elevated glutathione peroxidase 2 expression promotes cisplatin...

Research ArticleElevated Glutathione Peroxidase 2 Expression Promotes CisplatinResistance in Lung Adenocarcinoma

He Du,1 Bi Chen,2 Nan-Lin Jiao,3 Yan-Hua Liu,4 San-Yuan Sun ,4 and You-Wei Zhang 4

1Department of Medical Oncology, Affiliated Shanghai Pulmonary Hospital, Tongji University, Shanghai 200433, China2Department of Respiratory Medicine, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China3Department of Pathology, Affiliated Yijishan Hospital, Wannan Medical College, Wuhu 241001, China4Department of Medical Oncology, Xuzhou Central Hospital, Clinical School of Xuzhou Medical University, Xuzhou 221009, China

Correspondence should be addressed to San-Yuan Sun; [email protected] and You-Wei Zhang; [email protected]

He Du and Bi Chen contributed equally to this work.

Received 15 September 2019; Revised 16 December 2019; Accepted 9 January 2020; Published 6 March 2020

Academic Editor: Fabio Altieri

Copyright © 2020 He Du et al. This is an open access article distributed under the Creative Commons Attribution License, whichpermits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The aim of this study was to explore the roles of GPX2, a member of the glutathione peroxidase family (GPXs, GSH-Px), in cisplatin(DDP) resistance in lung adenocarcinoma (LUAD). GPX2 was found to be the most significantly upregulated gene in a DDP-resistant A549/DDP cell line compared with the parental A549 cell line by RNA sequencing. The knockdown of GPX2expression in A549/DDP cells inhibited cell proliferation in vitro and in vivo, decreased the IC50 values of DDP, inducedapoptosis, inhibited the activities of GSH-Px and superoxide dismutase (SOD), inhibited ATP production and glucose uptake,and increased malondialdehyde (MDA) and reactive oxygen species (ROS) production; while GPX2 overexpression in A549cells resulted in the opposite effects. Using gene set enrichment analysis (GSEA), we found that GPX2 may be involved in DDPresistance through mediating drug metabolism, the cell cycle, DNA repair and energy metabolism, and the regulation of anATP-binding cassette (ABC) transporters member ABCB6, which is one of the hallmark genes in glycolysis. Moreover,immunohistochemistry revealed that GPX2 was upregulated in 58.6% (89/152) of LUAD cases, and elevated GPX2 expressionwas correlated with high expression of ABCB6, high 18-fluorodeoxyglucose (18F-FDG) uptake, and adverse disease-free survival(DFS) in our cohort. The Cancer Genome Atlas (TCGA) data also indicated that GPX2 expression was higher in LUAD than itwas in normal lung tissues, and the mRNA expression levels of GPX2 and ABCB6 were positively correlated. In conclusion, ourstudy demonstrates that GPX2 acts as oncogene in LUAD and promotes DDP resistance by regulating oxidative stress andenergy metabolism.

1. Introduction

Lung cancer is the leading cause of cancer-related deathworldwide in bothmen and women. Non-small cell lung can-cer (NSCLC), which includes lung adenocarcinoma (LUAD)and squamous cell carcinoma, accounts for approximately85% of overall lung cancer incidence [1]. Cisplatin (DDP) isa first-line chemotherapeutic DNA damage-inducing drugfor lung cancer treatment. Currently, it is widely in use,despite new drugs being developed [2, 3]. However, resis-tance to DDP has become a key obstacle in the effective treat-

ment of patients with cancer [4]. Therefore, an improvedunderstanding of the molecular mechanism of DDP resis-tance is required for the treatment of lung cancer.

For decades, glutathione peroxidases (GPXs, GSH-Px)have been known to catalyze the reduction of H2O2 andreduce lipid hydroperoxides to their corresponding alcoholsby using glutathione (GSH) as a reductant [5]. The familyof GPXs comprises eight members (GPX1–8) in mammals,five of which are selenoproteins in humans (GPX1–4 and 6);thus, their expression depends on the supply of selenium (Se)[6]. Most Se-dependent GPXs are downregulated in tumor

HindawiOxidative Medicine and Cellular LongevityVolume 2020, Article ID 7370157, 14 pageshttps://doi.org/10.1155/2020/7370157

https://orcid.org/0000-0002-7477-7491

https://orcid.org/0000-0001-9374-329X

https://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1155/2020/7370157

cells, while only GPX2 is considerably upregulated in amajor-ity of solid tumors including LUAD in smokers [6, 7].Knockdown of GPX2 contributes to increase reactive oxy-gen species- (ROS-) dependent caspase activation in LUADcells [8]. Huang et al. [9] also found YAP suppresses lungsquamous cell carcinoma progression via downregulationof GPX2 and ROS accumulation. In our previous works,GPX2 was screened to be the most significantly upregulatedgene in a DDP-resistant A549/DDP cell line compared withthe parental A549 cell line by RNA sequencing (data notshown) [10], but its specific functions and potential mech-anisms are not yet clear. Thus, in the present study, weaimed to further explore the roles of GPX2 in DDP resis-tance in LUAD.

2. Materials and Methods

2.1. Patients. This study enrolled 152 primary LUAD patientswith a median age of 60 (range, 35–80) years at our institutesfrom 2010 to 2013, including 85 males and 67 females. Post-operative paraffin-embedded tumor tissues and correspond-ing normal tissues (>3 cm from tumor) from patients wereused. Patients underwent an operation and receivedplatinum-based doublets adjuvant chemotherapy after sur-gery. None of them received preoperative treatment, such aschemotherapy and radiation therapy. Tumor stage wasassessedbasedonthe2017 tumornodemetastasis (TNM)clas-sificationofmalignant tumorsby theAmerican JointCommit-tee on Cancer (AJCC). Cellular differentiation was graded inaccordancewith theWHOgrading system.Therewas anover-all survival (OS) data for all patients, and 125 of them haddisease-free survival (DFS) data. Preoperative positron emis-sion computed tomography (PET/CT) scans were performedon 55 patients. The study was carried out according to theapproved ethical standards of the ethics committee in our hos-pitals, and all the participants signed informed consent.

2.2. Cell Lines and Cell Culture. The human LUAD cell lineA549 was purchased from Shanghai Institutes for BiologicalSciences, Chinese Academy of Cell Resource Center. Cellswere cultured at 37°C with 5% CO2 in RPMI 1640 medium(HyClone, Logan, UT, USA) with 10% fetal bovine serum(FBS) and 1% penicillin/streptomycin. The constructionand culture of a DDP-resistant A549/DDP cell line, primaryLUAD cells’ isolation, and culture and identification of DDPsensitivity have been described in our previous study [11].

