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.

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?

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?

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?

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?

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?

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?

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?

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?

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

Clear selection

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