Establishment and Validation of an Individualized Cell Cycle Process-Related Gene Signature to Predict Cancer-Specific Survival in Patients with Bladder Cancer.

Run Shi,Paul Rogowski,Claus Belka,Shun Lu,Christian Stief,Xuanwen Bao,Alexander Buchner,Minglun Li,Jing Sun,Kristian Unger,Nina-Sophie Schmidt-Hegemann,Christian Schäfer

doi:10.3390/cancers12051146

Abstract

More accurate models are essential to identify high-risk bladder cancer (BCa) patients who will benefit from adjuvant therapies and thus helpful to facilitate personalized management of BCa. Among various cancer-related hallmarks and pathways, cell cycle process (CCP) was identified as a dominant risk factor for cancer-specific survival (CSS) in BCa. Using a series of bioinformatic and statistical approaches, a CCP-related gene signature was established, and the prognostic value was validated in other independent BCa cohorts. In addition, the risk score derived from the gene signature serves as a promising marker for therapeutic resistance. In combination with clinicopathological features, a nomogram was constructed to provide more accurate prediction for CSS, and a decision tree was built to identify high-risk subgroup of muscle invasive BCa patients. Overall, the gene signature could be a useful tool to predict CSS and help to identify high-risk subgroup of BCa patients, which may benefit from intensified adjuvant therapy.

Highlights

Bladder cancer (BCa) is a common malignancy in the urological system worldwide, with an estimated 430,000 newly diagnosed cases per year
A series of screening methods including Least absolute shrinkage and selection operator (LASSO) algorithm were used to screen out most promising candidates and to develop a robust cycle process (CCP)-related gene signature for cancer-specific survival (CSS)
A cycle process-related risk score (CCPRS) formula was established to quantify risk assessment for bladder cancer (BCa) patients, and the prognostic value was evaluated in the training and independent validation cohorts

Summary

Introduction

Bladder cancer (BCa) is a common malignancy in the urological system worldwide, with an estimated 430,000 newly diagnosed cases per year. Among these cases, about two-thirds are non-muscle-invasive bladder cancer (NMIBC), while the rest are classified as muscle-invasive bladder cancer (MIBC) [1]. Cancers 2020, 12, 1146 outcomes of BCa patients remain suboptimal. The standard treatment for localized MIBC is radical cystectomy with bilateral pelvic lymph node dissection, which provides a 5-year overall survival rate less than 50% [2]. Tumor-Node-Metastasis (TNM) staging and pathological grading systems are widely used for cancer management and survival prediction, clinical outcomes remain variable in BCa patients, even with similar characteristics [3]. Establishment of a more precise model is essential for individual patients to identify high-risk subgroup who may benefit from systemic adjuvant therapies

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Discussion

Conclusion