Squalene monooxygenase（SQLE) protects ovarian cancer cells from ferroptosis

doi:10.21203/rs.3.rs-2248156/v2

Download PDF

Research Article

Squalene monooxygenase（SQLE) protects ovarian cancer cells from ferroptosis

https://doi.org/10.21203/rs.3.rs-2248156/v2

This work is licensed under a CC BY 4.0 License

Version 2

posted

You are reading this latest preprint version

Background: Ovarian cancer is one of the three major gynecological cancers, which is closely related to squalene monooxygenase (SQLE). We aim to clarify the role of SQLE in ovarian cancer.

Methods: The expression of SQLE was detected by qRT-PCR, Western Bolt and immunohistochemistry. The association between SQLE and ferroptosis was demonstrated by TCGA, GTEx database, TMT protein sequencing, qRT-PCR, Western Bolt, immunofluorescence, ROS detection, and lipid peroxide detection. Animal experiments verified the relationship between SQLE and ferroptosis in ovarian cancer.

Results: The expression of SQLE increased in ovarian cancer tissues and cell lines. The decreased expression of SQLE caused ferroptosis of ovarian cancer cells, and enhanced the sensitivity of ovarian cancer cells to ferroptosis inducers.

Conclusion: Our study shows that SQLE is highly expressed in ovarian cancer tissues and cells, and the high expression of SQLE in ovarian cancer may promote the occurrence and development of ovarian cancer by protecting ovarian cancer cells from ferroptosis, thus enlightening new treatment methods for ovarian cancer.

Ovarian Cancer

Ferroptosis

Squalene monooxygenase (SQLE)

Ovarian cancer (OC) is ranked as the 3rd most frequent gynecological malignancy around the globe, however, the mortality rate associated with OC is the highest among these cancers. Patients with OC are mostly not aware of the disease and therefore, do not seek treatment until the symptoms develop, which appear in terminal stages or recurrent or metastasized conditions[1, 2]. OC has 3 histological types and epithelial OC (EOC) is the most frequent. The 5-year survival rate for EOC is 45.6% [3] and only 15.5% of patients without it. In some EOC cases, the patients may be diagnosed either too early or too late because of abnormal protein indicators [4]. Therefore, it is necessary to identify and characterize specific proteins involved in ovarian cell death. To counter this, novel approaches have been developed using next-generation sequencing.

Ferroptosis is a new form of programmed cell death, stimulated by chronic lipid peroxidation because of reactive oxygen species (ROS) production and iron overload. Unlike other programmed cell death (such as autophagy, apoptosis, necrosis, and cytokinesis) ferroptosis exhibits distinct morphological, biochemical, and genetic differences. The main features of ferroptosis are dense mitochondrial membranes, smaller mitochondria, decreased or lacking mitochondrial cristae, and disrupted outer membranes [5–7]. Furthermore, ferroptosis is primarily driven by lipid peroxidation (LPO), a build-up of the deadly lipid peroxide[7], ROS is a byproduct of aerobic processes that are constantly generated, transformed, and utilized by all organisms. Superoxide (O2-), hydrogen peroxide (H₂O₂), hydroxyl radical (HO-), and lipid peroxide (ROOH) are common ROS present in living organisms [8]. In cancer, the endogenous ROS generation is increased by certain enzymes such as lipoxygenases (LOXs), NADPH oxidases (NOXs), and cyclooxygenase (COXs) [9, 10].

Acsl4, a member of the acyl-coenzyme long-chain family (Acsl), is critically involved in ferroptosis, therefore, cellular lipids are considered important nodes for determining the sensitivity and ferroptosis resistance [8, 11]. Acsl4 modulates the CoA esterification into free fatty acids by using ATPs. Acyl-CoA once formed stimulates corresponding fatty acids for oxidation or lipid synthesis [9, 12]. When Glutathione Peroxidase 4 (GPX4) is inhibited, the transition from Glutathione (GSH) to GSH/oxidized glutathione (GSSH) is weakened and LPO accumulates, leading to ferroptosis in tumor cells [10, 13].