2.3. RNA Sequencing. RNA isolation, cDNA library con-struction, and RNA sequencing were performed by GenergyBio Company (Shanghai, China). Briefly, total RNA wasextracted from A549 and A549/DDP cells using TRIzolreagent (Thermo Fisher Scientific, Waltham, MA), and thequality of extracted RNA was assessed by a Bioanalyzer(Agilent, Waldbronn, Germany). Total RNA samples weretreated with DNase I to remove potential genomic DNA,and the polyadenylated fraction of RNA was isolated forRNA-Seq library preparation. A TruSeq Stranded mRNAsample prep kit (Illumina, San Diego, California, USA) wasused to construct the stranded libraries by following the

manufacturer’s instructions. All libraries were sequencedon an Illumina HiSeq 2500 sequencer (Novogene Bioinfor-matics Technology Co., Ltd., Beijing, China). Genes thatwere differentially expressed between A549 and A549/DDPcells were identified by DESeq2 R package. According tothe results of DESeq2 analysis, genes were classified as differ-entially expressed when fold changes were more than twoand the statistically calculated p value was less than 0.05.Three replicates were tested for each cell line.

2.4. Real-Time Quantitative PCR (qPCR). Total RNA wasextracted using TRIzol reagent (Thermo Fisher Scientific).Reverse transcription reaction was performed using 2μg oftotal RNA with a PrimeScript™ RT reagent kit (catalogueno. RR037A, Takara Biotechnology, Dalian, China). Geneexpression levels were measured using TB Green Premix ExTaq™ II kit (catalogue no. RR820A, TaKaRa) and an ABI7300 thermocycler (Applied Biosystems, Foster City, CA) atthe following conditions: 1 cycle at 95°C for 20min and 40cycles at 95°C for 5 s and 60°C for 30 s; 10 ng of sample cDNAand HPLC-grade water (add 20μl) were used. Glyceralde-hyde dehydrogenase (GAPDH) and β-actin (ACTB) wereused as reference genes. The specific primer sequences areas follows: GPX2-forward, 5′-GGTAGATTTCAATACGTTCCGGG-3′; GPX2-reverse, 5′-TGACAGTTCTCCTGATGTCCAAA-3′; GAPDH-forward, 5′-GGAGCGAGATCCCTCCAAAAT-3′; GAPDH-reverse, 5′-GGCTGTTGTCATACTTCTCATGG-3′; ACTB-forward, 5′-CATGTACGTTGCTATCCAGGC-3′; and ACTB-reverse, 5′-CTCCTTAATGTCACGCACGAT-3′. Data analysis was performedusing the 2−ΔΔCt method to determine relative expressionlevels of GPX2 [12].

2.5. Lentivirus Infection. Oligonucleotides encoding shorthairpin RNA (shRNA) targeting human GPX2 (point 510-531 shRNA-1, 5′-GCACAGAAAGCACTCATTAAA-3′;point 1035-1056 shRNA-2, 5′-GCGAACCCTCTCGTTATAATC-3′) were cloned into a pLKO.1 lentiviral vector(Addgene, Cambridge, MA, USA). The cDNA encodingGPX2 was obtained by reverse transcription PCR (primerforward (EcoRI): CGGAATTCATGGCTTTCATTGCCAAGTCC; reverse (BamHI): CGGGATCCGATGGCTAAAGATTGTGAG) and then were cloned into a pLVX-Purolentivirus vector (Clontech, Mountain View, CA, USA)for constructing pLVX-Puro-GPX2 expressing vector. ApLKO.1-scramble shRNA (shNC) and blank pLVX-Puro(vector) were used as negative control. Virus packaging wasperformed in HEK 293T cells after cotransfection of thelentiviral vectors constructed above with packaging plasmidpsPAX2 (Addgene) and envelope plasmid pMD2.G(Addgene) using Lipofectamine™ 2000 reagent (Invitrogen,Grand Island, NY, USA). Viruses were harvested 72h aftertransfection, and viral titers were determined. A549 cells orA549/DDP cells (1 × 105) were infected with 1 × 106 recombi-nant lentivirus-transducing units in the presence of 6μg/mLpolybrene (Sigma, Shanghai,China).Virus-containingculturemedium was replaced with fresh RPMI-1640 medium at 12 h

2 Oxidative Medicine and Cellular Longevity

postinfection, then cells were selected using 0.5mg/mL puro-mycin (Sigma) at 48 h postinfection.

2.6. Western Blotting. Proteins were extracted with a Nuclearand Cytoplasmic Protein Extraction kit (catalogue no. P0028,Beyotime, Shanghai, China). Cell protein lysates wereseparated by 10% sodium salt (SDS)-polyacrylamide gel elec-trophoresis (PAGE) and then electroblotted from the gelsonto polyvinylidene fluoride (PVDF) membranes (RocheDiagnostics, Mannheim, Germany). After blocking the mem-brane with 5% nonfatmilk powder and 0.1%Tween 20 in PBSfor 1 h, the membrane was incubated with primary antibodiesspecific to GPX2 (catalogue no. ab140130), p21 (ab218311),Cyclin D1 (ab134175), Bcl-2 (ab185002), Bax (ab32503),cleaved caspase 3 (ab32042), and GAPDH (ab181602); all ofwhich were acquired from Abcam (Cambridge, UK; the dilu-tion for allwas 1 : 1000).After extensivewashingwith blockingsolution, blots were exposed to horseradish peroxidase-conjugated goat anti-rabbit IgG (catalogue no. ZB-2301,Zsbio, Beijing, China; 1 : 2500 dilution). Finally, the proteinbands were imaged using an enhanced chemiluminescent(ECL) substrate (Merck Millipore, Hong Kong, China).

2.7. Gene Set Enrichment Analysis (GSEA). GSEA wasperformed by using a JAVA program (http://software.broadinstitute.org/gsea/index.jsp) with MSigDB C2 CP:canonical pathways gene set collection. Firstly, based on theircorrelation with GPX2 expression, GSEA generated anordered list of all genes and then a predefined gene set (sig-nature of gene expression upon perturbation of certaincancer-related gene) received an enrichment score (ES),which is a measure of statistical evidence rejecting the nullhypothesis that the members of the list are randomly dis-tributed in the ordered list. Parameters used for the analysiswere as follows: “c2.all.v5.0.symbols. gmt” gene sets to runGSEA, 1000 permutations to calculate p value, and the per-mutation type was set to gene set. The maximum gene setsize was fixed at 1500 genes, while the minimum size fixedat 15 genes. GPX2 expression level was used as phenotypelabel, and “Metric for ranking genes” was set to Pearsoncorrelation. All other basic and advanced fields were setto default.

2.8. Cell Viability and Proliferation Analysis. Cell countingkit-8 (CCK-8) assays were used to assess cell viability. Inshort, cells were seeded into 96-well plates for 0-48 h at aninitial density of 2 × 103 cells/well. Next, 90μl of freshserum-free medium and 10μl of CCK-8 reagent (catalogueno. C0037; Beyotime) were added to each well after decant-ing the old medium; then, the plates were incubated at 37°Cfor 1 h. The optical density (OD value) was measured at awavelength of 450nm by scanning with a microplate reader(Promega, Beijing, China). Using GraphPad Prism 5.0(GraphPad Software, La Jolla, CA, USA), IC50 values werecalculated by a DDP concentration-response curve (concen-tration gradients 0, 2, 5, 10, 20, and 40μg/mL for a 48 htreatment period).

