Dataset Information

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model.

ABSTRACT: Anti-tumor drugs can effectively shrink the lesions of primary lung cancer; however, it has limited therapeutic effect on patients with brain metastasis (BM). A BM preclinical model based on a multi-organ microfluidic chip has been established proficiently in our previous work. In this study, the BM subpopulation (PC9-Br) derived from the parental PC9 cell line was isolated from the chip model and found to develop obvious resistance to antineoplastic drugs including chemotherapeutic agents (cisplatin, carboplatin, pemetrexed) and tyrosine kinase inhibitors (TKIs) which target epidermal growth factor receptor (EGFR); this suggested that the acquisition of drug-resistance by brain metastatic cells was attributable to the intrinsic changes in PC9-Br. Hence, we performed proteomic and revealed a greatly altered spectrum of BM protein expression compared with primary lung cancer cells. We identified the hyperactive glutathione (GSH) metabolism pathway with the overexpression of various GSH metabolism-related enzymes (GPX4, RRM2, GCLC, GPX1, GSTM4, GSTM1). Aldehyde dehydrogenases (ALDH1A1, ALDH3A1) were also found to be upregulated in BM. What's more, loss of EGFR and phosphorylated EGFR in PC9-Br gave reasons for the TKIs resistance. Collectively, our findings indicated potential mechanisms for the acquirement of drug resistance occurred in BM, providing new strategies to overcome therapeutic resistance in lung cancer BM.

SUBMITTER: Xu M

PROVIDER: S-EPMC7783320 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model.

Xu Mingxin M Wang Yingyan Y Duan Wenzhe W Xia Shengkai S Wei Song S Liu Wenwen W Wang Qi Q

Frontiers in bioengineering and biotechnology 20201222

Anti-tumor drugs can effectively shrink the lesions of primary lung cancer; however, it has limited therapeutic effect on patients with brain metastasis (BM). A BM preclinical model based on a multi-organ microfluidic chip has been established proficiently in our previous work. In this study, the BM subpopulation (PC9-Br) derived from the parental PC9 cell line was isolated from the chip model and found to develop obvious resistance to antineoplastic drugs including chemotherapeutic agents (cisp ...[more]

PMID: 33415100

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Project description:Targeted anticancer therapies rely on the identification of patient subgroups most likely to respond to treatment. Predictive biomarkers play a key role in patient selection, while diagnostic and prognostic biomarkers expand our understanding of tumor biology, suggest treatment combinations, and facilitate discovery of novel drug targets. We have developed a high-throughput microfluidics method for mutation detection (MUT-MAP, mutation multi-analyte panel) based on TaqMan or allele-specific PCR (AS-PCR) assays. We analyzed a set of 71 mutations across six genes of therapeutic interest. The six-gene mutation panel was designed to detect the most common mutations in the EGFR, KRAS, PIK3CA, NRAS, BRAF, and AKT1 oncogenes. The DNA was preamplified using custom-designed primer sets before the TaqMan/AS-PCR assays were carried out using the Biomark microfluidics system (Fluidigm; South San Francisco, CA). A cross-reactivity analysis enabled the generation of a robust automated mutation-calling algorithm which was then validated in a series of 51 cell lines and 33 FFPE clinical samples. All detected mutations were confirmed by other means. Sample input titrations confirmed the assay sensitivity with as little as 2 ng gDNA, and demonstrated excellent inter- and intra-chip reproducibility. Parallel analysis of 92 clinical trial samples was carried out using 2-100 ng genomic DNA (gDNA), allowing the simultaneous detection of multiple mutations. DNA prepared from both fresh frozen and formalin-fixed, paraffin-embedded (FFPE) samples were used, and the analysis was routinely completed in 2-3 days: traditional assays require 0.5-1 µg high-quality DNA, and take significantly longer to analyze. This assay can detect a wide range of mutations in therapeutically relevant genes from very small amounts of sample DNA. As such, the mutation assay developed is a valuable tool for high-throughput biomarker discovery and validation in personalized medicine and cancer drug development.

Dataset Information

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model.

Publications

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model.

Similar Datasets

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