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AIM: To analyze the correlation between SLC52A2 and uveal melanoma(UM)based on the cancer genome atlas(TCGA)database, and preliminarily explore the influence of SLC52A2 on the prognosis of UM patients and potential mechanism.METHODS: The clinical information on 80 patients with UM and mRNA expression data of SLC52A2 were collected from TCGA database. According to the expression level of SLC52A2, 80 patients were divided into high and low expression groups by median method. The relationship between the expression of SLC52A2 and clinical pathological features, as well as the prognosis was analyzed. The age, sex, clinical stage, pathological stage, and mRNA expression of SLC52A2 were analyzed by univariate and multivariate Cox analysis to search the prognostic factors of UM. Enrichment analyses were used to predict the possible regulatory pathway of SLC52A2 in UM.RESULTS: The survival prognosis of patients with low expression of SLC52A2 was better than that of patients with high expression of SLC52A2(P<0.05). The level of SLC52A2 has no significant correlation with the age, sex, clinical stage, and pathological stage of patients in both groups(P>0.05). Multivariate Cox analysis showed that the high expression of SLC52A2 was a risk factor for poor prognosis. The nomogram prediction model developed by combining the expression of SLC52A2 with clinical pathological features could accurately predict the survival probability of UM patients. The infiltration abundance of Th2 and Treg cells in both groups has difference(all P<0.001). GSEA analysis showed that the gene of JAK-STAT(FDR=0.028, P=0.004)and PI3K/AKT(FDR=0.017, P=0.002)were rich in samples with high expression of SLC52A2.CONCLUSION: The high expression of SLC52A2 is a risk factor for the prognosis of UM patients. SLC52A2 can be used as a biomarker to predict the prognosis and to become a new target for the treatment of patients with UM.
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【Objective】 To select and identify miRNA signatures to predict TMB level in gastric cancer based on The Cancer Genome Atlas (TCGA) database and machine learning methods. 【Methods】 MiRNA expression and somatic mutation profiles of gastric cancer (GC) were downloaded from TCGA database. R "limma" package was performed to select differentially expressed miRNAs between high-TMB and low-TMB groups. Two machine learning algorisms, random forest (RF), and Support Vector Machine-Recursive Feature Elimination were utilized to identify miRNAs with the highest discriminative ability. ROC was used to test the predictive ability of these signatures in multiple datasets. Besides, immune cells of different TMB levels were compared by the CIBERSORT method. 【Results】 A total of 56 differentially expressed miRNAs (DE-miRNAs) were filtered. Functional enrichment analysis showed that these DE miRNAs are mainly enriched in signaling pathways related to tumor occurrence and development as well as immunity-related biological processes. The RF and SVM-RFE algorithms jointly identified 10 diagnostic features of miRNAs, among which only hsa-miR-210-3p is considered the most relevant predictive biomarker for TMB classification. The AUC value of hsa-miR-210-3p in the training, testing, and total sets is 0.822, 0.721, and 0.793, respectively, and has been validated in other cancer types. Besides, CIBERSORT analysis suggests differences in immune cell infiltration between high- and low-TMB groups. Meanwhile, there is a significant positive correlation between the expression of immune checkpoint related genes and mismatch repair related genes and hsa-miR-210-3p. 【Conclusion】 This study successfully identified hsa-miR-210-3p as a predictive biomarker for TMB classification, which can effectively predict TMB values in gastric cancer and other cancer patients and may provide some guidance for immunotherapy.