2.9. Flow Cytometry for Measuring Apoptosis. Cells were har-vested directly or 48 h after transfection and then were

washed with ice-cold phosphate-buffered saline (PBS).Annexin V-fluorescein isothiocyanate (FITC) apoptosisdetection kits (catalogue no. KGA108-1; Keygene Biotech,Nanjing, China) were used to detect apoptosis in a FACScaninstrument (Becton Dickinson, Mountain View, CA).

2.10. Oxidative Stress and Metabolite Analysis. Cells wereseeded into six-well plates (2 × 105 cells/well). After 24 h ofincubation, the cells were stained with 10μM 2,7-dichloro-fluoresceindiacetate (DCFH-DA; catalogue no. C10443;Thermo Fisher Scientific) at 37°C for 30min for ROS detec-tion; then, cells were washed with medium, and the fluores-cence was detected and analyzed by flow cytometry.Additionally, cells were pelleted and lysed in 0.5mL of celllysis solution (Beyotime) to evaluate oxidative stress accord-ing to the manufacturer’s protocol of GSH-Px (colorimetricmethod, catalogue no. A001-1-2), superoxide dismutase(SOD; WST-1 method, catalogue no. A001-3-2), and malon-dialdehyde (MDA; TBA method, catalogue no. A003-1-1)assay kits (Jiancheng Bioengineering Ltd., Nanjing, China);then, measurements were performed with a microplatereader (wavelengths of 412nm, 532nm, and 450nm, respec-tively). Cellular adenosine three phosphate (ATP) produc-tion was measured with an ATP assay kit (colorimetricmethod, catalogue no. A095-1-1; Jiancheng Bioengineering),and results were read by a UV-visible spectrophotometer(wavelength of 636nm). Protein content was measuredaccording to the Bradford method. Glucose uptake wasdetected with a 2-NBDG Glucose Uptake Assay kit (Cell-Based, catalogue no. K682-50; Biovision Technologies,Exton, PA) according to the manufacturer’s protocol; thefluorescence intensity of 2-NBDG in the cells was recordedusing a FACScan instrument (Becton Dickinson).

2.11. In Vivo Xenograft Model. Six-week-old male BALB/cnude mice were purchased from the Laboratory AnimalCenter of Nanjing Medical University and were main-tained under pathogen-free conditions. Tumor xenograftswere established by a subcutaneous injection of 0.1mL ofcell suspensions (2 × 106 cells/mL) into nude mice on theright side of the posterior flank (n = 6 mice per group).Tumor growth was examined every three days. After 5~7days, the tumor volume grew to ≈100mm3,and the mice were intraperitoneally injected with a sus-pension of PBS containing DDP (2.5mg/kg) twice perweek. All mice were sacrificed after 4 weeks. Tumor tissueswere excised, paraffin-embedded, and formalin-fixed; then,they were used to perform H&E staining and to detectGPX2 expression. The entire experimental protocol wasconducted based on the guidelines of the local institutionalanimal care and use committee.

2.12. Immunohistochemistry (IHC). Formalin-fixed, paraffin-embedded tissues were cut to generate consecutive 4μmsections, which were then subjected to IHC analysis. Thesections were incubated with antibodies against GPX2(catalogue no. ab140130, Abcam; 1 : 200 dilution) andATP binding cassette subfamily B member 6 (ABCB6)(b224575, Abcam; 1 : 200 dilution) at 4°C overnight. After

3Oxidative Medicine and Cellular Longevity

http://software.broadinstitute.org/gsea/index.jsp

http://software.broadinstitute.org/gsea/index.jsp

washing in PBS, sections were further incubated with a HRP-conjugated secondary antibody (catalogue no. ZB-2301,Zsbio; 1 : 500 dilution) for 30min at 37°C. Then, the tumortissues were incubated with a substrate-chromogen (DAB)solution for 10min. Finally, automated hematoxylin was

used to counterstain the slides for 5min. The immunostain-ing was microscopically evaluated by two independentpathologists. A semiquantitative scoring system was usedthat is based on the staining intensity and the proportion ofpositive cells [13].

Rela

tive m

RNA

expr

essio

n

A549 A549/DDP

50

60

40

30

20

10

0

⁎⁎

(a)

Rela

tive m

RNA

expr

essio

n

Sensitive Resistant

15

10

5

0

⁎

(b)

Gpx2

GAPDH

A549NC Vector Gpx2 NC ShGpx2-2ShGpx2-1ShNC

A549/DDP

(c)

A549

Gpx2Vector ShGpx2-1 ShGpx2-2ShNC

A549/DDP

P21

Cyclin D1

Bcl-2

Cleaved-caspase3

Bax

GAPDH

(d)

Figure 1: GPX2 expression of in cisplatin- (DDP-) resistant lung adenocarcinoma cell lines and tissues. The expression status of GPX2 inA549/DDP cells and the parental A549 cells was verified at the mRNA (a) and protein (c) levels. (b) GPX2 expression was analyzed inprimary tumor cells; 20 LUAD samples were considered to be DDP-sensitive (IC50 < 5mg/L), and 20 samples were considered to be DDP-resistant (IC50 > 10mg/L). (c) Lentiviral vector-meditated shRNAs were used to knock down GPX2 expression in A549/DDP cells, and aGPX2 overexpressed vector was transfected into A549 cells. (d) Western blot analysis of the expression levels of cell cycle and apoptosis-related proteins. ∗p < 0:05 and ∗∗p < 0:001.


OD

val

ue

A549

Times (h)

Gpx2⁎

0 12 24 480.0

0.5

1.0

1.5

2.0

2.5

Vector

⁎

⁎

Times (h)

OD

val

ue

A549/DDP

ShNcShGpx2-1ShGpx2-2

⁎⁎

0 12 24 480.0

0.5

1.0

1.5

⁎

(a)

Log DDP (𝜇g/mL)

Cell

surv

ival

A549

Vector (IC50 = 6.177)GPX2 (IC50 = 22.15)⁎

0.0 0.5 1.0 1.5 2.00

20

40

60

80

100A549/DDP

Cell

surv

ival

ShNc (IC50 = 28.44) ShGpx2-1 (IC50 = 5.751)ShGpx2-2 (IC50 = 5.811)

Log DDP (𝜇g/mL)0.0 0.5 1.0 1.5 2.0

0

50

100

150

⁎

(b)

