miRACA: A database for miRNAs associated with cancers and age related disorders (ARD)

doi:10.1007/s11515-018-1481-7

Front. Biol.

2018, Vol. 13

Issue (1) : 36-50 https://doi.org/10.1007/s11515-018-1481-7

RESEARCH ARTICLE

miRACA: A database for miRNAs associated with cancers and age related disorders (ARD)

Razia Rahman, Lokesh Kumar Gahlot, Yasha Hasija(

)

Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, Delhi-110042, India

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Abstract

BACKGROUND: With the given diversity and abundance of several targets of miRNAs, they functionally appear to interact with several elements of the multiple cellular networks to maintain physiologic homeostasis. They can function as tumor suppressors or oncogenes, whose under or overexpression has both diagnostic and prognostic significance in various cancers while being implicated as prospective regulators of age-related disorders (ARD) as well. Establishing a concatenate between ARD and cancers by looking into the insights of the shared miRNAs may have a practical relevance.

METHODS: In the present work, we performed network analysis of miRNA-disease association and miRNA-target gene interaction to prioritize miRNAs that play significant roles in the manifestation of cancer as well as ARD. Also, we developed a repository that stores miRNAs common to both ARD and cancers along with their target genes.

RESULTS: We have comprehensively curated all miRNAs that we found to be shared in both the diseases in the human genome and established a database, miRACA (Database for microRNAs Associated with Cancers and ARD) that currently houses information of 1648 miRNAs that are significantly associated with 38 variants supported with pertinent data. It has been made available online at http://genomeinformatics.dtu.ac.in/miraca/ for easy retrieval and utilization of data by the scientific community.

CONCLUSION: To the best of our knowledge, our database is the first attempt at compilation of such data. We believe this work may serve as a significant resource and facilitate the analysis of miRNA regulatory mechanisms shared between cancers and ARD to apprehend disease etiology.

Keywords miRNA cancer age related disorders (ARD) target genes database

Corresponding Author(s): Yasha Hasija

Online First Date: 15 March 2018 Issue Date: 26 March 2018

Cite this article:

Razia Rahman,Lokesh Kumar Gahlot,Yasha Hasija. miRACA: A database for miRNAs associated with cancers and age related disorders (ARD)[J]. Front. Biol., 2018, 13(1): 36-50.

URL:

https://academic.hep.com.cn/fib/EN/10.1007/s11515-018-1481-7
https://academic.hep.com.cn/fib/EN/Y2018/V13/I1/36

Fig.1 Graphical representation of the workflow.

Tab.1 Phenotypes included in ARD data collection

Tab.2 Phenotypes included in cancer data collection

Fig.2 miRNA-ARD bipartite network. The red colored node represents breast neoplasm, yellow colored node represents stomach neoplasm, and pink colored node represents colorectal neoplasm.

Fig.3 miRNA-cancer bipartite network.The red colored node represents hepatocellular carcinoma, yellow colored node represents breast neoplasm, and green colored node represents stomach neoplasm.

Fig.4 SharedmiRNAsasscociated with both ARD and cancers.

Fig.5 miRNA-target gene bipartite network. The yellow colored node represents BCL2, green colored node represents ZEB1, and blue colored node represents ITGB3.

Tab.3 Degree and closeness centrality values of the selected sharedmiRNAs (taking degree value 9 as the threshold value)

Tab.4 Functional annotation clustering analysis of the selected sharedmiRNA target genes with the highest enrichment score (data shown for first cluster only)

Fig.6 (A) Biological process analysis of the selected sharedmiRNA target genes. (B) Molecular function analysis of the selected sharedmiRNA target genes. (C) Pathway analysis of the selected sharedmiRNA target genes.

Tab.5 Biological process analysis of the selected sharedmiRNA target genes

Tab.6 Ontology analysis. Molecular function analysis of the selected sharedmiRNA target genes

Pathways	Number of genes (percentage)
CCKR (cholecystokinin receptor) signaling map	12 genes (14%)
Inflammation mediated by chemokine and cytokine signaling pathway	12 genes (14%)
Angiogenesis	11 genes (12.8%)
Gonadotropin-releasing hormone receptor pathway	8 genes (9.3%)
PDGF signaling pathway	8 genes (9.3%)
Integrin signaling pathway	8 genes (9.3%)
Wnt signaling pathway	7 genes (8.1%)
p53 pathway feedback loops 2	7 genes (8.1%)
Apoptosis signaling pathway	6 genes (7%)
Ras Pathway	6 genes (7%)
TGF-beta signaling pathway	6 genes (7%)
Alzheimer disease-presenilin pathway	5 genes (5.8%)
Interleukin signaling pathway	4 genes (4.7%)
pI3 kinase pathway	4 genes (4.7%)
p53 pathway	4 genes (4.7%)
T cell activation	3 genes (3.5%)
Oxidative stress response	3 genes (3.5%)
Toll receptor signaling pathway	3 genes (3.5%)
VEGF signaling pathway	3 genes (3.5%)
Insulin/IGF pathway-protein kinase B signaling cascade	3 genes (3.5%)
Cytoskeletal regulation by Rho GTPase	3 genes (3.5%)
EGF receptor signaling pathway	3 genes (3.5%)
Blood coagulation	3 genes (3.5%)
Alzheimer disease-amyloid secretase pathway	2 genes (2.3%)
axon guidance mediated by semaphorins	2 genes (2.3%)
B cell activation	2 genes (2.3%)
Axon guidance mediated by Slit/Robo	2 genes (2.3%)
Cadherin signaling pathway	2 genes (2.3%)
Cell cycle	2 genes (2.3%)
Endothelin signaling pathway	2 genes (2.3%)
Interferon-gamma signaling pathway	2 genes (2.3%)
FGF signaling pathway	2 genes (2.3%)
Huntington disease	2 genes (2.3%)
Insulin/IGF pathway-mitogen activated protein kinase kinase/MAP kinase cascade	2 genes (2.3%)
FAS signaling pathway	1 gene (1.2%)
p38 MAPK pathway	1 gene (1.2%)
p53 pathway by glucose deprivation	1 gene (1.2%)
Plasminogen activating cascade	1 gene (1.2%)
JAK/STAT signaling pathway	1 gene (1.2%)
MYO signaling pathway	1 gene (1.2%)
Hypoxia response via HIF activation	1 gene (1.2%)
p53 pathway feedback loops 1	1 gene (1.2%)
Heterotrimeric G-protein signaling pathway-Gq alpha and Go alpha mediated pathway	1 gene (1.2%)
Axon guidance mediated by netrin	1 gene (1.2%)
ALP23B signaling pathway	1 gene (1.2%)
Activin beta signaling pathway	1 gene (1.2%)
BMP/activin signaling pathway-drosophila	1 gene (1.2%)
Angiotensin ii-stimulated signaling through g proteins and beta-arrestin	1 gene (1.2%)

Tab.7 Ontology analysis. Pathway analysis of the selected sharedmiRNA target genes

Fig.7 Graph showing the distribution ofdisease class in miRACA.

Tab.8 List of disease class included in miRACA

Fig.8 (A) miRACA.About page. (B) miRACA.Home (Query) page. (C) miRACA.Results page.

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