The landscape of bacterial presence in tumor and adjacent normal tissue across 9 major cancer types using TCGA exome sequencing

Application of Fusobacterium nucleatum as a biomarker in gastrointestinal malignancies

The morbidity and mortality of gastrointestinal (GI) malignancies are among the highest in the world, posing a serious threat to human health. Because of the insidious onset of the cancer, it is difficult for patients to be diagnosed at an early stage, and it rapidly progresses to an advanced stage, resulting in poor treatment and prognosis. Fusobacterium nucleatum (F. nucleatum) is a gram-negative, spore-free anaerobic bacterium that primarily colonizes the oral cavity and is implicated in the development of colorectal, esophageal, gastric, and pancreatic cancers via various intricate mechanisms. Recent development in novel research suggests that F. nucleatum may function as a biomarker in GI malignancies. Detecting the abundance of F. nucleatum in stool, saliva, and serum samples of patients may aid in the diagnosis, risk assessment, and prognosis monitoring of GI malignancies. This editorial systematically describes the biological roles and mechanisms of F. nucleatum in GI malignancies focusing on the application of F. nucleatum as a biomarker in the diagnosis and prognosis of GI malignancies to promote the clinical translation of F. nucleatum and GI tumors-related research.

A review of machine learning methods for cancer characterization from microbiome data

Recent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.

Research progress on the microbiota in bladder cancer tumors

The microbiota, also referred to as the microbial community, is a crucial component of the human microenvironment. It is located predominantly in various organs, including the intestines, skin, oral cavity, respiratory tract, and reproductive tract. The microbiota maintains a symbiotic relationship with the human body, influencing physiological and pathological functions to a significant degree. There is increasing evidence linking the microbial flora to human cancers. In contrast to the traditional belief that the urethra and urine of normal individuals are sterile, recent advancements in high-throughput sequencing technology and bacterial cultivation methods have led to the discovery of specific microbial communities in the urethras of healthy individuals. Given the prevalence of bladder cancer (BCa) as a common malignancy of the urinary system, researchers have shifted their focus to exploring the connection between disease development and the unique microbial community within tumors. This shift has led to a deeper investigation into the role of microbiota in the onset, progression, metastasis, prognosis, and potential for early detection of BCa. This article reviews the existing research on the microbiota within BCa tumors and summarizes the findings regarding the roles of different microbes in various aspects of this disease.

Robustness of cancer microbiome signals over a broad range of methodological variation

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

Uncovering Microbial Composition of the Tissue Microenvironment in Bladder Cancer using RNA Sequencing Data

Purpose: Bladder cancer (BC) is one of the top 10 common tumors in the world. It has been reported that microbiota can colonize tissues and play important roles in tumorigenesis and progression. However, the current understanding of microorganisms in the BC tissue microenvironment remains unclear. Methods: In this study, we integrated the RNA-seq data of 479 BC tissue samples from seven datasets combined with a range of bioinformatics tools to explore the landscape of microbiome in the BC tissue microenvironment. Results: The pan-microbiome was estimated to surpass 1,400 genera. A total of seven core microbiota (Bacillus, Corynebacterium, Cutibacterium, Escherichia, Halomonas, Pasteurella, and Streptomyces) were identified. Among them, Bacillus was widely distributed in all datasets with a high relative abundance (10.11% of all samples on average). Moreover, some biological factors, including tissue source and tumor grade, were found significant effects on the microbial composition of the bladder tissue. Pseudomonas, Porphyrobacter, and Acinetobacter were enriched in tumor tissues, while Mycolicibacterium and Streptomyces were enriched in patients who showed durable response to BCG therapy. In addition, we established microbial co-occurrence networks and found that the BCG therapy may attenuate the microbiological interactions. Conclusions: This study clearly provided a microbial landscape of the BC tissue microenvironment, which was important for exploring the interactions between microorganisms and BC tissues. The identified specific taxa might be potential biomarkers for BC.

Distinct intratumoral microbiome of young-onset and average-onset colorectal cancer

BACKGROUND

The unexplained rise of young-onset CRC (yoCRC, age <50 years) is of concern. Evidence suggests that microbial dysbiosis may be a contributing factor, but the tumor microbial profile of yoCRC in comparison to average-onset CRC (aoCRC, age >60) has not been fully investigated.

METHODS

16S rRNA amplicon sequencing was performed in tumor and paired adjacent non-malignant fresh frozen tissue specimens prospectively collected from 136 yoCRC and 140 aoCRC patients. Phyloseq, microbiomeSeq, metagenomeSeq, and NetComi were utilized for bioinformatics analysis. Statistical tests included Fisher's exact test, ANOVA, PERMANOVA with Bonferroni correction, linear regression, and Wilcoxon test. p-value <0.05 was considered statistically significant.

