Abstract

Widespread mRNA 3′ UTR shortening through alternative polyadenylation1 promotes tumor growth in vivo2. A prevailing hypothesis is that it induces proto-oncogene expression in cis through escaping microRNA-mediated repression. Here we report a surprising enrichment of 3′UTR shortening among transcripts that are predicted to act as competing-endogenous RNAs (ceRNAs) for tumor-suppressor genes. Our model-based analysis of the trans effect of 3′ UTR shortening (MAT3UTR) reveals a significant role in altering ceRNA expression. MAT3UTR predicts many trans-targets of 3′ UTR shortening, including PTEN, a crucial tumor-suppressor gene3 involved in ceRNA crosstalk4 with nine 3′UTR-shortening genes, including EPS15 and NFIA. Knockdown of NUDT21, a master 3′ UTR-shortening regulator2, represses tumor-suppressor genes such as PHF6 and LARP1 in trans in a miRNA-dependent manner. Together, the results of our analysis suggest a major role of 3′ UTR shortening in repressing tumor-suppressor genes in trans by disrupting ceRNA crosstalk, rather than inducing proto-oncogenes in cis.

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Acknowledgements

This work was supported by US National Institutes of Health (NIH) grants R01HG007538, R01CA193466 and U54CA217297, Cancer Prevention Research Institute of Texas (CPRIT) grant RP150292 to W.L., CPRIT RP100107 to E.J.W. and A.-B.S., CPRIT RP140800 and Welch Foundation AU-1889 to E.J.W., and NIH RO1GM046454 and the Houston Endowment, Inc. to A.-B.S.

Author information

Author notes

  1. These authors contributed equally: Hyun Jung Park, Ping Ji.

  2. These authors jointly supervised this work: Eric J. Wagner, Wei Li.

Affiliations

  1. Division of Biostatistics, Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA

    • Hyun Jung Park
    • , Zheng Xia
    • , Benjamin Rodriguez
    • , Lei Li
    • , Jianzhong Su
    • , Kaifu Chen
    •  & Wei Li
  2. Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA

    • Hyun Jung Park
    • , Zheng Xia
    • , Benjamin Rodriguez
    • , Lei Li
    • , Jianzhong Su
    • , Kaifu Chen
    •  & Wei Li
  3. Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA

    • Hyun Jung Park
  4. Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX, USA

    • Ping Ji
    • , David Baillat
    • , Camila R. Fontes-Garfias
    •  & Eric J. Wagner
  5. Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA

    • Soyeon Kim
  6. Department of Pharmaceutical Sciences, College of Pharmacy and Health Sciences, Butler University, Indianapolis, IN, USA

    • Chioniso P. Masamha
  7. Department of Biochemistry and Molecular Biology, University of Texas, McGovern Medical School, Houston, TX, USA

    • Ann-Bin Shyu
  8. Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, USA

    • Joel R. Neilson

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Contributions

H.J.P. and W.L. conceived the project, designed the experiments and performed the data analysis. S.K. performed the regression analysis. Z.X. performed the APA analysis. L.L., J.S. and K.C. helped with data analysis. C.P.M., E.J.W. and A.-B.S. obtained the miRNA-Seq data. P.J., C.R.F.-G. and D.B. performed the NUDT21-knockdown experiments. H.J.P., P.J., E.J.W. and W.L. wrote the manuscript with input from B.R., A.-B.S., C.P.M. and J.R.N.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Eric J. Wagner or Wei Li.

Integrated supplementary information

  1. Supplementary Figure 1 3′UTR-shortening trans effect is associated with 3′UTR-shortening, but not with methylation changes.

    (a) Scatter plot showing anti-correlation between ceRNA gene expression change in tumors (Y-axis, tumor / normal) vs. degree of 3′UTR shortening in tumors (X-axis, ΔPDUI normal - tumor) of the associated 3′UTR-shortening genes. Methylation level change (tumor vs. normal) on promoter regions (±1 Kbp from TSS) of (b) 158 3′US ceRNA tumor suppressors and the same number of sample control tumor suppressors and (c) PTEN on the 5 randomly-selected tumor normal pairs in More 3′US and Less 3′US groups (defined in Fig. 3d). Statistical significance is estimated from t-test.

