Disulfidptosis-associated ferroptosis gene BCAT2 regulates c-MYC expression and promotes the malignant progression of epithelial ovarian cancer cells by interacting with GYS1

doi:10.21203/rs.3.rs-5317339/v1

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Research Article

Disulfidptosis-associated ferroptosis gene BCAT2 regulates c-MYC expression and promotes the malignant progression of epithelial ovarian cancer cells by interacting with GYS1

https://doi.org/10.21203/rs.3.rs-5317339/v1

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Purpose

Epithelial ovarian cancer (EOC) is a prevalent gynecological malignancy with a notoriously poor prognosis. Recent oncological research has highlighted ferroptosis and disulfidptosis as novel forms of cell death with potential therapeutic implications. However, the relationship between these processes and their role in EOC remains poorly understood.

Methods

Through comprehensive bioinformatics analyses, we identified six disulfidptosis-related ferroptosis genes in EOC samples. A prognostic model was developed utilizing these genes to assess their predictive power for EOC survival prognosis. We further investigated the dual role of BCAT2 in regulating ferroptosis and modulating GYS1, which is implicated in disulfidptosis. The influence of BCAT2 on cell proliferation, migration, and invasion was examined through its regulation of c-MYC and its impact on G2M phase and EMT-related proteins.

Results

Our findings reveal that BCAT2 plays a pivotal role in both ferroptosis and disulfidptosis in EOC. It not only regulates ferroptosis but also modulates GYS1, thereby influencing disulfidptosis. We observed a strong correlation between BCAT2 and GYS1 expression. Additionally, BCAT2's interaction with GYS1 extends its influence beyond ferroptosis, significantly disrupting disulfidptosis as well.

Conclusion

This study provides valuable insights into the complex interplay between disulfidptosis and ferroptosis in EOC, our findings underscore the potential of targeting BCAT2 and GYS1 as a therapeutic strategy for EOC.

EOC

risk model

disulfidptosis

ferroptosis

BCAT2

GYS1

In 2022, the latest data released by China's National Cancer Centre indicated a continuous rise in the incidence of gynecological tumors, with 61,100 new ovarian cancer cases and 32,600 related deaths annually. Epithelial ovarian cancer (EOC) constitutes 80% of all ovarian cancer cases (Cho KR et al.2009).Current treatment modalities include surgical intervention, chemotherapy, and targeted therapy (Eisenhauer EA 2017).Despite these efforts, the prognosis for EOC remains poor, primarily due to challenges such as early diagnostic difficulties (Nebgen DR et al. 2019), chemotherapy resistance (Awada A et al. 2022), and a high recurrence rate(Le Saux O et al.2020).Due to the ovary's deep pelvic location, early symptoms are often obscured, leading to a late-stage diagnosis in 70% of patients(Roett MA et al. 2019). Consequently, the 5-year survival rate for these patients falls below 50% (Moufarrij S et al. 2019), in contrast to nearly 90% for those diagnosed at an early stage (Terp SK et al. 2023). Addressing the improvement of diagnostic and therapeutic strategies for EOC is therefore imperative.

Tumor growth involves a complex interaction of growth and cell death, including newly identified forms like ferroptosis and disulfidptosis (Tong X et al. 2022).Ferroptosis, an iron-dependent regulated cell death, involves the accumulation of lipid peroxides on cell membranes, resulting in cell death (Jiang X et al. 2021).It is crucial for tumor suppression (Chen X et al.2021).In ovarian cancer, excess iron accumulation has been shown to enhance DNA damage repair, thereby increasing the malignant potential of ovarian cancer cells in terms of proliferation, migration, and invasion(Zhang Q et al.202).Disulfidptosis, a recently identified cell death process, occurs in cells with high SLC7A11 protein expression under glucose-starvation conditions. The inadequate NADPH supply prevents cystine reduction to cysteine, leading to disulfide stress and subsequent cell death (Liu X et al.2023). However, a risk prediction model for EOC based on disulfidptosis-associated ferroptosis genes has yet to be reported.

Our study presents a refined risk prediction model that could significantly impact clinical decision-making in the management of epithelial ovarian cancer. The model's accuracy and reliability were confirmed through extensive validation using the Cancer Genome Atlas (TCGA)data. Ultimately, the present investigation substantiated the significant role of the branched-chain amino acid transaminase 2 (BCAT2) gene in the pathophysiology of EOC, elucidating its potential as a prognostic biomarker and therapeutic target.

