Despite the significant progress in diagnosis and treatment over the past years in the understanding of breast cancer pathophysiology, it remains one of the leading causes of mortality worldwide among females. Novel technologies are needed to improve better diagnostic and therapeutic approaches, and to better understand the role of tumor-environment microbiome players involved in the progression of this disease. The gut environment is enriched with over 100 trillion microorganisms, which participate in metabolic diseases, obesity, and inflammation, and influence the response to therapy. In addition to the direct metabolic effects of the gut microbiome, accumulating evidence has revealed that a microbiome also exists in the breast and in breast cancer tissue. This microbiome enriched in the breast environment and the tumor microenvironment may modulate effects potentially associated with carcinogenesis and therapeutic interventions in breast tissue, which to date have not been properly acknowledged. Herein, we review the most recent works associated with the population dynamics of breast microbes and explore the significance of the microbiome on diagnosis, tumor development, response to chemotherapy, endocrine therapy, and immunotherapy. To overcome the low reproducibility of evaluations of tumor-related microbiome, sequencing technical escalation and machine deep learning algorithms may be valid for standardization of assessment for breast-related microbiome and their applications as powerful biomarkers for prognosis and predictive response in the future.

Several studies have indicated that the gut microbiome and tumor microbiota may affect tumors. Emerging metabolomics research illustrates the need to examine the variations in microbial metabolite composition between patients with cancer and healthy individuals. Microbial metabolites can impact the progression of tumors and the immune response by influencing a number of mechanisms, including modulation of the immune system, cancer or immune‑related signaling pathways, epigenetic modification of proteins and DNA damage. Microbial metabolites can also alleviate side effects and drug resistance during chemotherapy and immunotherapy, while effectively activating the immune system to exert tumor immunotherapy. Nevertheless, the impact of microbial metabolites on tumor immunity can be both beneficial and harmful, potentially influenced by the concentration of the metabolites or the specific cancer type. The present review summarizes the roles of various microbial metabolites in different solid tumors, alongside their influence on tumor immunity and treatment. Additionally, clinical trials evaluating the therapeutic effects of microbial metabolites or related microbes on patients with cancer have been listed. In summary, studying microbial metabolites, which play a crucial role in the interaction between the microbiota and tumors, could lead to the identification of new supplementary treatments for cancer. This has the potential to improve the effectiveness of cancer treatment and enhance patient prognosis.

The involvement of glycogenolysis, occurring in astrocytes but not in neurons, in learning is undisputed (Duran et al., JCBFM, in press). According to one school of thought the role of astrocytes for learning is restricted to supply of substrate for neuronal oxidative metabolism. The present ‘perspective’ suggests a more comprehensive and complex role, made possible by lack of glycogen degradation, unless specifically induced by either i) activation of astrocytic receptors, perhaps especially beta-adrenergic, or ii) even small increases in extracellular K+ concentration above its normal resting level. It discusses i) the known importance of glycogenolysis for glutamate formation, requiring pyruvate carboxylation; ii) the established role of K+-stimulated glycogenolysis for K+ uptake in cultured astrocytes, which probably indicates that astrocytes are an integral part of cellular K+ homeostasis in the brain in vivo; and iii) the plausible role of transmitter-induced glycogenolysis, stimulating Na+,K+-ATPase/NKCC1 activity and thereby contributing both to the post-excitatory undershoot in extracellular K+ concentration and the memory-enhancing effect of transmitter-mediated reduction of slow neuronal afterhyperpolarization (sAHP).

Cancer poses a severe threat to human health. Although conventional chemotherapy remains a cornerstone of cancer treatment, its significant side effects and the growing issue of drug resistance necessitate the urgent search for more efficient and less toxic anticancer drugs. In recent years, bacteriocins, antimicrobial peptides of microbial origin, have garnered significant attention due to their targeted antitumor activity. This unique activity is mainly attributed to their cationic and amphiphilic nature, which enables bacteriocins to specifically kill tumor cells without harming normal cells. When involving non-membrane-disrupting mechanisms, such as apoptosis induction, cell cycle blockade, and metastasis inhibition, the core mechanism of action is achieved by disrupting cell membranes, which endows bacteriocins with low drug resistance and high selectivity. However, the susceptibility of bacteriocins to hydrolysis and hemolysis in vivo limits their clinical application. To overcome these challenges, structural optimization of bacteriocins or their combination with nanotechnology is proposed for future development. This review aims to study the mechanism of action and current research status of bacteriocins as anticancer treatments, thus providing new insights for their clinical development and application.

Background: The relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets.Methods: We analyzed 16S rRNA sequencing data from 1,642 gastric biopsy samples and 394 stool samples across 11 independent studies. VSEARCH, QIIME and R packages such as vegan, phyloseq, cooccur, and random forest were used for data processing and analysis. PICRUSt software was employed to predict functions.Results: The α-diversity results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non-Helicobacter pylori (HP) commensals, which are crucial in both HP-negative and HP-positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712).Conclusions: This study examined the intratumoral and fecal microbiota of GC patients from a dual microecological perspective and identified Lactobacillus, Streptococcus, Roseburia, Faecalibacterium and Phascolarctobacterium as intratumoral and intestinal-specific co-differential bacteria. Furthermore, it confirmed the validity of the combination of Lactobacillus and Streptococcus as GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC.