How could I set up my cutoff for positive cells for PDL-1 and CCR7 on small subset of dendritic cells .I use unstained negative control for every sample & I use healthy controls .But, I am very confused how to interpretate those results .I need help
If you only have those two markers in your panel, then unstained controls will be fine for setting gates. If you have additional markers, you will want to use FMOs (Fluorescence minus one) to help you set your gates.
FMO #1: Sample stained with all the markers in your panel except for PD-L1
FMO #2: Sample stained with all the markers in your panel except for CCR7
Use the unstained or FMO controls to set your gates. For example, using data from FMO #1 or unstained control, create a dot plot that is PD-L1 on x-axis vs FSC-A or another marker on the y-axis. All of the cells that you see here are negative for PD-L1. Draw a tight gate around all of these cells and these will be PD-L1-. Next, draw a gate around all of the white space to the right of these cells and label this gate PD-L1+.
Apply these gates to your fully stained samples. If you have PD-L1+ events, they will show up in the PD-L1+ gate that you drew on your control.
This data represents the % PD-L1+ events of the parent (are these gated on a specific cell type?). For example, it could represent the percent of monocytes expressing PD-L1, if monocytes are the parent gate. Use this data to compare how the monocytes might change their expression of PD-L1 across different conditions, time points, or individuals, etc.
Marissa Fahlberg Really thanks for this helpful answer ..If I have 2 other markers for cell identification..Should I use FMO on this case ?
The answer is a bit subjective, but I suggest doing the FMOs for any markers that are not distinctly separated (clear positive and negative populations depicted by two obvious clusters that are not touching at all). It will make drawing your gates crystal clear and you won't have to second-guess your data and results. It's also powerful when writing a manuscript or protocol to establish the validity and rigor of your data.
A couple of references for a deeper explanation and further reading (both are open access):
- Roederer M. Spectral compensation for flow cytometry: visualization artifacts, limitations, and caveats. Cytometry. 2001 PMID: 11746088.
- Baumgarth N, Roederer M. A practical approach to multicolor flow cytometry for immunophenotyping. J Immunol Methods. 2000 PMID: 10986408.
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