Controlled Three-Dimensional Tumor Microenvironments Recapitulate

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Controlled three-dimensional tumor microenvironments recapitulate phenotypic features and differential drug response in early vs. advanced stage breast cancer Manjulata Singh, Harini Venkata Krishnan, Supraja Ranganathan, Brian Kiesel, Jan Hendrik Beumer, Sreeja Sreekumar, and Shilpa Sant ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.7b00081 • Publication Date (Web): 21 Mar 2017 Downloaded from http://pubs.acs.org on March 29, 2017

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ACS Biomaterials Science & Engineering

Controlled three-dimensional tumor microenvironments recapitulate phenotypic features and differential drug response in early vs. advanced stage breast cancer

Manjulata Singh1‡, Harini Venkata Krishnan1‡, Supraja Ranganathan1, Brian Kiesel1,2, Jan Hendrik Beumer1,2,3, Sreeja Sreekumar4, Shilpa Sant1, 2, 5, 6*

1

Department of Pharmaceutical Sciences, School of Pharmacy; University of Pittsburgh,

Pittsburgh, PA, USA. 2

University of Pittsburgh Cancer Institute, Pittsburgh, PA, USA.

3

Division of Hematology-Oncology, Department of Medicine, University of Pittsburgh School of

Medicine, Pittsburgh, PA, USA. 4

University of Pittsburgh Cancer Institute, Department of Pharmacology and Chemical Biology,

Women's Cancer Research Center, Magee-Women’s Research Institute, Pittsburgh, PA, USA. 5

Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.

6

McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA.

‡

Contributed equally to the work.

*Corresponding author: Shilpa Sant, PhD; Phone: 614-648 9804; Email: [email protected]. Mailing Address: Shilpa Sant, PhD Assistant Professor School of Pharmacy Department of Pharmaceutical Sciences Department of Bioengineering McGowan Institute for Regenerative Medicine University of Pittsburgh 3501 Terrace Street 808A Salk Hall Pittsburgh, PA 15261

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Abstract Progression to advanced stage metastatic disease, resistance to endocrine therapies and failure of drug combinations remain major barriers in the breast cancer therapy. Tumor microenvironments play an important role in progression from non-invasive to invasive disease as well as in response to therapies. Development of physiologically relevant, three-dimensional (3D) controlled microenvironments that can reliably recapitulate tumor progression from the early non-invasive to advanced metastatic stage will contribute to our understanding of disease biology and serve as a tool for screening of drug regimens targeting different disease stages. We have recently engineered physicochemical microenvironments by precisely controlling the size of 3D microtumors of non-invasive T47D breast cancer cells. We hypothesized that the precise control over physiochemical microenvironments will generate unique molecular signatures in size-controlled microtumors (small 150 µm vs. large 600 µm) leading to differential phenotypic features and drug responses. The results indicated that large (600 µm) T47D microtumors exhibited traits of clinically advanced tumors such as hypoxia, reactive oxygen species, mesenchymal marker upregulation and collective cell migration unlike non-hypoxic, non-migratory small microtumors (150 µm). Interestingly, large microtumors also lost estrogen receptor alpha (ER-α) protein, consequently showing resistance to 4-hydroxytamoxifen (4-OHT). On the other hand, large microtumors showed upregulation of pro-angiogenic marker, vascular endothelial growth factor (VEGF) and hence, were more responsive than small microtumors to the growth inhibition by anti-VEGF antibody. Surprisingly, both small and large microtumors exhibited comparable levels of phosphorylated epidermal growth factor receptor (pEGFR) and downstream signaling molecules such as AKT. As a consequence, both, small and large microtumors showed comparable growth inhibition in response to gefitinib (inhibitor preferentially targeting EGFR) in size-independent manner. Thus, precise control over the microenvironmental factors successfully recapitulated molecular characteristics underlying early vs. advanced stage disease using the same non-invasive T47D cells. Such unique molecular 2 ACS Paragon Plus Environment

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signatures further resulted in differential response of small and large microtumors to antiestrogen, and anti-VEGF treatments with comparable response to the EGFR-targeted therapies, underlining the importance of such stage-specific disease progression models in cancer drug discovery. Key Words: size-controlled microtumor model, three-dimensional in vitro models, breast cancer progression, in vitro drug screening, endocrine resistance, EGFR/VEGF targeted therapy

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INTRODUCTION Breast cancer is a clinically heterogeneous disease and is the second largest cause of cancerassociated deaths in women1. Also, 10–15% of breast cancer patients develop aggressive tumors and distant metastases within a few years of primary tumor detection2. This progression of breast cancer is categorized by the ‘stage’ of the disease such as non-invasive (stages 0-2) to invasive (stages 3-4)2. Development of endocrine therapy, chemotherapeutics and biological agents have significantly improved the treatment and survival rates in patients1. However, endocrine resistance and metastases present unmet clinical need for more efficacious drug/s and biomarkers3. Tumor heterogeneity further contributes to the variable/unpredictable therapeutic response and prognosis in breast cancer patients. Tumor growth, progression and drug response are known to be controlled by tumor microenvironment4. Tumor microenvironment consists of non-cellular components (pH, oxygen concentration, blood supply etc.), extracellular matrix (ECM), and cellular components (tumor and stromal cells). Metabolic stress and necrotic signals due to nutrient/oxygen gradients during tumor growth can induce epithelial to mesenchymal transition (EMT), an important hallmark in tumor progression. EMT further causes phenotypic changes in the non-invasive cells transforming them to invasive/aggressive type5. Such mechanisms pertaining to disease stage are widely studied using gene manipulations in 2D cell cultures and animal models. In 2D cell culture, researchers use breast cancer cell lines thoroughly characterized for their molecular status6 that match specific stage of the disease. The major caveat using different cell lines representing different stages of the disease (non-invasive vs. aggressive) is failure to capture molecular changes over time as a function of tumor progression. Alternatively, manipulation of cellular machinery through artificial culture conditions such as hypoxic chambers or genetic alterations can dysregulate other mechanisms influencing tumor progression7. Animal models are advantageous due to presence of more complex physiological

