BACKGROUNDGastric cancer(GC)has a high prevalence and mortality overall.GEN1 is associatedwith abnormal centrosome amplification,DNA damage and increasedapoptosis.To date,little is known about the function and mechani...BACKGROUNDGastric cancer(GC)has a high prevalence and mortality overall.GEN1 is associatedwith abnormal centrosome amplification,DNA damage and increasedapoptosis.To date,little is known about the function and mechanism of GEN1 inGC.AIMTo explore the cellular processes associated with GC will help to elucidate themechanism of the occurrence and development of GC and discover potentialtherapeutic targets.METHODSThe detection of GEN1 expression at mRNA and protein levels was done by realtimequantitative polymerase chain reaction and western blotting.The function ofGEN1 was verified by loss-of-function experiments in AGS cells.The genes coexpressedwith GEN1 were searched from the stomach adenocarcinomas(STAD)data in The Cancer Genome Atlas database.Kyoto Encyclopedia of Genes andGenomes(KEGG)enrichment analysis of the genes co-expressed with GEN1 tofurther identify the pathways involved in GEN1.Rescue experiments usingferroptosis inhibitor ferrostatin-1 and chemotherapeutic sensitivity assays withcisplatin were also performed.RESULTSSignificant up-regulation of GEN1 was observed in GC cell lines AGS and MGC-803.Inhibition of GEN1 induced cell apoptosis and decreased cell proliferation,cycle progression,migration in AGS cells.There were 264 genes co-expressedwith GEN1 in STAD cohort(r>0.4,P<0.001).KEGG enrichment analysis showed that GEN1 might be associated with the cell cycle,Fanconi anemia pathway,homologous recombination,oocytemeiosis and cellular senescence in GC.Furthermore,CCNA2,CCNB1,CCNB2,cyclin-dependent kinase(CDK)1,CDK2 and polo-like kinase 1 protein levels were lower in GEN1-knockdown AGS cells,manifesting that GEN1 wasassociated with the cell cycle pathway in AGS cells.Downregulation of GEN1 decreased adenosine triphosphatecontent and elevated reactive oxygen species in AGS cells,suggesting that GEN1 silencing led to mitochondrialdysfunction in AGS cells.In addition,GEN1 silencing caused an overt decrease in FTH1 and GPX4 protein levelsand a significant elevation in ACSL4 protein levels,implying that GEN1 silencing promoted AGS cell ferroptosis.Treatment with ferrostatin-1 rescued cell viability loss induced by GEN1 knockdown,confirming ferroptosis as akey death mechanism.Additionally,GEN1-deficient AGS cells showed enhanced sensitivity to cisplatin,with asignificantly reduced half-maximal inhibitory concentration compared to control cells.CONCLUSIONGEN1 promotes GC cell proliferation and migration while suppressing apoptosis and ferroptosis.Targeting GEN1not only disrupts mitochondrial function and cell cycle progression but also sensitizes GC cells to ferroptosis andchemotherapy.These findings highlight GEN1 as a potential therapeutic target for enhancing treatment efficacy ingastric cancer.展开更多
BACKGROUND Self-renewal of gastric cancer stem cells(GCSCs)is considered to be the underlying cause of the metastasis,drug resistance,and recurrence of gastric cancer(GC).AIM To characterize the expression of stem cel...BACKGROUND Self-renewal of gastric cancer stem cells(GCSCs)is considered to be the underlying cause of the metastasis,drug resistance,and recurrence of gastric cancer(GC).AIM To characterize the expression of stem cell-related genes in GC.METHODS RNA sequencing results and clinical data for gastric adenoma and adenocarcinoma samples were obtained from The Cancer Genome Atlas database,and the results of the GC mRNA expression-based stemness index(mRNAsi)were analyzed.Weighted gene coexpression network analysis was then used to find modules of interest and their key genes.Survival analysis of key genes was performed using the online tool Kaplan-Meier Plotter,and the online database Oncomine was used to assess the expression of key genes in GC.RESULTS mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues(P<0.0001).A total of 16 modules were obtained from the gene coexpression network;the brown module was most positively correlated with mRNAsi.Sixteen key genes(BUB1,BUB1 B,NCAPH,KIF14,RACGAP1,RAD54 L,TPX2,KIF15,KIF18 B,CENPF,TTK,KIF4 A,SGOL2,PLK4,XRCC2,a n d C1 orf112)were identified in the brown module.The functional and pathway enrichment analyses showed that the key genes were significantly enriched in the spindle cellular component,the sister chromatid segregation biological process,the motor activity molecular function,and the cell cycle and homologous recombination pathways.Survival analysis and Oncomine analysis revealed that the prognosis of patients with GC and the expression of three genes(RAD54 L,TPX2,and XRCC2)were consistently related.CONCLUSION Sixteen key genes are primarily associated with stem cell self-renewal and cell proliferation characteristics.RAD54 L,TPX2,and XRCC2 are the most likely therapeutic targets for inhibiting the stemness characteristics of GC cells.展开更多
