Objective To analyze the relationship between sCD30 levels and immunosuppressive therapies after renal transplantation and find out its clinical application. Methods 112 patients who underwent all ograft kidney transplants were divided into cyclosporine A (CsA) and Tacrolimus (FK506) group according to their immunosuppressive regimes. Relevant clinical data including serum creatinine and drug concentration were collected for statistical analysis. Results There was no difference in posttranspant sCD30 levels between CsA and FK506 groups. Also, serum creatinine levels between two groups has no difference after long-term (24 months) immunosuppressive therapies (P>0.05). sCD30 level was decreased in both two groups, and there was statistically significant difference before and at the 7th day after surgery (P <0.05). There was a significant correlation between pretransplant sCD30 levels and serum creatinine levels at the 24th h post-transplant in the linear regression analysis (P<0.01 for both groups). The correlation between serum drug concentration and sCD30 level was also significant (P <0.05). Conclusion Both immunosuppressive regimes can reduce post-transplant sCD30 level. There is a correlation between sCD30 level with long-term renal function and serum drug concentration of CsA/FK506.
Key words:
CD30; Renal transplantation; Immunosuppression; Serum drug concentration
We aimed to establish an immune-related gene (IRG) based signature that could provide guidance for clinical bladder cancer (BC) prognostic surveillance.Differentially expressed IRGs and transcription factors (TFs) between BCs and normal tissues were extracted from transcriptome data downloaded from the TCGA database. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to identify related pathways based on differently expressed IRGs. Then, univariate Cox regression analysis was performed to investigate IRGs with prognostic values and LASSO penalized Cox regression analysis was utilized to develop the prognostic index (PI) model.A total of 411 BC tissue samples and 19 normal bladder tissues in the TCGA database were enrolled in this study and 259 differentially expressed IRGs were identified. Networks between TFs and IRGs were also provided to seek the upstream regulators of differentially expressed IRGs. By means of univariate Cox regression analysis, 57 IRGs were analyzed with prognostic values and 10 IRGs were finally identified by LASSO penalized Cox regression analysis to construct the PI model. This model could significantly classified BC patients into high-risk group and low-risk group in terms of OS (P=9.923e-07) and its AUC reached 0.711. By means of univariate and multivariate COX regression analysis, this PI was proven to be a valuable independent prognostic factor (HR =1.119, 95% CI =1.066-1.175, P<0.001). CMap database analysis was also utilized to screen out 10 small molecules drugs with the potential for the treatment of BC.Our study successfully provided a novel PI based on IRGs with the potential to predict the prognosis of BC and screened out 10 small molecules drugs with the potential to treat BC. Besides, networks between TFs and IRGs were also displayed to seek its upstream regulators for future researches.
Abstract BackgroundCell division cycle-associated 7 (CDCA7), as a member of the cell division cycle associated family, was reported to be aberrantly expressed in both solid tumors and hematological tumors, suggesting its essential role in promoting tumorigenesis. Hence, we aimed to explore its comprehensive role of overall survival (OS) in clear cell renal cell carcinoma (ccRCC) and emphasis on immunity.MethodsThe RNA sequencing data and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Gene set enrichment analysis (GSEA) was adopted to explore CDCA7 associated signaling pathways. Univariate and multivariate Cox regression analyses were carried out to assess independent prognostic factors. Furthermore, roles of CDCA7 in human immunity were also investigated.ResultsOur results suggested that CDCA7 was overexpressed in ccRCC and its elevated expression was related to shorter OS (P<0.01). Univariate and multivariate Cox regression analyses identified CDCA7 as an independent prognostic factor (both P<0.05). The prognostic nomogram integrating CDCA7 expression level and clinicopathologic variables was constructed to predict 1-, 3- and 5-year OS. GSEA indicated that high CDCA7 expression was related to the apoptosis pathway, cell cycle pathway, JAK-STAT pathway, NOD like receptor pathway, P53 pathway, T cell receptor pathway and toll like receptor pathway, etc. As for immunity, CDCA7 was significantly associated with tumor mutational burden (TMB), immune checkpoint molecules, tumor microenvironment and immune infiltration.ConclusionsCDCA7 could serve as an independent prognostic factor for ccRCC and it was closely related to immunity
