m6A methylation reader IGF2BP2 activates endothelial cells to promote angiogenesis and metastasis of lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is a common type of lung cancer with a high risk of metastasis, but the exact molecular mechanisms of metastasis are not yet understood. METHODS: This study acquired single-cell transcriptomics profiling of 11 distal normal lung tissues, 11 primary LUAD tissues, and 4 metastatic LUAD tissues from the GSE131907 dataset. The lung multicellular ecosystems were characterized at a single-cell resolution, and the potential mechanisms underlying angiogenesis and metastasis of LUAD were explored. RESULTS: We constructed a global single-cell landscape of 93,610 cells from primary and metastatic LUAD and found that IGF2BP2 was specifically expressed both in a LUAD cell subpopulation (termed as LUAD_IGF2BP2), and an endothelial cell subpopulation (termed as En_IGF2BP2). The LUAD_IGF2BP2 subpopulation progressively formed and dominated the ecology of metastatic LUAD during metastatic evolution. IGF2BP2 was preferentially secreted by exosomes in the LUAD_IGF2BP2 subpopulation, which was absorbed by the En_IGF2BP2 subpopulation in the tumor microenvironment. Subsequently, IGF2BP2 improved the RNA stability of FLT4 through m6A modification, thereby activating the PI3K-Akt signaling pathway, and eventually promoting angiogenesis and metastasis. Analysis of clinical data showed that IGF2BP2 was linked with poor overall survival and relapse-free survival for LUAD patients. CONCLUSIONS: Overall, these findings provide a novel insight into the multicellular ecosystems of primary and metastatic LUAD, and demonstrate that a specific LUAD_IGF2BP2 subpopulation is a key orchestrator promoting angiogenesis and metastasis, with implications for the gene regulatory mechanisms of LUAD metastatic evolution, representing themselves as potential antiangiogenic targets.

Single-cell mechanistic studies of radiation-mediated bystander effects.

Ionizing radiation (IR) has been widely used in the diagnosis and treatment of clinical diseases, with radiation therapy (RT) being particularly rapid, but it can induce "bystander effects" that lead to biological responses in non-target cells after their neighboring cells have been irradiated. To help clarify how radiotherapy induces these effects, To help clarify how radiotherapy induces these effects, we analyzed single-cell RNA sequencing data from irradiated intestinal tissues on day 1 (T1 state), day 3 (T3 state), day 7 (T7 state), and day 14 (T14 state) after irradiation, as well as from healthy intestinal tissues (T0 state), to reveal the cellular level, molecular level, and involvement of different time irradiated mouse intestinal tissues in biological signaling pathways. In addition, changes in immune cell subpopulations and myeloid cell subpopulations after different radiation times were further explored, and gene regulatory networks (GRNs) of these cell subpopulations were constructed. Cellular communication between radiation-specific immune cells was explored by cell-to-cell communication events. The results suggest that radiotherapy trigger changes in immune cell subsets, which then reprogram the immune ecosystem and mediate systemic bystander effects. These radiation-specific immune cells participate in a wide range of cell-to-cell communication events. In particular, radiation-specific CD8+T cells appear to be at the core of communication and appear to persist in the body after recovery from radiotherapy, with enrichment analysis showing that radiation-specific CD8+ T cells are associated with ferroptosis. Thus, radiation-specific CD8+ T cells may be involved in cellular ferroptosis-mediated adverse effects caused by RT.

Adipose-derived mesenchymal stem cells may reduce intestinal epithelial damage in ulcerative colitis by communicating with macrophages and blocking inflammatory pathways: an analysis in silico.

