Early Detection of Colon Cancer Following Incidental Finding of Clostridium septicum Bacteremia

A novel bi-directional heterogeneous network selection method for disease and microbial association prediction

Microorganisms in the human body have a great impact on human health. Therefore, mastering the potential relationship between microorganisms and diseases is helpful to understand the pathogenesis of diseases and is of great significance to the prevention, diagnosis, and treatment of diseases. In order to predict the potential microbial disease relationship, we propose a new computational model. Firstly, a bi-directional heterogeneous microbial disease network is constructed by integrating multiple similarities, including Gaussian kernel similarity, microbial function similarity, disease semantic similarity, and disease symptom similarity. Secondly, the neighbor information of the network is learned by random walk; Finally, the selection model is used for information aggregation, and the microbial disease node pair is analyzed. Our method is superior to the existing methods in leave-one-out cross-validation and five-fold cross-validation. Moreover, in case studies of different diseases, our method was proven to be effective.

Predicting Microbe-Disease Association Based on Multiple Similarities and LINE Algorithm

Numerous microbes have been found to have vital impacts on human health through affecting biological processes. Therefore, exploring potential associations between microbes and diseases will promote the understanding and diagnosis of diseases. In this study, we present a novel computational model, named MSLINE, to infer potential microbe-disease associations by integrating Multiple Similarities and Large-scale Information Network Embedding (LINE) based on known associations. Specifically, on the basis of known microbe-disease associations from the Human Microbe-Disease Association Database, we first increase the known associations by collecting proven associations from existing literatures. We then construct a microbe-disease heterogeneous network (MDHN) by integrating known associations and multiple similarities (including Gaussian interaction profile kernel similarity, microbe function similarity, disease semantic similarity and disease-symptom similarity). After that, we implement random walk and LINE algorithm on MDHN to learn its structure information. Finally, we score the microbe-disease associations according to the structure information for every nodes. In the Leave-one-out cross validation and 5-fold cross validation, MSLINE performs better compared to other existing methods. Moreover, case studies of different diseases proved that MSLINE could predict the potential microbe-disease associations efficiently.

Diagnostic and Therapeutic Uses of the Microbiome in the Field of Oncology

Cancer is a leading cause of death worldwide and it can affect almost every part of the human body. Effective screening and early diagnosis of cancers is extremely difficult due to the multifactorial etiology of the disease and delayed presentation of the patients. The available treatments are usually not specific to the affected organ system, leading to intolerable systemic side effects and early withdrawal from therapies. In vivo and in vitro studies have revealed an association of specific microbiome signatures with individual cancers. The cancer-related human microbiome has also been shown to affect the response of tissues to chemotherapy, immunotherapy, and radiation. This is an excellent opportunity for us to design specific screening markers using the microbiome to prevent cancers and diagnose them early. We can also develop precise treatments that can target cancer-affected specific organ systems and probably use a lesser dose of chemotherapy or radiation for the same effect. This prevents adverse effects and early cessation of treatments. However, we need further studies to exactly clarify and characterize these associations. In this review article, we focus on the association of the microbiome with individual cancers and highlight its future role in cancer screenings, diagnosis, prognosis, and treatments.

Bacteria-Cancer Interface: Awaiting the Perfect Storm

Epidemiological evidence reveal a very close association of malignancies with chronic inflammation as a result of persistent bacterial infection. Recently, more studies have provided experimental evidence for an etiological role of bacterial factors disposing infected tissue towards carcinoma. When healthy cells accumulate genomic insults resulting in DNA damage, they may sustain proliferative signalling, resist apoptotic signals, evade growth suppressors, enable replicative immortality, and induce angiogenesis, thus boosting active invasion and metastasis. Moreover, these cells must be able to deregulate cellular energetics and have the ability to evade immune destruction. How bacterial infection leads to mutations and enriches a tumour-promoting inflammatory response or micro-environment is still not clear. In this review we showcase well-studied bacteria and their virulence factors that are tightly associated with carcinoma and the various mechanisms and pathways that could have carcinogenic properties.