Ferritin comprises ferritin light chain (FTL) and ferritin heavy chain 1 (FTH1) and maintains iron homeostasis in cells. Inhibition of iron reactive element binding protein 2 (IREB2) expression, which is a critical transcription factor that takes part in the iron metabolic process, notably increases FTL and FTH1 expression, this inhibits erastin-induced ferroptosis[11, 12].

Cholesterol is the major sterol in mammalian cell membranes and maintains cell integrity, fluidity, and intracellular homeostasis [13]. Squalene epoxidase (SQLE) acts by catalyzing squalene conversion to 2,3-epoxy squalene, the second rate-limiting enzyme in cholesterol biosynthesis. SQLE is expressed as a gene on chromosome 3p16 and has been implicated in cell cycle progression [14], apoptosis, and differentiation. SQLE was first identified by its function in cancer research [15, 16]. In breast cancer, it has been associated with prognosis, disease progression, immune environment, and as a ferroptosis regulator [17]. Low expression of SQLE in ALK + large cell lymphoma cells reduced squalene levels and make them sensitive to GPX4 inhibitors. It also inhibited in vivo tumor growth in nude mice and squalene accumulation, sensitized SQLE-deficient cells to ferroptosis stimulated by ML162 and RSL3 (GPX4 inhibitors) [18].

Data Acquisition and Processing

All the data utilized in this investigation have public access. Gene expression data and clinical history were acquired from the Cancer Genome Atlas (TCGA) and the GTEx databases. Then, to normalize raw expression data the Robust Multiarray Average was applied, and 58 genes associated with ferroptosis were selected.

Immunohistochemical Staining

SQLE staining was carried out on 149 OC tissues, 14 ovarian junctional ovarian tumors, and 6 benign ovarian lesions via the ABC Immunostaining program (Solebro, China). According to the blind randomized staining intensity assessments and stained cells percentage, microarrays were scored by 2 independent researchers. On a scale of 0 to 3; 0 = negative, 1 = weak, 2 = moderate, and 3 = strong. The percentage of positive staining cells ranged from 0 to 4: 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), and 4 (76–100%). Final product scores were 0 to 12, and if the final SQLE expression score was ≥ 6 it was declared positive.

Cell Culture

Normal human ovarian epithelial cell lines (IOSE-80) and human OC cell lines SKOV-3, OVCAR3, ES2, A2780, HEY, and HO8910 were utilized in this investigation. A2780 and HO8910 cells were propagated in RPMI-1640 media. SKOV-3 in McCoy's 5A media, and ES2 and HEY cells in DMEM. All the mediums were augmented with 10% fetal bovine serum. All cultures were put in the incubator with a moist atmosphere at 37°C and 5% CO2. The above cell lines were purchased from Pricella, Wuhan, China( https://www.procell.com.cn )All of them passed STR identification and mycoplasma detection.

ROS Detection

ROS levels in OC cells were evaluated by probe 2 ', 7'-DCFH-DA (Beyotime), this probe is oxidized to dichlorofluorescein (highly fluorescent) by intracellular oxygen. The cells were kept in dark augmented with a 10µM DCFH-DA for 30 minutes in the aforementioned incubator, followed by ice-cold PBS rinsing, thrice. Then the cells were re-dissolved in PBS (300µL) and their fluorescence intensity was determined by the flow cytometer (BD Biosciences), using FlowJo X 10.0. 7 Software.

Immunofluorescence Staining

A 24-hole plate was propagated with cells by a prearranged cell clamp, rinsed thrice with PBS, followed by fixation using 4% poly-formaldehyde for 15 minutes, and then transfused for 5 minutes in 0.1% Triton X, followed by overnight (4°C) incubation with an anti-incubation regimen targeting SQLE (diluted 1: 200), GPX4 (diluted 1: 200), ACSL4 (diluted 1: 200), COX2 (diluted 1: 200), NOX1 (diluted 1: 200), and for 1 hour with FTH1 (diluted 1: 200) at room temperature. Then, cells were kept in Alexa Fluor® 488 conjugated dizumab (dilution 1: 1,000) with 4', 6-diamidine-2-phenylindole (DAPI) at environmental temperature for 2 hours. Images were acquired via the fluorescence microscope.

shRNA knockdown of SQLE

A lentiviral shRNA vector was constructed, directed at the SQLE coding region sequence (GCATTGCCACTTTCACCTA) and this was used to establish SQLE-knockdown in SKOV3 and HEY cells. Successfully established knockdown cells were separated by puromycin resistance selection.