FINDINGS

yoCRC patients were more likely to have left-sided (72.8 vs. 54.3%), rectal (36.7% vs. 25%), and stage IV (28% vs. 15%) tumors. yoCRC tumors had significantly higher microbial alpha diversity (p = 1.5 × 10-5) and varied beta diversity (R2 = 0.31, p = 0.013) than aoCRC tumors. yoCRC tumors were enriched with Akkermansia and Bacteroides, whereas aoCRC tumors showed greater relative abundances of Bacillus, Staphylococcus, Listeria, Enterococcus, Pseudomonas, Fusobacterium, and Escherichia/Shigella. Akkermansia had a predominantly negative correlation with the microbial communities in yoCRC tumors. yoCRC and aoCRC tumors had distinct microbial profiles associated with tumor location, sidedness, stage, and obesity. Fusobacterium (R2 = -0.23, p = 0.001) and Akkermansia (R2 = 0.05, p = 0.001) abundance correlated with overall survival in yoCRC.

INTERPRETATION

Our study provides a comprehensive understanding of the microbial perturbations in yoCRC tumors. We identify microbial candidates that may highlight a distinct pathogenesis of yoCRC and serve as preventive, diagnostic, and therapeutic targets.

FUNDING

Sondra and Stephen Hardis Chair in Oncology Research (A.A.K.).

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.

Microbial gene expression analysis of healthy and cancerous esophagus uncovers bacterial biomarkers of clinical outcomes

Local microbiome shifts are implicated in the development and progression of gastrointestinal cancers, and in particular, esophageal carcinoma (ESCA), which is among the most aggressive malignancies. Short-read RNA sequencing (RNAseq) is currently the leading technology to study gene expression changes in cancer. However, using RNAseq to study microbial gene expression is challenging. Here, we establish a new tool to efficiently detect viral and bacterial expression in human tissues through RNAseq. This approach employs a neural network to predict reads of likely microbial origin, which are targeted for assembly into longer contigs, improving identification of microbial species and genes. This approach is applied to perform a systematic comparison of bacterial expression in ESCA and healthy esophagi. We uncover bacterial genera that are over or underabundant in ESCA vs healthy esophagi both before and after correction for possible covariates, including patient metadata. However, we find that bacterial taxonomies are not significantly associated with clinical outcomes. Strikingly, in contrast, dozens of microbial proteins were significantly associated with poor patient outcomes and in particular, proteins that perform mitochondrial functions and iron-sulfur coordination. We further demonstrate associations between these microbial proteins and dysregulated host pathways in ESCA patients. Overall, these results suggest possible influences of bacteria on the development of ESCA and uncover new prognostic biomarkers based on microbial genes. In addition, this study provides a framework for the analysis of other human malignancies whose development may be driven by pathogens.

From mucosal infection to successful cancer immunotherapy

The clinical management of advanced malignancies of the upper and lower urinary tract has been revolutionized with the advent of immune checkpoint blockers (ICBs). ICBs reinstate or bolster pre-existing immune responses while creating new T cell specificities. Immunogenic cancers, which tend to benefit more from immunotherapy than cold tumours, harbour tumour-specific neoantigens, often associated with a high tumour mutational burden, as well as CD8+ T cell infiltrates and ectopic lymphoid structures. The identification of beneficial non-self tumour antigens and natural adjuvants is the focus of current investigation. Moreover, growing evidence suggests that urinary or intestinal commensals, BCG and uropathogenic Escherichia coli influence long-term responses in patients with kidney or bladder cancer treated with ICBs. Bacteria infecting urothelium could be a prominent target for T follicular helper cells and B cells, linking innate and cognate CD8+ memory responses. In the urinary tract, commensal flora differ between healthy and tumoural mucosae. Although antibiotics can affect the prognosis of urinary tract malignancies, bacteria can have a major influence on cancer immunosurveillance. Beyond their role as biomarkers, immune responses against uropathogenic commensals could be harnessed for the design of future immunoadjuvants that can be advantageously combined with ICBs.