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Objective @# To observe the clinical significance of miR-135b-5p in oral squamous cell carcinoma (OSCC) tissues and to conduct a bioinformatics analysis of its predicted target genes.@*Methods @#The expression levels of miR-135b-5p in OSCC tissues and adjacent normal tissues were compared using data from TCGA and GEO databases, and the correlations of miR-135b-5p expression level with clinicopathologic characteristics were analyzed. Fresh tissues were collected in the clinic, and the expression of miR-135b-5p was verified by quantitative real-time PCR. The target genes with enriched pathways were analyzed by using bioinformatics methods. A protein-protein interaction network was constructed to screen hub genes.@*Results @#The expression levels of miR-135b-5p were significantly upregulated in OSCC tissues compared to adjacent normal tissues (P < 0.001) and had a good diagnostic capability (AUC=0.960, P < 0.001). The expression level of miR-135b-5p was positively correlated with histopathological grading (P=0.011). Enrichment analyses revealed that the target genes of miR-135b-5p were significantly associated with tumor-related signaling pathways, such as the calcium signaling pathway, the cGMP-PKG signaling pathway and the cAMP signaling pathway. Ten core target genes were obtained by screening: DLG2, ANK3, ERBB4, SCN2B, NBEA, GABRB2, ATP2B2, SNTA1, CACNA1D, and SPTBN4.@*Conclusion@#miR-135b-5p may act as an oncogene miRNA in OSCC and has the potential value of acting as a diagnostic biomarker and therapeutic target for OSCC.
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To analyze the expression of splicing factors in gastric cancer using bioinformatics methods and investigate the effect of aberrantly expressed serine/arginine-rich splicing factor(SRSF10)on the phenotype of gastric cancer cells. The RNA-seq data of gastric cancer and paracancerous tissues were downloaded from The Cancer Genome Atlas(TCGA)cancer database,and bioinformatics analysis was performed to obtain the splicing factors differentially expressed in gastric cancer.The splicing factor SRSF10 was selected to investigate its effect on the development of gastric cancer.RNA interference technology was used to construct SRSF10 knockdown gastric cancer cells.MTS,Transwell,and cell scratches were used to study the effect of SRSF10 knockdown on gastric cancer cell phenotype. A total of 48 splicing factors were identified in gastric cancer by a series of bioinformatics techniques,of which 35 were up-regulated and 13 were down-regulated.The splicing factor SRSF10,which was up-regulated,was selected for further study.It was found that the gastric cancer cells after SRSF10 knockdown proliferated more slowly and had lower migration ability than normal gastric cancer cells. Multiple splicing factors are found in gastric cancer and may play an important role in the development of gastric cancer.The splicing factor SRSF10 may contribute to the pathogenesis of gastric cancer.
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Humans , Alternative Splicing , Cell Cycle Proteins , Computational Biology , Gene Expression Regulation, Neoplastic , RNA Splicing Factors , Repressor Proteins , Serine-Arginine Splicing Factors , Stomach NeoplasmsABSTRACT
OBJECTIVE@#The microRNA (miRNA) prognostic model can predict the prognosis of patients with oral squamous cell carcinoma (OSCC) on the basis of bioinformatics. Moreover, it can accurately group OSCC patients to improve targeted treatment.@*METHODS@#We downloaded the miRNA and mRNA expression profile and clinical data of OSCC from The Cancer Genome Atlas (TCGA). The risk score model of miRNA was screened and established by univariate and multivariate Cox regression models. The performance of this prognostic model was tested by receiver operating characteristic (ROC) curves and area under the curve (AUC). The target genes of six miRNAs were predicted and intersected with differential mRNA for enrichment analysis by Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway and gene ontology (GO) enrichment analysis. A protein protein interaction network (PPI) was constructed to screen hub genes.@*RESULTS@#By using univariate and multivariate Cox regression analyses, the prognostic risk model was obtained. The AUC of the ROC curve for predicting 5-year survival in the training group, test group, and whole cohort were 0.757, 0.673, and 0.724, respectively. Furthermore, univariate Cox regression and multivariate Cox regression considering other clinical factors showed that the six-miRNAs signature could serve as an independent prognostic factor (P<0.001). The top 10 hub genes in the PPI network screened by intersecting target genes include CCNB1, EGF, KIF23, MCM10, ITGAV, MELK, PLK4, ADCY2, CENPF, and TRIP13. EGF and ADCY2 were associated with survival prognosis (P<0.05).@*CONCLUSIONS@#The six-miRNAs signature could efficiently function as a novel and independent prognostic model for OSCC patients, which may be a new method to guide the accurate targeting treatment of OSCC.