Quantitative Proteomics Based On Tandem Mass Spectrometry Tags

We useQ-Exactive HF for proteomic analysis, and then use ProteomeDiscoverer 2.4.1.15 (ThermoFisher Scientific).The software searches qualitative and quantitative data according to the search results, and performs expression level analysis and function analysis respectively after quality evaluation and preprocessing. Several common databases were used to annotate and analyze the identified proteins.

Quantitative real-time PCR (qRT-PCR)

qRT-PCR was performed as previously described (14) Primers used were:

human SQLE forward: TGA CAA TTC TCA TCT GAG GTC CA; human SQLE reverse: GAG GGA TAA CCC TTT AGC AGT TTT; human GPX4forward: GAGGCAAGACCGAAGTAAACTAC; human GPX4 reverse: CCGAACTGGTTACACGGGAA; human ACSL4 forward: CATCCCTGGAGCAGATACTCT; human ACSL4 reverse: TCACTTAGGATTTCCCTGGTCC; human COX2 forward: CTGGCGCTCAGCCATACAG; human COX2reverse: CGCACTTATACTGGTCAAATCCC; human NOX1forward: TTGTTTGGTTAGGGCTGAATGT; human NOX1 reverse: GCCAATGTTGACCCAAGGATTTT; human FTH1forward: CCCCCATTTGTGTGACTTCAT; human FTH1 reverse: GCCCGAGGCTTAGCTTTCATT; human GAPDH forward: ACCACAGTCCATGCCATCAC; human GAPDH reverse: TCCACCACCCTGTTGCTGTA

Western Blot Analysis

This analysis was carried out and quantified by the protocol described previously[19]. The following antibodies were utilized for probing the membranes; SQLE (proteintech Cat No. 12544-1-AP), GAPDH (proteintech Cat No. 60004-1-Ig), GPX4 (Affinity, catalog: DF6701), ACSL4 (Affinity, catalog: DF12141), COX2 (Affinity, catalog: AF7003), NOX1 (Affinity, catalog: DF8684), and FTH1 (Affinity, catalog: DF6278). The secondary antibody was HRP-conjugated goat anti-mouse (proteintech Cat No. SA00001-1) and goat anti-rabbit (proteintech, Cat No. SA00001-2).

C11-BODIPY Staining

Cells were propagated in 6-well plates, followed by 30 min of 10µM C11-BODIPY (Thermo Fisher Scientific) treatment. The fluorescence intensity of C11-bodipy staining was assessed via the BD LSRII flow cytometer (Becton Dickinson).

Animal Experiments

Female BALB/c nude mice were selected for this investigation and categorized as sh-ctrl group (administered with SKOV3 cells) and sh-SQLES1 group (administered with SQLE knockdown SKOV3 cells). In the right dorsum of each mouse ̴ 0.2mL of a cell suspension (1000 × 10⁴ cells) was administered. After the experiment ended, digital calipers were used to determine the size of the tumor in each mouse. The tumor volume was assessed every 5 days by calculating the width and length. 30 days later, each mouse was executed and the tumor tissue was removed and weighed. The nude mice used in this experiment were anesthetized with isoflurane gas using a small animal gas anesthesia machine in the injection of ovarian cancer cells and the dissection of tumor body. When the experiment was terminated, the nude mice were killed with chloral hydrate overdose anesthesia.Animal handling was performed according to institutional guidelines.

Statistical Analysis Of Cell Culture Experiments

Excel and Prism 9 (Graphpad software) were utilized for performing statistics. All experiments were repeated thrice minimum of three replicates per condition. Intergroup comparison was assessed and statistical significance was evaluated via two-tailed unpaired Student’s t-tests. Data are presented as mean ± standard deviation.

Bioinformatics predicted SQLE as a gene associated with the occurrence of ferroptosis in ovarian cancer. We verified in ovarian cancer tissues that SQLE was more highly expressed compared to controls, that knockdown of SQLE in ovarian cancer cell lines caused ferroptosis in ovarian cancer cells, and we verified this result in in vivo experiments and exacerbated the sensitivity of ovarian cancer cells to the ferroptosis inducer ML210.

