Objective The aim of this study was to investigate whether downregulation of FK506 binding protein 4(FKBP4)could inhibit the malignant progression of non-small cell lung cancer(NSCLC)by blocking the PI3K/Akt/mTOR signaling pathway.Methods NSCLC A549,H1975,H358 and PC-9 cell lines,as well as human bronchial epithelial cells(HBE)were routinely cul-tured.The expression of FKBP4 in these cells was detected by qRT-PCR,and NSCLC cell lines with the most significant different ex-pression of FKBP4 compared with HBE cells was screened.FKBP4 siRNA and NC siRNA were transfected into A549 cells,which were divided into the si-FKBP4 group and NC group.CCK-8 assay was used to detect the proliferative ability of si-FKBP4 group and NC group,flow cytometry was used to detect the apoptosis rate,scratch healing assay was used to detect the migration ability,Transwell assay was used to detect the invasion ability,and Western blot was used to detect the total and phosphorylation protein expression of PI3K and its downstream effectors Akt and mTOR.Results The expression of FKBP4 in A549 cells,H1975 cells,H358 cells and PC-9 cells were significantly higher than those in HBE cells(P<0.05),and its expression in A549 cells was the highest(P<0.001).Downregulation of FKBP4 could inhibit the proliferation,invasion and migration of A549 cells and promote the apoptosis of A549 cells(P<0.001).In addition,downregulation of FKBP4 also could inhibit the phosphorylation of PI3K,Akt and mTOR,resulting in bloc-king the PI3K/Akt/mTOR signaling pathway.Conclusion Downregulation of FKBP4 can inhibit the proliferation,invasion and mi-gration of NSCLC cells by blocking the PI3K/Akt/mTOR signaling pathway,and promote the apoptosis of NSCLC cells.

Objective Mendelian randomization was used to analyze the causal association between 20 serum metabolites and the risk of ovarian cancer.Methods The gene variations of 20 serum metabolites were obtained from the MRC IEU database as tool variables reflecting exposure levels,while gene variations of ovarian cancer patients were used as instrumental variables reflecting outcome levels.The ovarian cancer dataset ieu-a-1120 included 66,450 European women samples(of which 25,509 were ovarian cancer),and the dataset ieu-a-1228 included 54,990 European women samples(of which 14,049 were ovarian cancer).Two-sample two-way Mendelian randomization analysis was performed on both datasets.This study used inverse variance-weighted(IVW),weigh-ted median method,MR-Egger regression,and combined various analysis methods such as simple mode,and weighted mode.The caus-al effects of 20 metabolites and the risk of ovarian cancer were analyzed.Cochran's Q test was used to perform sensitivity analysis and to verify the reliability of the results.MR Egger intercept test was used to assess the horizontal pleiotropy of tool variables,and use the leave-one-out method to assess whether there were single nucleotide polymorphisms(SNPs)in the results that might have a potential impact on the incidence of ovarian cancer.Finally,the effects of uridine on ovarian cancer cells were verified through cell proliferation and apoptosis experiments.Results The results showed a negative correlation between uridine and the occurrence of ovarian cancer,with statistically significance(ieu-a-1228:P=0.025;ieu-a-1120:P=0.017).MR-Egger regression analysis confirmed the sensitiv-ity and robustness of the analysis results.The CCK8 assay confirmed that uridine inhibited the proliferation of ovarian cancer cells in a concentration-dependent manner,and uridine at a concentration of 10 mM significantly promoted apoptosis in SKOV3 cells(P<0.001)and A2780 cells(P<0.001).Flow cytometry analysis showed that after treatment for 24 hours,uridine at a concentration of 10 mM had the strongest pro-apoptotic effect on ovarian cancer cells,which was significant in SKOV3 and A2780 cells(P<0.05 and P<0.001,respectively).Conclusion Uridine is negatively correlated with the risk of ovarian cancer,which lays a theoretical founda-tion for further understanding the pathogenesis of ovarian cancer and optimizing clinical treatment strategies.

