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Metabolic profiling of triple-negative breast cancer cells reveals metabolic vulnerabilities.
Lanning, Nathan J; Castle, Joshua P; Singh, Simar J; Leon, Andre N; Tovar, Elizabeth A; Sanghera, Amandeep; MacKeigan, Jeffrey P; Filipp, Fabian V; Graveel, Carrie R.
Afiliação
  • Lanning NJ; California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA 90032 USA.
  • Castle JP; Van Andel Research Institute, 333 Bostwick Ave, NE, Grand Rapids, MI 49503 USA.
  • Singh SJ; Systems Biology and Cancer Metabolism, Program for Quantitative Systems Biology, University of California Merced, 2500 North Lake Road, Merced, CA 95343 USA.
  • Leon AN; California State University, Los Angeles, 5151 State University Drive, Los Angeles, CA 90032 USA.
  • Tovar EA; Van Andel Research Institute, 333 Bostwick Ave, NE, Grand Rapids, MI 49503 USA.
  • Sanghera A; Systems Biology and Cancer Metabolism, Program for Quantitative Systems Biology, University of California Merced, 2500 North Lake Road, Merced, CA 95343 USA.
  • MacKeigan JP; Van Andel Research Institute, 333 Bostwick Ave, NE, Grand Rapids, MI 49503 USA.
  • Filipp FV; College of Human Medicine, Michigan State University, 15 Michigan St. NE, Grand Rapids, MI 49503 USA.
  • Graveel CR; Systems Biology and Cancer Metabolism, Program for Quantitative Systems Biology, University of California Merced, 2500 North Lake Road, Merced, CA 95343 USA.
Cancer Metab ; 5: 6, 2017.
Article em En | MEDLINE | ID: mdl-28852500
ABSTRACT

BACKGROUND:

Among breast cancers, the triple-negative breast cancer (TNBC) subtype has the worst prognosis with no approved targeted therapies and only standard chemotherapy as the backbone of systemic therapy. Unique metabolic changes in cancer progression provide innovative therapeutic opportunities. The receptor tyrosine kinases (RTKs) epidermal growth factor receptor (EGFR), and MET receptor are highly expressed in TNBC, making both promising therapeutic targets. RTK signaling profoundly alters cellular metabolism by increasing glucose consumption and subsequently diverting glucose carbon sources into metabolic pathways necessary to support the tumorigenesis. Therefore, detailed metabolic profiles of TNBC subtypes and their response to tyrosine kinase inhibitors may identify therapeutic sensitivities.

METHODS:

We quantified the metabolic profiles of TNBC cell lines representing multiple TNBC subtypes using gas chromatography mass spectrometry. In addition, we subjected MDA-MB-231, MDA-MB-468, Hs578T, and HCC70 cell lines to metabolic flux analysis of basal and maximal glycolytic and mitochondrial oxidative rates. Metabolic pool size and flux measurements were performed in the presence and absence of the MET inhibitor, INC280/capmatinib, and the EGFR inhibitor, erlotinib. Further, the sensitivities of these cells to modulators of core metabolic pathways were determined. In addition, we annotated a rate-limiting metabolic enzymes library and performed a siRNA screen in combination with MET or EGFR inhibitors to validate synergistic effects.

RESULTS:

TNBC cell line models displayed significant metabolic heterogeneity with respect to basal and maximal metabolic rates and responses to RTK and metabolic pathway inhibitors. Comprehensive systems biology analysis of metabolic perturbations, combined siRNA and tyrosine kinase inhibitor screens identified a core set of TCA cycle and fatty acid pathways whose perturbation sensitizes TNBC cells to small molecule targeting of receptor tyrosine kinases.

CONCLUSIONS:

Similar to the genomic heterogeneity observed in TNBC, our results reveal metabolic heterogeneity among TNBC subtypes and demonstrate that understanding metabolic profiles and drug responses may prove valuable in targeting TNBC subtypes and identifying therapeutic susceptibilities in TNBC patients. Perturbation of metabolic pathways sensitizes TNBC to inhibition of receptor tyrosine kinases. Such metabolic vulnerabilities offer promise for effective therapeutic targeting for TNBC patients.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2017 Tipo de documento: Article