A novel prognostic biomarker for muscle invasive bladder urothelial carcinoma based on 11 DNA methylation signature

Figures & data

Table 1. Characteristics of training dataset and validation dataset

		Training dataset		Validation dataset		Total
Characteristics		No	%	No	%	No	%
All		319	100.0	80	100.0	399	100.0
Age
	<60	67	21.0	19	23.8	86	21.6
	≥60	252	79.0	61	76.2	313	78.4
Gender
	Male	228	71.5	64	80.0	292	73.2
	Female	91	28.5	16	20.0	107	26.8
Race
	White	253	79.3	65	81.3	318	79.7
	Asian	38	11.9	4	5.0	42	10.5
	Black OR African American	15	4.7	8	10.0	23	5.8
	Unknown	13	4.1	3	3.7	16	4.0
Stage ^a
	Stage II	110	34.5	16	20.0	126	31.6
	Stages III and IV	209	65.5	64	80.0	273	68.4
Grade
	Low Grade	19	6.0	1	1.3	20	5.0
	High Grade	300	94.0	79	98.7	379	95.0
Survival
	Death	129	40.4	40	50.0	169	42.4
	Alive	190	59.6	40	50.0	230	57.6
	MST ^b	35		21.9		33.1

a. Stage = Pathological Stage.

b. MST = Median Survival Time (Months)

Figure 1. Enrichment of KEGG paths with significant P values. The x-axis represents the number of DMRs involved in the pathway

Table 2. Survival analysis for risk module with OS as endpoints in the training dataset and validation dataset

	Training dataset (n = 319)						Validation dataset (n = 80)
	Univariate			Adjusted ^a			Univariate			Adjusted ^a
Variable	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P
Age ^b	2.05	1.22–3.46	0.007	1.53	0.90–2.60	0.120	1.99	0.83–4.75	0.121	1.49	0.59–3.73	0.400
Stage ^c	2.35	1.53–3.62	<.001	2.02	1.30–3.12	0.002	2.81	0.99–7.91	0.050	2.97	1.04–8.46	0.041
Gender ^d	0.90	0.62–1.30	0.565	0.90	0.62–1.32	0.591	0.92	0.44–1.92	0.815	0.70	0.32–1.51	0.360
Risk^e	2.99	1.91–4.66	<.001	2.58	1.64–4.05	<.001	2.87	1.36–6.06	0.006	2.77	1.25–6.15	0.012

a. Adjusted for Age, Pathological Stage, Gender b. ≥60 vs <60 (Ref)

c. Stages III and IV vs Stage II (Ref).

d. Female (Ref) vs Male.

e. High Risk vs Low Risk (Ref).

Figure 2. Kaplan-Meier curves and time-dependent receiver operating characteristic curves of methylation signature predicting the overall survival of MIBC. (a), (b) in training dataset. (c), (d) in validation dataset

Figure 3. Kaplan-Meier curves (a) in Total dataset, (b) in Female dataset, (c) in Male dataset and time-dependent receiver operating characteristic curves (d) of methylation signature predicting the overall survival of MIBC

Figure 4. Methylation signature nomogram to predict the risk of survival in patients with MIBC. (a) Nomogram of methylation signature predict the 5-years Survival probability of MIBC. (b) Calibration curve for the OS nomogram model in training dataset. (c) Calibration curve for the OS nomogram model in validation dataset