A549

Vector GPX2

104.9

104

103

102

101

102.1

Q1-LL96.6%

Q1-LR3.1%

Q1-UR0.1%

Q1-UL0.2%

Gate: P1

FL1-A

FL2-

A

103 104 105 106 106.8

104.9

104

103

102

101

102.1

Q1-LL71.6%

Q1-LR19.9%

Q1-UR7.6%

Q1-UL0.9%

Gate: P1

FL1-A

FL2-

A

103 104 105 106 106.8

104.9

104

103

102

101

102.1

Q1-LL90.2%

Q1-LR5.6%

Q1-UR3.7%

Q1-UL0.5%

Gate: P1

FL1-A

FL2-

A

103 104 105 106 106.8

104.9

104

103

102

101

102.1

Q1-LL98.3%

Q1-LR1.6%

Q1-UR0.1%

Q1-UL0.1%

Gate: P1

FL1-A

FL2-

A

103 104 105 106 106.8

DD

P0 𝜇

M10

𝜇M

A549/DDP

ShNc ShGPX2

104.9

104

103

102

101.5

101.7

Q1-LL98.2%

Q1-LR1.7%

Q1-UR0.0%

Q1-UL0.1%

Gate: P1

FL1-A

FL2-

A

103 104 105 106.4

104.9

104

103

102

101.5

101.7

Q1-LL97.7%

Q1-LR2.1%

Q1-UR0.1%

Q1-UL0.2%

Gate: P1

FL1-A

FL2-

A

103 104 105 106.4

104.9

104

103

102

101.5

101.7

Q1-LL75.7%

Q1-LR16.4%

Q1-UR7.1%

Q1-UL0.8%

Gate: P1

FL1-A

FL2-

A

103 104 105 106.4

104.9

104

103

102

101.5

101.7

Q1-LL60.3%

Q1-LR25.2%

Q1-UR11.7%

Q1-UL2.8%

Gate: P1

FL1-A

FL2-

A

103 104 105 106.4

(c)

Figure 2: Continued.


2.13. Statistical Analysis. The SPSS 16.0 software system(SPSS, Chicago, IL) was used for statistical analysis. p < 0:05was considered to indicate a statistically significant differ-ence. The data are expressed as the mean ± standard error.Differences between the 2 groups were analyzed using Stu-dent’s t test. Differences in frequency were examined by χ2

test. Overall survival (OS) and disease-free survival (DFS)were calculated using the Kaplan–Meier method and werecompared by log-rank testing. GPX2 expression was also ver-ified using the Gene Expression Profiling Interactive Analysis(GEPIA) online tool (http://gepia2.cancer-pku.cn/).

3. Results

3.1. The Expression Status of GPX2 in DDP-Resistant LUADCells and Tissues.We first analyzed transcriptome differencesbetween A549/DDP cells and the parental A549 cells by RNAsequencing. Integrated analysis with the Gene ExpressionOmnibus (GEO) data (E-GEOD-43493 and E-GEOD-43494) revealed that GPX2 was the most significantlyupregulated member in A549/DDP cells (SupplementaryTable S1). The expression status of GPX2 in A549 andA549/DDP cells was then verified, both at the mRNA andprotein levels (Figures 1(a) and 1(c)). Using primary tumor cellculture and drug susceptibility testing, 20 LUAD samples wereidentified to be DDP-sensitive (IC50 < 5μg/mL), and 20samples were identified to be DDP-resistant (IC50 > 10μg/mL).qPCR results showed that the expression level of GPX2 wasalso upregulated in DDP-resistant tissues (Figure 1(b)).

3.2. In Vitro Effects of GPX2 Expression on DDP Resistance.To study the role of GPX2 in the regulation of DDP resis-tance, we used specific shRNAs to knock down GPX2 expres-sion in A549/DDP cells, and a GPX2 overexpression vectorwas transfected into A549 cells (Figure 1(c)). GPX2 overex-pression in A549 cells induced an increase of Cyclin D1and Bcl-2 expression, and it induced an inhibition of p21,Bax, and cleaved caspase 3 expression; while GPX2 knock-down in A549/DDP cells caused the opposite effects(Figure 1(d)). Furthermore, GPX2 overexpression in A549cells promoted cell proliferation (Figure 2(a)) and increased

the IC50 values of DDP from 6.177μg/mL to 22.15μg/mL(Figure 2(b)); further, it inhibited apoptosis of A549 cellswhen they were treated with 10μM (3μg/mL) DDP(Figures 2(c) and 2(d)). However, GPX2 knockdown inA549/DDP cells inhibited cell proliferation (Figure 2(a)),decreased the IC50 values of DDP from 28.44μg/mL to5.751μg/mL (shGPX2-1) or 5.811μg/mL (shGPX2-2)(Figure 2(b)), and induced apoptosis with or without DDPtreatment (Figures 2(c) and 2(d)). It is worth noting thatlow-dose DDP (10μM) did not induce apoptosis inA549/DDP cells, but GPX2 knockdown in A549/DDP cellssignificantly increased cytotoxicity of DDP (increased apo-ptotic rate) (Figures 2(c) and 2(d)).

3.3. GPX2 Affects DDP Cytotoxicity In Vivo. Nude mice wereseparated into 4 groups (6 per group) according to whichcells they were inoculated with (mock or GPX2 overex-pressed A549 cells and mock or GPX2 knockdownA549/DDP cells). All the xenograft models were treated withDDP (2.5mg/kg). Tumor volumes were significantly reducedin mice bearing A549/DDP cells with GPX2 knockdown ascompared with mice bearing mock cells; while tumor vol-umes were increased obviously in mice bearing GPX2 over-expressing A549 cells in comparison with mice bearingmock cells (Figures 3(a) and 3(b)). GPX2 protein expressionin the xenograft was verified by IHC (Figure 3(c)). Theseresults indicate that knockdown of GPX2 enhances DDPcytotoxicity and overexpression of GPX2 promotes DDPresistance in vivo.

3.4. Potential Mechanisms of GPX2 that Promote DDPResistance. GSEA was performed to explore potential mech-anisms by which GPX2 promotes DDP resistance. We foundthat high expression of GPX2 was positively correlated withan oxidative phosphorylation gene set (ES = 0:6776158, p = 0,FDR = 0), a drug metabolism cytochrome gene set(ES = 0:6787219, p = 0, FDR = 0), a reactome regulation ofmitotic cell cycle gene set (ES = 0:62144023, p = 0, FDR = 0), ahallmark glycolysis gene set (ES = 0:47295266, p = 0, FDR = 0),a glycolysis and gluconeogenesis gene set (ES = 0:52196103,p = 0, FDR = 0), and a hallmark DNA repair gene set

A549A

popt

osis

rate

0Vector

0Gpx2

10Vector

10Gpx2

0

5

10

15

20

25

30

DDP(𝜇M)

⁎⁎

Apo

ptos

is ra

te

A549/DDP

05

10152025303540

0ShNC

0ShGpx2

10ShNC

10ShGpx2

DDP(𝜇M)

△

#

⁎

⁎⁎

(d)

Figure 2: In vitro effects of GPX2 expression in DDP resistance. Using a CCK-8 assay, (a) cell proliferation and (b) the IC50 values of DDPwere analyzed; ∗p < 0:05 vs. control. (c, d) Cell apoptosis was evaluated by flow cytometry, before and after 10μMDDP treatment; ∗p < 0:05vs. control (without DDP), ∗∗p < 0:05 vs. control (with DDP), △p > 0:05 vs. SiNC (without DDP), and #p < 0:05.


http://gepia2.cancer-pku.cn/

(ES = 0:4268115, p = 0, FDR = 0) (Figure 4). These events areall closely related to cisplatin resistance.

