scholarly journals Integrative Analysis of Genomic and Clinical Data Reveals Intrinsic Characteristics of Bladder Urothelial Carcinoma Progression

Genes ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 464 ◽  
Author(s):  
Bin Zhou ◽  
Rui Guo
Keyword(s):  
Bladder Cancer ◽  
Regulatory Networks ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Clinical Information ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Genomic Alteration ◽  
Structural Variations ◽  
New Perspective

The progression of bladder cancer is generally a complex and dynamic process, involving a variety of biological factors. Here, we aimed to identify a set of survival-related genes that play an important role in the progression of bladder cancer and uncover their synergistic patterns. Based on the large-scale genomic profiling data and clinical information of 404 bladder cancer patients derived from The Cancer Genome Atlas (TCGA) database, we first discovered 1078 survival-related genes related to their survival states using univariate and multivariate Cox proportional hazardous regression. We then investigated the dynamic changes of the cooperative behaviors of these 1078 genes by analyzing their respective genomic features, including copy number variations, DNA methylations, somatic mutations, and microRNA regulatory networks. Our analyses showed that during the progression of bladder cancer, the biological disorder involving the identified survival-related genes can be reflected by multiple levels of abnormal gene regulation, ranging from genomic alteration to post-transcriptional dysregulation. In particular, the stage-specific co-expression networks of these genes undergo a series of structural variations. Our findings provide useful hints on understanding the underlying complex molecular mechanisms related to the evolution of bladder cancer and offer a new perspective on clinical diagnosis and treatment of bladder cancer.

FADS1 is a Prognostic Biomarker in Bladder Cancer: A Study Based on TCGA Data

2020 ◽  
Vol 23 ◽  
Author(s):  
Ying Lu ◽  
Jing Shao ◽  
Xu Shu ◽  
Yaofei Jiang ◽  
Jianfang Rong ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Histological Grade ◽  
Clinical Stage ◽  
Fatty Acid Desaturase ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Normal Tissues ◽  
Potential Biomarker ◽  
T Classification

Aim and Objective: Fatty acid desaturase 1 (FADS1) has been reported to be a potential biomarker in various cancers. However, no study has explored the relationship between FADS1 expression and bladder cancer. Our study aimed to investigate the role of FADS1 in bladder cancer prognosis via The Cancer Genome Atlas (TCGA). Materials and Methods: RNA-Seq expression of 414 tumor tissues and 19 paired normal tissues, as well as corresponding clinical data, were downloaded from TCGA database. Two cancer cases were excluded due to a lack of clinical information. The association between FADS1 and the clinicopathological features of bladder cancer was analyzed. This study was conducted in October of 2019 in China. Results: The high expression of FADS1 in bladder cancer was significantly related to histological grade (OR = 0.155 for low vs. high), clinical stage (OR=2.074 for III or IV vs. I or II), T classification (OR=2.326 for T3 or T4 vs. T1 or T2), lymphatic metastasis (OR=1.923 for N1 or N2 or N3 vs. N0) and distant metastasis (OR=4.883 for yes vs. no) (all p-values <0.05). Bladder cancer with high FADS1 levels was related to a worse prognosis than bladder cancer with low FADS1 levels (p= 1.626*10-5 ), according to median expression value 3.622. FADS1 was an independent factor of overall survival in bladder cancer, with a hazard ratio of 1.048 (95%CI: 1.020–1.077, p = 0.001). Conclusions: Increased FADS1 expression in bladder cancer is associated with advanced clinical pathological features and may be a potential biomarker for poor prognosis.

scholarly journals A network view of microRNA and gene interactions in different pathological stages of colon cancer

2019 ◽  
Vol 12 (S7) ◽  
Author(s):  
Jia Wen ◽  
Benika Hall ◽  
Xinghua Shi
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Gene Interactions ◽  
New Strategy ◽  
Pathological Stages

Abstract Background Colon cancer is one of the common cancers in human. Although the number of annual cases has decreased drastically, prognostic screening and translational methods can be improved. Hence, it is critical to understand the molecular mechanisms of disease progression and prognosis. Results In this study, we develop a new strategy for integrating microRNA and gene expression profiles together with clinical information toward understanding the regulation of colon cancer. Particularly, we use this approach to identify microRNA and gene expression networks that are specific to certain pathological stages. To demonstrate the application of our method, we apply this approach to identify microRNA and gene interactions that are specific to pathological stages of colon cancer in The Cancer Genome Atlas (TCGA) datasets. Conclusions Our results show that there are significant differences in network connections between miRNAs and genes in different pathological stages of colon cancer. These findings point to a hypothesis that these networks signify different roles of microRNA and gene regulation in the pathogenesis and tumorigenesis of colon cancer.

