Gut microbiome: New biomarkers in early screening of colorectal cancer

Microbiome's Universe: Impact on health, disease and cancer treatment

The human microbiome is a diverse ecosystem of microorganisms that reside in the body and influence various aspects of health and well-being. Recent advances in sequencing technology have brought to light microbial communities in organs and tissues that were previously considered sterile. The gut microbiota plays an important role in host physiology, including metabolic functions and immune modulation. Disruptions in the balance of the microbiome, known as dysbiosis, have been linked to diseases such as cancer, inflammatory bowel disease and metabolic disorders. In addition, the administration of antibiotics can lead to dysbiosis by disrupting the structure and function of the gut microbial community. Targeting strategies are the key to rebalancing the microbiome and fighting disease, including cancer, through interventions such as probiotics, fecal microbiota transplantation (FMT), and bacteria-based therapies. Future research must focus on understanding the complex interactions between diet, the microbiome and cancer in order to optimize personalized interventions. Multidisciplinary collaborations are essential if we are going to translate microbiome research into clinical practice. This will revolutionize approaches to cancer prevention and treatment.

Beyond a vestigial organ: effects of the appendix on gut microbiome and colorectal cancer

The role of appendectomy in the pathogenesis of colorectal cancer (CRC) is a recent topic of contention. Given that appendectomy remains one of the most commonly performed operations and a first-line management strategy of acute appendicitis, it is inherently crucial to elucidate the association between prior appendectomy and subsequent development of CRC, as there may be long-term health repercussions. In this review, we summarize the data behind the relationship of CRC in post-appendectomy patients, discuss the role of the microbiome in relation to appendectomy and CRC pathogenesis, and provide an appraisal of our current understanding of the function of the appendix. We seek to piece together the current landscape surrounding the microbiome and immunological changes in the colon post-appendectomy and suggest a direction for future research involving molecular, transcriptomic, and immunologic analysis to complement our current understanding of the alterations in gut microbiome.

Gut microbiome-derived bacterial extracellular vesicles in patients with solid tumours

INTRODUCTION

Gut microbiome-derived nanoparticles, known as bacterial extracellular vesicles (bEVs), have garnered interest as promising tools for studying the link between the gut microbiome and human health. The diverse composition of bEVs, including their proteins, mRNAs, metabolites, and lipids, makes them useful for investigating diseases such as cancer. However, conventional approaches for studying gut microbiome composition alone may not be accurate in deciphering host-gut microbiome communication. In clinical microbiome research, there is a gap in the knowledge on the role of bEVs in solid tumor patients.

OBJECTIVES

Analyzing the functionality of bEVs using (meta)genomics and proteomics could highlight the unique aspects of host-gut microbiome interactions in solid tumor patients. Therefore, we performed a comparative analysis of the proteome and microbiota composition of gut microbiome-derived bEVs isolated from patients with solid tumors and healthy controls.

METHODS

After isolating bEVs from the feces of solid tumor patients and healthy controls, we performed spectrometry analysis of their proteomes and next-generation sequencing (NGS) of the 16S gene. We also investigated the gut microbiomes of feces from patients and controls using 16S sequencing and used machine learning to classify the samples into patients and controls based on their bEVs and fecal microbiomes.

RESULTS

Solid tumor patients showed decreased microbiota richness and diversity in both the bEVs and feces. However, the bEV proteomes were more diverse in patients than in the controls and were enriched with proteins associated with the metabolism of amino acids and carbohydrates, nucleotide binding, and oxidoreductase activity. Metadata classification of samples was more accurate using fecal bEVs (100%) compared with fecal samples (93%).

CONCLUSION

Our findings suggest that bEVs are unique functional entities. There is a need to explore bEVs together with conventional gut microbiome analysis in functional cancer research to decipher the potential of bEVs as cancer diagnostic or therapeutic biomarkers.

The microbiome as a biomarker of anal precancerous lesions in people with HIV

PURPOSE OF REVIEW

Early detection and treatment of human papillomavirus (HPV)-related anal dysplasia in some high-risk groups can help anal cancer prevention, but new tools to improve diagnostic and risk assessment are needed. Here, we aim to discuss the evidence on the role of the microbiome as a potential biomarker for anal high-grade squamous intraepithelial lesions (HSILs) in people with HIV (PWH).

RECENT FINDINGS

This review covers relevant studies on the links between the microbiome and HPV infection, cervical dysplasia/cancer, and anal HPV disease. It focuses on anal samples and precancerous lesions.

SUMMARY

The review highlights the promising potential of the anal microbiome as a novel biomarker for precancerous lesions in people with HIV, while also discussing limitations and future research needs.

Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients

BACKGROUND

Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we analyzed the expression levels of RhoB and DNp73 proteins in rectal cancer, as captured in immunohistochemical images, to predict the 5-year survival time of two patient groups: one with preoperative radiotherapy and one without.

METHODS

The utilization of deep convolutional neural networks in medical research, particularly in clinical cancer studies, has been gaining substantial attention. This success primarily stems from their ability to extract intricate image features that prove invaluable in machine learning. Another innovative method for extracting features at multiple levels is the wavelet-scattering network. Our study combines the strengths of these two convolution-based approaches to robustly extract image features related to protein expression.

RESULTS

The efficacy of our approach was evaluated across various tissue types, including tumor, biopsy, metastasis, and adjacent normal tissue. Statistical assessments demonstrated exceptional performance across a range of metrics, including prediction accuracy, classification accuracy, precision, and the area under the receiver operating characteristic curve.

CONCLUSION

These results underscore the potential of dual convolutional learning to assist clinical researchers in the timely validation and discovery of cancer biomarkers.

Bacterial infection and microbiota in carcinogenesis and tumor development

Microbiota colonize exposed body tissues (e.g., gastrointestinal tract, skin, lungs, female genital tract, and urogenital tracts) and unexposed sites (e.g., breast). Persistent bacterial infection in the host lead to the development of multiple disease. They are implicated in the pathogenesis of various complex diseases, including diabetes, atherosclerosis, autoimmune diseases, Alzheimer's disease, and malignant diseases. Amounting studies have demonstrated the role of bacterial infection in carcinogenesis. The study of microbiota in tumorigenesis is primarily focused on lung cancer, colorectal cancer (CRC), breast cancer, gastric cancer, and gynecologic tumors, and so on. Infection of Helicobacter pylori in gastric cancer carcinogenesis is recognized as class I carcinogen by the World Health Organization (WHO) decades ago. The role of Fusobacterium nucleatum in the development of colorectal cancer is extensively investigated. Variable bacteria have been cultured from the tumor tissues. The identification of microbiota in multiple tumor tissues reveal that bacterial infection and microbiota are associated with tumor development. The microbiota affects multiple aspects of carcinogenesis and tumor development, including favoring epithelial cells proliferation, establishing inflammatory microenvironment, promoting metastasis, and causing resistance to therapy. On the other hand, microbiota can shape a tumor surveillance environment by enhancing cell activity, and sensitize the tumor cells to immune therapy. In the present review, the roles of microbiota in multiple malignancies are summarized, and unraveling the mechanisms of host-microbiota interactions can contribute to a better understanding of the interaction between microbiota and host cells, also the development of potential anti-tumor therapeutic strategies.

Gut microbiota profiles in feces and paired tumor and non-tumor tissues from Colorectal Cancer patients. Relationship to the Body Mass Index

Colorectal Cancer (CRC) and Obesity constitute two of the most common malignancies in the western world, and previously have been associated with intestinal microbial composition alterations. Our main aim in this study is to provide molecular data on intestinal microbiota patterns in subjects with CRC, as well as to establish possible associations with their Body Mass Index (BMI). A total of 113 samples from 45 subjects were collected and submitted to metagenomics analysis for gut microbiota. This study was performed by 16S ribosomal RNA bacterial gene amplification and sequencing using the Ion Torrent™ technology. The same dominant phyla were observed in feces and colorectal tissues, although a greater proportion of Fusobacteriota was found in tumor samples. Moreover, at the genus level, LEfSe analysis allowed us to detect a significant increase in Fusobacterium and Streptococcus in colorectal tissues with respect to fecal samples, with a significant preponderance of Fusobacterium in tumor tissues. Also, our data revealed relevant associations between gut microbiota composition and tumor location. When comparing bacterial profiles between right and left colon cancers, those from the left-sided colon showed a significant preponderance, among others, of the order Staphylococcales. Moreover, phyla Firmicutes and Spirochaetota were more abundant in the group of right-sided CRCs and phylum Proteobacteria was increased in rectal cancers. In relation to BMI of patients, we detected significant differences in beta diversity between the normal weight and the obese groups of cases. Microbiota from obese patients was significantly enriched, among others, in Bacteroidales. Therefore, our results are useful in the molecular characterization of CRC in obese and non-obese patients, with a clear impact on the establishment of diagnostic and prognosis of CRC.