Objective This study aimed to construct a prognostic model for rectal adenocarcinomas based on immune-related long noncoding RNAs(lncRNAs)and verify its prediction efficiency.Methods Transcript data and clinical data ...Objective This study aimed to construct a prognostic model for rectal adenocarcinomas based on immune-related long noncoding RNAs(lncRNAs)and verify its prediction efficiency.Methods Transcript data and clinical data of rectal adenocarcinomas were downloaded from The Cancer Genome Atlas(TCGA)database.Perl software(strawberry version)and R language(version 3.6.1)were used to analyze the immune-related genes and immune-related lncRNAs of rectal adenocarcinomas,and the differentially expressed immune-related lncRNAs were screened according to the criteria|log2FC|>1 and P<0.05.The key immune-related lncRNAs were screened using single-factor Cox regression analysis and lasso regression analysis.Multivariate Cox regression analysis was performed to construct an immune-related lncRNA prognostic model using the risk scores.Next,we evaluated the effectiveness of the model through Kaplan-Meier(K-M)survival analysis,ROC curve analysis,and independent prognostic analysis of clinical features.In addition,prognostic biomarkers of immune-related lncRNAs in the model were analyzed by K-M survival analysis.Results In this study,we obtained gene expression profile matrices of 89 rectal adenocarcinomas and 2 paracancerous specimens from TCGA database and applied immunologic signatures to these transcripts.Through R and Perl software analysis,we obtained 847 immune-related lncRNAs and 331 protein-encoded immune-related genes in rectal adenocarcinomas.Eight important immune-related lncRNAs related to the prognosis of rectal adenocarcinomas were identified using univariate Cox regression and lasso regression analysis.Furthermore,four immune-related lncRNAs were identified as prognostic markers of rectal adenocarcinomas via multivariate Cox regression analysis.The prognostic risk model was as follows:risk score=(-4.084)*expression LINC01871+(3.112)*expression AL158152.2+(7.616)*expression PXN-AS1+(-0.867)*expression HCP5.The independent prognostic effect of the rectal adenocarcinoma risk score model was revealed through K-M analysis,ROC curve analysis,and univariate,and multivariate Cox regression analysis(P=0.035).LINC01871(P=0.006),PXN-AS1(P=0.008),and AL158152.2(P=0.0386)were closely correlated with the prognosis of rectal adenocarcinomas through the K-M survival analysis.Conclusion We constructed a prognostic model of rectal adenocarcinomas based on four immune-related lncRNAs by analyzing the data based on TCGA database,with high prediction accuracy.We also identified two biomarkers with poor prognosis(PXN-AS1 and AL158152.2)and one biomarker with good prognosis(LINC01871).展开更多
Objective The aim of this study was to construct a prognostic model of esophageal adenocarcinoma(EAC)based on immune-related long noncoding RNAs(immune-related lncRNAs)and identify prognostic biomarkers using the Canc...Objective The aim of this study was to construct a prognostic model of esophageal adenocarcinoma(EAC)based on immune-related long noncoding RNAs(immune-related lncRNAs)and identify prognostic biomarkers using the Cancer Genome Atlas(TCGA)database.Methods Whole genomic mRNA expression and clinical data of esophageal adenocarcinoma were obtained from the TCGA database.The software Strawberry Perl,R and R packets were used to identify the immune-related genes and lncRNAs of esophageal adenocarcinoma,and for data processing and analysis.The differentially expressed lncRNAs were detected while comparing esophageal adenocarcinoma and normal tissue samples.The key immune-related lncRNAs were screened using lasso regression analysis and univariate cox regression analysis,and used to construct the prognostic model using multivariate cox regression analysis.To evaluate the accuracy of the risk prognostic model,all esophageal adenocarcinomas were divided into high-risk and low-risk groups according to the median risk score,after which Kaplan-Meier(K-M)survival curves,operating characteristic(ROC)curve and independent prognostic analysis of clinical traits were created.In addition,statistically significant immune-related lncRNAs and potential prognostic biomarkers were identified using the prognostic model and multifactor cox regression analysis for k-m survival analysis.Results A total of 1322 differentially expressed immune-related