Integrin ß4 Regulates Cell Migration of Lung Adenocarcinoma Through FAK Signaling.

The role of the integrin family in malignancy has received increasing attention. Many studies have confirmed that ITGB4 could activate multiple signal pathways and promote cell migration in various cancers. However, the regulatory role of integrin ß4 (ITGB4) in lung adenocarcinoma (LUAD) is still unclear. Examination of the expression or survival analysis of ITGB4 in cells, pathological samples, and bioinformatics lung adenocarcinoma databases showed ITGB4 was highly expressed in LUAD and significantly associated with poor prognosis. Small interfering RNA and plasmids were performed to investigate the effect of changes in ITGB4 expression on lung adenocarcinoma. Focal adhesion kinase (FAK) inhibitor defactinib was used to further explore the molecular mechanism of ITGB4. The results showed depletion of ITGB4 inhibited migration and activation of FAK signaling pathways in lung adenocarcinoma cells. Moreover, increased ITGB4 expression activated FAK signaling and promoted cell migration, which can be reversed by defactinib. In addition, ITGB4 could interact with FAK in lung adenocarcinoma cells. ITGB4 may promote cell migration of lung adenocarcinoma through FAK signaling pathway and has the potential to be a biomarker for lung adenocarcinoma.

Corrigendum: Machine learning prediction model for post- hepatectomy liver failure in hepatocellular carcinoma: a multicenter study.

[This corrects the article DOI: 10.3389/fonc.2022.986867.].

A novel nomogram predicting overt hepatic encephalopathy after transjugular intrahepatic portosystemic shunt in portal hypertension patients.

We aim to develop a nomogram to predict overt hepatic encephalopathy (OHE) after transjugular intrahepatic portosystemic shunt (TIPS) in patients with portal hypertension, according to demographic/clinical indicators such as age, creatinine, blood ammonia, indocyanine green retention rate at 15 min (ICG-R15) and percentage of Portal pressure gradient (PPG) decline. In this retrospective study, 296 patients with portal hypertension who received elective TIPS in Beijing Shijitan Hospital from June 2018 to June 2020 were included. These patients were randomly divided into a training cohort (n = 207) and a validation cohort (n = 89). According to the occurrence of OHE, patients were assigned to OHE group and non-OHE group. Both univariate and multivariate analyses were performed to determine independent variables for predicting OHE after TIPS. Accordingly, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to compare the accuracy and superiority of a novel model with conventional Child-Pugh and MELD scoring model. Age (OR 1.036, 95% CI 1.002-1.070, p = 0.037), Creatinine (OR 1.011, 95% CI 1.003-1.019, p = 0.009), Blood ammonia (OR 1.025, 95% CI 1.006-1.044, p = 0.011), ICG-R15 (OR 1.030, 95% CI 1.009-1.052, p = 0.004) and Percentage decline in PPG (OR 1.068, 95% CI 1.029-1.109, p = 0.001) were independent risk factors for OHE after TIPS using multifactorial analysis. A nomogram was constructed using a well-fit calibration curve for each of these five covariates. When compared to Child-Pugh and MELD score, this new nomogram has a better predictive value (C-index = 0.828, 95% CI 0.761-0.896). Consistently, this finding was reproduceable in validation cohort and confirmed with DCA. A unique nomogram was developed to predict OHE after TIPS in patients with PHT, with a high prediction sensitivity and specificity performance than commonly applied scoring systems.

Association between the initial dose urate-lowering drugs and gout flares in adult males with gout.

OBJECTIVES: Frequent gout attacks in the initial introduction of urate-lowering therapy (ULT) are significant causes of poor drug adherence and ULT discontinuation. Initial low-dose urate-lowering drugs may be effective in reducing gout flares, however, robust evidence is sparse. The aim of this study was therefore to assess the association of initial dose urate-lowering drugs with gout flares in adult males with gout during the initial introduction of ULT. METHODS: This cohort study obtained data on consecutive gout patients from a single-center gout cohort study from August 2017 to October 2020. A standard questionnaire was applied to collect demographic and clinical information, and biochemical parameters were tested on the same day. The primary end point was to estimate the association of initial dose febuxostat with gout flares, using cox hazard models with inverse probability of treatment weighting (IPTW). RESULTS: A total of 582 gout patients were included in this study. During 6-week follow-up, 71 (12.2%) patients suffered gout flares. In the main analysis using cox hazard models with IPTW, compared with colchicine prophylaxis, initial low-dose febuxostat alone had no statistical significance with the increased risk of gout flares [hazard ratio (HR), 1.26; 95% CI, 0.58-2.72], while initial high-dose febuxostat was associated with an increased risk of gout flares (HR, 3.08; 95% CI, 1.34-7.07). CONCLUSIONS: This observational study demonstrated that initial low-dose febuxostat was equally effective in preventing gout flares as colchicine prophylaxis, while initial high-dose febuxostat alone was associated with an increased risk of gout flares.