Ulcerative colitis is a chronic, non-specific inflammatory disease that affects mainly the colonic mucosa and submucosa. The pathogenesis of ulcerative colitis is unclear, which limits the development of effective treatments. In this study, single-cell sequencing data from 18 ulcerative colitis samples and 12 healthy controls were downloaded from the Single Cell Portal database, cell types were defined through cluster analysis, and genes in each cluster that were differentially expressed in ulcerative colitis were identified. These genes were enriched in functional pathways related to apoptosis, immunity and inflammation. Analysis using iTALK software suggested extensive communication among immune cells. Single-cell sequencing data from adipose-derived mesenchymal stem cells from three healthy female donors were obtained from the Sequence Read Archive database. The SingleR package was used to identify different cell types, for each of which a stemness score was calculated. Pseudotime analysis was performed to infer the trajectory of cells. SCENIC software was used to identify the gene regulatory network in adipose-derived mesenchymal stem cells, and iTALK software was performed to explore the relationship among macrophages, adipose-derived mesenchymal stem cells and enterocytes. Molecular docking confirmed the possibility of cell-cell interactions via binding between surface receptors and their ligands. The bulk data were downloaded and analyzed to validate the expression of genes. Our bioinformatics analyses suggest that ulcerative colitis involves communication between macrophages and enterocytes via ligand-receptor pairs. Our results further suggest that adipose-derived mesenchymal stem cells may alleviate ulcerative colitis by communicating with macrophages to block inflammation.

Identification and Validation of a Malignant Cell Subset Marker-Based Polygenic Risk Score in Stomach Adenocarcinoma Through Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data.

Objectives: The aim of the present study was to construct a polygenic risk score (PRS) for poor survival among patients with stomach adenocarcinoma (STAD) based on expression of malignant cell markers. Methods: Integrated analyses of bulk and single-cell RNA sequencing (scRNA-seq) of STAD and normal stomach tissues were conducted to identify malignant and non-malignant markers. Analyses of the scRNA-seq profile from early STAD were used to explore intratumoral heterogeneity (ITH) of the malignant cell subpopulations. Dimension reduction, cell clustering, pseudotime, and gene set enrichment analyses were performed. The marker genes of each malignant tissue and cell clusters were screened to create a PRS using Cox regression analyses. Combined with the PRS and routine clinicopathological characteristics, a nomogram tool was generated to predict prognosis of patients with STAD. The prognostic power of the PRS was validated in two independent external datasets. Results: The malignant and non-malignant cells were identified according to 50 malignant and non-malignant cell markers. The malignant cells were divided into nine clusters with different marker genes and biological characteristics. Pseudotime analysis showed the potential differentiation trajectory of these nine malignant cell clusters and identified genes that affect cell differentiation. Ten malignant cell markers were selected to generate a PRS: RGS1, AADAC, NPC2, COL10A1, PRKCSH, RAMP1, PRR15L, TUBA1A, CXCR6, and UPP1. The PRS was associated with both overall and progression-free survival (PFS) and proved to be a prognostic factor independent of routine clinicopathological characteristics. PRS could successfully divide patients with STAD in three datasets into high- or low-risk groups. In addition, we combined PRS and the tumor clinicopathological characteristics into a nomogram tool to help predict the survival of patients with STAD. Conclusion: We revealed limited but significant intratumoral heterogeneity in STAD and proposed a malignant cell subset marker-based PRS through integrated analysis of bulk sequencing and scRNA-seq data.

A Five-microRNA Signature as Risk Stratification System in Uterine Corpus Endometrial Carcinoma.

