An Observational Study on the Prognostic Value of Neurometabolic Networks in Colorectal Cancer

OBJECTIVE(S) & HYPOTHESIS(ES) Objective: Evaluate area under curve (AUC) of BRIDGE in predicting overall survival (OS) for CRC patients. Compare the AUC of BRIDGE with clinical prediction models in predicting survival status for CRC patients. Evaluate the sensitivity, specificity, positive prediction value (PPV) and negative prediction value (NPV)of BRIDGE in predicting OS for CRC patients.

Hypothesis: BRIDGE achieves an AUC over 0.80 in predicting OS for CRC patients. BRIDGE is superior to clinical prediction models in terms of AUC in predicting OS for CRC patients.

BACKGROUND & RATIONALE Colorectal cancer (CRC), with annually increasing incidence and mortality worldwide, has become the second leading cause of cancer-related death. The gastrointestinal (GI) tract comprises a complex ecosystem with extensive interactions between normal or neoplastic epithelial cells with immune, neuronal, and other cell types, as well as microorganisms and metabolites within the gut lumen. Specifically, the intricate relationship between the GI tract and the central nervous system (CNS), collectively known as the brain-gut axis, plays a pivotal role in the pathogenesis of gastrointestinal disorders and neoplasm. For instance, chronic stress increased the risk of colon cancer via activating the COX-2/PEG2 system and promoted tumor cell dissemination by remodeling lymph vasculature. The bidirectional communications of the brain-gut axis are generally found to be mediated by neurotransmitters, inflammatory cytokines, metabolites, or gut microbiota. Nonetheless, the spotlight has shone primarily on the brain-gut crosstalk mechanisms in experimental cellular or animal models, with less attention paid to the structural and functional alterations on the brain networks at the patient level.

The evolution of functional neuroimaging modalities and neuroscience technologies has enabled accurate delineation of CNS activities. Specifically, nuclear medicine imaging technology using 2-18F fluoro-2-deoxy-D-glucose (18F-FDG) to adopt whole-body imaging information, is the optimal in vivo method for the investigation of regional human brain metabolism and associations with systemic disorders. The investigators have previously identified the neuronal metabolic-ventricular dyssynchronization axis which might related to major arrhythmic events using myocardial perfusion imaging and the brain 18F-FDG positron emission tomography (PET). Given the potential dual interactions of the brain-gut axis, identification of specific brain regions associated with CRC development and progression might lead to a better understanding of the disease's neurobiological underpinnings and inform the development of targeted therapeutic strategies. Hence, this study was structured to elucidate the role of neuro-metabolism and its potential mediator in regulating CRC tumorigenesis and metastasis. By delving into the neurometabolic-gut axis in CRC, the resulting mechanistic insights might be leveraged to identify diagnostic and prognostic biomarkers and to develop novel therapeutic interventions for CRC patients.

Previously, investigators have constructed a BRIDGE based on retrospective datasets. The study is conducted to further prospectively verify the clinical applicability and generalizability of BRIDGE in predicting OS for CRC patients. The prediction performance of BRIDGE will be evaluated in a prospective dataset, and compared to conventional clinical-based prediction models in the trial, which might potentially provide important evidence for the feasibility and clinical value of integration of brain images for artificial intelligence-aided GI cancer medicine.