Abstract A49: Transcription factor upregulation after mTOR inhibition by Torin1 induces growth factor receptor expression
Bibliographic record
Abstract
Abstract Introduction: mTOR (mammalian target of rapamycin) integrates signals from cellular nutrient status and growth factors, to regulate cell growth, proliferation, and metabolism. mTOR is a part of the PI3K-Akt-mTOR signalling pathway, the components of which are frequently mutated in human cancers. Various inhibitors of mTOR activity have been developed to target this pathway, including rapamycin and its analogs sirolimus, everolimus, temsirolimus. These inhibitors are currently approved for the treatment of certain cancers, and under investigation in clinical trials for the treatment of others. Despite displaying initial effectiveness in delaying tumor progression, mTOR inhibitors eventually lose efficacy and patients relapse due to development of resistance. Due to the regulation of cap-dependent translation by mTOR, treatment of cells with mTOR inhibitors inhibits general protein translation. However, a subset of proteins exhibit increased translation in response to mTOR inhibitors. We postulate that these proteins that exhibit upregulation in response to mTOR inhibition play a role in conferring mTOR inhibitor resistance. In this study, we aim to characterize the landscape of proteins that are upregulated in response to mTOR inhibition, in order to identify pathways that contribute to resistance. We use a second-generation mTOR inhibitor Torin1, which targets both mTORC1 and mTORC2 complexes. Methods: In order to study newly translated proteins after mTOR inhibition by Torin1 on a proteomic scale, we combined the methods of click chemistry with SILAC (stable isotopic labelling of amino acids in cell culture) and tandem mass spectrometry. The translatome was studied through click-pulse-SILAC experiments conducted at 2 hours and 24 hours post Torin1 treatment in MEFs (mouse embryonic fibroblasts) as well as PC3 prostate carcinoma cells. The total proteome of MEF and PC3 cells 24 hours after Torin1 treatment was studied using SILAC and tandem mass spectrometry. Proteomics data processing and pathway enrichment analysis was performed using the Perseus software, and upregulated proteins were subject to analysis by RNA silencing, qPCR, and click chemistry. Results: Translatome analysis after Torin1 treatment showed general translation inhibition as expected, except for a small subset of proteins with increased translation. Increased translation of growth factor receptors was observed 24 hours post-Torin1 treatment, and of many transcription factors 2 hours post-treatment. Total proteome analysis 24 hours post-treatment revealed an increase in total protein levels of many of these growth factor receptors as well as transcription factors. qPCR experiments revealed increased transcripts levels of these growth factor receptors as early as 2 hours post-treatment, suggesting transcriptional upregulation. Through cross-referencing our 2 hour translatome data with genome-wide ChIP-seq datasets accessed through Cscan, we determined candidate transcription factors that may be responsible for upregulating the expression of growth factor receptors. Knockdown studies suggest that some of these transcription factors are indeed responsible for the upregulation of growth factor receptors. Conclusion: mTOR inhibition by Torin1 suppresses general translation, but many transcription factors escape this suppression and exhibit increased expression. These transcription factors induce expression of growth factor receptors, consequently enhancing their signaling. These studies identify an axis which potentially reduces the efficacy of mTOR inhibitors in cancer therapy, as well as targets that may require simultaneous inhibition. Citation Format: Tianqing T. Yang, Gian L. Negri, Anders Kristensen, Poul H. B. Sorensen. Transcription factor upregulation after mTOR inhibition by Torin1 induces growth factor receptor expression. [abstract]. In: Proceedings of the AACR Special Conference on Translational Control of Cancer: A New Frontier in Cancer Biology and Therapy; 2016 Oct 27-30; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2017;77(6 Suppl):Abstract nr A49.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".