Journal: The Journal of Physiology

Article Title: Passive dehydration increases oxidative stress and mTOR signalling pathway activation in young men following resistance exercise

doi: 10.1113/jp288434

Figure Lengend Snippet: Figure 5. Protein expression results for REDD1 (n = 10) (A) and intramuscular H2O2 concentration (n = 11) (B). Data were normalized to Ponceau S (i.e. total protein stain; loading control). Representative blots (C) of PRE, 1 h and 3 h loading protein contents and the corresponding Ponceau S (total protein loaded) for an individual participant between conditions (EUHY and DEHY) run on the same gel. Molecular weight marker (kDa). AU, arbitrary units. All data are presented as means ± SD. ∗vs. PRE. † vs. EUHY. A significant interaction effect was observed for REDD1 (P = 0.028), along with significant main effects of condition (P = 0.007) and time (P = 0.010) for intramuscular H2O2 concentration.

Article Snippet: Immunoblotting was carried out using antibodies against AKT (1:1000; 4691S, Cell Signalling Technologies, Danvers, MA, USA), p-AKTS473 (1:1000; 4060S, Cell Signalling Technologies), mTOR (1:1000; 2983S, Cell Signalling Technologies), p-mTORS2448 (1:1000; 5536S, Cell Signalling Technologies), eEF2 (1:1000; 2332S, Cell Signalling Technologies), p-eEF2T56 (1:1000; 2331S, Cell Signalling Technologies), S6K (1:1000; 66638-1-Ig, Proteintech, Rosemont, IL, USA), p-S6KT389 (1:1000; 28735-1-Ig, Proteintech), rpS6 (1:1000; 2217S, Cell Signalling Technologies), p-rpS6S240/244 (1:1000; 5364S, Cell Signalling Technologies), LC3-I/II (1:1000; 12741S, Cell Signalling Technologies), p62 (1:1000; NBP1-48320, Novus Biologicals, Centennial, CO, USA), REDD1 (1:1000; 67059-1-Ig, Proteintech), and cathepsin L (1:1000; 55914T, Cell Signalling Technologies).

Techniques: Expressing, Concentration Assay, Staining, Control, Molecular Weight, Marker

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 1 Genetic alteration analysis of DDIT4 in glioma patients using cBioPortal. The analysis indicates that the DDIT4 gene is altered in less than 1% of patients. Alterations include copy number variations (CNV) such as deep deletions and somatic mutations, with no significant representation of other genetic changes

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques:

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 4 GeneMANIA network analysis for DDIT4 and associated genes. The analysis identifies gene sets enriched in the DDIT4 network, rep- resented by various edge colors indicating different types of interactions: Physical Interactions, Co-expression, Predicted, Co-localization, Genetic Interactions, Pathway, and Shared protein domains. Node colors correspond to the biological functions of the enriched gene sets, such as TOR signaling and response to oxygen levels

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques: Expressing

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 3 Prognostic analysis of DDIT4 mRNA expression in glioma patients using the GEPIA2 tool. High DDIT4 expression is significantly asso- ciated with worse prognosis in gliomas, including glioblastoma multiforme (GBM) and low-grade gliomas (LGG). A Kaplan–Meier curve for overall survival (OS) shows that patients with high DDIT4 expression have reduced survival compared to those with low expression. B Kaplan–Meier curve for recurrence-free survival (RFS) demonstrates a similar trend, with high DDIT4 expression correlating with shorter recurrence-free periods. Statistical significance is indicated with log-rank P-values

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques: Expressing

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 5 Immunohistochemical (IHC) analysis of DDIT4 protein expression in glial tumors and controls. A, A-1, A-2 Positive nuclear expression of DDIT4 in glial tumor tissues at different magnifications (100×, 200×, and 400×). B, B-1, B-2 Positive cytoplasmic expression of DDIT4 in glial tumor tissues at corresponding magnifications. C IHC staining of normal glial tissue. D Human normal kidney tissue as a positive con- trol. E Human normal kidney tissue as a negative control. F Isotype control for validation. Magnifications are indicated for each panel

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques: Immunohistochemical staining, Expressing, Immunohistochemistry, Negative Control, Control, Biomarker Discovery

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 6 Kaplan–Meier survival curves for disease-specific survival (DSS) and recurrence- free survival (RFS) based on nuclear DDIT4 protein expres- sion levels in glial tumors. A Kaplan–Meier analysis for DSS indicates that tumors with positive nuclear DDIT4 expression are associated with significantly worse survival compared to those with negative expression (Log-rank test, P = 0.013). B Kaplan–Meier analysis for RFS reveals a significant associa- tion between positive nuclear DDIT4 expression and shorter recurrence-free periods (Log- rank test, P = 0.024). Survival statistics include mean and median values with 95% con- fidence intervals, as shown in the accompanying tables

