The present protocol develops an image-based technique for rapid, non-destructive, and label-free regional cell density and viability measurement within 3D tumor aggregates. Findings revealed a cell-density gradient, with higher cell densities in core regions than outer layers in developing aggregates and predominantly peripheral cell death in HER2+ aggregates treated with Trastuzumab.
Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These relatively simple avascular constructs mimic key aspects of in vivo tumors, such as 3D structure and pathophysiological gradients. MCTSs models can provide insights into cancer cell behavior during spheroid development and in response to drugs; however, their requisite size drastically limits the tools used for non-destructive assessment. Optical Coherence Tomography structural imaging and Imaris 3D analysis software are explored for rapid, non-destructive, and label-free measurement of regional cell density within MCTSs. This approach is utilized to assess MCTSs over a 4-day maturation period and throughout an extended 5-day treatment with Trastuzumab, a clinically relevant anti-HER2 drug. Briefly, AU565 HER2+ breast cancer MCTSs were created via liquid overlay with or without the addition of Matrigel (a basement membrane matrix) to explore aggregates of different morphologies (thicker, disk-like 2.5D aggregates or flat 2D aggregates, respectively). Cell density within the outer region, transitional region, and inner core was characterized in matured MCTSs, revealing a cell-density gradient with higher cell densities in core regions compared to outer layers. The matrix addition redistributed cell density and enhanced this gradient, decreasing outer zone density and increasing cell compaction in the cores. Cell density was quantified following drug treatment (0 h, 24 h, 5 days) within progressively deeper 100 µm zones to assess potential regional differences in drug response. By the final timepoint, nearly all cell death appeared to be constrained to the outer 200 µm of each aggregate, while cells deeper in the aggregate appeared largely unaffected, illustrating regional differences in the drug response, possibly due to limitations in drug penetration. The current protocol provides a unique technique to non-destructively quantify regional cell density within dense cellular tissues and measure it longitudinally.
Researchers have largely turned to benchtop 3D culture in vitro systems to study some of the key features of tumor progression. Much of this research has been led by the re-emergence of multicellular tumor spheroids (MCTSs) and more complex organoids1,2. Although these models are avascular, they provide a powerful tool for recapitulating physiological and pathological processes that occur in vivo3,4,5. In particular, medium-sized models (300-500 µm diameter) can mimic key tumor features such as 3D structure, pathophysiological gradients, and metastatic signaling due to hypoxia within the core. It is well documented that these models display the characteristic concentric layers seen in vascularized in vivo tumors, namely, an outer layer of proliferative cells, a transitional layer of senescent/quiescent cells, and cells experiencing hypoxia in the core3,6,7,8,9. Unique insight can be gained from these models by characterizing cell behavior within these layers, during development and in response to the drug. However, the requisite MCTS size, necessary to develop the gradients that make them such powerful in vitro models, drastically limits the tools used for non-destructive assessment. Indeed, one of the biggest challenges with non-destructive analysis of MTCSs is quantifying cell-scale details. Bright-field and phase-contrast microscopy are routinely utilized to assess 3D MCTSs growth and development non-destructively. However, these modalities are limited to 2D projections, lacking the capacity to visualize the crucial 3D structure of these models10,11,12,13. Information on cytotoxicity and cell proliferation is typically collected through fluorescent imaging (i.e., light-sheet microscopy, confocal microscopy) or ex vivo immunohistological staining14,15,16. While these approaches provide valuable, high-resolution information on tissue structure, cellular density, and cellular function, they often require sample preparation such as optical clearing, fixing/staining, or embedding that prevents longitudinal analyses.
