Open Access
Open access
volume 11 issue 1 publication number 3651

H3K9me3-mediated epigenetic regulation of senescence in mice predicts outcome of lymphoma patients

Kolja Schleich 1
Julia Kase 1
Jan R Dörr 1
Saskia Trescher 2
Animesh Bhattacharya 1
Yong Yu 3
Elizabeth M. Wailes 1
Dorothy N. Y. Fan 1, 4
Philipp Lohneis 5
Maja Milanovic 1
Andrea Lau 1
Dido Lenze 6
Michael Hummel 4, 6
Bjoern Chapuy 7
Ulf Leser 2
Maurice Reimann 1
Soyoung Lee 1, 3, 4
Clemens A. Schmitt 1, 3, 4, 8, 9
Publication typeJournal Article
Publication date2020-07-20
scimago Q1
wos Q1
SJR4.761
CiteScore23.4
Impact factor15.7
ISSN20411723
General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy
Abstract
Lesion-based targeting strategies underlie cancer precision medicine. However, biological principles – such as cellular senescence – remain difficult to implement in molecularly informed treatment decisions. Functional analyses in syngeneic mouse models and cross-species validation in patient datasets might uncover clinically relevant genetics of biological response programs. Here, we show that chemotherapy-exposed primary Eµ-myc transgenic lymphomas – with and without defined genetic lesions – recapitulate molecular signatures of patients with diffuse large B-cell lymphoma (DLBCL). Importantly, we interrogate the murine lymphoma capacity to senesce and its epigenetic control via the histone H3 lysine 9 (H3K9)-methyltransferase Suv(ar)39h1 and H3K9me3-active demethylases by loss- and gain-of-function genetics, and an unbiased clinical trial-like approach. A mouse-derived senescence-indicating gene signature, termed “SUVARness”, as well as high-level H3K9me3 lymphoma expression, predict favorable DLBCL patient outcome. Our data support the use of functional genetics in transgenic mouse models to incorporate basic biology knowledge into cancer precision medicine in the clinic. Therapy-induced senescence reflects a biological effector principle that is underrecognized in lesion-focused cancer precision medicine. Here the authors utilize mouse lymphoma genetics to functionally dissect senescence and cross-species apply a novel senescence-based prognosticator to lymphoma patients.
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GOST Copy
Schleich K. et al. H3K9me3-mediated epigenetic regulation of senescence in mice predicts outcome of lymphoma patients // Nature Communications. 2020. Vol. 11. No. 1. 3651
GOST all authors (up to 50) Copy
Schleich K., Kase J., Dörr J. R., Trescher S., Bhattacharya A., Yu Y., Wailes E. M., Fan D. N. Y., Lohneis P., Milanovic M., Lau A., Lenze D., Hummel M., Chapuy B., Leser U., Reimann M., Lee S., Schmitt C. A. H3K9me3-mediated epigenetic regulation of senescence in mice predicts outcome of lymphoma patients // Nature Communications. 2020. Vol. 11. No. 1. 3651
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1038/s41467-020-17467-z
UR - https://doi.org/10.1038/s41467-020-17467-z
TI - H3K9me3-mediated epigenetic regulation of senescence in mice predicts outcome of lymphoma patients
T2 - Nature Communications
AU - Schleich, Kolja
AU - Kase, Julia
AU - Dörr, Jan R
AU - Trescher, Saskia
AU - Bhattacharya, Animesh
AU - Yu, Yong
AU - Wailes, Elizabeth M.
AU - Fan, Dorothy N. Y.
AU - Lohneis, Philipp
AU - Milanovic, Maja
AU - Lau, Andrea
AU - Lenze, Dido
AU - Hummel, Michael
AU - Chapuy, Bjoern
AU - Leser, Ulf
AU - Reimann, Maurice
AU - Lee, Soyoung
AU - Schmitt, Clemens A.
PY - 2020
DA - 2020/07/20
PB - Springer Nature
IS - 1
VL - 11
PMID - 32686676
SN - 2041-1723
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2020_Schleich,
author = {Kolja Schleich and Julia Kase and Jan R Dörr and Saskia Trescher and Animesh Bhattacharya and Yong Yu and Elizabeth M. Wailes and Dorothy N. Y. Fan and Philipp Lohneis and Maja Milanovic and Andrea Lau and Dido Lenze and Michael Hummel and Bjoern Chapuy and Ulf Leser and Maurice Reimann and Soyoung Lee and Clemens A. Schmitt},
title = {H3K9me3-mediated epigenetic regulation of senescence in mice predicts outcome of lymphoma patients},
journal = {Nature Communications},
year = {2020},
volume = {11},
publisher = {Springer Nature},
month = {jul},
url = {https://doi.org/10.1038/s41467-020-17467-z},
number = {1},
pages = {3651},
doi = {10.1038/s41467-020-17467-z}
}