scholarly journals Silencing of lncRNA MIR497HG via CRISPR/Cas13d Induces Bladder Cancer Progression Through Promoting the Crosstalk Between Hippo/Yap and TGF-β/Smad Signaling

2020 ◽  
Vol 7 ◽  
Author(s):  
Changshui Zhuang ◽  
Ying Liu ◽  
Shengqiang Fu ◽  
Chaobo Yuan ◽  
Jingwen Luo ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cell Line ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Transforming Growth Factor ◽  
Transforming Growth Factor Β ◽  
Pathological Process ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion

A subset of long non-coding RNAs (lncRNAs), categorized as miRNA-host gene lncRNAs (lnc-miRHGs), is processed to produce miRNAs and involved in cancer progression. This work aimed to investigate the influences and the molecular mechanisms of lnc-miRHGs MIR497HG in bladder cancer (BCa). The miR-497 and miR-195 were derived from MIR497HG. We identified that lnc-miRHG MIR497HG and two harbored miRNAs, miR-497 and miR-195, were downregulated in BCa by analyzing The Cancer Genome Atlas and our dataset. Silencing of MIR497HG by CRISPR/Cas13d in BCa cell line 5637 promoted cell growth, migration, and invasion in vitro. Conversely, overexpression of MIR497HG suppressed cell progression in BCa cell line T24. MiR-497/miR-195 mimics rescued significantly the oncogenic roles of knockdown of MIR497HG by CRISPR/Cas13d in BCa. Mechanistically, miR-497 and miR-195 co-ordinately suppressed multiple key components in Hippo/Yap and transforming growth factor β signaling and particularly attenuated the interaction between Yap and Smad3. In addition, E2F4 was proven to be critical for silencing MIR497HG transcription in BCa cells. In short, we propose for the first time to reveal the function and mechanisms of MIR497HG in BCa. Blocking the pathological process may be a potential strategy for the treatment of BCa.

Molecular subtyping of metastatic urothelial bladder cancer.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 326-326
Author(s):  
Charlotte Ackerman ◽  
Sanjeev Mariathasan ◽  
Dorothee Nickles ◽  
Alfonso Gomez De Liano Lista ◽  
Akhila Ganeshi Wimalasingham ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Therapy ◽  
Clinical Information ◽  
Progression Free Survival ◽  
The Cancer Genome Atlas ◽  
Urothelial Bladder Cancer ◽  
First Line ◽  
Metastatic Urothelial Cancer ◽  
Urothelial Bladder ◽  
Line Chemotherapy

326 Background: TCGA molecular sybtyping is established in metastatic urothelial bladder cancer (UBC). It remains unclear if it is of prognostic importance with chemotherapy in metastatic UBC. Data into immune therapy suggests TCGA subtyping is predictive to response. Methods: Archival formalin-fixed paraffin embedded (FFPE) tissue were analysed from 170 patients that had consented into a clinical trial (NCT00949455) after first line chemotherapy for metastatic disease. Gene expression levels were quantified by NanoString technology. Molecular subtypes were assigned according to The Cancer Genome Atlas (TCGA) subtypes. Clinical information was available for all patients and analysis on individual genes were explored. Results: 170 patients were analysed, 75% male. 107 (64%) patients received cisplatin based first-line chemotherapy, with 36% receiving carboplatin based regimen. Median overall survival (OS) was 15.73 months [95% CI: 13.87-17.58], and median progression free survival (PFS) was 10.71 months [95% CI: 8.97-12.45]. Samples were initially clustered into luminal (n=109) and basal (n=61) subtypes. Response to first line chemotherapy occurred in all subtypes but was shown to be significantly higher in the luminal subtype versus the basal subtype [58% vs 20%, p=0.01]. PFS was superior in luminal subtypes [11.8 months vs 8.9 months, p=0.005]. Exploratory analysis showed that luminal II subtype had the best outcome for OS [20.3 months, p=0.03] compared to the other subtypes. Outcomes with other genes including immune markers were explored. TCGA outcomes can be summarised in the table. Conclusions: In metastatic urothelial cancer, TCGA subclassifying influences outcome of patients post chemotherapy. [Table: see text]

scholarly journals Identification of an IRGP Signature to Predict Prognosis and Immunotherapeutic Efficiency in Bladder Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Liang-Hao Zhang ◽  
Long-Qing Li ◽  
Yong-Hao Zhan ◽  
Zhao-Wei Zhu ◽  
Xue-Pei Zhang
Keyword(s):  
Bladder Cancer ◽  
Stromal Cells ◽  
Molecular Mechanisms ◽  
Proportional Hazards ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Validation Set

