Tests could soon identify patients who will respond well to the available treatment for chronic myeloid leukaemia and those who will be resistant to it—which could improve their chances of survival.
SINGAPORE, 1 June 2023 – Scientists at Duke-NUS Medical School, A*STAR’s Genome Institute of Singapore (GIS), Singapore General Hospital (SGH) and their colleagues in Singapore have used artificial intelligence (AI) to accelerate the discovery of critical biomarkers that can predict, at diagnosis, patients with chronic myeloid leukaemia (CML) who will not respond to conventional treatment. With this early prognosis, such patients could receive a life-saving bone marrow transplant during the early stages of the disease.
CML is a type of blood cancer that develops when a genetic mutation results in the permanent switching-on of an enzyme called a tyrosine kinase. The mutation forms in a blood stem cell in the bone marrow, and causes the stem cell to change into an aggressive leukaemic cell, which eventually takes over healthy blood production.
The conventional treatment for CML is a tyrosine kinase inhibitor (TKI), which switches off the tyrosine kinase that was turned on as a result of the genetic mutation. However, not everyone responds similarly to these drugs. At one end of the spectrum, some patients respond exceptionally well—to the point where their life expectancy would be considered normal. At the other end, some patients hardly respond at all, and their disease progresses to an aggressive state called blast crisis that is resistant to all forms of standard therapy. Because the only treatment for blast crisis is a bone marrow transplant, which would be most effective when performed during the early stages of the disease, finding out if a patient is resistant to TKI therapy sooner could mean the difference between survival or an early death.
“Our work indicates that it will be possible to detect patients destined to undergo blast crisis when they first see their haematologist,” said Associate Professor Ong Sin Tiong, from Duke-NUS’ Cancer & Stem Cell Biology (CSCB) Programme, the study’s senior author. “This may save lives since bone marrow transplants for these patients are most effective during the early stages of CML.”
"Based on these findings, we aim to develop simple clinical tests that can advise physicians on the optimal choice of treatment at the time of diagnosis," added Dr Vaidehi Krishnan, Principal Research Scientist with the CSCB Programme and first author of the study.
“Single cell analysis coupled with the power of AI have provided a crystal ball for predicting drug response in leukaemia,” said Dr Shyam Prabhakar, Associate Director, Spatial and Single Cell Systems and Senior Group Leader, Systems Biology and Data Analytics at A*STAR’s GIS.
Assoc Prof Ong, together with Dr Prabhakar and colleagues from SGH, National Cancer Centre Singapore (NCCS), the Cancer Science Institute of Singapore at the National University of Singapore, and the Advanced Cell Therapy and Research Institute, Singapore, generated a cell ‘atlas’ from bone marrow samples taken from six healthy people and 23 patients with CML prior to treatment. The atlas allowed them to see the different types of cells and their proportions in each sample. The researchers conducted RNA sequencing at the single-cell level and employed machine learning algorithms to determine which genes and molecular processes were turned on and off in each cell.
The work revealed eight statistically significant features in pre-treatment bone marrow cells that were either associated with sensitivity to tyrosine kinase inhibitor treatment or extreme resistance to it.
Specifically, patients were more likely to respond well to treatment if their bone marrow samples showed a stronger tendency towards premature red blood cells and a specific type of tumour-destroying ‘natural killer cell’. As the proportions of these cells in the bone marrow shifted, patient response to treatment changed.
The research could lead to drug targets for preventing or delaying treatment resistance and blast crisis in patients with chronic myeloid leukaemia.
“Treatment outcomes of chronic myeloid leukaemia have improved tremendously over the years and many options are now available for our patients. Knowing which treatment works best for our patients will further enhance these outcomes and we are excited by the possibility of being able to do so,” said Associate Professor Charles Chuah, from Duke-NUS’ CSCB Programme, who is also Senior Consultant at the Department of Haematology, SGH and NCCS.
