TY - JOUR
T1 - The effects of biofilms on tumor progression in a 3D cancer-biofilm microfluidic model
AU - Deng, Yanlin
AU - Liu, Sylvia Yang
AU - Chua, Song Lin
AU - Khoo, Bee Luan
N1 - Funding Information:
The quantification of bacterial cell count further supported the presence of biofilm in the CT model. CFU counts were obtained after removing non-adherent bacteria. The CFU counts of adherent bacteria from the CT model were significantly higher than those from the CL model, especially at lower MOI 1:1 after 9 h of infection (by 2.25 times) (Fig. 3D, Supplementary Fig. 4C-D). Besides, since eDNA is a major component of UPEC biofilms (Devaraj et al. 2015, 2019), we hypothesized that eDNA was involved in biofilm formation in the CT model. By measuring the intensity of the UTI89-GFP fluorescence signal normalized to the background from the images captured by the Z-stack (Fig. 3E, Supplementary Figure 4E), we observed that the relative biofilm density on the periphery of cancer cell clusters of the CT model was higher than that of CL models, especially at higher MOI (500:1) (Fig. 3F, Supplementary Fig. 4F-G). The 3D reconstruction of cell clusters also clearly demonstrated the differential colonization of bacteria in these two models, and highlighted the presence of biofilm formation around the cancer cell clusters with the CT model. All these results corroborated our findings that eDNA-based biofilms formed by EB were present only in the CT model.Cancer stem-like properties are shown to be positively correlated with the cancer cell self-renewal and cancer metastasis (Chandrakesan et al., 2014). We demonstrated that the differential distribution of bacteria in CT and CL models affected the expression of CD44 and CD24, both of which are biomarkers corresponding to the CSC phenotype (Fig. 4A). CD24 is associated with the carcinogenicity of bladder cancer, and CD44 is positively correlated with the clinical stage of bladder cancer (Hofner et al., 2014). Specifically, under the CT model at all MOIs, the expression of CD44 in cancer cells increased significantly. Compared with clusters from the CL model, the proportion of CD44+ cells in the CT model was significantly higher 9 h after infection, especially when the MOI was low (1:1) (9 h: 1.23 times; Fig. 4B). A lower degree of infection could have allowed cells to gradually adapt over time, inducing epithelial to mesenchymal transition, thereby increasing the proportion of CSCs (Massague and Obenauf 2016). At 9 h and 24 h after infection in the CT model, the proportion of CD44+CD24+ cells was also significantly higher than that in the CL model, especially in the case of low MOI (1:1) (9 h: 1.89 times; Fig. 4D?E). When MOIs were higher at 100:1 and 500:1, the difference in the proportion of CSCs became less pronounced. The quantification of CD44 expression based on fluorescence intensity supported our findings that, compared with the CL model, the expression of CD44 in the CT model was significantly elevated 1?9 h after infection at all MOIs (Fig. 4F). This implied that cancer cells within the clusters were driven towards a cancer stem-like phenotype. Therefore, in cancer patients with systemic infection during chemotherapy, EB could play an important role in tumor progression and metastasis.B. L. Khoo: City University of Hong Kong (9610430), which is funded by the Research Grants Council (RGC). S.L. Chua: Hong Kong Polytechnic University Startup Fund (BE2B); Environmental and Conservation Fund (ECF 49/2019), Hong Kong and State Key Laboratory for Chemical Biology and Drug Discovery, Hong Kong.This study was supported by the City University of Hong Kong, which is funded by the Research Grants Council (RGC). This work was also supported by the Hong Kong Polytechnic University (BE2B), Environmental and Conservation Fund (ECF 49/2019), and State Key Laboratory for Chemical Biology and Drug Discovery.
Funding Information:
This study was supported by the City University of Hong Kong , which is funded by the Research Grants Council (RGC) . This work was also supported by the Hong Kong Polytechnic University ( BE2B ), Environmental and Conservation Fund ( ECF 49/2019 ), and State Key Laboratory for Chemical Biology and Drug Discovery .
Funding Information:
B. L. Khoo : City University of Hong Kong ( 9610430 ), which is funded by the Research Grants Council (RGC) . S.L. Chua: Hong Kong Polytechnic University Startup Fund ( BE2B ); Environmental and Conservation Fund (ECF 49/2019 ), Hong Kong and State Key Laboratory for Chemical Biology and Drug Discovery, Hong Kong .
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/5/15
Y1 - 2021/5/15
N2 - Components within the tumor microenvironment, such as intratumoral bacteria (IB; within tumors), affect tumor progression. However, current experimental models have not explored the effects of extratumoral bacteria (EB; outside tumors) on cancer progression. Here, we developed a microfluidic platform to analyze the influence of bacterial distribution on bladder cancer progression under defined conditions, using uropathogenic Escherichia coli. This was achieved by establishing coating (CT) and colonizing (CL) models to simulate the different invasion and colonization modes of IB and EB in tumor tissues. We demonstrated that both EB and IB induced closer cell-cell contacts within the tumor cluster, but cancer cell viability was reduced only in the presence of IB. Interestingly, cancer stem cell counts increased significantly in the presence of EB. These outcomes were due to the formation of extracellular DNA-based biofilms by EB. Triple therapy of DNase (anti-biofilm agent), ciprofloxacin (antibiotic), and doxorubicin (anti-cancer drug) could effectively eradicate biofilms and tumors simultaneously. Our preclinical proof-of-concept provides insights on how bacteria can influence tumor progression and facilitate future research on anti-biofilm cancer management therapies.
AB - Components within the tumor microenvironment, such as intratumoral bacteria (IB; within tumors), affect tumor progression. However, current experimental models have not explored the effects of extratumoral bacteria (EB; outside tumors) on cancer progression. Here, we developed a microfluidic platform to analyze the influence of bacterial distribution on bladder cancer progression under defined conditions, using uropathogenic Escherichia coli. This was achieved by establishing coating (CT) and colonizing (CL) models to simulate the different invasion and colonization modes of IB and EB in tumor tissues. We demonstrated that both EB and IB induced closer cell-cell contacts within the tumor cluster, but cancer cell viability was reduced only in the presence of IB. Interestingly, cancer stem cell counts increased significantly in the presence of EB. These outcomes were due to the formation of extracellular DNA-based biofilms by EB. Triple therapy of DNase (anti-biofilm agent), ciprofloxacin (antibiotic), and doxorubicin (anti-cancer drug) could effectively eradicate biofilms and tumors simultaneously. Our preclinical proof-of-concept provides insights on how bacteria can influence tumor progression and facilitate future research on anti-biofilm cancer management therapies.
KW - Antibacterial agents
KW - Biofilms
KW - Combinatorial therapy
KW - Drug screening
KW - Microfluidic tumor models
UR - http://www.scopus.com/inward/record.url?scp=85101872711&partnerID=8YFLogxK
U2 - 10.1016/j.bios.2021.113113
DO - 10.1016/j.bios.2021.113113
M3 - Journal article
C2 - 33677357
AN - SCOPUS:85101872711
SN - 0956-5663
VL - 180
JO - Biosensors
JF - Biosensors
M1 - 113113
ER -