lncRNAs were identified,28 of which were associated with prognosis via univariate cox regression analysis.In addition,K-M survival analysis showed that the total survival time of the higher risk group was significantly shorter than that of the lower risk group(P=1.063e-10).The area under the ROC curve of 5-year total survival rate was 0.90.The risk score showed independent prognostic risk for esophageal adenocarcinoma via single factor and multifactorial independent prognostic analyses.In addition,the HR and 95%CI of each key immune-related lncRNA were calculated using multivariate Cox regression.Using k-m survival analysis,we found that 5 out of 12 key significant immune-related lncRNAs had independent prognostic value[AL136115.1(P=0.006),AC079684.1(P=0.008),AC07916394.1(P=0.0386),AC087620.1(P=0.041)and MIRLET7BHG(P=0.044)].Conclusion The present study successfully constructed a prognostic model of esophageal adenocarcinoma based on the TCGA database,with moderate predictive accuracy.The model consisted of the expression level of 12 immune-related lncRNAs.Furthermore,the study identified one favorable prognostic biomarker,MIRLET7BHG,and four poor prognostic biomarkers(AL136115.1,AC079684.1,AC016394.1,and AC087620.1).展开更多
Objective To experimentally validate clinical samples,analyze the mRNA expression of the FYVE domain containing phosphatidylinositol 3-phosphate 5 kinase(PIKFYVE)gene,and its clinical significance based on the Cancer ...Objective To experimentally validate clinical samples,analyze the mRNA expression of the FYVE domain containing phosphatidylinositol 3-phosphate 5 kinase(PIKFYVE)gene,and its clinical significance based on the Cancer Genome Atlas(TCGA)database in hepatocellular carcinoma(HCC).MethodssData information on 424 clinical samples(including 374 cases of HCC tissues and 50 cases of non-tumorous liver tissues)were collected based on the TCGA database.Cox regression analysis and the Kaplan-Meier method were used to analyze the relationship between mRNA expression of the PIKFYVE gene and the clinical characteristics as well as survival prognosis in patients with HCC.The relationship betwen the PIKFYVE gene and immune cell infiltration was examined by correlation analysis with 24 kinds of immune cells.In addition,the mRNA expression level of the PIKFYVE gene and RACalpha serine/threonine-protein kinase(AKT1),phosphatase and tensin homolog(PTEN),protein kinase C alpha(PRKCA),inositol polyphosphate-5-phosphatase(INPP5D),phosphoinositide-3-kinase regulatory subunit 1(PIK3R1),inositol polyphosphate 4-phosphatase type II(INPP4B)and phospholipase C beta 4(PLCB4)gene correlations were analyzed in HCC tissues.At the same time,paraffin sections of highly differentiated,moderately differentiated,poorly differentiated,and non-tumor liver tissues from patients with HCC were collected from the Department of Pathology of the First Affiliated Hospital of Xinjiang Medical University.The histopathological observation was performed by HE staining.Immunohistochemistry was used to verify the expression levels of the PIKFYVE and Ki67 proteins in each clinical sample.The t-test was used for intergroup comparison of continuous data.The X test and Wilcoxon rank sum test were used for intergroup comparison of enumeration data.The Kaplan-Meier method was used for survival analysis.Results The expression level of the PIKFYVE gene was higher in the HCC tumor than that in normal liver tissue(P<0.01).The overall survival time of patients was significantly longer in the low expression group than that in the high expression group(HR=1.57,95%CI:1.10-2.25,P=0.014).The results of univariate Cox regression analysis showed that tumor stage,pathological grade,tumor status,residual tumor,and PIKFYVE expression level all had an effect on OS(P<0.05).The PIKFYVE prognostic risk model had a proportionate score of HR=1.533(95%CI:1.077-2.181,P=0.018).Multivariate Cox risk regression analysis showed that the PIKFYVE prognostic risk model had a proportionate score of HR=1.481(95%CI:0.886-2.476,P=0.134)and an area under the receiver operating characteristic curve of 0.559,indicating that it had predictive value for survival prediction.The results of the correlation analysis showed that the expression level of PIKFYVE was strongly correlated with immune cell infiltration and TP53(P<0.01).The results of immunohistochemical staining showed that the expression level of PIKFYVECwas significantly higher in HCC tissue samples than that in non-tumor liver tissues(P<0.01),and was negatively correlated with the degree of differentiation.Conclusion PIKFYVE,as an independent risk factor,is expected to be developed into a biomarker for clinical diagnosis,offering a reference for novel therapeutic agents in HCC.展开更多
