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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 detect the expression of N6-methyladenosine (m 6A) regulators in colorectal tumor samples and its clinical significance. Methods:From September to December 2021, the data regarding the expression of m 6A regulators in colorectal tumor samples were collected using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and the expression of m 6A regulators was compared between different clinical pathological characteristics and between different molecular subtypes. Survival analysis was conducted in patients with colorectal cancer with different m 6A expression levels. Results:In TCGA, insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1), insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3), and YTH N6-methyladenosine RNA binding protein 1 (YTHDF1) were higher in colorectal tumor samples than normal tissue samples (TCGA-COAD: IGF2BP3: 12.80 vs. 204.46, logFC = 4.00, P = 0.003; YTHDF1: 2 347.56 vs. 3712.77, logFC = 0.66, P < 0.001; TCGA-READ: IGF2BP1: 6.20 vs. 359.32, logFC = 5.82, P = 0.007; YTHDF1: 2 470.10 vs. 4 369.09, logFC = 0.82, P = 0.020). The intersection of TCGA and GEO databases showed that methyltransferase like 14 (METTL14), YTH domain m 6A RNA binding protein 3 (YTHDF3), and α-ketoglutarate dependent dioxygenase AlkB homolog 5 (ALKBH5) were downregulated in colorectal tumor samples compared with normal tissue samples (TCGA-COAD: METTL14: 1 051.56 vs. 711.40, logFC = -0.56, P < 0.001; YTHDF3:4 613.85 vs. 3 155.05, logFC = -0.55, P < 0.001, ALKBH5: 4 250.10 vs. 2 555.55, logFC = -0.73, P < 0.001; TCGA-READ vs. METTL14: 1 113.3 vs. 674.36, logFC = -0.72, P < 0.001; YTHDF3: 5 034.30 vs. 3 331.95, logFC = -0.60, P = 0.004; ALKBH5: 4 902.20 vs. 2 529.71, logFC = -0.95, P < 0.001; GEO-CRC vs. METTL14: 6.58 vs. 6.33, logFC = -0.06, P < 0.001; YTHDF3: 6.28 vs. 6.20, logFC = -0.02, P = 0.002; ALKBH5: 5.07 vs. 4.98, logFC = -0.02, P < 0.001). In colorectal tumor samples of different molecular subtypes, IGF2BP2, HNRNPC, TP53 and YTHDF2 expression was low in KRAS (IGF2BP2: 48.53 vs. 44.04, t = 2.64, P = 0.008; HNRNPC: 121.30 vs. 112.60, t = 2.32, P = 0.020; TP53: 65.30 vs. 60.26, t = 2.11, P = 0.034; YTHDF2: 54.07 vs. 51.19; t = 1.97, P = 0.048). Different clinical pathological characteristics showed that IGF2BP1 was higher in colorectal cancer with positive lymph nodes (8.97 vs. 6.11, W = 20 008, P = 0.002), distant metastasis (8.94 vs. 6.41, W = 19 104, P = 0.009), or stage Ⅲ-Ⅳ (7.46 vs. 7.13, W = 8 779, P = 0.025) than normal tissue. ALKBH5 overexpression, advanced age, presence of vascular invasion, and late pathological staging were significantly related to a short survival period (high ALKBH5 expression vs. low ALKBH5 expression: 5.85 years vs. not available, HR: 1.63, 95% CI: 1.071-2.491, P = 0.021; > 68 years vs. < 68 years: 6.78 years vs. not available, HR: 1.59, 95% CI: 1.049-2.422, P = 0.047; stage Ⅲ-Ⅳ vs. stage Ⅰ-Ⅱ: 4.55 years vs. 8.33 years, HR: 2.89, 95% CI: 1.895-4.425, P < 0.001; presence of vein invasion vs. absence of vein invasion: 5.48 years vs. not available, HR: 2.82, 95% CI: 1.672-4.783, P < 0.001). Conclusion:Some of the m 6A regulators are associated with the biological characteristics and prognosis of colorectal cancer.
