ||
| No | 27 | 7 (26.0%) | 20 (74.0%) | ||
| NA | 2 | 0 (0%) | 2 (100%) | ||
| Pathology | 10.092 | 0.001 | |||
| pGBM | 140 | 41 (29.3%) | 99 (70.7%) | ||
| sGBM | 40 | 2 (2.5%) | 38 (97.5%) |
IGFBP2 (high), high expression of IGFBP2 mRNA in GBM; IGFBP2 (low), low expression of IGFBP2 mRNA in GBM.
KPS, Karnofsky score. It is clinically used to evaluate patients’ functional status.
NA, not available (the same below).
pGBM, primary GBM; sGBM, secondary GBM.
Figure 1Representative RISH images of negative, low, moderate, and high IGFBP2 mRNA expression (100× and 400×)
Figure 2Representative multi-marker detection results
Case 1, IGFBP2low/IDH1+/TERTp−/Hsp27low; Case 2, IGFBP2high/IDH1−/TERTp+/Hsp27high.
Relationships between IGFBP2 and other biomarkers in GBMs
| Biomarker | Status | IGFBP2 | χ2 | ||
|---|---|---|---|---|---|
| High | Low | ||||
| IDH1 | Mutation | 7 | 50 | 6.182 | 0.013 |
| Wlid-type | 36 | 87 | |||
| Hsp27 | High | 19 | 34 | 5.910 | 0.015 |
| Low | 24 | 103 | |||
| TERTp | Mutation | 30 | 69 | 5.770 | 0.016 |
| Wlid-type | 12 | 68 | |||
Figure 3The prognostic value of IGFBP2 mRNA and TERT promoter mutation
(A–D) Overexpression of IGFBP2 mRNA (IGFBP2H) and TERT promoter mutation (TERTp+) predicted shorter survival of patients with GBM. (E,F) Multi-markers detection can stratify the patients into three groups with significantly different survival times, in which the patients with IGFBP2H/TERTp+ had a shorter survival.
Univariate and multivariate regression analyses of factors associated with disease- specific survival in GBMs
| Variable | Univariate regression | Multivariate regression | ||
|---|---|---|---|---|
| HR (95% CI) | HR (95% CI) | |||
| Age (≤50, >50) | 1.327 (0.867–2.032) | 0.193 | - | - |
| Gender (male, female) | 0.896 (0.587–1.367) | 0.609 | - | - |
| KPS (≤60, >60) | 0.691 (0.373–1.282) | 0.242 | - | - |
| Pathology (pGBM, sGBM) | 0.796 (0.485–1.307) | 0.368 | - | - |
| Radiotherapy (Y, N) | 0.306 (0.198–0.474) | <0.001 | 0.293 (0.184–0.467) | <0.001 |
| Chemotherapy (Y, N) | 0.232 (0.134–0.404) | <0.001 | 0.382 (0.213–0.684) | 0.001 |
| IDH1 (mutation, wild-type) | 0.526 (0.327–0.844) | 0.008 | 0.514 (0.316–0.837) | 0.007 |
| IGFBP2 (high, low) | 2.004 (1.228–3.272) | 0.005 | 2.356 (1.424–3.899) | 0.001 |
CI, confidence interval; HR, hazard ratio.
N, no; Y, yes.