文摘BACKGROUNDGastric cancer(GC)has a high prevalence and mortality overall.GEN1 is associatedwith abnormal centrosome amplification,DNA damage and increasedapoptosis.To date,little is known about the function and mechanism of GEN1 inGC.AIMTo explore the cellular processes associated with GC will help to elucidate themechanism of the occurrence and development of GC and discover potentialtherapeutic targets.METHODSThe detection of GEN1 expression at mRNA and protein levels was done by realtimequantitative polymerase chain reaction and western blotting.The function ofGEN1 was verified by loss-of-function experiments in AGS cells.The genes coexpressedwith GEN1 were searched from the stomach adenocarcinomas(STAD)data in The Cancer Genome Atlas database.Kyoto Encyclopedia of Genes andGenomes(KEGG)enrichment analysis of the genes co-expressed with GEN1 tofurther identify the pathways involved in GEN1.Rescue experiments usingferroptosis inhibitor ferrostatin-1 and chemotherapeutic sensitivity assays withcisplatin were also performed.RESULTSSignificant up-regulation of GEN1 was observed in GC cell lines AGS and MGC-803.Inhibition of GEN1 induced cell apoptosis and decreased cell proliferation,cycle progression,migration in AGS cells.There were 264 genes co-expressedwith GEN1 in STAD cohort(r>0.4,P<0.001).KEGG enrichment analysis showed that GEN1 might be associated with the cell cycle,Fanconi anemia pathway,homologous recombination,oocytemeiosis and cellular senescence in GC.Furthermore,CCNA2,CCNB1,CCNB2,cyclin-dependent kinase(CDK)1,CDK2 and polo-like kinase 1 protein levels were lower in GEN1-knockdown AGS cells,manifesting that GEN1 wasassociated with the cell cycle pathway in AGS cells.Downregulation of GEN1 decreased adenosine triphosphatecontent and elevated reactive oxygen species in AGS cells,suggesting that GEN1 silencing led to mitochondrialdysfunction in AGS cells.In addition,GEN1 silencing caused an overt decrease in FTH1 and GPX4 protein levelsand a significant elevation in ACSL4 protein levels,implying that GEN1 silencing promoted AGS cell ferroptosis.Treatment with ferrostatin-1 rescued cell viability loss induced by GEN1 knockdown,confirming ferroptosis as akey death mechanism.Additionally,GEN1-deficient AGS cells showed enhanced sensitivity to cisplatin,with asignificantly reduced half-maximal inhibitory concentration compared to control cells.CONCLUSIONGEN1 promotes GC cell proliferation and migration while suppressing apoptosis and ferroptosis.Targeting GEN1not only disrupts mitochondrial function and cell cycle progression but also sensitizes GC cells to ferroptosis andchemotherapy.These findings highlight GEN1 as a potential therapeutic target for enhancing treatment efficacy ingastric cancer.
基金the National Natural Science Foundation of China,No.81560389Key Research and Development Program of Jiangxi Province,No.20181BBG70015。
文摘BACKGROUND Self-renewal of gastric cancer stem cells(GCSCs)is considered to be the underlying cause of the metastasis,drug resistance,and recurrence of gastric cancer(GC).AIM To characterize the expression of stem cell-related genes in GC.METHODS RNA sequencing results and clinical data for gastric adenoma and adenocarcinoma samples were obtained from The Cancer Genome Atlas database,and the results of the GC mRNA expression-based stemness index(mRNAsi)were analyzed.Weighted gene coexpression network analysis was then used to find modules of interest and their key genes.Survival analysis of key genes was performed using the online tool Kaplan-Meier Plotter,and the online database Oncomine was used to assess the expression of key genes in GC.RESULTS mRNAsi was significantly upregulated in GC tissues compared to normal gastric tissues(P<0.0001).A total of 16 modules were obtained from the gene coexpression network;the brown module was most positively correlated with mRNAsi.Sixteen key genes(BUB1,BUB1 B,NCAPH,KIF14,RACGAP1,RAD54 L,TPX2,KIF15,KIF18 B,CENPF,TTK,KIF4 A,SGOL2,PLK4,XRCC2,a n d C1 orf112)were identified in the brown module.The functional and pathway enrichment analyses showed that the key genes were significantly enriched in the spindle cellular component,the sister chromatid segregation biological process,the motor activity molecular function,and the cell cycle and homologous recombination pathways.Survival analysis and Oncomine analysis revealed that the prognosis of patients with GC and the expression of three genes(RAD54 L,TPX2,and XRCC2)were consistently related.CONCLUSION Sixteen key genes are primarily associated with stem cell self-renewal and cell proliferation characteristics.RAD54 L,TPX2,and XRCC2 are the most likely therapeutic targets for inhibiting the stemness characteristics of GC cells.