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Humans , ATPases Associated with Diverse Cellular Activities , Biomarkers, Tumor , Carcinoma, Squamous Cell/genetics , Cell Cycle Proteins , Computational Biology , Head and Neck Neoplasms , MicroRNAs , Mouth Neoplasms/genetics , Prognosis , Squamous Cell Carcinoma of Head and NeckABSTRACT
Purpose: The cancer genome atlas (TCGA) is a comprehensive project supported by the National Cancer Institute (NCI) in the United States to explore molecular alterations in cancer, including uveal melanoma (UM). This led to TCGA classification for UM. In this report, we review the American Joint Committee on Cancer (AJCC) classification and TCGA classification for UM from the NCI's Center for Cancer Genomics (NCI CCG) (based on enucleation specimens [n = 80 eyes]) and from Wills Eye Hospital (WEH) (based on fine needle aspiration biopsy [FNAB] specimens [n = 658 eyes]). We then compare accuracy and predictability of AJCC versus (vs.) TCGA. Methods: Review of published reports on AJCC and TCGA classification for UM was performed. Outcomes based on AJCC 7th and 8th editions were assessed. For TCGA, UM was classified based on chromosomes 3 and 8 findings including disomy 3 (D3), monosomy 3 (M3), disomy 8 (D8), 8q gain (8qG), or 8q gain multiple (8qGm) and combined into four classes including Class A (D3/D8), Class B (D3/8qG), Class C (M3/8qG), and Class D (M3/8qGm). Outcomes of metastasis and death were explored and a comparison (AJCC vs. TCGA) was performed. Results: In the NCI CCG study, there were 80 eyes with UM sampled by enucleation (n = 77), resection (n = 2), or orbitotomy (n = 1) and analysis revealed four distinct genetic classes. Metastasis and death outcomes were subsequently evaluated per class in the WEH study. The WEH study reviewed 658 eyes with UM, sampled by FNAB, and found Class A (n = 342, 52%), B (n = 91, 14%), C (n = 118, 18%), and D (n = 107, 16%). Comparison by increasing class (A vs. B vs. C vs. D) revealed older mean patient age (P < 0.001), worse entering visual acuity (P < 0.001), greater distance from the optic disc (P < 0.001), larger tumor diameter (P < 0.001), and greater tumor thickness (P < 0.001). Regarding outcomes, more advanced TCGA class demonstrated increased 5-year risk for metastasis (4% vs. 20% vs. 33% vs. 63%,P < 0.001) with corresponding increasing hazard ratio (HR) (1.0 vs. 4.1, 10.1, 30.0,P= 0.01 for B vs. A andP < 0.001 for C vs. A and D vs. A) as well as increased 5-year estimated risk for death (1% vs. 0% vs. 9% vs. 23%,P < 0.001) with corresponding increasing HR (1 vs. NA vs. 3.1 vs. 13.7,P= 0.11 for C vs. A andP < 0.001 for D vs. A). Comparison of AJCC to TCGA classification revealed TCGA was superior in prediction of metastasis and death from UM. Conclusion: TCGA classification for UM is simple, accurate, and highly predictive of melanoma-related metastasis and death, more so than the AJCC classification.