Moreover, overexpression of GPX2 in A549 cells signifi-cantly increased the activity of GSH-Px and SOD, increasedATP production and glucose uptake, and decreased MDAproduction, regardless of DDP treatment (Figure 5(a)) butonly decreased ROS production with DDP treatment(Figure 5(b)). Knockdown of GPX2 in A549/DDP cells sig-nificantly inhibited the activity of GSH-Px and SOD, inhib-ited ATP production and glucose uptake, and increasedMDA and ROS production, regardless of DDP treatment(Figure 5). It is worth noting that low-dose DDP (10μM)did not induced the above changes in A549/DDP cells,but GPX2 knockdown in A549/DDP cells significantlyinduced these changes, indicating increased cytotoxicityof DDP (Figure 5).

3.5. Elevated GPX2 Expression Predicts Poor Prognosis. Tobetter understand the association between GPX2 expressionand DDP resistance, GPX2 expression was assessed in 152LUAD patients treated with platinum-based adjuvant che-motherapy. As ATP-binding cassette (ABC) transportermember ABCB6 is listed at the top of the hallmark glycol-ysis gene set (Supplementary Table S2), we detected ABCB6protein expression in cancerous tissues and correspondingadjacent tissues. GPX2 expression was upregulated (highexpression, score ≥ 3) in 89 LUAD cases (58.6%), and it wascorrelated with high expression of ABCB6 (Pearson r = 0:697),as showed in analysis of serial sections (Figures 6(a) and 6(d)).In 55 patients who received a preoperative PET/CT scan,elevated GPX2 protein was more frequent in the high 18-fluorodeoxyglucose (18F-FDG) uptake patients than that withthe low FDG uptake (Figures 6(a) and 6(c)). We further

A54

9A

549/

DD

P

VectorGpx2

ShNC

ShGpx2

(a)

Tum

or v

olum

e (m

m3 )

A549/DDP

A549

⁎

⁎

12 15 18 21 24 27 300

500

1000

1500

2000

2500

ShNCShGPX2GPX2Vector

Days

(b)

GPX

2H

E

A549 A549/DDP Vector Gpx2 ShNC ShGpx2

(c)

Figure 3: In vivo effects of GPX2 expression in DDP resistance. Cells (2 × 106 cells/100 μL PBS) were subcutaneously inoculated into the rightflank of BALB/c nu/nu mice, and the animals were randomly separated into 4 groups (6 per group) according to which cells they wereinoculated with. The mice were intraperitoneally injected with a suspension of PBS containing DDP (2.5mg/kg) twice per week, after thetumor volume grew to ≈100mm3. (a) The mice were sacrificed, and the tumors were isolated after 4 weeks. (b) The tumor size wasmonitored every 3 days after cells implantation. (c) Hematoxylin-eosin (HE) staining was performed, and GPX2 protein was detected byimmunohistochemistry (magnification ×200). ∗p < 0:05.


analyzed the mRNA expression of GPX2 in The CancerGenome Atlas (TCGA) data using the GEPIA online tool. Theresult indicated that GPX2 expression was significantly higherin LUAD (n = 483) than that in normal lung tissues (n = 347),and mRNA expression levels of GPX2 and ABCB6 werepositively correlated (Pearson r = 0:58) (Figure 6(b)).

GPX2 protein expression was not associated withpatients’ clinicopathological features in our cohort, includ-ing gender, age, size, cellular differentiation, lymph metasta-sis, and clinical stage (Table 1). By the end of follow-up, atotal of 88 patients had died within 6 years after surgery.Univariate survival analysis showed that patients with highexpression of GPX2 prefer to have inferior OS to that withlow expression [56.94 months (95% CI 41.50–51.77) vs.66.32 months (95% CI 57.857–74.778), p = 0:157](Figure 6(e)). Within 125 patients for whom DFS data wasavailable, high expression of GPX2 was associated withshorter DFS than low expression was [34.75 months (95%CI 29.746–39.747) vs. 48.91 months (95% CI 41.033–56.779), p = 0:009] (Figure 6(e)). Survival analysis fromTCGA database also verified that the increased GPX2 mRNAlevels in LUAD tend to be associated with shorter OS ½hazard ratio ðHRÞ = 1:3, p = 0:062� (Figure 6(f)). These datasuggest that GPX2 may affect prognosis and platinum resis-tance in LUAD.

4. Discussion

Overexpression of the GPX2 gene is observed in many can-cers, such as breast [14], liver [15], gastric [16], colorectal[17], nasopharyngeal [18], and esophageal squamous cellcarcinoma [19], as well as in premalignant lesions like Bar-rett’s esophagus [20]. GPX2 expression has been implicatedin tumor initiation, growth, development, and metastasis,and it is strongly correlated with low OS rates [13], whichsuggested that GPX2 acts as a bona fide oncogene. GPX2has been proposed to reduce oxidative DNA damage byreducing hydroperoxides and redox-sensitive pathways, thusfacilitating tumor growth [21, 22]. To date, no research hasbeen reported regarding the clinical significance of GPX2 inDDP resistance. In the present study, we first found GPX2was upregulated in the DDP-resistant LUAD cells and tissues,and elevated GPX2 expression was associated with adverseDFS for LUAD patients treated with platinum-based adjuvantchemotherapy. Functional experiments in vitro and in vivofurther confirmed that GPX2 promotes LUAD developmentand DDP resistance via promoting proliferation, antiapopto-sis, and mediating oxidative stress.

The antitumor activity of cisplatin occurs due to free rad-ical formation causing DNA cross-linking and apoptosis. Wehave found GPX2 can protect against oxidative damage,

ES = 0.6776156

NES = 2.7782354

Nominal p = 0.0

FDR q-value = 0

‘GPX2_pos’ (positively correlated)

‘GPX2_neg’ (negatively correlated)

Zero cross at 15676

0.7

0.6

0.5

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot:KEGG_OXIDATIVE_PHOSPHORYLATION

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.500.250.00

-0.25-0.50

0 5.000 10.000 15.000Rank in ordered dataset

20.000 25.000 30.000

Enrichment profile Hits Ranking metric scores

ES = 0.6787219

NES = 2.5764775

Nominal p = 0.0



Zero cross at 15676

0.7

0.6

0.5

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot:KEGG_DRUG_METABOLISM_CYTOCHROME_P450

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.500.250.00

-0.25-0.50

0 5.000 10.000 15.000 20.000 25.000 30.000

FDR q-value = 0

Rank in ordered dataset


ES = 0.62144023

NES = 2.3595057

Nominal p = 0.0

FDR q-value = 0



Zero cross at 15676

0.6

0.5

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot:REACTOME_REGULATION_OF_MITOTIC_CELL_CYCLE

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.500.250.00

-0.25-0.50


20.000 25.000 30.000


ES = 0.47295266

NES = 2.0982416

Nominal p = 0.0

FDR q-value = 0.0



Zero cross at 15676

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot:Enrichment plot: HALLMARK_GLYCOLYSIS

