Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules

Abstract

Seventy-five percent of patients with epithelial ovarian cancer present with advanced-stage disease that is extensively disseminated intraperitoneally and prognosticates the poorest outcomes. Primarily metastatic within the abdominal cavity, ovarian carcinomas initially spread to adjacent organs by direct extension and then disseminate via the transcoelomic route to distant sites. Natural fluidic streams of malignant ascites triggered by physiological factors, including gravity and negative subdiaphragmatic pressure, carry metastatic cells throughout the peritoneum. We investigated the role of fluidic forces as modulators of metastatic cancer biology in a customizable microfluidic platform using 3D ovarian cancer nodules. Changes in the morphological, genetic, and protein profiles of biomarkers associated with aggressive disease were evaluated in the 3D cultures grown under controlled and continuous laminar flow. A modulation of biomarker expression and tumor morphology consistent with increased epithelial-mesenchymal transition, a critical step in metastatic progression and an indicator of aggressive disease, is observed because of hydrodynamic forces. The increase in epithelial-mesenchymal transition is driven in part by a posttranslational up-regulation of epidermal growth factor receptor (EGFR) expression and activation, which is associated with the worst prognosis in ovarian cancer. A flow-induced, transcriptionally regulated decrease in E-cadherin protein expression and a simultaneous increase in vimentin is observed, indicating increased metastatic potential. These findings demonstrate that fluidic streams induce a motile and aggressive tumor phenotype. The microfluidic platform developed here potentially provides a flow-informed framework complementary to conventional mechanism-based therapeutic strategies, with broad applicability to other lethal malignancies.

Keywords: combination therapies; molecular targets; photodynamic therapy; stress response; tumor microenvironment.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Modeling fluidic determinants of ovarian cancer dissemination and growth. Tumor cell dissemination and colonization of distant sites is influenced by a complex array of factors including the physical stresses that tumor cells encounter as they interact with stromal beds. (A) Ovarian cancer disseminates predominantly via movement of intraperitoneal fluid leading to a distinctive distribution pattern of tumor nodules (orange) involving four common abdomino-pelvic sites: (1) cul-de-sac (peritoneal fold between the rectum and the posterior wall of the uterus); (2) right infracolic space (the apex formed by the termination of the small intestine of the small bowel mesentery at ileocecal junction); (3) left infracolic space (superior site of sigmoid colon); (4) Right paracolic gutter (communication between the upper and lower abdomen defined by the ascending colon and peritoneal wall). This characteristic distribution is influenced by preferential pathways of ascitic flow (blue arrows) that are established by the hydrodynamics of intraperitoneal fluid motion in the abdomino-pelvic cavity. The direction and strength of these fluidic pathways are determined by physical influences including negative subdiaphragmatic pressure, gravity, and organ mobility as well as by recesses formed by key anatomical structures: (i) cul-de-sac, (ii) termination of small intestine mesentery, (s) sigmoid colon, (iv) falciform ligament, and (v) phrenicocolic ligament. In contrast to this flow-based dissemination, the absence of ascites leads to metastatic spread that is largely proximal to the primary tumor. (B) Schematic of a microfluidic chip used to study the effect of sustained flow on the growth and molecular features of 3D ovarian cancer nodules. (C) Photograph of a microfluidic chip used in the experiments. (D) A side view of a microfluidic chip designed to study the impact of flow on the attachment and growth of ovarian cancer cells to a stromal bed. (E) Ovarian cancer cells were cultured successfully under continuous flow for 7 d in the microfluidic chip and formed 3D micronodules as shown in a 3D rendering (Left) and an optical slice (Right) of a two-photon autofluorescence image.

Fig. 2.

Computational modeling of flow in the microfluidic platform. (A) Schematics of the cross-section of microchannels with a stromal bed (Matrigel coating). (Top to Bottom) Velocity field (mm/s), shear rate (1/s), and y- and z- components of vorticity distribution (1/s) are plotted across the cross-section above the Matrigel. (B) Schematic for gaseous and thermal equilibration across porous tubing. The length of the tube inside the incubator was designed to be sufficiently long to allow gaseous and thermal equilibration before entry of the medium into microchannels. (C) CO2 concentration (moles/m3) and (D) Temperature (°C) contours on the axisymmetric layer of medium and porous tubing that feeds the microchannel with culture medium that is sufficiently equilibrated to the appropriate temperature and CO2 levels before entering the channel.

Fig. 3.