Salivary and fecal microbiota: potential new biomarkers for early screening of colorectal polyps

Objective

Gut microbiota plays an important role in colorectal cancer (CRC) pathogenesis through microbes and their metabolites, while oral pathogens are the major components of CRC-associated microbes. Multiple studies have identified gut and fecal microbiome-derived biomarkers for precursors lesions of CRC detection. However, few studies have used salivary samples to predict colorectal polyps. Therefore, in order to find new noninvasive colorectal polyp biomarkers, we searched into the differences in fecal and salivary microbiota between patients with colorectal polyps and healthy controls.

Methods

In this case-control study, we collected salivary and fecal samples from 33 patients with colorectal polyps (CP) and 22 healthy controls (HC) between May 2021 and November 2022. All samples were sequenced using full-length 16S rRNA sequencing and compared with the Nucleotide Sequence Database. The salivary and fecal microbiota signature of colorectal polyps was established by alpha and beta diversity, Linear discriminant analysis Effect Size (LEfSe) and random forest model analysis. In addition, the possibility of microbiota in identifying colorectal polyps was assessed by Receiver Operating Characteristic Curve (ROC).

Results

In comparison to the HC group, the CP group's microbial diversity increased in saliva and decreased in feces (p < 0.05), but there was no significantly difference in microbiota richness (p > 0.05). The principal coordinate analysis revealed significant differences in β-diversity of salivary and fecal microbiota between the CP and HC groups. Moreover, LEfSe analysis at the species level identified Porphyromonas gingivalis, Fusobacterium nucleatum, Leptotrichia wadei, Prevotella intermedia, and Megasphaera micronuciformis as the major contributors to the salivary microbiota, and Ruminococcus gnavus, Bacteroides ovatus, Parabacteroides distasonis, Citrobacter freundii, and Clostridium symbiosum to the fecal microbiota of patients with polyps. Salivary and fecal bacterial biomarkers showed Area Under ROC Curve of 0.8167 and 0.8051, respectively, which determined the potential of diagnostic markers in distinguishing patients with colorectal polyps from controls, and it increased to 0.8217 when salivary and fecal biomarkers were combined.

Conclusion

The composition and diversity of the salivary and fecal microbiota were significantly different in colorectal polyp patients compared to healthy controls, with an increased abundance of harmful bacteria and a decreased abundance of beneficial bacteria. A promising non-invasive tool for the detection of colorectal polyps can be provided by potential biomarkers based on the microbiota of the saliva and feces.

MicroRNA-31 induced by Fusobacterium nucleatum infection promotes colorectal cancer tumorigenesis

Persistent Fusobacterium nucleatum infection is associated with the development of human colorectal cancer (CRC) and promotes tumorigenicity, but the underlying mechanisms remain unclear. Here, we reported that F. nucleatum promoted the tumorigenicity of CRC, which was associated with F. nucleatum-induced microRNA-31 (miR-31) expression in CRC tissues and cells. F. nucleatum infection inhibited autophagic flux by miR-31 through inhibiting syntaxin-12 (STX12) and was associated with the increased intracellular survival of F. nucleatum. Overexpression of miR-31 in CRC cells promoted their tumorigenicity by targeting eukaryotic initiation factor 4F-binding protein 1/2 (eIF4EBP1/2), whereas miR-31 knockout mice were resistant to the formation of colorectal tumors. In conclusion, F. nucleatum, miR-31, and STX12 form a closed loop in the autophagy pathway, and continuous F. nucleatum-induced miR-31 expression promotes the tumorigenicity of CRC cells by targeting eIF4EBP1/2. These findings reveal miR-31 as a potential diagnostic biomarker and therapeutic target in CRC patients with F. nucleatum infection.

Profiling of the intestinal community of Clostridia: taxonomy and evolutionary analysis

Aim: Clostridia are relevant commensals of the human gut due to their major presence and correlations to the host. In this study, we investigated intestinal Clostridia of 51 healthy subjects and reconstructed their taxonomy and phylogeny. The relatively small number of intestinal Clostridia allowed a systematic whole genome approach based on average amino acid identity (AAI) and core genome with the aim of revising the current classification into genera and determining evolutionary relationships. Methods: 51 healthy subjects' metagenomes were retrieved from public databases. After the dataset's validation through comparison with Human Microbiome Project (HMP) samples, the metagenomes were profiled using MetaPhlAn3 to identify the population ascribed to the class Clostridia. Intestinal Clostridia genomes were retrieved and subjected to AAI analysis and core genome identification. Phylogeny investigation was conducted with RAxML and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) algorithms, and SplitsTree for split decomposition. Results: 225 out of 406 bacterial taxonomic units were ascribed to Bacillota [Firmicutes], among which 124 were assigned to the class Clostridia. 77 out of the 124 taxonomic units were referred to a species, altogether covering 87.7% of Clostridia abundance. According to the lowest AAI genus boundary set at 55%, 15 putative genera encompassing more than one species (G1 to G15) were identified, while 19 species did not cluster with any other one and each appeared to belong to a diverse genus. Phylogenetic investigations highlighted that most of the species clustered into three main evolutive clades. Conclusion: This study shed light on the species of Clostridia colonizing the gut of healthy adults and pinpointed several gaps in knowledge regarding the taxonomy and the phylogeny of Clostridia.

