Global Analysis of Microbiota Signatures in Four Major Types of Gastrointestinal Cancer

Detection and comparison of tumor cell-associated microbiota from different compartments of colorectal cancer

Introduction

Intratumoral microbes play an important role in the development of colorectal cancer (CRC). However, studying intratumoral microbes in CRC faces technical challenges, as tumor microbe communities are often contaminated by fecal microbes due to the structure of the gut folds and villi. The present study aimed to develop a new method for isolating tumor cell-associated microbiota and comparing microbial populations from different compartments.

Materials and methods

The distribution of intestinal bacteria was detected using immunohistochemistry combined with 5R-16s rRNA gene sequencing to explore the effects of the sampling site and number of washes on the detection of microbiota. The 5R-16s rRNA gene sequencing was performed using 44 samples from 11 patients with CRC, including CRC tumor tissues (TT), normal tissues adjacent to CRC (NT), tumor cells (TC), and normal cells (NC). TC and NC were obtained from the TT and NT using an enzymatic digestion method. The microbiota and their potential functions in the four groups were analyzed and compared to determine the differential microbiota related to CRC.

Results

Bacteria were mainly distributed in the feces covering intestinal tissues and in the epithelial cells and macrophages within the tissues. Different sampling sites and number of washes led to detection of different microbiota distributions. Although the cleaning method could be controlled, sampling sites varied and led to different microbiota distributions. The phyla of Firmicutes and Bacteroidetes were highly abundant in the conventionally used tissue samples, whereas Proteobacteria was the most abundant phyla in the cell samples isolated with the new method (i.e., after cell enzymatic hydrolysis). Detection of CRC cell-associated microbiota using a cell enzymatic digestion method showed that some bacteria, such as Fusobacterium, Eikenella, Shewanella, and Listeria, were more abundant in TT than NT, whereas the abundance of Akkermansia was lower in TT than NT. The tumor/normal ratios of some bacteria, such as Gemella, Escherichia, Shigella, and Blautia, were different between the cell and tissue samples.

Conclusion

The cell enzymatic digestion method reduced fecal bacterial contamination, enabling low biomass intratumoral microbiota to be detected and allowing prediction of bacterial distributions.

Intestinal Microbiota Modulates the Antitumor Effect of Oncolytic Virus Vaccines in Colorectal Cancer

BACKGROUND

Immunotherapies, such as oncolytic viruses, have become powerful cancer treatments, but only some patients with cancer can benefit from them, especially those with advanced-stage cancer, and new therapeutic strategies are needed to facilitate extended survival. The intestinal microbiota may contribute to colorectal cancer (CRC) carcinogenesis and the response to immunotherapy. However, whether and how the intestinal microbiota modulates the effects of oncolytic virus vaccines (OVVs) in CRC remain to be investigated.

METHODS

We generated an MC38-gp33 CRC mouse model and treated it with OVV-gp33 in early and advanced stages. Probiotics, fecal microbiota transplantation (FMT), and antibiotics (ABX) were administered to regulate the microbial composition of CRC mice at an advanced stage. The tumor growth rate and survival time of the mice were recorded; 16S rDNA sequencing was used to analyze the microbial composition and flow cytometry was used to detect T-cell subset activity.

RESULTS

OVV-gp33 treatment inhibited tumor growth and prolonged survival in the early stage of CRC but did not have a significant effect on the advanced stage of CRC. Moreover, 16S rDNA sequence analysis and flow cytometry showed significant differences in intestinal microbiota composition, microbial metabolites, and T-cell subsets in early and advanced-stage CRC. Probiotic and FMT treatment significantly enhanced the antitumor effect of OVV in the advanced stage of CRC with an increased abundance of activated CD8+ T cells and a decreased ratio of Treg cells, while depletion of the microbiota by ABX eliminated the antitumor activity of OVV with decreased CD8+ T-cell activation and upregulated Treg cells.

CONCLUSIONS

These results indicate that the intestinal microbiota and microbial metabolites play an important role in the antitumor effect of OVV in CRC. Furthermore, altering the intestinal microbiota composition can modulate the antitumor and immunomodulatory effects of OVV in CRC.

