Abstract
Bladder cancer (BLCA) is the fourth common cancer among males in the United States, which is also the fourth leading cause of cancer-related death in old males. BLCA has a high recurrence rate, with over 50% of patients which has at least one recurrence within five years. Due to the complexity of the molecular mechanisms and heterogeneous cancer feature, BLCA clinicians find it hard to make an efficient management decision as they lack reliable assessment of mortality risk. Meanwhile, there is currently no screening suitable prognostic signature or method recommended for early detection, which is significantly important to early-stage detection and prognosis. In this study, a novel model, named the risk-weighted sparse regression (RWSR) model, is constructed to identify a robust signature for patients of early-stage BLCA. The 17-gene signature is generated and then validated as an independent prognostic factor in BLCA cohorts from GSE13507 and TCGA_BLCA datasets. Meanwhile, a risk score model is developed and validated among the 17-gene signature. The risk score is also considered an independent factor for prognosis prediction, which is confirmed through prognosis analysis. The Kaplan-Meier with the log-rank test is used to assess survival difference. Furthermore, the predictive capacity of the signature is proved through stratification analysis. Finally, an effective patient classification is completed by a combination of the 17-gene signature and stage information, which is for better survival prediction and treatment decisions. Besides, 11 genes in the signature, such as coiled-coil domain containing 73 (CCDC73) and protein kinase, DNA-activated, and catalytic subunit (PRKDC), are proved to be prognosis marker genes or strongly associated with prognosis and progress of other types of cancer in published literature already. As a result, this paper would more accurately predict a patient's prognosis and improve surveillance in the clinical setting, which may provide a quantitative and reliable decision-making basis for the treatment plan.
Highlights
Bladder cancer (BLCA) is the fourth most common cancer for men in the United States, with an estimated 80,470 adults (61,700 men and 18,770 women) and 17,670 deaths (12,870 men and 4,800 women) in 2019 [1, 2]
A risk-weighted sparse regression model is proposed to screen the 17-gene signature, which represents the relationship between prognosis of early-stage BLCA patients and mRNA gene expression level
To predict the differences between ð15Þ the two risk BLCA patient groups based on survival time, we use the Kaplan-Meier method and calculate the log-rank value to identify the statistical significance between groups
Summary
Bladder cancer (BLCA) is the fourth most common cancer for men in the United States, with an estimated 80,470 adults (61,700 men and 18,770 women) and 17,670 deaths (12,870 men and 4,800 women) in 2019 [1, 2]. BLCA can be mainly divided into two subtypes based on the cancer cell infiltration: nonmuscle-invasive BLCA and muscle-invasive BLCA The former has a high recurrence rate but less aggressive, while the latter has a relatively poor prognosis and is easier to metastasize [7,8,9]. With the number of comorbidities increasing, it is complicated for clinicians too often making a challenging decision on how to choose effective treatment plans for an individual patient. In the phase of staging and risk assessment, further imaging studies [16] will be completed to confirm the stage after patients have confirmed muscle invasion histology, such as computed tomography (CT) or magnetic resonance imaging (MRI) Both tests are often unable to reliably identify T2 from T3a, T3b, or even T4a, separately. Based on fundamental enrichment analysis, it demonstrated that the 17-gene signature significantly participated in immune-, cell cycle-, and transport-associated biological processes
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