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.
Highlights
Lesion-based targeting strategies underlie cancer precision medicine
In the range of the progressing fraction of diffuse large B-cell lymphoma (DLBCL) patients treated with standard R-CHOP induction therapy, 35 of the 78 mice presented with re-growing lymph nodes (LN) during the 100-day observation period, while about half of the cohort remained relapse-free, and was considered cured, designated “never relapse [NR]” lymphomas (Fig. 1b, plateau of the green curve)
We established a transgenic lymphoma treatment platform that resembles some clinical results observed in DLBCL patient cohorts in response to CHOP-based therapies, ARTICLE
Summary
Lesion-based targeting strategies underlie cancer precision medicine. biological principles – such as cellular senescence – remain difficult to implement in molecularly informed treatment decisions. We utilized this model to investigate the impact of candidate genes or global effector programs, with particular interest in cellular senescence, on treatment outcome via reverse genetics[20,21,22,25,26,27,28] Stress response programs such as apoptosis and cellular senescence serve as important effector principles of anti-cancer therapy[29]. Dissecting TIS as a key contributor to long-term outcome, and, even more, anticipating the senescence response to a future therapy are difficult in primary patient material, underscoring the need for functional investigations in patient-predictive mouse models of cancer[35,36]. Our approach seeks to bioinformatically extract predictive signatures from outcome analyses in murine aggressive B-cell lymphoma models to inform precision medicine in DLBCL patients
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