Data acquisition

The study employed TCGA database data (https://portal.gdc.cancer.gov/), concentrating on EOC datasets to acquire RNA-seq, simple nucleotide variation (SNV) data, and clinical information from diverse brain sites.The transcriptome data included mRNAs from 427 tumor samples and 89 matched-normal samples.Clinical data were available for 565 patients, while SNV data were available for 407 patients, with 408 patients having accessible RNA-seq data and corresponding clinical information.Perl scripts (version 5.30; https://www.perl.org) were employed to extract clinicopathological details.

Liu (Liu X et al,2023) identified ten disulfidptosis-related genes relevant to this study. A total of 564 genes were obtained from the ferroptosis database (http://www.zhounan.org/ferrdb/current/).Spearman's correlation analysis (Cor > 0.3, P < 0.05) was conducted to explore the relationships between these genes, and the findings were visualized with a Sankey diagram.

The construction and validation of a risk model

This study employed the training set to construct a risk model centered on disulfidptosis-associated ferroptosis genes. The risk score was computed using the formula: (SLC1A5 * 0.2381) + (BRPF1 * 0.3792) + (RB1 * 0.2273) + (BCAT2 * 0.4241) + (ARF6 * 0.2824) + (GPT2 * 0.4271). The median risk score from the training set was used to stratify samples into low-risk and high-risk groups. The accuracy of the risk model was evaluated by generating ROC curves and calculating the C-index. Nomograms and calibration curves were generated with the 'survival,' 'replot,' and 'rms' packages to evaluate the model's predictive performance. Kaplan-Meier analysis and the log-rank test were used to compare survival outcomes across different risk categories.

Cell culture

The human ovarian cancer cell lines SKOV3 and A2780, as well as the human ovarian epithelial cell line IOSE-80, were sourced from the American Type Culture Collection (ATCC).A2780 cells were cultured in 1640 medium(Gibco, Grand Island, NY, USA), while SKOV3 and IOSE-80 cells were cultured in DMEM medium(Gibco, Grand Island, NY, USA), supplemented with 10% FBS (BI, Shanghai, China)and Penicillin/Streptomycin at 37°C in a humidified atmosphere with 5% CO2.

Antibodies, reagents, and siRNAs

Antibodies for BCAT2, GYS1, c-MYC, and CDK1 were obtained from Abcam (Cambridge, MA, USA), whereas those for E-cadherin, N-cadherin, Snail, Slug, CDC25C, and IgG were acquired from Cell Signaling Technology (Boston, MA, USA). Protein A/G was sourced from Thermo Fisher Scientific. The anti-β-actin antibody, serving as an internal control, was obtained from ZSGB-BIO (Beijing, China).Erastin was acquired from MCE (Sigma Aldrich, Shanghai, China).Two distinct BCAT2-specific siRNAs were designed by Huzhou Hippo Biotechnology Co., Ltd (Huzhou, Zhejiang, China).Specific siRNAs sequences for BCAT2 were showed in Supplement Table 1.

RNA extraction and qRT-PCR

Total RNA was extracted as per the manufacturer’s protocol, and 1 µg was reverse-transcribed into complementary DNA (cDNA). The primer sequences used were in Supplement Table 2. Real-time PCR was performed using the TAKARA kit protocol, starting with a pre-denaturation step at 95℃ for 30 seconds, followed by 40 cycles of 95℃ for 5 seconds and 60℃ for 34 seconds. Amplification and melting curves were generated, and data were analyzed using the 2^−Δct method. Each sample was tested in triplicate.

Western blot

Protein quantification was performed using the BCA method, and the separated proteins were obtained via SDS-PAGE. The primary antibody (1:1000) was incubated overnight and the secondary antibody (1:20000) was incubated for two hours.Finally, the target bands were visualized by fluorescence scanning using the BIO-RAD gel imaging system.β-actin was used as the internal reference. Each experiment was conducted thrice.

CCK8 assay

5000 treated SKOV3 cells per well were seeded into a 96-well plate.100 µL of fresh medium with 10% CCK8 solution (Jiangsu KeyGEN BioTECH Corp., Ltd, Jiangsu, China) was added, followed by a 2-hour incubation at 37°C. Absorbance at 450 nm was then measured using a Multiskan Spectrum 1500 spectrophotometer (Thermo, USA).

