title: Metabolic phenotypes in triple-negative breast cancer.
abstract: The aim of study was to investigate the metabolism of tumor and stromal cells necessary to determine differential tumor-stroma metabolic interactions according to the molecular subtypes of triple-negative breast cancer (TNBC). Tissues from 132 patients of TNBC were prepared for use as tissue microarrays (TMA). Expression of CK5/6, EGFR, claudin 3, claudin 4, claudin7, E-cadherin, AR, GGT1, STAT1, and interleukin-8 was evaluated by immunohistochemical staining using TMA to classify molecular subtypes of TNBC. In addition, immunohistochemical staining for Glut1, CAIX, BNIP3, MCT4, Beclin-1, LC3A, LC3B, and p62 was performed. According to glycolytic status determined by the immunohistochemical expression of Glut-1 and CAIX in tumor and stroma, the metabolic phenotypes of the TNBCs were defined as follows: Warburg type (tumor: glycolysis, stroma: non-glycolysis), reverse Warburg type (tumor: non-glycolysis, stroma: glycolysis), mixed metabolic type (tumor: glycolysis, stroma: glycolysis), and metabolic null type (tumor: non-glycolysis, stroma: non-glycolysis). TNBCs were classified as follows: 79 Warburg type (59.8 %), 7 reverse Warburg type (5.3 %), 24 mixed metabolic type (18.2 %), and 22 metabolic null type (16.7 %). There was no statistical significance between the metabolic phenotypes and molecular subtypes (P=0.706). Reverse Warburg type showed the most dysfunctional mitochondrial status for stromal cells, while Warburg type showed the most functional mitochondrial status (P=0.036). Regarding stromal autophagy status, reverse Warburg type showed the most activated status, while all of the Warburg and metabolic null types showed a non-activated status (P<0.001). In conclusion, Warburg type was the most common metabolic phenotype in TNBC, while reverse Warburg type was the most unusual. Metabolic phenotypes did not differ among the molecular subtypes of TNBCs.
authors: Department of Pathology, Yonsei University Health System, Seoul, South Korea.
authors: Sewha
authors: S
authors: Kim
authors: Do Hee
authors: DH
authors: Kim
authors: Woo-Hee
authors: WH
authors: Jung
authors: Ja Seung
authors: JS
authors: Koo
mesh_terms: D000328:Adult; D001343:Autophagy; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000145:classification* / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D005260:Female; D005347:Fibroblasts / Q000378:metabolism* / Q000473:pathology; D006019:Glycolysis; D006801:Humans; D007124:Immunoenzyme Techniques; D008207:Lymphatic Metastasis; D008875:Middle Aged; D008928:Mitochondria / Q000378:metabolism* / Q000473:pathology; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D010641:Phenotype; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D011980:Receptors, Progesterone / Q000378:metabolism; D017154:Stromal Cells / Q000378:metabolism* / Q000473:pathology; D015996:Survival Rate; D046888:Tissue Array Analysis
chemical_list: D014408:Biomarkers, Tumor; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone