Metagenomics analysis reveals universal signatures of the intestinal microbiota in colorectal cancer, regardless of regional differences

Decoding the link between microbial secondary metabolites and colorectal cancer

Colorectal cancer (CRC) is a prevalent form of cancer in humans, with the gut microbiota playing a significant role in its pathogenesis. Although previous research has primarily focused on the role of primary metabolites produced by gut microbes in CRC development, the role of secondary metabolites remains largely unexplored. Secondary metabolites are known to mediate crucial interactions between the microbiota and the host, potentially influencing CRC progression. However, their specific relationship to CRC pathogenesis is poorly understood. To address this gap, we performed a meta-analysis using fecal metagenomic data from a cohort of CRC patients and healthy controls, aiming to identify CRC-associated microbial secondary metabolite biosynthetic gene clusters (BGCs). Our findings not only provide valuable insights into the pathogenicity and carcinogenicity of CRC but also shed light on the potential mechanisms underlying its development.

Study on the Effect of Radish Sprouts on Short-Chain Fatty Acids and Gut Microbial Diversity in Healthy Individuals

This study aimed to assess the impact of radish sprouts on the gut microbiota of healthy individuals. Radish sprout additives, subjected to short-term storage and steam treatment, were used to intervene in an in vitro culture of human gut microbiota. The influence of radish sprouts on the gut microbiota was evaluated by monitoring short-chain fatty acid (SCFA) content and proportion in the fermentation broth, and microbial diversity was assessed using 16S rDNA amplicon sequencing. The results indicated that the gut microbiota produced a substantial amount of SCFA within 48 h of fermentation, with a right-skewed distribution across all groups. The addition of both digestates enhanced Firmicutes diversity, while Bacteroidetes and Proteobacteria diversity remained stable between the control and fresh sprout groups. The 30 s steam treatment group showed an increase in Bacteroidetes and a decrease in Proteobacteria diversity. The abundance of Bacilli, Bacillaceae, and Bacillus was significantly higher in both the fresh and steam-treated groups compared to the control. Both fresh and steam-treated radish sprout digestates enriched gut microbiota diversity, with steam treatment showing superior effects. These findings suggest that radish sprout consumption may positively influence gut microbiota, with steam treatment potentially enhancing these benefits.

Robust prediction of colorectal cancer via gut microbiome 16S rRNA sequencing data

Introduction. The study addresses the challenge of utilizing human gut microbiome data for the early detection of colorectal cancer (CRC). The research emphasizes the potential of using machine learning techniques to analyze complex microbiome datasets, providing a non-invasive approach to identifying CRC-related microbial markers.Hypothesis/Gap Statement. The primary hypothesis is that a robust machine learning-based analysis of 16S rRNA microbiome data can identify specific microbial features that serve as effective biomarkers for CRC detection, overcoming the limitations of classical statistical models in high-dimensional settings.Aim. The primary objective of this study is to explore and validate the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for colorectal cancer (CRC) detection and progression. The focus is on developing a classifier that effectively predicts the presence of CRC and normal samples based on the analysis of three previously published faecal 16S rRNA sequencing datasets.Methodology. To achieve the aim, various machine learning techniques are employed, including random forest (RF), recursive feature elimination (RFE) and a robust correlation-based technique known as the fuzzy forest (FF). The study utilizes these methods to analyse the three datasets, comparing their performance in predicting CRC and normal samples. The emphasis is on identifying the most relevant microbial features (taxa) associated with CRC development via partial dependence plots, i.e. a machine learning tool focused on explainability, visualizing how a feature influences the predicted outcome.Results. The analysis of the three faecal 16S rRNA sequencing datasets reveals the consistent and superior predictive performance of the FF compared to the RF and RFE. Notably, FF proves effective in addressing the correlation problem when assessing the importance of microbial taxa in explaining the development of CRC. The results highlight the potential of the human microbiome as a non-invasive means to detect CRC and underscore the significance of employing FF for improved predictive accuracy.Conclusion. In conclusion, this study underscores the limitations of classical statistical techniques in handling high-dimensional information such as human microbiome data. The research demonstrates the potential of the human microbiome, specifically in the colon, as a valuable source of biomarkers for CRC detection. Applying machine learning techniques, particularly the FF, is a promising approach for building a classifier to predict CRC and normal samples. The findings advocate for integrating FF to overcome the challenges associated with correlation when identifying crucial microbial features linked to CRC development.