Intratumoral microorganisms in tumors of the digestive system

Tumors of the digestive system pose a significant threat to human health and longevity. These tumors are associated with high morbidity and mortality rates, leading to a heavy economic burden on healthcare systems. Several intratumoral microorganisms are present in digestive system tumors, and their sources and abundance display significant heterogeneity depending on the specific tumor subtype. These microbes have a complex and precise function in the neoplasm. They can facilitate tumor growth through various mechanisms, such as inducing DNA damage, influencing the antitumor immune response, and promoting the degradation of chemotherapy drugs. Therefore, these microorganisms can be targeted to inhibit tumor progression for improving overall patient prognosis. This review focuses on the current research progress on microorganisms present in the digestive system tumors and how they influence the initiation, progression, and prognosis of tumors. Furthermore, the primary sources and constituents of tumor microbiome are delineated. Finally, we summarize the application potential of intratumoral microbes in the diagnosis, treatment, and prognosis prediction of digestive system tumors. Video Abstract.

Intratumor microbiota in cancer pathogenesis and immunity: from mechanisms of action to therapeutic opportunities

Microbial species that dwell human bodies have profound effects on overall health and multiple pathological conditions. The tumor microenvironment (TME) is characterized by disordered vasculature, hypoxia, excessive nutrition and immunosuppression. Thus, it is a favorable niche for microbial survival and growth. Multiple lines of evidence support the existence of microorganisms within diverse types of cancers. Like gut microbiota, intratumoral microbes have been tightly associated with cancer pathogenesis. Intratumoral microbiota can affect cancer development through various mechanisms, including induction of host genetic mutation, remodeling of the immune landscape and regulation of cancer metabolism and oncogenic pathways. Tumor-associated microbes modulate the efficacy of anticancer therapies, suggesting their potential utility as novel targets for future intervention. In addition, a growing body of evidence has manifested the diagnostic, prognostic, and therapeutic potential of intratumoral microorganisms in cancer. Nevertheless, our knowledge of the diversity and biological function of intratumoral microbiota is still incomplete. A deeper appreciation of tumor microbiome will be crucial to delineate the key pathological mechanisms underlying cancer progression and hasten the development of personalized treatment approaches. Herein, we summarize the most recent progress of the research into the emerging roles of intratumoral microbiota in cancer and towards clarifying the sophisticated mechanisms involved. Moreover, we discuss the effect of intratumoral microbiota on cancer treatment response and highlight its potential clinical implications in cancer.

Intratumor microbiome: selective colonization in the tumor microenvironment and a vital regulator of tumor biology

The polymorphic microbiome has been proposed as a new hallmark of cancer. Intratumor microbiome has been revealed to play vital roles in regulating tumor initiation and progression, but the regulatory mechanisms have not been fully uncovered. In this review, we illustrated that similar to other components in the tumor microenvironment, the reside and composition of intratumor microbiome are regulated by tumor cells and the surrounding microenvironment. The intratumor hypoxic, immune suppressive, and highly permeable microenvironment may select certain microbiomes, and tumor cells may directly interact with microbiome via molecular binding or secretions. Conversely, the intratumor microbiomes plays vital roles in regulating tumor initiation and progression via regulating the mutational landscape, the function of genes in tumor cells and modulating the tumor microenvironment, including immunity, inflammation, angiogenesis, stem cell niche, etc. Moreover, intratumor microbiome is regulated by anti-cancer therapies and actively influences therapy response, which could be a therapeutic target or engineered to be a therapy weapon in the clinic. This review highlights the intratumor microbiome as a vital component in the tumor microenvironment, uncovers potential mutual regulatory mechanisms between the tumor microenvironment and intratumor microbiome, and points out the ongoing research directions and drawbacks of the research area, which should broaden our view of microbiome and enlighten further investigation directions.

Location and condition based reconstruction of colon cancer microbiome from human RNA sequencing data

BACKGROUND

The association between microbes and cancer has been reported repeatedly; however, it is not clear if molecular tumour properties are connected to specific microbial colonisation patterns. This is due mainly to the current technical and analytical strategy limitations to characterise tumour-associated bacteria.

