3′-UTR shortening contributes to subtype-specific cancer growth by breaking stable ceRNA crosstalk of housekeeping genes

Fan, Zhenjiang; Kim, Soyeon; Bai, Yinge; Diergaarde, Brenda; Oesterreich, Steffi; Park, Hyun Jung

doi:10.1101/601526

Cited by 4 publications

(4 citation statements)

References 44 publications

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“…Recent studies have shown role of ceRNA network in the stabilization and translation efficiency of longer UTR APA isoforms. 3′‐UTR shortening can result in a reduction in protein expression in trans through its effect on ceRNA crosstalk (Fan et al, 2020; L. Li et al, 2014; H. J. Park et al, 2018).…”

Section: Mechanism Of the Paradox Of 3′‐utr Length Versus Protein Expressionmentioning

confidence: 99%

Alternative polyadenylation: An enigma of transcript length variation in health and disease

et al. 2021

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Alternative polyadenylation (APA) is a molecular mechanism during a pre‐mRNA processing that involves usage of more than one polyadenylation site (PA‐site) generating transcripts of varying length from a single gene. The location of a PA‐site affects transcript length and coding potential of an mRNA contributing to both mRNA and protein diversification. This variation in the transcript length affects mRNA stability and translation, mRNA subcellular and tissue localization, and protein function. APA is now considered as an important regulatory mechanism in the pathophysiology of human diseases. An important consequence of the changes in the length of 3′‐untranslated region (UTR) from disease‐induced APA is altered protein expression. Yet, the relationship between 3′‐UTR length and protein expression remains a paradox in a majority of diseases. Here, we review occurrence of APA, mechanism of PA‐site selection, and consequences of transcript length variation in different diseases. Emerging evidence reveals coordinated involvement of core RNA processing factors including poly(A) polymerases in the PA‐site selection in diseases‐associated APAs. Targeting such APA regulators will be therapeutically significant in combating drug resistance in cancer and other complex diseases. This article is categorized under: RNA Processing > 3′ End Processing RNA in Disease and Development > RNA in Disease Translation > Regulation

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Section: Mechanism Of the Paradox Of 3′‐utr Length Versus Protein Expressionmentioning

confidence: 99%

Alternative polyadenylation: An enigma of transcript length variation in health and disease

et al. 2021

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“…Also, this research was supported in part by the University of Pittsburgh Center for Research Computing through the resources provided. This manuscript has been released as a Pre-Print at Zhenjiang et al (2019Zhenjiang et al ( ) (doi: 10.1101.…”

Section: Data Availability Statementmentioning

confidence: 99%

3′-UTR Shortening Contributes to Subtype-Specific Cancer Growth by Breaking Stable ceRNA Crosstalk of Housekeeping Genes

Fan

Kim

Bai

et al. 2020

Front. Bioeng. Biotechnol.

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Shortening of 3 ′ UTRs (3 ′ US) through alternative polyadenylation is a post-transcriptional mechanism that regulates the expression of hundreds of genes in human cancers. In breast cancer, different subtypes of tumor samples, such as estrogen receptor positive and negative (ER+ and ER-), are characterized by distinct molecular mechanisms, suggesting possible differences in the post-transcriptional regulation between the subtype tumors. In this study, based on the profound tumorigenic role of 3 ′ US interacting with competing-endogenous RNA (ceRNA) network (3 ′ US-ceRNA effect), we hypothesize that the 3 ′ US-ceRNA effect drives subtype-specific tumor growth. However, we found that the subtypes are available in different sample sizes, biasing the ceRNA network size and disabling the fair comparison of the 3 ′ US-ceRNA effect. Using normalized Laplacian matrix eigenvalue distribution, we addressed this bias and built tumor ceRNA networks comparable between the subtypes. Based on the comparison, we identified a novel role of housekeeping (HK) genes as stable and strong miRNA sponges (sponge HK genes) that synchronize the ceRNA networks of normal samples (adjacent to ER+ and ER-tumor samples). We further found that distinct 3 ′ US events in the ER-tumor break the stable sponge effect of HK genes in a subtype-specific fashion, especially in association with the aggressive and metastatic phenotypes. Knockdown of NUDT21 further suggested the role of 3 ′ US-ceRNA effect in repressing HK genes for tumor growth. In this study, we identified 3 ′ US-ceRNA effect on the sponge HK genes for subtype-specific growth of ER-tumors.

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“…In complex biological systems such as humans, molecular and clinical features demonstrate variable associations in diseases such as cancer, asthma, and sepsis (1)(2) (3). Identifying the causal relations in the association is critical to improving translational understanding since causal relations can be used to identify potential therapeutic agents that can control the diseases.…”

Section: Introductionmentioning

confidence: 99%

Causal inference using deep-learning variable selection identifies and incorporates direct and indirect causalities in complex biological systems

Fan

Kernan²,

Benos

et al. 2021

Preprint

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In complex diseases, causal structure learning across biological variables is critical to identify modifiable triggers or potential therapeutic agents. A limitation of existing causal learning methods is that they cannot identify indirect causal relations, those that would interact through latent mediating variables. We developed the first computational method that identifies both direct and indirect causalities, causal inference using deep-learning variable-selection (causalDeepVASE). To accurately identify indirect causalities and incorporate them with direct causalities, causalDeepVASE develops a deep neural network approach and extends a flexible causal inference method. In simulated and biological data of various contexts, causalDeepVASE outperforms existing methods in identifying expected or validated causal relations. Further, causalDeepVASE facilitates a systematic understanding of complex diseases. For example, causalDeepVASE uniquely identified a possible causal relation between IFNγ and creatinine suggested in a polymicrobial sepsis model. In future biomedical studies, causalDeepVASE can facilitate the identification of driver genes and therapeutic agents.

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3′-UTR shortening contributes to subtype-specific cancer growth by breaking stable ceRNA crosstalk of housekeeping genes

Cited by 4 publications

References 44 publications

Alternative polyadenylation: An enigma of transcript length variation in health and disease

Alternative polyadenylation: An enigma of transcript length variation in health and disease

3′-UTR Shortening Contributes to Subtype-Specific Cancer Growth by Breaking Stable ceRNA Crosstalk of Housekeeping Genes

Causal inference using deep-learning variable selection identifies and incorporates direct and indirect causalities in complex biological systems

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