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system. However, the target tissue expression, metabolic processes and immune system are significantly different from humans resulting in varied toxicity/efficacy profiles of potential drug candidates8. Gene signatures/tissue microarrays derived from patient samples can provide relevant information pertaining to specific stage of the disease; however, availability of matching samples from the same patient at each stage of disease progression poses a major challenge9. Advances in tissue engineering and rapid development of biocompatible materials/methods has resulted in variety of 3D culture models with precise control over various factors in the tumor microenvironment4a,

10

. Tumor heterogeneity engineered in 3D models provide significant

advantages over 2D cultures for therapeutic drug screening. Several studies have reported the morphological, genotypic, phenotypic and metabolic changes in 3D as compared to 2D cultures4b,

11

. Due to their ability to mimic in vivo cellular behaviors, 3D models have been

engineered to capture significant hallmarks in cancer such as EMT, drug resistance, angiogenesis and metastasis and are further exploited to study breast cancer biology12. However, currently, there is no preclinical in vitro model that can capture tumor progression in real time in the same, non-invasive cell line model without genetic manipulations or artificial culture conditions. Tumor size is an important prognosis factor associated with metastatic spread and survival rates in breast cancer13. Hence, we exploited microtumor size to engineer reproducible, yet controlled 3D microenvironments where precise control over microtumor size was achieved by micropatterned hydrogels14. As demonstrated in our previous work15, these novel size-controlled MCF7 microtumor models (150, 300, 450 and 600 µm in diameter) recapitulated physiological milieu of solid tumors such as hypoxia, and metabolic stress along with size-dependent changes in the tumor microenvironment. In the current work, we selected two sizes, small 150 µm and large 600 µm of microtumors to highlight how microtumor size influences various non-cellular components in tumor microenvironment of T47D microtumors. We also investigated how these



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microenvironmental changes influence estrogen receptor (ER) and growth factor signaling to enhance tumor progression from non-invasive to advanced aggressive stage. We define advanced aggressive stage as ‘acquisition of mesenchymal phenotype and migratory behaviour’ by otherwise non-invasive T47D cells. Finally, using molecularly targeted small molecule drugs and antibody drugs, we demonstrate that the differential therapeutic drug response is dictated primarily by the presence or absence of unique molecular mechanisms characteristic of disease progression stage.

MATERIALS AND METHODS Cell culture The T47D breast cancer cell line was a kind gift from Prof. Steffi Oesterreich’s lab (Magee Women’s Research Institute, UPCI, Pittsburgh). All the cell culture supplies and media were obtained from Corning® and Mediatech®, respectively unless specified. T47D cells were maintained in T75 flasks in complete growth media (Dulbecco’s Modified Eagle medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS, Hyclone, Utah, USA) and 1% penicillin-streptomycin) in a humidified incubator maintained at 37 °C and 5% CO2. Prior to seeding into hydrogel microwell arrays, cells were cultured to achieve 50-70% confluence. Materials and reagents All chemicals were purchased from Sigma Aldrich (St. Louis, MO) unless specified. The antibodies anti-VEGF (sc-152) and anti-EGFR (1005; sc-03G) were procured from Santa Cruz Biotechnology (California, USA). Anti-ER alpha (NCL-L-ER-6F11) was purchased from Leica Biosystems (Illinois, USA). Anti-beta actin (MA5-15739-D680) was purchased from Thermo Scientific Inc. (Rockford, USA) while anti-phospho EGFR (Tyr 845) (2231S), anti-AKT(9272S), anti-phospho AKT (Ser 473) (4060S), anti-ERK1/2 (9102S), anti-phospho ERK1/2 (Thr 204/Tyr


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202)(4370P) were obtained from Cell Signaling Technology (Danvers, MA, USA). All secondary antibodies (Dylight 680, 800, Alexa Fluor 488 and 594) were procured from Thermo Scientific Inc. (Rockford, USA). 4-hydroxytamoxifen and Gefitinib were purchased from Sigma Aldrich (St. Louis, MO). Ruthenium-tris (4, 7-diphenyl-1, 10-phenanthroline) dichloride (Ru-dpp) was acquired from Santa Cruz Biotechnology (California, USA) while 2’, 7’–dichlorodihydrofluorescin diacetate (DCHFDA) was procured from Cayman Chemicals (Michigan, USA). Propidium iodide was obtained from Sigma Aldrich (St. Louis, MO) and RNAse I solution was purchased from Thermo Scientific Inc. (Rockford, USA). Fabrication of size-controlled three dimensional (3D) microtumors Microtumors of T47D breast cancer cells were fabricated as detailed in the previous work14-15. A pre-polymer silicone elastomer base solution and curing agent were combined in a ratio of 10:1 (Sylgard 184; Dow Corning Corporation, Midland, MI, USA). After removal of bubbles by degassing, the mixture was poured onto a silicon master patterned with an SU-8 photoresist and cured at 75°C for 45 min. PDMS stamps containing micropillars were peeled from the masters. The PDMS stamps (150 and 600 µm) were used to generate non-adhesive polyethylene glycol dimethacrylate (PEGDMA) microwell arrays. PDMS stamps were placed on a PEGDMA 1000 (20% w/v) solution containing photoinitiator Irgacure-1959 (1% w/w; Ciba AG CH-4002, Basel, Switzerland), and then photo-crosslinked by exposure to UV light (350–500 nm wavelength, 5 W/cm2) for 45 s using the OmniCure Series 2000 curing station (EXFO). The PDMS stamp was then peeled from the substrate. This generated hydrogel microwell devices that were sterilized and used for seeding the cells. The devices were sterilized in 70% isopropanol under UV for 45 min. Following this process, devices were washed three times with DPBS to remove isopropanol and observed under microscope for any imperfections/air bubbles. T47D cells (0.5x106 cells/ device/ 25µL media) were added to each device (1x1 cm2) in a 24well plate and allowed to settle for 30 min. This was followed by another round of cell seeding.