BACKGROUND: MicroRNAs (miRs) have been shown to play important roles in various cancers and may be a reliable prognostic marker. However, its prognostic value in endometrial carcinoma (UCEC) needs to be further explored. OBJECTIVES: The aim of this study was to create a miR-based signature to effectively predict the prognosis for patients with uterine corpus endometrial carcinoma (UCEC). METHODS: Using UCEC data set in TCGA, we identified differentially expressed miRs between UCEC and healthy endometrial tissues. The LASSO method was used to construct a miR-based signature prognosis index for predicting prognosis in the training cohort. The miR-based signature prognosis index was validated in an independent test cohort. MiRNet tool was applied to perform functional enrichment analysis of this miR-based signature. RESULTS: A total of 208 miRs were differentially expressed between UCEC and healthy endometrial tissues. Five miRs (miR-652, miR-3170, miR-195, miR-34a, and miR-934) were identified to generate a prognosis index (PI). The five-miR signature is a promising biomarker for predicting the 5-year-survival rate of UCEC with AUC = 0.730. The PI remained an independent prognostic factor adjusted by routine clinicopathologic factors. Using the PI, we could successfully identify the high-risk individuals, furthermore, it still worked in an independent test cohort. The five miRs involved in various pathways associated with cancer. CONCLUSION: We proposed and validated a five-miR signature that could serve as an independent prognostic predictor of UCECs.

Identification of the association between HMMR expression and progression of hepatocellular carcinoma via construction of a co-expression network.

The aim of the present study was to identify key genes involved in the progression of hepatocellular carcinoma (HCC). According to the theory of the multistep process of hepatocarcinogenesis and weighted gene co-expression network analysis, hub genes associated with the progression of HCC were identified using the gene expression profiles of patients with normal to chronic hepatitis/cirrhosis and dysplastic nodules to HCC. An independent dataset was used to verify the association between hub gene and clinical phenotype. The diagnostic and prognostic value of hub genes regarding HCC were evaluated. Gene set enrichment analysis (GSEA) was performed to explore the function of hub genes. A co-expression gene module positively associated with HCC progression was identified. Combined with a protein-protein interaction (PPI) network, a total of 10 common hub genes common to both the module of interest and the PPI network were selected as hub genes. Hyaluronan mediated motility receptor (HMMR) was selected as the candidate gene and was significantly upregulated in HCC at the mRNA and protein expression levels. HMMR is a promising diagnostic biomarker for HCC, and is also associated with its progression. The expression of HMMR was positively correlated with HCC tumor grade, pathological stage, tumor stage and Ishak score. The expression of HMMR was an independent prognostic factor compared with clinicopathological features. Patients with high expression levels of HMMR exhibited a less favorable prognosis. GSEA identified 6 representative gene sets that were associated with cancer. Overall, HMMR may serve an important role in HCC and may have potential as a biomarker of HCC diagnosis and progression.

Prognostic value of CXCL17 and CXCR8 expression in patients with colon cancer.

C-X-C motif chemokine ligand 17 (CXCL17) is a mucous chemokine and its expression is highly correlated with that of G protein-coupled receptor 35 (GPR35), which has been confirmed as its receptor and named C-X-C motif chemokine receptor 8 (CXCR8). CXCL17 is upregulated in several types of cancer. However, the biological role of this chemokine in colon cancer remains unknown. In the present study, the expression levels of CXCL17 and CXCR8 were examined using immunohistochemistry in 101 colon cancer tissues and 79 healthy tumour-adjacent tissues. CXCL17 and CXCR8 expression levels were increased in the colon cancer samples compared with tumour-adjacent samples. Patients with high CXCL17 expression had longer overall survival (OS) compared with patients with low expression of CXCL17 (log-rank test; P=0.027). However, CXCR8 expression, but not CXCL17, was an independent prognostic factor for OS in patients with colon cancer. The expression of CXCR8 correlated positively with that of CXCL17 in colon cancer samples (ρ=0.295; P=0.003). Furthermore, the combined high expression of CXCL17 and CXCR8 was a significant independent prognostic factor for OS in patients with colon cancer (P=0.001). In subgroups with a TNM stage of I-II, the patients with combined high expression of CXCL17 and CXCR8 had a longer survival compared with those without combined high expression (P=0.001). However, this difference was not observed in subgroups with a TNM stage of III-IV. Collectively, these findings suggest that CXCL17/CXCR8 signalling may be involved in colon cancer and contribute to improved patient outcomes.

Enhance the treatment of low strength wastewater at low temperature with the coexistence system of AnAOB and heterotrophic bacteria: Performance and bacterial community.