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques: Expressing

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 7 Kaplan–Meier survival curves for disease-specific survival (DSS) (A) and recur- rence-free survival (RFS) (B) in patients with glial tumors treated with temozolomide (TMZ). The analysis indicates no significant differences in DSS or RFS between patients with positive and nega- tive nuclear DDIT4 expres- sion under TMZ treatment (Log-rank test: P = 0.129 and P = 0.299, respectively)

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques:

Journal: Discover oncology

Article Title: Increased nuclear expression of DNA damage inducible transcript 4 can serve as a potential prognostic biomarker in patients with gliomas: a study based on data mining and experimental tools.

doi: 10.1007/s12672-025-01865-0

Figure Lengend Snippet: Fig. 8 Kaplan–Meier survival curves for disease-specific sur- vival (DSS) (A) and recurrence- free survival (RFS) (B) based on cytoplasmic DDIT4 protein expression levels in glial tumors. Kaplan–Meier analysis reveals no significant differ- ences in DSS or RFS between patients with positive and negative cytoplasmic DDIT4 expression (Log-rank test: P = 0.884 for DSS and P = 0.974 for RFS). Survival statistics, including mean and median values with 95% confidence intervals, are displayed in the accompanying tables

Article Snippet: Subsequently, the sections were incubated with a primary antibody specific for DDIT4 (1:80 dilution, Biorbyt, Cambridge, MA, UK) for an overnight at 4◦C.

Techniques: Expressing

Journal: Cell Reports

Article Title: Oxidative Stress Triggers Selective tRNA Retrograde Transport in Human Cells during the Integrated Stress Response

doi: 10.1016/j.celrep.2019.02.077

Figure Lengend Snippet:

Article Snippet: Rabbit Antibody against REDD1/DDIT4 , Novus Biologicals , Cat# NBP1-77321SS; RRID: AB_11036185.

Techniques: Recombinant, Cell Isolation, Reverse Transcription, SYBR Green Assay, Isolation, Sequencing, Software

Journal: PLoS Pathogens

Article Title: Influenza virus differentially activates mTORC1 and mTORC2 signaling to maximize late stage replication

doi: 10.1371/journal.ppat.1006635

Figure Lengend Snippet: ( A-C ) A549 cells were infected with WSN at MOI of 2 PFU/cell for the indicated times. Cell extracts were subjected to ( A ) western blot analysis to detect the depicted proteins and quantified as shown in or ( B ) RNA was purified for qRT-PCR to determine REDD1 mRNA levels. Mean and standard deviation are shown for qRT-PCR, n = 4 independent experiments done in triplicates. ** p <0.000004, Student's t -test. ( C ) A549 cells were transfected with siRNAs (pool of three each) targeting viral mRNAs and then infected for 7 h at MOI of 2 PFU/cell. Immunoblot analysis was performed to detect the depicted proteins, n = 3. ( D ) A549 cells were transfected with plasmids encoding the indicated virus proteins. At 48 h post-transfection, total RNA was purified and REDD1 mRNA levels were determined by qRT-PCR as in B . The bottom panel in D shows viral polymerase activity upon tranfection of the depicted viral proteins and/or minigenome as control. Minigenome mRNA was measured by qRT-PCR. In cells transfected with the complete set of plasmids that encode the viral polymerase we detect the minigenome RNA transcribed by pol I directly from the plasmid in addition to the minigenme RNA amplified by the influenza proteins, indicating protein activity. In cells transfected with the same plasmids except for PA, we only detect the minigenome RNA transcribed by pol I directly from the plasmid, and the average values was set to 1. The minigenome RNA level is higher when all plasmids were transfected ( n = 3). ( E, F ) MDCK cells were transfected with control plasmid of plasmid enconding the M2 protein. In E, RNA was purified for qRT-PCR to determine REDD1 mRNA levels as in B , n = 3, ***p<0.001. In F, cell extracts were subjected to western blot analysis to detect the depicted proteins ( n = 3). ( G ) U2OS-REDD1 cells were treated with vehicle or 1μg/ml tetracycline for 2 h prior to and during infection to induce REDD1 expression. Cells were infected at MOI of 2 PFU/cell for 6 h. Immunoblot analyses were performed to detect the depicted proteins. Total S6K serves as the loading control. The upper band in the S6K/p-S6K blots is p85 S6K, whereas the lower band is p70 S6K ( n = 3).

Article Snippet: Additional antibodies used for western blot analysis were against Rictor (Millipore 05–1471), IFITM3 (R&D Systems AF3377), MAVS (generated by Z. Chen laboratory), β-actin (Sigma A5441), REDD1 (Novus Biologicals NBP1-22966), ATG5 (Novus Biologicals NB110-53818), ATG7 (Sigma A2856), and LC3 (Novus Biologicals NB100-2220).

