A two-site combined prediction model based on HOXA9 DNA methylation for early screening of risks of meningioma progression

doi:10.12122/j.issn.1673-4254.2024.11.07

Abstract

Abstract:

Objective To establish a recurrence risk prediction model for meningioma based on HOXA9 DNA methylation. Methods Meningioma-related datasets were downloaded from GEO database for screening homeobox genes (HOXs) with prognostic values using differential methylation and ROC curve analysis and Cox regression analysis. The differentially methylated CpG sites with high predictive efficacy were selected to establish the risk prediction model using Lasso-Cox regression analysis, based on which the patients were divided into high- and low-risk groups by the cutoff value. The methylation levels of CpG sites were verified at the cell and tissue levels using methylation-specific PCR (MS-PCR). Clinical meningioma tissue samples were used to validate the predictive efficacy of the model. Results HOXA9 methylation level was significantly up-regulated in meningiomas (P<0.001) and showed a high diagnostic efficiency (AUC=0.884) as an independent risk factor for overall survival (P<0.01) positively correlated with the degree of malignancy and poor prognosis of meningioma (P<0.05). Risk stratification by HOXA9 methylation was more accurate than WHO grading for predicting recurrence and patient survival time. The AUCs of the sites cg03217995 and cg21001184 were both above 0.8 for meningioma diagnosis and above 0.6 for predicting recurrence. The patients' clinical characteristics differed significantly between the high- and low-risk groups (P<0.001), and the prediction score of the model was an independent prognostic factor for meningioma (P<0.05). MS-PCR results showed that the methylation levels of the two sites increased significantly in meningioma cells. In clinical samples, the combined model showed a high prediction efficiency (AUC=0.857), and the predicted risk of progression was highly consistent with the patients' actual condition. Conclusion High HOXA9 methylation level is a predictor for poor prognosis of meningiomas, and the combined prediction model based on its CpG sites provides a new approach to early screening of meningioma patients at risk of progression.

Key words: meningioma, HOXA9, DNA methylation, CpG sites, diagnosis, prognosis

Ruxue TAN, Xiaozhang BAO, Liang HAN, Zhaohui LI, Nan TIAN. A two-site combined prediction model based on HOXA9 DNA methylation for early screening of risks of meningioma progression[J]. Journal of Southern Medical University, 2024, 44(11): 2110-2120.

Figures/Tables 7

Tab.1 Primer sequences for MS-PCR

Site	Primer sequence (5'-3')		Product length (bp)
cg03217995	M	F:TGGTGTTTTGTATAGGGGTATCG	95
	M	R:AACCCAATATTTCTCTTCCCCG	95
	U	F:AGGGTTTGGTGTTTTGTATAGGGGTATTG	107
	U	R:CTCCTAAACCCAAGATTTCTCTTCCCCA	107
cg21001184	M	F:GGTCGTGCGCGTTACGTGTTCGT	92
	M	R:AAATTATAACTACAAAACATCGA	92
	U	F:TTTATTGGTTGTGTGTGTTATGTGTTTGT	104
	U	R:CTATAAAAATTATAACTACAAAACATCAA	104

Fig.2 Correlation analysis of HOXA9 methylation and clinical characteristics of meningioma. A: Univariate Cox analysis and multivariate Cox analysis of HOXA9 methylation and clinical characteristics with overall survival (OS) of meningioma patients. B: HOXA9 methylation difference in meningioma patients with CDKN2A/B deletion and TRAF7/AKT1 mutation. C: Proportion of meningioma patients with NF2-SSV, NF2-CNV, Chr22q Loss, and Chr1q Amp in hypomethylation (Hypo) and hypermethylation (Hyper) groups and box plot of the differences in gene instability. D: Kaplan-Meier survival curves for recurrence-free survival (RFS) and OS in Hypo and Hyper groups. E: Alluvial chart of Choudhury classification and WHO grade in Hypo and Hyper groups. F: Box plots comparing activation of molecular signatures of proliferation between HOXA9 groups. G: Brier prediction analysis of RFS and OS in HOXA9 groups and WHO grade in meningiomas. *P<0.05, **P<0.01, ****P<0.0001.

Fig.3 Screening of CpG sites. A: Volcano map of differential methylation of CpG sites. B: The location of CpG sited. C: Heat map of CpG sites. D: Differential methylation between cg03217995 and cg21001184 in meningiomas and meningeal tissues. E: ROC analysis of cg03217995 and cg21001184. ****P<0.0001.

Fig.4 Construction of the two-site combined prediction model. A: Heat map of CpG sites arranged by risk score. The relationship between the risk scores and patients' clinic pathological characteristics was evaluated (a, Wilcoxon test; b, One-way ANOVA test). B: RFS and OS survival curves grouped by risk score.

Tab.2 Univariate and multivariate analysis of two CpG sites RFS modeling risk scores

Characteristics	Total (n)	Multi score	Univariate analysis		Multivariate analysis
Characteristics	Total (n)	Multi score	HR (95% CI)	P	HR (95% CI)	P
Risk score	243	1.341±0.422	3.654 (1.586-8.420)	0.002	2.725 (1.184-2.269)	0.018
WHO grade
1	212	1.317±0.416	4.391 (2.504-7.700)	<0.0001	3.203 (1.257-8.161)	0.015
2	29	1.505±0.450
3	2	1.548±0.222
RT
Yes	29	1.499±0.390	4.382 (2.071-9.072)	<0.0001	1.282 (0.380-2.322)	0.689
No	214	1.320±0.423	4.382 (2.071-9.072)	<0.0001	1.282 (0.380-2.322)	0.689
Age (year)
≤60	139	1.304±0.393	0.934 (0.484-1.802)	0.838
>60	104	1.390±0.456	0.934 (0.484-1.802)	0.838

Fig.5 Validation of the combined prediction model of the two sites. A: MS-PCR results of CpG sites cg03217995 and cg21001184 in meningioma cells and meningioma tissues. The density of each strip was quantified by imaging analysis, and the relative band density value was calculated as the ratio of methylation to methylation plus unmethylation (M/U+M). U: Unmethylated; M: Methylated; MM: molecular marker. B: ROC of CpG sites cg03217995 and cg21001184 for diagnosis of meningioma patients. C: Prediction of meningioma patients at CpG sites cg03217995 and cg21001184. P: Patient. ***P<0.001, ****P<0.0001.

Tab.3 Clinical information and experimental results of meningioma tissue samples

Case No.	WHO grade	Progression	β value		Risk score
Case No.	WHO grade	Progression	cg03217995	cg21001184	Risk score
1	1	no	0.389±0.018	0.233±0.022	0.708
2	1	no	0.428±0.016	0.445±0.008	1.008
3	1	yes (Invasion)	0.668±0.037	0.393±0.006	1.228
4	2	no	0.330±0.039	0.344±0.036	0.779
5	2	no	0.437±0.015	0.157±0.016	0.668
6	2	yes (Multiple recurrence)	0.588±0.019	0.639±0.029	1.420
7	3	no	0.492±0.034	0.169±0.011	0.741
8	3	no	0.696±0.016	0.393±0.008	1.238
9	3	no	0.614±0.024	0.731±0.013	1.561

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