SQLE is a ferroptosis-associated gene and is highly expressed in ovarian cancer

Public accessible data sets were utilized. Gene expression data was obtained from Cancer Genome Atlas (TCGA) and GTEx databases. Because of the lack of para-cancer samples in TCGA-OV, the normal OC samples were obtained GTEx database to determine the differential ferroptosis gene expression in OC and normal ovarian samples. Then, the Robust Multi-array average was applied for normalizing the raw expression data [20]. 58 ferroptosis-associated genes were obtained (Fig. 1A). Target genes biological processes (BP) increased under oxidative stress, during homeostasis, metal ion activity response, and cofactor metabolic mechanism. Increased molecular functions (MF) were observed in trivalent iron binding, aldo-keto reductase (NADP), and oxidoreductase activities and cellular components (CC) was enhanced during the modulation of epithelial cell growth, lipid droplets, astrocyte projection, apical plasma membrane; KEGG enriched was observed in ferroptosis, hypoxia-inducible factor (HIF)-1 and NOD-like receptor signaling pathways, cancer’s central carbon metabolism, Kaposi's sarcoma related herpesvirus infection and PPAR signaling pathway (Fig. 1B).The org.Hs.eg.db package converts gene symbols and entrezIDs based on the mget function. The gene ratio is represented by the X-axis, i.e. the number of enriched genes in each GO/the number of the total genes. Y-axis depicts enriched specific functions or pathways. The diameter of the circle depicts the gene number enriched on each GO. Intense the red color higher the degree of GO enrichment. A = GO, B = KEGG. (MF: molecular functions, BP: biological processes, and CC: cellular components).

Squalene cyclooxygenase (SQLE) is an aberrant metabolic gene overexpressed in ovarian cancer

Western blot results of fresh tissues revealed markedly increased levels of SQLE in OC tissues than in normal tissues (Fig. 2A/B). In addition, immunohistochemistry in 149 ovarian cancers, 14 junctional ovarian tumors, and 6 benign ovarian lesions showed high expression of SQLE in OC, slight expression in junctional ovarian tumors, and low expression in benign ovarian lesions (Fig. 2C). The SQLE expression in the ovarian epithelial cell line (IOSE-80) was also low and in OC cell lines SKOV3, HEY, A2780, ES-2, HO8910, and OVCAR3 were different, which were verified by protein immunoblot and Real-Time PCR (Fig. 2D-E). SKOV3 and Hey in OC cell lines were highly expressed with SQLE using lentivirus as a vector to knock down SQLE and lentivirus with false interference sequences were taken as controls. OVCAR3 with low expression of SQLE in OC cell lines was selected to overexpress SQLE in OC cells using lentiviral vectors, and empty viral vectors were used as controls. SQLE knockdown and overexpression were validated by protein immunoblot, Quantum Real-Time PCR, and cell immunofluorescence assays (Fig. 2F-H).

Effect of SQLE on proteomics of SKOV3 ovarian cancer cells.

We selected lentivirus to knock down SQLE of ovarian cancer cell line SKOV3, and then carried out TMT proteomics sequencing. The results showed that after knocking down SQLE, there were 191 up-regulated proteins, 185 down-regulated proteins (Fig. 3A), and heat maps of protein abundance levels in different groups. There are 3 biological repeats (repeats 1, 2, 3). (Fig. 3B). The KEGG database was used to analyze the difference protein in the way of Pathway (combined with the KEGG annotation results), and the hypergeometric distribution test was used to calculate the significance of the enrichment of the difference protein in each Pathway entry and expressed with the p value. KEGG enrichment analysis top20 (sorted from large to small by log10Pvalue corresponding to each entry) (Fig. 3C).

SQLE knockdown resulted in ferroptosis and its overexpression prevented ferroptosis in ovarian cancer cells.