BackgroundIdentify immune-related gene pairs (IRGPs) signature related to the prognosis and immunotherapeutic efficiency for bladder cancer (BLCA) patients.Materials and MethodsOne RNA-seq dataset (The Cancer Genome Atlas Program) and two microarray datasets (GSE13507 and GSE31684) were included in this study. We defined these cohorts as training set to construct IRGPs and one immunotherapy microarray dataset as validation set. Identifying BLCA subclasses based on IRGPs by consensus clustering. The Lasso penalized Cox proportional hazards regression model was used to construct prognostic signature and potential molecular mechanisms were analyzed.ResultsThis signature can accurately predict the overall survival of BLCA patients and was verified in the immunotherapy validation set. IRGP-signatures can be used as independent prognostic risk factor in various clinical subgroups. Use the CIBERSORT algorithm to assess the abundance of infiltrating immune cells in each sample, and combine the results of the gene set enrichment analysis of a single sample to explore the differences in the immune microenvironment between IRPG signature groups. According to the results of GSVA, GSEA, and CIBERSORT algorithm, we found that IRGP is strikingly positive correlated with tumor microenvironment (TME) stromal cells infiltration, indicating that the poor prognosis and immunotherapy might be caused partly by enrichment of stromal cells. Finally, the results from the TIDE analysis revealed that IRGP could efficiently predict the response of immunotherapy in BLCA.ConclusionThe novel IRGP signature has a significant prognostic value for BLCA patients might facilitate personalized for immunotherapy.

scholarly journals MON-719 The Cellular and Molecular Landscape of Hypothalamic Patterning and Differentiation

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Thomas Kim
Keyword(s):  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Brain Atlas ◽  
Specific Gene ◽  
Cell Fate Specification ◽  
Human Hypothalamus ◽  
Fate Specification ◽  
Time Points

Abstract The hypothalamus is a central regulator of physiological homeostasis. During development, multiple transcription factors coordinate the patterning and specification of hypothalamic nuclei. However, the molecular mechanisms controlling hypothalamic patterning and cell fate specification are poorly understood. To identify genes that control these processes, we have used single-cell RNA sequencing (scRNA-Seq) to profile mouse hypothalamic gene expression across multiple developmental time points. We have further utilised scRNA-Seq to phenotype mutations in genes that play major roles in early hypothalamic patterning. To first understand hypothalamic development, hypothalami were collected at both embryonic (E10-E16, E18) and postnatal (PN4, PN8, PN14, PN45) time points. At early stages, when the bulk of hypothalamic patterning occurs (E11-E13), we observe a clear separation between mitotic progenitors and postmitotic neural precursor cells. We likewise observed clean segregation among cells expressing regional hypothalamic markers identified in previous large-scale analysis of hypothalamic development. This analysis reveals new region-specific markers and identifies candidate genes for selectively regulating patterning and cell fate specification in individual hypothalamic regions. With our rich dataset of developing mouse hypothalamus, we integrated our dataset with the Allen Brain Atlas in situ data, publicly available adult hypothalamic scRNA-Seq dataset to understand hierarchy of hypothalamic cell differentiation, as well as re-defining cell types of the hypothalamus. We next used scRNA-Seq to phenotype multiple mutant lines, including a line that has been extensively characterised as a proof of concept (Ctnnb1 overexpression), and lines that have not been characterised (Nkx2.1, Nkx2.2, Dlx1/2 deletion). We show that this approach can rapidly and comprehensively characterize mutants that have altered hypothalamic patterning, and in doing so, have identified multiple genes that simultaneously repress posterior hypothalamic identity while promoting prethalamic identity. This result supports a modified columnar model of organization for the diencephalon, where prethalamus and hypothalamus are situated in adjacent dorsal and ventral domains of the anterior diencephalon. These data serve as a resource for further studies of hypothalamic development and dysfunction, and able to delineate transcriptional regulatory networks of hypothalamic formation. Lastly, using our mouse hypothalamus as a guideline, we are comparing dataset of developing chicken, zebrafish and human hypothalamus, to identify evolutionarily conserved and divergent region-specific gene regulatory networks. We aim to use this knowledge and information of key molecular pathways of human hypothalamic development and produce human hypothalamus organoids.

scholarly journals iEDGE: integration of Epi-DNA and Gene Expression and applications to the discovery of somatic copy number-associated drivers in cancer

2019 ◽  
Author(s):  
Amy Li ◽  
Bjoern Chapuy ◽  
Xaralabos Varelas ◽  
Paola Sebastiani ◽  
Stefano Monti
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Regulatory Networks ◽  
Large Scale ◽  
Method Development ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cis And Trans

