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Objective To explore the expression, correlation with clinicopathologic parameters, and clinical significance of MIS18 binding protein 1 (MIS18BP1) in bladder cancer. Methods TCGA and GEO databases were used to analyze the mRNA expression of MIS18BP1 in tumors and controls, and the results were verified via qRT-PCR. UALCAN online database was utilized in the analysis of the expression of MIS18BP1 and its correlation with clinicopathological parameters and the degree of immune cell infiltration. Immunohistochemistry was employed to analyze the expression of MIS18BP1 in bladder cancer and its relationship with clinicopathological features. The ROC curve was applied to evaluate the diagnostic value of MIS18BP1 mRNA in bladder cancer. Results Bioinformatics analysis and qRT-PCR results revealed the increased expression of MIS18BP1 mRNA in bladder cancer compared with that in the control group (P<0.05). Immunohistochemistry unveiled the significantly high positive rate of MIS18BP1 protein in bladder cancer (P<0.05) and its correlation with the clinical stage of tumors, depth of invasion, and lymph node metastasis (P<0.05). The immune infiltration analysis showed the association of MIS18BP1 with immune cell infiltration in bladder cancer. Conclusion The increased expression level of MIS18BP1 gene and protein in bladder cancer may regulate the development of bladder cancer by influencing immune cell infiltration.
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Objective To construct a prognostic model for cuprotosis-related genes (CRGs) in patients with hepatocellular carcinoma (HCC). Methods Differential expression of CRGs in HCC was analyzed on the basis of datasets from the TCGA database. The potential mechanisms of CRGs and their related genes in HCC were explored through GO and KEGG enrichment analyses. The prognostic value of the CRGs was evaluated through Kaplan-Meier survival analysis, and the relationship between CRG expression and immune cell infiltration was investigated. CRGs significantly correlated with prognosis in patients with HCC were identified. A prognostic model was established through univariate, Lasso regression, and multivariate Cox regression analyses. The patients were divided into two groups by risk score. ROC curve was used in evaluating the prognostic model. The relationship of risk score or clinical factors with prognosis was analyzed through univariate and multivariate Cox regression analyses. Results A total of 11 differentially expressed CRGs in HCC were obtained. The main enriched GO item of CRGs and their related genes was oxidoreductase activity, acting on the aldehyde or oxo group of donors, and the main enriched KEGG pathway was carbon metabolism. The expression of CRGs was significantly correlated with pDC, T helper cells and other immune cells (P < 0.05). Three CRGs (CDKN2A, DLAT, and LIPT1) were screened and a prognostic model was constructed. There was significant difference in overall survival between the high- and low-risk groups (P < 0.001). The risk score is an independent risk factor for poor prognosis (P < 0.001). Conclusion The prognostic model for CRGs in patients with HCC is constructed using TCGA database data. This model may be used in evaluating patient prognosis.
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【Objective】 To investigate the expression characteristics of ABO gene mRNA in peripheral blood of patients with acute myeloid leukemia. 【Methods】 The RNA-seq data of acute myeloid leukemia in TCGA database and the whole blood RNA-seq data in GTEx database were downloaded. The difference of ABO gene mRNA expression between acute myeloid leukemia and GTEx whole blood samples was analyzed by R software, and the relationship between ABO gene mRNA expression and DNA methylation, immune infiltration and prognosis was analyzed. 【Results】 The expression level of ABO gene mRNA in acute myeloid leukemia(median: 1.333, P25: 3.654, P75: 0.401)was significantly lower than that in the control group(median: 3.576, P25: 3.747, P75: 3.470)(P<0.001). The expression level of ABO gene mRNA in acute myeloid leukemia was negatively correlated with the methylation of + 82(r=-0.249, P<0.001), + 618(r=-0.268, P<0.001), + 1 080(r=-0.105, P<0.001) and + 1 409(r=-0.210, P<0.001) at downstream of transcription start site, and positively correlated with the immune infiltration of nine types of immune cells (B cells, CD8 T cells, Cytotoxic cells, pDC, T cells, T helper cells, Tcm, Tfh and Treg) (P<0.001). There was no significant difference in overall survival between patients with high (median survival time: 366 days, confidence interval: 304-731 days) and low (median survival time: 731 days, confidence interval: 335-1 402 days) expression of ABO gene mRNA in acute myeloid leukemia (P>0.05). 【Conclusion】 The mRNA expression of ABO gene in peripheral blood of patients with acute myeloid leukemia is decreased, which is associated with DNA methylation of the first intron of ABO gene and immune infiltration, but not with the prognosis.
