DNA Methylation profiles as predictors of recurrence in non muscle invasive bladder cancer: an MS-MLPA approach

Abstract

Background: Although non muscle invasive bladder cancer (NMIBC) generally has a good long-term prognosis, up to 80% of patients will nevertheless experience local recurrence after the primary tumor resection. The search for markers capable of accurately identifying patients at high risk of recurrence is ongoing. We retrospectively evaluated the methylation status of a panel of 24 tumor suppressor genes (TIMP3, APC, CDKN2A, MLH1, ATM, RARB, CDKN2B, HIC1, CHFR, BRCA1, CASP8, CDKN1B, PTEN, BRCA2, CD44, RASSF1, DAPK1, FHIT, VHL, ESR1, TP73, IGSF4, GSTP1 and CDH13) in primary lesions to obtain information about their role in predicting local recurrence in NMIBC.

Methods: Formaldehyde-fixed paraffin-embedded (FFPE) samples from 74 patients operated on for bladder cancer were analyzed by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA): 36 patients had relapsed and 38 were disease-free at the 5-year follow up. Methylation status was considered as a dichotomous variable and genes showing methylation ≥20% were defined as "positive".

Results: Methylation frequencies were higher in non recurring than recurring tumors. A statistically significant difference was observed for HIC1 (P = 0.03), GSTP1 (P = 0.02) and RASSF1 (P = 0.03). The combination of the three genes showed 78% sensitivity and 66% specificity in identifying recurrent patients, with an overall accuracy of 72%.

Conclusions: Our preliminary data suggest a potential role of HIC1, GSTP1 and RASSF1 in predicting local recurrence in NMIBC. Such information could help clinicians to identify patients at high risk of recurrence who require close monitoring during follow up.

Figure 1

Electropherogram relating to a) undigested and b) digested HT1376 samples with methylation of APC and RASSF1 genes.

Figure 2

Methylation levels of the three significant genes (HIC1, RASSF1, GSTP1) showed as box plot.

Figure 3

Prognostic algorithm with the three significant genes (GSTP1, HIC1 and RASSF1). Sensitivity was evaluated as the number of recurrent tumors with unmethylated HIC1, RASSF1, GSTP1 relative to the total number of recurrent tumors analyzed. Specificity was evaluated as the number of non recurrent tumors with methylated phenotype relative to the total number of non recurrent tumors analyzed. Overall accuracy was calculated as the number of correctly classified tumors relative to the total number of analyzed tumors.

Figure 4

ROC curves relating to the three significant genes (HIC1,RASSF1, GSTP1) analyzed singly or in combination.

Figure 5

Recurrence-free survival in patients with methylated phenotype (samples with at least one of the three significant genes methylated) or unmethylated phenotype (samples with none of the three genes methylated).