Genomic alterations of cerebrospinal fluid cell-free DNA in leptomeningeal metastases of gastric cancer.

BACKGROUND: Leptomeningeal metastases (LM) were rare in gastric cancer (GC), and GC patients with LM (GCLM) generally suffer from poor prognosis. Nevertheless, the clinical utility of cerebrospinal fluid (CSF) circulating tumor DNA (ctDNA) was underinvestigated in GCLM. METHODS: We retrospectively studied 15 GCLM patients, and all patients had paired primary tumor tissue samples and post-LM CSF samples while 5 patients also had post-LM plasma samples. All samples were analyzed using next-generation sequencing (NGS), and the molecular and clinical features were correlated with clinical outcomes. RESULTS: CSF had higher mutation allele frequency (P = 0.015), more somatic mutations (P = 0.032), and more copy-number variations (P < 0.001) than tumor or plasma samples. Multiple genetic alterations and aberrant signal pathways were enriched in post-LM CSF, including CCNE1 amplification and cell cycle-related genes, and CCNE1 amplification was significantly associated with patients' overall survival (P = 0.0062). More potential LM progression-related markers were detected in CSF samples than in tumor samples, including PREX2 mutation (P = 0.014), IGF1R mutation (P = 0.034), AR mutation (P = 0.038), SMARCB1 deletion (P < 0.001), SMAD4 deletion (P = 0.0034), and TGF-beta pathway aberration (P = 0.0038). Additionally, improvement in intracranial pressure (P < 0.001), improvement in CSF cytology (P = 0.0038), and relatively low levels of CSF ctDNA (P = 0.0098) were significantly associated with better PFS. Lastly, we reported a GCLM case whose CSF ctDNA dynamic changes were well correlated with his clinical assessment. CONCLUSIONS: CSF ctDNA could more sensitively detect molecular markers and metastasis-related mechanisms than tumor tissues in GCLM patients, and our study sheds light on utilizing CSF ctDNA in prognostic estimation and clinical assessment in GCLM.

Efficacy and safety of LY01005 versus goserelin implant in Chinese patients with prostate cancer: A multicenter, randomized, open-label, phase III, non-inferiority trial.

BACKGROUND: LY01005 (Goserelin acetate sustained-release microsphere injection) is a modified gonadotropin-releasing hormone (GnRH) agonist injected monthly. This phase III trial study aimed to evaluated the efficacy and safety of LY01005 in Chinese patients with prostate cancer. METHODS: We conducted a randomized controlled, open-label, non-inferiority trial across 49 sites in China. This study included 290 patients with prostate cancer who received either LY01005 or goserelin implants every 28 days for three injections. The primary efficacy endpoints were the percentage of patients with testosterone suppression ≤50 ng/dL at day 29 and the cumulative probability of testosterone ≤50 ng/dL from day 29 to 85. Non-inferiority was prespecified at a margin of -10%. Secondary endpoints included significant castration (≤20 ng/dL), testosterone surge within 72 h following repeated dosing, and changes in luteinizing hormone, follicle-stimulating hormone, and prostate specific antigen levels. RESULTS: On day 29, in the LY01005 and goserelin implant groups, testosterone concentrations fell below medical-castration levels in 99.3% (142/143) and 100% (140/140) of patients, respectively, with a difference of -0.7% (95% confidence interval [CI], -3.9% to 2.0%) between the two groups. The cumulative probabilities of maintaining castration from days 29 to 85 were 99.3% and 97.8%, respectively, with a between-group difference of 1.5% (95% CI, -1.3% to 4.4%). Both results met the criterion for non-inferiority. Secondary endpoints were similar between groups. Both treatments were well-tolerated. LY01005 was associated with fewer injection-site reactions than the goserelin implant (0% vs . 1.4% [2/145]). CONCLUSION: LY01005 is as effective as goserelin implants in reducing testosterone to castration levels, with a similar safety profile. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04563936.