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Objective@#To compare the difference in somatic gene mutation of PTC subtypes between 114 patients with papillary thyroid carcinoma (PTC) and The Cancer Genome Atlas (TCGA) database.@*Methods@#Totally 114 PTC patients admitted to The First Affiliated Hospital of Nanjing Medical University were recruited. The 18 hotspot genes associated with thyroid cancer were detected in thyroidectomy specimens were using next generation sequencing. PTC data were downloaded from the TCGA database in the cBioPortal website, and the difference in the somatic gene mutation was compared between 114 PTC patients and the TCGA database@*Results@#The 114 PTC patients included 73 women (64.04%) and had a mean age of (39.23±13.18) years. The prevalence of BRAF V600E (66.67% vs. 48.68%), TERTp (3.51% vs. 0.41%), PDGFRA (1.75% vs. 0%), PTEN (3.51% vs. 0.41%) and TP53 gene mutations (4.39% vs. 0.61%) was significantly higher among the 114 PCT patients than in the TCGA database (P<0.05). The prevalence of BRAF V600E (80.88% vs. 54.99%), TP53 (7.35% vs. 0.57%) and TSHR gene mutations (2.94% vs. 0%) was significantly higher in classical PTC(CPTC) patients than in the TCGA database, and the prevalence of BRAF V600E (36.84% vs.13.86%) and TERTp gene mutations (10.53% vs. 0%) was significantly higher in follicular variant PTC (FVPTC) patients than in the TCGA database. According to the American Thyroid Association Risk Stratification of Thyroid Cancer Recurrence, the prevalence of BRAF V600E and TP53 gene mutations was 77.14% and 8.57% among moderate-risk CPTC patients, the prevalence of BRAF V600E gene mutation was 27.27% among low-risk FVPTC patients, and the prevalence of TERTp gene mutation was 33.33% among moderate-risk FVPTC patients, which were all higher than in the TCGA database (55.10%, 0%, 3.28%, and 0%, respectively; P<0.05).@*Conclusion@#There are significant differences in the type and rate of somatic gene mutations between 114 PTC patients and the TCGA database.
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Objective To establish a lncRNA prognostic risk model for gastrointestinal tumors based on the TCGA database and evaluate the prognosis of patients. Methods We collected the data of patients with esophageal cancer, gastric cancer, colon cancer and rectal cancer in the TCGA database. Univariate Cox analysis, Lasso and multivariate Cox analysis were performed to construct the prognostic risk scoring model. The model was validated and tested for independence. Time-dependent ROC curve analysis was performed to evaluate the clinical application value of the model. Results We established a prognostic risk model based on 13 lncRNAs. The three-year AUC of the training set and the validation set were 0.746 and 0.704, respectively. The pan-cancer data set was divided into high- and low-risk groups for survival analysis. The 5-year survival rate of the low-risk group was significantly higher than that of the high-risk group; among all cancer types, the five-year survival rates of the low-risk group were higher than those of the high-risk group. Multivariate Cox analysis showed that the risk score could be an independent indicator of prognosis. Conclusion The 13-gene prognostic risk score model is constructed successfully. The risk score obtained by this model can be used as an independent prognostic predictor of the patients with gastrointestinal cancer.