Characterization of tumor cell distribution in microfluidic channels immediately after flow (A–D), distribution of 3D tumor nodules in microfluidic channels after 7 d of growth (E and F), and comparison of 3D nodule volume and viability with equivalent nonflow cultures (G–I). (A) Intrachannel distribution of adherent ovarian cancer cells immediately after the introduction of three initial cell concentrations (104, 105, and 106 cells/mL) into the channels was quantified in three regions: proximal to the inlet (1.6–6.5 mm), middle (11.4–14.7 mm), and proximal to the outlet (19.4–24.3). (B) A concentration-dependent increase in the intrachannel tumor cell adherence density was observed in all three regions (P < 0.05). Within each initial cell concentration, results indicated no statistically significant difference in adherent cell densities across the channel in the three regions analyzed (P > 0.05). There was a trend toward decreased cell adherence density distal to the outlet at the initial cell concentration of 106 cells/mL. (C) Characterization of the number of adherent cells per linear mm [λ (x)] showed similar trends as a function of distance along the channel at the initial concentration of 106 cells/mL. (D) The number of cells adhered per linear distance across the channel [λ (y)] indicated higher concentration toward the channel center. (E and F) At an initial concentration of 106 cells/mL, adherent ovarian cancer cells that grew into 3D micronodules under the influence of continuous flow for 7 d were distributed along the full length of the channel (x axis) and across the width of the channel (y axis). (G) Compared with nonflow 3D cultures at all equivalent plating densities (black bars), growth under continuous flow (blue striped bars) resulted in a significant decrease in mean tumor volume. ***P < 0.001, *P = 0.01 to < 0.05. (H) A shift toward smaller tumors was observed in 3D nodules cultured under continuous flow (blue bars) compared with equivalent nonflow 3D cultures (white bars). (I) At all equivalent plating densities, 3D nodules grown under continuous flow (blue striped bars) had a significantly lower fractional viability than corresponding nonflow cultures (black bars). ***P < 0.001.

Fig. 4.

Biological characterization of 3D nodules cultured under flow vs. nonflow. (A) Compared with nonflow, 3D ovarian cancer nodules grown under flow exhibited morphological features indicative of increased EMT and a more motile phenotype, as observed by DIC and two-photon autofluorescence microscopy and on-chip immunofluorescence staining of a clinically relevant biomarker, EGFR. (B) Fractal dimension (a ratio describing how an object fills space out to its maximum radius with a value of 1 describing a line and a value of 2 a circle) was used to quantify the morphological features of 3D tumors grown under flow versus nonflow conditions. Fractal dimension was significantly lower under flow (1.78 ± 0.01, n = 8 fields) than in nonflow (1.87 ± 0.01, n = 6 fields) conditions (P < 0.05), supporting the observation that flow induces morphological changes consistent with increased EMT in 3D tumors. *** P < 0.001. (C) A significant down-regulation of E-cadherin and CDC2 gene expression was induced by flow (1.0 ± 0.10 and 1.0 ± 0.14, respectively) compared with nonflow cultures (1.5 ± 0.16 and 2.0 ± 0.25, respectively) (n = 6) (P < 0.05). EGFR gene expression levels were not significantly different between nonflow (1.1 ± 0.17) and flow (1.2 ± 0.12) conditions (n = 6), whereas a significant increase in p27Kip1 gene levels was observed under flow (5.3 ± 0.71) relative to nonflow cultures (1.0 ± 0.17) (n = 6) (P < 0.05). *** P < 0.001. (D) In the presence of flow, a significant increase in EGFR expression and phosphorylation was observed (0.70 ± 0.09 and 0.86 ± 0.10, n = 6 and 4, respectively) as compared with nonflow cultures (0.28 ± 0.06, and 0.51 ± 0.09, n = 6 and 4, respectively) (P < 0.05). E-cadherin protein expression decreased significantly in flow (0.19 ± 0.04) as compared with nonflow 3D cultures (0.45 ± 0.10) (n = 9) (P < 0.05), and vimentin expression increased significantly under flow (1.14 ± 0.19, n = 9) compared with nonflow (0.11 ± 0.04, n = 8) conditions (P < 0.05). A flow-induced down-regulation of β-catenin expression was observed (0.67 ± 0.10 under flow compared with 1.3 ± 0.10 in nonflow cultures) (n = 10) (P < 0.05). There was a trend toward a reversal of the protein expression of p27Kip1 and CDC2 (and activation for CDC2), relative to the gene expression for these markers, as a consequence of flow. ***P < 0.001, **P = 0.001 to <0.01, *P = 0.01 to <0.05.

Fig. 5.

Proposed model for hydrodynamic stress-induced modulation of ovarian cancer biology. (0) Baseline levels of EGFR activity and protein expression are maintained by a complex array of factors including recycling and degradation of the activated receptor complex. (1) Flow-induced stress causes a posttranslational up-regulation of EGFR expression and activation, which may result from decreased EGFR degradation and increased receptor recycling. (2) The resultant increase in EGFR signaling modulates molecular pathways (26, 27) that induce a transcriptionally regulated decrease in (3) E-cadherin protein expression. A concomitant reduction in β-catenin and an increase in vimentin protein expression are observed, indicative of EMT resulting from stress induced by hydrodynamic physical forces.

Fig. P1.

(A) This study was motivated by the need to identify the physical and biological factors that influence tumor heterogeneity within the context of ovarian cancer, an example of a lethal malignancy that disseminates and grows on stromal beds under the influence of preferential pathways of ascitic flow (blue arrows). (B) Ovarian cancer cells were cultured successfully under continuous flow for 7 d and formed viable micronodules in a custom bioengineered platform that integrates microfluidics and 3D tumor growth. (C) Flow-induced stress caused a posttranslational up-regulation of EGFR expression and activation, which may have resulted from decreased EGFR degradation and increased receptor recycling. The resulting increase in EGFR signaling led to a transcriptionally regulated decrease in E-cadherin protein expression. A concomitant significant decrease in β-catenin protein expression and increase in vimentin protein expression was observed.