Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures
December 26th, 2016
Identifying novel drug targets that transition from pre-clinical testing to human trials is a scientific priority. To that end, here we describe a functional genomics approach for examining the impact of gene depletion on cancer cell line spheroids, which more appropriately model human cancers in vivo.
The goal of this siRNA screen protocol is to investigate the impact of gene silencing on cancer cell line spheroid growth. Compared to traditional two-dimensional cell culture techniques, cancer spheroids display conditions more similar to those encountered in tumors in vivo. This method is useful for the functional assessment of frequently altered genes in human cancers, and more importantly, it can be used to determine which genes are potential oncogenes or tumor suppressors under more complex culture conditions, such as that seen in three-dimensional culture, and in particular, under hypoxia.
The main advantage of this technique is that it's readily adaptable so that researchers can use it to study their particular genes of interest in their preferred cell lines. We believe that it builds on current targeted sRNA screening approaches. It's generally appreciated that targeted screens, rather than whole genome strains allow scientists to ask specific questions and generate more robust results.
We have analyzed the effect of gene silencing on spheroid viability and size, but you could also use biometric dyes for a different screen readout, such as apoptosis. Demonstrating the procedure is Patty Wai from our laboratory. Begin by defrosting 96-well plates containing the siRNA library at room temperature.
Then spin for five minutes at 1, 000 times g, using a bench-top centrifuge. Use a multichannel pipette to add 10 microliters of reduced serum medium containing the optimized transfection reagent to the wells of each plate. Incubate for 15 minutes to allow transfection complexes, containing siRNA, to form.
As with any screening pipeline, spheroid forming capacity of cell lines in transfection conditions should be robustly optimized prior to performing the full screen. Next, trypsinize the cells to be screened until they detach from the flask. Once the cells have detached, neutralize the trypsin with an appropriate volume of cell-line-specific medium, transfer to a centrifuge tube, and spin for five minutes at 1, 000 times g in a bench-top centrifuge to collect the cells.
Discard the supernatant, and resuspend the pellet to a single-cell suspension with an appropriate volume of medium. Perform a cell count using an automated cell counter. Then dilute the suspension to 5, 000 cells per 180 microliters with cold media.
Transfer the cell suspension to a reservoir. Using a multichannel pipette, set at 180 microliters, pipette to mix and transfer the cell suspension to the 96-well plate containing the siRNA. Centrifuge the plate at 1, 000 times g in a pre-cooled, 4 degrees Celsius centrifuge for 10 minute, and then incubate the plate in a 37 degrees Celsius tissue culture incubator.
At this point, the cells will appear as a mosaic in the bottom of the wells. After 24 hours, observe the cells under a microscope. At this point, the cells should be aggregated together to form a single spheroid in the center of the well.
Add 100 microliters of complete medium to each well to encourage growth before returning to the incubator. After three days of growth, gently remove 100 microliters of medium from each well, and add 100 microliters of fresh medium. On day seven, examine the spheroids under a microscope, and then proceed to quantify the spheroid size on a plate reader that can quantitatively monitor spheroid growth over time.
To quantify the spheroid size, first open the software on the computer. Select 96-well plate, select the appropriate plate type, and enter an experiment name. Then, insert the 96-well plate containing the spheroids into a bench-top, micro-well plate imaging cytometer.
Next, select the Tumorsphere application. Select image-based focus to alter the focus so that the spheroid is in focus and has optimal contrast. Select the wells that require scanning and start scan.
Next, ensure that the object mask accurately represents the spheroid size. For BT474 spheroids grown for seven days, adjust Precision to High, and set the minimum Colony Diameter to 200 microns. Use the Export function to export the data in the form of an annotated data file that will be analyzed to identify siRNAs with a statistically significant effect on spheroid area.
After imaging, remove 100 microliters of medium from each well, and add 100 microliters of luminescent viability dye to determine cell viability. After incubating the plates for 15 minutes, scan the plate using a luminescent plate reader. This protocol may also be adapted for use with other cancer cell lines.
The reverse transfection procedure of non-targeting controls did not significantly affect viability for any of the lines tested, whereas the transfection of Ubiquitin B, a positive cell-killing control, significantly decreased viability. BT474 cells were reverse transfected with the 200-gene Human siGENOME siRNA Library in triplicate. Spheroid area and viability was observed.
Significant outliers with a z-score greater than 1.7 were identified. SiRNAs that significantly increased or reduced spheroid area and viability are shaded in blue, and red depicts the control siRNAs. This set of micrographs shows representative images of BT474 spheroids seven days after reverse transfection with E-Cadherin, a non-targeting control, PIK3CA, ERBB2, or SF3B1 siRNA.
This histogram shows how treatment with each siRNA affected cell viability seven days after reverse transfection. Knockdown of ERBB2 and PIK3CA significantly reduced cell viability compared to controls. This image demonstrates that the spheroids can be successfully immunostained to reveal the impact of gene silencing on target proteins.
Once mastered, several hundred genes can be screened in multiple cell lines in one day, and this allows for the robust identification of potentially new genes important for survival in three-dimensional culture. After watching this video, you should have a good understanding of how to successfully culture cancer cell spheroids that are amenable to sRNA-mediated gene silencing. You will also be able to investigate the impact of gene silencing by performing immunohistochemistry on the spheroids.
