Targeting glutamine-addiction and overcoming CDK4/6 inhibitor resistance in human esophageal squamous cell carcinoma

The dysregulation of Fbxo4-cyclin D1 axis occurs at high frequency in esophageal squamous cell carcinoma (ESCC), where it promotes ESCC development and progression. However, defining a therapeutic vulnerability that results from this dysregulation has remained elusive. Here we demonstrate that Rb and mTORC1 contribute to Gln-addiction upon the dysregulation of the Fbxo4-cyclin D1 axis, which leads to the reprogramming of cellular metabolism. This reprogramming is characterized by reduced energy production and increased sensitivity of ESCC cells to combined treatment with CB-839 (glutaminase 1 inhibitor) plus metformin/phenformin. Of additional importance, this combined treatment has potent efficacy in ESCC cells with acquired resistance to CDK4/6 inhibitors in vitro and in xenograft tumors. Our findings reveal a molecular basis for cancer therapy through targeting glutaminolysis and mitochondrial respiration in ESCC with dysregulated Fbxo4-cyclin D1 axis as well as cancers resistant to CDK4/6 inhibitors.

For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.
n/a Confirmed 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
No software was used.

Data analysis
We used R-Project Bioconductor (ver. 3.4.2, 09/28/2017) to normalize the affymetrix data. The code is listed in the following: # Load the script from the internet and install bioconductor source("http://bioconductor.org/biocLite.R") # Then, download and install each package biocLite("affy") biocLite("oligo") biocLite("limma") # Load the Affymetrix library library(affy) # Change the directory, read the relative CEL files in it, and normalize the data data <-ReadAffy() eset <-rma(data) # Finally, save the data to an output file that can be used by GSEA analysis (Data will be log2 transformed and normalized) write.exprs(eset,file="data.txt") 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.

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 The authors declare that all the data supporting the findings of this study are available with the article and its Supplementary Information files and from the corresponding author on reasonable request. In addition, the genome-wise data referenced during the study are available in a public repository from the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with GEO Accession #: GSE100942, GSE20347, GSE40513 and GSE84597, respectively.

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.

Sample size
For all cell-based work, three-distinct sample collections were performed in order to achieve high repeating efficiency and sufficient biostatistic significance. For all mice-based studies, 8 tumour samples were collected for final analysis; scientifically, this number can produce high confident statistical results.
Data exclusions No data was excluded from the final analysis.

Replication
All attempts at replication were successful.
Randomization All the cells and mice were randomly allocated into different groups.

Blinding
The investigators were blinded to group allocation during data collection and/or analysis.

Reporting for specific materials, systems and methods
We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. Authentication NIH3T3 and 293T cells have the authentication information from ATCC. The earliest frozen stocks of all ESCC cell lines (TE1, TE7, TE8, TE10 and TE15) have been stored at the Cell Culture Core of the University of Pennsylvania. All cells were authenticated by short tandem repeat analysis for highly polymorphic microsatellites FES/FPS, vWA31, D22S417, D10S526 and D5S592 as performed by the Cell Culture Core to validate the identity of cells by comparing the earliest stocks with those grown more than 8-12 passages. We established the MEF cells through a 3T9 protocol, in which cells were passaged and spontaneously transformed to proliferative cells after passage 9; the MEFs were identified through genotyping using PCR methods. TE7 PDR and TE10 PDR cells were cultured in medium containing 1μM palbociclib; the authentication of these cells was performed by flow cytometry analysis upon exposing to 1μM palbociclib for 24 hours (PDR cells can go through G1 arrest even in the presence of palbociclib).

Mycoplasma contamination
All cell lines were tested negative for mycoplasma contamination.
Commonly misidentified lines (See ICLAC register) TE7 cells were used in this study. TE7 cell, harboring cyclin D1 P287A mutation, is a good model to investigate the role of cyclin D1 in regulating Gln-addiction. Morphological observation characterizes that TE7 cells can form SCC xenografts.

Animals and other organisms
Policy information about studies involving animals; ARRIVE guidelines recommended for reporting animal research

Wild animals
The study did not involve wild animals.

Field-collected samples
The study did not involve samples collected from the field.

Ethics oversight
The protocol was approved by the Institutional Animal Care and Use Committee (IACUC) at the Medical University of South Carolina (MUSC). The MUSC ARC # is 3339.
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Flow Cytometry
Plots Confirm that: The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Sample preparation
The flow cytometry was performed on cell lines, and the biological sources of all the cells used are indicated above. The procedure for Annexin V staining: cells were firstly exposed to Gln-depletion, or relative treatment, for example, vehicle, CB, Met, CB+Met. After indicated treating time, cells will be trypsinized and suspended in medium collected before trypsinization. Cells will be washed in 1x PBS and stained by Annexin V following manufacture's protocol (BD Biosciences, Catalog No. 556420). The procedure for cell cycle analysis: cells were firstly exposed to medium with or without 1μM palbociclib for 24 hours. The next day, cells were trypsinized, washed, fixed and stained with 10 μg/mL propidium iodide (PI) containing 100 μg/mL RNaseA before FACS analysis.

Software
The data were collected using BD FACSuite software, and the data were analyzed using FlowJo vX.0.7.
Cell population abundance For Annexin V staining, the cell population abundance was about 80-94%; the cells were gated based on the control groups in order to keep consistency for a specific cell line.

nature research | reporting summary
October 2018 For cell cycle analysis, the cell population abundance was about 75-80%; the cells were gated for single cell based on SSC+FSC in asynchronized group.

Gating strategy
For apoptosis analysis, FSC vs SSC plots were firstly used to gate cells and to identify any changes in the scatter properties of the cells. To define Annexin V +/− population boundaries, control and staurosporine-treated cells were utilized. The boundary for +/− was determined by setting the gate in which no cell detected for unstained cells while positive cells were shown in staurosporine-treated groups. Thereafter, apply this gating for all the other groups in one specific analysis. For cell cycle analysis, the debris was excluded according to SSC+FSC gating and narrowed down to the single cell population. Thereafter, the DNA profile was optimized to adjust the G0/G1 peak to appear around channel 50 by changing the voltage.
Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information.