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BACKGROUND: Venous thromboembolism is a common complication in patients with glioma. The clotting factor von Willebrand factor (VWF) is a highly adhesive procoagulant molecule that mediates platelet adhesion to endothelial and subendothelial surfaces. In the current analysis, we examined The Cancer Genome Atlas (TCGA) data to assess the VWF gene in patients with lower grade gliomas. METHODS: For newly diagnosed gliomas, we evaluated the association between VWF and overall survival in the Genomic Data Commons TCGA Lower Grade Glioma (LGG) dataset in TCGA. Simple statistics were calculated to identify patterns of mutual exclusivity or co-occurrence of VWF mutations. For each pair of query genes an odds ratio was calculated that indicates the likelihood that the mutations in the two genes are mutually exclusive or co-occurrent across the selected cases. To determine whether the identified relationship was significant for a gene pair, Fisher's exact test was performed. RESULTS: Lower grade gliomas with less VWF gene expression had significantly better survival than those with more VWF gene expression (hazard ratio 0.64, 95% confidence interval 0.44 to 0.92, p=0.015 log rank test). When we analyzed the data with Cox regression, VWF expression had a significant effect on survival (p=0.02) that was unrelated to the effect of IDH1 expression (p=0.062), TP53 expression (p=0.135), independent of ATRX expression (p=0.021) and histology (astrocytoma versus oligoastrocytoma and oligodendroglioma, p=0.002). VWF mutations significantly co-occur with mutations in TP53 and ATRX (p<0.001). CONCLUSION: The deleterious prognostic effect of VWF expression and its co-occurrent mutations with TP53 and ATRX in lower grade gliomas are not surprising, given VWF's role in other cancers. Therefore, VWF gene expression may be a clinically important risk marker in lower grade glioma.
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Humans , Adhesives , Blood Platelets , Dataset , Gene Expression , Genes, vif , Genome , Glioblastoma , Glioma , Odds Ratio , Oligodendroglioma , Venous Thromboembolism , von Willebrand FactorABSTRACT
Objective To screen the metabolic associated genes (MAG) that are related to the survival of colorectal cancer (CRC) patients, investigate the relationship between the expression of dihydrolipoamide S-acetyltransferase (DLAT) and clinical significance and prognosis value in CRC, and establish the DLAT co-expression molecular regulatory network. Methods The cancer genome atlas (TCGA) database combined with whole genome transcript sequencing data and clinical case data were used to do the survival analysis of candidate MAG; The DLAT expression in CRC and the relationship between the expression level and pathological characteristics and prognosis of CRC patients were analyzed through GEO database, Oncomine and KM-plotter platforms. The DLAT co-expression gene lists were searched in cBioPortal and STRING to analyze functional clustering and pathway enrichment, and establish the DLAT co-expression molecular regulatory network. Results Survival analysis in multiple databases indicated that DLAT was the most relevant gene in candidate MAGs for survival in CRC patients (P0.05). Functional clustering of DLAT co-expression genes showed that DLAT was involved in the biological process including mitotic cell cycle, prolong and termination of mitochondrial protein translation, none-coding RNA metabolism and DNA conformation change. Pathway enrichment revealed that DLAT participated in the pathways including tricarboxylic acid cycle, oxidative phosphorylation and pyruvate metabolism. DLAT co-expression molecular regulatory network was established and 10 nodes with the highest connectivity were obtained as follows: PAICS, MAD2L1, HSPD1, GART, CS, RRM1, MRPL3, BUB1, CCNB1 and CHEK1. Conclusions The expression of metabolic gene DLAT in colorectal cancer is high, but the expression is lower in advanced colorectal cancer than in early colorectal cancer, and the prognosis is poor in patients with low expression, the TNM stage is late, and lymph node metastasis is more likely to occur in patients with advanced colorectal cancer. This finding lays a foundation for the research and application of potential molecular markers related to metabolism in colorectal cancer.