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Objective: To investigate the expression and significance of protease activated receptor 2 (PAR2) in ovarian epithelial carcinoma. Methods: PAR2 mRNA expression levels in 410 cases of epithelial ovarian carcinoma and 88 cases of human normal ovary were analyzed from cancer Genome Atlas (TCGA) database and tissue genotypic expression database (GTEx). Immunohistochemical (IHC) staining of PAR2 protein was performed in 149 patients with ovarian cancer who underwent primary surgical treatment at Cancer Hospital of Chinese Academy of Medical Sciences. Then the relationship between mRNA/protein expression of PAR2 and clinicopathological features and prognosis was analyzed. Gene functions and related signaling pathways involved in PAR2 were studied by enrichment analysis. Results: The mRNA expression of PAR2 in epithelial ovarian carcinoma was significantly higher than that in normal ovarian tissue (3.05±0.72 vs. 0.33±0.16, P=0.004). There were 77 cases showing positive and 19 showing strong positive of PAR2 IHC staining among the 149 patients, accounting for 64.4% in total. PAR2 mRNA/protein expression was closely correlated with tumor reduction effect and initial therapeutic effect (P<0.05). Survival analysis showed that the progression free survival time (P=0.033) and overall survival time (P=0.011) in the group with high PAR2 mRNA expression was significantly lower than that in the low PAR2 mRNA group. Multivariate analysis showed tumor reduction effect, initial therapeutic effect were independent prognostic factors on both progression-free survival and overall survival (P<0.05). The progression-free survival (P=0.016) and overall survival (P=0.038) of the PAR2 protein high expression group was significantly lower than that of the low group. Multivariate analysis showed PAR2 expression, initial treatment effect and chemotherapy resistance were independent prognostic factors on both progression-free survival and overall survival (P<0.05). Based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), PAR2 target genes were mainly enriched in function related to intercellular connection, accounting for 40%. Gene enrichment analysis (GSEA) showed that the Wnt/β-catenin signaling pathway (P=0.023), the MAPK signaling pathway (P=0.029) and glycolysis related pathway (P=0.018) were enriched in ovarian cancer patients with high PAR2 mRNA expression. Conclusions: PAR2 expression is closely related to tumor reduction effect, initial treatment effect and survival of ovarian cancer patients. PAR2 may be involved in Wnt/β-catenin signaling pathway and intercellular connection promoting ovarian cancer invasion and metastasis.
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Female , Humans , Carcinoma, Ovarian Epithelial , Receptor, PAR-2 , Ovarian Neoplasms/pathology , Prognosis , RNA, Messenger/metabolismABSTRACT
【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 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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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 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 level and clinical significance of ALDH5A1 in ovarian cancer (OC) tissues, as well as to explore the possible mechanism associated with the invasion and migration of OC cells. Methods We initially compared ALDH5A1 expression in metastatic tissues and the primary site of OC based on the GEO database. Then, wound-healing and Transwell assays were utilized to determine the biological role of OC cells transfected with ALDH5A1 siRNA. To unravel the potential mechanism of ALDH5A1 meditating the metastasis of OC, the coexpression profile of ALDH5A1 in OC cell lines and OC patients were generated using cBioPortal. Moreover, the TCGA and GEO databases were used to analyze the relationship between ALDH5A1 expression and the prognosis of OC patients. The HPA database was further used to confirm the relative expression of ALDH5A1 and MMPs in OC patients. Results ALDH5A1 expression was downregulated in metastatic tissues compared with the primary site of OC, and ALDH5A1 knockdown promoted the malignant behavior of OC cells. Additionally, the coexpression profile of ALDH5A1 was significantly enriched in the extracellular matrix (ECM) organization pathway. Western blot assay further confirmed that the expression of MMP, which played an important role in the ECM pathway, was negatively correlated with ALDH5A1 expression in OC. These results indicated that ALDH5A1 may participate in the metastasis and invasion of OC via the ECM organization pathway. Finally, KM survival plots revealed that the survival rates of OC patients with lower ALDH5A1 expression were obviously lower. Conclusion ALDH5A1 downregulation may promote the tumor metastasis and contribute to poor prognosis in OC.
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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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Mitochondria are dynamic organelles that continuously divide and fuse. In recent years, in addition to the studies related to mitochondrial metabolism, the unique dynamics of mitochondria have gradually attracted researchers' attention. A growing body of research has revealed that mitochondrial dynamics are related to the biological behavior of tumor cells. Mitochondrial fission proteins (mitochondrial fission protein 1, FIS1) mediate the assembly of mitochondrial fission complexes and participate in the execution of mitochondrial fission. They are important proteins in the process of mitochondrial fusion and fission. However, few studies have revealed the expression and role of FIS1 in human cervical cancer. In this study, the expression level of FIS1 in human cervical cancer tissues and paracancer tissues were compared. The results showed that the level of FIS1 mRNA in human cervical cancer tissues was significantly lower than that in paracancer tissues (P<0. 01). Further KEGG pathway and GO Term-BP pathway analysis showed that the differential genes are mainly related to mitochondrial biological functions. Subsequently, HeLa cells with overexpressed FIS1 were investigated for their proliferation, migration, mitochondrial fission and ROS levels. The experimental results showed that FIS1 overexpression decreased HeLa cell proliferation and migration ability, enhanced mitochondrial fission and higher ROS levels. In conclusion, the expression of FIS1 in human cervical cancer cells was attenuated, while overexpression of FIS1 resulted in a series of abnormal biological functions in human cervical cancer cells. Further studies can be carried out to investigate the role of FIS1 in the treatment of human cervical 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 investigate the application value of the human B cell-confinement receptor P2RY8 in the diagnosis and prognosis of hepatocellular carcinoma (HCC) and its association with tumor immunity. Methods The Cancer Genome Atlas database was used to compare the expression of P2RY8. R software package was used to analyze the correlation between P2RY8 and tumor staging, and the receiver operating characteristic (ROC) curve and a nomogram model were established for diagnosis and survival. Tumor Immune Evaluation Resource was used to analyze immune cell infiltration, immune cell biomarkers, and immune checkpoints. STRING database was used to analyze protein-protein interaction network information. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to analyze the function of P2RY8 and its interacting genes. For the purpose of validation, HCC tissue samples were collected from 64 patients who underwent radical surgery for HCC from June 2007 to November 2008, and the corresponding adjacent tissue samples were collected from 35 patients out of these patients (tissue chips were purchased from Shanghai Outdo Biotech Co., Ltd.); related clinical data and follow-up data were analyzed, and immunohistochemistry was used to measure the expression of P2RY8 in HCC and adjacent tissue samples. The t -test was used for comparison of normally distributed continuous data between two groups; the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups, and the Kruskal-Wallis H test was used for comparison between multiple groups. The chi-square test was used for comparison of categorical data between two groups. A Spearman correlation analysis was used to investigate the correlation between two variables. The Kaplan-Meier method was used to plot survival curves, and the log-rank test was used to calculate survival rates. Results P2RY8 was overexpressed in HCC, and the expression level of P2RY8 could accurately differentiate tumor from normal tissue, with an area under the ROC curve of 0.794. The patients with a higher expression level of P2RY8 tended to have a better prognosis ( P =0.005). The data from 64 clinical samples also confirmed that compared with the patients with a low expression level of P2RY8, the patients with a high expression level of P2RY8 had significantly higher 3-year survival rate (78.9% vs 46.2%, P =0.007), 5-year survival rate (76.3% vs 38.5%, P =0.002), and overall survival time [92.5 (48.8-102.0) months vs 33.0 (25.0-95.5) months, P =0.022], and the Kaplan-Meier survival curve further indicated that the expression level of P2RY8 was associated with the prognosis of HCC patients. In addition, P2RY8 was positively correlated with immune cell infiltration and immune checkpoint in HCC. The GO/KEGG pathway enrichment analyses showed that P2RY8 was enriched in the signal transduction pathways such as humoral immunity and cellular immunity. Conclusion P2RY8 participates in the development, progression, and immune regulation of HCC, and therefore, P2RY8 can serves as a potential biomarker and a therapeutic target for the diagnosis and prognosis of HCC.
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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 identify the potential prognostic biomarkers of the immune-related genes signature for patients with hepatocellular carcinoma (HCC). Methods Original HCC data were downloaded from TCGA, and the immune activity of each sample was calculated by ssGSEA. HCC samples were divided into high and low immune cell infiltration groups by "GSVA" package and "hclust" package. The ESTIMATE algorithm scored the tumor microenvironment in each HCC sample. The "limma" package and Venn diagram identified effective immune-related genes. Univariate Cox, Lasso regression and multivariate Cox regression analyses were used to explore key genes. The "rms" package was used to create nomograms and draw calibration curves. Results Compared with the high immune cell infiltration group, the tumor purity of the samples in the low immune cell infiltration group was higher, the immune score, ESTIMATE score and stromal score were lower. In the high immune cell infiltration group, the immune components were more abundant, and the expression levels of TIGIT, PD-L1, PD-1, LAG3, TIM-3, CTLA4 and HLA family were higher. Multivariate Cox regression analysis showed that four immune-related genes (S100A9, HMOX1, IL18RAP and FCER1G) were used to construct the prognosis model. Compared with other clinical features, the risk score of this prognostic model was recognized as an independent prognostic factor. Conclusion This study identified the immune-related core genes which may be used in targeted therapy and immunotherapy of HCC.
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Objective To construct a prognostic model of laryngeal cancer based on pyroptosis-related lncRNAs. Methods Transcriptome expression and clinical data of patients with laryngeal cancer were downloaded from TCGA database. Differentially-expressed pyroptosis-related lncRNAs were selected using Wilcox rank sum test and Spearman correlation analysis. LncRNAs associated with patients' prognosis were further selected using univariate Cox analysis (P < 0.05), and a prognostic model was established using multivariate Cox regression. ROC curve was used to assess the sensitivity and specificity of this model. Results There were a total of 483 differentially-expressed pyroptosis-related lncRNAs in laryngeal cancer tissues, compared with normal laryngeal tissues (|logFC|≥1, FDR < 0.05). Univariate Cox analysis showed that 23 differentially-expressed lncRNAs were associated with prognosis. Multivariate Cox regression analysis finally obtained a prognostic model based on 10 lncRNAs for predicting the survival of laryngeal carcinoma patients. AUC showed that the model had a good predictive ability (AUC > 0.8). Conclusion Pyroptosis-related lncRNAs can be used to predict the prognosis of patients with laryngeal cancer.
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Objective To investigate the expression and prognostic value of FOXO1 gene in liver cancer tissues based on TCGA and HPA databases. Methods The RNA-seq data of FOXO1 gene in liver cancer were downloaded from TCGA. The difference of FOXO1 gene expression between tumor and adjacent tissues was obtained via R software. The correlation between FOXO1 and clinicopathological features of liver cancer patients was analyzed. Survival analysis was carried out to evaluate the prognostic significance of FOXO1 gene expression in liver cancer patients. Univariate and multivariate Cox analyses were performed to explore prognostic factors. The correlation between FOXO1 expression and TIICs in tumor microenvironment was performed by CIBERSORT. KEGG pathways enrichment analysis was performed for the potential function of FOXO1 gene in liver cancer. Results FOXO1 was downregulated in liver cancer tissues compared with normal tissues (P=1.321E-15). Survival analysis showed that high expression of FOXO1 was positively associated with favorable OS of liver cancer patients (P < 0.05). Clinical stage, T and M stages could be prognostic indicators while FOXO1 wasn't an independent prognostic factor in patients with liver cancer. In TME of liver cancer, the expression of FOXO1 was positively correlated with resting memory CD4 T cells and naive B cells while negatively related to activated memory CD4 T cells and macrophages M2. GSEA identified that FOXO1 participated in multiple cancer-related pathways. Conclusion FOXO1 is down-regulated in liver cancer tissues, and its expression level is associated with OS of patients. FOXO1 might be a biomarker related to the prognosis of liver cancer patients and is expected to be a target for diagnosis and treatment of liver cancer.
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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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Objective:To study the relationship between differential expression of immune-related genes in breast cancer and tumor prognosis, and to find potential immunotherapy targets.Methods:Breast cancer transcriptome and the clinical data corresponding to the patient were downloaded from the TCGA database, bioinformatics methods were used to screen out the differentially expressed genes in cancer tissues, ImmPort database was combined to screen out the immunity closely related to the overall survival of the patient Gene, and COX regression was used to construct a risk scoring model for prognostic evaluation and evaluates its predictive ability.Results:A total of 2499 differentially expressed genes were found in breast cancer and adjacent tissues, and 138 differentially expressed immune-related genes were further screened. Single-factor COX analysis showed that 9 immune genes were related to prognosis, and multi-factor COX analysis screened 6 immune-related genes as independent risk factors for prognosis to construct a risk scoring model. COX regression analysis of clinical characteristics showed that the patient's risk value was an independent prognostic factor ( P<0.05) . Conclusions:There are multiple differentially expressed immune genes in breast cancer. These genes are closely related to the prognosis of patients. The risk scoring model constructed based on these immune genes can effectively predict the prognosis of patients and provide new potential therapeutic targets for breast cancer immunotherapy.