Abstract

To address the shortcomings of cystoscopy and urine cytology for detecting and grading bladder cancer (BC), ultrahigh performance liquid chromatography (UHPLC) coupled with Q-TOF mass spectrometry in conjunction with univariate and multivariate statistical analyses was employed as an alternative method for the diagnosis of BC. A series of differential serum metabolites were further identified for low-grade(LG) and high-grade(HG) BC patients, suggesting metabolic dysfunction in malignant proliferation, immune escape, differentiation, apoptosis and invasion of cancer cells in BC patients. In total, three serum metabolites including inosine, acetyl-N-formyl-5-methoxykynurenamine and PS(O-18:0/0:0) were selected by binary logistic regression analysis, and receiver operating characteristic (ROC) test based on their combined use for HG BC showed that the area under the curve (AUC) was 0.961 in the discovery set and 0.950 in the validation set when compared to LG BC. Likewise, this composite biomarker panel can also differentiate LG BC from healthy controls with the AUC of 0.993 and 0.991 in the discovery and validation set, respectively. This finding suggested that this composite serum metabolite signature was a promising and less invasive classifier for probing and grading BC, which deserved to be further investigated in larger samples.

Highlights

  • To address the shortcomings of cystoscopy and urine cytology for detecting and grading bladder cancer (BC), ultrahigh performance liquid chromatography (UHPLC) coupled with Quadrupole Time-of-Flight (Q-TOF) mass spectrometry in conjunction with univariate and multivariate statistical analyses was employed as an alternative method for the diagnosis of Bladder cancer (BC)

  • BC is classified as low-grade (LG) and high-grade (HG) tumors based on the degree by which cancer cells histologically differ from normal bladder cells

  • LG BC has a low risk of recurrence and progression, whereas HG BC is frequently associated with tumor recurrence and progression to metastatic, lethal disease[2]

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Summary

Introduction

Three serum metabolites including inosine, acetyl-N-formyl-5-methoxykynurenamine and PS(O18:0/0:0) were selected by binary logistic regression analysis, and receiver operating characteristic (ROC) test based on their combined use for HG BC showed that the area under the curve (AUC) was 0.961 in the discovery set and 0.950 in the validation set when compared to LG BC. Likewise, this composite biomarker panel can differentiate LG BC from healthy controls with the AUC of 0.993 and 0.991 in the discovery and validation set, respectively. Metabonomics is an intensive and direct approach for capturing diseases specific metabolic signatures as possible biomarkers and obtaining fundamental mechanistic insights into carcinogenesis and staging of cancer[11,12,13]

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