Sorting nexin 10 controls mTOR activation through regulating amino-acid metabolism in colorectal cancer

Abstract

Amino-acid metabolism plays a vital role in mammalian target of rapamycin (mTOR) signaling, which is the pivot in colorectal cancer (CRC). Upregulated chaperone-mediated autophagy (CMA) activity contributes to the regulation of metabolism in cancer cells. Previously, we found that sorting nexin 10 (SNX10) is a critical regulator in CMA activation. Here we investigated the role of SNX10 in regulating amino-acid metabolism and mTOR signaling pathway activation, as well as the impact on the tumor progression of mouse CRC. Our results showed that SNX10 deficiency promoted colorectal tumorigenesis in male FVB mice and CRC cell proliferation and survival. Metabolic pathway analysis of gas chromatography-mass spectrometry (GC-MS) data revealed unique changes of amino-acid metabolism by SNX10 deficiency. In HCT116 cells, SNX10 knockout resulted in the increase of CMA and mTOR activation, which could be abolished by chloroquine treatment or reversed by SNX10 overexpression. By small RNA interference (siRNA), we found that the activation of mTOR was dependent on lysosomal-associated membrane protein type-2A (LAMP-2A), which is a limiting factor of CMA. Similar results were also found in Caco-2 and SW480 cells. Ultra-high-performance liquid chromatography-quadrupole time of flight (UHPLC-QTOF) and GC-MS-based untargeted metabolomics revealed that 10 amino-acid metabolism in SNX10-deficient cells were significantly upregulated, which could be restored by LAMP-2A siRNA. All of these amino acids were previously reported to be involved in mTOR activation. In conclusion, this work revealed that SNX10 controls mTOR activation through regulating CMA-dependent amino-acid metabolism, which provides potential target and strategy for treating CRC.

Fig. 1. SNX10 deficiency promotes mouse colorectal tumorigenesis in male FVB mice.

a Average body weight of WT and SNX10 KO CRC male mice were calculated. b Tumors inside the colorectum of WT and SNX10 KO CRC male mice were photographed. c Tumor numbers were counted. d, e Tumor diameter and distribution were measured. f The tumor load was determined by totaling the diameters of all tumors for a given mouse. g CRC tissues from WT and SNX10 KO mice were fixed and stained with H&E. h Survival curves of WT and SNX10 KO CRC male mice. The incidence of tumors was 100% in all mice, and the CRC mice were maintained with regular food and water until death. Survival curves were calculated according to the Kaplan–Meier method; survival analysis was performed using the log-rank test. *P < 0.05, **P < 0.01, and ***P < 0.001

Fig. 2. SNX10 deficiency facilitates HCT116 cell proliferation and survival under nutritional deprivation.

a The colony-forming ability of WT, SXN10 KO HCT116 cells, and SXN10 KO HCT116 cells infected with Ad-vector or Ad-SNX10. b Quantification of colony numbers in a. c The proliferation of WT, SXN10 KO HCT116 cells, and SXN10 KO HCT116 cells infected with Ad-vector or Ad-SNX10 was measured by BrdU cell proliferation assay. d, e WT, SXN10 KO HCT116 cells, and SXN10 KO HCT116 cells infected with Ad-vector or Ad-SNX10 were cultured in EBSS for 0, 6, 12, 18, or 24 h. d The percentage of dead cells was determined by trypan blue exclusion assay at the indicated time points. e The cell viability was determined by MTT assay at the indicated time points. f WT and SXN10 KO HCT116 cells were untreated, or were treated with EBSS for 24 h, or were transfected with nontargeting siRNA (Si-NC) or LAMP-2A siRNA (Si-LAMP-2A), followed by EBSS treatment for 24 h, and the percentage of dead cells was determined by trypan blue exclusion assay. Data are derived from at least three independent experiments and represented as means ± SEM in the bar graphs. Not significant (n.s.), *P < 0.05, **P < 0.01, and ***P < 0.001

Fig. 3. Untargeted metabolomics and multivariate statistical analysis of tumor tissues from CRC male mice using UHPLC-QTOF in positive ion mode disclosed significant metabolic alternations caused by SNX10 deficiency.