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Objective Fibronectin 1 (FN1) is a glycoprotein involved in cellular adhesion and migration processes. The aim of this study was to investigate the expression and clinicopathological significance of FN1 in gastric cancer and to predict the possible mechanism of FN1. Methods GEO data and TCGA data were downloaded. FN1 expression in gastric cancer and adjacent tissues was analyzed by GSE54129 data, and then verified by GSE29272 and TCGA data. According to the expression profile data and FN1 expression, mRNA expression value was divided into low expression(<-0.475), and medium expression(-0.475~1.036), high expression (>1.036). FN1 expression in gastric cancer and clinicopathological relationship were analyzed. TCGA data and Kaplan Meier were used to analyze the relationship between the expression level of FN1 and the prognosis of gastric cancer patients; while gene concentration analysis (GSEA) was used to predict the related path of FN1. Results TCGA data showed the medium survival time of low, medium, high FN1 expression was respectively 63.5, 55.7, 39.4 months, and the difference between low expression and high expression in survival time was of statistical significance. Kaplan Meier Plotter online data analysis showed the medium survival time of FN1 high expression was shorter than that of low expression(P<0.01), which meant the higher the FN1 expression was, the worse the prognosis was. FN1 expression is an independent prognostic factor (HR=0.480,95% CI:0.336~0.686). High expression of FN1 samples enriched gene sets such as KRAS (FDR=0.052), P53(FDR=0.052), TGF-β(FDR=0.052), cell adhesion(FDR=0.0), extracellular matrix (FDR=0.043)and cytoskeletal protein regulation (FDR=0.052). Conclusion The high expression of FN1 is a poor prognostic factor for gastric cancer and can be used as an effective biomarker for predicting the metastasis and prognosis of gastric cancer. High expression of FN1 leads to abnormalities in KRAS, P53, TGF-β, ECM, cell adhesion and cytoskeletal protein regulatory pathways.
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Objective The objective of this study was to analyze the expression of ubiquitin -conjugating enzyme E2T (UBE2T)in primary liver cancer and its relationship with clinicopathological parameters and prognosis of patients with liver cancer. Methods The second generation sequencing data and clinical pathological data of UBE2T gene mRNA in normal liver tissues and liver cancer tissues were downloaded from the Cancer Genome Atlas(TCGA)database. The expression of UBE2T in cancer tissues and normal tissues was analyzed to elucidate the relationship between UBE2T at mRNA level and clinicopathological parameters of patients with liver cancer. Kaplan-Meier was used for prognostic analysis. The Cox proportional hazard regression model was performed for the multivariate analysis of the prognostic factors associated with HCC. Based on the results of gene set enrichment analysis(GSEA), UBE2T was involved in the possible regulating pathways of HCC development. Results The expression of UBE2T at mRNA level in hepatocarcinoma tissues was significantly higher than that in adjacent tissues(P<0. 01). The high expression of UBE2T was closely related to pathological grade,TNM staging,and vascular invasion(P<0. 01),suggesting a poor prognosis of patients with liver cancer. Multivariate Cox regression analysis showed that TNM staging,vascular invasion and UBE2T expression were independent risk factors affecting the prognosis of patients with liver cancer. Conclusion The high expression of UBE2T is significantly associated with the clinicopathological factors and prognosis of patients with liver cancer. It can be used as a potential marker for predicting the prognosis of liver cancer patients and a target for tumor therapy.
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To evaluate the differential expression profiles of the lncRNAs, miRNAs, mRNAs and ceRNAs, and their implication in the prognosis in clear cell renal cell carcinoma (CCRCC), the large sample genomics analysis technologies were used in this study. The RNA and miRNA sequencing data of CCRCC were obtained from The Cancer Genome Atlas (TCGA) database, and R software was used for gene expression analysis and survival analysis. Cytoscape software was used to construct the ceRNA network. The results showed that a total of 1 570 lncRNAs, 54 miRNAs, and 17 mRNAs were differentially expressed in CCRCC, and most of their expression levels were up-regulated (false discovery rate 2). The ceRNA regulatory network showed the interaction between 89 differentially expressed lncRNAs and 9 differentially expressed miRNAs. Further survival analysis revealed that 38 lncRNAs (including COL18A1-AS1, TCL6, LINC00475, UCA1, WT1-AS, HOTTIP, PVT1, etc.) and 2 miRNAs (including miR-21 and miR-155) were correlated with the overall survival time of CCRCC ( < 0.05). Together, this study provided us several new evidences for the targeted therapy and prognosis assessment of CCRCC.
