BACKGROUND: The coordinated transcriptional regulation of activated T-cells is based on a complex dynamic behavior of signaling networks. Given an external stimulus, T-cell gene expression is characterized by impulse and sustained patterns over the course. Here, we analyze the temporal pattern of activation across different T-cell populations to develop consensus gene signatures for T-cell activation. RESULTS: Here, we identify and verify general biomarker signatures robustly evaluating T-cell activation in a time-resolved manner. We identify time-resolved gene expression profiles comprising 521 genes of up to 10 disjunct time points during activation and different polarization conditions. The gene signatures include central transcriptional regulators of T-cell activation, representing successive waves as well as sustained patterns of induction. They cover sustained repressed, intermediate, and late response expression rates across multiple T-cell populations, thus defining consensus biomarker signatures for T-cell activation. In addition, intermediate and late response activation signatures in CAR T-cell infusion products are correlated to immune effector cell-associated neurotoxicity syndrome. CONCLUSION: This study is the first to describe temporally resolved gene expression patterns across T-cell populations. These biomarker signatures are a valuable source, e.g., monitoring transcriptional changes during T-cell activation with a reasonable number of genes, annotating T-cell states in single-cell transcriptome studies, or assessing dysregulated functions of human T-cell immunity.
%0 Journal Article
%1 Rade2023-eh
%A Rade, Michael
%A Böhlen, Sebastian
%A Neuhaus, Vanessa
%A Löffler, Dennis
%A Blumert, Conny
%A Merz, Maximilian
%A Köhl, Ulrike
%A Dehmel, Susann
%A Sewald, Katherina
%A Reiche, Kristin
%D 2023
%J Genome Biol.
%K topic_lifescience Biomarkers; Gene Non-negative T-cell Temporal Time Transcriptome activation; expression; factorization; gene matrix profiles; series;
%N 1
%P 287
%T A time-resolved meta-analysis of consensus gene expression profiles during human T-cell activation
%V 24
%X BACKGROUND: The coordinated transcriptional regulation of activated T-cells is based on a complex dynamic behavior of signaling networks. Given an external stimulus, T-cell gene expression is characterized by impulse and sustained patterns over the course. Here, we analyze the temporal pattern of activation across different T-cell populations to develop consensus gene signatures for T-cell activation. RESULTS: Here, we identify and verify general biomarker signatures robustly evaluating T-cell activation in a time-resolved manner. We identify time-resolved gene expression profiles comprising 521 genes of up to 10 disjunct time points during activation and different polarization conditions. The gene signatures include central transcriptional regulators of T-cell activation, representing successive waves as well as sustained patterns of induction. They cover sustained repressed, intermediate, and late response expression rates across multiple T-cell populations, thus defining consensus biomarker signatures for T-cell activation. In addition, intermediate and late response activation signatures in CAR T-cell infusion products are correlated to immune effector cell-associated neurotoxicity syndrome. CONCLUSION: This study is the first to describe temporally resolved gene expression patterns across T-cell populations. These biomarker signatures are a valuable source, e.g., monitoring transcriptional changes during T-cell activation with a reasonable number of genes, annotating T-cell states in single-cell transcriptome studies, or assessing dysregulated functions of human T-cell immunity.
@article{Rade2023-eh,
abstract = {BACKGROUND: The coordinated transcriptional regulation of activated T-cells is based on a complex dynamic behavior of signaling networks. Given an external stimulus, T-cell gene expression is characterized by impulse and sustained patterns over the course. Here, we analyze the temporal pattern of activation across different T-cell populations to develop consensus gene signatures for T-cell activation. RESULTS: Here, we identify and verify general biomarker signatures robustly evaluating T-cell activation in a time-resolved manner. We identify time-resolved gene expression profiles comprising 521 genes of up to 10 disjunct time points during activation and different polarization conditions. The gene signatures include central transcriptional regulators of T-cell activation, representing successive waves as well as sustained patterns of induction. They cover sustained repressed, intermediate, and late response expression rates across multiple T-cell populations, thus defining consensus biomarker signatures for T-cell activation. In addition, intermediate and late response activation signatures in CAR T-cell infusion products are correlated to immune effector cell-associated neurotoxicity syndrome. CONCLUSION: This study is the first to describe temporally resolved gene expression patterns across T-cell populations. These biomarker signatures are a valuable source, e.g., monitoring transcriptional changes during T-cell activation with a reasonable number of genes, annotating T-cell states in single-cell transcriptome studies, or assessing dysregulated functions of human T-cell immunity.},
added-at = {2024-09-10T10:41:24.000+0200},
author = {Rade, Michael and B{\"o}hlen, Sebastian and Neuhaus, Vanessa and L{\"o}ffler, Dennis and Blumert, Conny and Merz, Maximilian and K{\"o}hl, Ulrike and Dehmel, Susann and Sewald, Katherina and Reiche, Kristin},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2beabd77371074101f3215f13072cd719/scadsfct},
interhash = {00e452d4dfdc1f585a3aea0f741b25dd},
intrahash = {beabd77371074101f3215f13072cd719},
journal = {Genome Biol.},
keywords = {topic_lifescience Biomarkers; Gene Non-negative T-cell Temporal Time Transcriptome activation; expression; factorization; gene matrix profiles; series;},
language = {en},
month = dec,
number = 1,
pages = 287,
timestamp = {2024-11-22T15:48:26.000+0100},
title = {A time-resolved meta-analysis of consensus gene expression profiles during human T-cell activation},
volume = 24,
year = 2023
}