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After this step, excess cells were washed away carefully with DPBS, and cultured in complete media for the pre-determined time. The T47D cells were cultured in devices containing defined size microwells (150 and 600 µm in diameters) for 6 days and the 50% of culture media was replenished with 50% fresh media every 24 h. Measurements of reactive oxygen species (ROS) and intra-tumoral oxygen availability Small (150 µm) and large (600 µm) T47D microtumors were cultured using defined size microwell devices as described above for 6 days. For ROS detection, 10 µM DCHFDA was added to the microtumors and cultured for 3 h in an incubator. After a wash with PBS, microtumors were imaged using a confocal microscope (Olympus Fluoview, Olympus). To determine intra-tumoral oxygen availability, fluorescence of Ru-dpp (10-4 µM), (excitation, λmax 455 nm, emission λmax 613 nm), was used as elucidated previously14. Measurement of metabolic activity The microwell devices (1X1 cm2) with T47D microtumors (150 and 600 µm) were cultured in a 24-well plate as mentioned before. On pre-determined time intervals (day 1, 3 or 6), 10% v/v alamarBlue® solution (Thermo Scientific, Rockford, USA) was freshly prepared in complete growth media. The media from all wells was discarded and alamarBlue® solution (600 µL, 10% v/v) was added to each well containing microtumors. After 3 h of incubation at 37°C, the solution was gently mixed using a micropipette. The supernatant was transferred to a 96-well assay plate and the culture plate with devices containing microtumors was replenished with fresh media. The fluorescence intensity of alamar blue solution was measured on a microplate reader (H1 Synergy, Biotek Instruments, Winooski, VT, USA) using excitation and emission wavelengths of λmax, 530 nm and 590 nm, respectively. The percentage (%) growth of microtumors from each device was calculated using the equation: [(Relative fluorescence units at Day # (1, 3 or 6)/ Relative fluorescence units at Day 1)] x100.


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Cell cycle analysis Small and large microtumors were cultured as outlined above. Microtumors were harvested on day 1, 3 or 6 and pelleted using centrifugation for 3 min at 1200 RPM. The pellet was washed with PBS, disaggregated using trypsin for 7-10 min and cells were pelleted using centrifugation. The cell pellet was resuspended in cold PBS (500 µL). The cell suspension was added dropwise to cold absolute ethanol (500 µL). The sample was observed for clumping and any visible clumps were removed using tweezers. The microcentrifuge tubes sealed with parafilm were stored at 4 °C overnight. After this fixing process, cells were washed with cold PBS and centrifuged at 400 RPM for 10 min. The pellet was resuspended in propidium iodide solution (300 µL, 50 µg/mL containing 100 µg/mL RNase I solution). The tubes were vortexed briefly and incubated at 37 °C for 30 min. The data was acquired on a flow cytometer (BD Accuri C6, BD Biosciences, New Jersey, USA) using excitation wavelength 488 nm and emission wavelengths 585/40. For all the groups, total number of events recorded in the FL2-A vs. FL2-H channel was 20,000. The flow cytometry data were analysed using FlowJo software (FlowJo LLC, Oregon, USA). RNA isolation and quantitative PCR (qRT-PCR) analysis For each experiment, microtumors were harvested from at least three 1x1 cm2 devices and washed once with DPBS. Each device generates approximately 280 and 60 uniform 150 µm and 600 µm size microtumors respectively. RNA isolation was performed using GeneJET RNA purification kit (Thermo Scientific, Lithuania, EU) as per the manufacturer’s instructions. RNA concentration was measured using Nanodrop (Thermo Scientific, Lithuania, EU) and RNA quality and integrity was determined by absorbance ratio at 260/280 nm and on 1% agarose gel, respectively. mRNA expression of EMT markers was estimated by qRT-PCR using iScript Onestep-qRT-PCR Kit (BioRad Laboratories Inc., USA). Briefly, reaction mixture containing mRNA template (25 ng), 2X SYBR green master mix (5 µL) and respective primers (0.2 µM) was 6 ACS Paragon Plus Environment


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amplified in triplicates. Primer sequences for EMT markers were as described in previous work15. The housekeeping gene, β-actin (ACTB) was used as reference gene. The amplification protocol used was 10 min of reverse transcription at 50 °C followed by 40 cycles of denaturation for 15 sec at 95 °C, annealing for 30 sec at 55 °C and extension for 30 sec at 72 °C (7500 Fast Real-Time PCR System, Applied Biosystems, California, USA). mRNA expression was calculated using 2-∆∆Ct method16 and depicted as the mean ± SEM as fold change compared to the controls (day 1 samples). Protein extraction and western blotting Freshly harvested or frozen microtumors were homogenized in RIPA buffer containing Tris (50 mM, pH 7.4), NaCl (150 mM), sodium deoxycholate (0.5%), nonyl phenoxypolyethoxylethanol40 (1%), phenylmethylsulfonyl fluoride (0.05 mM), protease inhibitor cocktail for mammalian tissue extract and phosphatase inhibitor cocktail (Sigma-Aldrich Inc., Milwaukee, USA). Total protein content was quantified by Coomassie Plus (Bradford) Assay kit (Thermo Scientific, Rockford, USA). Fifty microgram protein samples were separated using 8-10% SDS-PAGE and transferred onto 0.45 µm PVDF membrane (Thermo Scientific, Rockford, USA). The PVDF membrane was blocked in Odyssey Blocking Buffer (PBS based, LiCor Biosciences, Nebraska, USA) for 2 h at room temperature. Further, blots were probed with primary antibodies by incubating overnight at 4 °C. The membrane was then washed thrice with PBS containing 0.1% Tween-20 (PBST) and incubated with respective fluorescently conjugated secondary antibodies for 2 h at room temperature on a rocking platform. The membranes were developed by scanning in Odyssey Infrared Imaging System (LI-COR® Biosciences, Lincoln, USA) and colored images were converted to grayscale by using Odyssey 3.0 software. Densitometry analysis of blots was done by ImageJ Software (National Institute of Health, USA). Immunofluorescence studies


