CAMEOS: CAncer Microbiome: Emergent Organisation and Stability across scales

by A. Sengupta and E. Letellier

Notwithstanding the recent run of breakthroughs in the realms of microbiomes and cancers–two complex systems on their own–much remains unknown at their interface: The Cancer Microbiome.

A growing body of fundamental and translational research indicates that the associated microbiome influences–and potentially–regulates cancer progression, crucially impacting the choice and efficacy of diagnostic and therapeutic approaches. At the scale of a microbe, cancer is a spatially structured active soft material, either close to thermodynamic equilibrium, kBT (product of the Boltzmann constant, kB, and temperature, T) for solid tumours or out-of-equilibrium for most metastatic cells. The associated microbiome–an active matter system–elicits emergent geometry, order and topology that, crucially, regulate local biophysical properties. Taken together, the cancer microbiome is a coupled active complex system where emergent properties underpin oncogenic attributes and progression. Yet, to date, such a framework remains unexplored, with bulk of existing studies focusing independently on one or the other. Little is known if and how biophysical emergence regulates the dynamics of cancer microbiome, leaving open a major chasm in our efforts to predict cancer progression, and innovatively harness this promising, yet unexplored functional parameter to advance diagnostic and therapeutic tools. Using a bottom up multi-scale experimental approach, CAMEOS pioneers a new line of cross-disciplinary research on cancer microbiome that lies at an exciting interface of physics, biology and machine learning (ML). By leveraging the synergy between the PI-s, and their upcoming collaborations within the UL (DCS, DPhyMS & LCSB), CAMEOS will discern the role of microbes–both direct and indirect–in shaping cancer phenotypes and micro-environments, in relation to microbial species and physiology. Focusing on colorectal cancer (CRC) as model system, CAMEOS will characterise the CRC and matrix physico-chemical properties, concomitantly with those of the associated microbes using on-chip and organoid- based platforms. A combination of advanced visualisation and biomolecular assays will capture the micro-scale dynamics, which using ML-based analysis tools, will reveal how microbes regulate CRC and matrix properties, ultimately feeding back into the dynamic microbial organisation and metabolism. Crucially, through time-series data, CAMEOS will be in a unique position to generate seminal data that will link CRC-matrix transformations, in real time, with microbial distribution and physiology, revealing emergent feedbacks that underpin sessile-to-metastatic (benign-to-malignant) changes. This original, ambitious, cross-disciplinary endeavour will break new grounds by presenting a novel integrated mechanistic framework that will uncover the role of nonlinear interactions, feedback and emergence in shaping the fitness and resilience of cancer-microbe ecosystems, thereby heralding innovative approaches which will harness emergent properties for the next generation of cancer prevention and management.

Prof. Dr. Anupam SENGUPTA

Prof. Dr. Elisabeth LETELLIER