METHODS

Here, we propose an approach to detect bacterial signals in human RNA sequencing data and associate them with the clinical and molecular properties of the tumours. The method was tested on public datasets from The Cancer Genome Atlas, and its accuracy was assessed on a new cohort of colorectal cancer patients.

RESULTS

Our analysis shows that intratumoural microbiome composition is correlated with survival, anatomic location, microsatellite instability, consensus molecular subtype and immune cell infiltration in colon tumours. In particular, we find Faecalibacterium prausnitzii, Coprococcus comes, Bacteroides spp., Fusobacterium spp. and Clostridium spp. to be strongly associated with tumour properties.

CONCLUSIONS

We implemented an approach to concurrently analyse clinical and molecular properties of the tumour as well as the composition of the associated microbiome. Our results may improve patient stratification and pave the path for mechanistic studies on microbiota-tumour crosstalk.

Functional Proteomic Profiling Analysis in Four Major Types of Gastrointestinal Cancers

Gastrointestinal (GI) cancer accounts for one in four cancer cases and one in three cancer-related deaths globally. A deeper understanding of cancer development mechanisms can be applied to cancer medicine. Comprehensive sequencing applications have revealed the genomic landscapes of the common types of human cancer, and proteomics technology has identified protein targets and signalling pathways related to cancer growth and progression. This study aimed to explore the functional proteomic profiles of four major types of GI tract cancer based on The Cancer Proteome Atlas (TCPA). We provided an overview of functional proteomic heterogeneity by performing several approaches, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), t-stochastic neighbour embedding (t-SNE) analysis, and hierarchical clustering analysis in oesophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ) tumours, to gain a system-wide understanding of the four types of GI cancer. The feature selection approach, mutual information feature selection (MIFS) method, was conducted to screen candidate protein signature subsets to better distinguish different cancer types. The potential clinical implications of candidate proteins in terms of tumour progression and prognosis were also evaluated based on TCPA and The Cancer Genome Atlas (TCGA) databases. The results suggested that functional proteomic profiling can identify different patterns among the four types of GI cancers and provide candidate proteins for clinical diagnosis and prognosis evaluation. We also highlighted the application of feature selection approaches in high-dimensional biological data analysis. Overall, this study could improve the understanding of the complexity of cancer phenotypes and genotypes and thus be applied to cancer medicine.

The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer

Microbiota can influence the occurrence, development, and therapeutic response of a wide variety of cancer types by modulating immune responses to tumors. Recent studies have demonstrated the existence of intratumor bacteria inside ovarian cancer (OV). However, whether intratumor microbes are associated with tumor microenvironment (TME) and prognosis of OV still remains unknown. The RNA-sequencing data and clinical and survival data of 373 patients with OV in The Cancer Genome Atlas (TCGA) were collected and downloaded. According to the knowledge-based functional gene expression signatures (Fges), OV was classified into two subtypes, termed immune-enriched and immune-deficient subtypes. The immune-enriched subtype, which had higher immune infiltration enriched with CD8+ T cells and the M1 type of macrophages (M1) and higher tumor mutational burden, exhibited a better prognosis. Based on the Kraken2 pipeline, the microbiome profiles were explored and found to be significantly different between the two subtypes. A prediction model consisting of 32 microbial signatures was constructed using the Cox proportional-hazard model and showed great prognostic value for OV patients. The prognostic microbial signatures were strongly associated with the hosts' immune factors. Especially, M1 was strongly associated with five species (Achromobacter deleyi and Microcella alkaliphila, Devosia sp. strain LEGU1, Ancylobacter pratisalsi, and Acinetobacter seifertii). Cell experiments demonstrated that Acinetobacter seifertii can inhibit macrophage migration. Our study demonstrated that OV could be classified into immune-enriched and immune-deficient subtypes and that the intratumoral microbiota profiles were different between the two subtypes. Furthermore, the intratumoral microbiome was closely associated with the tumor immune microenvironment and OV prognosis. IMPORTANCE Recent studies have demonstrated the existence of intratumoral microorganisms. However, the role of intratumoral microbes in the development of ovarian cancer and their interaction with the tumor microenvironment are largely unknown. Our study demonstrated that OV could be classified into immune-enriched and -deficient subtypes and that the immune enrichment subtype had a better prognosis. Microbiome analysis showed that intratumor microbiota profiles were different between the two subtypes. Furthermore, the intratumor microbiome was an independent predictor of OV prognosis that could interact with immune gene expression. Especially, M1 was closely associated with intratumoral microbes, and Acinetobacter seifertii could inhibit macrophage migration. Together, the findings of our study highlight the important roles of intratumoral microbes in the TME and prognosis of OV, paving the way for further investigation into its underlying mechanisms.

Basal Diet Fed to Recipient Mice Was the Driving Factor for Colitis and Colon Tumorigenesis, despite Fecal Microbiota Transfer from Mice with Severe or Mild Disease

Consumption of the total Western diet (TWD) in mice has been shown to increase gut inflammation, promote colon tumorigenesis, and alter fecal microbiome composition when compared to mice fed a healthy diet, i.e., AIN93G (AIN). However, it is unclear whether the gut microbiome contributes directly to colitis-associated CRC in this model. The objective of this study was to determine whether dynamic fecal microbiota transfer (FMT) from donor mice fed either the AIN basal diet or the TWD would alter colitis symptoms or colitis-associated CRC in recipient mice, which were fed either the AIN diet or the TWD, using a 2 × 2 factorial experiment design. Time-matched FMT from the donor mice fed the TWD did not significantly enhance symptoms of colitis, colon epithelial inflammation, mucosal injury, or colon tumor burden in the recipient mice fed the AIN diet. Conversely, FMT from the AIN-fed donors did not impart a protective effect on the recipient mice fed the TWD. Likewise, the composition of fecal microbiomes of the recipient mice was also affected to a much greater extent by the diet they consumed than by the source of FMT. In summary, FMT from the donor mice fed either basal diet with differing colitis or tumor outcomes did not shift colitis symptoms or colon tumorigenesis in the recipient mice, regardless of the basal diet they consumed. These observations suggest that the gut microbiome may not contribute directly to the development of disease in this animal model.

Microbiota in Tumors: From Understanding to Application

Microbes with complex functions have been found to be a potential component in tumor microenvironments. Due to their low biomass and other obstacles, intratumor microbiota is poorly understood. Mucosal sites and normal adjacent tissues are important sources of intratumor microbiota, while hematogenous spread also leads to the invasion of microbes. Intratumor microbiota affects the progression of tumors through several mechanisms, such as DNA damage, activation of oncogenic pathways, induction of immunosuppression, and metabolization of drugs. Notably, in different types of tumors, the composition and abundance of intratumor microbiota are highly heterogeneous and may play different roles in the progression of tumors. Because of the concern in this field, several techniques such as omics and immunological methods have been used to study intratumor microbiota. Here, recent progress in this field is reviewed, including the potential sources of intratumor microbiota, their functions and related mechanisms, and their heterogeneity. Techniques that can be used to study intratumor microbiota are also discussed. Moreover, research is summarized into the development of strategies that can be used in antitumor treatment and prospects for possible future research in this field.

A comprehensive analysis of intratumor microbiome in head and neck squamous cell carcinoma

PURPOSE

Human microbiome has been considered as the second genome of our body. The intratissue/intratumor microbiome analysis is a relatively new field and deserves more attention. In this study, we conducted a comprehensive analysis of microbiome signatures of head and neck squamous cell carcinoma (HNSC).

METHODS

The intratumor microbiome profiling and clinicopathological information about a total of 177 HNSC samples, including 155 tumors and 22 adjacent normal tissues, were obtained from The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA) databases. We identified the microbes that differed between tumors and normal tissues, and assessed their utility values as diagnostic biomarkers. The microbiome signatures under different conditions of clinicopathological parameters were also analyzed.

RESULTS

The intratissue microbiome profiles differed between tumor and normal samples of HNSC. The composition of four, six, and six microbes changed in tumors compared to normal tissues at the phylum, order, and genus levels, respectively (P < 0.05). Eight of the differential microbes performed well in distinguishing tumors from normal tissues (AUC > 0.7, P ≤ 0.001). The microbiome signature was found to be associated with tumor clinicopathological characteristics such as host-gender, host-age, tumor stage, and neoplasm histologic grade.

