Dataset Information

Deciphering the role of CDK4 in regulating metabolism and cell fate of triple-negative breast cancer cells

ABSTRACT: The shift on energetic demands of proliferating cells during tumorigenesis requires an intense crosstalk between cell cycle and metabolism. Beyond their role in cell proliferation, cell cycle regulators also modulate intracellular metabolism of normal tissues. Using both genetic and pharmacological approaches, we aimed to determine the metabolic role of CDK4 in TNBC cells. Unexpectedly, deletion of CDK4 only slightly reduces cell proliferation of triple negative breast cancer (TNBC) cell line and allows in vivo tumor formation. Furthermore, pro-apoptotic stimuli fail to induce proper cell death in CDK4-silenced, depleted or long-term CDK4/6 inhibitors-treated TNBC cells, with dampened mitochondrial calcium uptake. In the first mass spectrometry-based experiment linked to this project, we explored the proteome and phosphoproteome of WT vs CDK4 KO in triple negative breast cancer cells (MDA-MB-231).

INSTRUMENT(S): timsTOF, Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Malignant Cell, Breast Cancer Cell Line

DISEASE(S): Breast Cancer

SUBMITTER: Manfredo Quadroni

LAB HEAD: Lluis Fajas

PROVIDER: PXD046326 | Pride | 2024-11-26

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	201207_Fajas_TiO-I2_WT_12755.raw	Raw
	201207_Fajas_TiO-I2_WT_12756.raw	Raw
	201207_Fajas_TiO-I2_WT_12757.raw	Raw
	201207_Fajas_TiO-I2_WT_12758.raw	Raw
	201207_Fajas_TiO-I2_WT_12759.raw	Raw

Items per page:

1 - 5 of 20

Similar Datasets

Project description:Objective: Athletes increasingly engage in repeated sprint training that consists of repeated short all-out effort interspersed by short periods of recovery. When performed in hypoxia (RSH), it may lead to greater training effects than in normoxia (RSN), however the underlying molecular mechanisms remain unclear. This study aimed at elucidating the effects of RSH on skeletal muscle oxidative and glycolytic adaptations as compared to RSN. Methods: Healthy young men performed nine repeated sprint training sessions in three weeks. Each training session consisted in six series of six sprints in either normoxia (FiO2 = 20.9%, RSN, n = 7) or normobaric hypoxia (FiO2 = 13.6%, RSH, n = 9). Before and after the training period, exercise performance was assessed by using repeated sprint ability (RSA) and Wingate tests. Vastus lateralis muscle biopsies were performed to investigate muscle metabolic adaptations using proteomic combined to western blotting analyses. Results: We observed similar improvements in RSA and Wingate tests in both RSH and RSN groups. Proteomic analysis revealed a decrease in several proteins involved in oxidative phosphorylation (OXPHOS) in both groups and this was confirmed with western blot showing significant reductions in complexes I and V protein levels. RSN and RSH increased protein levels of the glycolytic enzyme hexokinase II, while only RSH induced a significant increase in the glucose transporter 4 (GLUT4) protein levels, suggesting superior glycolytic adaptations in response to hypoxia. This phenotype is further supported by proteomics data showing significant increase of proteins involved in glycolysis. Our proteomics data showed in the RSH group a specific increase in several S100A family proteins, among which S100A13 was the most modified, a result confirmed by western blot. S100A proteins have recently been shown to accelerate glycolytic phenotype of cancer cells by activating the protein kinase B (Akt) pathway. Our data corroborate these findings by showing in RSH group increased Akt phosphorylation as well as increased levels of proteins related to Akt downstream effects such as enhanced translation. Conclusions: Altogether our data indicate that RSH, as compared to RSN, potentiates the muscle glycolytic phenotype, possibly through the activation of S100A13 and the Akt pathway.

Dataset Information

Deciphering the role of CDK4 in regulating metabolism and cell fate of triple-negative breast cancer cells

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets