Abstract :
[en] Mounting evidence from 16S rRNA-based or metagenomic analyses suggests that
dysbiosis, a state of pathological microbial imbalance, is prevalent in the gut of patients with
CRC. Numerous microbial taxa have been identified of which representative isolate cultures
can interact with cancer cells, further triggering distinct disease pathways in animal models.
Nevertheless, how these complex interrelationships of a dysbiotic microbiota may be
involved in the pathogenesis of CRC remains a fundamental question and requires
multifaceted mechanistic studies. This thesis moves beyond observational studies, it integrates novel experimental approaches for the study of the gut microbiome in colorectal cancer. It incorporates current knowledge in the field as well as interdisciplinary approaches. My work aims at contributing to an ecosystem-level mechanistic understanding of the CRC-associated microbiome in the initiation and progression of the disease. In detail, the objective of my work comprised an integrative approach of microbiome-CRC interaction studies. We revised current knowledge on, and studied the CRC-associated bacteria, in particular Fusobacterium nucleatum (Fn) and Gemella morbillorum (Gm). We assessed their direct and indirect effects on CRC cells,
their interactions with immune cells, as well as their tumor-modulating potential in vitro, in
silico, and in vivo. The results presented in this thesis comprise new findings on human microbial cross-talk of Fn with CRC. We identified formate as a potential fusobacterial
oncometabolite, which enhanced cancer incidence and progression via increased cancer
stemness signaling. Furthermore, we discovered immune-suppressive functions of Gm in
the context of CRC.
With my work in collaboration projects, I contributed to the development of two novel
approaches in anti-cancer therapy: First, to the establishment of a personalized in vitro
model (iHuMiX) for the study of microbe-host-immune interactions in anti-cancer therapy,
and second, to the validation of an in silico workflow that uses metabolic rewiring strategies
for network-based drug target predictions for CRC therapy. Taken together, this thesis work
broadened the mechanistic understanding of CRC-associated microbes and it contributed
to potential strategies for the development of an improved CRC therapy.
Funders :
FNR - Fonds National de la Recherche [LU]
Internal Research Project grant provided by the University of Luxembourg
Action LIONS Vaincre le Cancer Luxembourg
Fondation du Pélican de Mie et Pierre Hippert-Faber, under the aegis of the Fondation de Luxembourg