The team next plans to use the findings to develop a predictive test of treatment resistance that hospitals can routinely use with their patients.
Reference: Vaidehi Krishnan, Florian Schmidt, Zahid Nawaz, Prasanna Nori Venkatesh, Kian Leong Lee, Xi Ren, Zhu En Chan, Mengge Yu, Meera Makheja, Nirmala Arul Rayan, Michelle Gek Liang Lim, Alice Man Sze Cheung, Sudipto Bari, Wee Joo Chng, Hein Than, John Ouyang, Owen Rackham, Tuan Zea Tan, William Ying Khee Hwang, Charles Chuah, Shyam Prabhakar, S. Tiong Ong; A Single-cell Atlas Identifies Pretreatment Features of Primary Imatinib Resistance in Chronic Myeloid Leukemia. Blood 2023; blood.2022017295. doi: https://doi.org/10.1182/blood.2022017295
About Duke-NUS Medical School
Duke-NUS is Singapore’s flagship graduate entry medical school, established in 2005 with a strategic, government-led partnership between two world-class institutions: Duke University School of Medicine and the National University of Singapore (NUS). Through an innovative curriculum, students at Duke-NUS are nurtured to become multi-faceted ‘Clinicians Plus’ poised to steer the healthcare and biomedical ecosystem in Singapore and beyond. A leader in ground-breaking research and translational innovation, Duke-NUS has gained international renown through its five signature research programmes and 10 centres. The enduring impact of its discoveries is amplified by its successful Academic Medicine partnership with Singapore Health Services (SingHealth), Singapore’s largest healthcare group. This strategic alliance has spawned 15 Academic Clinical Programmes, which harness multi-disciplinary research and education to transform medicine and improve lives.
For more information, please visit www.duke-nus.edu.sg
About Singapore General Hospital (SGH)
Singapore General Hospital, established in 1821, is the largest tertiary hospital in Singapore and ranked among the world’s best. It provides the most comprehensive patient-centred care with over 50 clinical specialties on its campus. As an Academic Medical Centre, it takes pride in training healthcare professionals and conducting cutting edge research to meet evolving needs of the nation as well as the region. Driven by a strong sense of purpose, SGH is committed to give of its best to heal and bring hope, as it has for over 200 years. For more information, please visit https://www.sgh.com.sg/
About the Agency for Science, Technology and Research (A*STAR)
A*STAR is Singapore's lead public sector R&D agency. Through open innovation, we collaborate with our partners in both the public and private sectors to benefit the economy and society. As a Science and Technology Organisation, A*STAR bridges the gap between academia and industry. Our research creates economic growth and jobs for Singapore, and enhances lives by improving societal outcomes in healthcare, urban living, and sustainability. A*STAR plays a key role in nurturing scientific talent and leaders for the wider research community and industry. A*STAR’s R&D activities span biomedical sciences to physical sciences and engineering, with research entities primarily located in Biopolis and Fusionopolis. For ongoing news, visit www.a-star.edu.sg.
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About A*STAR’s Genome Institute of Singapore (GIS)
The Genome Institute of Singapore (GIS) is an institute of the Agency for Science, Technology and Research (A*STAR). It has a global vision that seeks to use genomic sciences to achieve extraordinary improvements in human health and public prosperity. Established in 2000 as a centre for genomic discovery, the GIS pursues the integration of technology, genetics and biology towards academic, economic and societal impact, with a mission to “read, reveal and write DNA for a better Singapore and world”.
Key research areas at the GIS include Precision Medicine & Population Genomics, Genome Informatics, Spatial & Single Cell Systems, Epigenetic & Epitranscriptomic Regulation, Genome Architecture & Design, and Sequencing Platforms. The genomics infrastructure at the GIS is also utilised to train new scientific talent, to function as a bridge for academic and industrial research, and to explore scientific questions of high impact. For more information about GIS, please visit www.a-star.edu.sg/gis.
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