Techniques: Infection, Western Blot, Purification, Quantitative RT-PCR, Standard Deviation, Transfection, Virus, Activity Assay, Control, Plasmid Preparation, Amplification, Expressing

Journal: PLoS Pathogens

Article Title: Influenza virus differentially activates mTORC1 and mTORC2 signaling to maximize late stage replication

doi: 10.1371/journal.ppat.1006635

Figure Lengend Snippet: The viral protein HA and virus replication promote mTORC1 activation through PDPK1-mediated phosphorylation of AKT at T308. In addition, down-regulation of REDD1 by the viral M2 protein amplifies or support mTORC1 activation downstream of AKT. NS1 promotes AKT phosphorylation at S473 via mTORC2 and this process is known to regulate apoptosis. Differential AKT phosphorylation dictates downstream effects.

Article Snippet: Additional antibodies used for western blot analysis were against Rictor (Millipore 05–1471), IFITM3 (R&D Systems AF3377), MAVS (generated by Z. Chen laboratory), β-actin (Sigma A5441), REDD1 (Novus Biologicals NBP1-22966), ATG5 (Novus Biologicals NB110-53818), ATG7 (Sigma A2856), and LC3 (Novus Biologicals NB100-2220).

Techniques: Virus, Activation Assay, Phospho-proteomics

Journal: Experimental & molecular medicine

Article Title: YAP promotes global mRNA translation to fuel oncogenic growth despite starvation.

doi: 10.1038/s12276-024-01316-w

Figure Lengend Snippet: Fig. 5 DDIT4 suppresses the tumorigenicity of YAP-dependent uveal melanoma cells. a GNAQQ209L-mutant 92.1 and BRAFV600E-mutant OCM1 uveal melanoma cells were serum starved (or not) overnight and then restimulated (or not) with serum for 1 h. The samples were then subjected to analysis, as shown in Fig. 1a, as well as to YAP Phos-tag gel analysis. b Tet-ON DDIT4 92.1 and OCM1 cells were incubated in the absence or presence of doxycycline (Dox, 1 µg/ml) for 24 h and then analyzed as described in (a). c Relative anchorage-independent colony formation of Tet-ON DDIT4 92.1 or OCM1 cells maintained in the absence or presence of doxycycline for 3 weeks. The data are presented as the means ± s.e.m. (n = 5 independent replicates). ****p < 0.0001; n.s. not significant (unpaired Student’s t test). d Relative transwell migration quantification of Tet-ON DDIT4 92.1 and OCM1 cells in the absence or presence of doxycycline. The data are presented as the means ± s.e.m. (n = 4 independent replicates). ***p < 0.0005; n.s. not significant (unpaired Student’s t test). e Time course of xenograft tumor volume in nude mice injected with Tet-ON DDIT4 92.1 or OCM1 cells and treated (or not) with doxycycline (0.5 mg/ml) in the drinking water. The data are presented as the means ± s.e.m. (n = 4 mice per group). *p < 0.05, **p < 0.005, ***p < 0.0005; n.s. not significant (unpaired Student’s t test). f Weights of excised xenograft tumors from the mice in (e) at the end points (25 days or 14 days after Tet-ON DDIT4 92.1 or OCM1 cell injection, respectively). The data are presented as the means ± s.e.m. (n = 4 mice per group). *p < 0.05; n.s. not significant (unpaired Student’s t test).

Article Snippet: Antibodies against the following antigens were used for immunoblot analysis: puromycin (Kerafast, EQ0001), FLAG (Sigma-Aldrich, F3165), YAP/ TAZ (Cell Signaling Technology, #8418), YAP (Cell Signaling Technology, #14074), TEAD4 (Abcam, ab58310), CYR61 (Santa Cruz Biotechnology, sc-13100), DDIT4 (Novus Biologicals, NBP1-22966), mTOR (Cell Signaling Technology, #2972), phospho-S6 (Cell Signaling Technology, #2211), S6 (Cell Signaling Technology, #2217), phospho-4E-BP1 (Cell Signaling Technology, #2855), 4E-BP1 (Cell Signaling Technology, #9644), phosphoERK (Cell Signaling Technology, #9101), ERK1/2 (Cell Signaling Technology, #4695), phospho-S6K1 (Cell Signaling Technology, #9205), S6K1 (Cell Signaling Technology, #9202), phospho-AKT (Cell Signaling Technology, #4060 and #4056), AKT2 (Cell Signaling Technology, #3063), eIF4E (Santa Cruz Biotechnology, sc-9976), PABP-C1 (Abcam, ab21060), phospho-paxillin (Cell Signaling Technology, #2541), phospho-p38 (Cell Signaling Technology, #4511), and vinculin (Cell Signaling Technology, #13901).