This can offer valuable spacial information that may inform you of the underlying biology.
Overview
This article presents a functional genomics approach to identify potential drug targets by examining gene depletion effects on cancer cell line spheroids. These spheroids provide a more accurate model of human tumors in vivo compared to traditional 2D cultures.
Key Study Components
Area of Science
- Functional Genomics
- Cancer Biology
- Cell Culture Techniques
Background
- Gene silencing can reveal oncogenes and tumor suppressors.
- Cancer spheroids mimic the tumor microenvironment more closely than 2D cultures.
- Targeted siRNA screening allows for specific gene investigation.
- Hypoxic conditions can be studied using this method.
Purpose of Study
- To investigate the impact of gene silencing on cancer spheroid growth.
- To identify genes that may serve as novel drug targets.
- To enhance the understanding of gene function in a 3D culture environment.
Methods Used
- siRNA screening in cancer cell line spheroids.
- Optimization of transfection conditions for robust spheroid formation.
- Quantification of spheroid size and viability using imaging cytometry.
- Analysis of gene silencing effects on cell viability and growth.
Main Results
- Significant effects of specific siRNAs on spheroid viability and size were observed.
- Knockdown of ERBB2 and PIK3CA reduced cell viability compared to controls.
- Robust identification of genes important for survival in 3D culture was achieved.
- Adaptability of the method for various cancer cell lines was demonstrated.
Conclusions
- This approach allows for the screening of hundreds of genes in a single day.
- It provides a valuable tool for identifying potential therapeutic targets in cancer.
- The method enhances the understanding of gene function in a more physiologically relevant context.
Frequently Asked Questions
Executive Industry Relevance
Functional genomics screening in 3D cancer spheroid models enhances target validation by revealing gene dependencies under physiologically relevant conditions. This approach improves predictive confidence in identifying novel drug targets by capturing tumor microenvironment influences often missed in 2D cultures. The method supports early discovery decisions by linking gene silencing effects to spheroid growth and viability, enabling mechanistic de-risking of candidate targets.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Interrogates therapeutic hypotheses by assessing the impact of gene silencing on cancer spheroid growth and viability.
- Operational Value: Enables functional assessment of frequently altered genes in human cancers under complex culture conditions.
- Predictive Value: Identifies potential oncogenes or tumor suppressors that are critical for survival in 3D culture, supporting target prioritization.
Screening & Assay Development
- Scientific Value: Utilizes siRNA screening to generate quantitative readouts of spheroid area and viability for gene effect analysis.
- Operational Value: Requires optimization of transfection conditions and spheroid formation capacity to ensure robust and reproducible screening outcomes.
- Assay Readiness: Employs imaging cytometry and luminescent viability dyes to enable high-content, quantitative monitoring of spheroid growth over time.
Translational & Preclinical Research
- Translational Relevance: Confirms spatial impact of gene dependencies via immunohistochemistry, linking molecular findings to protein-level changes in spheroids.
- Preclinical Continuity: Demonstrates dependency on HER2 amplification and PIK3CA mutation in BT474 spheroids, validating known cancer drivers in a 3D model.
- Mechanistic De-risking: Provides spatial and functional validation of gene effects, reducing ambiguity in target mechanism before downstream investment.
Pipeline & Workflow Integration
The method integrates into the discovery continuum from target identification through lead optimization, particularly for targets requiring validation in complex, hypoxia-prone tumor models.
- Discovery Biology: Supports hypothesis testing and pathway clarification by linking gene knockdown to spheroid viability and size changes.
- Screening: Enables assay standardization through reverse transfection protocols and standardized spheroid formation in 96-well formats.
- Analytics: Generates quantitative spheroid area and viability data via imaging cytometry and luminescent readouts, enabling statistical identification of significant hits (e.g., z-score >1.7).
- Translational Research: Connects gene silencing effects to spatial protein expression via immunohistochemistry, enhancing biomarker alignment and mechanistic insight.
- Enterprise Reuse: Adaptable across cancer cell lines and siRNA libraries, positioning it as a reusable platform for target validation campaigns.
Operational & Enterprise Impact
- Scientific Value: Increases target validation confidence by revealing gene dependencies in a tumor-relevant 3D context.
- Operational Value: Promotes reproducibility through standardized spheroid formation, transfection optimization, and quantitative imaging workflows.
- Strategic Value: Improves go/no-go decisions by reducing false positives from 2D models and increasing confidence in target essentiality.
- Portfolio Impact: Enables risk-adjusted prioritization of targets based on functional evidence from physiologically relevant models.
Implementation Considerations
- Requires expertise in cell culture, transfection techniques, and 3D model handling to ensure robust spheroid formation.
- Dependent on access to imaging cytometry and luminescent plate readers for quantitative spheroid size and viability assessment.
- Necessitates optimization of transfection conditions and cell density (5,000 cells/180 µL) for consistent spheroid formation across wells.
- Requires adaptation considerations when extending to other cancer cell lines or hypoxia-modulated conditions.
- Practical limitation: Screening throughput depends on siRNA library size and imaging capacity, though hundreds of genes can be screened per day once optimized.