AbstractThe emergence of large-scale multi-omics data warrants method development for data integration. Genomic studies from cancer patients have identified epigenetic and genetic regulators – such as methylation marks, somatic mutations, and somatic copy number alterations (SCNAs), among others – as predictive features of cancer outcome. However, identification of “driver genes” associated with a given alteration remains a challenge. To this end, we developed a computational tool, iEDGE, to model cis and trans effects of (epi-)DNA alterations and identify potential cis driver genes, where cis and trans genes denote those genes falling within and outside the genomic boundaries of a given (epi-)genetic alteration, respectively.First, iEDGE identifies the cis and trans genes associated with the presence/absence of a particular epi-DNA alteration across samples. Tests of statistical mediation are then performed to determine the cis genes predictive of the trans gene expression. Finally, cis and trans effects are annotated by pathway enrichment analysis to gain insights into the underlying regulatory networks.We used iEDGE to perform integrative analysis of SCNAs and gene expression data from breast cancer and 18 additional cancer types included in The Cancer Genome Atlas (TCGA). Notably, cis gene drivers identified by iEDGE were found to be significantly enriched for known driver genes from multiple compendia of validated oncogenes and tumor suppressors, suggesting that the remainder are of equal importance. Furthermore, predicted drivers were enriched for functionally relevant cancer genes with amplification-driven dependencies, which are of potential prognostic and therapeutic value. All the analyses results are accessible athttps://montilab.bu.edu/iEDGE.

scholarly journals Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Yi Shen ◽  
Wei Xiong ◽  
Qi Gu ◽  
Qin Zhang ◽  
Jia Yue ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Molecular Subtypes ◽  
Therapeutic Targets ◽  
Clinical Information ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Liver Carcinoma ◽  
Normal Tissues ◽  
Omics Analysis ◽  
Cancer Tissues

Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis.Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes.Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p &lt; 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes.Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer.

scholarly journals Multi-omics analysis to identify driving factors in colorectal cancer

Epigenomics ◽  
2020 ◽  
Vol 12 (18) ◽  
pp. 1633-1650
Author(s):  
Xi Xu ◽  
Chaoju Gong ◽  
Yunfeng Wang ◽  
Yanyan Hu ◽  
Hong Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Mechanisms ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Omics Analysis ◽  
Competing Endogenous Rna Network ◽  
Cancer Genome Atlas

Aim: We aim to identify driving genes of colorectal cancer (CRC) through multi-omics analysis. Materials & methods: We downloaded multi-omics data of CRC from The Cancer Genome Atlas dataset. Integrative analysis of single-nucleotide variants, copy number variations, DNA methylation and differentially expressed genes identified candidate genes that carry CRC risk. Kernal genes were extracted from the weighted gene co-expression network analysis. A competing endogenous RNA network composed of CRC-related genes was constructed. Biological roles of genes were further investigated in vitro. Results: We identified LRRC26 and REP15 as novel prognosis-related driving genes for CRC. LRRC26 hindered tumorigenesis of CRC in vitro. Conclusion: Our study identified novel driving genes and may provide new insights into the molecular mechanisms of CRC.

scholarly journals Integrative Analysis to Uncover the Molecular Mechanisms of Caesalpinia sappan L. for Anti-Cancer Activity

2021 ◽  
Vol 16 (11) ◽  
pp. 1934578X2110399
Author(s):  
Bing Liu ◽  
Hao Lian
Keyword(s):  
Molecular Docking ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
The Cancer Genome Atlas ◽  
Network Pharmacology ◽  
Dependent Manner ◽  
Genomic Databases ◽  
Caesalpinia Sappan ◽  
Dose Dependent

Objectives: Caesalpinia Sappan L. is a traditional Chinese medicine with a long history. Recent studies have confirmed that Sappan has an antitumor effect, but its specific mechanism is still unclear. Methods: In this study, we used network pharmacology to predict the target and signal pathway of Sappan. In addition, the Cancer Genome Atlas and cancer cell lines encyclopedia large-scale genomic databases were used to analyze the relationship between different subtypes of Akt. Based on molecular docking technology, the interaction mode between small molecule compounds and protein targets was explored. Finally, we studied the effect of Sappan on Akt protein expression by Western blot in vitro. Results: AKT1 and AKT2 were significantly expressed in breast cancer cells, but they were significantly different from AKT3. Finally, molecular docking analysis showed that (3R,5R)-1,3,4,5-tetrakis(((E)-3-(3,4-dihydroxyphenyl)acryloyl)oxy)cyclohexane-1-carboxylic acid had a very ideal binding mode with Akt. Subsequent experiments showed that Sappan extract could induce apoptosis of HepG2 cells in a dose-dependent manner, and down regulate the phosphorylation level of Akt protein thr308 in a dose-dependent manner. Conclusions: This study provides new ideas for Sappan's anticancer research through the strategy of system pharmacology.

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