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【Objective】 To explore the expressions of adipocyte enhancer binding protein 1 （AEBP1） gene and its isoforms in different types of gliomas， and the influence of AEBP1 gene on the prognosis of patients with different types of gliomas. 【Methods】 We used the GEPIA2 visual network analysis tool to analyze AEBP1 gene expression levels in the tumor tissues of glioblastomas （GBM， including classical， mesenchymal， neural， and proneural ones） and low-grade gliomas （LGG， including astrocytoma， oligoastrocytoma， oligodendroglioma） in the TCGA database and normal human tissue samples in the TCGA and GTEx databases by one-way ANOVA. The distribution trend of isoforms of AEBP1 gene in gliomas was analyzed using the violin plot. The Kaplan-Meier survival curve was drawn and the Logrank test was used to analyze the influence of AEBP1 gene expression in GBM and LGG tumor tissues on the prognosis of glioma patients. 【Results】 The expression of AEBP1 in the tumor tissues of overall GBM and the four types of GBM was higher than that in the normal control tissues （P<0.05）. The expression of AEBP1 in astrocytoma and oligodendrocyte astrocytoma tumor tissues was higher than that in normal control tissues （P<0.05）. There were nine isoforms of AEBP1 gene in GBM and LGG， and the expression level in GBM was higher. The overall survival （OS） of the AEBP1 low expression group of GBM patients and the proneuronal GBM patients was better than that of the high expression group （P<0.05）. The OS and progression-free survival of LGG patients and the AEBP1 low-expression group of astroglioma were better than those of the high-expression group （P<0.05）. 【Conclusion】 AEBP1 has an important clinical value in the pathogenesis and development of GBM and LGG， and thus can be used as a diagnostic marker and a candidate gene for targeted therapy.
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【Objective】 To establish a prognostic model of fatty acid metabolism related genes for predicting the prognosis of renal clear cell carcinoma. 【Methods】 The differentially expressed fatty acid metabolism-related genes in renal clear cell carcinoma samples and normal samples in TCGA database were screened by R language software. The Cox proportional hazard regression model was used to select and establish a multigene prognostic model and the prognostic score was calculated. Patients were divided into high-risk group and low-risk group according to the median prognostic score. Kaplan-Meier survival curve was used to analyze the difference in two groups. The clinical pathological factors and prognostic score factors were included in the Cox regression model to analyze the factors affecting the survival of patients with renal clear cell carcinoma. ROC receiver operating curve analysis was used to evaluate the accuracy of the prognostic prediction model. The prognostic model of fatty acid metabolism-related genes and their correlation with clinical factors were analyzed. GSEA enrichment analysis analyzed the differences of gene sets in risk groups. 【Results】 A total of 4 differential genes (CPT1B, HADH, CYP4A11, and ACADSB) were selected to establish a prognostic model for genes related to fatty acid metabolism in renal cell carcinoma. The prognostic risk score (RS) formula is as follows: RS=0.490×CPT1B-0.428×HADH-0.11 × CYP4A11-0.372 × ACADSB. Kaplan-Meier survival analysis confirmed that the overall survival rate of patients with low-risk prognostic score was significantly higher in patients with overall renal clear cell carcinoma, and the difference was statistically significant (P<0.001). Cox regression analysis showed that the prognostic model of genes related to age and fatty acid metabolism is an independent influencing factor for the prognosis of patients with renal clear cell carcinoma (P<0.01). The 5 years’ AUC of the renal clear cell carcinoma ROC curve of the renal cancer fatty acid metabolism related gene model was 0.802. GSEA analysis showed that the difference of 81 gene sets in the low-risk group was statistically significant (P<0.05). 【Conclusion】 The prognostic model of renal cancer fatty acid metabolism-related genes can be used to predict the prognosis of patients with renal clear cell carcinoma, which is conducive to further guide clinical treatment.
