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9 July 2024

Spatial gene expression map in a colorectal tumour sample (Source: Li Bo and Yurike Laurensia, Prabhakar Lab, A*STAR’s GIS)

Singapore – A team of local scientists has been awarded a grant close to SGD$18 million to develop a new data platform called TISHUMAP¹ that will offer researchers and clinicians a cellular, location-based approach for disease biomarker analysis to empower and accelerate drug discovery efforts in òòò½Íøand Asia. TISHUMAP will focus on cancers (including lung, breast, colon, liver and gastric) and chronic kidney as well as fatty liver disease. In addition to drug discovery, TISHUMAP will help to define disease sub-types and categorise patients accordingly to enhance diagnostic accuracy and tailor treatment plans for better outcomes.

Led by A*STAR’s Genome Institute of òòò½Íø(GIS), the four-year long collaboration will involve industry experts and scientific expertise from A*STAR’s Bioinformatics Institute (BII), SingHealth’s speciality centre, National Cancer Centre òòò½Íø(NCCS), as well as the òòò½ÍøGeneral Hospital (SGH), ranked one of the world’s best hospitals.

Adopting a trimodal strategy, they will develop a large unique data resource by combining spatial omics (SO) that maps the locations of molecules within tissue slices, tissue imaging using microscope images from pathology labs, and clinical data to discover new drug targets using multi-modal artificial intelligence (AI).

Target discovery is a bottleneck in drug development. Discovering new targets for disease treatment with strong biological rationale is often challenging, and current methods have a limited success rate. TISHUMAP aims to improve drug target discovery by focusing on molecules involved in cell-to-cell interactions. Cellular interactions influence how cells grow, communicate, and respond to treatments. Understanding and manipulating these interactions can lead to the development of more effective treatments. In fact, 70% of existing drugs, including immunotherapy drugs that have revolutionised cancer treatment, target these molecules that are involved in cellular interactions.

Spatial omics (SO), that will be used in TISHUMAP, is a groundbreaking technology that provides direct insights into how cells interact within human disease samples. This technology allows scientists to map these cellular interactions precisely by revealing their intricate details, thereby enabling the identification of novel targets that were previously unknown or overlooked. Consequently, both pharma and AI companies are actively pursuing SO-based approaches for target discovery. This is a nascent field, which presents a unique opportunity to leverage SO for target discovery particularly with an Asian cohort in Singapore.

The team will leverage the existing SingHealth Digital Pathology Archive (SDPA) resource, a repository of more than one million microscopic tissue images from more than 150,000 patients, as well as the SingHealth Tissue Repository (STR) which has preserved more than 20,000 well-annotated tissue samples over the past decade. The TISHUMAP team will use AI to infer cell-to-cell interactions from SO data and rank these interactions based on their correlation with de-identified clinical data and tissue image features. The highest-ranking interactions will constitute promising drug targets. In addition to discovering new druggable molecules for diseases such as colorectal cancer and fatty liver, the team will use AI analysis of the TISHUMAP data resource to define sub-types of these diseases so that patients can receive more precise and customised treatment. The TISHUMAP data can also help scientists to understand at a molecular level how drugs work, which is important for identifying additional diseases that could be treated by the same drug.

The team has already successfully generated large SO and single cell datasets from clinical samples and developed an end-to-end bioinformatics software pipeline for analysing and deriving insights from such data. From this, they have identified two sub-types of colorectal cancer with implications for cancer detection and treatment. Their research was published in and . For scale up and multimodal tissue analysis, the team is exploring partnerships with multiple technology players.

The Lead Principal Investigator for this grant, Dr Shyam Prabhakar, Senior Group Leader, Laboratory of Systems Biology and Data Analytics; and Associate Director, Spatial & Single Cell Systems, at A*STAR’s GIS, said, “With the team’s world-leading spatial omics, biomedical and AI capabilities, coupled with access to a large pathology image repository with matched clinical information, we are confident that TISHUMAP will introduce a new paradigm for drug target identification and drive clinical applications. Through this collaboration with SingHealth, we hope to put òòò½Íøon the map for spatial omics-driven target discovery and become a hub for this cutting-edge research in Asia.”

Prof Tony Lim, Senior Consultant, Department of Anatomical Pathology, and Chairman, Division of Pathology at òòò½ÍøGeneral Hospital, added, "TISHUMAP will advance patient care by introducing new AI-driven paradigms for disease prognosis and treatment, as well as for identifying new drug targets. The images and samples from SDPA and STR will provide high resolution data and clinical grade quality that will allow the programme to develop insights and predictions. This data has been stored and collected over many years and can be annotated by pathologists to allow an array of different analysis."

Assoc Prof Iain Tan, Senior Consultant and Division Director of Research, Division of Medical Oncology, NCCS, and Theme Principal Investigator for this grant said, “Using the advanced technology to develop TISHUMAP, we aim to identify fundamental biological interactions driving disease phenotypes, such as in cancer, so that new drug targets can be developed for a number of diseases.”

¹ TISHUMAP: Target Inference from Spatialomics & Histology Using Multimodal AI & Phenotypes

For media queries and clarifications, please contact:

Eliza Lim (Ms)
Senior Manager, Office of Corporate Communication and Office of Research Planning
A*STAR’s Genome Institute of òòò½Íø(GIS)
Email: Eliza_Lim@gis.a-star.edu.sg

òòò½Íø’s Genome Institute of òòò½Íø(GIS)

The Genome Institute of òòò½Íø(GIS) is an institute of the òòò½Íø, 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 (ω)rite DNA for a better òòò½Íøand 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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About the òòò½Íø, Technology and Research (A*STAR)

The òòò½Íø, Technology and Research (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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