CYTO 2019 Workshop: Assuring Rigor and Reproducibility for use of Mass Cytometry in Clinical Research
The addition of mass cytometry to the pool of technologies in clinical studies requires more standardization and quality control. Discussion on the use of CyTOF assays for clinical research including panel design and validation, reagents and protocols for sample processing, instrument operation, quality control, regulatory oversight and data analysis is needed. We hope to bring together experts in the field at CYTO 2019 to learn from their experiences and discuss how best to overcome these challenges.
1. Are you currently using Mass Cytometry? More than one response can be selected.
No
Yes, for clinical trials
Yes, for research studies
2. If you are currently NOT using Mass Cytometry, what is preventing you from using this technology? More than one response can be selected.
Not interested
Using other single cell platforms
Lack of available instruments/reagents
Lack of knowledge/expertise with the technology
Challenges associated with required infrastructure
High cost
Afraid of the workflow/analysis complexity
Doubts about reproducibility/scalability
Takes too long to generate results
Other:
3. What type of clinical studies/research do you use Mass Cytometry for? More than one response can be selected.
Pre-clinical studies
Clinical trials
As a diagnostic tool
For treatment follow-up
Monitor disease progression
Small pilot studies
New target/biomarker discovery
Other:
4. Which area(s) in the CyTOF workflow do you struggle with? More than one response can be selected.
Experimental design
Reagent availability
Protocol optimization
Panel design
Panel validation
Instrumentation use
Sample processing
Maintaining quality control
Data analysis
5a. Regarding experimental design, what are the main challenges you have encountered? More than one response can be selected.
Scalability of CyTOF
Lack of statistical/power calculation support
Limited sample size
Complexity of longitudinal studies
Complexity of multi-site studies
Unclear outcomes, confounding factors, or too many patient subgroups
Lack of training/ guidance for troubleshooting
5b. How have you attempted to solve these main challenges?
Your answer
6a. Regarding reagent availability, what are the main challenges you have encountered? More than one response can be selected
Conjugation validation
Antibody staining resolution
Staining variation between lots/conjugations
Metal contamination
Few antibodies/clones/ metal available
Variation in barcoding kits
Limited number of reagent suppliers
Reagent back orders
6b. How have you attempted to solve these main challenges?
Your answer
7a. Regarding protocol optimization, what are the main challenges you have encountered? More than one response can be selected.
Issues with the sample collection protocol
Issues with sample storage protocol before or after staining
Issues with staining protocol
Issues with barcoding
Issues with environmental contaminants
Issues with sample clumping
Lack of automation and robotics
Lack of available training/guidance documents on protocol optimization
7b. How have you attempted to solve these main challenges?
Your answer
8a. Regarding panel design and validation, what are the main challenges you have encountered? More than one response can be selected.
Availability of tools/support to design a new panel
Adding/validating a new target
Tailoring a panel for a new sample type
Selecting appropriate positive/negative controls for rare cell subtypes
Differences in signal intensity between positive controls and patient samples
Clinically relevant markers below the limit of detection
Guidance for QC’ing the panel
Issues with antibody titration
Validation of custom-made reagents
Lack of available training/guidance on panel design and validation
8b. How have you attempted to solve these main challenges?
Your answer
9a. Regarding sample processing, what are the main challenges you have encountered? More than one response can be selected.
High level of cellular debris
Sample over-concentrated (too many cells)
Metal contamination
Cell clumping
Batch to batch variability
Low barcoding efficiency
Low cell recovery/viability
Processing samples from multiple study sites
Lack of automation and robotics
Lack of available training/guidance on sample processing
9b How have you attempted to solve these main issues?
Your answer
10a. Regarding instrumentation, what are the main challenges you have encountered? More than one response can be selected.
Instrument sensitivity
Bead normalization performance
Issues with super sampler
Issues with sample acquisition
Issues with machine cleaning
Issues with sample carry-over
Issues with speed of sample acquisition
Variation in sensitivity between different tuning procedures
Variation in sensitivity between different instruments
Variation between different operators
Lack of automation and robotics
Lack of training/guidance on instrument use
10b. How have you attempted to solve these main challenges?
Your answer
11a. Regarding quality control, what are the main challenges you have encountered? More than one response can be selected.
Batch effects
Lack of metal-specific QC beads
Lack of controls for instrument performance
Lack of measures of reproducibility
Lack of standards for QA/QC oversight
Lack of guidelines/consensus on QC processes
Lack of training on quality control methods
Lack of guidance for troubleshooting quality control related issues
11b. How have you attempted to solve these main challenges?
Your answer
12. Regarding software/data analysis and statistical evaluation, what are the main challenges you have encountered? More than one response can be selected.
Analysis algorithm complexity
Analysis algorithm availability
Batch analysis
Need for compensation
Lack of a bioinformatics support
Lack of understanding of the proper use of algorithms
Can’t keep up with new publications/methods/tools
Lack of agreement on clean-up gating protocol
Lack of reproducibility
12b. How have you attempted to solve these main challenges?
Your answer
13. Regarding industry regulation, what are the main challenges you have encountered? More than one response can be selected.
Lack of consensus in the field for sample processing and analysis
Lack of consensus in the field for instrument quality control
Lack of best practices for sample processing and analysis, and instrument quality control
14. How do you typically account for batch effects with CyTOF data?
Batch effects are not monitored
EQ beads and the normalizers by Fluidigm or Nolan lab
A healthy donor sample to visually inspect the staining and identify batch effects but don’t correct for it
Min/max scaling
Z-core normalization
In-house scaling method
Normalization using a biological control run as a separate sample
Normalization using a biological control spiked in the actual sample
Clear selection
15. What platform do you use for CyTOF data analysis?
FlowJo
FCS express
Cytobank
Gemstone
An adapted R-based pipeline
An in-house built R-based pipeline
Other:
Clear selection
16. Do you think CyTOF is mature enough to be used in clinical trials?
Yes
No
Clear selection
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