Objective The aim of this study was to analyze the relationship between polymorphism of epidermal growth factor(EGF)gene and sensitivity of concurrent chemoradiotherapy(CCRT)regimen containing cisplatin in esophageal cancer patients.Methods A prospective cohort study was conducted in 112 esophageal cancer patients who underwent CCRT treatment in Tianchang City People's Hospital and Haimen People's Hospital from March 2020 to February 2024 as the research subjects.All patients under-went EGF gene polymorphism detection and pathological features were analyzed at admission.The genotypes and alleles of EGF G-61A locus were counted.All patients were evaluated for the effect at 4 cycles of CCRT treatment.According to the pathological evalua-tion criteria established by Becker et al.the patients were divided into the CCRT-tolerant group and CCRT-sensitive group.The EGF G-61A locus gene polymorphism and clinicopathological features were compared between the two groups,and the relationship between EGF G-61A locus polymorphism and CCRT sensitivity of esophageal cancer was analyzed.Results A total of 112 patients with e-sophageal cancer were enrolled in this study,of which 106 patients were followed up.The results of EGF G-61A locus genotype detec-tion showed that among the 106 patients,33 cases had GG genotype,45 cases had GA genotype,and 28 cases had AA genotype.The results of allele detection showed that 73 cases had G allele and 33 cases had A allele.The results of CCRT treatment showed that 28 patients were tolerant to CCRT treatment and 78 patients were sensitive to CCRT treatment.The proportion of TNM stage Ⅳa,poor dif-ferentiation and CCRT tolerance in patients with EGF G-61A GG genotype was higher than that in patients with GA and AA geno-types.The proportion of TNM stageⅣa,low differentiation and CCRT tolerance in patients with EGF G-61A G allele was higher than that in patients with A allele.The difference was statistically significant(P<0.05).The proportion of TNM stage Ⅳa and low differen-tiation in the CCRT tolerance group was higher than that in the CCRT sensitive group,and the proportion of EGF G-61A GG genotype and G allele was higher than that in the CCRT treatment sensitive group,with significant differences(P<0.05).Logistic regression a-nalysis showed that TNM stage Ⅳa,poor differentiation,EGF G-61A GG genotype,and G allele were risk factors for CCRT tolerance in esophageal cancer(P<0.05).Conclusion The sensitivity of patients with esophageal cancer to CCRT regimen containing cisplatin is related to EGF G-61A gene polymorphism,and the EGF G-61A GG genotype and G allele may increase the risk of CCRT toler-ance.

Objective This study aimed to construct a risk scoring model based on DNA methylation featuresof ferroptosis-related gene,and systematically evaluate its predictive value for the prognosis and immunotherapy response of patients with colon canc-er.Methods Transcriptomic,DNA methylation,and clinical data of colon cancer patients were obtained from the Cancer Genome At-las(TCGA)and Gene Expression Omnibus(GEO)databases.Ferroptosis-related genes were identified from the FerrDb database.Fer-roptosis scores(FS)for each patient were calculated using the single-sample gene set enrichment analysis(ssGSEA)method,and con-struct a risk scoring model by combining differential methylation CpG sites with Cox regression analysis.The prognostic performance of the model was evaluated using receiver operating characteristic(ROC)curves,a nomogram,and decision curve analysis.The multiple algorithms were used to analyze the relationship between colon cancer models and immune cell infiltration,immunotherapy response,and chemotherapy sensitivity.Results A total of 49 ferroptosis-related genes significantly associated with overall survival(OS)were identified for calculating FS.The OS of colon cancer patients in the high-FS group was significantly shorter than that in the low-FS group(P=0.0075).The constructed DNA methylation risk score models included key CpG sites,and the ROC curves and multivariate Cox regression analysis at 1-,3-,and 5-years overall survival rate in the TCGA cohort and the GSE17536 validation cohort showed that the model was an independent prognostic factor for colon cancer patients.The low-risk group had higher immune scores and infil-tration levels of B cells and dendritic cells,while the high-risk group had a higher abundance of fibroblasts.Patients in the high-risk group showed upregulation of PD-L1 expression and higher immune phenotype scores.In addition,the model could also predict the sensitivity differences of commonly used chemotherapeutic drugs such as doxorubicin,gemcitabine,and paclitaxel.Conclusion The risk scoring model established using DNA methylation features of ferroptosis-related gene can be used to predict the prognosis of colon cancer patients and provide a new biomarker for achieving precision treatment.

