| Literature DB >> 34178700 |
Guanghou Fu1, Kok Suen Cheng2,3, Anqi Chen3, Zhijie Xu1, Xiaoyi Chen1, Junjie Tian1, Congcong Xu1, Yukun Sun3, Kuang Hong Neoh3, Yun Dai1, Ray P S Han2, Baiye Jin1.
Abstract
Bladder cancer is characterized by its frequent recurrence and progression. Effective treatment strategies need to be based on an accurate risk stratification, in which muscle invasiveness and tumor grade represent the two most important factors. Traditional imaging techniques provide preliminary information about muscle invasiveness but are lacking in terms of accuracy. Although as the gold standard, pathological biopsy is only available after the surgery and cannot be performed longitudinally for long-term surveillance. In this work, we developed a microfluidic approach that interrogates circulating tumor cells (CTCs) in the peripheral blood of bladder cancer patients to reflect the risk stratification of the disease. In a cohort of 48 bladder cancer patients comprising 33 non-muscle invasive bladder cancer (NMIBC) cases and 15 muscle invasive bladder cancer (MIBC) cases, the CTC count was found to be considerably higher in the MIBC group compared with the NMIBC group (4.67 vs. 1.88 CTCs/3 mL, P=0.019), and was significantly higher in high-grade bladder cancer patients verses low-grade bladder cancer patients (3.69 vs. 1.18 CTCs/3mL, P=0.024). This microfluidic assay of CTCs is believed to be a promising complementary tool for the risk stratification of bladder cancer.Entities:
Keywords: biomarker; bladder cancer; circulating tumor cells; microfluidics; risk stratification
Year: 2021 PMID: 34178700 PMCID: PMC8222714 DOI: 10.3389/fonc.2021.701298
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 6.244
Figure 1System setup and microfluidic chip design. (A) Lab-based setup of the microfluidic system. (B) An overview of the microfluidic chip. (C) Illustration of the experimental diagram. (D) Detailed design of the microfluidic chip. (E–H) Numerical simulation of the hydrodynamics in the microfluidic chip.
Figure 2Characterization of the microfluidic approach. (A) Capture efficiency of the microfluidic chip. (B) Intra-assay variability of the microfluidic assay under different cell concentration groups. (C) Identification of a putative CTC based on the microfluidic method.
Figure 3Immunofluorescent test on cell lines and validation on the bladder cancer patients. (A) Immunofluorescent staining on three bladder cancer cell lines. (B) Captured CTCs from the bladder cancer patients.
Baseline clinicopathological characteristics of the cohort.
| Characteristics | NMIBC1 (n=33) | MIBC2 (n=15) | P-value |
|---|---|---|---|
|
| 65.7 (10.2) | 65.6 (10.2) | 0.493 |
|
| 0.143 | ||
| Female | 2 (6.1) | 3 (20.0) | |
| Male | 31 (93.9) | 12 (80.0) | |
|
| 24.1 (3.5) | 24.4 (3.7) | 0.654 |
|
| 0.834 | ||
| Yes | 23 (69.7) | 10 (66.7) | |
| No | 10 (30.3) | 5 (33.3) | |
|
| 0.875 | ||
| Yes | 14 (42.4) | 6 (40.0) | |
| No | 19 (57.6) | 9 (60.0) | |
|
| 0.688 | ||
| Yes | 20 (60.6) | 10 (66.7) | |
| No | 13 (39.4) | 5 (33.3) | |
|
| |||
| Leucocyte (/uL) | 20.8 (4.5–52.5) | 34.6 (6.5–171.7) | 0.317 |
| Bacterium (/uL) | 42.2 (13.6–317.8) | 100.2 (28.1–513.5) | 0.247 |
|
| |||
| Serum creatinine (umol/L) | 81.0 (73.0–93.5) | 85.0 (77.0–92.0) | 0.456 |
| Serum urea (mmol/L) | 5.8 (5.2–6.8) | 5.6 (4.8–7.3) | 0.841 |
| Serum uric acid (umol/L) | 366.0 (287.0–435.5) | 344.0 (281.0–380.0) | 0.312 |
|
| 0.004 | ||
| PUNLMP | 5 (15.2) | 0 | |
| Low grade | 11 (33.3) | 0 | |
| High grade | 17 (51.5) | 15 (100.0) | |
|
| 0.259 | ||
| Yes | 14 (57.6) | 6 (40.0) | |
| No | 19 (42.4) | 9 (60.0) | |
|
| 0.724 | ||
| Nonmultifocality | 18 (54.5) | 9 (60.0) | |
| Multifocality | 15 (45.5) | 6 (40.0) | |
|
| 0.040 | ||
| < 20mm | 17 (51.5) | 3 (20.0) | |
| ≥ 20mm | 16 (48.5) | 12 (80.0) | |
|
| 0.151 | ||
| Radical Cystectomy | 4 (12.1) | 5 (33.3) | |
| TURBT3 | 29 (87.9) | 10 (66.7) | |
|
| 1.88 (0.76-3.00) | 4.67 (1.41-7.93) | 0.019 |
1MIBC, muscle-invasive bladder cancer; 2NMIBC, non-muscle-invasive bladder cancer; 3TURBT, Transurethral resection of bladder tumor.
Figure 4Correlations between CTC count and primary clinical outcomes: (A) histological grade, (B) invasiveness, (C) previous bladder cancer history, (D) multifocality, (E) progression risks of the NMIBC, (F) tumor size.
Figure 5Potential of CTCs as a prognostic biomarker for bladder cancer. (A, B) ROC analyses of CTCs as a prognostic biomarker for indicating tumor grade and invasiveness. (C, D) The histopathologic result of the primary bladder tumor and the liver metastasis of the patient with remote metastasis. The dynamic change of CTC count after surgery with regard to the whole patient cohort (E), NMIBC group (F), and MIBC group (G).