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

doi:10.1007/s11515-018-1481-7

Frontiers in Biology

2018, Vol. 13

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

本期目录

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.

Key words： miRNA cancer age related disorders (ARD) target genes database

收稿日期: 2017-09-09 出版日期: 2018-03-26

Corresponding Author(s): Yasha Hasija

引用本文:

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

链接本文:

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

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Tab.6

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%)

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