European meta-analysis identifies gut microbiome signature for colorectal cancer

A meta-analysis of almost 6,800 gut microbiome profiles has revealed a microbial signature linked to colorectal cancer. The discovery forms the basis on which future microbiome-based tools can be used to assess cancer risk and prevention, however, it is not a diagnostic test yet. 

This was found after integrating data from 27 studies by researchers from the Mi-EOCRC consortium spanning Germany, Switzerland, and the Netherlands and including the Zeller and Zimmermann groups at the European Molecular Biology Laboratory (EMBL) Heidelberg.

The team found consistent cancer microbiome patterns across various populations using a machine learning algorithm, which detected cancerous from noncancerous microbiomes. Notably, the researchers linked variations to dietary fiber intake.

According to the researchers, colorectal cancer’s microbiome signature is detectable in early-stage tumors but not as much in pre-cancerous adenomas.

Overcoming previous challenges

The researchers say their Cell Host & Microbe study is one of the most comprehensive analyses of colorectal cancer-associated gut microbiomes to date. 

Previous literature has reported that people with colorectal cancer and those without it have different microbiomes. However, many of these studies were small and used different sequencing methods, making it challenging to know which microbial changes are reproducible, as other meta-analyses have pointed out.

The study integrated data from 27 studies across Germany, Switzerland, and the Netherlands.Commenting on how the new study addresses previous challenges, Georg Zeller, visiting team leader at EMBL Heidelberg says: “The strength of this study is its comprehensiveness. We combined stool and tissue comparisons, dietary data, taxonomic analysis down to bacterial strains, and functional analysis of virulence factors.”

His team analyzed data from 6,779 publicly available gut microbiome sequencing profiles and 906 intestinal tissue samples. This was used to compare stool-based microbiome signals with those found in tumor tissue.

The new study made methodological advances using computational approaches that integrated datasets from different sequencing methods at scale.

“The key tool is a machine learning algorithm that is trained to distinguish cancer from non-cancer microbiomes,” comments Zeller, also a professor at the Leiden University Medical Center, the Netherlands. “It outputs a score of how ‘cancer-like’ a microbiome is. We can apply this to any existing human gut microbiome dataset, including from dietary intervention studies.”

The integration approach means the microbiome signature was not limited, but applicable across populations.

Furthermore, the researchers suggest that their tool can help build future machine learning for risk assessment, early detection, or personalized prevention research. However, larger tests are required to know whether microbiome data can complement or be combined with current clinical tests.

Detecting challenges

The study found that the microbes in the tumor tissue were similar to the colorectal cancer signature in fecal samples. 

Cancer-associated microbes were already detectable in early stages in tissue samples. But in stool samples and tumor locations further up the colon, detection was lower in early stages. The researchers explain that this might be because microbes from tumors are smaller or further away from the rectum.

“These results suggest that colorectal cancer-associated changes in the microbiome may appear early in disease development and raise the question of how the tumor shapes the microbiome and how the microbes impact the tumor microenvironment through signaling, metabolic, and other interactions,” comments Michael Zimmermann, group leader at EMBL Heidelberg.

F. nucleatum subsp. animalis was consistently found in colorectal cancer samples across multiple continents.Another limitation was that detecting adenoma-associated microbial changes, which was weaker than colorectal cancer changes.

“This limitation is important for future clinical translation, which the Mi-EOCRC consortium is aiming at,” adds Zimmermann. “It suggests that more sensitive approaches, larger datasets, or combinations with other measurements may be needed before microbiome-based tools could contribute to the reliable detection of early precancerous lesions.”

Impact of diet and fiber on disease

The team discovered that lower dietary fiber intake had strong associations with cancer-associated microbiome patterns. The opposite was also noted, as diets high in fiber intake were linked to reduced colorectal cancer microbiome signature scores.

Therefore, they note that diets and fiber can influence microbial patterns associated with colorectal cancer, indicating that gut microbes are relevant to cancer risk, progression, or prevention.

Furthermore, the researchers highlight that the machine learning scores can be applied to existing microbiome databases, including dietary intervention studies to help researchers better understand lifestyle impacts on disease-associated microbiome patterns.

Experts have previously advocated for the industry to innovate plant-based, high-fiber solutions to tackle the rising rates of colon cancer, as many consumers are misinformed about diet links to the disease. 

Bacterial enrichment linked to colorectal cancer

The team underscores the importance of distinguishing between Fusobacteria subspecies. This bacterial group has been often linked to colorectal cancer.

Some subspecies were especially common in colorectal cancer samples from particular geographic regions, such as Asia, while some carried different disease-related genes, explain the researchers.

Fusobacterium nucleatum subsp. animalis enrichment was consistently found in people with colorectal cancer across continents.

Previous research identified a pattern of bacteria, fungi, and viruses that occurs more frequently in patients with colorectal cancer — making up an “oncogenic microbiome.”

Another study found that the bacterial toxin colibactin increases the rates of colorectal cancer among young people.