The application of anammox process in mainstream wastewater treatment process is still facing challenges especially at the low temperature. To resolve this problem, the coexistence system of anaerobic ammonia-oxidizing bacteria (AnAOB) and heterotrophic bacteria (HB) was built in this study. The nitrogen removal efficiency mainly maintained at above 90% during the process of temperature reducing from 35 °C to 10 °C. The nitrogen removal rate were 0.30 g N·L-1·d-1 at both 25 and 15 °C and 0.10 g N·L-1·d-1 at 10 °C, respectively. Analysis of 16S rRNA genus sequencing revealed that as the temperature reduced to 10 °C, the Denutrotisoma genera presented a downward trend but Comamonadaceae genera showed an upward trend. At 10 °C, the contrast of anammox activities between granular and flocculent sludge in the system revealed that although the abundance of anammox genera was much lower in flocculent sludge than that in granular sludge, the anammox activities showed no significant discrepancy. And the abundance of Comamonadaceae and Chloroflexales genera were much higher in flocculent sludge than those in granular sludge, presenting their key roles to anammox activity at low temperature. The Circos diagram and Cluster of orthologous Group of protein functional predication showed that the functional abundance related to interaction among microbial communities were higher in flocculent sludge but those related to self-growth was higher in granular sludge. This result indicated the significance of the interactions based on the microbial diversity in the application of annamox process at low temperature.

MiRNA expression patterns are associated with tumor mutational burden in lung adenocarcinoma.

Background: Tumor mutational burden (TMB) has emerged as an independent biomarker to predict patient responses to treatment with immune checkpoint inhibitors (ICIs) for lung adenocarcinoma (LUAD). MicroRNAs (miRNAs) have a crucial role in the regulation of anticancer immune responses, but the association of miRNA expression patterns and TMB is not clear in LUAD. Methods: Differentially expressed miRNAs in samples with high TMB and low TMB samples were screened in the LUAD dataset in The Cancer Genome Atlas. The least absolute shrinkage and selection operator (LASSO) method was applied to develop a miRNA-based signature classifier for predicting TMB levels in the training set. An test set was used to validate this classifier. The correlation between the miRNA-based classifier index and the expression of three immune checkpoints (PD-1, PD-L1, and CTLA-4) were explored. Functional enrichment analysis was carried out of the miRNAs included in the miRNA-based signature classifier. Results: Twenty-five differentially expressed miRNAs were used to establish a miRNA-based signature classifier for predicting TMB level. The accuracy of the 25-miRNA-based signature classifier was 0.850 in the training set, 0.810 in the test set and 0.840 in the total set. This miRNA-based signature classifier index showed a low correlation with PD-1 and PD-L1, and no correlation with CTLA-4. Enrichment analysis for these 25 miRNA revealed they are involved in many immune-related biological processes and cancer-related pathways. Conclusion: MiRNA expression patterns are associated with tumor mutational burden and a miRNA-based signature classifier may serve as a biomarker for prediction of TMB levels in LUAD.

Construction and validation of a seven-microRNA signature as a prognostic tool for lung squamous cell carcinoma.

