The mTOR Complexes in Cancer Cell Metabolism

Lynch, Thomas P.; Moloughney, Joseph G.; Jacinto, Estela

doi:10.1007/978-3-319-34211-5_2

Cited by 3 publications

(1 citation statement)

References 182 publications

(254 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Being the only core factor for different distinct complexes, including the 1-mTORC1, mTOR complex (mTOR, raptor, and mLST8), complex 2-mTORC2 (mTOR, Rictor, SIN1, and mLST8), and a putative mTOR complex 3 (mTORC3), mTOR plays a vital part in diverse biological process, like in immunity, metabolism, survival, and cell proliferation, promoting anabolic metabolism (eg, amino acid, glucose, lipid, and nucleotide metabolism) and negatively regulating catabolic processes such as autophagy. [48][49][50][51][52] mTOR activity is frequently dysregulated in different human cancers, like liver, breast, prostate, lung, and renal carcinomas. 53 The immunerelated signaling pathways and some cancer-related pathways (basal cell carcinoma and p53 signaling pathways) were significantly high in the high-risk group.…”

Section: Discussionmentioning

confidence: 99%

A Seven-Autophagy-Related Long Non-Coding RNA Signature Can Accurately Predict the Prognosis of Patients with Renal Cell Carcinoma

Du¹,

Xiao²,

Huang³

et al. 2022

IJGM

View full text Add to dashboard Cite

Introduction. Renal cell carcinoma (RCC) is a common malignant tumor worldwide, and to explore, accurate prediction models are essential to the diagnosis and treatment. Methods: In the present study, the profile expression of RCC patients for long non-coding RNAs (lncRNAs) were obtained from the database of The Cancer Genome Atlas (TCGA). The Gene Set Enrichment Analysis (GSEA) showed that the gene sets related to autophagy are significantly differentially expressed among the paired normal tissues and RCC. Multivariate and univariate Cox analyses were used to construct the gene signature related to prognosis. Receiver Operating Characteristic (ROC) dependent on the time factor and the Kaplan-Meier curves are used for evaluating identified signatures. For gene signature combination, a nomogram with associated clinical constraints was designed. Results: Multivariate and Univariate Cox analyses presented seven autophagy-related lncRNAs were significantly correlated with Overall Survival (OS) for people with RCC. Risk scores of lncRNA prognostic signature, related to autophagy helped in distinguishing the patients accurately among the low-risk and high-risk RCC based on age, sex, grade of tumor, T, M, N, and AJCC stages. The RCC condition patients, as per their signature were put into the category of low and high-risk groups, having varying prognostic outcomes. Gene signature is an independent prognosticator for OS, accurately predicting 3-5 year survival time for RCC patients from either of the two groups. GSEA revealed that high-risk scores of the prognostic seven-long non-coding signature correlate with immuneregulatory and cancer, signaling pathways, whereas a low-risk score correlates with metabolism. The quantitative reverse chain reaction of transcription-polymerase verified differential expression of seven lncRNAs autophagy-related samples. Conclusion:The results depict that seven autophagy-related lncRNA prognostic signature helps in predicting the prognosis accurately among people with RCC.

show abstract

Section: Discussionmentioning

confidence: 99%

A Seven-Autophagy-Related Long Non-Coding RNA Signature Can Accurately Predict the Prognosis of Patients with Renal Cell Carcinoma

Du¹,

Xiao²,

Huang³

et al. 2022

IJGM

View full text Add to dashboard Cite

show abstract

KPT-9274, an Inhibitor of PAK4 and NAMPT, Leads to Downregulation of mTORC2 in Triple Negative Breast Cancer Cells

Cordover

Wei

Patel

et al. 2019

Chem. Res. Toxicol.

Self Cite

View full text Add to dashboard Cite

Triple negative breast cancer (TNBC) is difficult to treat due to lack of druggable targets. We have found that treatment with the small molecule inhibitor KPT-9274 inhibits growth of TNBC cells and eventually leads to cell death. KPT-9274 is a dual specific inhibitor of PAK4 and Nicotinamide Phosphoribosyltransferase (NAMPT). The PAK4 protein kinase is often highly expressed in TNBC cells and has important roles in cell growth, survival, and migration. Previously we have found that inhibition of PAK4 leads to growth inhibition of TNBC cells both in vitro and in vivo. Likewise, NAMPT has been shown to be dysregulated in cancer due to its role in cell metabolism. In order to understand better how treating cells with KPT-9274 abrogates TNBC cell growth, we carried out an RNA sequencing of TNBC cells treated with KPT-9274. As a result, we identified Rictor as an important target that is inhibited in the KPT-9274 treated cells. Conversely, we found that Rictor is predicted to be activated when PAK4 is overexpressed in cells, which suggests a role for PAK4 in the regulation of Rictor. Rictor is a component of mTORC2, one of the complexes formed by the serine/threonine kinase mTOR. mTOR is important for the control of cell growth and metabolism. Our results suggest a new mechanism by which the KPT-9274 compound may block the growth of breast cancer cells, which is via inhibition of mTORC2 signaling. Consistent with this, sequencing analysis of PAK4 overexpressing cells indicates that PAK4 has a role in activation of the mTOR pathway.