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Objective:To analyze and screen microRNA (miRNA) related to the prognosis of gastric cancer(GC) by bioinformatics analysis, and to construct and validate a risk score model.Methods:The human genome miRNA sequencing data and corresponding clinicopathological data of the 491 samples (446 GC tissue samples and 45 normal gastric tissue samples) were downloaded from the cancer genome atlas (TCGA) database. The differentially expressed microRNA (DEM) was analyzed with edgeR package of R 4.0.2 software and the obtained DEM’s profile was randomly divided into training set and test set according to the ratio of 1∶1. The miRNA related to prognosis were analyzed and screened with univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis was further performed to analyze the screened prognostic-related miRNA and then the prognostic risk score model was constructed. Kaplan-Meier curve, receiver operating characteristic curve (ROC), and dynamic area under the ROC were drawn to evaluate the predictive power of the model.Results:A total of 175 DEM in GC tissues were screened out based on the cut-off criteria of |log2 Fold Change|>1.5 and P<0.01. Six DEMs related to the overall survival rate of patients with GC were screened out by univariate Cox regression and LASSO regression analysis, and then a five-miRNA risk score model was successfully constructed by multivariate Cox regression. The risk score=0.183×hsa-miRNA-184+ 0.086×hsa-miRNA-675-0.231×hsa-miRNA-2115+ 0.548×hsa-miRNA-3943-1.455×hsa-miRNA-1246. In the training set, test set and overall data set, the cumulative survival rates of the patients with higher risk score were lower than those of the patients with lower risk score, respectively, and the differences were statistically significant ( χ2=18.90, 9.50 and 26.70, all P<0.05). The prediction power of the model was better than that of TNM stage. And the results of stratified analysis showed the predictive ability of the model in patients with early GC. The results of univariate Cox regression and multivariate Cox regression demonstrated that the risk score of the model, gae and M stage were independent risk factors for poor prognosis in patients with GC (hazard ratio(95% confidence interval)1.19(1.07 to 1.32), 1.20(1.06 to 1.40), 1.50(1.01 to 2.23), 1.90(1.28 to 2.90), 1.34(1.15 to 1.57), 2.10(1.05 to 4.40); all P<0.05). Conclusion:The 5-miRNA risk score model based on 5 miRNAs which was an independent prognostic factor had high accuracy in predicting the prognosis of patients with GC.
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Objective:To investigate the infiltration of immune cells and prognosis in papillary thyroid carcinoma (PTC) with cervical lymph nodes metastases.Methods:The RNA-seq data and clinicopathological data of PTC patients were downloaded from the Cancer Genome Atlas (TCGA) database. There were 85 patients in the PTC with cervical lymph nodes metastases group and 23 patients in the control group, according to the inclusion and exclusion criteria. CIBERSORT deconvolution algorithm was used to calculate the infiltration ratio of 22 kinds of immune cells in PTC with cervical lymph nodes metastases. Different immune infiltrating cells were compared between PTC with cervical lymph nodes metastases and normal thyroid. The correlation between clinical characteristics (age, gender, extra-thyroid invasion and TNM stage) and infiltration of immune cells were evaluated, then different immune cells related to the prognosis of PTC with cervical lymph nodes metastases patients were screened by Kaplan-Meier analysis.Results:The B cells naive, B cells memory, T cells CD8, macrophages M1, mast cells activated and eosinophils were down-regulated in tumor tissue compared with normal. Macrophages M0, macrophages M2, dendritic cells resting, dendritic cells activated and mast cells resting were higher in tumor tissue compared with that of normal. Macrophages M0, macrophages M2 and dendritic cells resting were positively correlated with extra-thyroid invasion and TNM stage, and patients with a high proportion of those immune cells had a shorter progression-free survival (PFS) . The B cells naive and T cells CD8 were negatively correlated with extra-thyroid invasion and TNM stage, and patients with a high proportion of those immune cells had a longer progression-free survival (PFS) .Conclusions:The pattern of immune cell infiltration of PTC with cervical lymph nodes metastases has specificity, and it was related to clinical characteristics and prognosis. This study provides theoretical evidences and new insights for the role of immune cell microenvironment in PTC lymph node metastasis.
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@#[Abstract] Objective: To explore the expression and biological significance of GABRE gene in colon cancer by mining data in the Oncomine and TCGA databases. Methods: The expression of the GABRE gene in colon cancer tissues and its correlation with the prognosis of patients were analyzed using the Oncomine and TCGA databases. The upstream miRNA targeting GABRE gene was identified using TargetScan, starBase, mirDIP, and miRWalk, and its expression and relationship with prognosis of colon cancer were analyzed. Furthermore, the GABRE co-expression genes were screened using the LinkedOmics database, and the GO enrichment analysis and KEGG pathway analysis were carried out. Results: The results showed that GABRE was highly expressed in colon cancer and indicated a poor prognosis (all P<0.05). The Venn diagram indicated that hsa-miR-370-3p targeted GABRE, and its expression was markedly increased in normal tissues (P<0.01). The expression of GABRE was positively correlated with the expressions of OGT and FAM156A genes, whereas negatively correlated with the expressions of ATP5A1 and MPDU1 genes (all P<0.05). GO biological process function and KEGG pathway enrichment analysis suggested that the GABRE gene may be involved in biological processes including protein dealkylation and regulation of cyclin-dependent protein kinase activity and enriched in taurine metabolism and NF-κB signaling pathway. Conclusions: GABRE gene is highly expressed in patients with colon cancer and indicates a poor prognosis, suggesting that the gene may serve as a potential novel target for the diagnosis and treatment of colon cancer.
