It is a well-known fact that cancer is considered the second leading cause of mortality across the globe. Although the human oral cavity and intestine are the natural habitat of thousands of microbes, dysbiosis results in malignancies, such as oral squamous cell carcinoma and colorectal cancer. Amongst the intestinal microbes, H. pylori is a deadly carcinogen. Also, causative pathogens for the development of pancreatic and colorectal cancer are found in the oral cavity, such as Fusobacterium nucleatum and Porphyromonas gingivalis. Many periodontopathic micro- organisms, like Streptococcus sp., Peptostreptococcus sp., Prevotella sp., Fusobacterium sp., Porphyromonas gingivalis, and Capnocytophaga gingivalis, strongly have an impact on the development of oral cancers. Three basic mechanisms are involved in pathogen-mediated cancer development, like chronic inflammation-mediated angiogenesis, inhibition of cellular apoptosis, and release of carcinogenic by-products. Microbiota has a dichotomous role to play in cancer, i.e., microbiota can be used for cancer management too. Shreds of evidence are there to support the fact that microbiota enhances the chemotherapeutic drug efficacy. This review presents the possible mechanism of the oncogenic effect of microbiota with emphasis on the oral microbiome and also attempts to explain the intricate role of microbiota in cancer management.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.2174/0115680096282503240124104029 | DOI Listing |
Front Oncol
December 2024
Department of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan, China.
Introduction: Despite the established influence of gut bacteria, the role of the gut virome in modulating colorectal cancer (CRC) patient chemotherapy response remains poorly understood. In this study, we investigated the impact of antiviral (AV) drug-induced gut virome dysbiosis on the efficacy of 5-FU in CRC treatment.
Methods: Using a subcutaneous CRC mouse model, we assessed tumor growth and immune responses following AV treatment, fecal microbiota transplantation (FMT), and 5-FU administration.
EXCLI J
December 2024
Department of Dentistry, Center for Education and Research on Dental Implants (CEPID), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil.
J Transl Med
January 2025
Department of Psychiatry and Psychotherapy, University Medical Center Mainz, 55131, Mainz, Germany.
Background: Recent research indicates a role of gut microbiota in development and progression of life-threatening diseases such as cancer. Carcinomas of the biliary ducts, the so-called cholangiocarcinomas, are known for their aggressive tumor biology, implying poor prognosis of affected patients. An impact of the gut microbiota on cholangiocarcinoma development and progression is plausible due to the enterohepatic circulation and is therefore the subject of scientific debate, however evidence is still lacking.
View Article and Find Full Text PDFAmino Acids
January 2025
Laboratory of Molecular Biology and Immunology, Department of Pharmacy, University of Patras, 26500, Rio-Patras, Greece.
Taurine, although not a coding amino acid, is the most common free amino acid in the body. Taurine has multiple and complex functions in protecting mitochondria against oxidative-nitrosative stress. In this comprehensive review paper, we introduce a novel potential role for taurine in protecting from deuterium (heavy hydrogen) toxicity.
View Article and Find Full Text PDFBrain Res Bull
January 2025
School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou 510006, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan. Electronic address:
The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these studies ignored the cooperative interactions and topological attributes of multi-omics networks. In this study, we constructed three types of brain graphs (BGs), three types of gut graphs (GGs), and nine types of brain-gut combined graphs (BGCGs) for each individual. We proposed a novel methodology of multi-omics graph convolutional network (MO-GCN) with an attention mechanism to construct a classification model by integrating all BGCGs.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!