a Total ion chromatograms of WT (WTM), SNX10 KO (KOM), and quality control samples (QC). b Retention time deviation of all samples. c Manhattan map showed the distribution of significant features (P < 0.05, green dots) in m/z and retention time. d 2D score plot between the selected PCs of PLS-DA model. e 3D score plot between the selected PCs of PCA model. f Volcano plot with fold change threshold and t-test threshold to select the important features

Fig. 4. Metabolic pathway networks based on the untargeted metabolomics using UHPLC-QTOF in negative ion mode and GC-MS analysis.

a Metabolic networks of activity pathways that based on the UHPLC-QTOF negative ion-mode analysis and generated from software Mummichog and visualized via Cytospace. Metabolites are colored green (concentration decrease) or red (concentration increase), the size and color intensity represent the connectivity of the metabolite in the networks and magnitude of fold change. b The metabolome view that based on the GC-MS analysis and generated from the web-based metabolomics analysis tool MetaboAnalyst. All matched pathways according to P values from pathway enrichment analysis and pathway impact values from pathway topology analysis. c Heatmap of the significant metabolites analyzed by GC-MS showed their concentration changing patterns across WT and KO samples

Fig. 5. Persistent activation of CMA degradation caused by SNX10 deficiency activates mTOR signaling.

a Representative western blots showed the expression of indicated proteins in WT and SNX10 KO HCT116 cells with the treatment of EBSS for 24 h. The bands of GAPDH, LAMP-2A, and p-mTOR were quantified using Quantity One software. b Co-staining of GAPDH and LAMP-2A in WT and SNX10 KO HCT116 cells treated with or without EBSS for 24 h. Anti-GAPDH and anti-LAMP-2A antibodies were used to detect endogenous GAPDH and LAMP-2A, respectively. Scale bar (5 μm). GAPDH- and LAMP-2A-positive puncta per cell from at least 200 cells in three independent experiments were quantified. c WT and SNX10 KO HCT116 cells were treated with EBSS and/or CQ for 24 h, the total proteins were isolated and immunoblotted with indicated antibodies. The bands of GAPDH, LAMP-2A, and p-mTOR were quantified using Quantity One software. d WT, SNX10 KO HCT116 cells, and SXN10 KO HCT116 cells infected with Ad-Vector or Ad-SNX10 were treated with EBSS for 24 h. LAMP-2A, GAPDH, and p-mTOR were detected by immunoblot, followed by densitometry quantification by Quantity One software. e WT and SNX10 KO HCT116 cells transfected with nontargeting siRNA (Si-NC) or LAMP-2A siRNA (Si-LAMP-2A) were treated with EBSS for 24 h, the total proteins were isolated and immunoblotted with indicated antibodies. The bands of GAPDH, LAMP-2A, and p-mTOR were quantified using Quantity One software. Data are derived from at least three independent experiments and represented as means ± SEM in the bar graphs. Not significant (n.s.), **P < 0.01, and ***P < 0.001

Fig. 6. Targeted metabolomics analysis of amino acids using GC-MS validated that SNX10 deficiency enhanced CMA process leading to the accumulation of specific amino acids that can activate mTORC1 in CRC cells

a WT, SNX10 KO HCT116 cells, and SNX10 KO HCT116 cells transfected with nontargeting siRNA (Si-NC) or LAMP-2A siRNA (Si-LAMP-2A) were treated with EBSS for 24 h, the total proteins were isolated and immunobloted with indicated antibodies. The bands of GAPDH, LAMP-2A, and p-mTOR were quantified using Quantity One software. b Relative levels of amino acids in WT, SNX10 KO and transfected with nontargeting siRNA (Si-NC) or LAMP-2A siRNA (Si-LAMP-2A) HCT116 cells. c Represented chromatogram of targeted metabolomics analysis of amino acids using GC-MS. d Pearson correlation analysis of amino-acid cellular concentrations with LAMP-2A and p-mTOR levels, blue dots represent positive correlation and red dots represent negative correlation, the deeper the color of the dots the greater the radius and the stronger the correlation. Data are derived from at least three independent experiments and represented as means ± SEM in the bar graphs. Not significant (n.s.), *P < 0.05, **P < 0.01, and ***P < 0.001

Fig. 7

Hypothetical regulatory mechanism of SNX10 on amino-acid metabolism through CMA pathway and its effect on tumor progression by mTORC1 activation