show abstract

mTOR signalling and cellular metabolism are mutual determinants in cancer

2018

View full text Add to dashboard Cite

Oncogenic signalling and metabolic alterations are interrelated in cancer cells. mTOR, which is frequently activated in cancer, controls cell growth and metabolism. mTOR signalling regulates amino acid, glucose, nucleotide, fatty acid and lipid metabolism. Conversely, metabolic inputs, such as amino acids, activate mTOR. In this Review, we discuss how mTOR signalling rewires cancer cell metabolism and delineate how changes in metabolism, in turn, sustain mTOR signalling and tumorigenicity. Several drugs are being developed to perturb cancer cell metabolism. However, their efficacy as stand-alone therapies, similar to mTOR inhibitors, is limited. Here, we discuss how the interdependence of mTOR signalling and metabolism can be exploited for cancer therapy. rapamycin treatment. Activation of mTORC1 by growth factors and nutrientsThe activation of mTORC1 is dependent on nutrients and growth factors. In response to nutrients, mTORC1 translocates from the cytoplasm to the lysosomal surface, where it is activated by growth factors via PI3K-AKT signalling. Growth factors, for instance, insulin, activate AKT4 via a cognate receptor, phosphoinositide-dependent kinase 1 (PDK1) and PI3K (Fig. 1). AKT inhibits the TSC1-TSC2 complex5, which is a GTPase-activating protein (GAP) for the small GTPase RHEB6. GTP-bound RHEB directly binds and activates mTORC1 at the lysosome 7,8 (Fig. 1). Nutrient-induced lysosomal translocation of mTORC1Nutrients, in particular amino acids, promote lysosomal localization of mTORC1 via the RAS-related GTP-binding proteins (RAGs) 9 , thereby enabling mTORC1 to encounter RHEB. RAGs are small GTPases that form obligate heterodimers. RAGA or RAGB associates with RAGC or RAGD. In the active state, GTP-bound RAGA or RAGB and GDP-bound RAGC or RAGD bind RAPTOR and thereby recruit mTORC1 to the lysosomal surface. The nucleotide binding status of the RAGs is tightly regulated by amino acids 9 obtained from intracellular synthesis, protein turnover or extracellular sources via specific transporters (Fig. 1; for details, see following sections). Among the amino acids, leucine, arginine and glutamine are the most effective activators of mTORC1. Leucine and arginine bind to sestrin 2 and CASTOR1, respectively, ultimately to activate the RAGs and mTORC1 (for details, see Fig. 1, ref. 10 and references therein). The lysosomal amino acid transporter SLC38A9 promotes mTORC1 activation by exporting essential amino acids to the cytoplasm 11 , where, for example, leucine can bind sestrin 2. Leucine export is stimulated by arginine binding to SLC38A9 (ref. 11 ). Glutamine activates RAGs by promoting glutaminolysis. During glutaminolysis, glutaminase (GLS) and glutamate dehydrogenase (GDH) convert glutamine to αketoglutarate (αKG), which ultimately activates mTORC1 via prolyl hydroxylases (PHDs) by promoting GTP loading of RAGB12 (Fig. 1). Leucine also stimulates αKG production by directly binding and allosterically activating GDH. Furthermore, glutamine activates mTORC1 independently of RAGs via the small GTPase ADPri...

show abstract

The mTOR Complexes in Cancer Cell Metabolism

Cited by 3 publications

References 182 publications

A Seven-Autophagy-Related Long Non-Coding RNA Signature Can Accurately Predict the Prognosis of Patients with Renal Cell Carcinoma

A Seven-Autophagy-Related Long Non-Coding RNA Signature Can Accurately Predict the Prognosis of Patients with Renal Cell Carcinoma

KPT-9274, an Inhibitor of PAK4 and NAMPT, Leads to Downregulation of mTORC2 in Triple Negative Breast Cancer Cells

mTOR signalling and cellular metabolism are mutual determinants in cancer

Contact Info

Product

Resources

About