Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers

Oncogene volume 38, pages 6678–6695 (2019)Cite this article

Subjects

Abstract

Alternative splicing represents a critical posttranscriptional regulation of gene expression, which contributes to the protein complexity and mRNA processing. Defects of alternative splicing including genetic alteration and/or altered expression of both pre-mRNA and trans-acting factors give rise to many cancers. By integrally analyzing clinical data and splicing data from TCGA and SpliceSeq databases, a number of splicing events were found clinically relevant in tumor samples. Alternative splicing of KLK2 (KLK2_51239) was found as a potential inducement of nonsense-mediated mRNA decay and associated with poor survival in prostate cancer. Consensus K-means clustering analysis indicated that alternative splicing events could be potentially used for molecular subtype classification of cancers. By random forest survival algorithm, prognostic prediction signatures with well performances were constructed for 31 cancers by using survival-associated alternative splicing events. Furthermore, an online tool for visualization of Kaplan–Meier plots of splicing events in 31 cancers was explored. Briefly, alternative splicing was found of significant clinical relevance with cancers.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Code availability

Research code that was used to implement methods described in this study is publicly available on GitHub: https://github.com/yjzhang2013/OncoSplicing.

References

  1. Baralle FE, Giudice J. Alternative splicing as a regulator of development and tissue identity. Nat Rev Mol Cell Biol. 2017;18:437–51.

    Article  CAS  Google Scholar 

  2. Kelemen O, Convertini P, Zhang Z, Wen Y, Shen M, Falaleeva M, et al. Function of alternative splicing. Gene. 2013;514:1–30.

    Article  CAS  Google Scholar 

  3. Blencowe BJ. The relationship between alternative splicing and proteomic complexity. Trends Biochem Sci. 2017;42:407–8.

    Article  CAS  Google Scholar 

  4. da Costa PJ, Menezes J, Romao L. The role of alternative splicing coupled to nonsense-mediated mRNA decay in human disease. Int J Biochem Cell Biol. 2017;91:168–75.

    Article  Google Scholar 

  5. Tabrez SS, Sharma RD, Jain V, Siddiqui AA, Mukhopadhyay A. Differential alternative splicing coupled to nonsense-mediated decay of mRNA ensures dietary restriction-induced longevity. Nat Commun. 2017;8:306.

    Article  Google Scholar 

  6. Wollerton MC, Gooding C, Wagner EJ, Garcia-Blanco MA, Smith CW. Autoregulation of polypyrimidine tract binding protein by alternative splicing leading to nonsense-mediated decay. Mol Cell. 2004;13:91–100.

    Article  CAS  Google Scholar 

  7. Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet. 2008;40:1413–5.

    Article  CAS  Google Scholar 

  8. Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, et al. Alternative isoform regulation in human tissue transcriptomes. Nature. 2008;456:470–6.

    Article  CAS  Google Scholar 

  9. Davuluri RV, Suzuki Y, Sugano S, Plass C, Huang TH. The functional consequences of alternative promoter use in mammalian genomes. Trends Genet. 2008;24:167–77.

    Article  CAS  Google Scholar 

  10. Climente-Gonzalez H, Porta-Pardo E, Godzik A, Eyras E. The functional impact of alternative splicing in cancer. Cell Rep. 2017;20:2215–26.

    Article  CAS  Google Scholar 

  11. Bauman JA, Li SD, Yang A, Huang L, Kole R. Anti-tumor activity of splice-switching oligonucleotides. Nucleic Acids Res. 2010;38:8348–56.

    Article  CAS  Google Scholar 

  12. Li H, Wang Z, Xiao W, Yan L, Guan W, Hu Z, et al. Androgen-receptor splice variant-7-positive prostate cancer: a novel molecular subtype with markedly worse androgen-deprivation therapy outcomes in newly diagnosed patients. Mod Pathol. 2018;31:198–208.

    Article  CAS  Google Scholar 

  13. Kahles A, Lehmann KV, Toussaint NC, Huser M, Stark SG, Sachsenberg T, et al. Comprehensive analysis of alternative splicing across tumors from 8,705 patients. Cancer Cell. 2018;34:211–24 e6.

