Integration of metabolomics and transcriptomics to reveal metabolic

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Integration of metabolomics and transcriptomics to reveal metabolic characteristics and key targets associated with cisplatin resistance in non-small cell lung cancer Yuhuan Shi, Yuanyuan Wang, Wanying Huang, Yang Wang, Rong Wang, and Yongfang Yuan J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.9b00209 • Publication Date (Web): 02 Aug 2019 Downloaded from pubs.acs.org on August 3, 2019

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Journal of Proteome Research

Integration of metabolomics and transcriptomics to reveal metabolic characteristics and key targets associated with cisplatin resistance in non-small cell lung cancer

Yuhuan Shi1#,Yuanyuan Wang1#, Wanying Huang2, Yang Wang 2, Rong Wang1, Yongfang Yuan1*

1Department

of Pharmacy, Shanghai 9th People's Hospital, Shanghai Jiao Tong

University School of Medicine, 639 Zhi Zao Ju Rd, Shanghai 200011, China 2Department

of Pharmacology and Chemical Biology, Shanghai Jiao Tong University

School of Medicine, Shanghai 200025, China

# These

authors contributed equally to the manuscript

*Address correspondence to: Yongfang Yuan, Ph D ， Department of Pharmacy, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, China. E-mail: [email protected]

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ACS Paragon Plus Environment

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ABSTRACT

Continuous exposure to cisplatin can induce drug resistance to limit efficacy, however, the underlying mechanisms correlated to cisplatin resistance are still unclear. Drug-sensitive A549 cells and cisplatin-resistant A549/DDP cells were used to explore the potential metabolic pathways and key targets associated with cisplatin resistance by integrating untargeted metabolomics with transcriptomics. Data are available via ProteomeXchange with identifier PXD013265. The results of comprehensive analyses showed that 19 metabolites were significantly changed in A549/DDP vs A549 cells, and some pathways had a close relationship with cisplatin resistance, such as the biosynthesis of aminoacyl-tRNA, glycerophospholipid metabolism, and glutathione metabolism. Moreover, transcriptomics analysis showed glutathione metabolism was also obviously affected in A549/DDP, which indicated that glutathione metabolism played an import role in the process of drug resistance. Meanwhile, transcriptomics analysis suggested the four enzymes related to glutathione metabolism - CD13, GPX4, RRM2B, and OPLAH as potential targets of cisplatin resistance in NSCLC. Further studies identified the over-expressions of these four enzymes in A549/DDP. The elucidation of mechanism and discovery of new potential targets may help us have a better understanding of cisplatin resistance.

KEYWORDS

metabolomics; transcriptomics; cisplatin resistance; NSCLC

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INTRODUCTION With the increasing morbidity and mortality, more than 1.5 million people died from lung cancer every year, it’s the most prevalent cancer all over the world. Non–small cell lung cancer (NSCLC) accounts for nearly 85% of all lung cancer patients1. Patients are often in advanced stages when they are diagnosed with NSCLC2, cisplatin (DDP) is usually the first-line chemotherapeutic drug for advanced NSCLC over two decades because of its wide and strong curative effects by cross-link DNA causing DNA damage in cancer cells3. However, due to the cisplatin resistance occurrence, chemotherapeutic effects are undermined and limited. Thus, to explore the underlying mechanism of cisplatin resistance in NSCLC is of great significance. Although multiple mechanisms associated with cisplatin resistance such as altered DNA repair, defective drug transport system and drug inactivation are widely reported, cisplatin resistance is still ongoing4, 5. Now, the metabolic pattern and shift between drug-sensitive A549 cells and cisplatin-resistant A549/DDP cells were explored by integrating untargeted metabolomics with transcriptomics to deeply understand the cisplatin resistance.

Metabolomics have been widely applied to quantify the changes of metabolites in cells, tissues and the whole organism, aimed to study the dynamic changes of endogenous metabolites and reflect the metabolic pathways and shifts in biological processes6. The integration of ultra-high performance liquid chromatography (UPLC) and quadrupole time-of-flight tandem mass spectrometry (Q/TOF-MS) provides rapid separation, detection and high resolution as a useful technique support to the untargeted metabolomics analysis. The application of metabolomics offeres new insights to explore the mechanisms of multidrug resistance. RNA sequencing (RNA-Seq) is an important way for the transcriptome analysi to find many essential functional genes and provide much genetic information underlying biological systems. Moreover, it has the potential to explore targets involved in drug resistance and pinpoint related pathways in tumor 3



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process7. Metabolomics and transcriptomics focus on metabolites and functional mRNAs respectively. The joint application of the two“omics”technologies possesses the high efficiency of identifying key metabolic pathways and functional genes in lung cancer patients8.

In this study, it is the first time to combine the UPLC-Q/TOF-MS with RNA-Seq analysis to evaluate the changes of metabolites in A549 and A549/DDP cells before and after cisplatin exposure. Through reasonable prediction of the resulting networks, potential metabolic pathways and targets were attempted to be identified to understand the mechanisms underlying cisplatin resistance in NSCLC.

MATERIALS AND METHODS Materials and Reagents A549 cells were obtained from ATCC, cisplatin - resistant A549/DDP cells were established as described previously9. Cisplatin was purchased from Sigma (Germany). HPLC grade methanol、acetonitrile、formic acid were purchased from Merck company (Germany), Watson's distilled water was used as Deionized Water. RNA kit was purchased from Takara company (Japan). CCK8 kit and BCA assay kit were provided by Beyotime Biotechnology Corporation (Shanghai, China). RSL and bestatin were purchased from sigma company (USA).

