Network-based approaches for anticancer therapy

Seo, Hyunduk; Kim, Wanyeon; Lee, Ji-Hyung; Youn, BuHyun

doi:10.3892/ijo.2013.2114

Cited by 13 publications

(8 citation statements)

References 85 publications

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“…On the contrary, if the hubs are targeted, then the system becomes extremely fragile and is more prone to collapse in response to drug treatment [52]. Keeping this in mind, it is clear that, in order to design a therapeutic strategy with higher chances of success, a correct classification of the network being studied should be performed before hand, together with a precise identification of its hubs [92].…”

Section: For Therapeutic Applicationsmentioning

confidence: 98%

PTEN ceRNA networks in human cancer

Poliseno

Pandolfi

2015

Methods

108

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Section: For Therapeutic Applicationsmentioning

confidence: 98%

PTEN ceRNA networks in human cancer

Poliseno

Pandolfi

2015

Methods

108

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“…Functionalization of previously uncharacterized transcripts could be achieved, partially by identifying the ceRNA interactors, to present a framework for predicting and validating ceRNA interactions; this strategy may be universally applied to any transcript. In a scale-free network, links between nodes follow a power-law distribution, which suggests that most nodes have only a few links, while a few nodes can possess a large number of links [164]. These post-transcriptional ceRNETs can be considered as scale-free networks, because their structure is constructed upon smaller interconnected subnetworks, in which the nodes (ceRNAs) are linked by a large number of connections (miRNAs) [11].…”

Section: Potential Prognostic Biomarkers and Therapeutic Targets In Hccmentioning

confidence: 99%

The emerging roles of non-coding competing endogenous RNA in hepatocellular carcinoma

Xiao

et al. 2020

Cancer Cell Int

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Accumulating evidence has emerged revealing that noncoding RNAs (ncRNAs) play essential roles in the occurrence and development of hepatocellular carcinoma (HCC). However, the complicated regulatory interactions among various ncRNAs in the development of HCC are not entirely understood. The newly discovered mechanism of competing endogenous RNAs (ceRNAs) uncovered regulatory interactions among different varieties of RNAs. In recent years, a growing number of studies have suggested that ncRNAs, including long ncRNAs, circular RNAs and pseudogenes, play major roles in the biological functions of the ceRNA network in HCC. These ncRNAs can share microRNA response elements to affect microRNA affinity with target RNAs, thus regulating gene expression at the transcriptional level and both physiological and pathological processes. The ncRNAs that function as ceRNAs are involved in diverse biological processes in HCC cells, such as tumor cell proliferation, epithelial-mesenchymal transition, invasion, metastasis and chemoresistance. Based on these findings, ncRNAs that act as ceRNAs may be promising candidates for clinical diagnosis and treatments. In this review, we discuss the mechanisms and research methods of ceRNA networks. We also reviewed the recent advances in studying the roles of ncRNAs as ceRNAs in HCC and highlight possible directions and possibilities of ceRNAs as diagnostic biomarkers or therapeutic targets. Finally, the limitations, gaps in knowledge and opportunities for future research are also discussed.

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“…The efficacy of a single miRNA therapy can also be questioned. Mechanisms of drug resistance and tumor recurrence can and probably will occur due to compensatory pathways present in the same network (reviewed by [ 87 ]). Thus, aiming at marginal nodes might lead to a deviation of a pathway in a certain network, but the outcome might still be the same through alternative routes.…”

Section: Therapeutic Perspectives Of Mirna Network In Cancermentioning

confidence: 99%

Using microRNA Networks to Understand Cancer

Dragomir

Mafra

Dias

et al. 2018

IJMS

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Human cancers are characterized by deregulated expression of multiple microRNAs (miRNAs), involved in essential pathways that confer the malignant cells their tumorigenic potential. Each miRNA can regulate hundreds of messenger RNAs (mRNAs), while various miRNAs can control the same mRNA. Additionally, many miRNAs regulate and are regulated by other species of non-coding RNAs, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs). For this reason, it is extremely difficult to predict, study, and analyze the precise role of a single miRNA involved in human cancer, considering the complexity of its connections. Focusing on a single miRNA molecule represents a limited approach. Additional information could come from network analysis, which has become a common tool in the biological field to better understand molecular interactions. In this review, we focus on the main types of networks (monopartite, association networks and bipartite) used for analyzing biological data related to miRNA function. We briefly present the important steps to take when generating networks, illustrating the theory with published examples and with future perspectives of how this approach can help to better select miRNAs that can be therapeutically targeted in cancer.

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Network-based approaches for anticancer therapy

Cited by 13 publications

References 85 publications

PTEN ceRNA networks in human cancer

PTEN ceRNA networks in human cancer

The emerging roles of non-coding competing endogenous RNA in hepatocellular carcinoma

Using microRNA Networks to Understand Cancer

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