Helicobacter pylori was not detected in oral squamous cell carcinomas from cohorts of Norwegian and Nepalese patients

Pandey, Sushma; Follin-Arbelet, Benoit; Pun, Chin Bahadur; Gautam, Dej Kumar; Johannessen, Anne Christine; Petersen, Fernanda Cristina; Costea, Daniela Elena; Sapkota, Dipak

doi:10.1038/s41598-020-65694-7

Cited by 6 publications

(4 citation statements)

References 37 publications

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“…Although there has been a recent surge in global studies on oral microbiome, its dysbiosis, and its association with oral cancer and gut microbiome ( Ahn et al., 2012 ; Shillitoe, 2018 ), only a limited number of studies have been reported from the developing countries ( Acharya et al., 2017 ; Batool et al., 2020 ; Nolan-Kenney et al., 2020 ; Pandey et al., 2020 ; Rai et al., 2021 ). Importantly, it is much needed to decipher the dysbiosis in oral microbiome due to the consumption of smokeless-tobacco-based products and their association with oral cancer.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Effect of Smokeless Tobacco Consumption on Oral Microbiome in Healthy and Oral Cancer Patients

Saxena

Gupta

et al. 2022

Front. Cell. Infect. Microbiol.

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Oral cancer is a globally widespread cancer that features among the three most prevalent cancers in India. The risk of oral cancer is elevated by factors such as tobacco consumption, betel-quid chewing, excessive alcohol consumption, unhygienic oral condition, sustained viral infections, and also due to dysbiosis in microbiome composition of the oral cavity. Here, we performed an oral microbiome study of healthy and oral cancer patients to decipher the microbial dysbiosis due to the consumption of smokeless-tobacco-based products and also revealed the tobacco-associated microbiome. The analysis of 196 oral microbiome samples from three different oral sites of 32 healthy and 34 oral squamous cell carcinoma (OSCC) patients indicated health status, site of sampling, and smokeless tobacco consumption as significant covariates associated with oral microbiome composition. Significant similarity in oral microbiome composition of smokeless-tobacco-consuming healthy samples and OSCC samples inferred the possible role of smokeless tobacco consumption in increasing inflammation-associated species in oral microbiome. Significantly higher abundance of Streptococcus was found to adequately discriminate smokeless-tobacco-non-consuming healthy samples from smokeless-tobacco-consuming healthy samples and contralateral healthy site of OSCC samples from the tumor site of OSCC samples. Comparative analysis of oral microbiome from another OSCC cohort also confirmed Streptococcus as a potential marker for healthy oral microbiome. Gram-negative microbial genera such as Prevotella, Capnocytophaga, and Fusobacterium were found to be differentially abundant in OSCC-associated microbiomes and can be considered as potential microbiome marker genera for oral cancer. Association with lipopolysaccharide (LPS) biosynthesis pathway further confirms the differential abundance of Gram-negative marker genera in OSCC microbiomes.

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Section: Introductionmentioning

confidence: 99%

Assessing the Effect of Smokeless Tobacco Consumption on Oral Microbiome in Healthy and Oral Cancer Patients

Saxena

Gupta

et al. 2022

Front. Cell. Infect. Microbiol.

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“…Furthermore, other genera such as Helicobacter , Lactobacillus , and Fusobacterium were also identified as significant when discriminating HNSC, STAD, and ESCA cancer samples. While Helicobacter has been associated with head and neck cancer 29 , its presence in these tumors is controverse 30 . In the case of gastric cancer, however, there is no doubt on the causal relationship between Helicobacter (pylori) and non-cardia gastric cancer 31 .…”

Section: Resultsmentioning

confidence: 99%

Machine learning-based approaches for cancer prediction using microbiome data

Freitas

Silva

Sousa

et al. 2023

Sci Rep

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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.

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“…= -0.191, P = 0.012). Regardless of race, lifestyle and habitual risk factors, the absence of H. pylori in the available OSCC cohorts indicates that H. pylori is unlikely to contribute to OSCC pathogenesis[ 18 ].…”

Section: Oral Cancermentioning

confidence: 99%

Effects ofHelicobacter pyloriinfection in gastrointestinal tract malignant diseases: From the oral cavity to rectum

Kuo¹,

Yu²,

Wang³

et al. 2022

WJGO

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Helicobacter pylori ( H. pylori ) has infected approximately fifty percent of humans for a long period of time. However, improvements in the public health environment have led to a decreased chance of H. pylori infection. However, a high infection rate is noted in populations with a high incidence rate of gastric cancer (GC). The worldwide fraction of GC attributable to H. pylori is greater than 85%, and a high H. pylori prevalence is noted in gastric mucosa-associated lymphoid tissue lymphoma patients. These results indicate that the majority of GC cases can be prevented if H. pylori infection is eliminated. Because H. pylori exhibits oral-oral or fecal-oral transmission, the relationship between this microorganism and other digestive tract malignant diseases has also attracted attention. This review article provides an overview of H. pylori and the condition of the whole gastrointestinal tract environment to further understand the correlation between the pathogen and the host, thus allowing improved realization of disease presentation.

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Helicobacter pylori was not detected in oral squamous cell carcinomas from cohorts of Norwegian and Nepalese patients

Cited by 6 publications

References 37 publications

Assessing the Effect of Smokeless Tobacco Consumption on Oral Microbiome in Healthy and Oral Cancer Patients

Assessing the Effect of Smokeless Tobacco Consumption on Oral Microbiome in Healthy and Oral Cancer Patients

Machine learning-based approaches for cancer prediction using microbiome data

Effects ofHelicobacter pyloriinfection in gastrointestinal tract malignant diseases: From the oral cavity to rectum

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