Objective: The aim of this study was to construct and validate a microRNA (miR)-based signature as a prognostic tool for lung squamous cell carcinoma (LUSC). Materials and methods: With the use of mature miR expression profiles downloaded from The Cancer Genome Atlas database, we identified differentially expressed miRs between LUSC and matched healthy lung tissue. Thereafter, we carried out an evaluation of the association of differentially expressed miRs with overall survival (OS) with the use of univariate and multivariate Cox regression analysis. This analysis was eventually employed for the construction of a miR-based signature, which effectively predicted the prognosis. The functional enrichment analysis of the miRs included in the signature was used to explore their potential molecular mechanism in LUSC. Results: A total of 316 miRs were differentially expressed between LUSC and matched healthy lung tissues in the training set. Following the univariate and multivariate Cox regression analysis, we found that seven miRs were independent prognostic factors. Each patient received a signature index ranging from 0 to 7. Patients with LUSC were divided into high-risk, intermediate-risk, and low-risk groups in accordance with their signature index and the OS in the three groups was significantly different. This finding remains consistent in the validation set. Besides that, this seven-miR signature remained an independent prognostic factor in comparison with routine clinicopathologic features. The seven-miR signature is a promising biomarker for predicting the 5-year survival rate of LUSC with an area under the receiver operating characteristic curveof 0.712 in the training set and 0.688 in the validation set, respectively. The target genes of seven miRs may be involved in various pathways associated with lung cancer, for instance the mitogen-activated protein kinase signaling pathway and the Wnt signaling pathway. Conclusion: Using this signature, patients with LUSC can be divided into high-risk, intermediate-risk, and low-risk groups for more personalized management.

A seven-miRNA expression-based prognostic signature and its corresponding potential competing endogenous RNA network in early pancreatic cancer.

The present study aimed to establish a microRNA (miRNA/miR) signature to predict the prognosis of patients with pancreatic cancer (PC) at the early stage and to investigate the involvement of competing endogenous RNAs (ceRNAs) in PC. Using mature miRNA expression profiles from The Cancer Genome Atlas, differentially expressed miRNAs in tissues derived from patients exhibiting early PC and tissues from healthy individuals were compared. The least absolute shrinkage and selection operator regression method was used to construct a miRNA-based signature for predicting prognosis. The miRNet tool, gene set enrichment analysis (GSEA) and the LncRNADisease database were utilized to explore the mechanistic involvement of ceRNAs. A total of seven downregulated miRNAs in PC (miR-424-5p, miR-139-5p, miR-5586-5p, miR-126-3p, miR-3613-5p, miR-454-3p and miR-1271-5p) were selected to generate a signature. Based on this seven-miRNA signature, it was possible to stratify patients with PC into low- and high-risk groups. The overall survival of the low-risk group was significantly longer than that of the high-risk group (P<0.001). The seven-miRNA signature was able to predict the 2-year-survival rate of patients with early PC with an area under the curve of 0.750. Furthermore, as opposed to routine clinicopathological features, this seven-miRNA signature was an independent prognostic factor according to multivariate Cox regression analysis. GSEA indicated that the extracellular matrix receptor interaction pathway and the transforming growth factor-ß signaling pathway were enriched in the high-risk group. A ceRNA network of the seven-miR signature was constructed. In conclusion, the present study provided a seven-miRNA signature, according to which patients with early PC may be divided into high- and low-risk groups. The ceRNA network of the prognostic signature was preliminarily explored.

Enhanced microbial metabolism in one stage partial nitritation-anammox system treating low strength wastewater by novel composite carrier.

One stage partial nitritation-anammox (PN-A) process has attracted more and more attention due to the low investment cost but the instability in treating low strength wastewater. In this study, for producing a novel composite carrier that could provide high ammonia microenvironment in low strength wastewater, the zeolites and floating materials were combined in the spherical shell and distributed evenly by the spherical polyhedron. And a moving bed biofilm reactor (MBBR) with the composite carriers and ordinary carriers without zeolites as control group was operated for nearly 120 days. The PN-A process were realized in 53 days, and the total nitrogen removal efficiency reached around 85% at influent ammonium concentration of 50 mg/L finally. Analysis of 16S rRNA gene sequencing revealed that the composite carriers showed significant promotion on the proliferation of ammonium oxidizing bacteria (AOB) and enrichment of anaerobic ammonium oxidizing bacteria (AnAOB), accounting for 19.14% and 41.65% on the surface, respectively. Moreover, the existence of relative higher abundance of ammonia on the composite carrier surface was validated by the metabolite biomarker of glutamate and especially spermidine. The metabolomics analysis and 16S rRNA function prediction showed that the protein synthesis pathway was obviously upregulated on the composite carriers surface compared with that on the ordinary carriers surface. The higher abundance of glutamate and putrescine indicated that the composite carrier could stimulate the metabolism and growth of bacteria. The present study provided a functional carrier to realize the transformation of activated sludge system into PN-A system treating low strength wastewater, which is significant to the application of the process in mainstream.