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.50

0.250.00

-0.25-0.50


20.000 25.000 30.000


ES = 0.52196104

NES = 1.925841

Nominal p = 0.0

FDR q-value = 3.2772918E-4



Zero cross at 15676

0.5

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot:KEGG_GLYCOLYSIS_GLUCONEOGENESIS

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.500.250.00

-0.25-0.50


20.000 25.000 30.000


ES = 0.4268115

NES = 1.8245285

Nominal p = 0.0

FDR q-value = 0.001975737



Zero cross at 15676

0.4

0.3

Enric

hmen

t sco

re (E

S)

Enrichment plot: HALLMARK_DNA_REPAIR

Rank

ed li

st m

etric

(Pea

rson

)

0.2

0.1

0.0

1.000.750.50

0.250.00

-0.25-0.50


20.000 25.000 30.000


Figure 4: Gene set enrichment analysis (GSEA). GSEA showed that high expression of GPX2 is positively correlated with an oxidativephosphorylation gene set, a drug metabolism cytochrome P450 gene set, a reactome regulation of mitotic cell cycle gene set, a hallmarkglycolysis gene set, a glycolysis and gluconeogenesis gene set, and a hallmark DNA repair gene set.


A549

4

3

2

0

1

MD

A (n

mol

/mg

prot

)

DDP(𝜇M) 0Vector

0Gpx2

10Vector

10Gpx2

⁎

⁎⁎⁎⁎

A549/DDP

MD

A (n

mol

/mg

prot

)

4

5

3

2

1

00

ShNC0

ShGpx210

ShNC10

ShGpx2

△

⁎⁎

⁎

#

Act

ivity

(U/m

g pr

ot)

706050

4030

2010

0

GSH-PxSOD

A549

0Vector

0Gpx2

10Vector

10Gpx2

⁎⁎

⁎⁎

⁎

⁎

Act

ivity

(U/m

g pr

ot)

60

50

40

30

20

10

0

A549/DDP

△ △

#

0ShNC

0ShGpx2

10ShNC

10ShGpx2

GSH-PxSOD

⁎⁎

⁎⁎

⁎⁎

1200

1000

800

600

400

200

0

ATP

(𝜇m

ol/g

prot

)

DDP(𝜇M) 0Vector

0Gpx2

10Vector

10Gpx2

⁎⁎

⁎ 600

500

400

300

200

100

0

ATP

(𝜇m

olgp

rot)

0ShNC

0ShGpx2

10ShNC

10ShGpx2

△

#

⁎⁎

⁎

10002000300040005000600070008000

0

2-N

BDG

fluo

resc

ence

0Vector

0Gpx2

10Vector

10Gpx2

⁎⁎

⁎

1000

2000

3000

4000

5000

6000

0

2-N

BDG

fluo

resc

ence △

0

#

ShNC0

ShGpx210

ShNC10

ShGpx2

⁎⁎

⁎

(a)

A549

Vector GPX2A549/DDP

shNC shGPX2

X-mean 6.41X-mean 5.78 X-mean 14.2X-mean 6.99

X-mean 18.6 X-mean 11.8 X-mean 7.91 X-mean 20.0

DD

P

Fluorescence value

Coun

ts

0 𝜇

M10

𝜇M

33

33

100

C

101

FL1 log FL1 log FL1 log FL1 log102 103 100 101 102 103 100 101 102 103 100 101 102 103

17

C

10

C

10

C

32

C

C

33

C

11

C

100 101

FL1 log FL1 log FL1 log FL1 log102 103 100 101 102 103 100 101 102 103 100 101 102 103

(b)

A549

0

5

10

15

20

25

Mea

nflu

ores

cenc

e val

ue

DDP(𝜇M) DDP(𝜇M)0Vector

0Gpx2

10Vector

10Gpx2

⁎⁎

A549/DDP

0

5

10

15

20

25

△

#

Mea

nflu

ores

cenc

e val

ue

0ShNC

0ShGpx2

10ShNC

10ShGpx2

⁎⁎

⁎

(c)

Figure 5: Oxidative stress and metabolite analysis. (a) Cellular malondialdehyde (MDA) production, activity of glutathione peroxidase(GSH-Px) and superoxide dismutase (SOD), adenosine three phosphate (ATP) production, and glucose uptake were analyzed in A549cells and A549/DDP cells with or without DDP treatment. (b, c) Reactive oxygen species (ROS) testing by flow cytometry in A549 cellsand A549/DDP cells with or without DDP treatment. ∗p < 0:05 vs. control (without DDP), ∗∗p < 0:05 vs. control (with DDP), △p > 0:05vs. ShNC (without DDP), and #p < 0:05.


GPX

2A

BCB6

PET/

CT

#1 #2

(a)

Expr

essio

n lo

g 2 (T

PM+1

)

0

2

4

6

8

10

12

LUAD (num(T)=483; num(N)=347)

⁎p value = 0

0 2 4 6 8 10

2

3

4

5

6

7

8

Log2(GPX2 TPM)

log 2

(ABC

B6 T

PM)

R = 0.58

(b)

GPX2 low GPX2 high(n = 26) (n = 29)

20 ⁎

15

10

5

0

FDG

SU

V m

ax

(c)

Figure 6: Continued.


GPX2 scoresA

BCB6

scor

es

p < 0.001Pearson r = 0.697

0 2 4 60

2

4

6

(d)

Logrank p = 0.157

Ove

rall

surv

ial

6389 80 52 36 28 1

59 42 32 23 4LowHigh

Number at risk

HR = 1.36(0.888-2.083)

0 20 40 60 80 1000.0

0.2

0.4

0.6

0.8

1.0

HighExpression Expression

Low

Time (Months) Time (Months)

Dise

ase f

ree s

urvi

val

HR = 1.707(1.145-2.544)Logrank p = 0.009

5471 53 21 10 2 0

44 28 17 7 0

0 20 40 60 80 1000.0

0.2

0.4

0.6

0.8

1.0

HighLow

(e)

Ove

rall

surv

ival

0 50 100 150 200 250

0.0

0.2

0.4

0.6

0.8

1.0

Months

Low GPX2 groupHigh GPX2 group

Logrank p = 0.062 HR(high) = 1.3p(HR) = 0.062n(high) = 239n(low) = 239

(f)

Figure 6: Elevated GPX2 expression predicts poor prognosis. (a) GPX2 and ABCB6 proteins expression by immunohistochemical staining(magnification ×200) in lung adenocarcinoma (LUAD) patients with high and low 18-fluorodeoxyglucose (18F-FDG) uptake. (b) Using theGEPIA online tool, the mRNA expression of GPX2 between LUAD (n = 483) and lung tissues (n = 347) and relationship between GPX2 andABCB6 mRNA expression in LUAD were analyzed. (c) High expression of GPX2 was correlated with high 18F-FDG uptake in LUADpatients. (d) Relationship between the IHC scores of GPX2 and ABCB6 in our cohort. (e) Univariate survival analysis of overall survival(OS) and disease-free survival (DFS) in our cohort with high expression of GPX2 protein compared with that of low expression. (f)Survival analysis of LUAD from The Cancer Genome Atlas (TCGA) database using the GEPIA tool.


