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High-frequency recurrence index for predicting multiple recurrences in non-muscle-invasive bladder cancer (Discovery cohort)

ABSTRACT: Non-muscle invasive bladder cancer (NMIBC) has a recurrence rate of more than 50% after transurethral resection (TUR) and Calmette-Guérin (BCG) treatment. This study aimed to develop a high-frequency recurrence index (HfRI) to predict multiple recurrences in NMIBC patients and guide personalized treatment strategies. In this study, we analyzed transcriptome data (Discovery cohort) of 45 high-risk NMIBC patients who received intravesical BCG treatment, including patients with >=2 recurrences, to identify genes significantly associated with high-frequency recurrence and construct a signature. In addition, we validated the predictive performance using transcriptome data of 94 patients (Discovery cohort).

ORGANISM(S): Homo sapiens

PROVIDER: GSE294703 | GEO | 2026/02/07

REPOSITORIES: GEO

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Project description:Background Bladder cancer represents a heterogeneous disease with distinct clinical challenges. Non-muscle invasive bladder cancer (NMIBC) typically presents as indolent and slow-growing, yet a critical clinical challenge remains: identifying which patients will progress to muscle-invasive disease requiring radical interventions. Early detection of progression propensity is essential, as once muscle invasion occurs, the risk of distant metastasis increases substantially, and treatment shifts from conservative TURBT (Transurethral Resection of Bladder Tumor) to aggressive surgical interventions with significant morbidity. Current risk stratification methods fail to adequately predict this transition in approximately 30% of cases, highlighting the urgent need for more accurate prognostic tools. Objective This retrospective study aimed to develop and validate a transcriptomics-based mRNA score for predicting early NMIBC recurrence, comparing its performance against traditional risk stratification methods. Methods We analyzed mRNA expression profiles from primary retrospective NMIBC tumor specimens (n=25) collected between [2018-2022]. Traditional risk stratification tools, including EORTC scoring, were applied alongside our novel mRNA-based risk score to evaluate predictive accuracy for recurrence. Results The transcriptomics-based mRNA score demonstrated a median prediction accuracy of 90% across 10,000 resampling iterations for predicting early NMIBC recurrence, significantly outperforming traditional EORTC risk scores. Our comprehensive gene set identified 435 differentially expressed genes associated with recurrence. Kaplan-Meier analysis showed significantly different recurrence-free survival between high and low mRNA risk score groups (Bonferroni corrected p-value<0.0001). Conclusions This retrospective analysis confirms that mRNA expression-based risk stratification provides superior predictive accuracy compared to conventional clinicopathologic risk tools. Implementation of this gene signature could potentially reduce over-investigation and improve surveillance cost-effectiveness after TURBT in patients with primary high-risk NMIBC. These findings may transform the clinical management paradigm by enabling more personalized follow-up protocols based on molecular risk assessment.

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High-frequency recurrence index for predicting multiple recurrences in non-muscle-invasive bladder cancer (Discovery cohort)

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