CD4+ conventional T cells-related genes signature is a prognostic indicator for ovarian cancer.

Introduction: It is believed that ovarian cancer (OC) is the most deadly form of gynecological cancer despite its infrequent occurrence, which makes it one of the most salient public health concerns. Clinical and preclinical studies have revealed that intratumoral CD4+ T cells possess cytotoxic capabilities and were capable of directly killing cancer cells. This study aimed to identify the CD4+ conventional T cells-related genes (CD4TGs) with respect to the prognosis in OC. Methods: We obtained the transcriptome and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD4TGs were first identified from single-cell datasets, then univariate Cox regression was used to screen prognosis-related genes, LASSO was conducted to remove genes with coefficient zero, and multivariate Cox regression was used to calculate riskscore and to construct the CD4TGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), decision curve analysis (DCA), nomogram, and calibration were made to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in risk groups were conducted to explore the tightly correlated pathways with the risk group. The role of riskscore has been further explored in the tumor microenvironment (TME), immunotherapy, and chemotherapy. A risk signature with 11 CD4TGs in OC was finally established in the TCGA database and furtherly validated in several GEO cohorts. Results: High riskscore was significantly associated with a poorer prognosis and proven to be an independent prognostic biomarker by multivariate Cox regression. The 1-, 3-, and 5-year ROC values, DCA curve, nomogram, and calibration results confirmed the excellent prediction power of this model. Compared with the reported risk models, our model showed better performance. The patients were grouped into high-risk and low-risk subgroups according to the riskscore by the median value. The low-risk group patients tended to exhibit a higher immune infiltration, immune-related gene expression and were more sensitive to immunotherapy and chemotherapy. Discussion: Collectively, our findings of the prognostic value of CD4TGs in prognosis and immune response, provided valuable insights into the molecular mechanisms and clinical management of OC.

A Signature Constructed Based on the Integrin Family Predicts Prognosis and Correlates with the Tumor Microenvironment of Patients with Lung Adenocarcinoma.

As an important element in regulating the tumor microenvironment (TME), integrin plays a key role in tumor progression. This study aimed to establish prognostic signatures to predict the overall survival and identify the immune landscape of patients with lung adenocarcinoma based on integrins. The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus datasets were used to obtain information on mRNA levels and clinical factors (GSE72094). The least absolute shrinkage and selection operator (LASSO) model was used to create a prediction model that included six integrin genes. The nomogram, risk score, and time-dependent receiver operating characteristic analysis all revealed that the signatures had a good prognostic value. The gene signatures may be linked to carcinogenesis and TME, according to a gene set enrichment analysis. The immunological and stromal scores were computed using the ESTIMATE algorithm, and the data revealed, the low-risk group had a higher score. We discovered that the B lymphocytes, plasma, CD4+ T, dendritic, and mast cells were much higher in the group with low-risk using the CiberSort. Inflammatory processes and several HLA family genes were upregulated in the low-risk group. The low-risk group with a better prognosis is more sensitive to immune checkpoint inhibitor medication, according to immunophenoscore (IPS) research. We found that the patients in the high-risk group were more susceptible to chemotherapy than other group patients, according to the prophetic algorithm. The gene signatures could accurately predict the prognosis, identify the immune status of patients with lung adenocarcinoma, and provide guidance for therapy.

A CT Radiomics-Based Risk Score for Preoperative Estimation of Intraoperative Superior Mesenteric-Portal Vein Involvement in Pancreatic Ductal Adenocarcinoma.