To test whether SQLE knockdown results in ferroptosis, changes in the generation of ROS and lipid peroxides in OC cell lines SKOV3 were measured. In Hey and OVCAR3 after SQLE knockdown, a slight ROS decrease and lipid peroxides in OC cells were noticed. ROS-induced lipid peroxidation is critically involved in cell ferroptosis [16].(Fig. 4D) .Furthermore, the expression of ferroptosis-associated molecular markers COX2, NOX1, ACSL4, GPX4, and FTH1 was validated using protein immunoblot, quantational real-time PCR, and cellular immunofluorescence, and showed no significant upregulation of COX2, NOX1, and downregulation of FTH1 in knockdown and overexpression of SQLE.(Fig. 4A-C)

SQLE knockdown increased the sensitivity of ovarian cancer cells to ferroptosis inducers, whereas SQLE overexpression decreased the sensitivity of ovarian cancer cells to ferroptosis inducers

To further investigate whether intervention with SQLE alters OC cells' sensitivity to ferroptosis inducers, intracellular lipid peroxide levels were assessed by flow cytometry for 30 minutes after treatment with 10uM of ML210 (ferroptosis inducer) in SQLE knockdown and OVCAR3 overexpressed SKOV3 and Hey cells. The GXP4 expression levels were validated by protein immunoblot and cell immunofluorescence assay after treatment with C11-BODIPY staining for 1 hour. (Fig. 5A).It was found that treatment with SQLE after knockdown in SKOV3 and Hey increased intracellular lipid peroxide accumulation and depleted GPX4, while treatment with SQLE after overexpression of OVCAR3 resulted in a relative decrease in intracellular lipid peroxide accumulation and less GPX4 depletion.(Fig. 5B-C).

Expression of COX2, NOX1, ACSL4, GPX4, FTH1 in subcutaneous tumors of nude mouse ovarian cancer tissues

In the preliminary investigation it was we found that SQLE inhibited the growth of OC xenografts in nude mice [18](Fig. 6A-B) .Here, further investigation was carried out to evaluate whether SQLE induces ferroptosis in SKOV3 cells in vivo, immunohistochemistry results show elevated mRNA levels of COX2, NOX1, ACSL4, and FTH1 when SQLE is downregulated in vivo (Fig. 6C-D).

Ovarian cancer is a disease with a poor prognosis and the advancement in treatment procedures is close to none [1]. There are 3 types of primary ovarian tumors: epithelial tumors (60%), germline tumors (30%), and intersex tumors (8%). Most of the malignant OC (80–85%) are epithelial OC [21]. During this investigation, the high expression of SQLE as a gene associated with ferroptosis in ovarian cancer patients' tissues was investigated. Silencing SQLE resulted in the aggregation of ROS, and lipid peroxides in OC cells, accompanied by increased expression of enzymes related to endogenous ROS such as NOX1 and COX2. Furthermore, ACSL4 upregulation, one of the key factors associated with ferroptosis, promotes lipid peroxides increase. SQLE was protected from GPX4[22], and it has been reported that the knockout of FTH1 in the gut of mice leads to excessive iron absorption and promotes ferroptosis [23, 24]. SQLE silencing inhibited ferroptosis by consuming GPX4 and FTH1. Moreover, SQLE silencing increased the compensation for ROS and lipid peroxides accumulation and reduced cell damage. Cholesterol, essential membrane components, and various biological metabolites are involved in cancer [25]. However, the effect of cholesterol on cancer advancement is undetermined [26]. Recent studies have shown a positive link between increased serum cholesterol and the risk of certain types of cancer, such as prostate cancer. Statin-blocking cholesterol levels are associated with a reduced risk of melanoma, non-Hodgkin's lymphoma, and endometrial and breast cancers [27–30]. In this investigation SQLE Silencing sensitized OC cells to the GPX4 inhibitor (ML210) to ferroptosis, adding to a pathway enhancing ferroptosis in hopes of providing promising drug targets for ovarian cancer treatment.

To make a long story short.Our study shows that SQLE is highly expressed in ovarian cancer tissues and cells, and the high expression of SQLE in ovarian cancer may promote the occurrence and development of ovarian cancer by protecting ovarian cancer cells from ferroptosis, thus enlightening new treatment methods for ovarian cancer.