Colony-formation assay

BCAT2-silenced cells were seeded in 6-well plates at a density of 1000 cells per well and incubated at 37°C for 14 days.The cells were fixed with methanol, stained with crystal violet, and colonies with over 50 cells were counted.

Assay for EdU (5-ethynyl-2-deoxyuridine)

Treated-SKOV3 cells were seeded at 3000 cells per well in 96-well plates and incubated overnight at 37°C.An EdU assay was performed following the manufacturer's guidelines (Jiangsu KeyGEN BioTECH Corp., Ltd).The cells were promptly examined using a fluorescence microscope, with each sample tested in duplicate.

Flow cytometry (FL)

Cell apoptosis was assessed after 48 hours by counting cells after digestion with EDTA-free trypsin.1×10^6 cells were labeled with FITC/PI dye and analyzed using a BD LSRFortessa flow cytometer (New Jersey, NJ, USA) in triplicate.For cell cycle analysis, after digestion and counting, cells were lysed using RNAase, fixed in 70% ethanol for 2 hours, and stained with PI dye. Data were processed and analyzed using FlowJo (FlowJo_v10.8.1).

Transwell migration and invasion

In the Transwell migration assay, 3 × 10^4 cells were seeded in the upper chamber of a Transwell insert within a 24-well plate, using 1% FBS medium in the upper chamber and 20% FBS medium in the lower chamber. After 24 hours, the chambers were fixed in 4% paraformaldehyde for 10 minutes, air-dried, and stained with crystal violet.For the Transwell invasion assay, 5 × 104 cells were seeded in the upper chamber, with the chambers coated with matrix gel. After 48 hours, the same steps as in the migration assay were followed.

ROS assay

The impact of reactive oxygen species (ROS) production was assessed using the ROS Assay Kit (Jiangsu KeyGEN BioTECH Corp., Ltd). After the treatment period, the cells were incubated with a 10 µM DCFH-DA probe for 1 hour at 37°C.The fluorescent signal intensity, indicating the ROS levels, was recorded using fluorescence microscopy.

JC-1

Mitochondrial membrane potential was evaluated with the JC-1 assay kit (Jiangsu KeyGEN BioTECH Corp., Ltd). SKOV3 cells underwent a 24-hour treatment with 2.5 µM Erastin.The cells were incubated with JC-1 reagent in PBS at 37°C for 15 minutes. The intensity of the mitochondrial membrane potential fluorescence signal was captured using fluorescence microscopy, with red fluorescence representing early apoptotic cells and green fluorescence indicating normal cells.

Co-immunoprecipitation(Co-IP) binding protein profiling

The supernatant from Erastin-treated SKOV3 cells was collected and divided into three groups: the Flag IP group, the IgG IP group, and the Input group.The supernatant from both the BCAT2 and IgG IP groups was incubated overnight at 4℃ in a chromatography cabinet with 5 µL of either rabbit anti-BCAT2 monoclonal antibody or anti-rabbit IgG antibody, followed by the addition of loading buffer. Protein mixtures were then subjected to identification by Shotgun LC-MS/MS mass spectrometry.

Statistical analysis

Data analysis was conducted using R software (v4.2.1) and GraphPad Prism 8.01 (La Jolla, CA, USA). Statistical inference for categorical data utilized the Chi-square test, while the t-test or Wilcoxon test was selected based on data normality and variance homogeneity. P-value < 0.05 was considered statistically significant.

Construction and validation of a risk model based on the disulfidptosis associated ferroptosis gene

To develop the disulfidptosis-associated ferroptosis risk model and evaluate its performance, 10 disulfidptosis genes closely linked to the prognosis of patients with EOC were identified using LASSO-COX analysis (Fig. 1a), and 29 ferroptosis genes with significant prognostic relevance were determined via forest plot analysis (Fig. 1b).Subsequently, six disulfidptosis-associated ferroptosis genes (ARF6, BCAT2, BRPF1, GTP2, RB1, SLC1A5) were identified through Pearson correlation analysis (Fig. 1c).Additional, ARF6, BCAT2, BRPF1, GTP2, RB1, SLC1A5 were elevated in EOC cells (SKOV3 and A2780) compared to normal epithelial ovarian cells (IOSE-80) (Supplement Fig. 1a-g). Among these, BCAT2 showed a strong correlation with the disulfidptosis gene GYS1 (***P < 0.001). For this study, BCAT2 was selected as a pivotal marker for further experimentation.

