Triple‐negative breast cancer (TNBC), an aggressive, metastatic and recurrent breast cancer (BC) subtype, currently suffers from a lack of adequately described spontaneously metastatic preclinical models that faithfully reproduce the clinical scenario. We describe two preclinical spontaneously metastatic TNBC orthotopic murine models for the development of advanced therapeutics: an immunodeficient human MDA‐MB‐231‐Luc model and an immunocompetent mouse 4T1 model. Furthermore, we provide a broad range of multifactorial analysis for both models that could provide relevant information for the development of new therapies and diagnostic tools. Our comparisons uncovered differential growth rates, stromal arrangements and metabolic profiles in primary tumors, and the presence of cancer‐associated adipocyte infiltration in the MDA‐MB‐231‐Luc model. Histopathological studies highlighted the more rapid metastatic spread to the lungs in the 4T1 model following a lymphatic route, while we observed both homogeneous (MDA‐MB‐231‐Luc) and heterogeneous (4T1) metastatic spread to axillary lymph nodes. We encountered unique metabolomic signatures in each model, including crucial amino acids and cell membrane components. Hematological analysis demonstrated severe leukemoid and lymphoid reactions in the 4T1 model with the partial reestablishment of immune responses in the immunocompromised MDA‐MB‐231‐Luc model. Additionally, we discovered β‐immunoglobulinemia and increased basal levels of G‐CSF correlating with a metastatic switch, with G‐CSF also promoting extramedullary hematopoiesis (both models) and causing hepatosplenomegaly (4T1 model). Overall, we believe that the characterization of these preclinical models will foster the development of advanced therapeutic strategies for TNBC treatment, especially for the treatment of patients presenting both, primary tumors and metastatic spread.

Clinical parameters used in type 2 diabetes mellitus (T2D) diagnosis and monitoring such as glycosylated haemoglobin (HbA1c) are often unable to capture important information related to diabetic control and chronic complications. In order to search for additional biomarkers, we performed a pilot study comparing T2D patients with healthy controls matched by age, gender, and weight. By using 1H-nuclear magnetic resonance (NMR) based metabolomics profiling of red blood cells (RBCs), we found that the metabolic signature of RBCs in T2D subjects differed significantly from non-diabetic controls. Affected metabolites included glutathione, 2,3-bisphophoglycerate, inosinic acid, lactate, 6-phosphogluconate, creatine and adenosine triphosphate (ATP) and several amino acids such as leucine, glycine, alanine, lysine, aspartate, phenylalanine and tyrosine. These results were validated by an independent cohort of T2D and control patients. An analysis of the pathways in which these metabolites were involved showed that energetic and redox metabolism in RBCs were altered in T2D, as well as metabolites transported by RBCs. Taken together, our results revealed that the metabolic profile of RBCs can discriminate healthy controls from T2D patients. Further research is needed to determine whether metabolic fingerprint in RBC could be useful to complement the information obtained from HbA1c and glycemic variability as well as its potential role in the diabetes management.

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The prevalence of diabetes type 1 (T1D) in the world populations is continuously growing. Although treatment methods are improving, the diagnostic is still symptom-based and sometimes far after onset of the disease. In this context, the aim of the study was the search of new biomarkers of the disease in red blood cells (RBCs), until now unexplored. The metabolomic and the lipidomic profile of RBCs from T1D patients and matched healthy controls was determined by NMR spectroscopy, and different multivariate discrimination models were built to select the metabolites and lipids that change most significantly. Relevant metabolites were further confirmed by univariate statistical analysis. Robust separation in the metabolomic and lipidomic profiles of RBCs from patients and controls was confirmed by orthogonal projection on latent structure discriminant analysis (OPLS-DA), random forest analysis, and significance analysis of metabolites (SAM). The main changes were detected in the levels of amino acids, organic acids, creatine and phosphocreatine, lipid change length, and choline derivatives, demonstrating changes in glycolysis, BCAA metabolism, and phospholipid metabolism. Our study proves that robust differences exist in the metabolic and lipidomic profile of RBCs from T1D patients, in comparison with matched healthy individuals. Some changes were similar to alterations found already in RBCs of T2D patients, but others seemed to be specific for type 1 diabetes. Thus, many of the metabolic differences found could be biomarker candidates for an earlier diagnosis or monitoring of patients with T1D.