Ethics approval and consent to participate

This study was conducted in accordance with the relevant guidelines and regulations (Declaration of Helsinki) and in accordance with ARRIVE guidelines（ https://arriveguidelines.org ).The manuscript was ethically approved by the Research Ethics Committee of Bengbu Medical College (approval No. S2022281).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

All data needed to evaluate the conclusions of the paper are in the paper and/or supplementary materials. Figure 1A-B analysed used clinical data publicly available in the following online databases: TCGA(https://www.cancer.gov/), GTEx (Genotype-Tissue Expression (GTEx) (nih.gov)), and Figure 3s proteomic sequencing analysis data is added to the supplementary materials.

Funding

The present study was supported by the Foundation of Educational Department in Anhui province, (No.KJ2021A0720),and

the Bengbu Medical College Postgraduate Innovation Plan, (No.Byycx21092)

Authors' contributions

R.Z. wrote the main manuscript text and prepared figures 1-6. All authors reviewed the manuscript."

Acknowledgements

We thank all the participants in this study for their valuable input. We also thank the Central Laboratory of Bengbu Medical College for providing research equipment and technical support for this study.

Kuroki L, Guntupalli SR. Treatment of epithelial ovarian cancer. BMJ. 2020;371:m3773.
Doubeni CA, Doubeni AR, Myers AE. Diagnosis and Management of Ovarian Cancer. Am Fam Physician. 2016;93(11):937–44.
Oronsky B, Ray CM, Spira AI, Trepel JB, Carter CA, Cottrill HM. A brief review of the management of platinum-resistant-platinum-refractory ovarian cancer. Med Oncol. 2017;34(6):103.
He WP, Guo YY, Yang GP, Lai HL, Sun TT, Zhang ZW, et al. CHD1L promotes EOC cell invasiveness and metastasis via the regulation of METAP2. Int J Med Sci. 2020;17(15):2387–95.
Wang H, Liu C, Zhao Y, Gao G. Mitochondria regulation in ferroptosis. Eur J Cell Biol. 2020;99(1):151058.
Chen X, Kang R, Kroemer G, Tang D. Broadening horizons: the role of ferroptosis in cancer. Nat Rev Clin Oncol. 2021;18(5):280–96.
Li D, Li Y. The interaction between ferroptosis and lipid metabolism in cancer. Signal Transduct Target Ther. 2020;5(1):108.
Klasson TD, LaGory EL, Zhao H, Huynh SK, Papandreou I, Moon EJ, et al. ACSL3 regulates lipid droplet biogenesis and ferroptosis sensitivity in clear cell renal cell carcinoma. Cancer Metab. 2022;10(1):14.
Ma Y, Zhang X, Alsaidan OA, Yang X, Sulejmani E, Zha J, et al. Long-Chain Acyl-CoA Synthetase 4-Mediated Fatty Acid Metabolism Sustains Androgen Receptor Pathway-Independent Prostate Cancer. Mol Cancer Res. 2021;19(1):124–35.
Chen P, Li X, Zhang R, Liu S, Xiang Y, Zhang M, et al. Combinative treatment of β-elemene and cetuximab is sensitive to KRAS mutant colorectal cancer cells by inducing ferroptosis and inhibiting epithelial-mesenchymal transformation. Theranostics. 2020;10(11):5107–19.
Arosio P, Elia L, Poli M. Ferritin, cellular iron storage and regulation. IUBMB Life. 2017;69(6):414–22.
Fang Y, Chen X, Tan Q, Zhou H, Xu J, Gu Q. Inhibiting Ferroptosis through Disrupting the NCOA4-FTH1 Interaction: A New Mechanism of Action. ACS Cent Sci. 2021;7(6):980–9.
Espinosa G, López-Montero I, Monroy F, Langevin D. Shear rheology of lipid monolayers and insights on membrane fluidity. Proc Natl Acad Sci U S A. 2011;108(15):6008–13.
Nagai M, Sakakibara J, Wakui K, Fukushima Y, Igarashi S, Tsuji S, et al. Localization of the squalene epoxidase gene (SQLE) to human chromosome region 8q24.1. Genomics. 1997;44(1):141–3.
Gill S, Stevenson J, Kristiana I, Brown AJ. Cholesterol-dependent degradation of squalene monooxygenase, a control point in cholesterol synthesis beyond HMG-CoA reductase. Cell Metab. 2011;13(3):260–73.
Zelcer N, Sharpe LJ, Loregger A, Kristiana I, Cook EC, Phan L, et al. The E3 ubiquitin ligase MARCH6 degrades squalene monooxygenase and affects 3-hydroxy-3-methyl-glutaryl coenzyme A reductase and the cholesterol synthesis pathway. Mol Cell Biol. 2014;34(7):1262–70.
Tang W, Xu F, Zhao M, Zhang S. Ferroptosis regulators, especially SQLE, play an important role in prognosis, progression and immune environment of breast cancer. BMC Cancer. 2021;21(1):1160.
Garcia-Bermudez J, Baudrier L, Bayraktar EC, Shen Y, La K, Guarecuco R, et al. Squalene accumulation in cholesterol auxotrophic lymphomas prevents oxidative cell death. Nature. 2019;567(7746):118–22.
Chai W, Ye F, Zeng L, Li Y, Yang L. HMGB1-mediated autophagy regulates sodium/iodide symporter protein degradation in thyroid cancer cells. J Exp Clin Cancer Res. 2019;38(1):325.
Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4(2):249–64.
Devouassoux-Shisheboran M, Genestie C. Pathobiology of ovarian carcinomas. Chin J Cancer. 2015;34(1):50–5.
Stockwell BR, Jiang X, Gu W. Emerging Mechanisms and Disease Relevance of Ferroptosis. Trends Cell Biol. 2020;30(6):478–90.
Tao Y, Wu Q, Guo X, Zhang Z, Shen Y, Wang F. MBD5 regulates iron metabolism via methylation-independent genomic targeting of Fth1 through KAT2A in mice. Br J Haematol. 2014;166(2):279–91.
Kong N, Chen X, Feng J, Duan T, Liu S, Sun X, et al. Baicalin induces ferroptosis in bladder cancer cells by downregulating FTH1. Acta Pharm Sin B. 2021;11(12):4045–54.
Xu H, Zhou S, Tang Q, Xia H, Bi F. Cholesterol metabolism: New functions and therapeutic approaches in cancer. Biochim Biophys Acta Rev Cancer. 2020;1874(1):188394.
Garcia-Ruiz C, Conde de la Rosa L, Ribas V, Fernandez-Checa JC. Mitochondrial cholesterol and cancer. Semin Cancer Biol. 2021;73:76–85.
Shafique K, McLoone P, Qureshi K, Leung H, Hart C, Morrison DS. Cholesterol and the risk of grade-specific prostate cancer incidence: evidence from two large prospective cohort studies with up to 37 years' follow up. BMC Cancer. 2012;12:25.
Pelton K, Freeman MR, Solomon KR. Cholesterol and prostate cancer. Curr Opin Pharmacol. 2012;12(6):751–9.
Allott EH, Howard LE, Cooperberg MR, Kane CJ, Aronson WJ, Terris MK, et al. Serum lipid profile and risk of prostate cancer recurrence: Results from the SEARCH database. Cancer Epidemiol Biomarkers Prev. 2014;23(11):2349–56.
Cardwell CR, Hicks BM, Hughes C, Murray LJ. Statin use after colorectal cancer diagnosis and survival: a population-based cohort study. J Clin Oncol. 2014;32(28):3177–83.

No competing interests reported.

Download PDF

Version 2

posted

You are reading this latest preprint version

Squalene monooxygenase（SQLE) protects ovarian cancer cells from ferroptosis

Status:

Version 2

Abstract

Figures

Introduction

Materials And Methods

Data Acquisition and Processing

Immunohistochemical Staining

Cell Culture

ROS Detection

Immunofluorescence Staining

shRNA knockdown of SQLE

Quantitative Proteomics Based On Tandem Mass Spectrometry Tags

Quantitative real-time PCR (qRT-PCR)

Western Blot Analysis

C11-BODIPY Staining

Animal Experiments

Statistical Analysis Of Cell Culture Experiments

Results

SQLE is a ferroptosis-associated gene and is highly expressed in ovarian cancer

Squalene cyclooxygenase (SQLE) is an aberrant metabolic gene overexpressed in ovarian cancer

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 2