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@#[Abstract] Objective: To screen the key genes associated with esophageal adenocarcinoma by using TCGA and GEO databases, and to analyze their biological functions, relevant signaling pathways and clinical significance. Methods: The esophageal adenocarcinoma data downloaded from TCGA database and GSE92396 microarray data from GEO database were integrated. The analysis of differentially expressed genes (DEGs) were performed by using DEseq2 and Limma packages of R software to obtain the co-differentially expressed genes, which were then chosen for the GO function enrichment analysis and KEGG pathway analysis with clusterProfiler package of R software. The key node genes that regulate the protein expressions in esophageal adenocarcinoma were screened out by protein-protein interaction (PPI) network analysis using the string website and Cytoscape 3.7.2 software. The correlation between key node genes and the survival of patients was further analyzed by combining with TCGA database. Results: By analyzing the chip data of 90 cases of adenocarcinoma tissues and 18 cases of normal esophageal tissues from databases, a total of 521 co-differentially expressed genes were obtained, including 356 upregulated genes and 165 downregulated genes. These genes were closely related to the metabolic-associated functions mainly involving epidermis development, epidermal cell differentiation and signaling pathways involving cytokine-cytokine receptor interaction, etc. The PPI network analysis revealed 15 key node genes. The survival time for patients with low CXCL8 and CCL20 expression was significantly longer compared with the patients with high expression level (median survival: 32.4 vs 19.7 months, P<0.05; 32.4 vs 13.9 months, P<0.05). Conclusion: These results show that CXCL8 and CCL20 may play an important role in the occurrence, development and prognosis of esophageal adenocarcinoma, and may be used as potential indicators to judge the prognosis of patients.
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Objective@#To search new prognosis-related genes in gastric cancer by analyzing the high-throughput sequencing data of gastric cancer in TCGA database, and then provide data support for future studies. @*Methods@#The RNA-seq expression matrix data and patient-related clinical data from 375 gastric cancer tissues and 45 adjacent noncancerous tissues were downloaded from the TCGA database. The data were collated and standardized based on the R language. The difference of gene expression was analyzed by the edgeR and DEseq software packages. The survival analysis of obtained differential genes was performed by the univariate and multivariate COX regressions combined with clinical data of patients, and then the genes with clinical significance were screened out. @*Results@#A total of 364 differential genes were obtained by the edgeR and DEseq analysis. Subsequently, the functional enrichment analysis found that these genes were mainly involved in protein digestion and absorption, cytochrome P450 system of drug and exogenous substance metabolism, chemical carcinogenesis, gastric acid secretion and so on. The univariate COX regression analysis showed that FAP, FAT3, PDK4 and ZNF365 genes had significant influences on the prognosis of gastric cancer patients. The multivariate COX stepwise regression analysis showed that the risk model constructed by FAP and PDK4 could predict the prognosis of gastric cancer patients. @*Conclusion: @#FAP, FAT3, PDK4 and ZNF365 genes may be the prognostic markers of gastric cancer, which may provide data supports for future clinical and basic studies.
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@# Objective: To screen differentially expressed lncRNA, miRNA and mRNA in colorectal cancer (CRC) in TCGA database, and to explore their relationship with CRC prognosis and related biological functions. Methods: RNA sequencing (RNA-Seq) data and miRNA-Seq data of CRC samples were downloaded from the TCGAdatabase and analyzed, and differentially expressed lncRNA, miRNA and mRNA were screened by R program. The lncRNA-miRNA-mRNA ceRNA network in CRC was constructed by analyzing and integrating the relationships between differentially expressed RNAs through miRcode, TargetScan and miRTarbase databases.KaplanMeier method was used to analyze the relationship between the expression of lncRNA, miRNA, mRNA in ceRNA network and the survival prognosis of patients.Finally, the signal pathways involved in the occurrence and development of CRC were analyzed by GSEA functional enrichment analysis software. Results: A total of 614 differentially expressed lncRNAs, 244 differentially expressed miRNAs, and 12 672 differentially expressed mRNAs in CRC were identified; a ceRNA network consisting of 139 lncRNAs, 37 miRNAs and 228 mRNAs was constructed;It was found that 58 lncRNAs, 23 miRNAs, and 150 mRNAs were associated with the prognosis of CRC.The results of GSEA enrichment analysis showed that mRNA was mainly involved in signaling pathways such as Notch, Hedgehog and TGF-β. Conclusion: CRC-related ceRNA network was successfully constructed and lncRNAs, miRNAs and mRNAs associated with CRC prognosis were screened. It provides a valuable preliminary basis for further in-depth clinical research and basic experimental research on CRC.
