|
| Status |
Public on Jun 01, 2016 |
| Title |
TC32: Ridaforolimus-Selected-C9 |
| Sample type |
protein |
| |
|
| Source name |
Resistant Ewing Sarcoma Cell line to mTOR blockade
|
| Organism |
Homo sapiens |
| Characteristics |
cell type: Ewing Sarcoma cell line
cell line: TC32 clone
|
| Treatment protocol |
TC32 and TC71 ES clones with acquired resistance to ridaforolimus were generated by maintaining the corresponding parental cell lines with increasing concentrations of the agents (up to 50 μM) for 7 months. All parental and acquired drug resistant cell lines were tested twice per year for mycoplasma contamination using the MycoAlert Detection Kit (Lonza Group Ltd.) according to the manufacturer’s protocol and validated using short-tandem repeat fingerprinting with an AmpFLSTR Identifier kit as previously described. Herein, we determine subtle differences in acquired mechanism of resistance by ridaforolimus which inhibits only mTORC1 in ewing sarcoma cell lines using RPPA.
|
| Growth protocol |
Ewing Sarcoma cell lines sensitive or resistant to ridaforolimus grown in 2D-monolayer cultures were maintained in RPMI 1640 medium (Mediatech) containing 10% (vol/vol) fetal bovine serum (Gemini Bio-Products) and antibiotics (100 IU/ml penicillin and 100 mg/ml streptomycin [Mediatech]) in a humidified incubator at 37°C in a 5% CO2 atmosphere.
|
| Extracted molecule |
protein |
| Extraction protocol |
Protein extraction from cell lines was performed by homogenizing an approximate 10 mg of frozen tissue in 500 ul of the lysis buffer containing protease and phosphatase inhibitors using an electric tissue homogenizer (Pro Scientific). Total lysed proteins were quantified using BCA protein assay kit and stored for further analyses for RPPA.
|
| Label |
167 Primary Antibodies
|
| Label protocol |
Using a 2470 Arrayer (Aushon BioSystems), sample arrays were were processed, spotted onto nitrocellulose-coated FAST slides.
|
| |
|
| Hybridization protocol |
Protein-lysed-spots were probed with 167 validated primary antibodies and detected using a DakoCytomation-catalyzed system with secondary antibodies.
|
| Scan protocol |
Slides were scanned on a flatbed scanner to produce 16-bit tiff images. Spots from tiff images were identified and their densities were quantified by MicroVigene. Relative protein levels for each sample were determined by interpolation of each dilution curve from the standard curve (supercurve) of the slide (antibody). Supercurve is constructed from a script in R written by the informatics department. These raw values are given as log2 values. MicroVigene software program (VigeneTech) was used for automated spot identification, background correction, and individual spot-intensity determination.
|
| Description |
RPPA
|
| Data processing |
Expression data was normalized for possible unequal protein loading, taking into account the signal intensity for each sample for all antibodies tested. Log2 values were median-centered by protein to account for variability in signal intensity by time and were calculated using the formula log2 signal – log2 median. Principal component analysis was used to check for a batch effect and feature-by-feature two-sample t-tests were used to assess differences between treatment and control groups. We also used feature-by-feature one-way analysis of variance (ANOVA) followed by the Tukey test to perform pair comparisons for all groups. Beta-uniform mixture models were used to fit the resulting p value distributions to adjust for multiple comparisons. The cutoff p values and number of significant proteins were computed for several different false discovery rates (FDRs). Biostatistical analyses comparing two groups were performed using an unpaired t-test with Gaussian distribution followed by the Welch correction. To distinguish between treatment groups, we used one-way ANOVA with the Geisser-Greenhouse correction. Differences with p values <0.05 were considered significant. Within clustered image maps (CIM), unsupervised double hierarchical clustering used the Pearson correlation distance and Ward’s linkage method as the clustering algorithm to link entities (proteins or genes) and samples.
|
| |
|
| Submission date |
Feb 19, 2016 |
| Last update date |
Jun 01, 2016 |
| Contact name |
Joseph A. Ludwig |
| E-mail(s) |
jaludwig@mdanderson.org
|
| Phone |
713-792-4265
|
| Organization name |
UT-MD-Anderson Cancer Center
|
| Department |
Sarcoma Medical Oncology
|
| Lab |
Sarcoma Medical Oncology
|
| Street address |
4SCR2-1042 1901 East Rd
|
| City |
Houston |
| State/province |
Texas |
| ZIP/Postal code |
77054 |
| Country |
USA |
| |
|
| Platform ID |
GPL21489 |
| Series (2) |
| GSE78122 |
In vitro proteomic expression changes in Ewing sarcoma cell lines after mTOR blockade |
| GSE78124 |
Insulin-Like Growth Factor Receptor 1 and Mammalian Target Of Rapamycin Blockade: Novel Mechanisms of Resistance and Synergistic Drug Combinations for Ewing Sarcoma |
|
