Ornithine and breast cancer: a matched case-control study

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

A new 68Ga-labeled ornithine derivative for PET imaging of ornithine metabolism in tumors

Ornithine metabolism plays a vital role in tumorigenesis. For cancer cells, ornithine is mainly used as a substrate for ornithine decarboxylase (ODC) for the synthesis of polyamines. The ODC as a key enzyme of polyamine metabolism has become an important target for cancer diagnosis and treatment. To non-invasively detect the levels of ODC expression in malignant tumors, we have synthesized a novel ⁶⁸Ga-labeled ornithine derivative ([⁶⁸Ga]Ga-NOTA-Orn). The synthesis time of [⁶⁸Ga]Ga-NOTA-Orn was about 30 min with a radiochemical yield of 45-50% (uncorrected), and the radiochemical purity was > 98%. [⁶⁸Ga]Ga-NOTA-Orn was stable in saline and rat serum. Cellular uptake and competitive inhibition assays using DU145 and AR42J cells demonstrated that the transport pathway of [⁶⁸Ga]Ga-NOTA-Orn was similar to that of L-ornithine, and it could interact with the ODC after transporting into the cell. Biodistribution and micro-positron emission tomography (Micro-PET) imaging studies showed that [⁶⁸Ga]Ga-NOTA-Orn exhibited rapid tumor uptake and was rapidly excreted through the urinary system. All above results suggested that [⁶⁸Ga]Ga-NOTA-Orn is a novel amino acid metabolic imaging agent with great potential of tumor diagnosis.

Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics

Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, p-value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.

Breast Cancer-Derived Microvesicles Are the Source of Functional Metabolic Enzymes as Potential Targets for Cancer Therapy

Membrane-derived extracellular vesicles, referred to as microvesicles (MVs), have been proposed to participate in several cancer diseases. In this study, MV fractions were isolated by differential ultracentrifugation from a metastatic breast cancer (BC) cell line MDA-MB-231 and a non-cancerous breast cell line MCF10A, then analyzed by nano-liquid chromatography coupled to tandem mass spectrometry. A total of 1519 MV proteins were identified from both cell lines. The data obtained were compared to previously analyzed proteins from small extracellular vesicles (sEVs), revealing 1272 proteins present in both MVs and sEVs derived from the MDA-MB-231 cell line. Among the 89 proteins unique to MDA-MB-231 MVs, three enzymes: ornithine aminotransferase (OAT), transaldolase (TALDO1) and bleomycin hydrolase (BLMH) were previously proposed as cancer therapy targets. These proteins were enzymatically validated in cells, sEVs, and MVs derived from both cell lines. The specific activity of OAT and TALDO1 was significantly higher in MDA-MB-231-derived MVs than in MCF10A MVs. BLMH was highly expressed in MDA-MB-231-derived MVs, compared to MCF10A MVs. This study shows that MVs carry functional metabolic enzymes and provides a framework for future studies of their biological role in BC and potential in therapeutic applications.