Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer

Table 5 Studies regarding circulating metabolomics and proteomics in blood as potential biomarkers for bladder cancer

Authors (year)	Sample type	No. of patients	Laboratory technique	Clinical application	Detection rate	Refs.
Cao et al. (2012)	Serum	112	¹H NMR measurements	Discrimination of patients with BC from healthy individuals	Detected abnormal serum metabolic profiles in 100% of patients	[196]
Bansal et al. (2013)	Serum	99	¹H NMR measurements	Diagnostic biomarker	Sensitivity = 94%, specificity = 97%	[197]
Tan et al. (2017)	Serum	172	UHPLC coupled with Q-TOF MS	Diagnostic biomarker	AUC = 0.961	[198]
Schwamborn et al. (2009)	Serum	248	MALDI-TOF–MS	Diagnostic biomarker	Sensitivity = 96.4%, specificity = 86.5%	[199]
Bansal et al. (2014)	Serum	90	MALDI-TOF–MS	Diagnostic biomarker	AUC = 0.946 (S100A8 and S100A9)	[200]
Bansal et al. (2016)	Serum	160	ELISA, MARS	Diagnostic biomarker	AUC = 0.957 (S100A9)	[201]
Amara et al. (2019)	Serum	87	LC–MS	Predict disease progression	OS (p = 0.0065)	[207]
Minami et al. (2010)	Serum	2	Reversed-phase high-performance liquid chromatography	Predict prognosis	RFS (p = 0.026), CSS (p = 0.041)	[208]
Lemańska-Perek et al. (2019)	Plasma	6	MALDI-TOF–MS	Predict disease progression	Increasing abundance in progressing BC	[209]

AUC area under the receiver operating characteristics curve, ELISA enzyme linked immunosorbent assay, OS overall survival, RFS recurrence-free survival, CSS cancer-specific survival, NMR nuclear magnetic resonance, LC–MS liquid chromatography–mass spectrometry, Q-TOF MS quadrupole time of flight mass spectrometry, UHPLC ultra-high performance liquid chromatography, MALDI-TOF–MS matrix-assisted laser desorption/ionization time of flight mass spectrometry

ISSN: 1689-1392