BACKGROUND: The current radiologic criteria for assessing intraoperative superior mesenteric-portal vein (SMPV) involvement (i.e., presence of tumor-SMPV contact >180° or venous deformity) in pancreatic ductal adenocarcinoma (PDAC) are highly specific but insufficiently sensitive. Therefore, development of improved markers for a more accurate prediction is essential. This study aimed to develop a risk score model to estimate SMPV involvement in PDAC using radiomics analysis of computed tomography (CT) images. METHODS: Data from two institution-based cohorts of PDAC patients undergoing preoperative CT scans were used to develop (n = 173) and validate (n = 156) a radiomics-based risk score of SMPV involvement using clinical and imaging variables. A radiomics signature was developed based on 2436 radiomic features extracted from the semi-automatic three-dimensional segmentation ofn CT images. The SMPV involvement risk score was built using multivariate logistic regression and compared with the current radiologic criteria. RESULTS: The study surgically identified SMPV involvement in 59 (34.1%) and 57(36.5 %) patients with PDAC in the development and validation cohorts, respectively. A 12-feature-based radiomics signature achieved areas under receiver operating characteristics curves (AUCs) of 0.89 or greater for estimating SMPV involvement. Multivariate regression identified the radiomics signature and SMPV deformity as associated with SMPV involvement. The risk score model had significantly improved AUC (0.928 vs. 0.768; P < 0.001) and sensitivity (84.2% vs. 66.7%; P = 0.025) in the radiologic evaluation. CONCLUSIONS: The novel risk score in this study, combining radiomics signature and venous deformity, demonstrated promising performance for estimating SMPV involvement preoperatively for patients with PDAC.

Machine learning prediction model for post- hepatectomy liver failure in hepatocellular carcinoma: A multicenter study.

Introduction: Post-hepatectomy liver failure (PHLF) is one of the most serious complications and causes of death in patients with hepatocellular carcinoma (HCC) after hepatectomy. This study aimed to develop a novel machine learning (ML) model based on the light gradient boosting machines (LightGBM) algorithm for predicting PHLF. Methods: A total of 875 patients with HCC who underwent hepatectomy were randomized into a training cohort (n=612), a validation cohort (n=88), and a testing cohort (n=175). Shapley additive explanation (SHAP) was performed to determine the importance of individual variables. By combining these independent risk factors, an ML model for predicting PHLF was established. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, and decision curve analyses (DCA) were used to evaluate the accuracy of the ML model and compare it to that of other noninvasive models. Results: The AUCs of the ML model for predicting PHLF in the training cohort, validation cohort, and testing cohort were 0.944, 0.870, and 0.822, respectively. The ML model had a higher AUC for predicting PHLF than did other non-invasive models. The ML model for predicting PHLF was found to be more valuable than other noninvasive models. Conclusion: A novel ML model for the prediction of PHLF using common clinical parameters was constructed and validated. The novel ML model performed better than did existing noninvasive models for the prediction of PHLF.

Deciphering the expression patterns of homologous recombination-related lncRNAs identifies new molecular subtypes and emerging therapeutic opportunities in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is the leading killer among women with gynecologic malignancies. Homologous recombination deficiency (HRD) has attracted increasing attention due to its significant implication in the prediction of prognosis and response to treatments. In addition to the germline and somatic mutations of homologous recombination (HR) repair genes, to widely and deeply understand the molecular characteristics of HRD, we sought to screen the long non-coding RNAs (lncRNAs) with regard to HR repair genes and to establish a prognostic risk model for EOC. Herein, we retrieved the transcriptome data from the Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA) databases. HR-related lncRNAs (HRRlncRNAs) associated with prognosis were identified by co-expression and univariate Cox regression analyses. The least absolute shrinkage and selection operator (LASSO) and multivariate stepwise Cox regression were performed to construct an HRRlncRNA risk model containing AC138904.1, AP001001.1, AL603832.1, AC138932.1, and AC040169.1. Next, Kaplan-Meier analysis, time-dependent receiver operating characteristics (ROC), nomogram, calibration, and DCA curves were made to verify and evaluate the model. Gene set enrichment analysis (GSEA), immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) in the risk groups were also analyzed. The calibration plots showed a good concordance with the prognosis prediction. ROCs of 1-, 3-, and 5-year survival confirmed the well-predictive efficacy of this model in EOC. The risk score was used to divide the patients into high-risk and low-risk subgroups. The low-risk group patients tended to exhibit a lower immune infiltration status and a higher HRD score. Furthermore, consensus clustering analysis was employed to divide patients with EOC into three clusters based on the expression of the five HRRlncRNAs, which exhibited a significant difference in checkpoints' expression levels and the tumor microenvironment (TME) status. Taken together, the results of this project supported that the five HRRlncRNA models might function as a biomarker and prognostic indicator with respect to predicting the PARP inhibitor and immune treatment in EOC.