The disulfidptosis genes and ferroptosis gene were categorized into high-risk and low-risk groups. Kaplan-Meier survival curve analysis indicated that higher risk scores correlated with reduced overall survival (OS) rates in patients (Fig. 1d-e).

Validation of the risk prediction model

To establish whether the prognostic model's risk scores could serve as independent predictors of prognosis in patients with EOC, an analysis of the testing datasets was conducted, which showed that the mortality rate consistently increased with rising risk scores (Supplemtnt Fig. 1a). In the high-risk group, five genes (ARF6, BCAT2, BRPF1, RB1, SLC1A5) were upregulated, while GTP2 was downregulated, as depicted in Supplement Fig. 1b -g. These genes may thus serve as indicators of poor prognosis.

Further analysis of the prediction model in relation to clinicopathological characteristics revealed that high-risk patients had a worse prognosis for age (> 65 years or ≤ 65 years), grading (G3-G4), and staging (III-IV), while no significant differences were observed for grading (G1) and staging (I-II) (Supplement Fig. 2a-f).

Univariate and multivariate Cox proportional hazards models, both univariate and multivariate, identified age, staging, and risk score as independent prognostic factors (Fig. 2d and 2e).The ROC analysis indicated area under the curve (AUC) for the risk score in predicting OS was 0.539(Fig. 2f), with AUC values increasing over 1, 3, and 5 years, reaching a 5-year AUC of 0.637 (Fig. 2g).The C-index also suggested that the model's stability improved over time (Fig. 2h).A Nomogram was developed using risk scores and clinicopathological features to accurately estimate 1-, 3-, and 5-year survival probabilities for EOC patients. As shown in Fig. 2i, the Nomogram proved to be a reliable tool for predicting EOC prognosis. The OS Nomogram calibration curves provided a more precise evaluation of the risk model's predictive accuracy over 1, 3, and 5 years (Fig. 2j).

Identification of BCAT2 as a disulfidptosis-associated ferroptosis gene

Considering BCAT2's involvement in disulfidptosis-associated ferroptosis, SKOV3 cells were exposed to different concentrations of Erastin (0, 0.5, 1, 1.5, 2, and 2.5 µM) for 24 hours.CCK8 analysis demonstrated that increased Erastin concentrations led to reduced proliferative capacity (Fig. 3a).Additionally, higher Erastin concentrations were associated with decreased ROS levels, with 2.5 µM identified as the optimal concentration (Fig. 3b).Subsequently, BCAT2 was silenced in SKOV3 cells using two siRNAs. qRT-PCR and Western blot analyses verified that siRNAs successfully silenced BCAT2 at both mRNA and protein levels (Fig. 3c and 3d).CCK8 analysis showed that BCAT2 knockdown decreased cell viability, while subsequent Erastin (2.5 µM) treatment increased SKOV3 cell activity (Fig. 3e).Similarly, BCAT2 silencing led to reductions in both ROS levels and mitochondrial membrane potential (Fig. 3f and 3g).

Current literature(Liu X et al.2023) indicates that disulfidptosis involves disulfide stress, leading to the formation of disulfide bonds between actin cytoskeletal proteins, which causes the collapse of the F-actin network and subsequent cell death.After Erastin treatment, the cells exhibited significant changes, such as actin aggregation and cellular crumpling, compared to the untreated group.However, BCAT2 knockdown partially restored cellular morphology and reduced actin aggregation (Fig. 3h).Western blot analysis following BCAT2 knockdown indicated the downregulation of GYS1 expression at the protein level (Fig. 3i).Furthermore, under Erastin treatment, GYS1 expression further decreased after BCAT2 knockdown (Fig. 3j).These findings suggest that BCAT2 may modulate disulfidptosis through its influence on GYS1.

BCAT2 knockdown suppressed SKOV3 cell proliferation, migration, and invasion.

