Table 1 Studies regarding blood-based CTCs as potential biomarkers for bladder cancer
Authors (year) | Sample type | No. of patients | Laboratory technique | Clinical application | Detection rate | Refs. |
|---|---|---|---|---|---|---|
Qi et al. (2014) | Serum | 120 | ELISA, RT-qPCR | Diagnostic biomarker | AUC = 81.9%, sensitivity = 82.1%, specificity = 61.9% | [52] |
Kim et al. (2020) | Peripheral blood | 20 | Whole exome sequencing | Discrimination of MIBC from NMIBC and healthy individuals | KMT2C mutations were detected in 20% of CTCs | [53] |
Gazzaniga et al. (2014) | Peripheral blood | 102 | CellSearch System | Predict prognosis | DFS (p = 0.005), PFS (p = 0.004) | [56] |
Soave et al. (2017) | Peripheral blood | 188 | CellSearch System | Predict prognosis | RFS (p < 0.001), CSS (p < 0.001) | [57] |
Rink et al. (2012) | Peripheral blood | 100 | CellSearch System | Predict prognosis | OS (p = 0.003), CSS (p = 0.002), RFS (p < 0.001) | [58] |
Gazzaniga et al. (2012) | Peripheral blood | 44 | CellSearch System | Predict prognosis | TFR (p < 0.001) | [59] |
Rink et al. (2011) | Peripheral blood | 50 | CellSearch System | Predict prognosis | OS (p = 0.001), CSS (p < 0.001), PFS (p < 0.001) | [60] |
Soave et al. (2017) | Peripheral blood | 226 | CellSearch System | Predict prognosis | OS (p < 0.001), CSS (p < 0.001), RFS (p < 0.001) | [61] |
Beije et al. (2022) | Peripheral blood | 273 | CellSearch System | Predict treatment response | CTC-positive patients treated with NAC have longer survival times | [63] |
Osman et al. (2004) | Peripheral blood | 62 | Nested RT-PCR | Monitoring recurrence | Positive predict value = 79%, negative predict value = 50% | [64] |
Abrahamsson et al. (2017) | Peripheral blood | 88 | CellSearch System | Predict disease progression | Disease progression (p = 0.049) | [65] |
Haga et al. (2020) | Peripheral blood | 26 | FISHMAN-R system | Predict disease progression | More CTC detected in progressive BC (p = 0.01) | [66] |
Gradilone et al. (2010) | Peripheral blood | 54 | RT-PCR, CELLection Dynabeads | Monitoring recurrence | DFS (p < 0.001) | [67] |
Nicolazzo et al. (2017) | Peripheral blood | 54 | RT-PCR, CELLection Dynabeads | Predict prognosis | DFS (p < 0.0001), CSS (p < 0.0001) | [68] |
Busetto et al. (2017) | Peripheral blood | 155 | CellSearch System | Predict prognosis | TFR (p < 0.0001), TTP (p < 0.0001) | [69] |
Nicolazzo et al. (2019) | Peripheral blood | 102 | CellSearch System | Predict prognosis | TFR (p < 0.001), TSR (p < 0.001), TTP (p < 0.001) | [70] |
Fu et al. (2021) | Peripheral blood | 48 | Microfluidic-Assay System | Early risk stratification | More CTC detected in progressive BC (p = 0.024) | [71] |
Winters et al. (2015) | Peripheral blood | 31 | CellSearch System | Predict treatment response | Evaluate chemotherapy response: CTC declined after chemotherapy | [72] |
Nicolazzo et al. (2021) | Peripheral blood | 20 | CellSearch System, ScreenCell | Treatment monitoring | Serial evaluation of CTCs can guide treatment selection for suitable PD-L1 inhibitors after BCG failure | [73] |
Anantharaman et al. (2016) | Peripheral blood | 25 | Algorithmic analysis | Predict treatment response | High PD-L1+ /CD45− CTC burden and low burden of apoptotic CTCs had worse overall survival | [74] |