The overall goal of our research is to understand the modes of action (MoAs) of xenobiotics, such as environmental agents and drugs; and predict their human efficacy and/or toxicity. We develop and use novel phenotypic and molecular profiling methods to elucidate the MoAs of xenobiotics, and build computational models and tools that can predict the in vivo effects of these agents. Our current research is focused on three major areas, namely phenotypic profiling and digital pathology, toxicodynamics of xenobiotics, and pulmonary effects of xenobiotics (Fig. 1).
Figure 1. Our current research areas
Our members come from different scientific backgrounds, including chemistry, cell biology, immunology, computer science, and bioinformatics. We collaborate with different academic, clinical, industrial, and governmental research groups, including Institute of Molecular and Cell Biology (IMCB), Singapore Institute of Food and Biotechnology Innovation (SIFBI), Singapore General Hospital (SGH), National Cancer Center of Singapore (NCCS), Lee Kong Chain (LKC) Medicine, Harvard Beth Israel Deaconess Medical Center (BIDMC), and the United States Environmental Protection Agency (US EPA).
Imaging-based phenotypic profiling is a computational procedure to construct quantitative and compact representations of cellular or tissue phenotypes based on images obtained from high-throughput cellular imaging (Bougen-Zhukov et al., 2017). Our group has developed several phenotypic profiling methods, including the Drug-Profiling (“D-profiling”) algorithm for drug or chemical screening, and a user-friendly and efficient software tool called “cellXpress” (Laksameethanasan et al., 2013; Fig. 2). These methods and tools can handle terabytes of image data collected under large numbers of experimental conditions. Phenotypic profiles constructed using these methods have been used to classify the effects of small molecules and assess potentially harmful effects of chemicals and environmental agents (Miller et al., 2020; Hussain et al., 2020; Friedman et al., 2019; Lee et al., 2018; and Su et al., 2016).
Figure 2. CellXpress 2.0 can handle and quantify highly-multiplexed and large microscopy images obtained from human tissue microarrays (TMA).
Recent advances in multiplex immunohistochemistry/immunofluorescence (mIHC/IF) technologies have enabled simultaneous measurements of large numbers of markers on the same tissue sections, and more comprehensive views of the cellular compositions and immune responses at the tumor microenvironment (TME). The reproducibility and interpretation of the complex staining patterns and analysis results obtained from these technologies are vital to their general adoptions. Thus, we develop an online platform for managing, visualizing, and sharing large tissue images called the HistoPathology Analytics (HPA) Platform (Fig. 3). The platform can help researchers and clinicians to rapidly and accurately quantify the effects of cancer therapeutic agents, resulting in more systematic clinical decision-making processes (Leong et al., 2021). An online public portal for mIHC/IF images and results for immunooncology called ImmunoAtlas (https://ImmunoAtlas.org) has also been built based on the HPA Platform (Lee at al, 2021).
Figure 3. HistoPath Analytics (HPA) is a cloud-based digital histopathology platform developed by the Loo’s Lab at BII for organizing, sharing, visualizing, and analyzing large histological images.
Many xenobiotics have unknown and/or non-specific intracellular targets. To study the toxicodynamics of these chemicals, unbiased approaches that do not require prior information about the targets or mechanisms of the chemicals are required. Together with eight other research teams from A*STAR, we are developing the Toxicity Mode-of-Action Discovery (ToxMAD) Platform to elucidate the modes of action of xenobiotics in major target cell types using advanced phenotypic, signaling, and genomic profiling methods. Our focus is to study chemical analogs with related structures but differential cellular effects (Goh et al., 2021; Jaladanki et al., 2021), and develop fit-for-purpose assays that will be used by regulatory agencies and industrial research laboratories to assess chemical safety. We also participated in an international case study that demonstrates the utility of in vitro bioactivity as a lower bound estimate of in vivo adverse effect levels in risk-based prioritization (Friedman et al., 2019).
Human lungs are exposed to inhaled or blood-borne soluble xenobiotics that may originate from the environment, food, consumer products, and/or pharmaceuticals. We are broadly interested in the understanding the biological targets and pathways affected by these chemicals in the lung cells. We have developed a high-throughput and predictive in vitro pulmonary toxicity assay (Fig. 4; Lee et al., 2018). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). We also studied the effects of talc particles, a sclerosis agent commonly used in the management of malignant pleural effusions, in human lung cancer cells (Bougen-Zhukov, et al., 2019). We found a novel role of the PI3K pathway in talc-induced cell death and IL-6 secretion, which are key cellular events known to drive pleural fibrosis. This provides a better understanding of the mechanisms of talc sclerosis in the malignant pleural space.
Figure 4. Immunofluorescence microscopy images of human lung cells showing different phenotypic responses to non-toxic (blue) and toxic (red) chemicals.
Loo Lit Hsin is a Senior Principal Investigator at the Bioinformatics Institute (BII), A*STAR, Singapore. He is also an adjunct Assistant Professor at the Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore. He was the recipient of the Lush Prize – Science Award (2016), Award for Excellence in Postdoctoral Research (2010) and the Alfred Gilman Award (2009) by the University of Texas Southwestern (UTSW) Medical Center, and the Doctoral Award in Mathematical Sciences and Engineering (2005) by Drexel University. Dr. Loo was a postdoctoral fellow in the Bauer Center for Genomics Research at Harvard University (2005), and then in the Department of Pharmacology at the UTSW Medical Center, USA (2005-2010).
Dr. Loo’s background is in computational and systems pharmacology/toxicology. He is leading an interdisciplinary team of scientists developing in vitro and computational models for predicting the effects and/or targets of chemical compounds with diverse or unknown structures. Dr. Loo is also leading A*STAR’s participations in the International Workgroup on Accelerating the Pace of Chemical Risk Assessments (APRCA) and the associated Point-of-Departure case study. His research team has developed novel imaging-based phenotypic profiling methods and tools that led to the first high-throughput and predictive in vitro platform for nephrotoxicity prediction. They also develop and manage the HPA Platform and ImmunoAtlas portal to promotes open science and collaborations that can accelerate the adoptions of phenotypic profiling and/or multiplex IHC technologies in immuno-oncology.
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