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Harvested microtumors were fixed with cold paraformaldehyde (PFA, 4%) for 30 min at room temperature, washed with PBS to remove residual PFA and again fixed with 95% methanol on ice for 15 min. This was followed by permeabilization with Triton X-100 (0.1%) for 1.5 h and blocking with BSA (3%) to avoid non-specific binding. Microtumors were placed on depression slides and incubated with primary antibody (1:100) overnight at 4 °C in a humidified chamber along with a negative control (without primary antibody). After washing three times with PBST, microtumors were incubated with fluorescently labelled secondary antibodies for 1 h at room temperature. Nuclei were stained with Hoechst (1:300) at 4 °C overnight. Images were acquired on a confocal microscope (Olympus Fluoview, Olympus) as a z-stack containing a series of 5µm slices using 10X (lower magnification) or 40X (higher magnification) objectives. The images are presented as 2D projection of maximum intensity. Measurement of microtumor growth inhibition in response to 4-Hydroxytamoxifen (4OHT), VEGF antibody and EGFR inhibitor (Gefitinib) The T47D cells were seeded in 150 and 600 µm hydrogel microwell devices (1x1 cm2) in 24 well plates and cultured for three days as described previously. For drug treatments, 4-OHT was solubilized in DMSO (10 mM stock solution) and stored away from light. On day 3, media were removed from wells and metabolic activity was assessed by adding alamarBlue® solution (600 µL, 10% v/v, Thermo Scientific, Rockford, USA). Only media with 10% alamar Blue® solution was used as a blank sample. After removal of the remaining alamarBlue® solution, 4-OHT (600 µL, 50 µM in growth media) was added to the wells (treatment groups) while fresh media with equal volume of DMSO was added to the control/vehicle groups. The culture plate was replaced back into the incubator for additional three days. On day 6, the microtumors were again analysed for metabolic activity by alamarBlue® assay. The percentage growth for microtumors on day 6 in each device was calculated as per the equation: percentage (%) growth = [(Relative fluorescence units at Day 6)/ Relative fluorescence units at Day 3)] x100. Further, percentage



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growth for treatment group of each 150 and 600 µm microtumors was calculated using respective vehicle treated group as 100% growth. Similarly, microtumors were treated with antiVEGF antibody (1:100 in growth media) or gefitinib (5 µM) from day 3 to day 6. AlamarBlue® or Cell-Titer Glo® (Promega, Madison, WI, USA) assays were used on day 6 to determine viability of vehicle or gefitinib-treated microtumors as per the manufacturer’s protocol. The percentage viability was calculated with vehicle-treated group as 100%. 4-OHT quantification in microtumors by mass spectrometry Harvested T47D microtumors were washed with DPBS, pelleted and sonicated in potassium chloride-Tris HCl buffer for 15 s and incubated on ice for 2 h. The mixture was analysed by LCMS/MS method to quantitate 4-OHT (Sigma-Aldrich, St. Louis, MO) in microtumor lysate as described below using [D6]-4-hydroxytamoxifen (Toronto Research Chemicals, North York, Ontario, Canada) as an internal standard. The HPLC method used an Agilent 1100 autosampler and Agilent 1100 binary pump (Agilent Technologies, Palo Alto, CA) with a Synergi Polar-RP 80A (4 µm particle size, 2 mm x 100 mm) column at ambient temperature. Mobile phase solvent A was 0.1% v/v formic acid in methanol, and mobile phase solvent B was 0.1% v/v formic acid in water. Isocratic mobile phase conditions were used with 78% mobile phase A pumped at 0.3 mL/min for the entire duration of the 5 min run time. Retention time was 1.5 min. A Waters Quattro Micro (Milford, MA) mass spectrometer was used in positive-ion multiple reaction monitoring (MRM) mode (4.0 kV capillary voltage, 40 V cone voltage, 22 V collision voltage) to monitor m/z 388.0>72.0 for 4hydroxytamoxifen and m/z 394.0>78.0 for [D6]-4-hydroxytamoxifen. Standards (10, 30, 100, 300, 1000, 3000, 5000 and 10000 ng/mL) were prepared in a 50/50 mixture of potassium chloride lysis buffer and human plasma (Lampire Biological Laboratories Inc., Pipersville, PA). For microtumor samples, microtumor lysate (50 µL) was combined with blank plasma (50 µL) to match the calibrator sample matrix and volume (100 µL). Resulting 9 ACS Paragon Plus Environment

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microtumor lysate concentrations were corrected for the dilution after analysis. Internal standard solution (10 µL, 1 µg/mL) was added to each tube prior to addition of sample. Ice cold methanol (300 µL) was then added and the samples were vortexed for 1 min using a Vortex Genie-2 (Scientific Products, Bohemia, NY). Samples were then centrifuged at 12,500 x g for 3 min and the resulting supernatant (100 µL) was transferred to an autosampler vial. The sample injection volume was 5 µL. Statistical analysis Results are presented as mean ± SEM (standard error of mean) from three independent experiments with multiple replicates of microdevices. A one-way analysis of variance (ANOVA) followed by a Tukey’s multiple comparison test or t-test was used to compare control and test groups. A p-value less than 0.05 was considered significant. Graph Pad Prism (V6.0) was used to perform the statistical analysis.

RESULTS AND DISCUSSION Controlling microtumor size regulates non-cellular components in the solid tumor microenvironment Tumor microenvironment in breast cancer exhibits unique characteristic features at each stage of disease progression17. Compared to early stage, advanced stage malignant breast tumor microenvironment displays hypoxia, enhanced angiogenesis, basement membrane degradation and tumor cell invasion mediated by complex tumor-stromal interactions17-18. To recreate controlled physicochemical microenvironments, we have previously used microfabricated hydrogel microarrays and generated hundreds of uniform microtumors with precisely controlled sizes in the range of 150-600 µm using various head and neck, cervical and breast cancer cell lines14-15. Size-controlled MCF7 microtumors grown in these microfabricated hydrogel



