Reduction in ETFDH expression optimizes cancer cell bioenergetics
Papadopoli, D.; Palia, R.; Jovanovic, P.; Tabaries, S.; Ciccolini, E.; Sabourin, V.; Igelmann, S.; McLaughlan, S.; Zhan, L.; Kim, H.; Chekkal, N.; Szkop, K. J.; Bertomeu, T.; Zeng, J.; Vassalakis, J.; Afzali, F.; Mzoughi, S.; Guccione, E.; Tyers, M.; Avizonis, D.; Larsson, O.; Postovit, L.-M.; Djuranovic, S.; Ursini-Siegel, J.; Siegel, P. M.; Pollak, M.; Topisirovic, I.
Show abstract
Mitochondrial electron transport flavoprotein (ETF) insufficiency causes metabolic diseases known as a multiple acyl-CoA dehydrogenase deficiency (MADD). In contrast to muscle, ETFDH is a non-essential gene in acute lymphoblastic leukemia NALM-6 cells, and its expression is reduced across human cancers. ETF insufficiency caused by decreased ETFDH expression limits flexibility of OXPHOS fuel utilization but paradoxically increases cancer cell bioenergetics and accelerates neoplastic growth by activation of the mTORC1/BCL-6/4E-BP1 axis. Collectively, these findings reveal that while ETF insufficiency is rare and has detrimental effects in non-malignant tissues, it is common in neoplasia, where ETFDH downregulation leads to bioenergetic and signaling reprogramming that accelerate neoplastic growth.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A novel non-catalytic scaffolding activity of Hexokinase 2 contributes to EMT and metastasis 97%
- C/EBPB-dependent Adaptation to Palmitic Acid Promotes Stemness in Hormone Receptor Negative Breast Cancer 97%
- Dual Ribosome Profiling reveals metabolic limitations of cancer and stromal cells in thetumor microenvironment 97%
Similar papers in this journal
Similar papers in this journal
- CIP2A interacts with TopBP1 and is selectively essential for DNA damage-induced basal-like breast cancer tumorigenesis 96%
- EZH2 synergizes with BRD4-NUT to drive NUT carcinoma growth through silencing of key tumor suppressor genes 96%
- PAX3-FOXO1 drives targetable cell state-dependent metabolic vulnerabilities in rhabdomyosarcoma 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.