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

Zhou, Bin; Guo, Rui

doi:10.3390/genes10060464

Cited by 10 publications

(8 citation statements)

References 39 publications

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“…It has been demonstrated that modulating gene expression is one of the most important ways for CNV to play diversi ed roles in diseases [11][12][13][14]. In this study, the results showed that 5022 gene expressions in TCGA were signi cantly modulated by CNV (p <0.05, adjusted p <0.2) and 577 genes in TARGET were signi cantly associated with CNV (p <0.05, adjusted p <0.2).…”

Section: Integrative Analysis Of Gene Expressions In Concordance Withmentioning

confidence: 59%

Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

Niu¹,

Wu²,

Li³

et al. 2020

Preprint

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Purpose Acute myeloid leukemia (AML) is caused by multiple genetic alterations in the hematopoietic progenitors, and molecular genetic analysis has provided useful information for AML diagnosis and prognosis. However, an integrative understanding about the prognosis value of specific copy number variation (CNV) and CNV-modulated gene expression has been limited. Methods We conducted an integrative analysis of CNV profiling and gene expression using data from the TARGET and TCGA AML cohorts. The CNV data from TCGA were analyzed using the GISTIC. CNV survival analysis and mRNA survival analysis were conducted with the Multivariate Cox proportional hazards regression model using R software with “survminer” and “survival” packages. KEGG cancer panel genes were extracted from the cancer related pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG). The R package “circlize” was used for mapping the CNV genes to chromosomes. Results From this investigation, we observed distinct CNV patterns in the AML risk groups as well as the expression of 251 genes significantly modulated by CNV in both cohorts. There were 102 CNV genes (located at 7q31-34, 16q24) associated with clinical outcomes in AML, which were identified in the TARGET cohort and validated in the TCGA cohort, three of which being miRNA genes (MIR29A, MIR183, MIR335) that overlapped with a KEGG cancer panel. Five genes were identified whose expressions were modulated by CNV and significantly associated with clinical outcomes, and among them, the deletion of SEMA4D and CBFB were found to potentially have protective effects against AML. Moreover, the distribution of CNV in these five CNV-modulated genes was independent of the risk groups, which suggests that they are independent prognosis factors. Conclusion Overall, this study identified 102 CNV genes and five CNV-modulated gene expressions that are crucial for developing new modes of prognosis evaluation and target therapy for AML.

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Section: Integrative Analysis Of Gene Expressions In Concordance Withmentioning

confidence: 59%

Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

Niu¹,

Wu²,

Li³

et al. 2020

Preprint

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“…From that, Benjamini and Hochberg's false discovery rate (FDR) may be a better choice. Likewise, many previous works [49][50][51][52][53] related the expression levels of each identified driver gene to prognostic value (e.g., the overall survival of patients), and the genes when P-value ≤ 0.05 (Log-rank test) were considered to define significant association. Again, FDR control is crucial, so we developed the tool 'geneSA' (https ://githu b.com/huyng uyen2 50896 /geneS A) to automatically do the above task and only preserve the genes if Q-value ≤ 0.05 (Benjamini-Hochberg FDR).…”

Section: List Of Improvements Proposed In the Work Selection Of Drivmentioning

confidence: 99%

“…1, Stage 2-Step 4) and patient stratification ( Fig. 1, Stage 2-Step 5), which is a common selection from previous studies 10,11,14,49,51,52 . Furthermore, these previous works performed the hierarchical clustering method using complete linkage and Euclidean distance for the clustering task in co-expression network construction and patient stratification.…”

Section: Selection Of Tools For Unsupervised Identification Of Co-expmentioning

confidence: 99%

“…For survival rate, we performed a survival analysis for the expression profiles of each driver gene, like in refs. [49][50][51][52][53] . In brief, given a driver gene, the median expression of that gene was calculated across the patients, then the patients were classified into two groups based on the expression of the gene.…”

Section: Selection Of Tools For Unsupervised Identification Of Co-expmentioning

confidence: 99%

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Improving existing analysis pipeline to identify and analyze cancer driver genes using multi-omics data

Nguyen¹,

2020

Sci Rep

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The cumulative of genes carrying mutations is vital for the establishment and development of cancer. However, this driver gene exploring research line has selected and used types of tools and models of analysis unsystematically and discretely. Also, the previous studies may have neglected low-frequency drivers and seldom predicted subgroup specificities of identified driver genes. In this study, we presented an improved driver gene identification and analysis pipeline that comprises the four most widely focused analyses for driver genes: enrichment analysis, clinical feature association with expression profiles of identified driver genes as well as with their functional modules, and patient stratification by existing advanced computational tools integrating multi-omics data. The improved pipeline's general usability was demonstrated straightforwardly for breast cancer, validated by some independent databases. Accordingly, 31 validated driver genes, including four novel ones, were discovered. Subsequently, we detected cancer-related significantly enriched gene ontology terms and pathways, probable drug targets, two co-expressed modules associated significantly with several clinical features, such as number of positive lymph nodes, Nottingham prognostic index, and tumor stage, and two biologically distinct groups of BRCA patients. Data and source code of the case study can be downloaded at https://github.com/hauldhut/drivergene.

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“…Numerous miRNA studies have identified histological grade and stage (pT) classification-dependent miRNA expression and have proven the existence of miRNAs alterations related to the two divergent pathways found in the development of NMIBC and MIBC [8,9]. Only a few studies have analyzed miRNA as a prognostic and predictive biomarker [10,11,12]. Each miRNA can have multiple targets, and changes in their expression profile could have a magnified effect on cellular phenotype.…”

Section: Introductionmentioning

confidence: 99%

MicroRNAs Which Can Prognosticate Aggressiveness of Bladder Cancer

Borkowska

Konecki

Pietrusiński

et al. 2019

Cancers

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Bladder cancer (BC) is still characterized by a very high death rate in patients with this disease. One of the reasons for this is the lack of adequate markers which could help determine the biological potential of the tumor to develop into its invasive stage. It has been found that some microRNAs (miRNAs) correlate with disease progression. The purpose of this study was to identify which miRNAs can accurately predict the presence of BC and can differentiate low grade (LG) tumors from high grade (HG) tumors. The study included 55 patients with diagnosed bladder cancer and 30 persons belonging to the control group. The expression of seven selected miRNAs was estimated with the real-time PCR technique according to miR-103-5p (for the normalization of the results). Receiver operating characteristics (ROC) curves and the area under the curve (AUC) were used to evaluate the feasibility of using selected markers as biomarkers for detecting BC and discriminating non-muscle invasive BC (NMIBC) from muscle invasive BC (MIBC). For HG tumors, the relevant classifiers are miR-205-5p and miR-20a-5p, whereas miR-205-5p and miR-182-5p are for LG (AUC = 0.964 and AUC = 0.992, respectively). NMIBC patients with LG disease are characterized by significantly higher miR-130b-3p expression values compared to patients in HG tumors.

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

Cited by 10 publications

References 39 publications

Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

Identification of Prognostic Signature Based on the Copy Number Variation (CNV) and Expression in Acute Myeloid Leukemia

Improving existing analysis pipeline to identify and analyze cancer driver genes using multi-omics data

MicroRNAs Which Can Prognosticate Aggressiveness of Bladder Cancer

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