Colon Cancer: From Epidemiology to Prevention

Abstract

Colorectal cancer (CRC) is one of the most prevalent cancers affecting humans, with a complex genetic and environmental aetiology. Unlike cancers with known environmental, heritable, or sex-linked causes, sporadic CRC is hard to foresee and has no molecular biomarkers of risk in clinical use. One in twenty CRC cases presents with an established heritable component. The remaining cases are sporadic and associated with partially obscure genetic, epigenetic, regenerative, microbiological, dietary, and lifestyle factors. To tackle this complexity, we should improve the practice of colonoscopy, which is recommended uniformly beyond a certain age, to include an assessment of biomarkers indicative of individual CRC risk. Ideally, such biomarkers will be causal to the disease and potentially modifiable upon dietary or therapeutic interventions. Multi-omics analysis, including transcriptional, epigenetic as well as metagenomic, and metabolomic profiles, are urgently required to provide data for risk analyses. The aim of this article is to provide a perspective on the multifactorial derailment of homeostasis leading to the initiation of CRC, which may be explored via multi-omics and Gut-on-Chip analysis to identify much-needed predictive biomarkers.

Keywords: colorectal cancer; epidemiology; gut-on-chip; inter-individual diversity; intestinal microbiota; intra-individual variation; multi-omics; prevention; regenerative inflammation; risk factors.

Figure 5

Gut-on-chip microfluidic device with human villus intestinal epithelium and human vascular endothelium formed on a flexible membrane with an active flow and peristalsis-like motion and capabilities to co-culture with bacteria and human immune cells. Adapted with permission from Bein et al. [198] (Elsevier license number: 5282361055514).

Figure 1

Environmental and molecular factors, biological modalities cross-linked in an overview of lifestyle, genomic, epigenomic, transcriptomic, proteomic, metabolomic, and metagenomic interactions leading to CRC-predisposing dysplasia.

Figure 2

Proximal and distal colon regionalization in terms of CRC incidence, outcome, molecular pathways leading to CRC, and microbes and metabolites involved.

Figure 3

Mitosis and regenerative inflammation genes can serve as biomarkers of risk because they vary among individuals and intestinal site. Violin plots depict a wide inter-individual distribution in expression of 30 mitosis and regenerative inflammation genes in the human colon (sigmoid muscularis and transverse muscularis and mucosa) and oesophagus (mucosa and muscularis). * denote >2 or <0.5 gene expression fold change between sigmoid muscularis (n = 318) and transverse muscularis and mucosa (n = 368) calculated in Transcripts Per Million from RNA-Seq data retrieved from GTEx Analysis Release V8 (dbGaP Accession phs000424.v8.p2; https://www.gtexportal.org/home/datasets (accessed on 4 May 2022)).

Figure 4

Overview of the MS imaging workflow towards CRC metabolomics. Preparation steps require the collection of healthy, adjacent-to-polyps, or tumorous colonic mucosa specimens, followed by snap freezing and cryosectioning of tissues onto compatible glass slides. Imaging requires ionization of desorbed molecules across the thin tissue surface followed by rastering. The reconstruction of metabolomic spatial distribution maps produced allows the multivariate statistical analysis of the metabolomic profile on the colonic specimen. The ensuing classification and quantification of all the metabolomic derivatives may be combined with other omic platforms to provide combinatorial, multi-omics-based biomarkers potentially applicable toward CRC prevention, diagnosis, or prognosis upon treatment.