916 Utilizing spectral flow cytometry for deep memory phenotyping of tumor infiltrating lymphocyte products

Background

It has been well established that the memory phenotype of post-expansion tumor infiltrating lymphocyte (TIL) products is associated with the durable, complete response rate to adoptive cell transfer. This is because different T-cell subsets have varying abilities to persist, proliferate and lyse tumor cells upon infusion. Spectral cytometry is revolutionizing the way T-cell products are being analyzed; however, there are many panels being run which have not been fully optimized making reproducibility problematic.

Methods

We utilized a 5-laser Cytek Aurora spectral flow cytometer to perform a 19-color panel focused specifically on the memory phenotypes of T-cells. We analyzed post-expansion TIL products from melanoma, renal cell carcinoma, non-small cell lung cancer and squamous cell carcinoma which were expanding using both the PreREP/REP protocol and an anti-CD3/CD28 bead-based expansion method. Both traditional gating and t-distributed stochastic neighbor embedding (tSNE) was performed using FlowJo V10.9.0.

Results

Successful optimization of a 19-color T-cell specific panel was achieved. Utilizing tSNE, we were able to visualize significant differences in the memory phenotypes of TIL products which expanded from the various tumor types and expansion methods. Unique subsets of CD8+/CD62L+/CCR7- T-cells are of particular interest which would be missed utilizing traditional gating alone on naïve, stem-cell like memory, central memory, tissue-resident memory, effector-memory, and effector populations.

Conclusions

Spectral cytometry is a powerful tool allowing for the deep T-cell phenotyping of TIL products. Analysis of these high-dimensional data sets, via tSNE, is a promising way to discover novel T-cell subsets that may otherwise be overlooked. However, caution should be taken when optimizing these panels, specifically when attempting to stain a large number of antigens on a single-cell type. This approach could be applied to clinical grade TIL products in the future to determine if there is a correlation between unique phenotypes and response to therapy.

Acknowledgements

We acknowledge the Moffitt Cancer Center Flow Cytometry Core Facility staff for their assistance with instrument maintenance.

Ethics Approval

Samples were collected in a de-identified manner under the following Moffitt Cancer Center approved IRB approved protocols: MCC20559, MCC22065 and MCC14690.

Consent

Written informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.