基金Supported by a grant from the Health Commission of Hubei Province Scientific Research Project(No.WJ2019M118)。
文摘Objective This study aimed to construct a prognostic model for rectal adenocarcinomas based on immune-related long noncoding RNAs(lncRNAs)and verify its prediction efficiency.Methods Transcript data and clinical data of rectal adenocarcinomas were downloaded from The Cancer Genome Atlas(TCGA)database.Perl software(strawberry version)and R language(version 3.6.1)were used to analyze the immune-related genes and immune-related lncRNAs of rectal adenocarcinomas,and the differentially expressed immune-related lncRNAs were screened according to the criteria|log2FC|>1 and P<0.05.The key immune-related lncRNAs were screened using single-factor Cox regression analysis and lasso regression analysis.Multivariate Cox regression analysis was performed to construct an immune-related lncRNA prognostic model using the risk scores.Next,we evaluated the effectiveness of the model through Kaplan-Meier(K-M)survival analysis,ROC curve analysis,and independent prognostic analysis of clinical features.In addition,prognostic biomarkers of immune-related lncRNAs in the model were analyzed by K-M survival analysis.Results In this study,we obtained gene expression profile matrices of 89 rectal adenocarcinomas and 2 paracancerous specimens from TCGA database and applied immunologic signatures to these transcripts.Through R and Perl software analysis,we obtained 847 immune-related lncRNAs and 331 protein-encoded immune-related genes in rectal adenocarcinomas.Eight important immune-related lncRNAs related to the prognosis of rectal adenocarcinomas were identified using univariate Cox regression and lasso regression analysis.Furthermore,four immune-related lncRNAs were identified as prognostic markers of rectal adenocarcinomas via multivariate Cox regression analysis.The prognostic risk model was as follows:risk score=(-4.084)*expression LINC01871+(3.112)*expression AL158152.2+(7.616)*expression PXN-AS1+(-0.867)*expression HCP5.The independent prognostic effect of the rectal adenocarcinoma risk score model was revealed through K-M analysis,ROC curve analysis,and univariate,and multivariate Cox regression analysis(P=0.035).LINC01871(P=0.006),PXN-AS1(P=0.008),and AL158152.2(P=0.0386)were closely correlated with the prognosis of rectal adenocarcinomas through the K-M survival analysis.Conclusion We constructed a prognostic model of rectal adenocarcinomas based on four immune-related lncRNAs by analyzing the data based on TCGA database,with high prediction accuracy.We also identified two biomarkers with poor prognosis(PXN-AS1 and AL158152.2)and one biomarker with good prognosis(LINC01871).
基金a grant from the Health Commission of Hubei Province Scientific Research Project(No.WJ2019M118).