Improved diagnostic efficiency of CRC subgroups revealed using machine learning based on intestinal microbes

BACKGROUND

Colorectal cancer (CRC) is a common cancer that causes millions of deaths worldwide each year. At present, numerous studies have confirmed that intestinal microbes play a crucial role in the process of CRC. Additionally, studies have shown that CRC can be divided into several consensus molecular subtypes (CMS) based on tumor gene expression, and CRC microbiomes have been reported related to CMS. However, most previous studies on intestinal microbiome of CRC have only compared patients with healthy controls, without classifying of CRC patients based on intestinal microbial composition.

RESULTS

In this study, a CRC cohort including 339 CRC samples and 333 healthy controls was selected as the discovery set, and the CRC samples were divided into two subgroups (234 Subgroup1 and 105 Subgroup2) using PAM clustering algorithm based on the intestinal microbial composition. We found that not only the microbial diversity was significantly different (Shannon index, p-value < 0.05), but also 129 shared genera altered (p-value < 0.05) between the two CRC subgroups, including several marker genera in CRC, such as Fusobacterium and Bacteroides. A random forest algorithm was used to construct diagnostic models, which showed significantly higher efficiency when the CRC samples were divided into subgroups. Then an independent cohort including 187 CRC samples (divided into 153 Subgroup1 and 34 Subgroup2) and 123 healthy controls was chosen to validate the models, and confirmed the results.

CONCLUSIONS

These results indicate that the divided CRC subgroups can improve the efficiency of disease diagnosis, with various microbial composition in the subgroups.

Echinacoside inhibits colorectal cancer metastasis via modulating the gut microbiota and suppressing the PI3K/AKT signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Echinacoside (ECH) is the dominant phenylethanoid glycoside-structured compound identified from our developed herbal formula Huangci granule, which has been previously reported to inhibit the invasion and metastasis of CRC and prolong patients' disease-free survival duration. Though ECH has inhibitory activity against aggressive colorectal cancer (CRC) cells, its anti-metastasis effect in vivo and the action mechanism is undetermined. Given that ECH has an extremely low bioavailability and gut microbiota drives the CRC progression, we hypothesized that ECH could inhibit metastatic CRC by targeting the gut microbiome.

AIM OF THE STUDY

The purpose of this study was to investigate the impact of ECH on colorectal cancer liver metastasis in vivo and its potential mechanisms.

MATERIALS AND METHODS

An intrasplenic injection-induced liver metastatic model was established to examine the efficiency of ECH on tumor metastasis in vivo. Fecal microbiota from the model group and the ECH group were separately transplanted into pseudo-sterile CRLM mice in order to verify the role of gut flora in the ECH anti-metastatic effect. The 16S rRNA gene sequence was applied to analyze the structure and composition of the gut microbiota after ECH intervention, and the effect of ECH on short-chain fatty acid (SCFAs)-producing bacteria growth was proven by anaerobic culturing in vitro. GC-MS was applied to quantitatively analyze the serum SCFAs levels in mice. RNA-seq was performed to detect the gene changes involving tumor-promoting signaling pathway.

RESULTS

ECH inhibited CRC metastasis in a dose-dependent manner in the metastatic colorectal cancer (mCRC) mouse model. Manipulation of gut bacteria in the mCRC mouse model further proved that SCFA-generating gut bacteria played an indispensable role in mediating the antimetastatic action of ECH. Under an anaerobic condition, ECH benefited SCFA-producing microbiota without affecting the total bacterial load, presenting a dose-dependent promotion on the growth of a butyrate producer, Faecalibacterium prausnitzii (F.p). Furthermore, ECH-reshaped or F.p-colonized microbiota with a high butyrate-producing capability inhibited liver metastasis by suppressing PI3K/AKT signaling and reversing the epithelial-mesenchymal transition (EMT) process, whereas this anti-metastatic ability was abrogated by the butyrate synthase inhibitor heptanoyl-CoA.

CONCLUSION

This study demonstrated that ECH exhibits oral anti-metastatic efficacy by facilitating butyrate-producing gut bacteria, which downregulates PI3K/AKT signaling and EMT. It hints at a novel role for ECH in CRC therapy.