Background: Long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of renal cell carcinoma (RCC) by competing in binding to miRNAs, and related competitive endogenous RNA (ceRNA) networks have been constructed in several cancers.However, the coexpression network has been poorly explored in RCC.Methods: We collected RCC RNA expression profile data and relevant clinical features from The Cancer Genome Atlas (TCGA).A cluster analysis was explored to show different lncRNA expression patterns.Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene set enrichment analysis (GSEA) were performed to analyze the functions of the intersecting mRNAs.Targetscan and miRanda bioinformatics algorithms were used to predict potential relationships among RNAs.Univariate Cox proportional hazards regression was conducted to determine the RNA expression levels and survival times.Results: Bioinformatics analysis revealed that the expression profiles of hundreds of aberrantly expressed lncRNAs, miRNAs, and mRNAs were significantly changed between different stages of tumors and non-tumor groups.By combining the data predicted by databases with intersection RNAs, a ceRNA network consisting of 106 lncRNAs, 26 miRNAs and 69 mRNAs was established.Additionally, a protein interaction network revealed the main hub nodes (VEGFA, NTRK2, DLG2, E2F2, MYB and RUNX1).Furthermore, 63 lncRNAs, 4 miRNAs and 31 mRNAs were significantly associated with overall survival.Conclusion: Our results identified cancer-specific lncRNAs and constructed a ceRNA network for RCC.A survival analysis related to the RNAs revealed candidate biomarkers for further study in RCC.
Background: We noticed that most of previous studies focused their attention merely on the relationships between tumor and adjacent tissues. Few of them made attempts to reveal the associations linked to tumor progression. Hence, we aimed to reveal prognostic factors related to clear cell renal cell carcinoma (ccRCC) progression based on m6A-related genes between T1/T2 and T3/T4.Methods: Differentially expressed m6A-related genes were identified in ccRCC patients obtained from the TCGA database. By means of univariate regression analysis and LASSO regression, two prognostic indexes (PIs) were established and carefully evaluated. Independent prognostic factor was evaluated by univariate and multivariate cox regression analyses and cMap database was utilized to screen out candidate small molecule drugs.Results: Finally, 340 records of T1/T2 and 190 records of T3/T4 ccRCC samples associated with clinical information were enrolled for analysis. As for T1/T2, we successfully established and carefully evaluated two individualized PIs (Riskscore1 T1/T2 and Riskscore2 T1/T2) based on clinical characteristics and three key m6A-related genes (METTL14, KIAA1429 and YTHDF2). In terms of T3/T4, we successfully established and carefully evaluated two individualized PIs (Riskscore1 T3/T4 and Riskscore2 T3/T4) based on clinical characteristics and three key m6A-related genes (METTL14, FTO and METTL3). By means of cMap database, MK-886, cefapirin and chlorhexidine were found to be negatively correlated with ccRCC progression, indicating the potential to prevent ccRCC patients progressing from T1/T2 to T3/T4.Conclusion: We successfully established and carefully evaluated two individualized prognostic signatures (Riskscore1 and Riskscore2) based on clinical characteristics and key m6A-related genes between T1/T2 and T3/T4 of ccRCC samples. Moreover, small molecule drugs related to ccRCC progression were also identified.Funding Statement: The authors stated: "None declared."Declaration of Interests: The authors stated: "None declared."Ethics Approval Statement: The authors stated: "Not applicable."
This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks.AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated.The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes.AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.
Though numerous studies have been conducted to investigate the associations between five 8q24 polymorphisms (rs6983267 T>G, rs1447295 C>A, rs16901979 C>A, rs6983561 A>C and rs10090154 C>T) and prostate cancer (PCa) risk, the available results remained contradictory. Therefore, we performed a comprehensive meta-analysis to derive a precise estimation of such associations. We searched electronic databases PubMed, EMBASE, Web of Science and Wan Fang for the relevant available studies up to February 1st, 2017, and 39 articles were ultimately adopted in this meta-analysis. All data were extracted independently by two investigators and recorded in a unified form. The strength of association between 8q24 polymorphisms and PCa susceptibility was evaluated by the pooled odds ratios (ORs) with 95% confidence intervals (CIs). Subgroup analysis was conducted based on ethnicity, source of controls and genotypic method. Overall, a total of 39 articles containing 80 studies were adopted in this meta-analysis. The results of this meta-analysis indicated that five 8q24 polymorphisms above were all related to PCa susceptibility. Besides, in the subgroup analysis by ethnicity, all selected 8q24 polymorphisms were significantly associated with PCa risk in Asian population. In addition, stratification analysis by source of controls showed that significant results were mostly concentrated in the studies' controls from general population. Moreover, when stratified by genotypic method, significant increased PCa risks were found by TaqMan method. Therefore, this meta-analysis demonstrated that 8q24 polymorphisms (rs6983267 T>G, rs1447295 C>A, rs16901979 C>A, rs6983561 A>C and rs10090154 C>T) were associated with the susceptibility to PCa, which held the potential biomarkers for PCa risk.
