Tissue-associated microbial detection in cancer using human sequencing data

Domestication and Genetic Improvement Alter the Symbiotic Microbiome Structure and Function of Tomato Leaf and Fruit Pericarp

Many studies have attempted to explore the changes in the structure and function of symbiotic microbiomes, as well as the underlying genetic mechanism during crop domestication. However, most of these studies have focused on crop root microbiomes, while those on leaf and fruit are rare. In this study, we generated a comprehensive dataset including the metagenomic (leaf) and metatranscriptomic (fruit pericarp in the orange stage) data of hundreds of germplasms from three tomato clades: Solanum pimpinellifolium (PIM), cherry tomato (S. lycopersicum var. cerasiforme) (CER), and S. lycopersicum group (BIG). We investigated the effect of domestication and improvement processes on the structure of the symbiotic microbiome of tomato leaf and fruit pericarp, as well as its genetic basis. We were able to obtain the composition of the symbiotic microbiome of tomato leaf and fruit pericarp, based on which the tomato clade (PIM, CER, or BIG) was predicted with high accuracy through machine learning methods. In the processes of tomato domestication and improvement, changes were observed in the relative abundance of specific bacterial taxa, Bacillus for example, in the tomato leaf and fruit pericarp symbiotic microbiomes, as well as in the function of these symbiotic microbiomes. In addition, SNP loci that were significantly associated with microbial species that are characteristic of tomato leaf were identified. Our results show that domestication and genetic improvement processes alter the symbiotic microbiome structure and function of tomato leaf and fruit pericarp. We propose that leaf and fruit microbiomes are more suitable for revealing changes in symbiotic microbiomes during the domestication process and the underlying genetic basis for these changes due to the exclusion of the influence of environmental factors such as soil types on the microbiome structure.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.

SIGNIFICANCE

Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

Fusobacterium nucleatum is associated with inflammation and poor survival in early-stage HPV-negative tongue cancer

Persistent pathogen infection is a known cause of malignancy, although with sparse systematic evaluation across tumor types. We present a comprehensive landscape of 1060 infectious pathogens across 239 whole exomes and 1168 transcriptomes of breast, lung, gallbladder, cervical, colorectal, and head and neck tumors. We identify known cancer-associated pathogens consistent with the literature. In addition, we identify a significant prevalence of Fusobacterium in head and neck tumors, comparable to colorectal tumors. The Fusobacterium-high subgroup of head and neck tumors occurs mutually exclusive to human papillomavirus, and is characterized by overexpression of miRNAs associated with inflammation, elevated innate immune cell fraction and nodal metastases. We validate the association of Fusobacterium with the inflammatory markers IL1B, IL6 and IL8, miRNAs hsa-mir-451a, hsa-mir-675 and hsa-mir-486-1, and MMP10 in the tongue tumor samples. A higher burden of Fusobacterium is also associated with poor survival, nodal metastases and extracapsular spread in tongue tumors defining a distinct subgroup of head and neck cancer.

Prospects and Challenges of the Study of Anti-Glycan Antibodies and Microbiota for the Monitoring of Gastrointestinal Cancer

Over the past decades, a large amount of data has been accumulated in various subfields of glycobiology. However, much clinically relevant data and many tools are still not widely used in medicine. Synthetic glycoconjugates with the known structure of glycans are an accurate tool for the study of glycan-binding proteins. We used polyacrylamide glycoconjugates (PGs) including PGs with tumour-associated glycans (TAGs) in immunoassays to assess the prognostic potential of the serum level of anti-glycan antibodies (AG Abs) in gastrointestinal cancer patients and found an association of AG Abs with survival. The specificity of affinity-isolated AG Abs was investigated using synthetic and natural glycoconjugates. AG Abs showed mainly a low specificity to tumour-associated and tumour-derived mucins; therefore, the protective role of the examined circulating AG Abs against cancer remains a challenge. In this review, our findings are analysed and discussed in the context of the contribution of bacteria to the AG Abs stimulus and cancer progression. Examples of the influence of pathogenic bacteria colonising tumours on cancer progression and patient survival through mechanisms of interaction with tumours and dysregulated immune response are considered. The possibilities and problems of the integrative study of AG Abs and the microbiome using high-performance technologies are discussed.

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.

Molecular profiling and identification of prognostic factors in Chinese patients with small bowel adenocarcinoma

Small bowel adenocarcinoma (SBA) is a rare malignancy with a poor prognosis and limited treatment options. Despite prior studies, molecular characterization of this disease is not well defined, and little is known regarding Chinese SBA patients. In this study, we conducted multigene next-generation sequencing and 16S ribosomal RNA gene sequencing on samples from 76 Chinese patients with surgically resected primary SBA. Compared with colorectal cancer and Western SBA cohorts, a distinctive genomic profile was revealed in Chinese SBA cohorts. According to the levels of clinical actionability to targetable alterations stratified by OncoKB system, 75% of patients harbored targetable alterations, of which ERBB2, BRCA1/2, and C-KIT mutations were the most common targets of highest-level actionable alterations. In DNA mismatch repair-proficient (pMMR) patients, significant associations between high tumor mutational burden and specific genetic alterations were identified. Moreover, KRAS mutations/TP53 wild-type/nondisruptive mutations (KRAS^mut /TP53^wt/non-dis ) were independently associated with an inferior recurrence-free survival (hazard ratio [HR] = 4.21, 95% confidence interval [CI] = 1.94-9.14, P < .001). The bacterial profile revealed Proteobacteia, Actinobacteria, Firmicutes, Bacteroidetes, Fusobacteria, and Cyanobacteria were the most common phyla in SBA. Furthermore, patients were clustered into three subgroups based on the relative abundance of bacterial phyla, and the distributions of the subgroups were significantly associated with the risk of recurrence stratified by TP53 and KRAS mutations. In conclusion, these findings provided a comprehensive molecular basis for understanding SBA, which will be of great significance in improving the treatment strategies and clinical management of this population.

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.

Current trend and development in bioinformatics research

This is an editorial report of the supplements to BMC Bioinformatics that includes 6 papers selected from the BIOCOMP'19-The 2019 International Conference on Bioinformatics and Computational Biology. These articles reflect current trend and development in bioinformatics research.