citations

                    Prediction of tumor-reactive T cell receptors from scRNA-seq data for personalized T cell therapy
                

Authors:

C L Tan , K Lindner, T Boschert , Z Meng , A Rodriguez Ehrenfried , A De Roia , G Haltenhof , A Faenza , F Imperatore, L Bunse , J M Lindner , R P Harbottle , M Ratliff , R Offringa, I Poschke , M Platten , E W Green

In:

Source: Nature
Publication Date: (2024)
Issue: :

Research Area:

Cancer Research/Cell Biology

Immunotherapy / Hematology

Cells used in publication:

T cell, human stim.: Species: human; Tissue Origin: blood
PBMC, human: Species: human; Tissue Origin: blood

Culture Media:

X-VIVO

Platform:

4D-Nucleofector® X-Unit

Experiment

The rapid expansion protocol was used to expand T cells. PBMCs from three independent donors were irradiated at 40?Gy using a Gammacell 1000 (AECL) irradiation device to serve as feeder cells. Then, 1?×?107 cells from each donor were pooled together, cells were spun down (400g, 10?min, room temperature) and resuspended in rapid expansion protocol media (X-Vivo15 (Lonza, BE02-060Q), 2% human AB serum (H4522-100ML, Sigma-Aldrich), 2.5?µg?ml-1 Fungizone (15290-018, Gibco), 20?µg?ml-1 gentamicin (2475.1, Roth), 100?IU?ml-1 penicillin and 100?µg?ml-1 streptomycin (15140122, Life Technologies))...

CR reactivity screening via flow cytometry

TCR-encoding RNA was electroporated into expanded healthy donor PBMCs using the Lonza 4D-Nucleofector (program EO-115, solution P3 supplemented according to the manufacturer’s recommendations), which were plated into 48-well plates containing TexMACS media (130-097-196, Miltenyi) supplemented with 2% human AB serum...

TCR reactivity screening via xCELLigence real-time killing assays

Primary human CD3+ cells were isolated from healthy donor volunteers using the Pan T cell isolation kit from Miltenyi Biotec according to the manufacturer’s instructions. The isolated T cells were then activated for 3?days using the human T Cell TransAct kit (Miltenyi Biotec) according to the manufacturer’s instructions and cultured in TexMACS medium from Miltenyi Biotec supplemented with IL-7 and IL-15, both at a final concentration of 10?ng?ml-1, at a concentration of 1?×?106?cells?ml-1. 3 days post activation 2?×?106 cells were washed and resuspended in 20?µl of primary P3 solution (Lonza), mixed with 2?µg of S/MAR DNA nanovectors and pulsed with the FI-115 pulsing code using the Lonza 4D-Nucleofector.

Abstract

The identification of patient-derived, tumor-reactive T cell receptors (TCRs) as a basis for personalized transgenic T cell therapies remains a time- and cost-intensive endeavor. Current approaches to identify tumor-reactive TCRs analyze tumor mutations to predict T cell activating (neo)antigens and use these to either enrich tumor infiltrating lymphocyte (TIL) cultures or validate individual TCRs for transgenic autologous therapies. Here we combined high-throughput TCR cloning and reactivity validation to train predicTCR, a machine learning classifier that identifies individual tumor-reactive TILs in an antigen-agnostic manner based on single-TIL RNA sequencing. PredicTCR identifies tumor-reactive TCRs in TILs from diverse cancers better than previous gene set enrichment-based approaches, increasing specificity and sensitivity (geometric mean) from 0.38 to 0.74. By predicting tumor-reactive TCRs in a matter of days, TCR clonotypes can be prioritized to accelerate the manufacture of personalized T cell therapies.

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