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microarrays showed size-dependent changes in their physicochemical features (hypoxia and reactive oxygen species) and growth kinetics. In this study, we chose another hormone receptor positive cell line, T47D, to generate the size-controlled microtumors and investigate differential response to clinically used molecularly targeted therapies. When T47D cells were seeded in 150 µm and 600 µm size non-adhesive PEGDMA hydrogel microwells, cells compacted forming uniform size microtumors within 24 h and continued to grow until harvested after six days of culture (Supplementary Figure S1A). Each 1x1 cm2 device generated 280 ± 12 and 60 ± 5 uniform 150 µm and 600 µm size microtumors, respectively, providing multiple in-device replicates for all the studies. Such precise control over microtumor size is important because it offers control over various non-cellular factors in the tumor microenvironment. We first analysed size-dependent changes in the non-cellular factors such as hypoxia and reactive oxygen species (ROS) in the microenvironment of small (150 µm) and large (600 µm) microtumors. Presence of hypoxia was assessed by intra-tumoral oxygen availability by oxygen sensitive Ru-dpp staining. The fluorescence of Ru-dpp is enhanced in regions of hypoxia and quenched under normoxic conditions. This is exploited to visualize spatial distribution of hypoxia in microtumors. Ru-dpp staining (indicated by red, Figure S1B) was enhanced to a greater extent in the core of the large microtumors in contrast to the smaller ones. ROS were visualized in the microtumors using the 2’, 7’–dichlorofluorescin diacetate (DCHFDA) probe. DCHFDA a non-fluorescent compound, that becomes fluorescent after reaction with hydroxyl and peroxyl ROS. After 3 h incubation with DCHFDA, ROS (green staining) were detected in central core of the large T47D microtumors (Figure S1C). No ROS production was observed in small (150 µm) microtumors. Further confirmation of the presence of hypoxic microenvironment in large microtumors was provided by protein expression of molecular marker of hypoxia, hypoxia inducible factor 1-alpha (HIF-1α) known to promote tumor progression19. Western blotting


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confirmed the increased expression of HIF-1α in large microtumors (600 µm) compared to the smaller ones as well as 2D cultures (Figure S1D). Thus, induction of HIF-1α observed in large microtumors recapitulates hypoxic microenvironment, a common feature of advanced solid tumors in vivo20. Hypoxic cells have been shown to generate ROS21, a likely reason for presence of ROS in large microtumors. Taken together, these results demonstrate that microtumor size can regulate non-cellular factors in the solid tumor microenvironment. Despite daily media replenishment over six-day culture, large (600 µm) microtumors show presence of hypoxia and ROS in contrast to 150 µm microtumors. Size-induced microenvironmental changes affect microtumor growth, metabolic activity and cell cycle progression We next sought to investigate the effect of size-induced hypoxia on growth of 150 µm and 600 µm size microtumors using direct cell number counting, metabolic activity assay (alamar blue) and cell cycle analysis by flow cytometry. First, using trypan blue dye exclusion, we counted the total number of cells/microtumor in 150 µm and 600 µm T47D microtumors on days 1, 3 and 6. The cell number in 150 µm microtumors increased from 181±87 on day 1 to 345±119 on day 6 (≈1.9 fold change). Similarly, the cell number in 600 µm microtumors increased from 5487±617 on day 1 to 8230 ± 2212 resulting in similar (≈1.5 fold) (Figure 1A). MCF7 microtumors of 150 µm and 600 µm also demonstrated similar trend of increased cell number/ microtumor on day 6 compared to day 115. Next, we measured metabolic activity by alamarBlue® assay that is based on the enzymatic reduction

of

resazurin

to

resorufin

by

nicotinamide

adenine

dinucleotide (NADH)

dehydrogenase. To decouple effects of number of cells/ microtumor and microtumor size on metabolic activity, percentage growth of microtumors in each device was calculated over 6 days by normalizing their alamarBlue activity to that on day 1. Statistical analysis revealed that large microtumors (600 µm) had significantly higher metabolic activity (Figure 1B) on days 3 and 6 12 ACS Paragon Plus Environment


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than that of small microtumors. Higher metabolic activity observed in large microtumors compared to the smaller ones (150 µm) may be necessary to ensure cell survival in the more stressful hypoxic microenvironment (Figure 1B). We further investigated whether the observed microtumor size-dependent changes in the noncellular factors (hypoxia, ROS) affect the cell cycle progression. Cell cycle progression from G0/G1 (gap/DNA repair phase), S (synthesis phase) to G2/M (growth/mitotic phase) has been shown to be influenced by the tumor microenvironment22. For example, oxidative stress can cause DNA damage and arrest the cells in the G0/G1 phase22. On the other hand, a higher proliferation index is associated with higher proportion of cells in the G2/M phase23. We performed propidium iodide (PI) staining of dissociated 150 µm and 600 µm size microtumors to determine their cellular DNA content by flow cytometry. Twenty thousand cells were counted in the final gate after removal of debris and doublets for all samples (n=3 independent experiments). Representative histograms from day 1, 3 and 6 microtumors as well as 2D cultures of T47D cells are shown in Supplementary Figure S2. Time-dependent changes observed in the DNA content from day 1 to day 6 revealed that 150 µm microtumors exhibited a decrease in G0/G1 phase (75.6 ± 5.8 to 65.5 ± 1.2%) along with increase in S (7.2 ± 2 to 11.9 ± 0.5%) and G2/M phase (11.6 ± 3.8 to 15.2 ± 3.5 %) (Figure 1C) on day 6 compared to day 1. Compared to small microtumors or 2D cultures on day 6, large microtumors consisted of significantly lower (43.8 ± 6.2 %) proportion of cells in G0/G1 phase (Figure 1C and 1D). However, unlike small microtumors, there were no significant changes in S (≈13%) and G2/M (≈10%) phases (Figure 1C) in 600 µm microtumors between day 1 and 6 as well as compared to 2D cells and small microtumors (Figure 1D). This suggests that microtumor size did not affect DNA synthesis (S) or growth/mitotic phase (G2/M). Instead, the decrease in G0/G1 phase in large microtumors was accompanied by significant increase (from 4.4 ± 1.8 to 28.9 ± 3.2 %) in sub G0/G1 cells, identified by less than 2N DNA content. The percentage of cells in sub 13 ACS Paragon Plus Environment

