Microbial communities and human cells, through a dynamic crosstalk, maintain a mutualistic relationship that contributes to the maintenance of cellular metabolism and of the immune and neuronal systems. This dialogue normally occurs through the production and regulation of hormonal intermediates, metabolites, secondary metabolites, proteins, and toxins. When the balance between host and microbiota is compromised, the dynamics of this relationship change, creating favorable conditions for the development of diseases, including cancers. Microbiome metabolites can be important modulators of the tumor microenvironment contributing to regulate inflammation, proliferation, and cell death, in either a positive or negative way. Recent studies also highlight the involvement of microbiota metabolites in inducing epithelial–mesenchymal transition, thus favoring the setup of the metastatic niche. An investigation of microbe-derived metabolites in “liquid” human samples, such as plasma, serum, and urine, provide further information to clarify the relationship between host and microbiota.

β-catenin plays an important role as regulatory hub in several cellular processes including cell adhesion, metabolism, and epithelial mesenchymal transition. This is mainly achieved by its dual role as structural component of cadherin-based adherens junctions, and as a key nuclear effector of the Wnt pathway. For this dual role, different classes of proteins are differentially regulated via β-catenin dependent mechanisms. Here, we applied a liquid chromatography-mass spectrometry (LC-MS/MS) approach to identify proteins modulated after β-catenin knockdown in the breast cancer cell line MCF-7. We used a label free analysis to compare trypsin-digested proteins from CTR (shCTR) and β-catenin knockout cells (shβcat). This led to the identification of 98 differentially expressed proteins, 53 of them were up-regulated and 45 down-regulated. Loss of β-catenin induced morphological changes and a significant modulation of the expression levels of proteins associated with primary metabolic processes. In detail, proteins involved in carbohydrate metabolism and tricarboxylic acid cycle were found to be down-regulated, whereas proteins associated to lipid metabolism were found up-regulated in shβcat compared to shCTR. A loss of mitochondrial mass and membrane potential was also assessed by fluorescent probes in shβcat cells with respect to the controls. These data are consistent with the reduced expression of transcriptional factors regulating mitochondrial biogenesis detected in shβcat cells. β-catenin driven metabolic reprogramming resulted also in a significant modulation of lipogenic enzyme expression and activity. Compared to controls, β-catenin knockout cells showed increased incorporation of [1-¹⁴C]acetate and decreased utilization of [U-¹⁴C]glucose for fatty acid synthesis. Our data highlight a role of β-catenin in the regulation of metabolism and energy homeostasis in breast cancer cells.

With the advent of novel molecular platforms for high-throughput/next-generation sequencing, the communities of commensal and pathogenic microorganisms that inhabit the human body have been defined in depth. In the last decade, the role of microbiota-host interactions in driving human cancer plasticity and malignant progression has been well documented. Germ-free preclinical models provided an invaluable tool to demonstrate that the human microbiota can confer susceptibility to various types of cancer and can also modulate the host response to therapeutic treatments. Of interest, besides the detrimental effects of dysbiosis on cancer etiopathogenesis, specific microorganisms have been shown to exert protective activities against cancer growth. This has strong clinical implications, as restoration of the physiologic microbiota is being rapidly implemented as a novel anticancer therapeutic strategy. Here, we reviewed past and recent literature depicting the role of microbiota-host interactions in modulating key molecular mechanisms that drive human cancer plasticity and lead to malignant progression. We analyzed microbiota-host interactions occurring in the gut as well as in other anatomic sites, such as oral and nasal cavities, lungs, breast, esophagus, stomach, reproductive tract, and skin. We revealed a common ground of biological alterations and pathways modulated by a dysbiotic microbiota and potentially involved in the control of cancer progression. The molecular mechanisms most frequently affected by the pathogenic microorganisms to induce malignant progression involve epithelial-mesenchymal transition- (EMT-) dependent barrier alterations and tumor-promoting inflammation. This evidence may pave the way to better stratify high-risk cancer patients based on unique microenvironmental/microbial signatures and to develop novel, personalized, biological therapies.

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia associated with alterations in carbohydrate, lipid, and protein metabolism. The prognosis of T2DM patients is highly dependent on the development of complications, and therefore the identification of biomarkers of T2DM progression, with minimally invasive techniques, is a huge need. In the present study, we applied a ¹H-Nuclear Magnetic Resonance (¹H-NMR)-based metabolomic approach coupled with multivariate data analysis to identify serum metabolite profiles associated with T2DM development and progression. To perform this, we compared the serum metabolome of non-diabetic subjects, treatment-naïve non-complicated T2DM patients, and T2DM patients with complications in insulin monotherapy. Our analysis revealed a significant reduction of alanine, glutamine, glutamate, leucine, lysine, methionine, tyrosine, and phenylalanine in T2DM patients with respect to non-diabetic subjects. Moreover, isoleucine, leucine, lysine, tyrosine, and valine levels distinguished complicated patients from patients without complications. Overall, the metabolic pathway analysis suggested that branched-chain amino acid (BCAA) metabolism is significantly compromised in T2DM patients with complications, while perturbation in the metabolism of gluconeogenic amino acids other than BCAAs characterizes both early and advanced T2DM stages. In conclusion, we identified a metabolic serum signature associated with T2DM stages. These data could be integrated with clinical characteristics to build a composite T2DM/complications risk score to be validated in a prospective cohort.