Bacterial Sequencing Reads in Blood Exome Files from Melanoma and Cervical Cancer Patients are Associated with Cancer Recurrence

Bacteremia poses great risk for morbidity and mortality for immunocompromised cancer patients. Although the presence of bacteria within solid tumors is gaining greater attention, few studies have analyzed species of bacteria in the blood and their effect on cancer clinical outcomes. Using the Kraken 2 taxonomic profiling tool, we classified bacteria present in blood and primary tumors of cervical cancer and melanoma cases. The Cancer Genome Atlas (TCGA) melanoma blood exome files with Pseudomonas species were found to represent a worse disease-free survival (DFS) probability, while a worse overall survival (OS) result was evidenced for both the TCGA and Moffitt Cancer Center melanoma datasets. Cervical cancer cases with reads representing the Bradyrhizobium genus and Bradyrhizobium sp. BTAi1 found in blood and tumor exome files were found to have lower DFS. Additionally, reduced DFS and OS were observed for cervical cancer cases positive for Bacteroides species including Bacteroides fragilis. This study provides novel evidence and a novel approach for indicating that bacteria in blood is associated with cancer recurrence. These findings may guide the development of more efficient prognostic and screening tools related to bacterial blood infections of melanoma and cervical cancer patients.

Machine learning-based approaches for cancer prediction using microbiome data

Emerging evidence of the relationship between the microbiome composition and the development of numerous diseases, including cancer, has led to an increasing interest in the study of the human microbiome. Technological breakthroughs regarding DNA sequencing methods propelled microbiome studies with a large number of samples, which called for the necessity of more sophisticated data-analytical tools to analyze this complex relationship. The aim of this work was to develop a machine learning-based approach to distinguish the type of cancer based on the analysis of the tissue-specific microbial information, assessing the human microbiome as valuable predictive information for cancer identification. For this purpose, Random Forest algorithms were trained for the classification of five types of cancer-head and neck, esophageal, stomach, colon, and rectum cancers-with samples provided by The Cancer Microbiome Atlas database. One versus all and multi-class classification studies were conducted to evaluate the discriminative capability of the microbial data across increasing levels of cancer site specificity, with results showing a progressive rise in difficulty for accurate sample classification. Random Forest models achieved promising performances when predicting head and neck, stomach, and colon cancer cases, with the latter returning accuracy scores above 90% across the different studies conducted. However, there was also an increased difficulty when discriminating esophageal and rectum cancers, failing to differentiate with adequate results rectum from colon cancer cases, and esophageal from head and neck and stomach cancers. These results point to the fact that anatomically adjacent cancers can be more complex to identify due to microbial similarities. Despite the limitations, microbiome data analysis using machine learning may advance novel strategies to improve cancer detection and prevention, and decrease disease burden.

Intratumoural microbiota: from theory to clinical application

Cancer is a major cause of high morbidity and mortality worldwide. Several environmental, genetic and lifestyle factors are associated with the development of cancer in humans and result in suboptimal treatment. The human microbiota has been implicated in the pathophysiological process of cancer and has been used as a diagnostic, prognostic and risk assessment tool in cancer management. Notably, both extratumoural and intratumoural microbiota are important components of the tumor microenvironment, subtly influencing tumorigenesis, progression, treatment and prognosis. The potential oncogenic mechanisms of action of the intratumoural microbiota include induction of DNA damage, influence on cell signaling pathways and impairment of immune responses. Some naturally occurring or genetically engineered microorganisms can specifically accumulate and replicate in tumors and then initiate various anti-tumor programs, ultimately promoting the therapeutic effect of tumor microbiota and reducing the toxic and side effects of conventional tumor treatments, which may be conducive to the pursuit of accurate cancer treatment. In this review, we summarise evidence revealing the impact of the intratumoural microbiota on cancer occurrence and progress and potential therapeutic and diagnostic applications, which may be a promising novel strategy to inhibit tumor development and enhance therapeutic efficacy. Video Abstract.

Could the tumor-associated microbiota be the new multi-faceted player in the tumor microenvironment?

Microorganisms have been identified in tumor specimens for over a century. It is only in recent years that tumor-associated microbiota has become a rapidly expanding field. Assessment techniques encompass methods at the frontiers of molecular biology, microbiology, and histology, requiring a transdisciplinary process to carefully decipher this new component of the tumor microenvironment. Due to the low biomass, the study of tumor-associated microbiota poses technical, analytical, biological, and clinical challenges and must be approached as a whole. To date, several studies have begun to shed light on the composition, functions, and clinical relevance of the tumor-associated microbiota. This new piece of the tumor microenvironment puzzle could potentially change the way we think about and treat patients with cancer.

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.

