|
| Status |
Public on Apr 20, 2021 |
| Title |
223310 |
| Sample type |
RNA |
| |
|
| Source name |
Subcutaneous tumor
|
| Organism |
Mus musculus |
| Characteristics |
disease: Melanoma
genotype: Hgftg;Cdk4R24C/R24C
mouse strain: B6.cBrd
treatment: Non-responders to 10mg/kg anti-mouse PD-L1 mIgG1 D265A in PBS
|
| Treatment protocol |
See publication Materials and Methods: Immunotherapy treatment
|
| Growth protocol |
See publication Materials and Methods: Melanoma allograft model
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Tumor samples were lysed and homogenized for RNA isolation using the RNeasy Mini Kit following manufacturer’s protocol for purification of total RNA with on-column DNase digestion (Qiagen). RNA purity and concentration were determined spectrophotometrically, and RNA quality was assessed using the Agilent Technology Tape Station RNA Screen Tape.
|
| Label |
Biotin
|
| Label protocol |
A total input of 800ng of isolated RNA was applied to the Message Amp II-Biotin Enhanced aRNA Amplification Kit according to manufacture protocol for first and second Strand cDNA synthesis followed by in-vitro transcription (IVT) reaction to synthesize the complementary RNA (cRNA) for transcriptional amplification and biotin labeling.
|
| |
|
| Hybridization protocol |
A total of 20 ug of biotinylated cRNA was then fragmented for hybridization on the Affymetrix GeneChip Mouse Genome 430 2.0 Array.
|
| Scan protocol |
GeneChip Operating Software Tool was used for data capture and quality
|
| Data processing |
Raw CEL files from the scan were analyzed using a microarray pipeline written in ‘R’. Data were normalized using the Robust Multichip Average (RMA) method. Linear modeling was performed using Limma’s lmFit function (LIMMA, RRID:SCR_010943, Limma powers differential expression analyses for RNA-sequencing and microarray studies), and differential gene expression was determined using the contrasts.fit and eBayes functions. Top pathways for each comparison (Non-responders, Responders, and Relapse; normalized with control IgG treatment samples) were determined using (Gene Set Enrichment Analysis) GSEA (SeqGSEA, RRID:SCR_005724, http://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Gsea_Citation). The top 10 up and down regulated pathways were generated from Reactome (Reactome diagram viewer: data structures and strategies to boost performance) based on NES scores if Q-value meets threshold of less than 0.1. The top genes from Reactome were then used to run GSVA (Gene Set Variation Analysis for microarray and RNA-seq data) to find enrichment for each sample. Heatmaps were generated for the GSVA analysis, columns (samples) were sorted by group and rows (pathways) were clustered by Euclidean distance. Individual sample differential expression heatmap was analyzed by computing the log fold-change between a sample against the mean expression of the IgG samples, upper and lower limits shown on the heat map are log values from -2 to 2. Gene expression data from this report is available through the Collaborative Bioinformatics Resource of NIH, Center for Cancer Research (CCR). https://zenodo.org/record/3770853#.X9PmhhNKg_N.
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| |
|
| Submission date |
Apr 19, 2021 |
| Last update date |
Apr 20, 2021 |
| Contact name |
abdalla abdelmaksoud |
| E-mail(s) |
abdalla.abdelmaksoud@nih.gov
|
| Organization name |
NCI
|
| Street address |
37 Convent Dr
|
| City |
bethesda |
| State/province |
maryland |
| ZIP/Postal code |
20814 |
| Country |
USA |
| |
|
| Platform ID |
GPL1261 |
| Series (1) |
| GSE172320 |
Gene Expression profile for the characterization of PD-L1 blockade in melanoma model |
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