% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{MurciaPienkowski:305606,
author = {V. Murcia Pienkowski and T. Boschert$^*$ and P. Skoczylas
and A. Sanecka-Duin and M. Jasiński and B. Król-Józaga
and G. Mazzocco and S. Stachura and L. Bunse$^*$ and J.
Kaczmarczyk and E. Green$^*$ and A. Blum},
title = {{C}omputational identification of cross-reactive {TCR}
epitopes with {ARD}itox.},
journal = {Journal of cancer research and clinical oncology},
volume = {151},
number = {12},
issn = {0301-1585},
address = {Heidelberg},
publisher = {Springer},
reportid = {DKFZ-2025-02256},
pages = {311},
year = {2025},
note = {#LA:D170#},
abstract = {Cellular immunotherapies, such as those utilizing T
lymphocytes expressing native or engineered T cell receptors
(TCRs), have demonstrated therapeutic efficacy. However,
some engineered high-affinity TCRs have caused fatal
off-target immunotoxicity due to targeting epitopes later
found to be expressed by both tumor cells and healthy
tissues. Unfortunately, TCRs can be cross-reactive to
epitopes with highly distinct sequences, making prediction
difficult, and the exquisite sequence specificity of TCRs
means that safety studies in mice miss human-specific
epitopes.To address this issue, we developed ARDitox, a
novel in silico method based on computational immunology and
artificial intelligence (AI) for predicting and analyzing
potential TCR off-target toxicities. We tested the
performance of ARDitox on four TCRs reported to target
tumor-associated antigens, two of which are known to cause
clinical immunotoxicity (MAGEA3112-120 and MAGEA3168-176
epitopes), one of which has experimentally identified
off-target antigens (AFP158-166 epitope), and the last one
for which no cross-reactive epitopes are known
(NY-ESO-1157-165).ARDitox confirmed the previously
identified immunotoxic epitopes. We then expanded our
analyses to a novel TCR targeting the tumor-associated
antigen NLGN4X, frequently upregulated in gliomas. For this
target, ARDitox identified a cross-reactive peptide that
would not have been found using mouse models, highlighting
the value of our computational approach.Our findings
underscore the value of the ARDitox in silico method for the
early and reliable identification of off-target epitopes for
further preclinical evaluation. This platform strongly
supports the development of safer TCR-mediated
immunotherapies.},
keywords = {Humans / Epitopes, T-Lymphocyte: immunology / Cross
Reactions: immunology / Receptors, Antigen, T-Cell:
immunology / Computational Biology: methods / Antigens,
Neoplasm: immunology / Mice / Animals / Computer Simulation
/ Artificial Intelligence / T-Lymphocytes: immunology / 3R
(Other) / Cell therapy (Other) / Cross-reactivity (Other) /
Off-target toxicity (Other) / Safety (Other) / TCR (Other) /
Epitopes, T-Lymphocyte (NLM Chemicals) / Receptors, Antigen,
T-Cell (NLM Chemicals) / Antigens, Neoplasm (NLM Chemicals)},
cin = {D170 / HD01},
ddc = {610},
cid = {I:(DE-He78)D170-20160331 / I:(DE-He78)HD01-20160331},
pnm = {314 - Immunologie und Krebs (POF4-314)},
pid = {G:(DE-HGF)POF4-314},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:41175267},
doi = {10.1007/s00432-025-06330-7},
url = {https://inrepo02.dkfz.de/record/305606},
}