Uncovering the special microbiota associated with occurrence and progression of gastric cancer by using RNA-sequencing

Gastric cancer (GC) has been identified as the third deadly cancer in the world. Accumulating researches suggest a potential role of microorganisms in tumorigenesis. However, the composition of microbiota in GC tissues is not clear and it changes throughout the different stages of GC remain mostly elusive. Our study integrated RNA-Seq data of 727 samples derived from gastric tissues across four datasets and revealed its microbial composition. In order to remove the false positive results, core taxa were defined and characterized. Based on it, we analyzed the influence of biological factors on its composition. The pan-microbiome of gastric tissues was estimated to be over than 1400 genera. Seventeen core genera were identified. Among them, Helicobacter, Lysobacter were significantly enriched in normal tissues, while Pseudomonas was enriched in tumor tissues. Interestingly, Acinetobacter, Pasteurella, Streptomyces, Chlamydia, and Lysobacter, showed a significant increase trend during tumor development and formed strong intra/inter-correlations among them or with other genera. Furthermore, we found that tumor stage played an important role in altering the microbial composition of GC tissues. This study provides support for the in-depth study of tumor microbiome, and the specific microbiome excavated provides a possibility for the subsequent identification of potential biomarkers for GC.

Microbial composition of tumorous and adjacent gastric tissue is associated with prognosis of gastric cancer

Helicobacter pylori (H. pylori) infection has been considered as the main causal factor in gastric carcinogenesis, but other bacterial species may also play an important role in pathophysiology of gastric cancer. The aim of the study was to explore the link between gastric cancer prognosis and the mucosal microbial community in tumorous and adjacent gastric tissue. The bacterial profile was analysed using 16S sequencing (V1-V2 region). Microbial differences were mostly characterized by lower relative abundances of H. pylori in tumorous gastric tissues. Bacterial community and outcome data analysis revealed the genus Fusobacterium and Prevotella significantly associated with worse overall survival in gastric cancer patients. In particular, Fusobacterium was associated with significant increase in hazard ratio in both univariable and multivariable analysis and independently validated using TCMA data. Phylogenetic biodiversity of Fusobacterium species in the stomach revealed F. periodonticum as the most prevalent in healthy subjects, while F. nucleatum was most abundant in patients with gastric cancer. Bacterial community network analysis in gastric cancer suggests substantial complexity and a strong interplay between F. nucleatum and Prevotella. In summary, mucosal microbial community in the stomach was associated with worse overall survival in gastric cancer patients. Strongest negative impact on prognosis was linked to the abundance of F. nucleatum in tumorous specimens, suggesting its translational relevance in management of gastric cancer patients.

Circulating Bacterial DNA as Plasma Biomarkers for Lung Cancer Early Detection

Lung cancer is a leading cause of cancer deaths and early diagnosis can significantly improve outcomes. Pathogenic bacteria have been shown to play a role in tumorigenesis and its analysis provides a new approach for cancer diagnosis. To evaluate the potential of bacteria as plasma biomarkers for early lung cancer detection, we analyzed eight lung-cancer-related bacterial genera in 58 lung cancer patients and 58 controls using ddPCR. Our results showed that five genera had higher DNA abundance in lung tumor tissues compared with normal tissues. Three of these genera (Selenomonas, Streptococcus, and Veillonella) displayed consistent changes in plasma, with higher DNA abundance in lung cancer patients compared with controls. When used as a panel, these three bacterial genera had a sensitivity of 75% and specificity of 78% for lung cancer detection, regardless of stage or histology. The performance of this biomarker panel was confirmed in an independent cohort of 93 lung cancer cases and 93 controls. Thus, circulating bacterial DNA has the potential to be used as plasma biomarkers for early lung cancer detection.

The pan-cancer landscape of abnormal DNA methylation and intratumor microorganisms

Microorganisms play very important roles in carcinogenesis, tumor progression, and resistance upon treatment. Due to the challenge of accurately acquiring samples and quantifying low-biomass tissue microorganisms, most studies have focused on the effect of gut microorganisms on cancer treatments, especially the efficacy of immunotherapy. Although recent publications reveal the potential interactions between intratumor microorganisms and the immune microenvironment, whether and to what extent the intratumor microorganism could affect progression and treatment outcome remain controversial. This study is aiming to evaluate the associations among intratumor microorganisms, DNA methylation cancer driver genes, immune response, and clinical outcomes from a pan-cancer perspective, using 6,876 TCGA samples across 21 cancer types. We revealed that tumor microorganism dysbiosis is closely associated with the abnormal tumor methylome and/or tumor microenvironment, which might serve to enhance the proliferation ability and fitness for the therapy of tumors. These findings shed the light on a better understanding of the interactions between tumor cells and carcinogens during and after tumor formation, as well as microorganism-associated methylation alterations that could further serve as biomarkers for clinical outcome assessment.

