Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The impact of the human microbiome, the diverse collection of microorganisms that inhabit nearly every niche in the human body, in shaping the immune response to dysbiotic events is apparent if poorly understood, particularly in complex, evolving disease states such as breast cancer. The impacts can be both indirect via metabolites and immune-interactions along the skin, gut, and oral cavities where the microbial communities are most abundant, or direct in the tumor microenvironment where microbial activities can promote growth or clearance of cancerous cells. Based on reports of using gut microbial signatures to predict therapeutic efficacy, the role that gut microbes and their metabolites may play in shaping the success or failure of immunotherapy has been extensively reviewed. In this review, we dissect the evidence for the direct and distal impact of microbes on oncogenesis, tumor growth and the immune responses to combat or promote tolerance of breast cancer tumors. Implementation of robust, valid analyses and methods are lacking in the field, and we provide recommendations for researchers and clinicians to work together to characterize the micro-biome-immune-breast cancer interactions that will hopefully enable the next generation of biomarkers and targets for improving disease outcomes.

Download full-text PDF

Source
http://dx.doi.org/10.1615/CritRevImmunol.2022043153DOI Listing

Publication Analysis

Top Keywords

breast cancer
12
potential immune-microbiome
4
immune-microbiome interactions
4
interactions breast
4
cancer
4
cancer advance
4
advance treatment
4
treatment what's
4
what's holding
4
holding back?
4

Similar Publications

Purpose: Breast cancer remains a significant public health challenge globally, as well as in India, where it is the most frequently diagnosed cancer in females. Significant disparities in incidence, mortality, and access to health care across India's sociodemographically diverse population highlight the need for increased awareness, policy reform, and research.

Design: This review consolidates data from national cancer registries, global cancer databases, and institutional findings from a tertiary care center to examine the epidemiology, clinical challenges, and management gaps specific to India.

View Article and Find Full Text PDF

ObjectiveTo study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists.MethodsIn a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a €1 additional running cost of AI instead of the €3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice.

View Article and Find Full Text PDF

Background: Among childhood cancer survivors, germline rare variants in autosomal dominant cancer susceptibility genes (AD CSGs) could increase subsequent neoplasm (SNs) risks, but risks for rarer SNs and by age at onset are not well understood.

Methods: We pooled the Childhood Cancer Survivor Study and St Jude Lifetime Cohort (median follow-up = 29.7 years, range 7.

View Article and Find Full Text PDF

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.

View Article and Find Full Text PDF

Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.

Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.

View Article and Find Full Text PDF