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G0/G1 phase remained low (4.5 ± 2.7 %) in 150 µm microtumors. Thus, increase in sub G0/G1 cells in large microtumors may be attributed to the higher percentage of dormant cell population24. Our previous work has shown an outer ring of highly proliferative Ki-67-positive cells and central area of PI-stained cells in large MCF7 microtumors (another ER+ cell line) compared to the small ones15. Controlling microtumor size can thus generate a mixed population of cells within the same microtumor with intra-tumoral heterogeneity in terms of cell cycle and proliferative status. Large microtumors acquire aggressive phenotype demonstrated by mesenchymal marker upregulation and collective cell migration Interestingly, starting from day 3-4 of culture, about 55-65% of large microtumors migrated out of the hydrogel microwell arrays while the small ones (150 µm) remained intact inside the hydrogel devices (Figure 2A) similar to our observation for MCF7 microtumors15. Further, high magnification as well as Hoechst-stained images revealed collective migration of cells in the large microtumors. The collective migration of 600 µm microtumors resembles breast cancer migration in vivo where a cohort of cells from primary tumor develop mesenchymal motility without complete loss of cell-cell adhesion25. To investigate molecular mechanisms responsible for observed migration in large T47D microtumors, we analysed time-dependent changes in the signalling molecules reported for classical EMT (Figure 2B). mRNA expression of EMT markers including SNAIL, SLUG, TWIST, VIMENTIN (VIM) and E-CADHERIN (E-CAD) was measured on days 1, 3 and 6. Transcriptional levels of EMT markers such as SNAIL, SLUG and TWIST were significantly upregulated in large microtumors on day 6 compared to day 1 and small microtumors. The mesenchymal marker, VIM showed nearly 7-fold upregulation in mRNA expression in large microtumors on day 6 compared to day 1. Small microtumors had no significant change in VIM at day 6 compared to day 1 (Figure 2B). Overall, large microtumors displayed time-dependent upregulation of mesenchymal markers at mRNA level suggesting



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mesenchymal transformation of non-invasive epithelial T47D cells when cultured as large (600 µm) microtumors. Interestingly, mRNA levels of epithelial marker, E-CAD, in large microtumors increased significantly at day 6 compared to day 1 while E-CAD protein showed similar expression levels in small and large microtumors (Figure 2C). This may be due to posttranslational modifications of E-CAD but cannot be explained with our current data. We also observed time-dependent increase in VIM expression in the large microtumors compared to small microtumors. Immunofluorescence imaging on day 6 indicated heterogeneous distribution of VIM in large microtumors (Figure 2D). While small and large microtumors had homogenous membranous E-CAD expression, VIM expression was found to be high in cells at the periphery and at the migratory front of large microtumors; however, it was not expressed in the small microtumors. It should be noted that the lower degree of VIM staining in the inner core of large microtumors is not due poor penetration of antibodies as we obtained uniform E-CAD staining in the large microtumors. Similarly, as will be discussed later, estrogen receptor-alpha (ER-α) antibody stained large microtumors uniformly on day 1 while capturing loss of ER-α in the inner core on day 6. E-CAD was not lost in large microtumors at transcriptional or translational level by mRNA or protein analysis, as reported for classical EMT (upregulation of mesenchymal markers with simultaneous loss of epithelial marker, E-CAD)26. Recent studies have also reported that the loss of E-CAD is not a necessity for EMT27. Clinically, it is observed that, ovarian cancer and inflammatory breast cancers exhibit high metastatic and invasive phenotype despite having high E-CAD levels28. This represents a partial EMT phenotype where cells acquire mesenchymal phenotype without loss of epithelial markers like E-CAD29. Similarly, a partial EMT phenotype has been associated with collective migration due to weak cell-cell adhesion in the hybrid epithelial and mesenchymal cell populations30. This collective cell migration in large microtumors can be linked to the aggressive phenotype of tumors found in clinically advanced


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stage cancers31. Cumulatively, these results suggest that large microtumors of non-invasive T47D cells acquire aggressive phenotype similar to the advanced breast tumors as demonstrated by mesenchymal marker upregulation and migratory phenotype. This is the first study that demonstrates time-dependent EMT changes in 3D in vitro models and transformation to advanced stage in tumor progression as a function of microenvironmental changes using a single cell line and without genetic manipulation. When grown as large microtumors, ER+ T47D cells lose ER-α α expression at the protein level and exhibit endocrine resistance The estrogen receptor alpha (ER-α) is responsible for driving the growth of ER+ breast tumors. It has been widely used as a prognostic marker for ER+ breast cancer progression as well as to predict the response to endocrine therapy32. Clinically, it is reported that ER-α levels are downregulated at both gene and protein levels with tumor progression33. Therefore, we measured protein expression of ER-α in the small and large microtumors. We observed significant loss of ER-α protein in the large microtumors on days 3 and 6 (compared to day 1) (Figure 3Ai). Densitometry evaluation showed more than 5-fold decrease in ER-α protein expression on day 6 compared to day 1 in large microtumors (Figure 3Aii). On the contrary, small microtumors exhibited negligible changes in ER-α protein expression from day 1 to day 6. ER-α receptor downregulation has been linked to proteasome-mediated degradation triggered by hypoxia34. Thus, loss of ER-α protein in large microtumors may be attributed to the higher levels of hypoxia and HIF-1α present in the large microtumors (Figure S1D). Immunofluorescence studies further supported link between hypoxia and loss of ER-α in large microtumors. As shown in Figure 3B, the ER-α expression in small microtumors was maintained throughout the culture period, thus confirming the protein expression data (Figure 3A). On the other hand, large microtumors (600 µm) showed time-dependent decrease in ER-α



