Hanna Carvalho de Sá1, Massuo Jorge Kato2, Alessandra Estrela-Lima3, Gisele André Baptista Canuto1
Feline mammary carcinoma (FMC) is one of the most frequently diagnosed types of neoplasia in cats, with 80-90% of tumors being malignant [1]. Furthermore, few studies have attempted to understand the metabolic alterations involved in this disorder. Metabolomics is an interesting strategy for elucidating the metabolic alterations caused by the presence of clinical disorders such as cancer. Thus, in this study, we applied a global metabolomics approach to understand the metabolic alterations caused by cancer in an animal model. Blood serum samples were collected from cats with FMC (n=20) and compared to a control group (healthy cats, n=12). The samples were subjected to protein precipitation by adding cold methanol and kept at -20°C for 30 min. The extracts were centrifuged, and the supernatant was collected and lyophilized. The samples were then derivatized by silylation, with a previous oximation step. The derivatized extracts were immediately analyzed by gas chromatography coupled to mass spectrometry (GC-MS). Different software (XCMS/AMDIS and MS-DIAL) were evaluated for data processing, in which the best method chosen was MS-DIAL due to its greater capacity for annotating the metabolites (MS-DIAL = 119 IDs and XCMS/AMDIS = 64 IDs) and a higher percentage of annotated metabolites with RSD <30% (MS-DIAL = 59.2% and XCMS = 18.8%). Different data normalization strategies were also evaluated, and EigenMS with cubic root data transformation and Pareto data scaling was selected. The OPLS-DA model was built to find the metabolic differences between the Cancer and Control groups. The model demonstrated strong correlation (R² > 0.94) and predictive capability (Q² > 0.62). The Variable Importance on Projection (VIP) analysis was applied to identify discriminant metabolites with a VIP score > 1, resulting in 28 significant metabolites. A metabolic pathway analysis in the MetaboAnalyst 6.0 platform using the KEGG library for the metabolism of domestic cats (Felis catus) was performed to understand the metabolic alterations involved in cancer. Four pathways were significantly altered: alanine, aspartate, and glutamate metabolism (FDR = 5.85E-04), glyoxylate and dicarboxylate metabolism (FDR = 9.68E-03), butanoate metabolism (FDR = 9.68E-03), and arginine and proline metabolism (FDR = 9.68E-03). Amino acids were down-regulated in the cancer group compared to the control group. These results corroborate with previous data evaluated in humans [2] and dogs [3], indicating similarities in the metabolism of the organisms. These changes are reflected in a higher demand by cancer cells for nitrogen sources, tumor growth, and development [4]. The results obtained from the metabolomic evaluation in animal models can provide important insights for a better understanding of breast cancer metabolism, enabling the design of new treatment strategies.
Agradecimentos: FAPESB; IQ-USP