Table 1. Challenges and required developments for better microbial outcomes in CRC.

CRC: colorectal cancer; PCR: polymerase chain reaction.

Methodology	Limitation	Development
Population sample	Heterogenicity (i.e. geography and lifestyle); most current studies include western populations [59].	Comprehensive and diverse studies for a better microbial database [57].
Study design	Case-control: Controls are affected by host and environmental factors (i.e. diet and genetics) [60].	Individualised approach (i.e. paired diseased-healthy tissue samples, diet, and metabolic analysis) for a personalised diagnosis and personalised therapy (i.e. pre/probiotics) [63].
Sample collection	Faecal samples (partially reflect gut microbiome) [54].	Tissue (mucosal) samples for a better understanding of environmental processes and biological interactions [64].
Microbial sample	Non-bacterial microbial components (i.e. virome, mycobiome, and protozoans). Non-bacterial microbial dataset (limited): gut virome dysbiosis (differ in CRC stages, patients - control) [54].	Taxonomy-based analysis: CRC-associated bacterial taxa + less covered taxonomic groups (i.e. fungi and viruses) [23]. Distinct sequencing techniques (i.e. regions, depth, and PCR) avoid heterogenicity bias [57].
Data analysis	Independent taxons analysis: Without considering ecological correlation -> decretive host-microbial interaction [65].	Functional-based analysis: Combined omics (i.e. metagenomic, metatranscriptomics, metaproteomics, and metabolomics) approaches of a mechanistic host-microbial interaction for direct causal effect [23].