# Microbiome and metabolite signatures for cirrhosis to HCC risk stratification: progress, controversies, and gaps

## TL;DR

This paper explores how gut microbiome and metabolite changes could help predict liver cancer risk in patients with cirrhosis.

## Contribution

It highlights novel microbiome and metabolite signatures that may offer early risk stratification for cirrhosis to HCC progression.

## Key findings

- Decreased SCFA-related bacteria and increased inflammation-related bacteria are linked to higher HCC risk.
- Bile acid spectrum shifts and other intestinal metabolite abnormalities are associated with cirrhosis progression.
- Microbiome changes may reflect early tumor-promoting conditions through the gut-liver axis.

## Abstract

The progression from cirrhosis to hepatocellular carcinoma (HCC) is a key outcome in the management of chronic liver disease. This process has a long incubation period and significant individual differences, making early warning still difficult. Clinical follow-up mainly relies on imaging examinations and alpha fetoprotein, but the ability to identify high risk precancerous states is limited. The imbalance of gut microbiota and its metabolites may occur earlier than the visible stage of tumors. They can affect barrier integrity, chronic inflammation, immune surveillance, and metabolic homeostasis through the gut liver axis, and participate in the formation of a pro tumor microenvironment. Therefore, such changes may provide more upstream risk stratification clues for the population with cirrhosis. This article summarizes previous research evidence and summarizes the common microbiome and metabolite characteristics of cirrhosis and high-risk populations, including a decrease in short chain fatty acid (SCFA) related symbiotic bacteria, an increase in inflammation related bacteria, bile acid spectrum shift, and other intestinal derived metabolite abnormalities. This article also outlines the key mechanisms that these features may correspond to, such as barrier damage and microbial translocation, immune suppression, etc. There are still significant uncertainties at present. The effect of SCFA is context dependent. Different etiologies, diets, medications, and complications can lead to significant confounding and affect cross cohort consistency. Subsequent research requires longitudinal cohort validation and the promotion of multi omics integration and the construction of interpretable predictive models to support clinical translation.