New software unveils relationships between RNA modifications and cancers

 

NUS scientists develop a new computational tool

Credit: iStock.com / Christoph Burgstedt

A team of researchers from the Cancer Science Institute of Singapore (CSI Singapore) at the National University of Singapore has developed a software that can reveal the relationships between RNA modifications and the development of diseases and survival outcomes.

Professor Daniel Tenen and Dr Henry Yang developed ModTect, a new computational software that identifies novel RNA modifications using pre-existing sequencing data from clinical cohort studies. It has revealed associations between certain types of RNA modifications and different survival outcomes in 33 different types of cancer.

“This work is one of the few studies demonstrating the association of mRNA modification with cancer development. We show that the epitranscriptome was dysregulated in patients across multiple cancer types and was additionally associated with cancer progression and survival outcomes,” explained Yang, a research associate professor from CSI Singapore.

Epitranscriptomics is the study of how small chemical modifications to RNA can alter its function and stability. Previous studies have suggested a link between certain RNA modifications and the development of diseases such as Alzheimer’s disease and cancer.

“In the past decade, the ability to sequence the human genome has transformed the study of normal processes and diseases such as cancer. We anticipate that studies like this one will have a major impact on the characterisation of disease and lead to novel therapeutic approaches,” commented Tenen, a senior principal investigator from CSI Singapore. He added that studies like theirs will lead to the complete sequencing of RNA and detections of modifications in RNA.

The team’s breakthrough was published in Science Advances on 4 August 2021.
 

What are RNA modifications?

Unlike the double-stranded DNA, RNAs are single-stranded molecules that regulate protein expression and cell signalling. Just like how some reference books cannot be borrowed from the library, messenger RNA (mRNA) functions like a photocopier to bring necessary information out of the library. The mRNA copies genetic instructions from the DNA in the cell nucleus and carries it to the ribosomes where proteins are synthesised. The information, made up of unique combinations of nucleotides, specify which amino acids are required to build a specific protein. Apart from mRNA, there are also other types of RNAs that can stop protein translation and gene expression to relieve the ribosomes when a protein is no longer needed.

Further modifications to the RNA may also occur, which is akin to highlighting specific sections of the photocopied text. Identifying these small chemical modifications and understanding how they alter the function of RNAs and their link to diseases have been challenging. This is largely because collecting and processing patient samples is labour and time-intensive, especially when done for large patient cohorts. Detecting RNA modifications is also technically tough as it requires treating a limited source of rare patient samples with an array of chemicals that are difficult to access.
 

Software makes epitranscriptomics easier

To overcome these limitations, the CSI Singapore team developed a software, called ModTect, that looks for ‘misincorporation’ signals to detect RNA modifications using available RNA sequences from other large clinical cohort studies. Misincorporation signals include mismatch signals, which arise when random nucleotides are incorporated during sequencing, and deletion signals, which occur when part of the nucleotide sequence is missing. Unlike other models, ModTect does not require training on a database of misincorporation signal profiles to identify or classify them and is even able to identify previously unknown types of mRNA modifications.

To test the software, the team applied it to RNA-sequencing datasets collected from more than 11,000 cancer patient samples. With robust statistical filtering, ModTect revealed RNA modification sites that were associated with cancer progression and survival outcomes in patients. This provides support for the potential use of RNA modifications as disease biomarkers for both diagnosis and prognosis.
 

Unravelling the mystery of elusive sequences differences

The study of epitranscriptomes is an emerging and rapidly developing field with around 170 documented RNA modifications. With ModTect, Yang and his team are now able to provide fresh insights into the relationships between diseases and RNA modifications, which could be incorporated into clinical assessment in the future.

The team is hopeful that their contribution can further help research that establishes any potential causal or mechanistic relationship between RNA modifications and diseases.
 

Adapted by Audrey Khoo from Newly developed software unveils relationships between RNA modifications and cancers

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