SP1 - SeneSys

Utilization of systems-medicine-derived „Profile/State-Fate (P/SF)“ cluster models as biomarkers of response, denominator of treatment choices, and as novel targeting principles

The overarching role of SP1 in this consortium is the systems-medicine-based generation and validation of static/dynamic "Profile/State-Fate (P/SF)" cluster models as predictors, stratifiers, and novel targeting principles. The specific contribution of SP1 is to provide numerous transcriptome datasets from human and murine models of oncogene- and therapy-induced senescence (OIS, TIS) that can be evaluated regarding various aspects of cellular senescence – i.e. the global arrest state on one hand and selective functionalities such as the senescence-associated secretory phenotype (SASP) or stemness reprogramming. Subsequent to bioinformatic modeling-governed determination of novel P/SF cluster models via clinically and molecularly co-annotated datasets (prior to or under standard chemo[immune]therapy) of human diffuse large B-cell lymphoma (DLBCL) and murine Eµ-myc transgenic lymphoma, additional lymphoma profiles will be assigned to distinct P/SF clusters to assess their predictive role.
Next step is the identification of novel status-based target principles and the derivation of P/SF cluster model-specific therapy strategies in collaboration with SP2 and SP5, as well as their exploration them in adequate human and murine test systems. We will also compare the predictive power and therapeutic relevance of these P/SF cluster models in subgroups of differently treated DLBCL patient cohorts (e.g. R-CHOP vs. ImbruVeRCHOP study patients) which were assigned to the very same P/SF cluster models. As a perspective, the predictive power of P/SF cluster models or their modeling algorithms will also be tested in non-lymphoma contexts (i.e. other malignancies and non-malignant diseases such as neurodegenerative diseases).

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