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Humans , Carcinoma, Renal Cell , Genetics , Kidney Neoplasms , Genetics , MicroRNAs , Genetics , RNA, Long Noncoding , Genetics , TranscriptomeABSTRACT
Tumor-specific gene mutations might generate suitable neoepitopes for cancer immunotherapy that are highly immunogenic and absent in normal tissues. The high heterogeneity of the tumor genome poses a big challenge for precision cancer immunotherapy. Mutations characteristic of each tumor can help to distinguish it from other tumors. Based on these mutations' characteristic, it is possible to develop immunotherapeutic strategies for specific tumors. In this study, a tumor neoantigen prediction scheme was proposed, in which both the intracellular antigen presentation process and the ability to bind with extracellular MHC molecule were taken into consideration. The overall design is meritorious and may help reduce the cost for validation experiments compared with conventional methods. This strategy was tested with several cancer genome datasets in the TCGA database, and a number of potential tumor neoantigens were predicted for each dataset. These predicted neoantigens showed tumor type specificity and were found in 20% to 70% of cancer patients. This scheme might prove useful clinically in future.
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Humans , Antigens, Neoplasm , Computational Biology , Genome, Human , Immunotherapy , Mutation , NeoplasmsABSTRACT
OBJECTIVE: To assess whether radiomics features derived from multiparametric MRI can predict the tumor grade of lower-grade gliomas (LGGs; World Health Organization grade II and grade III) and the nonenhancing LGG subgroup. MATERIALS AND METHODS: Two-hundred four patients with LGGs from our institutional cohort were allocated to training (n = 136) and test (n = 68) sets. Postcontrast T1-weighted images, T2-weighted images, and fluid-attenuated inversion recovery images were analyzed to extract 250 radiomics features. Various machine learning classifiers were trained using the radiomics features to predict the glioma grade. The trained classifiers were internally validated on the institutional test set and externally validated on a separate cohort (n = 99) from The Cancer Genome Atlas (TCGA). Classifier performance was assessed by determining the area under the curve (AUC) from receiver operating characteristic curve analysis. An identical process was performed in the nonenhancing LGG subgroup (institutional training set, n = 73; institutional test set, n = 37; and TCGA cohort, n = 37) to predict the glioma grade. RESULTS: The performance of the best classifier was good in the internal validation set (AUC, 0.85) and fair in the external validation set (AUC, 0.72) to predict the LGG grade. For the nonenhancing LGG subgroup, the performance of the best classifier was good in the internal validation set (AUC, 0.82), but poor in the external validation set (AUC, 0.68). CONCLUSION: Radiomics feature-based classifiers may be useful to predict LGG grades. However, radiomics classifiers may have a limited value when applied to the nonenhancing LGG subgroup in a TCGA cohort.
