Microbiome in human cancers

Causal Association Between Microbiome and Oral-Oropharyngeal Cancer: A Mendelian Randomization Study

INTRODUCTION AND AIMS

This study aimed to examine the causal link between oral microbiome and the risk of oral and oropharyngeal squamous cell carcinoma (OOPSCC) using Mendelian randomization (MR).

METHODS

Utilizing single nucleotide polymorphisms as instrumental variables, we applied the MR inverse-variance weighted approach to assess the impact of salivary and tongue microbiome on OOPSCC. The data were obtained from the CNGBdb database and the UK Biobank, and analytical procedures were performed using the R package 'TwoSampleMR'. To ensure the robustness of our findings, we conducted sensitivity studies, which included the MR-Egger intercept test, to establish strong correlations and eliminate the phenomenon of horizontal pleiotropy.

RESULT

Our large-scale MR study revealed a genetically predisposed causal relationship between 13 microbial taxa, each from saliva and tongue, with OOPSCC. Notably, microbial taxa from six genera, including Prevotella, Neisseria, Veillonella, Granulicatella, Treponema, and Streptococcus, in both salivary and tongue microbiomes, showed this relationship. Conversely, several taxa, including Hemophilus, Solobacterium, Campylobacter, and Porphyromonas, predominantly demonstrated an inverse relationship, suggesting a protective effect. The robustness of our findings was further confirmed through sensitivity analyses, providing additional confidence in our results.

CONCLUSION

Our MR study indicates that the oral microbiota has a significant causal impact on the risk of oral and oropharyngeal cancers. The microbial biomarkers we identified, which are linked to OOPSCC, have the potential to uncover the underlying mechanisms and pave the way for new therapeutic approaches for targeted treatment of these malignancies.

A comprehensive analysis of the uterine microbiome in endometrial cancer patients - identification of Anaerococcus as a potential biomarker and carcinogenic cofactor

Introduction

Endometrial cancer (EC) is a significant gynecological malignancy with increasing incidence worldwide. Emerging evidence highlights the role of the uterine microbiome in the pathogenesis of EC. This study aims to characterize the uterine microbiome in EC patients and identify potential microbial biomarkers, with a focus on Anaerococcus as a differentiating taxon.

Methods

The endocervical canal swabs from patients with EC (n=16) and non-cancerous patients (EM, n=13) were collected. The V3-V4 region of the 16S rRNA gene was sequenced using the Illumina platform. Bioinformatic analyses were performed with QIIME2, and statistical comparisons were conducted to assess differences in microbial composition and diversity. In vitro experiments were conducted to assess the functional impact of Anaerococcus on human uterine fibroblasts, including its ability to adhere to the human cells and induce oxidative stress.

Results

The α-diversity metrics, including Shannon entropy and observed amplicon sequence variants (ASVs), revealed significantly higher microbial diversity in EC samples compared to EM. Anaerococcus was identified as a key taxon differentiating EC from EM groups, showing a higher relative abundance in EC samples. Functional predictions and in vitro assays indicated that Anaerococcus may contribute to carcinogenesis by inducing reactive oxygen species (ROS) production, and has the high ability to adhere to the human endometrial fibroblasts.

Discussion

The study provides evidence of distinct microbial signatures in EC, with Anaerococcus emerging as a potential biomarker. The in vitro findings suggest its role in endometrial carcinogenesis, underscoring its potential as a target for future diagnostic and therapeutic applications.

The elusive male microbiome: revealing the link between the genital microbiota and fertility. Critical review and future perspectives