CONCLUSION

Overall, our results revealed an intratissue microbiome signature of HNSC. We concluded that the intratumor microbiome signature may also reflect human biology in both healthy and disease status, and provide novel perspective for microbiota research about their roles in tumors.

Exploring the Potential of Exosome-Related LncRNA Pairs as Predictors for Immune Microenvironment, Survival Outcome, and Microbiotain Landscape in Esophageal Squamous Cell Carcinoma

Accumulating studies have demonstrated the indispensable roles of exosomes and long non-coding RNAs (lncRNAs) in cancer progression and the tumor microenvironment (TME). However, the clinical relevance of exosome-related lncRNAs (ER-lncRNAs) in esophageal squamous cell carcinoma (ESCC) remains unclear. Three subtypes were identified by consensus clustering of 3459 valid ER-lncRNA pairs, of which subtype A is preferentially related to favorable prognosis, lower stromal and immune scores, and higher tumor purity scores. Higher immune cell infiltration, higher mRNA levels of immune checkpoints, higher stromal and immune scores, and lower tumor purity were found in subtype C, which presented a poor prognosis. We developed a prognostic risk score model based on 8 ER-lncRNA pairs in the GEO cohort using univariate Cox regression analysis and LASSO Cox regression analysis. Patients were divided into a high risk-score group and low risk-score group by the cut-off values of the 1-year ROC curves in the training set (GEO cohort) and the validation set (TCGA cohort). Receiver operating characteristic (ROC) curves, Decision curve analysis (DCA), clinical correlation analysis, and univariate and multivariate Cox regression all confirmed that the prognostic model has good predictive power and that the risk score can be used as an independent prognostic factor in different cohorts. By further analyzing the TME based on the risk model, higher immune cell infiltration and more active TME were found in the high-risk group, which presented a poor prognosis. Patients with high risk scores also exhibited higher mRNA levels of immune checkpoints and lower IC50 values, indicating that these patients may be more prone to profit from chemotherapy and immunotherapy. The top five most abundant microbial phyla in ESCC was also identified. The best ER-lncRNAs (AC082651.3, AP000487.1, PLA2G4E-AS1, C8orf49 and AL356056.2) were identified based on machine learning algorithms. Subsequently, the expression levels of the above ER-lncRNAs were analyzed by combining the GTEx and TCGA databases. In addition, qRT-PCR analysis based on clinical samples from our hospital showed a high degree of consistency. This study fills the gap of ER-lncRNA model in predicting the prognosis of patients with ESCC and the risk score-based risk stratification could facilitate the determination of therapeutic option to improve prognoses.

The Intratumor Microbiota Signatures Associate With Subtype, Tumor Stage, and Survival Status of Esophageal Carcinoma

Altered human microbiome characteristic has been linked with esophageal carcinoma (ESCA), analysis of microbial profiling directly derived from ESCA tumor tissue is beneficial for studying the microbial functions in tumorigenesis and development of ESCA. In this study, we identified the intratumor microbiome signature and investigated the correlation between microbes and clinical characteristics of patients with ESCA, on the basis of data and information obtained from The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA) databases. A total of 82 samples were analyzed for microbial composition at various taxonomic levels, including 40 tumor samples of esophageal squamous cell carcinoma (ESCC), 20 tumor samples of esophageal adenocarcinoma (EAD), and 22 adjacent normal samples. The results showed that the relative abundance of several microbes changed in tumors compared to their paired normal tissues, such as Firmicutes increased significantly while Proteobacteria decreased in tumor samples. We also identified a microbial signature composed of ten microbes that may help in the classification of ESCC and EAD, the two subtypes of ESCA. Correlation analysis demonstrated that compositions of microbes Fusobacteria/Fusobacteriia/Fusobacteriales, Lactobacillales/Lactobacillaceae/Lactobacillus, Clostridia/Clostridiales, Proteobacteria, and Negativicutes were correlated with the clinical characteristics of ESCA patients. In summary, this study supports the feasibility of detecting intratumor microbial composition derived from tumor sequencing data, and it provides novel insights into the roles of microbiota in tumors. Ultimately, as the second genome of human body, microbiome signature analysis may help to add more information to the blueprint of human biology.