Cell Culture and CCK8 Assay A549 and A549/DDP cells were cultured in DMEM (Hyclone) media with 10% FBS (Sigma) at 37°C with 5% CO2, the viability of A549 and A549/DDP cells was evaluated by using CCK8 kit. Cells were seeded in 96-well plates at 3500 cells per well, after 24 hours, different concentrations of cisplatin (0 - 150 μM) were added to the plate and then incubated for another 48 h at 37°C. After that, the CCK8 solution was put into the wells 4


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and incubated for 1 h before the measurement of the optical density (OD) at 450 nm according to the instructions.

RNA-Seq Analysis Total RNA was extracted from the cells seeded in six well plates by using RNA kit (Takara) following the manufactor instructions. RNA-seq analysis was completed by Beijing genomics institute through the BGISEQ-500 system. Raw data were filtered by using SOAP nuke and saved as FASTQ format10. Clean reads were mapped to reference transcriptome by using Bowtie2 and HISAT software, the gene expression level was calculated by RSEM. Gene ontology (GO) and KEGG pathway enrichment were conducted by DAVID.

UPLC/Q-TOF/MS The UPLC/Q-TOF/MS was performed by using an Agilent 1290 Infinity UPLC, coupled with an Agilent 6538 UHD and an Accurate-Mass Q-TOF/MS. The separation was carried out on a Waters HILIC column (1.7 μm, 100×3.0 mm) with mobile phase consisting of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B) ( 0~2 min，5% B；2~13 min，5%→95% B；13~15 min，95% B), the flow rate was 0.4 ml/min and the injection volume was set to 3 μl. The data was detected by MS detector under positive and negative ion modes respectively. The optimized system conditions were performed as follows: Gas flow rate 11 L/min, gas temperature at 350℃, nebulizer 50 Psi, Capillary 4 KV (+)/3.5 KV (-), Mass range m/z 50~1500.

Samples Preparation A549 and A549/DDP cells were cultured in 6 cm dishes, when grown to a confluency of nearly 90%, cells were divided into 4 groups (n=12): A549 (-), A549 (+), A549/DDP (-), A549/DDP (+). A549 (+) and A549/DDP (+) groups were incubated with 50 μM

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cisplatin for 48 hours, while A549 (-) and A549/DDP (-) groups were incubated without cisplatin. Cells were washed twice with PBS before adding precooled methanol to the cell culture dishes, then the suspension was transferred into 1.5 ml Ep tube and centrifuged at 13000 rpm at 4℃ for 10 minutes. 1 ml supernate was collected to dry under nitrogen, then dissolved by 200 μl 50% acetonitrile with inter standard 2-Chloro-L-phenylalanine. After the mixture was vortexed for 90 s and centrifuged at 13000 rpm for 15 minutes at 4℃, the supernatant was pipetted into vials for analysis. To validate the experimental accuracy and stability, 20 μl cell sample from each group was transferred into a vial and mixed to be the quality control (QC) sample.

Western Blot Analysis After 48 hours of cell culture, the cells from different groups were lysed in cell lysis buffer and the protein concentrations were quantified with the BCA assay kit. The collected samples were heated and separated by different consistencies of sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS – PAGE), followed by transferring to PVDF membranes. The membranes were incubated with designated primary antibodies against E-Cadherin, p-/ERK1/2, p-/STAT3, p-/AKT, CD13, GPX4, RRM2B, OPLAH, GAPDH and β-actin at 4 °C overnight after blocked with 5% nonfat milk. GAPDH and β-actin were selected as the housekeeping genes. All these antibodies were purchased from CST (Cell Signaling Technology, Inc., USA). At last, the membranes underwent second incubation with suitable secondary antibodies at room temperature. Chemiluminescence signals were observed and analyzed by using an enhanced chemiluminescence system (Fusion FX7 Spectra; Vilber Lourmat, Eberhardzell, Germany). Targets Inhibition And Genes Silence

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A549/DDP cells were harvested and seeded into 96-well plates at 3500 cells/well. After 24 hours, cisplatin (0 - 100 uM) in DMEM medium supplemented with GPX4 inhibitor RSL (10 nM) or CD13 inhibitor bestatin (125 μM) were added to the plates and examined by CCK8. The siRNA （20 nM ）was transfected to A549/DDP cells to induce the OPLAH and RRM2B gene silence by using Lipofectamine 3000 reagent. Independent siOPLAH

(siOPLAH

#1,

GCCGTCTTTCTGTCCTTCA,

ACCAGAAACCTGCACGACA) CCTATGATAATACCATTAA,

and siRRM2B

siRRM2B #2

siOPLAH (siRRM2B

#2 #1

CGGTTTGTCATCTTTCCAA)

candidates were purchased from GenePharma (China). The transfection efficiency was detected by western blot. CCK8 assay was designed to detect the effect of cisplatin on cell viability under the siRNA transfecting according to the manufacturer's protocol. Statistical Analysis The western blot data was performed using prism 6 software, and represented as mean ± SD, a P-value of 0.05 or less was considered as statistical significance. The principal component analysis (PCA) and partial least-squares discrimination analysis (PLS-DA) were used to analyze the UPLC-Q-TOF/MS data by using SIMCA-P software (13.0). Those metabolites satisfied with variable influence in the projection (VIP)>1, |Pcorr|>0.52 and p

Integration of metabolomics and transcriptomics to reveal metabolic

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