    Article  CAS  Google Scholar 

  14. Tian J, Wang Z, Mei S, Yang N, Yang Y, Ke J, et al. CancerSplicingQTL: a database for genome-wide identification of splicing QTLs in human cancer. Nucleic Acids Res. 2018;47:D909–16.

    Article  Google Scholar 

  15. Jayasinghe RG, Cao S, Gao Q, Wendl MC, Vo NS, Reynolds SM, et al. Systematic analysis of splice-site-creating mutations in cancer. Cell Rep. 2018;23:270–81 e3.

    Article  CAS  Google Scholar 

  16. Li Y, Sun N, Lu Z, Sun S, Huang J, Chen Z, et al. Prognostic alternative mRNA splicing signature in non-small cell lung cancer. Cancer Lett. 2017;393:40–51.

    Article  CAS  Google Scholar 

  17. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57.

    Article  CAS  Google Scholar 

  18. Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinf. 2003;4:2.

    Article  Google Scholar 

  19. Hong SK. Kallikreins as biomarkers for prostate cancer. Biomed Res Int. 2014;2014:526341.

    PubMed  PubMed Central  Google Scholar 

  20. Ylitalo EB, Thysell E, Jernberg E, Lundholm M, Crnalic S, Egevad L, et al. Subgroups of castration-resistant prostate cancer bone metastases defined through an inverse relationship between androgen receptor activity and immune response. Eur Urol. 2017;72:E147–7.

    Article  Google Scholar 

  21. Guo ZQ, Zheng T, Chen B, Luo C, Ouyang S, Gong S, et al. Small-molecule targeting of E3 ligase adaptor SPOP in kidney cancer. Cancer Cell. 2016;30:474–84.

    Article  CAS  Google Scholar 

  22. Han L, Diao L, Yu S, Xu X, Li J, Zhang R, et al. The genomic landscape and clinical relevance of A-to-I RNA editing in human cancers. Cancer Cell. 2015;28:515–28.

    Article  CAS  Google Scholar 

  23. Chen F, Zhang Y, Gibbons DL, Deneen B, Kwiatkowski DJ, Ittmann M, et al. Pan-cancer molecular classes transcending tumor lineage across 32 cancer types, multiple data platforms, and over 10,000 cases. Clin Cancer Res. 2018;24:2182–93.

    Article  CAS  Google Scholar 

  24. Karpinski P, Pesz K, Sasiadek MM. Pan-cancer analysis reveals presence of pronounced DNA methylation drift in CpG island methylator phenotype clusters. Epigenomics. 2017;9:1341–52.

    Article  CAS  Google Scholar 

  25. Hoadley KA, Yau C, Wolf DM, Cherniack AD, Tamborero D, Ng S, et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell. 2014;158:929–44.

    Article  CAS  Google Scholar 

  26. Gerstberger S, Hafner M, Tuschl T. A census of human RNA-binding proteins. Nat Rev Genet. 2014;15:829–45.

    Article  CAS  Google Scholar 

  27. Sebestyen E, Singh B, Minana B, Pages A, Mateo F, Pujana MA, et al. Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks. Genome Res. 2016;26:732–44.

    Article  CAS  Google Scholar 

  28. Fu XD, Ares M Jr. Context-dependent control of alternative splicing by RNA-binding proteins. Nat Rev Genet. 2014;15:689–701.

    Article  CAS  Google Scholar 

  29. Eilertsen IA, Sveen A, Stromme JM, Skotheim RI, Nesbakken A, Lothe RA. Alternative splicing expands the prognostic impact of KRAS in microsatellite stable primary colorectal cancer. Int J Cancer. 2018;144:841–7.

    Article  Google Scholar 

  30. Ryan MC, Cleland J, Kim R, Wong WC, Weinstein JN. SpliceSeq: a resource for analysis and visualization of RNA-Seq data on alternative splicing and its functional impactsfunctional impacts. Bioinforma. 2012;28:2385–7.

    Article  CAS  Google Scholar 

  31. Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012;7:562–78.

    Article  CAS  Google Scholar 

  32. Kahles A, Ong CS, Zhong Y, Ratsch G. SplAdder: identification, quantification and testing of alternative splicing events from RNA-Seq data. Bioinforma. 2016;32:1840–7.