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expression in the central hypoxic core (Figure 3B, lower panel) confirming results of western blotting (Figure 3A). This finding has high clinical significance, as we were able to induce loss of ER-α in large microtumors in real time without affecting ER-α expression in small ones, though both are multicellular aggregates of the same non-invasive T47D cells. Interestingly, clinical studies have reported loss of ER-α, at both gene and protein levels as the disease progresses from intraductal to invasive carcinomas33, 35. It is reported that about 30% of patients lose ER-α as the disease progresses to advanced stages36. Taken together, these observations offer mechanistic insights into tumor progression of ER+ T47D microtumors as a function of microtumor size and may be attributed to loss of ER-α in large microtumors due to size-induced hypoxic microenvironment. Importantly, this phenotype further validates that the large microtumors (600 µm) show traits of advanced stage breast tumors observed clinically. We further explored whether the large microtumors exhibited endocrine resistance, another feature of ER+ breast cancer progression37. A standard drug of choice in endocrine therapy, 4hydroxytamoxifen (4-OHT) was used to treat the microtumors (50 µM for days 3-6). The small (150 µm) microtumors treated with 4-OHT exhibited only 14% growth, significantly reduced compared to that in the vehicle-treated group (Figure 3C). In contrast, large microtumors treated with 4-OHT exhibited 65% growth of that observed in the vehicle controls. The data indicated that small microtumors were significantly more sensitive to growth inhibition by 4-OHT than the larger ones. Results from mass spectrometry demonstrated that there was no significant difference in total amount of 4-OHT/microtumor (ng/microtumor) between small and large microtumors (Figure 3D) suggesting that the observed differences in drug response are not due to the size-dependent drug diffusion limitation. Researchers have elucidated HIF-1α as a direct transcriptional target of ER-α that correlates strongly with poor outcomes to endocrine therapy in ER+ patients38. Therefore, these observations together suggest that the endocrine


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resistance in large microtumors may be due to the loss of the target ER-α aligning with the clinical data. Anti-VEGF treatment preferentially inhibited migration and metabolic activity in large T47D microtumors New blood vessel formation/ angiogenesis is one of the important hallmarks of tumor progression. Expression of pro-angiogenic factor, vascular endothelial growth factor (VEGF) is a spontaneous response of solid tumors to overcome the diffusional limitations and resume survival. Western blot analysis revealed higher expression of VEGF in large microtumors than smaller ones (150 µm) (Figure 4A). Hence, we investigated microtumor response to anti-VEGF antibody treatment from day 3-6. Assessment of metabolic activity after anti-VEGF treatment revealed that large microtumors were more susceptible to growth inhibition than smaller ones (Figure 4B). Anti-VEGF antibody treatment decreased the growth of large microtumors by 23.5±4.3 % compared to respective vehicle-treated controls (Figure 4B) while no significant effect was observed on the growth of small microtumors. This suggests that VEGF may play important role in the cell survival of aggressive large microtumors. Although we see significant growth inhibition in large microtumors compared to the smaller ones, the effect is not as pronounced as 4-OHT treatment. This may be because the primary goal of anti-VEGF treatment clinically is to inhibit angiogenic response and not tumor growth. Other In vitro studies have also shown no effect of VEGF inhibitors on tumor survival in VEGF-engineered cancer cell lines but significantly inhibited endothelial cell migration39. Importantly, anti-VEGF antibody treatment attenuated collective migration observed in large microtumors (Figure 4C). Thus, dependence of large microtumors on VEGF signalling unlike small microtumors is responsible for their higher sensitivity to anti-VEGF treatment. Together, differential sensitivity of large microtumors highlighting endocrine resistance to ER-targeted 4-OHT (small molecule drug) and significantly higher growth inhibition with VEGF-targeted anti-VEGF antibody (large molecule) emphasizes 18 ACS Paragon Plus Environment


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that underlying molecular mechanisms such as downregulated ER expression or upregulated VEGF expression are primarily responsible for the observed drug response as against microtumor size-dependent diffusion limitation. T47D microtumors display constitutive activation of AKT and ERK1/2, downstream signaling molecules of EGFR pathway, irrespective of microtumor size Endocrine resistance in advanced stage breast cancer is often associated with dependence on alternative pathways for growth such as epidermal growth factor receptor (EGFR) and/or human epidermal growth receptors (HER2/3/4) signaling40. Hence, we determined expression of proteins important for proliferation/survival and tumor progression that are downstream of the EGFR pathway. These included EGFR, AKT, ERK1/2 and their phosphorylated forms that depict activation of pathway/s41. Comparable levels of phosphorylated-EGFR (Tyr 845) levels were detected in small and large microtumors in spite of significantly reduced total EGFR expression levels in the large microtumors as a function of time (Figure 5A). The observed decrease in total EGFR protein expression in the large microtumors was further confirmed by immunofluorescent imaging that showed loss of EGFR in the inner core of large microtumors (Figure 5B). In contrast, small microtumors did not show any time-dependent changes in EGFR expression. Protein expression and phosphorylation levels of signal transduction molecules downstream of EGFR pathway such as AKT did not exhibit significant differences between small and large microtumors (Figure 5A). Our results are in accordance with a recently published study where fulvestrant-resistant T47D cells showed decreased levels of total EGFR with phosphorylated EGFR levels comparable to that of parental T47D cells. Similarly, these resistant T47D cells showed similar expression and phosphorylation levels of AKT42. Dependence on EGFR pathway has been exploited in breast cancer for treatment with tyrosine kinase inhibitors that block signal transduction to reduce proliferation of tumors43. Gefitinib, ATPcompetitive kinase inhibitor is a selective inhibitor of EGFR/HER1 pathway and has been used 19 ACS Paragon Plus Environment

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in the treatment of endocrine resistant breast cancer43. When treated with gefitinib (5 µM) for 3 days, small and large microtumors resulted in 11±14% and 29±4% growth inhibition, respectively with no statistically significant differences among them (Figure 5C). Higher dose of gefitinib (25 µM) resulted in much higher and significant growth inhibition in both small (55±1%) and large microtumors (66±6%); however, these values were not statistically different (Figure 5D). This further indicates that effect of gefitinib treatment was independent of microtumor size due to similar EGFR signaling pathway in small and large microtumors (Figure 5A). Gefitinib treatment (5 µM) prevented phosphorylation of ERK1/2 in treated microtumors of both small and large sizes (Figure 5E). Together, these results confirm that the microtumor models truly respond to therapy based on the status of the underlying molecular mechanisms. In summary, although small and large microtumors were generated from the same ER+ parental T47D cell line, size-dependent microenvironmental changes such as hypoxia, ROS and proangiogenic factors induced downstream signalling such as loss of ER-α, and upregulation of VEGF in large microtumors. Such differential pathway activation between 150 and 600 µm microtumors further led to differential response to ER-targeted anti-estrogen, and anti-VEGF antibody without much difference in EGFR-targeted gefitinib response. Non-migratory small microtumors retaining ER+ status were more sensitive to anti-estrogen 4-OHT similar to early stage breast cancer patients while migratory large microtumors with loss of ER-α showed endocrine resistance; however, upregulated VEGF levels rendered them more sensitive to antiVEGF therapy similar to the advanced stage breast cancer patients. With similar expression levels of signal transduction molecules involved in EGFR pathway, both small and large microtumors responded in size-independent manner to EGFR-targeted gefitinib. This further validates that differential drug response observed in 150 and 600 µm microtumors is not due to microtumor size-mediated drug diffusion limitations but indeed due to the differential microenvironment-mediated signalling changes.