which is consistent with previous studies on DDP resistance.We also found by GSEA that GPX2 may be involved in DDPresistance through regulating drug metabolism, cell cycle,DNA repair, and energy metabolism by GSEA. An abnormalmetabolic phenotype is a hallmark of cancer [23], but its rolesin chemoresistance are not yet fully defined. Cancer cells,unlike normal cells, mainly depend on glycolysis to produceenergy even in the presence of oxygen; this is referred to asthe Warburg effect or aerobic glycolysis [24]. The cancer cellbenefits from this strategy because glycolysis also providessubstrates for anabolic processes, which is believed to offera selective advantage for the proliferation and survival[25]. However, under some circumstances, cancer cells havethe ability to adapt their metabolism to different environ-ments and treatments, increasing adaptability and tumorresistance to therapies [26]. In this sense, an increase of mito-chondrial oxidative phosphorylation (OXPHOS), theessential cellular process that uses oxygen, and simplesugars to create ATP, has been described for some tumors[27, 28]. ROS, the byproducts of aerobic metabolism, playcritical roles in regulating the decision-making of both gly-colysis and OXPHOS [29]. When cells are exposed toenvironmental stress and damaging agents such as DDP,intracellular ROS production dramatically increases andtriggers the apoptotic machinery of cells [30]. To achieveoxidative stress balance, cells coordinate adaptiveresponses to regulate ROS production and antioxidant sys-tems including SOD and GPXs. In the present study,GPX2 expression was found to reduce ROS insult, increaseSOD/GPXs activity, increase ATP production, and increaseglucose uptake. These data imply that GPX2 may mediatemetabolic alterations of LUAD via ROS.

ABCB6 is considered to be one of the hallmark genes ofglycolysis, and we found that expression levels of GPX2 andABCB6 in LUAD were positively correlated both in our cohortand in TCGA data. We also found GPX2 protein upregulationwas more frequent in patients with high 18F-FDG uptake thanthat in low uptake patients, which further confirmed thatGPX2 was involved in energy metabolism in LUAD. The

human ABC superfamily of transporters facilitates transloca-tion of heterogeneous substrates including metabolic products,lipids and sterols, peptides and proteins, saccharides, aminoacids, inorganic and organic ions, metals, and drugs acrossthe cell membrane. To transport both cytotoxic agents and tar-geted anticancer drugs across extracellular and intracellularmembranes against a concentration gradient, ABCs use energyacquired by the hydrolysis of ATP and play important roles inmultidrug resistance [31]. Minami et al. [32] have foundexpression of ABCB6 is related to resistance to 5-FU, SN-38,and vincristine in an arsenite-resistant human epidermoid car-cinoma KB-3-1 cell line. In addition, ABCB6 has been associ-ated with a broad range of physiological functions, includingtumorigenesis and progression [33, 34] but has not been previ-ously studied in LUAD. In the present study, we verified thecorrelation of ABCB6 and GPX2 expression in LUAD, buttheir interaction in glucose metabolism needs further study.

5. Conclusions

Our study demonstrates that GPX2 acts as oncogene inLUAD and promotes DDP resistance via mediating oxidativestress and energy metabolism, thus providing new insightinto the mechanisms underlying GPXs and contributing todevelopments of LUAD treatments.

Data Availability

The testing methods and experimental data used to supportthe findings of this study are included within the article andthe supplementary information file.

Conflicts of Interest

The authors declare that there are no conflicts of interestregarding the publication of this paper.

Table 1: Association between GPX2 expression in LUAD tissues and clinicopathological features.

Characteristics No. High expression of GPX2 n (%) p value

GenderMale 85 52 (61.1)

0.460Female 67 37 (55.2)

Age<60 71 40 (56.3)

0.604≥60 81 49 (60.5)

Tumor size>3 cm 67 41 (61.2) 0.557

≤3 cm 85 48 (56.5)

DifferentiationWell/moderate 102 56 (54.9)

0.192Poor 50 33 (66.0)

Lymph metastasisNo 81 44 (54.3)

0.258Yes 71 45 (63.4)

StageI/II 68 36 (52.9)

0.206III/IV 84 53 (63.1)

∗p < 0:05.


Authors’ Contributions

He Du and Bi Chen contributed equally to this work.

Acknowledgments

This work was supported by grants from the National Natu-ral Science Foundation of China (Grant Numbers: 81472615,81600044).

Supplementary Materials

Supplementary 1. Table S1. Top 15 genes were screened to besignificantly upregulated in A549/DDP cells vs. A549 cells byRNA sequencing.

Supplementary 2. Table S2. HALLMARK_GLYCOLYSISgene set2.

References

[1] W. Chen, R. Zheng, P. D. Baade et al., “Cancer statistics inChina, 2015,” CA: A Cancer Journal for Clinicians, vol. 66,no. 2, pp. 115–132, 2016.

[2] M. Wen, J. Xia, Y. Sun et al., “Combination of EGFR-TKIswith chemotherapy versus chemotherapy or EGFR-TKIs alonein advanced NSCLC patients with EGFR mutation,” Biologics,vol. 12, pp. 183–190, 2018.

[3] K. Shen, J. Cui, Y. Wei et al., “Effectiveness and safety of PD-1/PD-L1 or CTLA4 inhibitors combined with chemotherapyas a first-line treatment for lung cancer: a meta-analysis,” Jour-nal of Thoracic Disease, vol. 10, no. 12, pp. 6636–6652, 2018.

[4] L. Galluzzi, I. Vitale, J. Michels et al., “Systems biology of cis-platin resistance: past, present and future,” Cell Death & Dis-ease, vol. 5, no. 5, article e1257, 2014.

[5] R. Brigelius-Flohé and M. Maiorino, “Glutathione peroxi-dases,” Biochimica et Biophysica Acta (BBA) - General Subjects,vol. 1830, no. 5, pp. 3289–3303, 2013.

[6] A. P. Kipp, “Selenium-dependent glutathione peroxidases dur-ing tumor development,” Advances in Cancer Research,vol. 136, pp. 109–138, 2017.

[7] M.Woenckhaus, L. Klein-Hitpass, U. Grepmeier et al., “Smok-ing and cancer-related gene expression in bronchial epithe-lium and non-small-cell lung cancers,” The Journal ofPathology, vol. 210, no. 2, pp. 192–204, 2006.

[8] L. M. Leon, M. Gautier, R. Allan et al., “The nuclear hypoxia-regulated NLUCAT1 long non-coding RNA contributes toan aggressive phenotype in lung adenocarcinoma through reg-ulation of oxidative stress,” Oncogene, vol. 38, no. 46,pp. 7146–7165, 2019.