To further investigate the role of BCAT2 in EOC, a series of functional assays were conducted. The CCK8 assay results indicated that BCAT2 silencing markedly inhibited SKOV3 cell proliferation (Fig. 4a, P < 0.001).Additionally, BCAT2 knockdown markedly reduced the colony-forming ability of SKOV3 cells (Fig. 4b, P < 0.001).EdU staining further confirmed that BCAT2 knockdown significantly decreased SKOV3 cell proliferation (Fig. 4c, P < 0.0001).The Transwell assay demonstrated that BCAT2 silencing reduced cell migration and invasion in SKOV3 cells (Fig. 4d and 4e, P < 0.01).Flow cytometry analysis indicated that BCAT2 knockdown did not significantly impact apoptosis (Fig. 4f, P > 0.05), but it did affect cell division by inducing a G2M phase arrest (Fig. 4g, P < 0.01).In conclusion, BCAT2 knockdown impacts cell proliferation, migration, and invasion, indicating its potential as a therapeutic target for EOC.

BCAT2 affects the G2M phase and EMT-associated marker by regulating c-MYC expression

As mentioned earlier, BCAT2 knockdown impacts the G2M phase in SKOV3 cells.Western blot analysis indicated elevated CDC25C and reduced CDK1 protein levels, implying that BCAT2 disrupts cell division by arresting the G2M phase and inhibiting cell proliferation.(Fig. 5a, P < 0.01).

Epithelial-mesenchymal transition (EMT) is intricately linked to cell migration and invasion (Huang Y et al.2022) The impact of BCAT2 on these processes was examined by analyzing EMT-related markers using Western blot. As shown in Fig. 5b,E-cadherin expression increased, N-cadherin expression decreased, and the protein levels of transcription factors Snail and Slug were reduced (P < 0.01).These findings indicate that BCAT2 knockdown indeed affects EMT, thereby influencing cell migration and invasion.

The c-MYC oncogene, known to function as a transcription factor in the malignant progression of various tumors, has been shown to enhance EMT when overexpressed (Su B et al.2018). Western blot analysis revealed a significant reduction in c-MYC expression following BCAT2 knockdown (Fig. 5c). BCAT2 may regulate the G2M phase and EMT in SKOV3 cells by modulating c-MYC, thereby influencing cell proliferation, migration, and invasion (P < 0.001).

BCAT2 binds to GYS1

While it has been established that BCAT2 can regulate GYS1, the precise nature of their relationship remains unclear. To further investigate this by using Co-IP proteomics sequencing (Fig. 6a). The sequencing results demonstrated that the disulfidptosis gene GYS1 was highly expressed in the Input group but not in the IgG group, suggesting a potential binding interaction between GYS1 and BCAT2 (Fig. 6b).Further validation through Co-IP followed by Western blot analysis confirmed that BCAT2 binds to GYS1, but not to c-MYC (Fig. 6c and 6d).

EOC is the most prevalent malignancy in gynecology, yet its diagnosis and treatment continue to pose significant challenges.Ferroptosis-related genes are crucial in tumor progression, impacting systemic therapy(Zhou Q et al.2024), radiotherapy ( Lang X et al.2019), and immunotherapy(Gao W et al.2022), thereby offering a novel theoretical foundation for cancer treatment( Chen X et al.2021).Recently, disulfidptosis has also garnered significant attention, playing a pivotal role in various cancers (Zhao D et al.2023).For instance, disulfidptosis genes such as POU5F1 and CTSE serve as markers influencing prognosis, chemotherapy sensitivity, and survival in bladder cancer(Chen H et al.2023) and lung cancer (Huang J et al.2023).Bioinformatics analyses reveal that disulfidptosis-related signatures, such as MYL6, PDLIM1, ACTN4, FLNB, SLC7A11, and CD2AP, influence tumor progression and drug sensitivity in EOC(Cong Y et al.2024).Current research(Xu QT et al.2024) underscores the potential of machine learning models in investigating the role of programmed death genes in colon cancer, with N-6 methylation-associated programmed death models significantly contributing to the disease's diagnosis and management(Wu Q et al.2023).However, the role of disulfidptosis-associated ferroptosis genes in EOC has yet to be reported.In this study, Kaplan-Meier analysis indicated that a higher risk score correlates with poorer prognosis in patients with EOC.The accuracy and robustness of our prediction model were further validated by ROC curves, Nomograms, and Nomogram calibration curves, with model stability, accuracy, and sensitivity improving over time.

BCAT2, an enzyme crucial for amino acid metabolism and the catabolism of branched-chain amino acids (BCAAs) (Kang ZR et al.2024), is integral to numerous physiological and pathological processes. It combats high-fat diet-induced obesity and promotes white-fat browning by influencing the PRDM16 and PPARγ7 interaction (Ma QX et al.2022).Moreover, BCAT2 inhibits tumor growth by reducing BCAA levels, thereby suppressing tumor progression in pancreatic ductal carcinoma(Lei MZ et al.2020).In melanoma, BCAT2 affects tumor progression through the epigenetic regulation of FASN and ACLY expression (Tian Y et al.2023).Our experiments demonstrated that in EOC, BCAT2 knockdown inhibits tumor growth, migration, and invasion via the c-MYC-G2M phase/EMT pathway, indicating its pro-carcinogenic role in EOC.

Beyond its established involvement in ferroptosis (Wang K et al.2021), our research showed that, upon Erastin stimulation, BCAT2 silencing reversed the effects on growth, ROS levels, and mitochondrial membrane potential in SKOV3 cells. This suggests BCAT2 as a key regulator of ferroptosis in these cells.

Our findings revealed that BCAT2 binds to GYS1 and influences F-actin dynamics by regulating GYS1, marking the first exploration of BCAT2's role in disulfidptosis.This discovery represents a significant innovation, offering a new therapeutic target for EOC.However, the relationship between BCAT2 and GYS1 remains unexplored in existing literature.BCAT2 catalyzes the conversion of branched-chain keto acids (BCKAs), which are subsequently metabolized in the mitochondria to produce acetyl-CoA, entering the tricarboxylic acid cycle for ATP generation ( Zhou Q et al.2024).GYS1, as a glycogen synthase, is involved in glycogen synthesis, a process requiring substantial energy (Chen SL et al.2020).There may be an interaction between BCAT2, which generates energy through metabolism, and GYS1, which consumes energy for glycogen synthesis.Thus, BCAT2 may influence disulfidptosis through its interaction with GYS1.

However, the precise mechanisms by which BCAT2 and GYS1 interact and modulate the relationship between disulfidptosis and ferroptosis remain unclear and warrant further investigation.

This research is the first to identify BCAT2 as a disulfidptosis-associated ferroptosis gene that influences c-MYC, thereby promotes the malignant progression of epithelial ovarian cancer cells by interacting with GYS1 (Fig. 6e).

Co-IP Co-immunoprecipitation

EOC Epithelial ovarian cancer

qRT-PCR quantitative RT-PCR

BCAT2 Branched-chain amino acid transaminase 2

EMT epithelial-mesenchymal transformation

EdU 5-ethynyl-2’-deoxyuridine; messager RNA mRNA

NC negative control

GYS1 Glycogen synthase 1

FL Flow cytometry

Acknowledgements

The authors thank the participants.

Funding

No funding.

Competing Interests

No conflict of interest for those involved in this study

Authors' contributions

ZYT and CM performed the experiments and wrote the manuscript. CDL funded and revised the article. All authors have reviewed and endorsed the final manuscript.

Data availability

All supplementary data are represented in the article

Ethics declarations

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Consent for publication

Not applicable.

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Disulfidptosis-associated ferroptosis gene BCAT2 regulates c-MYC expression and promotes the malignant progression of epithelial ovarian cancer cells by interacting with GYS1

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Abstract

Purpose

Methods

Results

Conclusion

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Background

Methods

Data acquisition

The construction and validation of a risk model

Cell culture

Antibodies, reagents, and siRNAs

RNA extraction and qRT-PCR

Western blot

CCK8 assay

Colony-formation assay

Assay for EdU (5-ethynyl-2-deoxyuridine)

Flow cytometry (FL)

Transwell migration and invasion

ROS assay

JC-1

Co-immunoprecipitation(Co-IP) binding protein profiling

Statistical analysis

Results

Construction and validation of a risk model based on the disulfidptosis associated ferroptosis gene

Validation of the risk prediction model

Identification of BCAT2 as a disulfidptosis-associated ferroptosis gene

BCAT2 affects the G2M phase and EMT-associated marker by regulating c-MYC expression

BCAT2 binds to GYS1

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1