Abstract A49: Transcription factor upregulation after mTOR inhibition by Torin1 induces growth factor receptor expression
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».