Optical Coherence Tomography (OCT) is a non-destructive structural imaging modality that has the potential to overcome some of the challenges mentioned above. It boasts cellular resolution and a sufficiently wide field of view (up to 10 mm x 10 mm) capable of visualizing entire multicellular aggregates17,18,19. Importantly, due to the visible nature of the light used, this technique is completely non-destructive and label-free17. Also, samples can be imaged in situ without requiring sample preparation, such that samples can be taken straight from the incubator, quickly scanned with OCT (scan duration ~5-10 min), then returned to the incubator, enabling longitudinal characterization. Many studies seeking to use OCT to analyze tumor spheroid behavior have recently emerged. In one of the most exciting demonstrations, Huang et al. used OCT to non-destructively detect necrotic cores within large tumor spheroid models, noting that live and dead cell regions possess discernible differences in optical attenuation, which may be utilized for label-free viability monitoring20. Similarly, Hari et al. conducted refractive index (RI) measurements of human colon cancer (HCT116) spheroids imaged with OCT to study the presence of hypoxia within the samples21. Their measurements were not sufficient for direct inferences, though they did observe lower RI in locations that correlated with the site, though not size, of necrotic cores, later identified via confocal microscopy. Abd El-Sadek et al. used OCT to visualize and quantify regional tissue viability of breast cancer tumor models22. They reported two OCT-based methods for visualizing tissue dynamics and showed a moderate correlation between differences in these metrics and microscopy-identified regions of live/dead cells.
Our published work using OCT built upon this prior literature to establish a quantitative, non-destructive approach to measure the 3D morphology and cell count within MCTSs breast cancer models during development10,23. Using Imaris 3D rendering image analysis software to count the number of cell-sized objects (i.e., spots) imaged within the OCT volume scans, the cell counts were non-destructively measured in MCTSs that were statistically similar to those determined via hemocytometer upon aggregate dissociation. However, due to the structural nature of OCT, cell membranes still present after cell death by necrosis may be erroneously counted as live cells. Furthermore, this characterization was extended to non-destructively track cell viability within individual aggregates subjected to a drug regimen with promising success10. Importantly, it was noted that similar cell viability was reported from our OCT-Imaris approach with what was benchmarked within these samples upon dissociation. This non-destructive and label-free cell approach enables cells to be counted within 3D constructs and dense aggregates longitudinally without sacrificing the construct/aggregate structure.
The present work reports an improved approach to directly quantify regional cell density within dense aggregates by leveraging the ability of OCT-Imaris to measure both 3D aggregate morphology and cell number. This methodological advancement provides a more detailed picture of cells' spatial distribution and proliferation within the characteristic concentric layers of MCTSs models. Rather than simply calculating an overall average aggregate cell density, such local density measurements can reveal cell density gradients, such as those associated with compaction. This regional assessment is also applied to aggregates treated with a chemotherapeutic to assess regional drug response, as measured by changes in local cell density. This combination of OCT and advanced imaging analysis methods provide quantification of regional cell viability, which may be used to explore drug penetration based on which regions experience decreases in cell density. This is the first report to non-destructively quantify regional cell density and viability in response to the drug within dense cellular tissues and measure it longitudinally. Such characterization of three-dimensional cell density and spatial distribution throughout entire MCTSs may help optimize drug delivery in cancer treatment and improve the understanding of cancer model progression.
AU565 (HER2+) and MDA-MB-231 breast cancer cell lines were used for the present study (see Table of Materials).
1. Preparing tumor aggregates
2. Administration of Trastuzumab (TZM) to AU565 cell aggregates
3. Optical Coherence Tomography imaging
NOTE: Samples herein were imaged with Optical Coherence Tomography (OCT) during each day of maturation (1-4), and then again on day 5 (24 h post-drug-addition) and day 9 (120 h post-drug-addition) for selected drugged aggregates. A commercial Spectral-Domain Optical Coherence Tomography (SDOCT, see Table of Materials) system for OCT imaging was used for the current study. Although this approach is amenable to almost any OCT system, and the procedure followed will be generally similar between different systems, some of the detailed steps that follow are specific to the present equipment.
4. Image analysis
Figure 1: Schematic illustration. (A) The concentric layer (shells) approach for assessing regional cell density in spherical aggregates. (B) The regional plug method was developed to evaluate local cell density in non-spherical aggregates, where small (100 µm diameter) spherical plugs (shown in yellow) are used as density indicators at each zone/thickness. (C) The spatially-refined regional plug method is employed for drug penetration studies. Please click here to view a larger version of this figure.