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Humans , Cohort Studies , Genome , Glioma , Machine Learning , Magnetic Resonance Imaging , ROC Curve , World Health OrganizationABSTRACT
PURPOSE: We investigated B-cell lymphoma 2 (BCL2) regulation across DNA, RNA, protein, and methylation status according to molecular subtype of breast cancer using The Cancer Genome Atlas (TCGA) database. MATERIALS AND METHODS: We analyzed clinical and biological data on 1,096 breast cancers from the TCGA database. Biological data included reverse phase protein array (RPPA), mRNA sequencing (mRNA-seq), mRNA microarray, methylation, copy number alteration linear, copy number alteration nonlinear, and mutation data. RESULTS: The luminal A and luminal B subtypes showed upregulated expression of RPPA and mRNAseq and hypomethylation compared to the human epidermal growth factor receptor 2 (HER2) and triple-negative subtypes (all p < 0.001). No mutations were found in any subjects. High mRNA-seq and high RPPA were strongly associated with positive estrogen receptor, positive progesterone receptor (all p < 0.001), and negative HER2 (p < 0.001 and p=0.002, respectively). Correlation analysis revealed a strong positive correlation between protein and mRNA levels and a strong negative correlation between methylation and protein and mRNA levels (all p < 0.001). The high BCL2 group showed superior overall survival compared to the low BCL2 group (p=0.006). CONCLUSION: The regulation of BCL2 was mainly associated with methylation across the molecular subtypes of breast cancer, and luminal A and luminal B subtypes showed upregulated expression of BCL2 protein, mRNA, and hypomethylation. Although copy number alteration may have played a minor role, mutation status was not related to BCL2 regulation. Upregulation of BCL2 was associated with superior prognosis than downregulation of BCL2.
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Humans , Breast Neoplasms , Breast , DNA , Down-Regulation , Estrogens , Gene Expression Regulation , Genome , Lymphoma, B-Cell , Methylation , Phenobarbital , Prognosis , Protein Array Analysis , ErbB Receptors , Receptors, Progesterone , RNA , RNA, Messenger , Up-RegulationABSTRACT
Human tongue cancer (TC) is an aggressive malignancy with a very poor prognosis.There is an urgent need to elucidate the underlying molecular mechanisms involved in TC progression.mRNA expression profiles play a vital role in the exploration of cancer-related genes.Therefore,the purpose of our study was to identify the progression associated candidate genes of TC by bioinformatics analysis.Five microarray datasets of TC samples were downloaded from the Gene Expression Omnibus (GEO) database and the data of 133 TC patients were screened from The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSC) database.The integrated analysis of five microarray datasets and the RNA sequencing data of TC samples in TCGA-HNSC was performed to obtain 1023 overlapping differentially expressed genes (DEGs) in TC and adjacent normal tissue (ANT) samples.Next,Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to enrich the significant pathways of the 1023 DEGs and PI3K-Akt signaling pathway (P=0.011) was selected to be the candidate pathway.A total of 23 DEGs with |log2 fold change (FC)｜ ≥1.0 in phosphatidylinositol 3-kinase-serine/threonine kinase (PI3K-Akt) signaling pathway were subjected to survival analysis of 125 eligible TC samples in TCGA database,indicating increased integrin-α3 gene (ITGA3) expression was significantly associated with poorer prognosis.Taken together,our study suggested ITGA3 may facilitate the development of TC via activating PI3K-Akt signaling pathway.
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Human tongue cancer (TC) is an aggressive malignancy with a very poor prognosis.There is an urgent need to elucidate the underlying molecular mechanisms involved in TC progression.mRNA expression profiles play a vital role in the exploration of cancer-related genes.Therefore,the purpose of our study was to identify the progression associated candidate genes of TC by bioinformatics analysis.Five microarray datasets of TC samples were downloaded from the Gene Expression Omnibus (GEO) database and the data of 133 TC patients were screened from The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSC) database.The integrated analysis of five microarray datasets and the RNA sequencing data of TC samples in TCGA-HNSC was performed to obtain 1023 overlapping differentially expressed genes (DEGs) in TC and adjacent normal tissue (ANT) samples.Next,Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to enrich the significant pathways of the 1023 DEGs and PI3K-Akt signaling pathway (P=0.011) was selected to be the candidate pathway.A total of 23 DEGs with |log2 fold change (FC)｜ ≥1.0 in phosphatidylinositol 3-kinase-serine/threonine kinase (PI3K-Akt) signaling pathway were subjected to survival analysis of 125 eligible TC samples in TCGA database,indicating increased integrin-α3 gene (ITGA3) expression was significantly associated with poorer prognosis.Taken together,our study suggested ITGA3 may facilitate the development of TC via activating PI3K-Akt signaling pathway.
