The aim of this study was to investigate selected proteomic markers of the metabolic phenotype of breast carcinomas as prognostic markers of cancer progression. For this purpose, a series of 101 breast carcinomas and 13 uninvolved breast samples were examined for quantitative differences in protein expression of mitochondrial and glycolytic markers. The β-subunit of the mitochondrial H ⁺ -ATP synthase (β-F1-ATPase) and heat shock protein 60 (Hsp60), and the glycolytic glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase and lactate dehydrogenase were identified by immunological techniques. Correlations of the expression level of the protein markers and of the ratios derived from them were established with the clinicopathological information of the tumors and the follow-up data of the patients. The metabolic proteome of breast cancer specimens revealed a pronounced shift towards an enhanced glycolytic phenotype concurrent with a profound alteration on the mitochondrial β-F1-ATPase/Hsp60 ratio when compared with normal samples. Discriminant analysis using markers of the metabolic signature as predictor variables revealed a classification sensitivity of ∼97%. Kaplan–Meier survival analysis showed that several of the proteomic variables significantly correlated with overall and disease-free survival of the patients. The expression level of β-F1-ATPase per se allowed the identification of a subgroup of breast cancer patients with significantly worse prognosis. Multivariate Cox regression analysis indicated that tumor expression of β-F1-ATPase is a significant marker independent from clinical variables to assess the prognosis of the patients. We conclude that the alteration of the mitochondrial and glycolytic proteomes is a hallmark feature of breast cancer further providing relevant markers to aid in the prognosis of breast cancer patients.

Better knowledge of the biology of breast cancer has allowed the use of new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different levels of information, which is important if it helps in making clinical decisions. microRNA (miRNA) and protein expression profiles were obtained from 71 estrogen receptor–positive (ER⁺) and 25 triple-negative breast cancer (TNBC) samples. RNA and proteins obtained from formalin-fixed, paraffin-embedded tumors were analyzed by RT-qPCR and LC/MS-MS, respectively. We applied probabilistic graphical models representing complex biologic systems as networks, confirming that ER⁺ and TNBC subtypes are distinct biologic entities. The integration of miRNA and protein expression data unravels molecular processes that can be related to differences in the genesis and clinical evolution of these types of breast cancer. Our results confirm that TNBC has a unique metabolic profile that may be exploited for therapeutic intervention. Cancer Res; 75(11); 2243–53. ©2015 AACR.

Neoplasia publishes the results of novel investigations in all areas of oncology research.