  2. Supplementary Figure 2 Sequence features of 3′UTRs of 500 tumor suppressors and their 3′US ceRNAs (381).

    (a). 3′UTR lengths, (b) their phastCons score based on alignments of 45 vertebrate genomes with Human (the smaller, the faster it evolves15), and (c) the number of putative polyA motifs16 in the 3′UTRs. Statistical significance is estimated from t-test.

  3. Supplementary Figure 3 MAT3UTR performance analysis.

    (a). Transcript X has a constituitive proximal 3′-UTR (pUTR) and a distal 3′-UTR that might be shortened in tumors (dUTR) (b). X is a set of 3′US genes that are ceRNA partners of y′, and Y is a set of ceRNA partners to X. The edge represents ceRNA crosstalk. Note that this model is implicitly dependent on y′, since X and Y are defined on the basis of y′. Observed gene expression changes (tumor/normal) vs. MAT3UTR model scores (c) and MAT3UTR-control model score (d). Correlation (e) and mean square error (f) of MAT3UTR model scores based on 100 runs of 10-fold cross validation, when the model is learned from the ridge regression and classical linear regression. (g) Observed PTEN expression change (tumor/normal) vs. MAT3UTR score for each tumor/normal pair.

  4. Supplementary Figure 4 AGO2 and DICER expression in NUDT21 KD HeLa cell.

    Detection of AGO2 associated genes in HeLa cells by real time PCR (a) RNA-binding protein immunoprecipitation (RIP) was performed with AGO2 antibody, normal mouse IgG was served as a control. The RIP complex was detected by western blot with another AGO2 antibody from Rat. (b) AGO2 associated genes were measured by real time PCR. Two candidate ceRNAs, PHF6 and LARP1, and LAMC1 3′UTR shortening gene were enriched up to 229.5, 343.6 and 232.1 fold. FOS was served as a positive control and 7SK snRNA as a negative control. (c) Dicer1 expression level in Ctrl and NUDT21 KD HeLa cells (d) Scatterplot showing miRNA expression levels in Ctrl or NUDT21 KD HeLa cells, where black lines indicate differentially expressed miRNAs (2-fold up or down).

  5. Supplementary Figure 5 Knock down of PHF6 and LARP1 increase cell growth.

    PHF6 and LARP1 was reduced by siRNAs (a) and led to increase cell growth (b). In (b), the sample size is triplicate for each time point and two-sided T- test was used to calculate the p-values.

Supplementary information

  1. Supplementary Text and Figures

    Supplementary Figures 1–5 and Supplementary Note

  2. Reporting Summary

  3. Supplementary Table 1

    Tab 3US ceRNA hub contains 591 ceRNA partners of 3′ UTR–shortening genes in TCGA breast cancer data that are connected to more than 500 genes in the normal ceRNET

  4. Supplementary Table 2

    The MAT3UTR for BRCA tab contains information of 1,548 differentially expressed 3′ US ceRNA partners in breast tumor/normal ceRNETs; MAT3UTR score indicates predicted expression changes from the MAT3UTR model

  5. Supplementary Table 3

    The MAT3UTR for NUDT21 tab contains information on 57 tumor suppressors that are 3′ US ceRNA partners in wild-type and NUDT21 KD data; MAT3UTR score indicates predicted expression changes from MAT3UTR

  6. Supplementary Table 4

    The Coefs for MAT3UTR for NUDT21 tab contains β_miRj (coefficients) from eq. (3) (Methods) for each miRNA (miRj) and each gene (y′)

  7. Supplementary Table 5

    Primer sequences for RIP–qPCR

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DOI

https://doi.org/10.1038/s41588-018-0118-8

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