In a prior publication, a method was established for the non-destructive measurement of global cell density within cellular aggregates using OCT10. Herein, this technique is extended to assess the regional cell density of developing cell aggregates. Figure 1 shows a schematic of this extension, where cell density can be evaluated in concentric layers of a spheroid or more locally by looking instead at small (100 µm diameter) spherical plugs, denoted by the yellow circles in Figure 1B,C. MDA-MB-231 tumor spheroids were assessed initially by setting a center point within the aggregate and counting the number of objects/cells in sequential concentric layers of the spheroid. These results are presented in Figure 2. Student's t-testing revealed significantly higher cell density in the spheroid core than in the transitional (p = 4.3e-4) and outer layers (p = 4.0e-6). This result indicates compaction in the spheroid core after 4 days.
Figure 2: Differences in regional density calculated by concentric layer approach for spherical MDA-MB-231 aggregates. The figure illustrates a radial cell-density gradient with cells (n = 3) most densely packed in the aggregate core, and the local cell density decreasing with distance from the core. The average total cell count is shown with a blue line. The scale bar for the inset image is 100 µm. Data shown as mean ± SD (*= p < 0.05, ***= p < 0.001). Please click here to view a larger version of this figure.
However, a limitation of this concentric layer technique is that it can only be used on spherical aggregates. Thus, the cell counting approach was adapted to establish a Regional Plug method, which samples small zones at sequential locations through the aggregate, akin to a virtual biopsy. These plugs provide measurements of the local cell density at specific depths. This technique was validated against the concentric layer approach by performing analyses on the same MDA-MB-231 spheroids (Figure 3). Results showed good agreement between the regional plug and concentric layer approaches for these spherical aggregates. Student's t-tests revealed no statistical differences between the approaches for measuring the outer and transitional layers (p = 0.243 and 0.484, respectively) and a slight but significant difference when calculating the densities at the aggregate core (p = 0.017).
Figure 3: Concentric zone and regional plug approaches deliver similar results for quantifying cell density in spherical MDA-MB-231 aggregates (n = 3). Data shown as mean ± SD (* = p < 0.05). Please click here to view a larger version of this figure.
This technique was then applied to assess both spherical and non-spherical tumor aggregates on Day 4 of maturity (Figure 4), observing a similar trend toward core compaction for all morphologies tested, irrespective of cell type. This trend was most prominent in the samples prepared with Matrigel (the basement membrane matrix), an additive known to promote aggregation yet whose exogenous factors and composition are poorly characterized31,32,33. Interestingly, the addition of the matrix does not appear to affect the volume or cell count and thus seems to have negligible influence on cell proliferation. Rather, the matrix addition appears to redistribute cell density, promoting significant core compaction and decreasing cell density in the outer layers. These results also indicate that AU565 cells appear less sensitive to matrix-mediated aggregation effects than MDA-MB-231 cells. These findings provide valuable insight into the physical mechanisms by which the matrix enables cell aggregation in different breast cancer cell lines. Importantly, the regional plug approach should suit any MCTSs displaying spherical or non-spherical aggregate geometries.
Figure 4: Matrix addition promotes more aggregation and redistributes cell density in cancer cell lines. For both MDA-MB-231 (A,B) and AU565 (C,D) cell lines, matrix addition decreases density in the outer zone and increases compaction in the center (n = 3) without appreciably changing the overall cell count. Average total cell counts are shown with blue lines. Inset scale bars = 100 µm. Data shown as mean ± SD (*= p < 0.05, **= p < 0.01, ***= p < 0.001). Please click here to view a larger version of this figure.
Next, this regional plug approach was used to track cell death in TZM-treated tumor aggregates non-destructively. AU565 MCTSs prepared with the membrane matrix were treated with TZM on Day 4 of development, and cultured through day 9, with key OCT imaging timepoints at 0 h (pre-drug), 24 h, and 120 h (5 days). The spatially-defined regional plug method was applied at each timepoint, with plugs set every 100 µm throughout the entire thickness of each aggregate, as shown by the yellow circles in Figure 1C. The size of the center plug was held constant while the outer plug was allowed to fluctuate in diameter, corresponding to changing aggregate size. Minor fluctuations in cell density were observed over time within the inner 500 µm of each aggregate, indicating minimal cell death (Figure 5). Indeed, most cell deaths occurred in the outer 200 µm of each aggregate, particularly in the outermost 100 µm, which disappeared completely by the 120 h time point for all aggregates analyzed. The visualization of cell death as indicative drug response mostly in the outer layers of MCTSs is consistent with drug penetration issues of TZM, a clinically relevant antibody drug with a molecular weight of 145 kDa34. Indeed, the drug relies on passive diffusion through these dense cellular models, which is expected to challenge its ability to penetrate deeper than 200 µm into the models.