Cryptosporidium infection induced the dropping of SCFAS and dysbiosis in intestinal microbiome of Tibetan pigs

The infection of Cryptosporidium in pigs causes digestive system ailments, diarrhea and weight loss serving as an economic burden, especially in newborn animals. The bacterial fermentation products of short-chain fatty acids have important roles in immune function, microbiota regulation, osmotic balance and metabolism. However, till now little knowledge is available about the effect of Cryptosporidium infection on microbiota and SCFAs in plateau pigs. Hence, we performed this study to explore the response of microbiota and SCFAs in the natural infection of Cryptosporidium in Tibetan pigs. Cryptosporidium positive (infected, G) and negative samples (healthy, J) in our previous study were used for high throughputsequencing and Gas Chromatography-Mass Spectrometer analysis. Over 81 000 and 74 000 filtered sequences were detected in healthy and infected Tibetan pigs, respectively. Lower sample richness and evenness were observed in Cryptosporidium infection, as alpha diversity analysis found that chao1 (p < 0.05), faith_pd (p < 0.05), and observed_features in group G were significantly lower than pigs in group J. A total of 4 and 27 significant different phyla and genera were found between group G and J. The changed genera were Psychrobacter, Desemzia, Succiniclasticum, Treponema, Campylobacter, Atopobium, Olsenella, Pediococcus, Peptococcus, Sharpea, Desulfovibrio, Acinetobacter, Rhodococcus, Anaerostipes, Turicibacter, Lactobacillus, RFN20, Phascolarctobacterium, Roseburia, Megasphaera, Streptococcus, Blautia, Lachnospira, rc4_4, Gemmiger, Dorea, Oribacterium and Prevotella, which affected the microbiota functions with 360 abundance changed enzymes, and pathways in L1, L2 and L3 levels of KEGG. The concentration of acetic acid (p < 0.01), butyric acid (p < 0.05) and caproic acid (p < 0.01) were lower in group G. In conclusion, the present study herein uncovered that the host responses to Cryptosporidium infection in Tibetan pigs with 27 of significantly changed genera decreased SCFAs in pigs, which may provide insights in further developing novel therapy against this protozoan.

The global research of microbiota in colorectal cancer screening: a bibliometric and visualization analysis

Aims

We conducted bibliometric and visualization analyses to evaluate the current research status, hotspots, and trends related to the human microbiota markers in colorectal cancer screening.

Methods

The related studies were acquired from the Web of Science Core Collection (WoSCC) database on 5 January 2023. Analyses of the co-occurrence and cooperation relationships between the cited authors, institutions, countries/regions, cited journals, cited articles, and keywords in the studies were carried out using CiteSpace 5.8.R3 software and the Online Analysis platform of Literature Metrology. Additionally, relevant knowledge graphs were drawn to perform visualization analyses; a keywords cluster analysis and a burst analysis were also conducted.

Results

After analyzing 700 relevant articles, this bibliometric analysis found that the annual publications showed an increasing trend from 1992 to 2022. Yu Jun from the Chinese University of Hong Kong had the highest cumulative number of publications, whereas Shanghai Jiao Tong University was the most productive institution. China and the USA have contributed the largest number of studies. The keywords frequency analysis demonstrated that "colorectal cancer," "gut microbiota," "Fusobacterium nucleatum," "risk," and "microbiota" were the most frequent keywords, and the keywords cluster analysis found that the current hotspots were as follows: (a) the precancerous lesions of colorectal cancer (CRC) that need to be screened, such as inflammatory bowel disease (IBD) and advanced adenoma, (b) the gut-derived microbiome for CRC screening, and (c) the early detection of CRC. The burst analysis further showed that the combination of microbiomics with metabolomics might be the future research trend in the field of CRC screening.

Conclusion

The findings of the current bibliometric analysis firstly provide an insight into the current research status, hotspots, and future trends in the field of CRC screening based on the microbiome; the research in this field is becoming more in-depth and diversified. Some human microbiota markers, especially "Fusobacterium nucleatum," are promising biomarkers in CRC screening, and a future hotspot might be the combined analysis of microbiomics and metabolomics for CRC risk screening.