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AIM:To investigate the clinical characteristics of microRNA(miR)-196b in colorectal cancer(CRC)and to study its biological function in 5-fluorouracil(5-FU)resistance.METHODS:miRNA sequence dataset and the corresponding clinical data of CRC patients were downloaded from The Cancer Genome Atlas(TCGA).Expression level and clinical characteristics of miR-196b in CRC patients were analyzed using SPSS 17.0.CRC cell line overexpres-sing miR-196b was established using transient transfection method.MTS test was used to evaluate the effect of miR-196b overexpression on 5-FU resistance.RESULTS:miR-196b expression was associated with lymph node metastasis and TNM stage(P<0.05),but not related with age and sex.Lymph node metastasis and distant metastasis were independent prog-nostic factors for rectal patients(P<0.05).The expression level of miR-196b was not associated with survival condition of rectal patients.The viability of the cells overexpressing miR-196b treated with different concentrations of 5-FU was signifi-cantly higher than that in control group(P<0.05).CONCLUSION:miR-196b may be a potential biomarker of TNM stage and lymph node metastasis in CRC.miR-196b increases the 5-FU resistance of CRC cells.
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Objective To identify genes associated with prognosis or differentiated type in gastric cancer from fre quently mutated genes or highly-expressed genes,using large-scale genomic data from The Cancer Genome Atlas.Methods The somatic mutation data,RNAseqV2 data and clinical information were downloaded from the TCGA website.The frequency of deleterious somatic mutations for each gene was counted to select the frequently mutated genes.DESeq2 was used to analyze the gene expression data.Then survival analysis was performed on genes highlyexpressed in the tumor tissue.Kaplan-Meier curves were generated by R-survival package,and significance was evaluated by log-rank test.Results The frequency for pathogenic mutations in PIK3CA and APC was significantly discordant between different grades of gastric cancer.2 040 genes were up-regulated in tumor tissue,while 2 357 genes were down-regulated.Among the up-regulated genes,7 genes were associated with poor prognosis of gastric cancer and one was associated with better prognosis.Conclusions Genes associated with differentiation types or prognosis in gastric cancer are identified.The result may clue us future research on potential prognostic markers in clinical treatment.
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Objective To investigate the prognostic significance of bone morphogenetic protein 2 (BMP2) expression in glioblastoma multiforme (GBM) and related pathways.Methods RNASeqV2 data and GSE7696 series matrix data were downloaded from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database,respectively.The correlation between BMP2 expression and prognosis was evaluated using Kaplan-Meier and multivariate COX analysis.Gene set enrichment analysis (GSEA) was used to predict the functional gene sets and/or pathways modulated by BMP2.Results Decreased expression of BMP2 is an independent predictor of poor prognosis.Furthermore,genes that are upregulated in response to interferon-α proteins were enriched in samples with low BMP2 expression.Conclusion Low expression of BMP2 indicates poor prognosis in GBM patients.Genes that are upregulated in response to interferon-α proteins may also be implicated in prognosis.
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Esophageal cancer is a common malignant tumor,whose pathogenesis and prognosis factors are not fully understood.This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer.The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas (TCGA),and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma.The result showed that 12 modules were associated with one or more survival data such as recurrence status,recurrence time,vital status or vital time.Furthemaore,survival analysis showed that 5 out of the 12 modules were related to progression-free survival (PFS) or overall survival (OS).As the most important module,the midnight blue module with 82 genes was related to PFS,apart from the patient age,tumor grade,primary treatment success,and duration of smoking and tumor histological type.Gene ontology enrichment analysis revealed that "glycoprotein binding" was the top enriched function of midnight blue module genes.Additionally,the blue module was the exclusive gene clusters related to OS.Platelet activating factor receptor (PTAFR) and feline Gardner-Rasheed (FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database.In conclusion,our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.