Figure 5: Cell viability in response to the drug, measured throughout the aggregate thickness. The plug at the inner core was kept constant at 100 µm diameter, while that in the outer zone was allowed to fluctuate with changing aggregate size. (A) Regional cell density in response to TZM addition revealed that cell death was largely constrained to the outer 200 µm, particularly the outer 100 µm, which disappeared completely after 120 h of treatment. The inner 500 µm thickness of the aggregates observed little change in cell count (n = 3). Average total cell counts are shown with corresponding colored lines for each timepoint. Data are shown as average ± SD. (B) Heat-map plot representing the change in the average cell density in response to the drug as a function of the aggregate thickness. Please click here to view a larger version of this figure.
Significance
Multicellular tumor spheroids (MCTSs) are powerful 3D in vitro models for studying tumor progression and drug screening1,2,3. Advancing the utility of these relatively simple aggregate models relies heavily on the characterization of their key features, such as morphology and cell density, which are known to influence both tumor model progression and therapeutic response. However, their requisite size introduces challenges in evaluating these characteristics, particularly for non-destructive analyses. The presented method provides a new tool for longitudinal and label-free quantification of cell density and viability within discrete regions of dense 3D aggregate models. The same aggregate can be re-imaged with Optical Coherence Tomography (OCT) over multiple development days. These volumetric scans can be analyzed to characterize how cell density evolves regionally during MCTSs maturation. These same principles apply to the analysis of drugged aggregates, which can be imaged longitudinally throughout a given drug regimen to determine where cell density is decreasing, i.e., where the drug may be actively killing cells. This approach significantly improves over prior methods for obtaining similar cell-scale information, which traditionally requires fixation, staining and/or sectioning, thus precluding longitudinal analyses. Indeed, this tool has the potential to dramatically reduce the number of samples needed for a given study as the same samples can be analyzed consecutively. This is also expected to introduce added value at each time point as developments can be tracked within a single aggregate as it responds to a given stimulus, rather than relying on correlated data from age-matched terminal samples. Beyond this MCTS application demonstrated herein, this OCT-Imaris method can study other cellular aggregates, embryoid bodies, more complex organoids, or tissue samples up to a few millimeters thick. This protocol will improve the understanding of cell compaction during aggregate development and drug response within dense aggregate models.
Modifications
The presented protocol was optimized for analysis of MDA-MB-231 and AU565 MCTSS models. Models made using other cell lines are applicable; however, some protocol optimization may be required due to changes in average cell size and aggregate morphology. A separate study was performed in which MDA-MB-231 and AU565 cells were plated in 2D and obtained an average cell size via microscopy. This diameter was utilized as the XY diameter within the Imaris "spots" function such that objects of this approximate size were counted. Changing this value changes the number of objects located within the sample10, and more accurate results are expected when this input closely matches cell size. Thus, a suitable XY diameter must be informed by the average cell size for the used cell type.
Critical steps and troubleshooting
One of the critical steps during OCT imaging is the selection of scan resolution. The pixel size set by the user must be sufficiently small such that multiple pixels are needed to comprise the average size of the cell type being used. This improves the accuracy of the "spots" analysis within Imaris by improving OCT's resolution of the cells and reducing the possibility that stochastic pixel noise will negatively affect cell counting.
Isolation of the sample within the Imaris reference frame greatly influences the output values for cell density. As the user performs this step, it is accompanied by a level of subjectivity and bias that must be applied consistently across all sample analyses. When isolating the sample within the volume scan to begin Imaris analysis, care must be taken to trace aggregate outlines accurately and avoid the inclusion of artifacts (i.e., reflections from substrates or media height).