Microbial Biomarkers for Lung Cancer: Current Understandings and Limitations

As our "hidden organ", microbes widely co-exist at various sites on the human body. These microbes are collectively referred to as the microbiome. A considerable number of studies have already proven that the microbiome has significant impacts on human health and disease progression, including cancers. The recent discovery of cancer-specific microbiomes renders these cancer-associated microbes as potential biomarkers and therapeutic targets. While at low biomass levels, the lung microbiome still dramatically influences the initiation, progression and treatment of lung cancers. However, research on lung cancer-associated microbiomes is emerging, and most profiling studies are performed within three years. Unfortunately, there are substantial inconsistencies across these studies. Variations in microbial diversity were observed, and different microbial biomarkers for lung cancer have been proposed. In this review, we summarized the current findings of lung cancer microbiome studies and attempt to explain the potential reasons for the dissimilarities. Other than lung microbiomes, oral and airway microbiomes are highly related to lung microbiomes and are therefore included as well. In addition, several lung cancer-associated bacterial genera have been detected by different independent studies. These bacterial genera may not be perfect biomarkers, but they still serve as promising risk factors for lung cancers and show great prognostic value.

Bacteria for Treatment: Microbiome in Bladder Cancer

The human body contains a variety of microbes. The distribution of microbes varies from organ to organ. Sequencing and bioinformatics techniques have revolutionized microbial research. Although previously considered to be sterile, the urinary bladder contains various microbes. Several studies have used urine and bladder tissues to reveal the microbiome of the urinary bladder. Lactic acid-producing bacteria, such as Bifidobacterium, Lactobacillus, and Lactococcus, are particularly beneficial for human health and are linked to bladder cancer. This review highlights the analysis protocols for microbiome research, the studies undertaken to date, and the microbes with therapeutic potential in bladder cancer.

Microbial and molecular differences according to the location of head and neck cancers

Background

Microbiome has been shown to substantially contribute to some cancers. However, the diagnostic implications of microbiome in head and neck squamous cell carcinoma (HNSCC) remain unknown.

Methods

To identify the molecular difference in the microbiome of oral and non-oral HNSCC, primary data was downloaded from the Kraken-TCGA dataset. The molecular differences in the microbiome of oral and non-oral HNSCC were identified using the linear discriminant analysis effect size method.

Results

In the study, the common microbiomes in oral and non-oral cancers were Fusobacterium, Leptotrichia, Selenomonas and Treponema and Clostridium and Pseudoalteromonas, respectively. We found unique microbial signatures that positively correlated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in oral cancer and positively and negatively correlated KEGG pathways in non-oral cancer. In oral cancer, positively correlated genes were mostly found in prion diseases, Alzheimer disease, Parkinson disease, Salmonella infection, and Pathogenic Escherichia coli infection. In non-oral cancer, positively correlated genes showed Herpes simplex virus 1 infection and Spliceosome and negatively correlated genes showed results from PI3K-Akt signaling pathway, Focal adhesion, Regulation of actin cytoskeleton, ECM-receptor interaction and Dilated cardiomyopathy.

Conclusions

These results could help in understanding the underlying biological mechanisms of the microbiome of oral and non-oral HNSCC. Microbiome-based oncology diagnostic tool warrants further exploration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02554-6.

PathogenTrack and Yeskit: tools for identifying intracellular pathogens from single-cell RNA-sequencing datasets as illustrated by application to COVID-19

Pathogenic microbes can induce cellular dysfunction, immune response, and cause infectious disease and other diseases including cancers. However, the cellular distributions of pathogens and their impact on host cells remain rarely explored due to the limited methods. Taking advantage of single-cell RNA-sequencing (scRNA-seq) analysis, we can assess the transcriptomic features at the single-cell level. Still, the tools used to interpret pathogens (such as viruses, bacteria, and fungi) at the single-cell level remain to be explored. Here, we introduced PathogenTrack, a python-based computational pipeline that uses unmapped scRNA-seq data to identify intracellular pathogens at the single-cell level. In addition, we established an R package named Yeskit to import, integrate, analyze, and interpret pathogen abundance and transcriptomic features in host cells. Robustness of these tools has been tested on various real and simulated scRNA-seq datasets. PathogenTrack is competitive to the state-of-the-art tools such as Viral-Track, and the first tools for identifying bacteria at the single-cell level. Using the raw data of bronchoalveolar lavage fluid samples (BALF) from COVID-19 patients in the SRA database, we found the SARS-CoV-2 virus exists in multiple cell types including epithelial cells and macrophages. SARS-CoV-2-positive neutrophils showed increased expression of genes related to type I interferon pathway and antigen presenting module. Additionally, we observed the Haemophilus parahaemolyticus in some macrophage and epithelial cells, indicating a co-infection of the bacterium in some severe cases of COVID-19. The PathogenTrack pipeline and the Yeskit package are publicly available at GitHub.

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.

