Integrated analysis of microbiota and gut microbial metabolites in blood for breast cancer.

Gut microbiota and associated metabolites have been linked to breast carcinogenesis. Evidences demonstrate blood microbiota primarily originates from the gut and may act as a biomarker for breast cancer. We aimed to characterize the microbiota-gut microbial metabolites cross-talk in blood and develop a composite diagnostic panel for breast cancer. We performed 16S rRNA gene sequencing and metabolomics profiling on blood samples from 107 breast cancer cases and 107 age-paired controls. We found that the alpha diversity of the blood microbiota was decreased in breast cancer compared to controls. There were significantly different profiles of microbiota and gut microbial metabolites in blood between these two groups, with nine bacterial genera and four gut microbial metabolites increased in patients, while thirty-nine bacterial genera and two gut microbial metabolites increased in controls. Some breast cancer-associated gut microbial metabolites were linked to differential blood microbiota, and a composite microbiota-metabolite diagnostic panel was further developed with an area under the curve of 0.963 for breast cancer. This study underscored the pivotal role of microbiota and gut microbial metabolites in blood and their interactions for breast carcinogenesis, as well as the potential of a composite diagnostic panel as a non-invasive biomarker for breast cancer.IMPORTANCEOur integrated analysis demonstrated altered profiles of microbiota and gut microbial metabolites in blood for breast cancer patients. The extensive correlation between microbiota and gut microbial metabolites in blood assisted the understanding of the pathogenesis of breast cancer. The good performance of a composite microbiota-gut microbial metabolites panel in blood suggested a non-invasive approach for breast cancer detection and a novel strategy for better diagnosis and prevention of breast cancer in the future.

EAT-Lancet Diet Pattern, Genetic Predisposition, Inflammatory Biomarkers, and Risk of Lung Cancer Incidence and Mortality.

SCOPE: The association between a planetary and sustainable EAT-Lancet diet and lung cancer remains inconclusive, with limited exploration of the role of genetic susceptibility and inflammation. METHODS AND RESULTS: The study includes 175 214 cancer-free participants in the UK Biobank. Fourteen food components are collected from a 24-h dietary recall questionnaire. A polygenic risk score is constructed through capturing the overall risk variants for lung cancer. Sixteen inflammatory biomarkers are assayed in blood samples. Participants with the highest EAT-Lancet diet scores (≥12) have a lower risk of lung cancer incidence (hazard ratio [HR] = 0.64, 95% confidence interval [CI]: 0.51-0.80) and mortality (HR = 0.65, 95% CI: 0.48-0.88), compared to those with the lowest EAT-Lancet diet scores (≤8). Interestingly, there is a significantly protective trend against both lung adenocarcinoma and lung squamous cell carcinoma with higher EAT-Lancet diet scores. Despite no significant interactions, a risk reduction trend for lung cancer is observed with increasing EAT-Lancet diet scores and decreasing genetic risk. Ten inflammatory biomarkers partially mediate the association between the EAT-Lancet diet and lung cancer risk. CONCLUSION: The study depicts a lower risk of lung cancer conferred by the EAT-Lancet diet associated with lower inflammation levels among individuals with diverse genetic predispositions.

Sex disparity in the association between metabolic-anthropometric phenotypes and risk of obesity-related cancer: a prospective cohort study.

BACKGROUND: Sex disparity between metabolic-obesity (defined by body mass index, BMI) phenotypes and obesity-related cancer (ORC) remains unknown. Considering BMI reflecting overall obesity but not fat distribution, we aimed to systematically assess the association of our newly proposed metabolic-anthropometric phenotypes with risk of overall and site-specific ORC by sex. METHODS: A total of 141,579 men (mean age: 56.37 years, mean follow-up time: 12.04 years) and 131,047 women (mean age: 56.22 years, mean follow up time: 11.82 years) from the UK Biobank was included, and designated as metabolic-anthropometric phenotypes based on metabolic status (metabolically healthy/unhealthy), BMI (non-obesity/obesity) and body shape (pear/slim/apple/wide). The sex-specific association of different phenotypes with overall and site-specific ORC was assessed by hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression models. RESULTS: We found metabolically unhealthy and/or obesity phenotypes conveyed a higher risk in men than in women for overall ORC and colorectal cancer compared with metabolically healthy non-obesity phenotype (Pinteraction < 0.05). Of note, metabolically healthy obesity phenotype contributed to increased risks of most ORC in men (HRs: 1.58 ~ 2.91), but only correlated with higher risks of endometrial (HR = 1.89, 95% CI: 1.54-2.32) and postmenopausal breast cancers (HR = 1.17, 95% CI: 1.05-1.31) in women. Similarly, even under metabolically healthy, men carrying apple and wide shapes phenotypes (metabolically healthy apple/wide and metabolically healthy non-obesity apple/wide) suffered an increased risk of ORC (mainly colorectal, liver, gastric cardia, and renal cancers, HRs: 1.20 ~ 3.81) in comparison with pear shape or non-obesity pear shape. CONCLUSIONS: There was a significant sex disparity between metabolic-anthropometric phenotypes and ORC risk. We advised future ORC prevention and control worth taking body shape and sex disparity into account.