Transcriptomic data of BT549 triple negative breast cancer cells treated with 20 μM NU7441,a DNA-dependent kinase inhibitor

Published: 5 February 2024| Version 2 | DOI: 10.17632/xjz27scmjd.2


DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is a multifunctional serine-threonine protein kinase that plays pleiotropic roles in cancer.NU7441 is a specific DNA-PKcs inhibitor.We investigated the effect of the DNA-dependent kinase (DNA-PK) inhibitor, NU7441, on the transcriptome of BT549 triple negative breast cancer (TNBC) cells.Total RNA extracted from NU7441 or vehicle-treated cells was processed for preparation of sequencing libraries . Assessment of read quality was performed using fastqc tool. Trimming and filtering low-quality reads were performed using fastp. Reads were aligned by hisat2. SAM files were converted to BAM files using Samtools. Mapped reads were quantified using featureCounts.The RNA sequencing results were also subjected to gene differential expression analysis, Gene Ontology (GO) analysis and KEGG pathway analysis. After NU7441 treatment, total number of 2045 differential genes were selected according to |log2(FoldChange)| >= 1 & padj<= 0.05, among which 1365 genes were down-regulated and 680 genes were up-regulated. The differential genes in pattern recognition receptors (PRRs) immune responses signals, including NOD-like receptor signaling, Toll-like receptor signaling, RIG-I-like receptor signaling and Cytosolic DNA-sensing pathways were noted in this paper .


Steps to reproduce

The BT549 cell line was cultured on cell culture plates, and the DNA-PKcs inhibitor, NU7441, was added for 48 h at a concentration of 20 μM (below the IC50 value) when the cell density grew to 80%. Control cells are set up at the same time. BT549 cells were collected. Total RNA was extracted from the cells using Trizol reagent. RNA quality was determined using an Agilent 5400 and quantified using a NanoDrop, and the RNA samples were used to construct sequence libraries. The first strand of cDNA was synthesised in M-MuLV reverse transcriptase system using fragmented mRNA as template and random oligonucleotides as primers, followed by degradation of the RNA strand by RNaseH, and synthesis of the second strand of cDNA using dNTPs as raw material under DNA polymerase I. The purified double-stranded cDNA was extracted from the cells using Agilent 5400 and quantified by NanoDrop. The purified double-stranded cDNA was end-repaired, A-tailed and ligated into sequencing junctions, and the cDNA of 370-420 bp was screened with AMPure XP beads, amplified by PCR, and the PCR products were purified again with AMPure XP beads to obtain the final library. Paired-end RNA-seq sequencing library was sequenced with the Illumina HiSeq xten (2 × 150 bp read length) by Novogene (Beijing , China). R statistical package was utilized for differential expression analysis. The raw reads were in FASTQ format. The quality of the reads were assessed using fastqc tool. The adapters, and low quality reads were filtered out from the FASTQ files using fastp tool. TThe fastqc tool was used to re-assess the filtered reads prior to mapping. The FASTQ files after the quality trimming and assessment were used for mapping. The Ensemble Homo sapiens GRCh38 genome was used as reference genome for mapping the clipped reads ( _ sapiens/Info/Index ). Prior to mapping, indexing of reference genome was done using HISAT2 indexing scheme. Subsequently, clean reads were mapped using the HISAT2 tool against the index file . The featureCounts tool was used for quantification of mapped reads. Differentially expressed genes were screened using edgeR, and differentially expressed genes were subjected to gene ID conversion, GO functional annotation and enrichment analysis, and KEGG functional annotation and enrichment analysis using clusterProfiler(v4.10.0) in R studio.


Dalian Medical University


Molecular Genetics, Molecular Oncology


Natural Science Foundation of Liaoning Province