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Objective To investigate the mechanism of AR/let-7 signaling pathway in inhibiting the proliferation of TNBC and its significance for survival.Methods Human breast cancer MDA-MB-453 cells were cultured in vitro and divided into experimental group and control group.The experimental group was added with androgen dihydrotestosterone(DHT),and the control group was added nothing.The cell proliferation was detected by CCK-8,cell cycle was detected by flow cytometry,AR expression was detected by Western blot,and let-7 expression was detected by real-time fluorescent quantitative PCR.The AR,let-7 expression data and survival data of TNBC patients were downloaded from the Cancer Genomes Atlas (TCGA).The expression of AR and let-7 between cancer tissues and normal breast tissues and their relationship with survival was analyzed.Results Cellular experiments showed that the proliferation rate of cancer cells in the experimental group was significantly lower than that in the control group(1.22±0.11 vs 2.26±0.23,t=7.065,P＜0.05),and the ratio of G1/S in the experimental group was greater than in the control group (1.08±0.03 vs 0.68±0.03,t=17.321,P=0.000).The AR and let-7a,b,c,and d were overexpressed in the experimental group.The TCGA data showed that AR,let-7a-1,let-7a-2,let7a-3,and let-7c were lower in breast cancer tissues than in normal tissues (P＜0.05),while let-7d was higher in breast cancer tissues (P＜0.05).The AR,let-7a-1,let-7a-2,let-7a-3,and let-7c were used to cluster the patients into high-expression group and low-expression group,and the overall survival in the high-expression group appeared to be higher,while the difference was not statistically significant (P=0.163).Conclusions The AR/let-7 signaling pathway is up-regulated by DHT activation,which blocks cells in the G1 phase and inhibits cell proliferation.Patients with high expression of AR,let-7a-1,let-7a-2,let-7a-3,and let-7c may have better overall survival.It is suggests that the AR/let-7 signaling pathway may become a new target for TNBC.
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@#Objective To establish a multi-gene prognostic model for predicting the prognosis of breast cancer using Cancer Genome Atlas (TCGA) database, and to analyze the relationship between the multi-gene prognostic model and clinical and pathological features of breast cancer. Methods The mRNA data and clinical information of breast cancer cohort were downloaded from TCGA database. Differentially expressed genes (DEGs) were identified by R language software in breast cancer tissues and normal tissues. DEGs related to overall survival of patients were selected by univariate Cox regression model, and a multi-gene signature model was identified by multivariate Cox regression model. Patients were divided into high risk cohort and low risk cohort according to prognostic index calculated by prognostic index formula based on the result of multivariate Cox regression model. Factors were analyzed by univariate and multivariate Cox regression models according to clinicopathological characteristics and prognostic index related with survival of patients with breast cancer. Survival analysis of subgroups was conducted according to age, estrogen receptor status, Her-2 receptor status, lymph node status and pathological stage. Kaplan-Meier（K-M）survival analysis was used to evaluate the prognostic prediction of the multi-gene signature in overall patients and subgroups. Results Eight DEGs were selected to conduct a survival related multi-gene signature from total of 2 142 DEGs in univariate and multivariate Cox regression model analysis including CEL，POU3F2，CYP24A1，FABP7，MURC，GCCR，LRP1B and PRSS2. Prognostic index formula was as follows： PI=0.156 × the expression of CEL + 0.112 × the expression of POU3F2-0.071 × the expression of CYP24A1-0.065 × the expression of FABP7 +0.135×the expression of MURC-0.201×the expression of GCGR-0.063×the expression of LRP1B- 0.090×the expression of PRSS2. Cox regression model analysis demonstrated that age, pathological stage and eight-gene signature were validated as the novel and independent prognostic factors (P＜0.05). According to survival analysis (K-M plot), the accurate prognostic performance of eight-gene signature was confirmed in both overall patients and subgroups (except Ⅳ stage). Patients with low risk of prognostic score showed significantly longer OS compared with patients of high risk of prognostic score (P＜0.01). Conclusion The eight-gene prognostic signature can be used to predict the prognosis of breast cancer patients. It is verified in the subgroup of breast cancer according to the clinicopathological features, which is helpful to further guide the clinical treatment.
