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非小细胞肺癌细胞顺铂耐药后高级生物信息学分析及通路预测。

Advanced bioinformatic analysis and pathway prediction of NSCLC cells upon cisplatin resistance.

机构信息

School of Basic Pharmaceutical and Toxicological Sciences, College of Pharmacy, University of Louisiana Monroe, Monroe, LA, USA.

Department of Pharmaceutical Sciences, School of Pharmacy, Texas Tech University Health Sciences Center, Amarillo, TX, USA.

出版信息

Sci Rep. 2021 Mar 22;11(1):6520. doi: 10.1038/s41598-021-85930-y.

DOI:10.1038/s41598-021-85930-y
PMID:33753779
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7985311/
Abstract

This study aims to identify pathway involvement in the development of cisplatin (cis-diamminedichloroplatinum (II); CDDP) resistance in A549 lung cancer (LC) cells by utilizing advanced bioinformatics software. We developed CDDP-resistant A549 (A549/DDP) cells through prolonged incubation with the drug and performed RNA-seq on RNA extracts to determine differential mRNA and miRNA expression between A549/DDP and A549 cells. We analyzed the gene dysregulation with Ingenuity Pathway Analysis (IPA; QIAGEN) software. In contrast to prior research, which relied on the clustering of dysregulated genes to pathways as an indication of pathway activity, we utilized the IPA software for the dynamic evaluation of pathway activity depending on the gene dysregulation levels. We predicted 15 pathways significantly contributing to the chemoresistance, with several of them to have not been previously reported or analyzed in detail. Among them, the PKR signaling, cholesterol biosynthesis, and TEC signaling pathways are included, as well as genes, such as PIK3R3, miR-34c-5p, and MDM2, among others. We also provide a preliminary analysis of SNPs and indels, present exclusively in A549/DDP cells. This study's results provide novel potential mechanisms and molecular targets that can be explored in future studies and assist in improving the understanding of the chemoresistance phenotype.

摘要

本研究旨在利用先进的生物信息学软件,鉴定顺铂(cis-diamminedichloroplatinum(II);CDDP)耐药 A549 肺癌(LC)细胞中涉及的通路。我们通过长时间用药物孵育来建立 CDDP 耐药 A549(A549/DDP)细胞,并对 RNA 提取物进行 RNA-seq,以确定 A549/DDP 和 A549 细胞之间差异表达的 mRNA 和 miRNA。我们使用 IPA(QIAGEN)软件分析基因失调。与先前的研究不同,我们不是依赖于失调基因聚类到通路上来指示通路活性,而是利用 IPA 软件根据基因失调水平对通路活性进行动态评估。我们预测了 15 条对化疗耐药有显著贡献的通路,其中一些通路以前没有被报道或详细分析过。其中包括 PKR 信号通路、胆固醇生物合成和 TEC 信号通路,以及 PIK3R3、miR-34c-5p 和 MDM2 等基因。我们还对 A549/DDP 细胞中特有的 SNP 和 indels 进行了初步分析。本研究的结果提供了新的潜在机制和分子靶点,可以在未来的研究中进行探索,并有助于提高对化疗耐药表型的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/a157bf1995ce/41598_2021_85930_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/6a78c0c0ea65/41598_2021_85930_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/73de75dc8781/41598_2021_85930_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/c0f9a3b6faed/41598_2021_85930_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/0dc2c6c18fb8/41598_2021_85930_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/f4f0b22c2212/41598_2021_85930_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/a157bf1995ce/41598_2021_85930_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/6a78c0c0ea65/41598_2021_85930_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/73de75dc8781/41598_2021_85930_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/c0f9a3b6faed/41598_2021_85930_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/0dc2c6c18fb8/41598_2021_85930_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/f4f0b22c2212/41598_2021_85930_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e6fd/7985311/a157bf1995ce/41598_2021_85930_Fig6_HTML.jpg

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