Identification of a 13-gene-based classifier as a potential biomarker to predict the effects of fluorouracil-based chemotherapy in colorectal cancer.

The aim of the current study was to develop a predictor classifier for response to fluorouracil-based chemotherapy in patients with advanced colorectal cancer (CRC) using microarray gene expression profiles of primary CRC tissues. Using two expression profiles downloaded from the Gene Expression Omnibus database, differentially expressed genes (DEGs) between responders and non-responders to fluorouracil-based chemotherapy were identified. A total of 791 DEGs, including 303 that were upregulated and 488 that were downregulated in responders, were identified. Functional enrichment analysis revealed that the DEGs were primarily involved in 'cell mitosis', 'DNA replication' and 'cell cycle' signaling pathways. Following feature selection using two methods, a random forest classifier for response to fluorouracil-based chemotherapy with 13 DEGs was constructed. The accuracy of the 13-gene classifier was 0.930 in the training set and 0.810 in the validation set. The receiver operating characteristic curve analysis revealed that the area under the curve was 1.000 in the training set and 0.873 in the validation set (P=0.227). The 13-gene-based classifier described in the current study may be used as a potential biomarker to predict the effects of fluorouracil-based chemotherapy in patients with CRC.

Efficacy of carboplatin plus S-1 for the treatment of non-small cell lung cancer: A protocol for a systematic review of randomized controlled trial.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the most common lung cancer. Numerous clinical studies have reported that the combination of carboplatin and S-1 (CS) can be used to treat NSCLC effectively. However, no systematic review has been conducted to assess its efficacy and safety for NSCLC. This systematic review aims to evaluate the efficacy and safety of CS for treatment of patients with NSCLC. METHODS: This study will retrieve the following electronic databases from inception to the February 1, 2019: Cochrane Library, EMBASE, MEDILINE, CINAHL, AMED, and 4 Chinese databases without any language limitations. This systematic review will include randomized controlled trials (RCTs) and case-control studies for assessing the efficacy and safety of CS for the treatment of NSCLC. Cochrane risk of bias will be used as methodological quality assessment for each qualified study. The RevMan V.5.3 software will be utilized to synthesize the data and conduct the meta-analysis if it is allowed. The data will be pooled by using the random-effects model or fixed-effects model. RESULTS: The primary outcome is overall response rate. The secondary outcomes are overall survival, progression-free survival, the disease control rate, and any adverse events. CONCLUSION: It will provide latest evidence to determine the efficacy and safety of CS for treatment of patients with NSCLC. ETHICS AND DISSEMINATION: No research ethic approval is needed in this study because this study will not analyze individual patient data. The results are expected to disseminate through peer-reviewed journals. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019124860.

Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma.

Growing evidence has revealed that long noncoding RNAs (lncRNAs) have an important impact on tumorigenesis and tumor progression via a mechanism involving competing endogenous RNAs (ceRNAs). However, their use in predicting the survival of a patient with hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to develop a novel lncRNA expression-based risk score system to accurately predict the survival of patients with HCC. In our study, using expression profiles downloaded from The Cancer Genome Atlas database, the differentially expressed messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) were explored in patients with HCC and normal liver tissues, and then a ceRNA network constructed. A risk score system was established between lncRNA expression of the ceRNA network and overall survival (OS) or recurrence-free survival (RFS); it was further analyzed for associations with the clinical features of patients with HCC. In HCC, 473 differentially expressed lncRNAs, 63 differentially expressed miRNAs, and 1417 differentially expressed mRNAs were detected. The ceRNA network comprised 41 lncRNA nodes, 12 miRNA nodes, 24 mRNA nodes, and 172 edges. The lncRNA expression-based risk score system for OS was constructed based on six lncRNAs (MYLK-AS1, AL359878.1, PART1, TSPEAR-AS1, C10orf91, and LINC00501), while the risk score system for RFS was based on four lncRNAs (WARS2-IT1, AL359878.1, AL357060.1, and PART1). Univariate and multivariate Cox analyses showed the risk score systems for OS or RFS were significant independent factors adjusted for clinical factors. Receiver operating characteristic curve analysis showed the area under the curve for the risk score system was 0.704 for OS, and 0.71 for RFS. Our result revealed a lncRNA expression-based risk score system for OS or RFS can effectively predict the survival of patients with HCC and aid in good clinical decision-making.