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Objective To analyze and validate the key molecular targets correlated with the overall survival of patients with HER2-positive breast cancer.Methods First,the survival time and transcriptome data of patients with HER2-positive breast cancer in stage Ⅰ / Ⅱ and Ⅲ/Ⅳ were downloaded from the TCGA database.The significantly differential genes between overall survival ＜2 years and ＞8.5 years in stage Ⅰ / Ⅱ were picked out by edgeR package,and the pathways were enriched by KEGG.Similarly,the differential genes between overall survival ＜2 years and ＞7 years in stage Ⅲ/Ⅳ were analyzed.Furthermore,KEGG pathway analysis was performed using the differential genes overlapped by stage Ⅰ /Ⅱ and Ⅲ/Ⅳ.Second,the relationships between the expression levels of key node genes and other genes in enriched pathway and the overall survival of patients with HER2-positive breast cancer were validated by KMplot database.Last,the correlation between the activity of pathway enriched in KEGG and the resistance to anti-HER2 treatment was validated in HER2-positive breast cancer cell line BT474.Results In patients with stage Ⅰ / Ⅱ HER2-positive breast cancer whose overall survival was ＜2 years,PI3K/AKT was the 9th signaling pathway enriched by up-regulated differential genes.In patients with stage Ⅲ/Ⅳ whose overall survival was ＜2 years,PI3K/AKT was the 2nd signaling pathway enriched by up-regulated differential genes.Furthermore,PI3K/AKT was the first signal pathway enriched by the overlapping upregulated genes of patients in stage Ⅰ / Ⅱ and Ⅲ / Ⅳ whose overall survival was ＜2 years.Patients with high expression of PI3K and AKT (key node genes) or CFAP221 and COL4A6 (other genes) of PI3K/AKT pathway had shorter overall survival than those with low expression.PI3K inhibitors could enhance the growth inhibitory effect of HER2 small molecule inhibitor on HER2-positive breast cancer cell line BT474.Conclusions The overexpression of PI3K/AKT pathway is associated with the shorter overall survival in HER2-positive breast cancer patients,and associated with anti-HER2 resistance in HER2-positive breast cancer cell line.
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Objective To analyse the expression and clinical significance of 12 kinds of microRNAs (miR) in patients with ovarian cancer using public gene expression databases. Methods The microRNA expression data were screened in dataset GSE14407 and TCGA database, then 12 kinds of microRNAs were obtained including miR-10B, miR-1244, miR-622, miR-21, miR-503, Let-7D, miR-155, miR-30C, miR-17, miR-101-1, miR-186 and miR-770. The expression data of these 12 kinds of microRNAs were compared and identified to find the differential ones between normal tissue and tumors. Data of 505 ovary cancer patients were divided into two groups by age, tumor grade, clinical stage, disease location, tumor residual and microRNA expression. Kaplan-Meier survival analysis and Cox multivariate analysis were used to compare the overall survival of ovary cancer patients between two groups. Results Compared with ovary cancer, the expression levels of Let-7D and miR-101-1 were higher, but the expression levels of miR-155 and miR-770 were decreased, in adjacent tissue of ovary tumor (P<0.05). The Kaplan-Meier survival analysis result showed that lower survival rates were found in patients with age≥59 years, clinical stage (Ⅲ+Ⅳ) and lower Let-7D expression (P<0.05). The multivariate Cox regression analysis showed that the decreased expression level of Let-7D was the independent risk factor for the prognosis of ovarian cancer. Conclusion The expression of Let-7D is correlated with the prognosis of ovarian cancer, which is the independent biomarker to predict prognosis of ovarian cancer.