Background: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer.
Results: We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.
Conclusions: We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.
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http://dx.doi.org/10.1186/1476-4598-9-3 | DOI Listing |
World J Urol
January 2025
Department of Urology, University of Health Sciences, Bagcilar Training and Research Hospital, Istanbul, 34200, Turkey.
Purpose: As Bladder EpiCheck (BE) is a promising urinary biomarker for diagnosis and follow up of non-muscle-invasive bladder cancer (NMIBC), there are no studies evaluated this tool for second transurethral resection (TUR) indication. We aim to evaluate the performance of BE in predicting residual tumor before second TUR in NMIBC and its effects on clinical decision making.
Methods: A total of 50 patients who were diagnosed with NMIBC and indicated for a second TUR were included in the study prospectively.
J Appl Clin Med Phys
January 2025
Department of Radiation Medicine and Applied Sciences, UC San Diego Health, La Jolla, California, USA.
Purpose: Daily online adaptive radiotherapy (ART) improves dose metrics for gynecological cancer patients, but the on-treatment process is resource-intensive requiring longer appointments and additional time from the entire adaptive team. To optimize resource allocation, we propose a model to identify high-priority patients.
Methods: For 49 retrospective cervical and endometrial cancer patients, we calculated two initial plans: the treated standard-of-care (Initial) and a reduced margin initial plan (Initial) for adapting with the Ethos treatment planning system.
J Mater Chem B
January 2025
Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, China.
Sulfur-containing small molecules, mainly including cysteine (Cys), homocysteine (Hcy), glutathione (GSH), and hydrogen sulfide (HS), are crucial biomarkers, and their levels in different body locations (living cells, tissues, blood, urine, saliva, ) are inconsistent and constantly changing. Therefore, it is highly meaningful and challenging to synchronously and accurately detect them in complex multi-component samples without mutual interference. In this work, we propose a steric hindrance-regulated probe, NBD-2FDCI, with single excitation dual emissions to achieve self-adaptive detection of four analytes.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Purpose: To create a system to enable the identification of histological variants of bladder cancer in a simple, efficient, and noninvasive manner.
Material And Methods: In this multicenter diagnostic study, we retrospectively collected basic information and CT images about the patients concerned from three hospitals. An interactive deep learning-based bladder cancer image segmentation framework was constructed using the Swin UNETR algorithm for further features extraction.
Unlabelled: Immune escape is a critical hallmark of cancer progression and underlies resistance to multiple immunotherapies. However, it remains unclear when the genetic events associated with immune escape occur during cancer development. Here, we integrate functional genomics studies of immunomodulatory genes with a tumor evolution reconstruction approach to infer the evolution of immune escape across 38 cancer types from the Pan-Cancer Analysis of Whole Genomes dataset.
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