Human Gut Microbiota-associated Gastrointestinal Malignancies: A Comprehensive Review

The human gastrointestinal tract houses trillions of microbes. The gut and various types of microorganisms, including bacteria, viruses, fungi, and archaea, form a complex ecosystem known as the gut microbiota, and the whole genome of the gut microbiota is referred to as the gut microbiome. The gut microbiota is essential for homeostasis and the overall well-being of a person and is increasingly considered an adjunct "virtual organ," with a complexity level comparable to that of the other organ systems. The gut microbiota plays an essential role in nutrition, local mucosal homeostasis, inflammation, and the mucosal immune system. An imbalanced state of the gut microbiota, known as dysbiosis, can predispose to development of various gastrointestinal malignancies through three speculated pathogenic mechanisms: (a) direct cytotoxic effects with damage to the host DNA, (b) disproportionate proinflammatory signaling inducing inflammation, and (c) activation of tumorigenic pathways or suppression of tumor-suppressing pathways. Several microorganisms, including Helicobacter pylori, Epstein-Barr virus, human papillomavirus, Mycoplasma species, Escherichia coli, and Streptococcus bovis, are associated with gastrointestinal malignancies such as esophageal adenocarcinoma, gastric adenocarcinoma, gastric mucosa-associated lymphoid tissue lymphoma, colorectal adenocarcinoma, and anal squamous cell carcinoma. Imaging plays a pivotal role in diagnosis and management of microbiota-associated gastrointestinal malignancies. Appropriate use of probiotics, fecal microbiota transplantation, and overall promotion of the healthy gut are ongoing areas of research for prevention and treatment of malignancies. Online supplemental material is available for this article. ^©RSNA, 2021.

Growth rate alterations of human colorectal cancer cells by 157 gut bacteria

Several bacteria in the human gut microbiome have been associated with colorectal cancer (CRC) by high-throughput screens. In some cases, molecular mechanisms have been elucidated that drive tumorigenesis, including bacterial membrane proteins or secreted molecules that interact with the human cancer cells. For most gut bacteria, however, it remains unknown if they enhance or inhibit cancer cell growth. Here, we screened bacteria-free supernatants (secretomes) and inactivated cells of over 150 cultured bacterial strains for their effects on cell growth. We observed family-level and strain-level effects that often differed between bacterial cells and secretomes, suggesting that different molecular mechanisms are at play. Secretomes of Bacteroidaceae, Enterobacteriaceae, and Erysipelotrichaceae bacteria enhanced cell growth, while most Fusobacteriaceae cells and secretomes inhibited growth, contrasting prior findings. In some bacteria, the presence of specific functional genes was associated with cell growth rates, including the virulence genes TcdA, TcdB in Clostridiales and FadA in Fusobacteriaceae, which both inhibited growth. Bacteroidaceae cells that enhanced growth were enriched for genes of the cobalamin synthesis pathway, while Fusobacteriaceae cells that inhibit growth were enriched for genes of the ethanolamine utilization pathway. Together, our results reveal how different gut bacteria have wide-ranging effects on cell growth, contribute a better understanding of the effects of the gut microbiome on host cells, and provide a valuable resource for identifying candidate target genes for potential microbiome-based diagnostics and treatment strategies.

Clostridium perfringens enterotoxin induces claudin-4 to activate YAP in oral squamous cell carcinomas

Claudin (CLDN)-4 expression has been associated with malignancy in various cancers. When CLDN4 expression was examined in oral squamous cell carcinoma (OSCC), 22 out of 57 (39%) cases showed immunoreactivity in the nucleus. Nuclear CLDN4-positive cases showed a stronger correlation with cancer progression than the negative cases. Intratumoral anaerobic bacterial DNA examination revealed nuclear CLDN4 expression in 81% of Clostridium perfringens-positive cases. Treatment of human oral squamous cell carcinoma cell lines HSC3 and HSC4 with Clostridium perfringens enterotoxin (CPE), induced CLDN4 nuclear translocation to enhance epithelial-mesenchymal transition (EMT), stemness, cell proliferation and invasive ability. In addition, CPE treatment suppressed phosphorylation of yes-associated protein-1 (YAP1) and promoted YAP1 nuclear translocation, resulting in increased expression of YAP1 target genes; cyclin D1 and connective tissue growth factor. Moreover, it was revealed that the complex of YAP1, CLDN4 and zona occludens-2 (ZO-2) was formed by CPE treatment, further suppressing YAP1 phosphorylation by LATS1 and activating it. Thus YAP activation in OSCC was regarded important in promoting malignant phenotypes. Our research suggested that the control of oral anaerobic bacteria may suppress YAP activation and in turn tumor progression.