[9] H. Huang,W. Zhang, Y. Pan et al., “YAP suppresses lung squa-mous cell carcinoma progression via deregulation of theDNp63-GPX2 axis and ROS accumulation,” Cancer Research,vol. 77, no. 21, pp. 5769–5781, 2017.

[10] Y. Zhang, H. Du, Y. Li, Y. Yuan, B. Chen, and S. Sun, “ElevatedTRIM23 expression predicts cisplatin resistance in lung ade-nocarcinoma,” Cancer Science, vol. 111, no. 2, pp. 637–646,2020.

[11] Y. W. Zhang, Y. Zheng, J. Z. Wang et al., “Integrated analysisof DNA methylation and mRNA expression profiling revealscandidate genes associated with cisplatin resistance in non-

small cell lung cancer,” Epigenetics, vol. 9, no. 6, pp. 896–909,2014.

[12] K. J. Livak and T. D. Schmittgen, “Analysis of relative geneexpression data using real-time quantitative PCR and the2−ΔΔCT method,” Methods, vol. 25, no. 4, pp. 402–408, 2001.

[13] R. Brigelius-Flohé and A. P. Kipp, “Physiological functions ofGPx2 and its role in inflammation-triggered carcinogenesis,”Annals of the New York Academy of Sciences, vol. 1259,pp. 19–25, 2012.

[14] A. Naiki-Ito, M. Asamoto, N. Hokaiwado et al., “Gpx2 is anoverexpressed gene in rat breast cancers induced by three dif-ferent chemical carcinogens,” Cancer Research, vol. 67, no. 23,pp. 11353–11358, 2007.

[15] D. Liu, L. Sun, J. Tong, X. Chen, H. Li, and Q. Zhang, “Prog-nostic significance of glutathione peroxidase 2 in gastric carci-noma,” Tumor Biology, vol. 39, no. 6, 2017.

[16] T. Liu, X. F. Kan, C. Ma et al., “GPX2 overexpression indicatespoor prognosis in patients with hepatocellular carcinoma,”Tumor Biology, vol. 39, no. 6, 2017.

[17] Y. Murawaki, H. Tsuchiya, T. Kanbe et al., “Aberrant expres-sion of selenoproteins in the progression of colorectal cancer,”Cancer Letters, vol. 259, no. 2, pp. 218–230, 2008.

[18] C. Liu, X. He, X. Wu, Z. Wang, W. Zuo, and G. Hu, “Clinico-pathological and prognostic significance of GPx2 proteinexpression in nasopharyngeal carcinoma,” Cancer Biomarkers,vol. 19, no. 3, pp. 335–340, 2017.

[19] Z. Lei, D. Tian, C. Zhang, S. Zhao, and M. Su, “Clinicopatho-logical and prognostic significance of GPX2 protein expressionin esophageal squamous cell carcinoma,” BMC Cancer, vol. 16,no. 1, 2016.

[20] H. Mörk, M. Scheurlen, O. Al-Taie et al., “Glutathione perox-idase isoforms as part of the local antioxidative defense systemin normal and Barrett's esophagus,” International Journal ofCancer, vol. 105, no. 3, pp. 300–304, 2003.

[21] L. N. Barrera, A. Cassidy, W. Wang et al., “TrxR1 and GPx2are potently induced by isothiocyanates and selenium, andmutually cooperate to protect Caco-2 cells against freeradical-mediated cell death,” Biochimica et Biophysica Acta(BBA) - Molecular Cell Research, vol. 1823, no. 10, pp. 1914–1924, 2012.

[22] B. L. Emmink, J. Laoukili, A. P. Kipp et al., “GPx2 suppressionof H2O2 stress links the formation of differentiated tumor massto metastatic capacity in colorectal cancer,” Cancer Research,vol. 74, no. 22, pp. 6717–6730, 2014.

[23] D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: thenext generation,” Cell, vol. 144, no. 5, pp. 646–674, 2011.

[24] P. Vaupel, H. Schmidberger, and A. Mayer, “The Warburgeffect: essential part of metabolic reprogramming and centralcontributor to cancer progression,” International Journal ofRadiation Biology, vol. 95, no. 7, pp. 912–919, 2019.

[25] S. E. Elf and J. Chen, “Targeting glucose metabolism in patientswith cancer,” Cancer, vol. 120, no. 6, pp. 774–780, 2014.

[26] E. Obre and R. Rossignol, “Emerging concepts in bioenergeticsand cancer research: metabolic flexibility, coupling, symbiosis,switch, oxidative tumors, metabolic remodeling, signaling andbioenergetic therapy,” The International Journal of Biochemis-try & Cell Biology, vol. 59, pp. 167–181, 2015.

[27] A. M. Strohecker and E. White, “Targeting mitochondrialmetabolism by inhibiting autophagy in BRAF-driven cancers,”Cancer Discovery, vol. 4, no. 7, pp. 766–772, 2014.


http://downloads.hindawi.com/journals/omcl/2020/7370157.f1.doc

http://downloads.hindawi.com/journals/omcl/2020/7370157.f2.xlt

[28] P. Lis, M. Dyląg, K. Niedźwiecka et al., “The HK2 dependent"Warburg effect" and mitochondrial oxidative phosphoryla-tion in cancer: targets for effective therapy with 3-bromopyru-vate,” Molecules, vol. 21, no. 12, article 1730, 2016.

[29] L. Yu, M. Lu, D. Jia et al., “Modeling the genetic regulation ofcancer metabolism: interplay between glycolysis and oxidativephosphorylation,” Cancer Research, vol. 77, no. 7, pp. 1564–1574, 2017.

[30] H. Kurokawa, H. Ito, and H. Matsui, “The cisplatin-derivedincrease of mitochondrial reactive oxygen species enhancesthe effectiveness of photodynamic therapy via transporter reg-ulation,” Cell, vol. 8, no. 8, p. 918, 2019.

[31] Z. Chen, T. Shi, L. Zhang et al., “Mammalian drug efflux trans-porters of the ATP binding cassette (ABC) family in multidrugresistance: a review of the past decade,” Cancer Letters,vol. 370, no. 1, pp. 153–164, 2016.

[32] K. Minami, Y. Kamijo, Y. Nishizawa et al., “Expression ofABCB6 is related to resistance to 5-FU, SN-38 and vincristine,”Anticancer Research, vol. 34, no. 9, pp. 4767–4773, 2014.

[33] R. Tsunedomi, N. Iizuka, K. Yoshimura et al., “ABCB6 mRNAand DNA methylation levels serve as useful biomarkers forprediction of early intrahepatic recurrence of hepatitis Cvirus-related hepatocellular carcinoma,” International Journalof Oncology, vol. 42, no. 5, pp. 1551–1559, 2013.

[34] K. Polireddy, H. Chavan, B. A. Abdulkarim, andP. Krishnamurthy, “Functional significance of the ATP-binding cassette transporter B6 in hepatocellular carcinoma,”Molecular Oncology, vol. 5, no. 5, pp. 410–425, 2011.


elevated glutathione peroxidase 2 expression promotes cisplatin...

Documents