TRIM21 and PHLDA3 negatively regulate the crosstalk between the PI3K/AKT pathway and PPP metabolism

PI3K/AKT signaling is known to regulate cancer metabolism, but whether metabolic feedback regulates the PI3K/AKT pathway is unclear. Here, we demonstrate the important reciprocal crosstalk between the PI3K/AKT signal and pentose phosphate pathway (PPP) branching metabolic pathways. PI3K/AKT activation stabilizes G6PD, the rate-limiting enzyme of the PPP, by inhibiting the newly identified E3 ligase TIRM21 and promotes the PPP. PPP metabolites, in turn, reinforce AKT activation and further promote cancer metabolic reprogramming by blocking the expression of the AKT inhibitor PHLDA3. Knockout of TRIM21 or PHLDA3 promotes crosstalk and cell proliferation. Importantly, PTEN null human cancer cells and in vivo murine models are sensitive to anti-PPP treatments, suggesting the importance of the PPP in maintaining AKT activation even in the presence of a constitutively activated PI3K pathway. Our study suggests that blockade of this reciprocal crosstalk mechanism may have a therapeutic benefit for cancers with PTEN loss or PI3K/AKT activation.

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection

Data analysis
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors/reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

Hong Wu
Mar 15, 2020 Softmax pro 6.3 was used to collect fluorescent and absorption data for enzyme assay. Perkinelmer 2030 manager was used for luciferase signal collection. Seahorse XFe24 was used for ECR detection. Real-Time PCR Analysis Software CFX Maestro Software was used for Real-Time PCR signal collection. Image lab 5.0 was used for western blot and colony signal collection. Xcalibur Software 2.2.0 was used for metabolism signal collection. BD FACSuite Flow Cytometry Software was used for FACS signal collection.
OriginPro 2018C b9.5.0.193 was used for data plotting and statistical analysis. Image lab 5.0 was used for western blot data and colony formation analyzing. Xcalibur Software 2.2.0 was used for metabolism data acquisition and processing. Flowjo V10 was used for FACS data analyzing. Statistical analyses were conducted in R v3.6.0. Pathway activity score was calculated by R package GSVA V1.20.0.

October 2018
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative. The source data underlying Figure 1 -7 as well as Supplementary Figure 1 -7 are provided as a Source Data file. All the other data supporting the findings of this study are available within the article and its supplementary information files and from the corresponding author upon reasonable request. The TCGA database used in the study was along with appropriately accessible links.
Statistical methods were not used to predetermine sample size. All sample size was at least three independent replicates. Animal and patient sample size was determined by experimental feasibility and sample availability to demonstrate certain results.
No data were excluded from the analyses.
Biological replications (three biological replicates at least) and statistics were indicated in the legends. All attempts at replication were successful based on replications on different days showing comparable significance level for biological comparison.
Samples were allocated into experimental groups by the confirmed genetic modification of the cell line (e.g. CRISPR-Cas9 deletion, siRNA knocking down, doxycycline-induced protein expression) and/or culturing conditions (e.g. isotope tracing). Mouse samples were allocated into experimental groups by the confirmed Pten genetic deletion. This design does not allow for randomization, as the origin of samples is critical. However, whenever possible samples were analyzed in a randomized order (i.e. when run on liquid-chromatography mass spectrometry).
The researchers were blinded during animals research data collection, experiments apart from animal studies, and data analysis.