TBC1 domain-containing proteins are frequently involved in triple-negative breast cancers in connection with the induction of a glycolytic phenotype

Abstract

Metabolic plasticity is a hallmark of cancer, and metabolic alterations represent a promising therapeutic target. Since cellular metabolism is controlled by membrane traffic at multiple levels, we investigated the involvement of TBC1 domain-containing proteins (TBC1Ds) in the regulation of cancer metabolism. These proteins are characterized by the presence of a RAB-GAP domain, the TBC1 domain, and typically function as attenuators of RABs, the master switches of membrane traffic. However, a number of TBC1Ds harbor mutations in their catalytic residues, predicting biological functions different from direct regulation of RAB activities. Herein, we report that several genes encoding for TBC1Ds are expressed at higher levels in triple-negative breast cancers (TNBC) vs. other subtypes of breast cancers (BC), and predict prognosis. Orthogonal transcriptomics/metabolomics analysis revealed that the expression of prognostic TBC1Ds correlates with elevated glycolytic metabolism in BC cell lines. In-depth investigations of the three top hits from the previous analyses (TBC1D31, TBC1D22B and TBC1D7) revealed that their elevated expression is causal in determining a glycolytic phenotype in TNBC cell lines. We further showed that the impact of TBC1D7 on glycolytic metabolism of BC cells is independent of its known participation in the TSC1/TSC2 complex and consequent downregulation of mTORC1 activity. Since TBC1D7 behaves as an independent prognostic biomarker in TNBC, it could be used to distinguish good prognosis patients who could be spared aggressive therapy from those with a poor prognosis who might benefit from anti-glycolytic targeted therapies. Together, our results highlight how TBC1Ds connect disease aggressiveness with metabolic alterations in TNBC. Given the high level of heterogeneity among this BC subtype, TBC1Ds could represent important tools in predicting prognosis and guiding therapy decision-making.