BackgroundApoptosis-related genes (ARGs) were used to develop a novel signature for forecasting overall survival (OS) and examining their relationships with immune infiltrates in bladder cancer (BC).MethodsGene expression matrices as well as related clinical data were acquired for BC samples from online datasets. According to differentially expressed ARGs acquired from normal bladder tissues and cancer samples, functional enrichment analyses were conducted. With the assistance of LASSO and Cox regression analysis, a novel model was successfully established and evaluated by external and internal validations.ResultsEventually, 17 ARGs (SLC5A6, GULP1, TAP1, MMP9, P4HB, FOXL2, CIDEC, EN2, NES, EPHA7, SUSD2, TMPRSS3, HOXB7, SATB1, MEST, PCDHGC3, ASPM) were utilized to construct the signature. Our constructed signature significantly distinguished high-risk from low-risk BC patients of OS by internal and external validations and was also proven to be able to serve as an independent prognostic biomarker (all P < 0.05). Furthermore, a prognostic nomogram was also constructed based on TCGA dataset to predict OS prognosis in BC suffers. Besides, this ARG based model was markedly associated with clinical characteristics like tumor stage (P = 3.98e−06), race (P = 8.255e−06), N stage (P = 0.002), T stage (P = 3.679e−05) and M stage (P = 0.002). As for immune infiltration, our established model was significantly associated with seven tumor-infiltrating immune cells.ConclusionsA prognostic signature was successfully developed by us according to 17 ARGs in BC using external and internal verifications, enabling clinicians to predict BC suffers' OS and promote specific individualization of patient care.
Nicotinamide phosphoribosyltransferase (NAMPT), also known as pre-B-cell colony-enhancing factor (PBEF) or visfatin, has been reported to be a crucial factor involved in tumor metabolism, angiogenesis and cell apoptosis. However, its definite roles in patients with malignant cancer remain unclear.Three online databases PubMed, Embase and Web of Science were looked through comprehensively for eligible articles, published before November, 2018. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) of overall survival (OS) or disease-free survival time or recurrence-free survival (DFS/RFS) were calculated to determine the associations between NAMPT expression and cancer prognosis.A total of ten eligible studies were finally enrolled for this analysis. Our results indicated that elevated NAMPT expression was associated with poor OS in breast cancer by both univariate and multivariate analysis (pooled HR =3.23, 95% CI: 1.93-5.41, I2=21.1%, P=0.283; pooled HR =3.34, 95% CI: 2.13-5.22, I2=0.0%, P=0.791; respectively) and in gastric cancer by univariate analysis (pooled HR =2.47, 95% CI: 1.07-5.73, I2=91.1%, P=0.001). Moreover, high expression of NAMPT was also related to poor DFS/RFS in breast cancer by univariate and multivariate analysis (pooled HR =3.85, 95% CI: 2.59-5.71, I2=0.0%, P=0.700; pooled HR =3.43, 95% CI: 2.36-4.99, I2=0.0%, P=0.737; separately). Similar results could be found in urothelial carcinoma (pooled HR =3.14, 95% CI: 1.73-5.71, I2=47.8%, P=0.166; pooled HR =3.06, 95% CI: 1.57-5.98, I2=0.0%, P=0.860). Besides, the translational level of NAMPT was also validated by UALCAN and the Human Protein Atlas database [immunohistochemistry (IHC)].Our results shed light on that NAMPT might be an oncogenic factor in breast cancer, gastric cancer and urothelial carcinoma.
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