Identification of key genes involved in the metastasis of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal malignant tumor in adults. The aim of the present study was to identify the key genes involved in ccRCC metastasis. Expression profiling data for ccRCC patients with metastasis and without metastasis were obtained from The Cancer Genome Atlas database. The datasets were used to identify differentially expressed genes (DEGs) between the metastasis group and the non-metastasis group using the DESeq2 package. Function enrichment analyses of DEGs were performed. The protein-protein interaction (PPI) network was constructed and analyzed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape for further analysis of the identified hub genes. A total of 472 DEGs were identified, including 247 that were upregulated and 225 that were downregulated in the metastasis group. Gene Ontology enrichment analysis revealed that DEGs were mainly enriched in cell transmembrane movement and mitotic cell cycle process. Kyoto Encyclopedia of Genes Genomes pathway analysis revealed that the DEGs were mainly involved in the 'cell cycle' (hsa04110), 'collecting duct acid secretion' (hsa04966), 'complement and coagulation cascades' (hsa04610) and 'aldosterone-regulated sodium reabsorption' (hsa04960) pathways. Using the PPI network, 35 hub genes were identified, and the majority of them were upregulated in ccRCC tissue compared with normal kidney tissue. The expression levels of certain hub genes (CDKN3, TPX2, BUB1B, CDCA8, UBE2C, NDC80, RRM2, NCAPG, NCAPH, PTTG1, FAM64A, ANLN, KIF4A, CEP55, CENPF, KIF20A, ASPM and HJURP) were significantly associated with overall survival and recurrence-free survival in ccRCC. The present study has identified key genes associated with the metastasis of ccRCC.

Expression and gene regulation network of RBM8A in hepatocellular carcinoma based on data mining.

RNA binding motif protein 8A (RBM8A) is an RNA binding protein in a core component of the exon junction complex. Abnormal RBM8A expression is associated with carcinogenesis. We used sequencing data from the Cancer Genome Atlas database and Gene Expression Omnibus, analyzed RBM8A expression and gene regulation networks in hepatocellular carcinoma (HCC). Expression was analyzed using OncomineTM and Gene Expression Profiling Interactive Analysis tools, while RBM8A alterations and related functional networks were identified using cBioPortal. LinkedOmics was used to identify differential gene expression with RBM8A and to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. Gene enrichment analysis examined target networks of kinases, miRNAs and transcription factors. We found that RBM8A is overexpressed and the RBM8A gene often amplified in HCC. Expression of this gene is linked to functional networks involving the ribosome and RNA metabolic signaling pathways. Functional network analysis suggested that RBM8A regulates the spliceosome, ribosome, DNA replication and cell cycle signaling via pathways involving several cancer-related kinases, miRNAs and E2F Transcription Factor 1. Our results demonstrate that data mining efficiently reveals information about RBM8A expression and potential regulatory networks in HCC, laying a foundation for further study of the role of RBM8A in carcinogenesis.

Identification and validation of a four-miRNA (miRNA-21-5p, miRNA-9-5p, miR-149-5p, and miRNA-30b-5p) prognosis signature in clear cell renal cell carcinoma.