Proper placement of reference frames during regional plug analysis is another critical step. As stated in the introduction, the three critical zones to analyze during model development are the proliferative outer region, the transitional region consisting of senescent/quiescent cells, and the hypoxic core. The placement of reference frames within the center of each layer is expected to yield the most accurate estimation of cell density within that region. This reference frame placement is of even greater importance for the detailed regional plug analyses used herein for the drug study, as evenly spaced zones must be established to analyze drug response more accurately.
Limitations and future research
The main limitation of the proposed method is the user-based slice-by-slice tracing performed within Imaris to isolate the aggregate within the OCT volume scan. This is a critical step for accurate results, which is somewhat subjective and, therefore, expected to impart some level of inter-user variability. To address this, we are currently seeking to incorporate an edge-detection algorithm performed within Matlab (or similar) prior to uploading the scan into Imaris. This algorithm should objectively identify sample edges in progressive B-scan slices, after which the proposed analyses can be performed on this pre-isolated sample region. Addressing this limitation will remove user-based variability and is expected to lead to wider applicability of this OCT-based tool.
The ability of OCT to accurately image live cells within aggregates during drug treatment is contingent on the mode of cell death on which the drug operates. The prior work revealed quantitative inaccuracies in the live cell count reported from OCT/Imaris in response to Doxorubicin, a well-known anti-cancer drug that kills cells via necrosis and apoptosis10. This is hypothesized to be due to the leftover cell membranes during necrosis, which are expected to appear as live cells during structural imaging. TZM is known to kill cells primarily via apoptosis35; thus, when cells die, they must break down into pieces sufficiently small to not be tracked/counted by OCT. Though further validation testing with an apoptotic drug is needed, our early pilot experiments show the excellent agreement of OCT/Imaris to dissociated cell counts in MCTSs drugged with TZM (unpublished data). Hence, the live cell results presented herein are anticipated to be more accurate than necrosis-inducing drugs. This distinction must be kept in mind when applying this approach for viability testing in drugged aggregates.
Future research in the non-destructive evaluation of tumor aggregates is expected to improve the understanding of how they develop and respond to both external stimuli and drug treatment. Development of analytical tools, such as the one presented herein, should expand the model utility and improve result accuracy, particularly within impactful applications such as drug screening and delivery/efficacy assessment.
The authors have nothing to disclose.
This study was supported by NIH R01 BRG CA207725 (MB/DTC) and NIH R01 CA233188 (MB). We would like to thank AMC Pharmacy for the Trastuzumab provided for these experiments.
96 well plates | Greiner Bio-One | 650970 | CellStar Cell-Repellent Surface, https://shop.gbo.com/en/usa/products/bioscience/cell-culture-products/cellstar-cell-repellent-surface/ |
0.25% trypsin, 2.21 mM EDTA | Corning | 25-053-CI | |
AU565 breast cancer cells | ATCC | ||
Dulbecco's Modified Eagle's Medium | Corning | 10-013-CV | |
Fetal Bovine Serum | ATCC | 30-2020 | |
FIJI software | open-source | (Fiji Is Just) ImageJ v2.1/1.5.3j | Downloaded from https://imagej.net/software/fiji/ |
Hemocytometer | Fisher Scientific | 0267151B | |
Imaris image analysis software | Bitplane | Current version 9.8 | |
L-glutamine | Lonza | 17-605E | |
Matrigel | Corning | 354263 | |
MDA-MB-231 breast cancer cells | ATCC | ||
Microscope | Zeiss | Z1 AxioVision | |
Penicilin streptomycin | Corning | 30-0002CI | |
Plate centrifuge | Eppendorf | ||
RPMI medium 1640 | Gibco | 11875-085 | |
Spectral Domain Optical Coherence Tomography | ThorLabs | TEL220C1 | |
T75 cell culture flasks | Greiner Bio-One | 658175 | |
Trastuzumab | Remnant clinical samples of Trastuzumab were used in this study, generously gifted by the Albany Medical College Pharmacy. |