NUS develops new cancer detection tool using big data analytics

“This is a big step forward in personalizing cancer treatment and ensuring better patient outcomes,” said Professor Lim Chwee Teck, Mechanobiology Institute, NUS Biomedical Engineering.
By Dean Koh
12:32 AM

Credit: NUS

A research team led by Professor Lim Chwee Teck and Dr Lim Su Bin from the National University of Singapore (NUS)’s Department of Biomedical Engineering has discovered a new personalized tool to detect cancer, predict patient survivability and how well a cancer patient would respond to immunotherapy.

This tool is a specially-designed cancer 'scorecard' to be used with the standard blood test for cancer (also known as liquid biopsy). 

HOW IT WORKS

This 'scorecard', which the team termed as the Tumor Matrisome Index (TMI), is a panel of 29 selected genes produced in the extracellular matrix (ECM) of the human body. ECM is the space around cells and provides structural and biochemical support to surrounding cells, behaving like a scaffolding. In a series of studies, the NUS team found that these 29 genes had appeared repeatedly as a consistent factor in patients diagnosed with non-small-cell lung cancer (NSCLC) which accounts for approximately 85% of all lung cancers.

To develop and validate the TMI “scorecard”, Dr Lim used big data and predictive analysis of over 30,000 patient-derived biopsies. Using public datasets of healthy individuals and cancer patients, the team noticed that cancer patients had a higher set of TMI scores. Testing a person’s TMI signature can determine if someone has cancer or not.

The team also examined the 29-gene TMI in 11 major cancer types - lung, pancreas, prostate, kidney, stomach, colon, ovary, breast, liver, bladder and melanoma. They found that the TMI scores distinguish cancers from normal tissues, and that each cancer type has a specific TMI signature.

So far, the TMI signature can diagnose with certainty someone with lung cancer, but further validation is required for the other 10 cancer types. The team also showed that TMI scores could be used to predict how successful a patient might react to cancer treatments, such as immunotherapy.

As determining if a tumor is likely to recur is a challenge because it is often done through macroscopic imaging techniques which can be non-specific, the team found that a patient’s TMI scores could give a better gauge on his or her survivability. 

In their research with NSCLC, the team discovered that that high TMI scores were consistently associated with early recurrence of cancer and metastatic spread, leading to an increased risk of death. 

For cancers such as colon, liver, renal, and breast cancers, the higher the TMI scores, the higher the risk of cancer recurrence or metastasis, and hence, the lower the patient’s chances of survival. The reverse is true for gastric and ovarian cancers: the higher the TMI scores, the lower the risk of cancer recurrence or metastasis and the better the chances of survival but this requires more validation and study.

FUTURE PLANS

Prof Lim and his team plan to work with their clinical collaborators to conduct further clinical tests to validate the use of TMI on other cancer types. This will determine how accurate and specific TMI will be in the diagnosis and prognosis of patients via liquid biopsy or blood test.

ON THE RECORD

“TMI can be used together with liquid biopsy, which is less invasive and less painful for the patient compared to conventional tumor biopsies. As it only requires a blood test instead of day surgery, it can be done more frequently over the course of treatment, providing doctors with real-time information on how the patient is responding to treatment. Tissue biopsy is often done at the start and end of treatment, while liquid biopsies can be done frequently, allowing doctors to track more efficiently how well treatment is progressing. This is a big step forward in personalizing cancer treatment and ensuring better patient outcomes,” explained Prof Lim in a statement. 

More regional news

Above image: A screenshot of the COVID-19 assessment tool in Alcidion's Patientrack solution.

By

Above image: A screengrab of Mediplat's first call remote health consult service. Credit: MedPeer

By