There is a growing focus on understanding the role of the male microbiome in fertility issues. Although research on the bacterial communities within the male reproductive system is in its initial phases, recent discoveries highlight notable variations in the microbiome's composition and abundance across distinct anatomical regions like the skin, foreskin, urethra, and coronary sulcus. To assess the relationship between male genitourinary microbiome and reproduction, we queried various databases, including MEDLINE (available via PubMed), SCOPUS, and Web of Science to obtain evidence-based data. The literature search was conducted using the following terms "gut/intestines microbiome," "genitourinary system microbiome," "microbiome and female/male infertility," "external genital tract microbiome," "internal genital tract microbiome," and "semen microbiome." Fifty-one relevant papers were analyzed, and eleven were strictly semen quality or male fertility related. The male microbiome, especially in the accessory glands like the prostate, seminal vesicles, and bulbourethral glands, has garnered significant interest because of its potential link to male fertility and reproduction. Studies have also found differences in bacterial diversity present in the testicular tissue of normozoospermic men compared to azoospermic suggesting a possible role of bacterial dysbiosis and reproduction. Correlation between the bacterial taxa in the genital microbiota of sexual partners has also been found, and sexual activity can influence the composition of the urogenital microbiota. Exploring the microbial world within the male reproductive system and its influence on fertility opens doors to developing ways to prevent, diagnose, and treat infertility. The present work emphasizes the importance of using consistent methods, conducting long-term studies, and deepening our understanding of how the reproductive tract microbiome works. This helps make research comparable, pinpoint potential interventions, and smoothly apply microbiome insights to real-world clinical practices.

Diabetic Patient with CA-MRSA Pneumonia and Plasma Cell Neoplasm: A Case Report of Severe Complications and Prognosis

BACKGROUND The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) has been increasing in recent years, becoming a cause of community-acquired infection. Interestingly, its role in malignancy recently started to be considered after a noticed increase in reported cases and studies discussing the potential association. CASE REPORT In the present case, the patient had known and uncontrolled diabetes mellitus and a history of multiple abscesses that were previously treated by incision and drainage. The patient received a diagnosis of severe pneumonia, and MRSA was found in blood cultures. Further tests for HIV, hemagglutinin type 1, and neuraminidase type 1 (H1N1) were negative. The D test was also performed for macrolide-inducible resistance and was negative, indicating the need for intravenous administration of clindamycin. An echocardiogram ruled out endocarditis. Subsequently, the patient experienced progressive back pain and weakness involving the lower limbs. A pathological fracture was discovered, along with nerve root compression. An urgent posterior spine fixation was then performed by a neurosurgeon. A biopsy was collected at the site of the pathological fracture, and histopathological tests indicated a plasma cell neoplasm. CONCLUSIONS MRSA is known to cause serious and dangerous infections, including necrotizing pneumonia. Furthermore, a link between MRSA and plasma cell dyscrasia has been considered in several reports. This necessitates the need for further studies to clarify this hidden association, which may help in the course and prognosis of these patients.

iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers

BACKGROUND

The development of precision medicine is essential for personalized treatment and improved clinical outcome, whereas biomarkers are critical for the success of precision therapies.

AIM

To investigate whether iCEMIGE (integration of CEll-morphometrics, MIcro biome, and GEne biomarker signatures) improves risk stratification of breast cancer (BC) patients.

METHODS

We used our recently developed machine learning technique to identify cellular morphometric biomarkers (CMBs) from the whole histological slide images in The Cancer Genome Atlas (TCGA) breast cancer (TCGA-BRCA) cohort. Multivariate Cox regression was used to assess whether cell-morphometrics prognosis score (CMPS) and our previously reported 12-gene expression prognosis score (GEPS) and 15-microbe abundance prognosis score (MAPS) were independent prognostic factors. iCEMIGE was built upon the sparse representation learning technique. The iCEMIGE scoring model performance was measured by the area under the receiver operating characteristic curve compared to CMPS, GEPS, or MAPS alone. Nomogram models were created to predict overall survival (OS) and progress-free survival (PFS) rates at 5- and 10-year in the TCGA-BRCA cohort.

RESULTS

We identified 39 CMBs that were used to create a CMPS system in BCs. CMPS, GEPS, and MAPS were found to be significantly independently associated with OS. We then established an iCEMIGE scoring system for risk stratification of BC patients. The iGEMIGE score has a significant prognostic value for OS and PFS independent of clinical factors (age, stage, and estrogen and progesterone receptor status) and PAM50-based molecular subtype. Importantly, the iCEMIGE score significantly increased the power to predict OS and PFS compared to CMPS, GEPS, or MAPS alone.

CONCLUSION

Our study demonstrates a novel and generic artificial intelligence framework for multimodal data integration toward improving prognosis risk stratification of BC patients, which can be extended to other types of cancer.