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This study shows that i) tumor microenvironment plays a significant role in dictating molecular mechanisms involved in tumor progression and hence, it warrants development of physiologically relevant 3D models with precise and reproducible control over tumor microenvironment; and ii) the disease stage-specific tumor models that recapitulate underlying molecular mechanisms of disease progression will be instrumental for effective screening of targeted therapies.

CONCLUSIONS We have developed size-controlled 3D microtumors as in vitro models to recapitulate early and advanced stage of the breast cancer using non-invasive T47D cells. By manipulating microtumor size (and size alone) in 3D cultures without any other artificial culture conditions, we were able to transform non-invasive T47D cells into aggressive migratory phenotypes. When cultured in non-adhesive PEG hydrogel microwells, precisely controlled, uniform microtumor sizes elicited reproducible changes in the tumor microenvironment in small (150 µm) and large (600 µm) T47D microtumors. Small microtumors fabricated from the same non-invasive cell line showed minimal phenotypic changes and served as a 3D control of early stage, non-aggressive disease. On the other hand, large microtumors displayed hypoxic microenvironment, upregulation of ROS, HIF-1α and VEGF and increase in dormant cell population compared to small microtumors. These changes further triggered underlying signaling mechanisms and recapitulated important hallmarks of breast tumor progression such as upregulation of mesenchymal makers without loss of epithelial cadherin (E-CAD), migratory phenotype, and loss of ER-α. Importantly, small microtumors representing early stage disease showed significantly high growth inhibition in response to small molecule drug, 4-OHT, which failed to effectively inhibit growth of large microtumors due to loss of ER. On the contrary, anti-VEGF antibody was more effective in inhibiting growth of large microtumors due to high expression of


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VEGF. EGFR-targeted gefitinib showed comparable growth inhibition independent of microtumor size due to similar underlying EGFR pathway status in both the microtumor sizes. Future studies are needed to gain detailed mechanistic insights to explain this observation. In summary, the size-controlled microtumor model is an advance over other models in several important ways such as reproducibility, controlled microenvironments and ability to capture tumor progression within 6 days making it suitable to screen drugs and develop better therapies in a stage-specific manner. These models currently lack extracellular matrix and stromal cells like fibroblasts and immune cells that are integral part of the in vivo tumor microenvironment. Future studies will focus on incorporation of these microenvironmental factors to create more complex and realistic tumor microenvironments that exist in vivo.

Acknowledgment This work is supported by NIH funding (EB018575) and the start-up funds from the Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh (SS). This project used the UPCI Cancer Pharmacokinetics and Pharmacodynamics Facility (CPPF) and was supported in part by award P30CA047904 (JHB). The authors thank Dr. Wen Xie, Center for Pharmacogenomics, School of Pharmacy, University of Pittsburgh for access to qRT-PCR instruments. Authors thank Dr. Steffi Oesterriech for providing T47D cell line, Sharlee Mahoney for help with the flow cytometer, Dr. Ipsita Banerjee for access to the flow cytometer, and MengNi Ho for help with gefitinib studies. The authors also thank Drs. Steffi Oesterriech and Vinayak Sant, University of Pittsburgh for insightful discussions and critical review of the manuscript.

Supporting Information The supplementary information pertaining to figures S1 and S2 are attached in the supporting information file.



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Author Contribution SS, MS, HVK designed the study; MS, HVK, SR, BK, S. Sreekumar, and SS performed the experiments; HVK, SS, MS, JHB, and S. Sreekumar analysed the data; SS, MS, and HVK wrote the manuscript, all authors reviewed and revised the manuscript.


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FIGURE LEGENDS Figure 1. Size-induced microenvironmental changes affect microtumor growth, metabolic activity and cell cycle progression (A) T47D microtumors (150 and 600 µm in diameter) harvested on day 1, 3 and 6 were dissociated into single cell suspension. Cells were counted under light microscope by trypan blue dye exclusion and cell number/ microtumor was calculated. Microtumors show significant increase in cell number/microtumor on day 6 compared to day 1. Data are represented as mean ± SEM (n = 4-6; * p < 0.05) (B) Metabolic activity of microtumors was determined at day 1, 3 and 6 by alamarBlue® assay. Percentage growth in 150 and 600 µm microtumors was calculated by normalizing RFUs of each device to respective RFUs on day 1. 600 µm microtumors had significantly higher activity on day 3 and 6 compared to 150 µm microtumors. Data are represented as mean ± SEM (n = 4; * p < 0.05, ** p < 0.01, one-way ANOVA comparing 150 vs. 600 at each day). (C) Cell cycle analysis was performed by flow cytometry of propidium iodide-stained single cell suspension of microtumors harvested on day 1, 3, and 6. Twenty thousand cells were collected per sample after removal of debris and doublets. Percentage of cells in each phase was calculated using FlowJo software. Table shows percentage of cells in each cell cycle phase (Sub G0/G1, G0/G1, S, G2/M) in 150 µm and 600 µm microtumors harvested on day 1, 3 and 6. Data are represented as mean ± SEM (n = 3). (D) Large microtumors show significant increase in Sub G0/G1 phase and decrease in G0/G1 phase with no differences in S and G2/M phase compared to small microtumors and 2D. Data are represented as mean ± SEM (n = 3; ** p < 0.01, *** p

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