The interplay between Helicobacter pylori and gastrointestinal microbiota

The complex population of microbes in the human gastrointestinal (GI) tract interacts with itself and with the host, exerting a deep influence on health and disease development. The development of modern sequencing technology has enabled us to gain insight into GI microbes. Helicobacter pylori colonization significantly affects the gastric microenvironment, which in turn affects gastric microbiota and may be correlated with colonic microbiota changes. Crosstalk between H. pylori and GI commensal flora may play a role in H. pylori-related carcinogenicity and extragastric manifestations. We review current knowledge on how H. pylori shapes GI microbiota with a specific focus on its impact on the stomach and colon. We also review current evidence on colonic microbiota changes attributed to eradication therapy based on the clinical studies performed to date.

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.

Effects of Helicobacter pylori Infection on the Oral Microbiota of Reflux Esophagitis Patients

The human oral microbiota plays a vital role in maintaining metabolic homeostasis. To explore the relationship between Helicobacter pylori (Hp) and reflux esophagitis, we collected 86 saliva samples from reflux esophagitis patients (RE group) and 106 saliva samples from healthy people (C group) for a high-throughput sequencing comparison. No difference in alpha diversity was detected between the RE and the C groups, but beta diversity of the RE group was higher than the C group. Bacteroidetes was more abundant in the RE group, whereas Firmicutes was more abundant in the C group. The linear discriminant analysis effect size analysis demonstrated that the biomarkers of the RE group were Prevotella, Veillonella, Leptotrichia, and Actinomyces, and the biomarkers of the C group were Lautropia, Gemella, Rothia, and Streptococcus. The oral microbial network structure of the C group was more complex than that of the RE group. Second, to explore the effect of Hp on the oral microbiota of RE patients, we performed the ¹⁴C-urea breath test on 45 of the 86 RE patients. We compared the oral microbiota of 33 Hp-infected reflux esophagitis patients (REHpp group) and 12 non-Hp-infected reflux esophagitis patients (REHpn group). No difference in alpha diversity was observed between the REHpn and REHpp groups, and beta diversity of the REHpp group was significantly lower than that of the REHpn group. The biomarkers in the REHpp group were Veillonella, Haemophilus, Selenomonas, Megasphaera, Oribacterium, Butyrivibrio, and Campylobacter; and the biomarker in the REHpn group was Stomatobaculum. Megasphaera was positively correlated with Veillonella in the microbial network of the REHpp group. The main finding of this study is that RE disturbs the human oral microbiota, such as increased beta diversity. Hp infection may inhibit this disorderly trend.

Bacterial Diversity Correlates with Overall Survival in Cancers of the Head and Neck, Liver, and Stomach

One in five cancers is attributed to infectious agents, and the extent of the impact on the initiation, progression, and disease outcomes may be underestimated. Infection-associated cancers are commonly attributed to viral, and to a lesser extent, parasitic and bacterial etiologies. There is growing evidence that microbial community variation rather than a single agent can influence cancer development, progression, response to therapy, and outcome. We evaluated microbial sequences from a subset of infection-associated cancers-namely, head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD) from The Cancer Genome Atlas (TCGA). A total of 470 paired tumor and adjacent normal samples were analyzed. In STAD, concurrent presence of EBV and Selemonas sputigena with a high diversity index were associated with poorer survival (HR: 2.23, 95% CI 1.26-3.94, p = 0.006 and HR: 2.31, 95% CI 1.1-4.9, p = 0.03, respectively). In LIHC, lower microbial diversity was associated with poorer overall survival (HR: 2.57, 95% CI: 1.2, 5.5, p = 0.14). Bacterial within-sample diversity correlates with overall survival in infection-associated cancers in a subset of TCGA cohorts.

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

The gut microbiota has been previously linked with tumorigenesis and gastrointestinal cancer progression; however, intra-tumor microbiota analysis has just emerged and deserves increasing attention. Based on the public databases of The Cancer Microbiome Atlas (TCMA) and The Cancer Genome Atlas (TCGA), this study identified the tissue/organ microbial signatures generated from 443 biosamples of four major gastrointestinal cancer types, including esophageal carcinoma (ESCA), which further includes esophageal adenocarcinoma (EAD) and esophageal squamous cell carcinoma (ESCC), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). According to partial least squares discrimination analysis (PLS-DA), the profile differences in microbial communities between the tumor and normal samples were not particularly noticeable across the four cancer cohorts, whereas paired comparison analyses revealed several specific differences in bacteria between tumor and normal samples in the EAD, STAD, and COAD samples. The taxa classified from the phylum to genus level revealed a trend of distinguishable microbial profiles between upper and lower gastrointestinal tumors. The Bacteroidetes/Firmicutes ratio in lower gastrointestinal tract tumors was nearly three times that in upper gastrointestinal tract tumors. We also determined the relative tissue/organ-prevalent microbes for each of the four cohorts at the order and genus levels. Microbe Alistipes, Blautia, Pasteurellales, and Porphyromonas compositions were correlated with the clinical characteristics of patients with gastrointestinal cancer, particularly colorectal cancer. Taken together, our findings indicate that microbial profiles shift across different gastrointestinal cancer types and that microbial colonization is highly site-specific. Composition of specific microbes can be indicative of cancer stage or disease progression. Overall, this study indicates that the microbial community and abundance in human tissues can be determined using publicly available data, and provides a new perspective for intra-tissue/organ microbiota research.