Diet-mediated gut microbial community modulation and signature metabolites as potential biomarkers for early diagnosis, prognosis, prevention and stage-specific treatment of colorectal cancer

BACKGROUND

Over the last decade, studies have shown an increased incidence of colorectal cancer (CRC), particularly early onset colorectal cancer (EOCRC). Researchers have demonstrated that dietary behavior, especially among young adults, influences alterations in the gut microbial community, leading to an increased accumulation of pathogenic gut microbiota and a decrease in beneficial ones. Unfortunately, CRC is likely to be diagnosed at a late stage, increasing CRC-related mortality. However, this alteration in the gut microbiota (gut dysbiosis) can be harnessed as a biomarker for non-invasive diagnosis, prognosis, prevention, and treatment of CRC in an effort to prevent late diagnosis and poor prognosis associated with CRC.

AIM OF REVIEW

This review discusses identification of potential biomarkers by targeting diet-mediated gut dysbiosis for the stage-specific diagnosis, prognosis, treatment, and prevention of CRC. Our findings provide a comprehensive insight into the potential of protumorigenic bacteria (e.g.pathogenic Escherichia coli,enterotoxigenic Bacteroides fragilis and Fusobacterium nucleatum) and their metabolites (e.g., colibactin and B. fragilis toxin) from gut dysbiosis as biomarkers for the diagnosis of CRC.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Collectively, a detailed understanding of the available data from current studies suggests that, further research on quantification of metabolites and stage-specific pathogenic microbial abundance is required for the diagnosis and treatment of CRC based on microbial dysbiosis. Specifically, future studies on faecal samples, from patient with CRC, should be conducted for F. nucleatum among different opportunistic bacteria, given its repeated occurrence in faecal samples and CRC biopsies in numerous studies. Finally, we discuss the potential of faecal microbial transplantation (FMT) as an intervention to restore damaged gut microbiota during CRC treatment and management.

Intestinal Microbiota and miRNA in IBD: A Narrative Review about Discoveries and Perspectives for the Future

Inflammatory bowel disease (IBD) includes Crohn's disease (CD) and ulcerative colitis (UC) and comprises a chronic gastrointestinal tract disorder characterized by hyperactive and dysregulated immune responses to environmental factors, including gut microbiota and dietary components. An imbalance of the intestinal microbiota may contribute to the development and/or worsening of the inflammatory process. MicroRNAs (miRNAs) have been associated with various physiological processes, such as cell development and proliferation, apoptosis, and cancer. In addition, they play an important role in inflammatory processes, acting in the regulation of pro- and anti-inflammatory pathways. Differences in the profiles of miRNAs may represent a useful tool in the diagnosis of UC and CD and as a prognostic marker in both diseases. The relationship between miRNAs and the intestinal microbiota is not completely elucidated, but recently this topic has gained prominence and has become the target of several studies that demonstrate the role of miRNAs in the modulation of the intestinal microbiota and induction of dysbiosis; the microbiota, in turn, can regulate the expression of miRNAs and, consequently, alter the intestinal homeostasis. Therefore, this review aims to describe the interaction between the intestinal microbiota and miRNAs in IBD, recent discoveries, and perspectives for the future.

New Insights into the Relationship between Gut Microbiota and Radiotherapy for Cancer

Cancer is the second most common cause of death among humans in the world, and the threat that it presents to human health is becoming more and more serious. The mechanisms of cancer development have not yet been fully elucidated, and new therapies are changing with each passing day. Evidence from the literature has validated the finding that the composition and modification of gut microbiota play an important role in the development of many different types of cancer. The results also demonstrate that there is a bidirectional interaction between the gut microbiota and radiotherapy treatments for cancer. In a nutshell, the modifications of the gut microbiota caused by radiotherapy have an effect on tumor radiosensitivity and, as a result, affect the efficacy of radiotherapy and show a certain radiation toxicity, which leads to numerous side effects. What is of new research significance is that the "gut-organ axis" formed by the gut microbiota may be one of the most interesting potential mechanisms, although the relevant research is still very limited. In this review, we combine new insights into the relationship between the gut microbiota, cancer, and radiotherapy. Based on our current comprehensive understanding of this relationship, we give an overview of the new cancer treatments based on the gut microbiota.

Fusobacterium nucleatum and Malignant Tumors of the Digestive Tract: A Mechanistic Overview

Fusobacterium nucleatum (F. nucleatum) is an oral anaerobe that plays a role in several oral diseases. However, F. nucleatum is also found in other tissues of the digestive tract, and several studies have recently reported that the level of F. nucleatum is significantly elevated in malignant tumors of the digestive tract. F. nucleatum is proposed as one of the risk factors in the initiation and progression of digestive tract malignant tumors. In this review, we summarize recent reports on F. nucleatum and its role in digestive tract cancers and evaluate the mechanisms underlying the action of F. nucleatum in digestive tract cancers.