15

Yvonne TAY

In recent years, next-generation sequencing has revealed the existence of thousands of non-coding RNAs, which comprise the majority of the human transcriptome. Our work focuses on understanding the role that these non-coding RNAs play in cancer development, and exploring their potential utility as diagnostic biomarkers and targeted therapeutics for precision medicine.

csitmsy[at]nus.edu.sg

Principal Investigator, Cancer Science Institute of Singapore, NUS
Associate Professor, Department of Biochemistry, NUS.

2022, 2021 Faculty of Dentistry Excellence in Teaching Award
2021 Yong Loo Lin School of Medicine Teaching Excellence Award
2021 Yong Loo Lin School of Medicine Young Researcher of the Year Award
2015 Young Scientist Award
2015 Singapore National Research Foundation Fellowship
2014 NUS President’s Assistant Professorship
2011-2014 Special Fellowship, Leukemia & Lymphoma Society
2009 Philip Yeo Prize for Outstanding Achievement in Research, A*STAR Biomedical Research Council, Singapore
2004-2008 A*STAR Graduate Scholarship, Agency for Science, Technology and Research, Singapore

The dysregulated expression of critical genes is one of the driving forces that transforms a normal cell into a cancer cell. In addition to genomic alterations, aberrant changes in post-transcriptional regulation by factors including non-coding RNAs and RNA binding proteins represent another mechanism to modify gene function and thus contribute to tumorigenesis.

The advent of next-generation sequencing technologies has led to the identification of thousands of non-coding RNAs, only a handful of which have been functionally characterized. In addition to studying non-coding RNAs in their own right, our group is also interested in studying the non-coding regions of protein-coding mRNAs (untranslated regions, UTRs). As many mRNA populations comprise transcripts with different UTRs, and these UTRs control key processes such as stability, localization and transport, a better understanding of their function may lead to insights into the regulation of key cancer genes.

Our work has three main focus areas: (1) Deconvoluting RNA:RNA networks in cancer and understanding how they contribute to carcinogenesis; (2) Understanding the interplay between RNA:RNA interactions and RNA:protein interactions and (3) Examining potential crosstalk between these post-transcriptional networks and RNA processing pathways such as splicing and editing. Our long-term goal is to translate our basic research discoveries into the clinic, we anticipate that our work will open new avenues for the development of novel RNA-based anti-cancer diagnostics and therapeutics.

yt-research-1

Fig 1. Different species of RNAs, including messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) can co-regulate each other in competing endogenous RNA networks by sequestering or ‘sponging’ shared microRNAs. The dysregulation of any single RNA can lead to a ripple effect across the network and thus modulate carcinogenesis.

yt-research-2-768x789

Fig 2. The butterfly effect of RNA alterations on transcriptomic equilibrium. The different modifications affecting either target RNAs or miRNAs and/or both, such as genetic modification (A), alternative polyadenylation (APA) (B), RNA methylation (C), RNA editing (D), and isomiR production (E). Ovals represent the miRNA response elements (MREs); double-headed arrows represent bi-directional regulation in which the thickness indicates the strength of the regulation; single-headed arrows indicate increase (pointed up) or decrease (pointed down) in RNA expression; red stars indicate non-specific nucleotide alteration; grey crosses indicate loss of interaction; red lightning bolts represent mutation events; yellow circles with an A represent methylation marks; grey circle with an I represents A-to-I RNA editing.

1. Chan JJ*, Zhang B*, Chew XH, Salhi A, Kwok ZH, Lim CY, Desi N, Subramaniam N, Siemens A, Kinanti T, Ong S, Sanchez-Mejias A, Ly PT, An O, Sundar R, Fan X, Wang S, Siew BE, Lee KC, Chong CS, Lieske B, Cheong WK, Goh Y, Fam WN, Ooi MG, Koh BTH, Iyer SG, Ling WH, Chen J, Yoong BK, Chanwat R, Bonney GK, Goh BKP, Zhai W, Fullwood MJ, Wang W, Tan KK, Chng WJ, Dan YY, Pitt JJ, Roca X, Guccione E, Vardy LA, Chen L, Gao X, Chow PKH, Yang H, Tay Y. (2022) Pan-cancer pervasive upregulation of 3’UTR splicing drives tumorigenesis. Nat Cell Biol. 24(6), 928-939.

2. Desi N*, Tong QY*, Teh V, Chan JJ, Zhang B, Tabatabaeian H, Tan HQ, Kapeli K, Jin W, Lim CY, Kwok ZH, Tan HT, Wang S, Siew BE, Lee KC, Chong CS, Tan KK, Yang H, Kappei D, Yeo GW, Chung MCM, Tay Y. (2022) Global analysis of RNA-binding proteins identifies a positive feedback loop between LARP1 and MYC that promotes tumorigenesis. Cell Mol Life Sci. 79(3), 147.

3. Kwon J, Liu YV, Gao C, Bassal MA, Jones AI, Yang J, Chen Z, Li Y, Yang H, Chen L, Di Ruscio A, Tay Y*, Chai L*, Tenen DGT*. (2021) Pseudogene-mediated DNA demethylation leads to oncogene activation. Sci Adv. 7(40), eabg1695.

4. Chan JJ, Tabatabaeian H, Tay Y. (2022) 3’UTR heterogeneity and cancer progression. Trends Cell Biol. S0962-8924(22)00232-X.  

5. Kwok ZH, Zhang B, Chew XH, Chan JJ, Teh V, Yang H, Kappei D, Tay Y. (2021) Systematic analysis of intronic microRNAs reveals cooperativity within the multi-component FTX locus to promote colon cancer development. Cancer Res 81(5), 1308-1320.

6. Chan JJ, Kwok ZH, Chew XH, Zhang B, Liu C, Soong TW, Yang H, Tay Y. (2018) A FTH1 gene:pseudogene:microRNA network regulates tumorigenesis in prostate cancer. Nucleic Acids Research. 46(4), 1998-2011.

7. Tay Y, Rinn J, Pandolfi PP. (2014) The multilayered complexity of ceRNA crosstalk and competition. Nature. 505, 344-352.

8. Tay Y, Kats L, Salmena L, Weiss D, Tan SM, Ala U, Karreth F, Poliseno L, Provero P, Di Cunto F, Lieberman J, Rigoutsos I, Pandolfi PP. (2011) Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs. Cell 147, 344–357.

9. Tay Y, Zhang J, Thomson AM, Lim B, Rigoutsos I. (2008) MicroRNAs to Nanog, Oct4 and Sox2 coding regions modulate embryonic stem cell differentiation. Nature 455(7216),1124-1128. 

10. Miranda KC*, Huynh T*, Tay Y*, Ang YS*, Tam WL, Thomson AM, Lim B, Rigoutsos I. (2006) A pattern-based method for the identification of microRNA binding sites and their corresponding heteroduplexes. Cell 126(6), 1203-1217. 

Lab Members