Targeting butyrophilins for cancer immunotherapy

Vγ9Vδ2⁺ T cells form part of the innate immune repertoire and are activated by phosphorylated antigens produced by many bacteria and tumors. They have long been suggested as promising targets for anti-tumor therapies, but clinical trials so far have not shown major successes. Several recent discoveries could help to overcome these shortfalls, such as those leading to an improved understanding of the role of butyrophilin molecules BTN2A1 and BTN3A1, in Vγ9Vδ2⁺ T cell activation. Moreover, we propose that studies suggesting the presence of live bacteria in a variety of tumors (tumor microbiome), indicate that the latter might be harnessed as a source of high affinity bacterial phosphoantigen to trigger or enhance anti-tumor immune responses.

The Landscape of Microbial Composition and Associated Factors in Pancreatic Ductal Adenocarcinoma Using RNA-Seq Data

Recent research studies on interrogation of the tumor microbiome (including bacteria, viruses, and fungi) have yielded important insights into the role of microbes in carcinogenesis, therapeutic responses, and resistance. Once thought to be a sterile organ, a number of studies have showed the presence of microbes within this organ in PDAC status. A microbiome–pancreas axis for PDAC (pancreatic ductal adenocarcinoma) carcinogenesis is proposed. However, the microbial composition of localized PDAC tissue is still unclear. The associations between microbiome and PDAC reported in previous studies were detected in an indirect way, which mostly used samples from stool, oral saliva, and intestinal samples. This study integrated 582 samples derived from PDAC tissues across four datasets and presented a landscape of tumor microbiome at the genus level in PDAC based on remining of RNA-Seq data. On average, there are hundreds of genera distributed in the PDAC tissue, and dozens of core microbiota were identified by PDAC tissue. The pan-microbiome of PDAC tissue was also estimated, which might surpass 2,500 genera. In addition, sampling sites (stroma vs. epithelium) and tissue source (human tissue vs. PDX) were found to have great effects on the microbial composition of PDAC tissue, but not the traditional risk factors (sex and age). It is the first study to systematically focus on exploring the microbial composition of PDAC tissue and is helpful to have a deep understanding of tumor microbiome. The identified specific taxa might be potential biomarkers for follow-up research studies.

Prognostic value of intratumoral Fusobacterium nucleatum and association with immune-related gene expression in oral squamous cell carcinoma patients

Changes in the oral microbiome, particularly Fusobacterium nucleatum, are associated with oral squamous cell carcinoma (OSCC). F. nucleatum has been reported to modulate local immunity in cancers. We aimed to assess the association between intratumoral F. nucleatum and clinico-pathological features, relapse, and overall survival (OS) in two independent cohorts of patients with OSCC, and to explore the interplay with immune-related genes. We retrospectively analyzed tissue samples from a first cohort of 122 patients with head and neck squamous cell carcinoma, including 61 OSCC (cohort #1), and a second cohort of 90 additional OSCC (cohort #2). We then performed a sensitivity analysis on the merged cohort of OSCC patients (N = 151). F. nucleatum 16S rRNA gene sequences were quantified using real-time quantitative PCR. The presence of gram-negative bacteria and macrophages was confirmed by LPS and CD163 immunostainings, respectively. F. nucleatum positivity was associated with older age, less alcohol and combined alcohol plus tobacco consumption, and less frequent lymph node invasion. There was a trend for a lower recurrence rate in F. nucleatum-positive cases, with less metastatic relapses compared to F. nucleatum-negative tumors, and significantly longer OS, relapse-free and metastasis-free survival. F. nucleatum status was independently associated with OS in multivariate analysis. Immune-related gene and immunohistochemistry analyses showed that gram-negative bacteria load inversely correlated with M2 macrophages. F. nucleatum-associated OSCC has a specific immune microenvironment, is more frequent in older, non-drinking patients, and associated with a favorable prognosis.

