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Transcriptomic profiling of A549 lung adenocarcinoma cells treated with natural killer cell-derived exosomes reveals pyroptosis-related ceRNA networks_miRNAseq

ABSTRACT: Lung adenocarcinoma (LUAD) remains a challenging malignancy with limited treatment options. Natural killer (NK) cell-derived exosomes have emerged as a promising anti-cancer therapeutic approach. To investigate the transcriptomic mechanisms underlying NK exosome-induced cytotoxicity in LUAD, we performed comprehensive RNA sequencing of A549 human LUAD cells treated with exosomes isolated from NK92 human NK cells (NK92-exo) versus untreated controls. This dataset includes mRNA and miRNA expression profiles from NK92-exo-treated and control A549 cells after 72 hours of treatment. Analysis revealed significant alterations in the expression of pyroptosis-related genes, particularly the downregulation of miR-5096 and upregulation of CARD8. Furthermore, we constructed competing endogenous RNA (ceRNA) networks involving lncRNAs, circRNAs, miRNAs, and mRNAs that may mediate the observed pyroptotic cell death. This transcriptomic resource provides insights into the molecular mechanisms of NK exosome-induced anti-tumor effects and identifies potential therapeutic targets for LUAD treatment.

ORGANISM(S): Homo sapiens

PROVIDER: GSE312865 | GEO | 2026/09/29

REPOSITORIES: GEO

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Project description:Purpose: Although Nm23-H1 lacks secretion signal peptide, its presence in the extracellular space and extracellular vesicles (EVs) is widely reported. Proteomics profiling revealed that EVs released by cancer cells may contain Nm23-H1 proteins but the role of vesicular Nm23-H1 remains unknown. Here, we investigated the function of vesicular Nm23-H1 by performing transcriptome analysis of the recipient post 24 h of PBS (control) or exosome treatment. Methods: MCF-7 cells were treated with PBS or exosomes for 24 h. Cells were lysed in TRIzol. RNA quality was verified with Agilent 5400 fragment analyzer prior to library preparation. SMART-Seq2 library construction was performed, and sequencing was carried out in 2×100 cycle paired-end mode on a BGI DNBSEQ-G400 sequencer. FASTQ raw read files were trimmed using cutadapt to remove adapter sequences, primers, poly-A tails, and other types of unwanted sequences. The trimmed reads were then be mapped to the genome (UCSC hg38) using STAR with default parameters. Reads were quantified and differentially expressed genes (DEGs) were identified using DEBrowser (v1.19.1) as a graphical interface to DESeq2 with significance considered at q-value ≤ 0.05 and absolute fold change ≥ 1.2. qRT–PCR validation was performed using SuperScript® III First-Strand Kit and LightCycler 480 SYBR Green I assays. Results: We examined the changes in the transcriptome of MCF-7 cells post exosome treatment. Polyadenylated RNA-sequencing was performed on RNA isolated from the recipient cells post 24 h of PBS (control) or exosome treatment. Upon 231 exo treatment, changes in the transcript levels of 122 differentially expressed genes (DEGs) were observed, whereas 231/H1 exo treatment induced a differential expression of 449 genes. A common set of 45 genes was found to be regulated by both 231 exo and 231/H1 exo treatments. More importantly, the comparison between 231/H1 exo and 231 exo treatments revealed 107 differentially expressed genes. Conclusions: Our transcriptome analysis of the recipient cells post exosome treatment revealed multiple genes that are regulated upon exosome treatment. Exosomes with an elevated level of Nm23-H1 caused alterations in the transcript level of multiple cancer-related genes in the recipient cells. Moreover, it stimulated type I interferon signaling via STAT1 phosphorylation. These results indicate an atypical signaling pathway mediated by the uptake of exosomes with an elevated level of Nm23-H1, which may account for the anti-metastatic effect of Nm23-H1 in the tumor microenvironment.

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Transcriptomic profiling of A549 lung adenocarcinoma cells treated with natural killer cell-derived exosomes reveals pyroptosis-related ceRNA networks_miRNAseq

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