METRICs

Despite the expanding interest in immunotherapy, only a minority of patients experience substantial benefits, highlighting the need for predictive biomarkers and combinatorial strategies. Combining immunotherapy with radiotherapy (RT) may be synergetic as RT may provoke immune response. However, several trials reported no or little benefit, indicating that further optimization and mechanistic insights are needed.
Both immunotherapy and RT are tightly linked to alterations of tumor metabolism. Within ERC ONco-Energetics_OFF, we profiled a wide panel of cancer cells according to wired metabolic profiles and metabolic flexibility reflected by differential capacity to adapt metabolism when challenged. Importantly, both traits correlated markedly with the response to immunotherapy.
Another important determinant is the gut microbiota. We performed gut microbiota metagenomic analyses and plasma metabolic analyses on stool and blood of cancer patients at different time-points after CAR T cell infusion, as well as tumor and bone marrow biopsies. A specific gut microbiota composition (abundance of Akkermansia muciniphila) and decrease in the indole metabolic pathway were observed in responding patients. Combined treatment with CAR T cells and Akkermansia spp supplementation improved tumor control in a mouse model of a high-grade B cell lymphoma. Additionally, the secretome of tumor biopsies from refractory patients showed higher concentrations of immune checkpoint proteins and higher expression of proteins implicated in myeloid cell homeostasis (PD-L1, Flt3L, and IL-4).
Based on our findings, we hypothesize that the cancer cell’s metabolic profile, metabolome landscape and gut microbiome may serve as predictive biomarkers of immunotherapy-RT combinations and offer caveats for further interventions. We hypothesize that RT may be optimized and exploited to render the myeloid compartment more flexible for CAR T cells.
We will apply a holistic approach exploiting our complementary expertise. We aim to collect in 3 centers (FR, SP, CA) tumor and sequential blood and stool samples from 400 cancer patients (150 already biobanked) treated with different combinations of immunotherapy-RT and, as comparators, with other immunotherapy combinations +/- chemotherapy and with single-agent immunotherapy or RT. We will perform metabolomics and metagenomics analyses to identify the perturbations associated with response. We will then devise strategies to sensitize to the combination and validate in 2D (DE, IT), patient-derived 3D (TR) and animal (CA, DE, IT) models. Furthermore, different RT regimens will be tested to determine the optimal combination protocol (CA). Finally, the impact of cancer cell’s metabolic profile on the response to the combination will be dissected (DE, TR).
METRICs begins with clinical observations and multi-omics analyses of human samples, follows to preclinical studies and finally goes back to the clinic for evaluation in clinical trials.