- The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer.. - Decision curve analysis (DCA) indicated that the clinical value of the nomogram was higher than the stage model and TNM model in predicting overall survival analysis. - To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.. - The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.. - 2 Key Laboratory of Gansu Province for Urological Diseases, Lanzhou, China Full list of author information is available at the end of the article Li et al. - https://doi.org/10.1186/s z. - Bladder cancer (BC) is the tenth most commonly diag- nosed carcinoma, with an estimated 549,000 new cases and 200,000 deaths reported globally in 2018, and BC ranks the first in urinary malignant neoplasm among males [1]. - Zhang et al. - constructed a pre- diction tool based on clinical parameters to predict the survival of patients with BC [5]. - Xie et al. - utilized the expression of B4GALT1 to predict the prognosis of patients with muscle-invasive bladder cancer, and the expression of B4GALT1 was correlated with OS of patients with BC [8]. - However, it is a challenge to predict the OS of pa- tients with BC using a single signature, because of the impact of genetic heterogeneity [11]. - Therefore, it is es- sential to develop a comprehensive prognostic evaluation system that can improve the predictive accuracy of the prognosis of patients with BC.. - Song et al. - identified signature com- bined immune-related genes and clinical characters to predict the OS of patients with BC, which suggested the signature was clinically useful for patients with BC [15].. - And the gene-based risk score was calculated through the step- wise multivariate cox coefficient multiplied by the ex- pression of the gene. - Estimation and validation of the multi-gene model The testing set ( n = 162) and the whole set ( n = 405) were utilized to assess the predictive validity of the multi-gene prognostic signature. - In the validation set, the risk score of each patient was calculated via the coef- ficient of the candidate genes obtained above. - cbioportal.org . - Construction and validation of the prognostic nomogram Based on risk score and some clinical parameters, a nomogram was established to predict the probability of 1-year, 3-year, and 5-year OS using R package “rms”. - The score of the prediction of nomograms for each patient was calculated via R package “nomogramFormu- lar” [29]. - Li et al. - Taking the intersection of the up-regulated and down-regulated genes in the three data sets, 151 up- regulated genes and 143 down-regulated genes were ob- tained (Fig. - 1 Flowchart of the whole study. - Then six-gene-based signature (Risk score. - Figure 4 B showed the survival status of the patients. - patients with BC (Fig. - Validation of the six-gene prognostic signature. - 7N-O) indicated that the patients with high-risk score had significantly worse OS. - In the group of AJCC-stage, the patients with the high-risk score in the early stage did not have signifi- cantly worse OS (Fig. - 7G), while in stage III and stage IV, the patients with the high-risk score have. - B: Survival status of the patients. - C: Heatmap of the expression profiles of the six prognostic genes in low- and high-risk group. - D: Kaplan – Meier survival analysis of the six-gene signature. - Time-dependent ROC analysis of the six-gene signature. - A: Expression pattern of the six prognostic genes between tumor and normal bladder tissue. - 7J), while in the T3/4 group, the patients with the high-risk score have worse OS (Fig. - Construction and validation of the gene-based nomogram. - The calibration plot for pa- tient survival prediction suggested that the predicted outcome of the six-gene prognostic nomogram showed consistency with the actual outcome (Fig. - The expression of SORBS2, GPC2, SETBP1, FGF11, APOL1, H1–2 , and PDGFD were significantly correlated with OS of patients with BC. - It is necessary to screen potential prognostic biomarkers and construct satisfying tools to predict the survival of patients with BC.. - In the previous study, numerous prognosis predictions of patients with BC are based on clinical information only . - The six genes, except SORBS2 , are significantly related to the overall survival of patients with bladder cancer.. - Bosse et al. - 7 Kaplan – Meier survival analysis of the six-gene risk score level in different subgroups. - The group of age (A-B), gender (C-D), race (E-F), AJCC-N (L-M), AJCC-M (N-O) indicated that the patients with high-risk score had significantly worse OS. - In the group of AJCC-stage, the patients with the high-risk score in the stage I/II did not have significantly worse OS (G), while in stage III and stage IV, the patients with the high-risk score have significantly worse OS (H-I). - In the group of AJCC-T, the patients with high-risk score in T0/1/2 did not have significantly worse OS (J), while in T3/4 group, the patients with the high risk-score have worse OS (K). - 8 Validation of the six-gene signature. - Kaplan – Meier survival analysis of the 6-gene signature in validation set. - D: Time-dependent ROC analysis of the six-gene signature in whole set. - E: Time-dependent ROC analysis of the six-gene signature in testing set. - F: Time-dependent ROC analysis of the six-gene signature in GSE13507 dataset. - 9 Construction of gene-based prognostic model and evaluation of the nomogram. - B-D: The calibration plot of the nomogram for agreement test between 1-, 3- and 5-year OS prediction and actual outcome in TCGA dataset. - H: The time-dependent ROC curves of the nomogram in TCGA dataset. - Shou et al. - FGF11 , fibro- blast growth factor 11, is a member of the fibroblast growth factor (FGF) family. - 3 E) and the patients with low H1–2 expression had a high probability of death, which means the low expression of H1–2 is related with progression and bad prognosis of patients with BC.. - Based on our analysis, these genes may be a potential novel therapeutic target for patients with BC. - The time-dependent ROC indicated that the AUC of the nomogram was larger than that of the risk score, resulting from the combination with clinical parame- ters. - org/10.1186/s z.. - The first draft of the manuscript was written by JL and JC, and all authors. - commented on previous versions of the manuscript. - https://doi.org/10.3322/caac.21492.. - https://doi.org/10.21037/atm . - https://doi.org/10.1016/j.eururo . - https://doi.org lt;354::AID-CNCR1009>3.0.CO;2-9.. - doi.org/10.1097/MD . - https://doi.org/10.7150/jca.27381.. - https://doi.org/10.1186/s . - Overexpression of the ASPM gene is associated with aggressiveness and poor outcome in bladder cancer. - https://doi.org/10.3892/ol.2018.9762.. - https://doi.org/10.1038/nrc3817.. - https://doi.org/10.3389/fonc . - https://doi.org/1 0.2147/CMAR.S185205.. - https://doi.org/10.21037/atm-20-1102.. - https://doi.org/10.3389/fendo . - https://doi.org . - https://doi.org/10.1038/s y.. - https://doi.org/10.1093/nar/gkv007.. - https://doi.org/10.1093/bioinformatics/btp616.. - Identification of hub genes associated with progression and prognosis in patients with bladder Cancer. - https://doi.org/10.3389/fgene . - https://doi.org/10.18637/jss.v039.i05.. - https://doi.org/10.1126/scisignal.2004088.. - https://doi.org CD-12-0095.. - doi.org/10.1002/sim.5958.. - https://doi.org/10.1002/pro.3715.. - doi.org/10.1089/omi.2011.0118.. - Development and validation of a nomogram to predict the prognosis of patients with squamous cell carcinoma of the bladder. - https://doi.org/10.1042/BSR2 0193459.. - Nomograms to predict individual prognosis of patients with squamous cell carcinoma of the urinary bladder. - https://doi.org/10.1016/j.ccell . - https://doi.org/10.1038/s . - https://doi.org/10.3892/or . - https://doi.org/10.1681/ASN . - https://doi.org/10.1 093/ndt/gfy176.. - https://doi.org/10.1002/jcp.28716.. - https://doi.org/10.1152/physrev
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