PURPOSE: Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers with high mortality worldwide. However, biomarkers for predicting prognosis in ccRCC are limited. In this study, we attempted to identify potential prognostic biomarkers of ccRCC. METHODS: Clinical information and the preprocessed ccRCC mature miRNA expression profiles in The Cancer Genome Atlas database were downloaded from UCSC Xena. The miRNAs differentially expressed between ccRCCs and matched normal tissues were analyzed using the "limma" package. A miRNA-based signature was constructed using the multivariate Cox regression model with prognosis index (PI) formula. Patients with ccRCC were divided into low-risk and high-risk subgroups according to median PI. The survival times were compared between the two groups using Kaplan-Meier analysis with log-rank test. The training set was used to construct a miRNA-based signature for predicting prognosis. The test set was used to verify the signature. Target gene prediction and functional enrichment analysis of the four miRNAs were performed using miRNet. RESULTS: We identified four miRNAs, miRNA-21-5p, miRNA-9-5p, miR-149-5p, and miRNA-30b-5p, as independent prognostic indicators. Next, we used these four miRNAs to construct a four-miRNA PI for each patient. Results revealed that patients in the high-risk group (n=119) had significantly shorter survival time than those in the low-risk group (n=118) (high-risk/low-risk group log-rank P=0.000). This four-miRNA signature is an independent prognostic factor compared with routine clinicopathological features in the test set. These miRNAs targeted 1,634 genes, and a miRNA-target gene network was constructed using miRNet. The target genes of these four miRNAs were involved in various pathways related to cancer. CONCLUSION: Our observations suggest that the four-miRNA signature correlated with the survival of patients with ccRCC and can be used as a prognostic biomarker of ccRCC.

miRNA-21 and miRNA-223 expression signature as a predictor for lymph node metastasis, distant metastasis and survival in kidney renal clear cell carcinoma.

Purpose: The aim of this study was to generate a novel miRNA expression signature to effectively assess nodal metastasis, distant metastasis and predict prognosis for patients with kidney renal clear cell carcinoma (KIRC) and explore its potential mechanism of affecting the prognosis. Method: Using expression profiles downloaded from the Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between KIRC and paired normal tissues. The diagnostic values of the differentially expressed miRNAs for nodal metastasis and distant metastasis were evaluated by Receiver Operating Characteristic (ROC) curve analysis. Then, we evaluated the impact of miRNAs on overall survival (OS) by univariate and multivariate COX regression analyzes. This analysis was ultimately used to construct a miRNA signature that effectively assessed nodal metastasis, distant metastasis and predicted prognosis. The functional enrichment analysis of the miRNAs included in the signatures was used to explore its potential molecular mechanism in KIRC. Results: Based on our cutoff criteria (P < 0.05 and |log2FC| > 1.0), we identified 104 differentially expressed microRNAs (miRNAs), including 43 that were up-regulated in KIRC tissues and 61 that were down-regulated. We found 12 miRNAs were potentially diagnostic biomarkers of nodal metastasis and distant metastasis by ROC curve analysis. Two miRNAs (miRNA-21 and miRNA-223) were significant miRNAs independently associated with OS based on Cox univariate and multivariate analysis. We generated a signature index based on expression of these two miRNAs, and the two-miRNA signature is promising as a biomarker for diagnosing nodal metastasis, distant metastasis and predicting 5-year survival rate of KIRC with areas under the curve (AUC)=0.738, 0.659 and 0.731, respectively. Patients were stratified into high-risk and low-risk groups, according to median of the signature prognosis indexes. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group (P = 0.000). The functional enrichment analysis suggested that the target genes of two miRNAs may be involved in various pathways related to cancer, p53 signaling pathway, apoptosis, and MAPK signaling pathway. Conclusion: The two-miRNA signature could assess nodal metastasis, distant metastasis and predict survival of KIRC. As a promising prediction tool, the mechanism of the two miRNAs in KIRC deserves further study.