Functional Decoding of Non-Coding Transcriptomes in Tumor Progression and Metabolic Alteration

In recent years, deep sequencing technologies have unraveled the non-coding constituents of the transcriptome, most notably circular RNA (circRNAs) and long non-coding RNAs (lncRNAs). Despite the lack of protein-coding potential, these once uncharted parts have emerged as key determinant in gene regulation, acting as critical switches that fine-tune transcriptional and signaling output. Importantly, based on the unique expression patterns of these non-coding RNAs (ncRNAs) in different types of cancers, they may presumably be exploited as new tumor markers and/or treatment targets. However, since ncRNA research is still in its infancy, only a limited number of cancer-related ncRNAs has been entirely studied. With our extensive in-house tumor transcriptome database as the basis, this proposal therefore aims to employ a systems approach to demarcate circRNA- and lncRNA-mRNA gene networks and further provide an thorough understanding of their molecular actions, particularly in the context of tumor metabolism. In the first aim, via integrating our in-house oral cancer RNA sequencing datasets with public data, we will conduct a circRNA/lncRNA expression analysis to comparatively profile distinctions between tumor and matched normal tissues. We will then identify and verify ncRNA signatures with clinical relevance. Next, we will undertake an integrated computational approach to map functional networks of these non-coding RNAs. Based on molecular co-expression and interactome, the ncRNA-centric regulatory network will be constructed in a comprehensive manner. In the second part, a series of cell biology and functional assays will be executed to lend further support to the above in silico predictions, and to explore mechanistically the contribution of circRNA/lncRNA candidates to oral cancer malignant progression and metabolic alteration. As proof of principle, we present in this proposal tumor-associated circRNA/lncRNA candidates and further provide preliminary findings for their functional connection to tumorigenesis. Taken together, this integrated research approach is expected to provide new insights to the biology of the non-coding transcriptome and also its potential as target for translational medicine and therapeutic interventions of cancer. More importantly, the integrative design of our proposal can be extended to functional characterization of circRNAs or lncRNAs in other physiological or disease contexts.

Project ID:PC10901-0296
External Project ID:MOST107-2320-B182-042-MY3