    Article  CAS  Google Scholar 

  33. Taliaferro JM, Vidaki M, Oliveira R, Olson S, Zhan L, Saxena T, et al. Distal alternative last exons localize mRNAs to neural projections. Mol cell. 2016;61:821–33.

    Article  CAS  Google Scholar 

  34. Miller MB, Yan Y, Wu Y, Hao B, Mains RE, Eipper BA. Alternate promoter usage generates two subpopulations of the neuronal RhoGEF Kalirin-7. J Neurochem. 2017;140:889–902.

    Article  CAS  Google Scholar 

  35. Ushijima T, Hanada K, Gotoh E, Yamori W, Kodama Y, Tanaka H, et al. Light controls protein localization through phytochrome-mediated alternative promoter selection. Cell. 2017;171:1316.

    Article  CAS  Google Scholar 

  36. Tien JF, Mazloomian A, Cheng SG, Hughes CS, Chow CCT, Canapi LT, et al. CDK12 regulates alternative last exon mRNA splicing and promotes breast cancer cell invasion. Nucleic Acids Res. 2017;45:6698–716.

    Article  CAS  Google Scholar 

  37. Ladomery MR, Harper SJ, Bates DO. Alternative splicing in angiogenesis: the vascular endothelial growth factor paradigm. Cancer Lett. 2007;249:133–42.

    Article  CAS  Google Scholar 

  38. Prinos P, Garneau D, Lucier JF, Gendron D, Couture S, Boivin M, et al. Alternative splicing of SYK regulates mitosis and cell survival. Nat Struct Mol Biol. 2011;18:673–9.

    Article  CAS  Google Scholar 

  39. Varela I, Tarpey P, Raine K, Huang D, Ong CK, Stephens P, et al. Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature. 2011;469:539–42.

    Article  CAS  Google Scholar 

  40. Gao W, Li W, Xiao T, Liu XS, Kaelin WG Jr. Inactivation of the PBRM1 tumor suppressor gene amplifies the HIF-response in VHL-/- clear cell renal carcinoma. PNAS. 2017;114:1027–32.

    Article  CAS  Google Scholar 

  41. Hogner A, Krause H, Jandrig B, Kasim M, Fuller TF, Schostak M, et al. PBRM1 and VHL expression correlate in human clear cell renal cell carcinoma with differential association with patient’s overall survival. Urol Oncol. 2018;36:94e1–e14.

    Article  Google Scholar 

  42. Kim JY, Lee SH, Moon KC, Kwak C, Kim HH, Keam B, et al. The impact of PBRM1 expression as a prognostic and predictive marker in metastatic renal cell carcinoma. J Urol. 2015;194:1112–9.

    Article  CAS  Google Scholar 

  43. Stros M, Launholt D, Grasser KD. The HMG-box: a versatile protein domain occurring in a wide variety of DNA-binding proteins. Cell Mol Life Sci. 2007;64:2590–606.

    Article  CAS  Google Scholar 

  44. Popp MW, Maquat LE. Organizing principles of mammalian nonsense-mediated mRNA decay. Annu Rev Genet. 2013;47:139–65.

    Article  CAS  Google Scholar 

  45. Chang YF, Imam JS, Wilkinson MF. The nonsense-mediated decay RNA surveillance pathway. Annu Rev Biochem. 2007;76:51–74.

    Article  CAS  Google Scholar 

  46. Lu JW, Plank TD, Su F, Shi XJ, Liu C, Ji Y, et al. The nonsense-mediated RNA decay pathway is disrupted in inflammatory myofibroblastic tumors. J Clin Invest. 2016;126:3058–62.

    Article  Google Scholar 

  47. Lindeboom RG, Supek F, Lehner B. The rules and impact of nonsense-mediated mRNA decay in human cancers. Nat Genet. 2016;48:1112–8.

    Article  CAS  Google Scholar 

  48. Shum EY, Jones SH, Shao A, Dumdie J, Krause MD, Chan WK, et al. The antagonistic gene paralogs Upf3a and Upf3b govern nonsense-mediated RNA decay. Cell. 2016;165:382–95.