Oral cancer is one of the most common malignant tumors in the head and neck,with approximately 90%of oral cancer being squamous cell carcinoma.Oral squamous cell carcinoma(OSCC)has a high degree of malignancy and a poor prognosis,posing a serious threat human health.The occurrence and development of OSCC are relatively complex,influenced and regulated by multiple factors and levels,and the molecular mechanisms is currently not fully understood.Long non-coding RNA(lncRNA)can exert various biological functions by regulating gene expression and function at the transcriptional,translational,and post-translational lev-els.The occurrence and development of OSCC involve the abnormal expression of lncRNA.Therefore,this article reviews the relevant research on the function and molecular mechanisms of lncRNA in OSCC,in order to provide a reference for future studies.

Ferroptosis is a non-apoptotic programmed cell death driven by iron ion-mediated lipid peroxidation,which is closely related to the occurrence and development of various tumors.In recent years,many studies have shown that non-coding RNA(ncRNA)can affect tumor drug resistance by regulating the ferroptosis pathway.This article summarizes the molecular mechanisms of ncRNAs regulating sorafenib resistance in hepatocellular carcinoma(HCC)through ferroptosis,with a focus on the regulatory roles of different ncRNA subtypes such as microRNA(miRNA),long noncoding RNA(lncRNA),and circular RNA(circRNA).The article not only contributes to a deeper analysis of the key molecular mechanisms by which ncRNA mediate sorafenib resistance in HCC through ferroptosis pathways,but also provides a theoretical basis for exploring novel diagnostic biomarkers and therapeutic targets for HCC in the future.

As a common malignant tumor,breast cancer is the main cause of cancer death in women.Radiotherapy(RT)is one of its main treatment methods for breast cancer.RT resistance refers to the resistance of tumor cells and tissues to the biological effects of RT.The occurrence of RT resistance is closely related to the recurrence,metastasis and prognosis deterioration of breast cancer.In recent years,RT resistance of breast cancer has become a core issue in the field of RT research.The aim of this article is to review the potential mechanisms,influencing factors and corresponding countermeasures of breast cancer RT resistance,and to provide new ideas for the implementating personalized precision medicine in clinical practice.

Objective The aim of this study was to explore the effects of changes in the estrogen receptor alpha 36(ER-α36)expression on the proliferation and membrane-initiated estrogen signaling in glioblastoma U251 cells.Methods The expression and localization of ER-α36 and EGFR glioblastoma U87 cells and U251 cells were determined by immunofluorescence,qRT-PCR and Western blot.The effect of upregulating ER-α 36 on U251 cell proliferation and estrogen signaling pathway activity by low con-centrations of 100 pmol/L icariin isomer(SNG162)was detected by MTT assay and Western blot.Results ER-α36 and EGFR were co-expressed in the cell membrane of glioblastoma.Compared with DMSO(control group),the expression ER-α36(P<0.01)and EG-FR increased in U251 cells treated with SNG162(P<0.05);Further experments also found that low concentrations of SNG162 in-creased the expression of cycle related proteins-cyclin D1,cyclin B,cyclin E and CDK4(P<0.01),and enhanced the proliferative a-bility of U251 cells(P<0.05).Conclusion The low concentration of SNG162 upregulates the expression of ER-α36,activates the estrogen-mediated ERK1/2 MAPK,p38 MAPK,and EGFR/Src signaling pathways,promotes glioblastoma proliferation,and activates the membrane initialized estrogen signaling pathway.

Objective The aim of this study was to reveal the association characteristics between cancer and depression u-sing the data from community-based multi-morbidity study in rural China(COMMON),and provide a scientific basis for early pre-vention and intervention of depression in cancer patients.Methods We collected questionnaire responses,physical examination re-cords,health insurance data,and electronic medical records from both cancer and non-cancer participants.Using propensity score matching at a 1∶4 ratio,we balanced baseline characteristics between the cancer and control groups.We then compared the preva-lence of depression between these groups,as well as across subgroups stratified by age,sex,income,and other factors.The association between cancer and depression risk was assessed using univariate and multivariate logistic regression.Finally,we conducted sensitivity analyses by restricting the regression models to participants with mild-to-severe depression.Results After matching the baseline characteristics,a total of 206 cancer patients and 824 controls were included in the study,and all baseline characteristics between the two groups.Among all individuals,women,participants under 60 years old and those from low-income families(10,000-34,999 Yuan per year),the cancer group had a higher prevalence of depression than the non-cancer group(P<0.05),no difference was found in other subgroup(P>0.05).The results of multivariate logistic regression analysis showed that cancer was an independent risk factor for depression,and the risk of depression in cancer patients was 2.38 times that of participants without cancer(95%CI:1.44-3.89,P<0.001).The analysis results of different gender,age,and family income subgroups showed that the effect of cancer on the risk of de-pression was different among subgroups(P<0.05).Conclusions Cancer is an independent risk factor for depression.Therefore,the assessment and intervention of mental health should be paid attention during the treatment of cancer patients.It is of great significance to screen for depression in cancer patients and intervene in them to improve the life quality of patients.In addition,paying attention to high-risk groups can help to implement targeted prevention and intervention and improve their mental health.

Objective The aim of this study was to screen diagnostic and prognostic markers for esophageal cancer,explore their potential mechanisms of action,and provide new insights for early diagnosis and precision treatment of esophageal cancer.Meth-ods The protein-coding genes in transcriptome sequencing data(RNA-seq)of esophageal cancer from The Cancer Genome Atlas(TCGA)were extracted and analyzed.The KEGG pathways and protein-protein interaction(PPI)network relationships enriched in differentially expressed genes(DEGs)were used as prior information.The prior incorporation mixed graphical model(piMGM)was em-ployed to construct an integrative regulatory network.Genes related to disease status,survival time,and survival outcomes were identi-fied as diagnostic and prognostic markers.The prediction models and calculate the risk score were constructed using multivariate Cox regression analysis.Results A total of 180 DEGs between tumor and normal tissues were obtained,which were mainly enriched in KEGG pathways such as cell cycle,cellular senescence,gastric acid secretion,p53 signaling pathway,and IL-17 signaling pathway.MT1M,SLC9A4,GPER1,MT1A,CCL20,and MDFI were identified as key genes through gene regulatory network analysis.Together with clinical variables,a prognostic prediction model was constructed and the risk score was calculated.According to the optimal cutoff value,the patients were divided into the high-and low-risk groups with significantly different prognoses:the area under the curve(AUC)of the esophageal cancer diagnosis model was 0.978(95%CI:0.935-0.996),the AUCs of the 1-year and 3-years overall survival prediction models were 0.783(95%CI:0.646-0.896)and 0.779(95%CI:0.598-0.999),respectively,and the AUCs of the 1-year and 3-years disease-free survival prediction models were 0.787(95%CI:0.664-0.848)and 0.762(95%CI:0.575-0.900),respectively.Conclusion The six markers identified in this study can effectively predict the incidence and prognosis of pa-tients with esophageal cancer,laying a solid foundation for the development of efficient diagnostic tools and precise treatment regimens for esophageal cancer.