The intratumor microbiome predicts prognosis across gender and subtypes in papillary thyroid carcinoma

While the intratumor microbiome has become increasingly implicated in cancer development, the microbial landscape of papillary thyroid carcinoma (PTC) is essentially uninvestigated. PTC is characterized by varied prognosis between gender and cancer subtype, but the cause for gender and subtype-based dissimilarities is unclear. Women are more frequently diagnosed with PTC, while men suffer more advanced-staged PTC. In addition, tall cell variants are more aggressive than classical and follicular variants of PTC. We hypothesized that intratumor microbiome composition distinctly alters the immune landscape and predicts clinical outcome between PTC subtypes and between patient genders. Raw whole-transcriptome RNA-sequencing, Level 3 normalized mRNA expression read counts, and DNA methylation 450 k sequencing data for untreated, nonirradiated tumor, and adjacent normal tissue were downloaded from the Genomic Data Commons (GDC) legacy archive for 563 thyroid carcinoma patients. Microbe counts were extracted using Pathoscope 2.0 software. We correlated microbe abundance to clinical variables and immune-associated gene expression. Gene-set enrichment, mutation, and methylation analyses were conducted to correlate microbe abundance to characterize microbes' roles. Overall, PTC tumor tissue significantly lacked microbes that are populated in adjacent normal tissue, which suggests presence of microbes may be critical in controlling immune cell expression and regulating immune and cancer pathways to mitigate cancer growth. In contrast, we also found that microbes distinctly abundant in tall cell and male patient cohorts were also correlated with higher mutation expression and methylation of tumor suppressors. Microbe dysbiosis in specific PTC types may explain observable differences in PTC progression and pathogenesis. These microbes provide a basis for developing specialized prebiotic and probiotic treatments for varied PTC tumors.

Bacterial, Archaea, and Viral Transcripts (BAVT) Expression in Gynecological Cancers and Correlation with Regulatory Regions of the Genome

Simple Summary

Microorganisms are found in all human tissues. Some of them are responsible for cancer formation. In our study we found gene expression from bacteria, archaea, and viruses in the upper female genital tract and this expression was associated with ovarian and endometrial cancer. We also found that the expression from these organisms may be involved in regulatory mechanisms of infection and cancer formation. Some of the processes associated with these organisms may affect cancer heterogeneity and be potential targets for cancer therapy.

Abstract

Bacteria, archaea, and viruses are associated with numerous human cancers. To date, microbiome variations in transcription have not been evaluated relative to upper female genital tract cancer risk. Our aim was to assess differences in bacterial, archaea, and viral transcript (BAVT) expression between different gynecological cancers and normal fallopian tubes. In this case-control study we performed RNA sequencing on 12 normal tubes, 112 serous ovarian cancers (HGSC) and 62 endometrioid endometrial cancers (EEC). We used the centrifuge algorithm to classify resultant transcripts into four indexes: bacterial, archaea, viral, and human genomes. We then compared BAVT expression from normal samples, HGSC and EEC. T-test was used for univariate comparisons (correcting for multiple comparison) and lasso for multivariate modelling. For validation we performed DNA sequencing of normal tubes in comparison to HGSC and EEC BAVTs in the TCGA database. Pathway analyses were carried out to evaluate the function of significant BAVTs. Our results show that BAVT expression levels vary between different gynecological cancers. Finally, we mapped some of these BAVTs to the human genome. Numerous map locations were close to regulatory genes and long non-coding RNAs based on the pathway enrichment analysis. BAVTs may affect gynecological cancer risk and may be part of potential targets for cancer therapy.

Tissue-associated microbial detection in cancer using human sequencing data

Cancer is one of the leading causes of morbidity and mortality in the globe. Microbiological infections account for up to 20% of the total global cancer burden. The human microbiota within each organ system is distinct, and their compositional variation and interactions with the human host have been known to attribute detrimental and beneficial effects on tumor progression. With the advent of next generation sequencing (NGS) technologies, data generated from NGS is being used for pathogen detection in cancer. Numerous bioinformatics computational frameworks have been developed to study viral information from host-sequencing data and can be adapted to bacterial studies. This review highlights existing popular computational frameworks that utilize NGS data as input to decipher microbial composition, which output can predict functional compositional differences with clinically relevant applicability in the development of treatment and prevention strategies.

Characterization of the human tumor microbiome reveals tumor-type specific intra-cellular bacteria

Many characteristics of cancer such as proliferation, survival, progression, immunogenicity, sensitivity, and resistance to therapy are not just endogenously driven by the tumor cells themselves, but are greatly affected by their interaction with the components of their microenvironment. In our recent report, we comprehensively characterized the bacterial content of solid tumors, which is strongly related to tumor type and subtype, largely presenting as metabolically-active and intra-cellular. Our integration with clinical patient data indicates potential avenues of cross-talk between the tumors and their bacterial counterparts paving the way for a deeper understanding of the physiological/biological context of the tumor and how to harness bacteria in therapy settings.