Scientists detail major mechanism lung cancers use to evade immuneattack WeillCornell NatureComms
CRISPR knockouts in the HKP1 and CMT-167 cell lines were generated using sgRNA-CAS9 ribonucleoprotein complexes being electroporated using the NEON transfection system . Materials used to generate sgRNA-CAS9 RNP complexes were purchased from Integrated DNA Technologies. In brief, duplexed sgRNAs were generated by mixing ATTO-550-tracrRNA and target crRNAs in a 1:1 ratio, heating the mixture at 95 °C for 5 min. RNPs were generated by mixing sgRNAs with CAS9 in a 1:1.
For intracellular staining, if stimulation and golgi blocking were required, samples were incubated for 4 h in complete RPMI at 37 °C in a humidified incubator, with PMA , ionomycin , Brefeldin A , and Monensin . Following this, samples were surface stained as above before undergoing fixation and permeabilization in accordance with the manufacturers’ protocol. Following this samples were stained with intracellular antibodies, washed and resuspended in FACS Buffer.
cDNA libraries were generated using the Illumina TruSeq RNA Sample Preparation kit V2 with non-stranded Poly A selection, in accordance with the manufacturer’s protocol. About 2 × 50 bp single-end sequencing was performed on the HiSeq 4000 sequencer. Raw sequencing reads were aligned to the mm9 mouse reference genome using Tophat2 .
FPKM expression matrices were employed for heatmaps and Log2 transformed FPKM values were used for principal component analysis and visualized using ggplot2 in R . Heatmaps were made using the Pheatmap and RColorBrewer packages, and the Venny web portal was used to make all Venn diagrams. Differential gene expression was performed on non-normalized counts using the standard DESeq2 package protocol in R, with pairwise comparisons of all WT vs KO, day 10 WT vs KO, and day 14 WT vs KO.
NSCLC-specific IRE1α gene expression signatures were generated by taking the up and downregulated genes identified by DGE at a variety of cutoffs and applying them to the TCGA-LUAD mRNA-seq dataset using the ssGSEA function of the GSVA package , generating a per patient enrichment score for each signature. Patients were ranked by enrichment score and evaluated for clinicopathologic factors in the top and bottom tertiles.
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