Latest news with #TumourImmuneMicroenvironmentSpatial
New Paper
a day ago
- Health
- New Paper
Singapore AI system may help predict liver cancer recurrence
A scoring system powered by artificial intelligence (AI) that was developed by researchers here could help predict the recurrence of a common form of liver cancer. Developed by scientists from A*Star's Institute of Molecular and Cell Biology (IMCB) and Singapore General Hospital (SGH), the system can predict relapses of hepatocellular carcinoma (HCC). Affecting more than 20 out of every 100,000 people here annually, HCC is the fourth-most-common cancer among men in Singapore, as well as the third-most-common cause of cancer deaths among males here. The Tumour Immune Microenvironment Spatial (Times) score analyses the precise spatial distribution, or the exact location, of immune cells called natural killer (NK) cells and five specific genes within liver tumour tissues. NK cells are a type of white blood cell that destroys diseased cells, such as cancer cells, and a lower number of NK cells is an indicator of a higher risk of relapse. "Instead of just counting how many NK cells are present, we analyse exactly where they are positioned relative to the cancer cells," said Dr Joe Yeong, a principal investigator at both A*Star IMCB and SGH's anatomical pathology department. "By understanding how NK cells are distributed and how they interact with cancer cells - for example, whether they are close enough to attack the cancer effectively - we can predict the likelihood of cancer returning after surgery," said Dr Yeong, one of the study's authors. Identifying these spatial patterns allows Times to predict the risk of recurrence with about 82 per cent accuracy. Existing staging methods - frameworks that evaluate how advanced the cancer is, allowing doctors to recommend the most suitable treatments - vary in their accuracy. Dr Yeong - who is also director of immunopathology at the SingHealth Duke-NUS Pathology Academic Clinical Programme - noted that up to 70 per cent of liver cancer patients experience recurrence within five years. An accurate prediction method would allow doctors to more easily identify patients at greater risk of cancer recurrence, he said. "Times offers a significant advancement in predicting these outcomes, enabling clinicians to intervene at the earliest possible stage. This can significantly enhance patient care and improve survival outcomes." He noted that the precision medicine approach seeks to tailor treatments that meet patients' specific needs, based on factors such as genetics and lifestyle. Even though a large proportion of liver cancer patients experience relapses, it is not viable to offer all of them therapeutics as it would be very costly to them, Dr Yeong said. Getting an accurate prediction of their risks would help optimise the costs to patients, he added. AI was used to analyse vast amounts of data, with more than 100 trillion data points gathered from liver tumour samples, as well as create a scoring system tailored to Asian patients. It is also currently being used to refine the Times score for clinical use, Dr Yeong said. "By automating the analysis of patients' surgical tissue samples, AI ensures the process is efficient and consistent, paving the way for integration into routine clinical workflows, such as through a potential diagnostic test kit," he added. The study was the cover story for the April 15, 2025, issue of the peer-reviewed scientific journal Nature. Ms Denise Goh, the study's co-first author, said the Times scoring system "transforms routine tissue slides into powerful predictive tools". "By identifying patients at higher risk of relapse, we can proactively alter treatment strategies and monitoring, potentially saving more lives," said the senior research officer at A*Star IMCB. The researchers validated the accuracy of the Times system using samples from 231 patients across five hospitals in Singapore and China. The technology is now accessible through a free web portal for research use, with plans under way to integrate Times into routine clinical workflows. The team is planning further studies at SGH and the National Cancer Centre Singapore to validate the technology, scheduled to begin later in 2025. Discussions are ongoing with partners to develop Times into a clinically approved diagnostic test kit.
Straits Times
2 days ago
- Health
- Straits Times
AI system developed in Singapore could help predict liver cancer recurrence
Find out what's new on ST website and app. Dr Joe Yeong is a co-author of the study published in the peer-reviewed scientific journal Nature. SINGAPORE - A scoring system powered by artificial intelligence (AI) that was developed by researchers here could help predict the recurrence of a common form of liver cancer. Developed by scientists from A*Star's Institute of Molecular and Cell Biology (IMCB) and Singapore General Hospital (SGH), the system can predict relapses of hepatocellular carcinoma (HCC). Affecting more than 20 out of every 100,000 people here annually, HCC is the fourth-most-common cancer among men in Singapore, as well as the third-most-common cause of cancer deaths among males here. The Tumour Immune Microenvironment Spatial (Times) score analyses the precise spatial distribution, or the exact location, of immune cells called natural killer (NK) cells and five specific genes within liver tumour tissues. NK cells are a type of white blood cell that destroys diseased cells, such as cancer cells, and a lower number of NK cells is an indicator of a higher risk of relapse. 'Instead of just counting how many NK cells are present, we analyse exactly where they are positioned relative to the cancer cells,' said Dr Joe Yeong, a principal investigator at both A*Star IMCB and SGH's anatomical pathology department. 'By understanding how NK cells are distributed and how they interact with cancer cells – for example, whether they are close enough to attack the cancer effectively – we can predict the likelihood of cancer returning after surgery,' said Dr Yeong, one of the study's authors. Top stories Swipe. Select. Stay informed. 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Dr Yeong – who is also director of immunopathology at the SingHealth Duke-NUS Pathology Academic Clinical Programme – noted that up to 70 per cent of liver cancer patients experience recurrence within five years. An accurate prediction method would allow doctors to more easily identify patients at greater risk of cancer recurrence, he said. 'Times offers a significant advancement in predicting these outcomes, enabling clinicians to intervene at the earliest possible stage. This can significantly enhance patient care and improve survival outcomes.' He noted that the precision medicine approach seeks to tailor treatments that meet patients' specific needs, based on factors such as genetics and lifestyle. Even though a large proportion of liver cancer patients experience relapses, it is not viable to offer all of them therapeutics as it would be very costly to them, Dr Yeong said. Getting an accurate prediction of their risks would help optimise the costs to patients, he added. AI was used to analyse vast amounts of data, with more than 100 trillion data points gathered from liver tumour samples, as well as create a scoring system tailored to Asian patients. It is also currently being used to refine the Times score for clinical use, Dr Yeong said. 'By automating the analysis of patients' surgical tissue samples, AI ensures the process is efficient and consistent, paving the way for integration into routine clinical workflows, such as through a potential diagnostic test kit,' he added. The study was the cover story for the April 15, 2025, issue of the peer-reviewed scientific journal Nature. Ms Denise Goh, the study's co-first author, said the Times scoring system 'transforms routine tissue slides into powerful predictive tools'. 'By identifying patients at higher risk of relapse, we can proactively alter treatment strategies and monitoring, potentially saving more lives,' said the senior research officer at A*Star IMCB. The researchers validated the accuracy of the Times system using samples from 231 patients across five hospitals in Singapore and China. The technology is now accessible through a free web portal for research use, with plans under way to integrate Times into routine clinical workflows. The team is planning further studies at SGH and the National Cancer Centre Singapore to validate the technology, scheduled to begin later in 2025. Discussions are ongoing with partners to develop Times into a clinically approved diagnostic test kit.