文摘Objective The aim of this study was to construct a prognostic model of esophageal adenocarcinoma(EAC)based on immune-related long noncoding RNAs(immune-related lncRNAs)and identify prognostic biomarkers using the Cancer Genome Atlas(TCGA)database.Methods Whole genomic mRNA expression and clinical data of esophageal adenocarcinoma were obtained from the TCGA database.The software Strawberry Perl,R and R packets were used to identify the immune-related genes and lncRNAs of esophageal adenocarcinoma,and for data processing and analysis.The differentially expressed lncRNAs were detected while comparing esophageal adenocarcinoma and normal tissue samples.The key immune-related lncRNAs were screened using lasso regression analysis and univariate cox regression analysis,and used to construct the prognostic model using multivariate cox regression analysis.To evaluate the accuracy of the risk prognostic model,all esophageal adenocarcinomas were divided into high-risk and low-risk groups according to the median risk score,after which Kaplan-Meier(K-M)survival curves,operating characteristic(ROC)curve and independent prognostic analysis of clinical traits were created.In addition,statistically significant immune-related lncRNAs and potential prognostic biomarkers were identified using the prognostic model and multifactor cox regression analysis for k-m survival analysis.Results A total of 1322 differentially expressed immune-related lncRNAs were identified,28 of which were associated with prognosis via univariate cox regression analysis.In addition,K-M survival analysis showed that the total survival time of the higher risk group was significantly shorter than that of the lower risk group(P=1.063e-10).The area under the ROC curve of 5-year total survival rate was 0.90.The risk score showed independent prognostic risk for esophageal adenocarcinoma via single factor and multifactorial independent prognostic analyses.In addition,the HR and 95%CI of each key immune-related lncRNA were calculated using multivariate Cox regression.Using k-m survival analysis,we found that 5 out of 12 key significant immune-related lncRNAs had independent prognostic value[AL136115.1(P=0.006),AC079684.1(P=0.008),AC07916394.1(P=0.0386),AC087620.1(P=0.041)and MIRLET7BHG(P=0.044)].Conclusion The present study successfully constructed a prognostic model of esophageal adenocarcinoma based on the TCGA database,with moderate predictive accuracy.The model consisted of the expression level of 12 immune-related lncRNAs.Furthermore,the study identified one favorable prognostic biomarker,MIRLET7BHG,and four poor prognostic biomarkers(AL136115.1,AC079684.1,AC016394.1,and AC087620.1).
文摘Objective To experimentally validate clinical samples,analyze the mRNA expression of the FYVE domain containing phosphatidylinositol 3-phosphate 5 kinase(PIKFYVE)gene,and its clinical significance based on the Cancer Genome Atlas(TCGA)database in hepatocellular carcinoma(HCC).MethodssData information on 424 clinical samples(including 374 cases of HCC tissues and 50 cases of non-tumorous liver tissues)were collected based on the TCGA database.Cox regression analysis and the Kaplan-Meier method were used to analyze the relationship between mRNA expression of the PIKFYVE gene and the clinical characteristics as well as survival prognosis in patients with HCC.The relationship betwen the PIKFYVE gene and immune cell infiltration was examined by correlation analysis with 24 kinds of immune cells.In addition,the mRNA expression level of the PIKFYVE gene and RACalpha serine/threonine-protein kinase(AKT1),phosphatase and tensin homolog(PTEN),protein kinase C alpha(PRKCA),inositol polyphosphate-5-phosphatase(INPP5D),phosphoinositide-3-kinase regulatory subunit 1(PIK3R1),inositol polyphosphate 4-phosphatase type II(INPP4B)and phospholipase C beta 4(PLCB4)gene correlations were analyzed in HCC tissues.At the same time,paraffin sections of highly differentiated,moderately differentiated,poorly differentiated,and non-tumor liver tissues from patients with HCC were collected from the Department of Pathology of the First Affiliated Hospital of Xinjiang Medical University.The histopathological observation was performed by HE staining.Immunohistochemistry was used to verify the expression levels of the PIKFYVE and Ki67 proteins in each clinical sample.The t-test was used for intergroup comparison of continuous data.The X test and Wilcoxon rank sum test were used for intergroup comparison of enumeration data.The Kaplan-Meier method was used for survival analysis.Results The expression level of the PIKFYVE gene was higher in the HCC tumor than that in normal liver tissue(P<0.01).The overall survival time of patients was significantly longer in the low expression group than that in the high expression group(HR=1.57,95%CI:1.10-2.25,P=0.014).The results of univariate Cox regression analysis showed that tumor stage,pathological grade,tumor status,residual tumor,and PIKFYVE expression level all had an effect on OS(P<0.05).The PIKFYVE prognostic risk model had a proportionate score of HR=1.533(95%CI:1.077-2.181,P=0.018).Multivariate Cox risk regression analysis showed that the PIKFYVE prognostic risk model had a proportionate score of HR=1.481(95%CI:0.886-2.476,P=0.134)and an area under the receiver operating characteristic curve of 0.559,indicating that it had predictive value for survival prediction.The results of the correlation analysis showed that the expression level of PIKFYVE was strongly correlated with immune cell infiltration and TP53(P<0.01).The results of immunohistochemical staining showed that the expression level of PIKFYVECwas significantly higher in HCC tissue samples than that in non-tumor liver tissues(P<0.01),and was negatively correlated with the degree of differentiation.Conclusion PIKFYVE,as an independent risk factor,is expected to be developed into a biomarker for clinical diagnosis,offering a reference for novel therapeutic agents in HCC.