A Novel Nomogram for Prediction of Post-Hepatectomy Liver Failure in Patients with Resectable Hepatocellular Carcinoma: A Multicenter Study.

Objective: To develop a nomogram for predicting post-hepatectomy liver failure (PHLF) in patients with resectable hepatocellular carcinoma (HCC) based on portal hypertension, the extent of resection, ALT, total bilirubin, and platelet count. Methods: Patients with HCC hospitalized from January 2015 to December 2020 were included in a retrospective cohort study. 595 HCC patients were divided into a training cohort (n=416) and a validation cohort (n=179) by random sampling. Univariate and multivariable analyses were performed to identify the independent variables to predict PHLF. The nomogram models for predicting the overall risk of PHLF and the risk of PHLF B+C were constructed based on the independent variables. Comparisons were made by using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) with traditional models, such as FIB-4 score, APRI score, CP class (Child-Pugh), MELD score (model of end-stage liver disease), and ALBI score (albumin-bilirubin) to analyze the accuracy and superiority of the nomogram. Results: We discovered that portal hypertension (yes vs no) (OR=1.677,95% CI:1.817-4.083, p=0.002), the extent of liver resection (OR=1.872,95% CI:3.937-47.096, p=0.001), ALT (OR=1.003,95% CI:1.003-1.016, P=0.003), total bilirubin (OR=1.036,95% CI:1.031-1.184, p=0.005), and platelet count (OR= 1.004, 95% CI:0.982-0.998, p=0.020) were independent risk factors for PHLF using multifactorial analysis. The nomogram models were constructed using well-fit calibration curves for each of these five covariates. When compared to the FIB4, ALBI, MELD, and CP score, our nomogram models have a better predictive value for predicting the overall risk of PHLF or the risk of PHLF B+C. The validation cohort's results were consistent. DCA also confirmed the conclusion. Conclusion: Our models, in the form of static nomogram or web application, were developed to predict PHLF overall risk and PHLF B+C risk in patients with HCC, with a high prediction sensitivity and specificity performance than other commonly used scoring systems.

Development and validation of AKI prediction model in postoperative critically ill patients: a multicenter cohort study.

BACKGROUND: Acute kidney injury (AKI) is a common complication, especially among postoperative critically ill patients. Early identification of AKI is essential for reducing mortality. METHODS: Multicenter data were used to develop an AKI prediction model for critically ill postoperative patients. A total of 1731 patients admitted to intensive care units (ICUs) were divided into a development set (n=1196) and a validation set (n=535) according to the principle of 7:3 randomization. Multivariate logistic regression analysis was performed on the predictors identified by univariate analysis, and a nomogram was created based on the predictors. The area under the receiver operating characteristic curve (AUROC) was used to assess the discrimination of the model. Calibration curves were generated, and the Hosmer-Lemeshow (HL) goodness of fit test was carried out. Decision curve analysis (DCA) was performed to assess the net clinical benefit. RESULTS: The final model included 7 predictors: age, emergency surgery, abnormal basal creatinine level (BCr), chronic kidney disease (CKD), use of nephrotoxic drugs, diuretic use, and the Sequential Organ Failure Assessment (SOFA) score. A nomogram was drawn based on the predictors. The AUROC of the model in the development set was 0.725 (95% confidence interval (CI): 0.696-0.754). In the validation set, the AUROC was 0.706 (95% CI: 0.656-0.744). The model showed good discrimination (>70%) in both sets, and the HL test indicated that the model fit was good (P>0.05). DCA showed that our model is clinically useful. CONCLUSION: The novel prediction model can be used to identify high-risk postoperative patients and provide a scientific and effective basis for clinicians to identify AKI early with a nomogram.

Noninvasively Assessed Portal Hypertension Grade Predicts Post-Hepatectomy Liver Failure in Patients With HepatocellCarcinoma: A Multicenter Study.

