Inborn-like errors of metabolism are determinants of breast cancer risk, clinical response and survival: A study of human biochemical individuality
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Citações na Scopus
8
Tipo de produção
article
Data de publicação
2018
Título da Revista
ISSN da Revista
Título do Volume
Editora
IMPACT JOURNALS LLC
Autores
SILVA, I. da
VIEIRA, R. C.
STELLA, C.
LOTURCO, E.
CARVALHO, A. L.
VEO, C.
NETO, C.
SILVA, S. M.
D'AMORA, P.
SALZGEBER, M.
Citação
ONCOTARGET, v.9, n.60, p.31664-31681, 2018
Resumo
Breast cancer remains a leading cause of morbidity and mortality worldwide yet methods for early detection remain elusive. We describe the discovery and validation of biochemical signatures measured by mass spectrometry, performed upon blood samples from patients and controls that accurately identify ( > 95%) the presence of clinical breast cancer. Targeted quantitative MS/MS conducted upon 1225 individuals, including patients with breast and other cancers, normal controls as well as individuals with a variety of metabolic disorders provide a biochemical phenotype that accurately identifies the presence of breast cancer and predicts response and survival following the administration of neoadjuvant chemotherapy. The metabolic changes identified are consistent with inborn-like errors of metabolism and define a continuum from normal controls to elevated risk to invasive breast cancer. Similar results were observed in other adenocarcinomas but were not found in squamous cell cancers or hematologic neoplasms. The findings describe a new early detection platform for breast cancer and support a role for pre-existing, inborn-like errors of metabolism in the process of breast carcinogenesis that may also extend to other glandular malignancies. Statement of Significance: Findings provide a powerful tool for early detection and the assessment of prognosis in breast cancer and define a novel concept of breast carcinogenesis that characterizes malignant transformation as the clinical manifestation of underlying metabolic insufficiencies. © da Silva et al.
Palavras-chave
Breast cancer, Metabolism, Prognosis, Response, Survival
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