    Article  CAS  Google Scholar 

  49. Ge Y, Porse BT. The functional consequences of intron retention: Alternative splicing coupled to NMD as a regulator of gene expression. Bioessays. 2014;36:236–43.

    Article  CAS  Google Scholar 

  50. Yan Q, Weyn-Vanhentenryck SM, Wu J, Sloan SA, Zhang Y, Chen K, et al. Systematic discovery of regulated and conserved alternative exons in the mammalian brain reveals NMD modulating chromatin regulators. PNAS. 2015;112:3445–50.

    Article  CAS  Google Scholar 

  51. Green RE, Lewis BP, Hillman RT, Blanchette M, Lareau LF, Garnett AT, et al. Widespread predicted nonsense-mediated mRNA decay of alternatively-spliced transcripts of human normal and disease genes. Bioinforma. 2003;19:i118–21.

    Article  Google Scholar 

  52. Nam RK, Zhang WW, Klotz LH, Trachtenberg J, Jewett MA, Sweet J, et al. Variants of the hK2 protein gene (KLK2) are associated with serum hK2 levels and predict the presence of prostate cancer at biopsy. Clin Cancer Res. 2006;12:6452–8.

    Article  CAS  Google Scholar 

  53. Vuong CK, Black DL, Zheng S. The neurogenetics of alternative splicing. Nat Rev Neurosci. 2016;17:265–81.

    Article  CAS  Google Scholar 

  54. Traunmuller L, Gomez AM, Nguyen TM, Scheiffele P. Control of neuronal synapse specification by a highly dedicated alternative splicing program. Science. 2016;352:982–6.

    Article  Google Scholar 

  55. Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O’Keeffe S, et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci. 2014;34:11929–47.

    Article  CAS  Google Scholar 

  56. Bates DO, Morris JC, Oltean S, Donaldson LF. Pharmacology of Modulators of Alternative Splicing. Pharmacol Rev. 2017;69:63–79.

    Article  CAS  Google Scholar 

  57. Han T, Goralski M, Gaskill N, Capota E, Kim J, Ting TC, et al. Anticancer sulfonamides target splicing by inducing RBM39 degradation via recruitment to DCAF15. Science. 2017;356:eaal3755.

    Article  Google Scholar 

  58. Arzalluz-Luque A, Conesa A. Single-cell RNAseq for the study of isoforms-how is that possible? Genome Biol. 2018;19:110.

    Article  Google Scholar 

  59. Tilgner H, Jahanbani F, Gupta I, Collier P, Wei E, Rasmussen M, et al. Microfluidic isoform sequencing shows widespread splicing coordination in the human transcriptome. Genome Res. 2018;28:231–42.

    Article  CAS  Google Scholar 

  60. Schafer S, Miao K, Benson CC, Heinig M, Cook SA, Hubner N. Alternative splicing signatures in RNA-seq data: percent spliced in (PSI). Curr Protoc Hum Genet. 2015;87:11.16.1–14.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Xudong Zhang of Genek Company for helpful advices of data processing. This work was funded by the National Natural Science Foundation of China (81702522, 81602236) and National Major Scientific and Technological Special Project for Significant New Drugs Development (2017ZX09304022).

Author information

Authors and Affiliations

  1. Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China

    Yangjun Zhang, Libin Yan, Jin Zeng, Hui Zhou, Haoran Liu, Gan Yu, Weimin Yao, Ke Chen, Zhangqun Ye & Hua Xu

  2. Institute of Urology of Hubei Province, Wuhan, 430030, China

    Yangjun Zhang, Libin Yan, Jin Zeng, Hui Zhou, Haoran Liu, Gan Yu, Weimin Yao, Ke Chen, Zhangqun Ye & Hua Xu

Authors
  1. Yangjun Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Libin Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jin Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hui Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haoran Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gan Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Weimin Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ke Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Zhangqun Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Hua Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hua Xu.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Yan, L., Zeng, J. et al. Pan-cancer analysis of clinical relevance of alternative splicing events in 31 human cancers. Oncogene 38, 6678–6695 (2019). https://doi.org/10.1038/s41388-019-0910-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41388-019-0910-7

This article is cited by

Search

Advanced search

Quick links