Dynamic multi-OMICs of glioblastoma reveal sensitivity to neddylation inhibition dependent on nuclear PTEN and DNA replication pathways
Ferdosi, S. R.; Taylor, B.; Lee, M.; Peng, S.; Tang, N.; Bybee, R.; Reid, G.; Hartmen, L.; Garcia-Mansfield, K.; Sharma, R.; Pirrotte, P.; Furnari, F.; Dhruv, H. D.; Berens, M. E.
Show abstract
Withdrawal StatementThe authors have withdrawn their manuscript because the reported synergy of TOP2A inhibitors plus MLN4924 proved to be untrue (not reproducible). Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author (mberens@tgen.org).
Matching journals
The top 11 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Metabolic-imaging of human glioblastoma explants: a new precision-medicine model to predict tumor treatment response early 93%
- Novel kinome profiling technology reveals drug treatment is patient and 2D/3D model dependent in GBM 91%
- BNIP3 upregulation characterizes cancer cell subpopulation with increased fitness and proliferation 88%
Similar papers in this journal
- FYN tyrosine kinase, a downstream target of receptor tyrosine kinases, modulates anti-glioma immune responses 91%
- TIGIT expression dictates the immunosuppressive reprogramming of myeloid cells in glioblastoma 91%
- Pyruvate carboxylation identifies Glioblastoma Stem-like Cells opening new metabolic strategy to prevent tumor recurrence 90%
Similar papers in this journal
- Probing the glioma micro-environment: analysis using biopsy in combination with ultra-fast cyclic immunolabeling 90%
- THOC1 complexes with SIN3A to regulate R-loops and promote glioblastoma progression 90%
- Subclonal evolution and expansion of THY1-positive cells is associated with recurrence in glioblastoma 89%
"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.