Purpose: To determine the predictive value of portal hypertension (PH) for the development of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). Patients and methods: This study enrolled a total of 659 patients with HCC that received hepatectomy as a first-line therapy. PH was classified as grade 0, 1, and 2 according to whether the indirect criteria for PH were met: 1) patients had obvious varicose veins and 2) splenomegaly was present and platelet count < 100 × 109/L. The effects of each variable on the occurrence of PHLF were assessed using univariate and multivariate analyses. Results: PH grade 2 (odds ratio [OR] = 2.222, p = 0.011), higher age (OR = 1.031, p = 0.003), hepatitis C infection (OR = 3.711, p = 0.012), open surgery (OR = 2.336, p < 0.001), portal flow blockage (OR = 1.626, p = 0.023), major hepatectomy (OR = 2.919, p = 0.001), hyperbilirubinemia (≥ 17.2 µmol/L, OR = 2.113, p = 0.002), and high levels of alpha-fetoprotein (> 400n g/ml, OR = 1.799, p = 0.008) were significantly associated with PHLF occurrence. We performed a subgroup analysis of liver resection and found that the extent of liver resection and PH grade were good at distinguishing patients at high risk for PHLF, and we developed an easy-to-view roadmap. Conclusion: PH is significantly related to the occurrence of PHLF in patients who underwent hepatectomy. Noninvasively assessing PH grade can predict PHLF risk.

Safety and immunogenicity of COVID-19 vaccination in patients with hepatocellular carcinoma (CHESS-NMCID 2101): A multicenter prospective study.

Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccinations in hepatocellular carcinoma (HCC) patients are limited. In this multicenter prospective study, HCC patients received two doses of inactivated whole-virion COVID-19 vaccines. The safety and neutralizing antibody were monitored. Totally, 74 patients were enrolled from 10 centers in China, and 37 (50.0%), 25 (33.8%), and 12 (16.2%) received the CoronaVac, BBIBP-CorV, and WIBP-CorV, respectively. The vaccines were well tolerated, where pain at the injection site (6.8% [5/74]) and anorexia (2.7% [2/74]) were the most frequent local and systemic adverse events. The median level of neutralizing antibody was 13.5 (interquartile range [IQR]: 6.9-23.2) AU/ml at 45 (IQR: 19-72) days after the second dose of vaccinations, and 60.8% (45/74) of patients had positive neutralizing antibody. Additionally, lower γ-glutamyl transpeptidase level was related to positive neutralizing antibody (odds ratio = 1.022 [1.003-1.049], p = 0.049). In conclusion, this study found that inactivated COVID-19 vaccinations are safe and the immunogenicity is acceptable or hyporesponsive in patients with HCC. Given that the potential benefits may outweigh the risks and the continuing emergences of novel severe acute respiratory syndrome coronavirus 2 variants, we suggest HCC patients to be vaccinated against COVID-19. Future validation studies are warranted.

Deferasirox shows inhibition activity against cervical cancer in vitro and in vivo.

OBJECTIVE: Iron depletion may be a novel therapeutic strategy for cancer. This study aimed to assess the inhibition effects of deferasirox (DFX), an oral iron chelator, on cervical cancer. METHODS: In this study, we performed immunohistochemical analysis, enzyme-linked immunoassay, cell viability and invasive ability assay, cell cycle and apoptosis analysis, protein expression investigation, molecular mechanism investigation, and in vivo murine xenograft model to evaluate the impact of DFX on cervical cancer. RESULTS: The cervical cancer cell lines viability decreased and cell apoptosis was induced after DFX incubation. Additionally, DFX promoted cell cycle arrest by regulating the expression of cell cycle regulators cyclin D1, cyclin E and proliferating cell nuclear antigen (PCNA) in cervical cancer cell lines. DFX also decreased cell invasion by upregulating the expression of NDRG1 and downregulating c-Myc. The activation of Akt and the MEK/ERK signaling pathway was inhibited by DFX. DFX also significantly suppressed xenograft tumor growth, decreased the levels of ferritin in serum and tumor tissue, reduced iron deposits and reactive oxygen species (ROS) levels in xenografts of DFX-treated group compared with the control group, with no serious side effects. CONCLUSION: Present study demonstrated the inhibitory effect of DFX against cervical cancer, and provided a potential therapeutic agent for cervical cancer.