Techniques: Mutagenesis, Incubation, Migration, Injection

Journal: Experimental & molecular medicine

Article Title: YAP promotes global mRNA translation to fuel oncogenic growth despite starvation.

doi: 10.1038/s12276-024-01316-w

Figure Lengend Snippet: Fig. 6 Proposed model for the regulation of translation by serum in a manner dependent on the YAP/TAZ–TEAD–DDIT4–mTORC1 axis. (Left) In cells with an adequate supply of nutrients and growth factors (serum), G proteins such as Gq/G11 become activated, resulting in LATS1/2 inactivation and the consequent dephosphorylation of YAP/TAZ, which then translocate to the nucleus and bind to cognate TEAD transcription factors to activate the transcription of downstream target genes. However, some genes, such as DDIT4, are transcriptionally repressed by YAP/TAZ. Given that DDIT4 suppresses mTORC1 activity via TSC1/2, downregulation of DDIT4 by YAP/TAZ promotes mTORC1 activation, which ultimately leads to increased cap-dependent translation, especially of 5′TOP-containing mRNAs that encode components of the translational machinery. (Right) Conversely, YAP/TAZ are inactive under nutrient-poor conditions, resulting in high DDIT4 expression, suppression of mTORC1 activity, and inhibition of translation. Forced YAP activation in serum-starved cells is sufficient to restore translation to levels characteristic of serum-replete conditions.

Article Snippet: Antibodies against the following antigens were used for immunoblot analysis: puromycin (Kerafast, EQ0001), FLAG (Sigma-Aldrich, F3165), YAP/ TAZ (Cell Signaling Technology, #8418), YAP (Cell Signaling Technology, #14074), TEAD4 (Abcam, ab58310), CYR61 (Santa Cruz Biotechnology, sc-13100), DDIT4 (Novus Biologicals, NBP1-22966), mTOR (Cell Signaling Technology, #2972), phospho-S6 (Cell Signaling Technology, #2211), S6 (Cell Signaling Technology, #2217), phospho-4E-BP1 (Cell Signaling Technology, #2855), 4E-BP1 (Cell Signaling Technology, #9644), phosphoERK (Cell Signaling Technology, #9101), ERK1/2 (Cell Signaling Technology, #4695), phospho-S6K1 (Cell Signaling Technology, #9205), S6K1 (Cell Signaling Technology, #9202), phospho-AKT (Cell Signaling Technology, #4060 and #4056), AKT2 (Cell Signaling Technology, #3063), eIF4E (Santa Cruz Biotechnology, sc-9976), PABP-C1 (Abcam, ab21060), phospho-paxillin (Cell Signaling Technology, #2541), phospho-p38 (Cell Signaling Technology, #4511), and vinculin (Cell Signaling Technology, #13901).

Techniques: De-Phosphorylation Assay, Activity Assay, Activation Assay, Expressing, Inhibition

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Expression of DDIT4 is upregulated in LUAD cell lines and tissues. A. DDIT4 expression is upregulated in LUAD cell lines. B. DDIT4 expression is upregulated in LUAD tissues.

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Expressing

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Representative images of immunohistochemical staining of DDIT4 in lung adenocarcinoma tissue. A. Strong positive staining for DDIT4 in LUAD. B. Medium positive staining for DDIT4 in LUAD. C. Negative staining for DDIT4 in LUAD (A, B, C: 100× magnification).

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Immunohistochemical staining, Staining, Negative Staining

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Relationship between expression levels of DDIT4 and clinicopathological features of 75 LUAD specimens

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Expressing

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Kaplan-Meier survival curves for 75 LUAD patients according to DDIT4 expression status (log-rank test, P = 0.013).

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Expressing

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Univariate and multivariate analysis of prognostic factors in 75 LUAD patients

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques:

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: Analysis of the DDIT4 gene in the TCGA database. A. Expression of DDIT4 in NSCLC in the TCGA database. B. Expression of DDIT4 in LUAD in the TCGA database. C. Expression of DDIT4 in LUSC in the TCGA database. D. The relationship between the expression levels of DDIT4 and OS in NSCLC. E. The relationship between the expression levels of DDIT4 and OS in LUAD. F. The relationship between the expression levels of DDIT4 and OS in LUSC.

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Expressing

Journal: Journal of Cancer

Article Title: DDIT4 overexpression associates with poor prognosis in lung adenocarcinoma

doi: 10.7150/jca.60118

Figure Lengend Snippet: DDIT4 expression is unregulated in LUAD under hypoxia.

Article Snippet: Antibodies against DDIT4 were purchased from Atlas Antibodies AB (Sweden).

Techniques: Expressing