We mix 10kg of passion, then add 5000 spatulas full of hard work. We heat our portion with a warmth of confidence and run the mixture in a perseverance gel. We stain for patience and resilience in a buffer full of success! We see the bands and marks of million of accomplishments shining strong under the light of learning. We transfer our knowledge portion into marks of aspiration of excellence which show today and tomorrow all the way.
Tumor is an evolving ecosystem. The dynamics interplay between heterogeneous tumor cells and their tissue microenvironment dictates how tumor initiates, develop, and metastasize. The central theme of our research program in our laboratory is to explore the co-evolution between tumor cells and the tumor microenvironment (TME) during the development of therapeutic resistance and metastatic relapse. An in-depth mechanistic understanding of the multifactorial co-evolution with TME is essential for developing precision anti-cancer treatments, such as anti-cancer targeted therapy and immunotherapy.
As a translational cancer biology laboratory, we integrate multidisciplinary, innovative approaches, including cancer biology, neuroscience, bioengineering, and computer sciences, to investigate the dynamic interactions between the tumor and its tumor microenvironment. We use genetic animal tumor models to model the clinical scenarios, examine molecular underpinnings, and conduct rationally designed pre-clinical tests of novel combinatorial anti-cancer therapies to overcome drug resistance and prevent/treat tumor metastasis.
Research Theme #1 – Define and track the evolving tumor heterogeneity using single cell analysis
Tumor is an extremely heterogeneous entity. Tumor and its microenvironment are an intricate co-evolving ecosystem. The constant interplay between the tumor and the tumor microenvironment (TME) dictates tumor initiation, progression, and metastasis. The TME, including the primary tumor milieu and the secondary metastatic niche, is a highly dynamic, but spatially restrained co-opted by tumor cells for immune evasion and metastatic outgrowth. A mechanistic understanding of the multifactorial TME is essential for the development of precision anti-cancer treatments. Our lab focuses on resolving the spatial and cellular heterogeneity of the TME and how the interplay between primary tumor cells and TME provokes drug resistance and metastasis.
How do we delineate the evolving tumor heterogeneity?
Developing acquired resistance to targeted cancer therapy is one of the most significant clinical challenges. Acquiringresistance under drug selection pressure is a result of evolutionary adaptation to a complex and dynamic tumor microenvironment (TME). We use transgenic mouse models to model the trajectory of tumor evolution. We investigate how the tumor responds to selection pressure, e.g. chemotherapy and targeted therapy, and how those “pillars” of modern cancer therapies reshape the tumor immune landscape and influence cancer immunotherapy and cancer metastasis. By employing the single-cell RNA-sequencing, namely CITE-seq and spectral flow cytometry approach, we dissect the enormous heterogeneity of the tumor microenvironment. Through the high throughput single-cell analysis, we develop testable hypotheses on tumor immunity and develop novel strategies to target the bewildered tumor microenvironment. Read here: Nat Commun. 2019 Aug 23;10(1):3817. doi: 10.1038/s41467-019-11729-1. BioRxiv 671198 Read the news here.[Full text]. And our newest preprint here bioRxiv 2022.03.28.485781.
How can we track the pattern of evolving tumor heterogeneity?
The co-evolution between the tumor and its TME is not mediated by a handful of specific genetic mutations or epigenetic marks. Rather, such co-evolution is a highly plastic and continuous transcriptome trajectory. The crosstalk between transcriptome regulators and spatially dependent extracellular signaling cues (cells and/or factors) collectively regulate the co-evolution between the tumor and the TME. Defining the continuous transcriptome trajectory – the past, current, and future – of tumor co-evolution will lead to novel anti-cancer therapies that deliver a more sustained control of tumor progression and metastasis.
Dedicated regulatory cell signaling circuits control tumor cell heterogeneity and diverse responses to extracellular cues/stressors. The highly redundant nature of signaling circuits and the dynamic non-linear cross-talks in response to environmental cues (e.g. from the metastatic niche) pose major research challenges. We ask a fundamental question: If the circuit is a non-linear network, is there an identifiable trajectory that controls overall tumor immunity? A comprehensive system biology approach to map the signaling circuits’ evolving trajectory that regulates tumor-immune cell interaction is the only way to advance our understanding of brain metastatic immune evasion. To tackle this research challenge, we apply multiplexed genetic perturbation approach, e.g. Perturb-seq or CROP-seq, and a machine-learning system biology approach to investigate the signaling plasticity and redundancy during the tumor cell and TME immune cell interaction.
Research Theme #2 – How do tumor cells metastasize to the brain?
Tumor metastatic adaptation at the brain microenvironment (the niche)
We explore how tumor cells colonized at brain tissue microenvironment and epigenetically adapt to such drastically different tissue. We recently discovered an unexpected metabolic transcriptome shifting during early brain metastatic colonization, a process driven by epigenetic up-regulation of glutamate decarboxylase 1 (GAD1). Adaptive up-regulation of GAD1 in metastatic cells in the brain microenvironment facilities metastatic colonization. To exploit this brain metastasis-specific adaptation for treatment, we further showed that repurposing the FDA-approved anti-seizure therapy vigabatrin inhibits the GAD1-mediated GABA metabolic pathway, significantly decreasing brain metastases in vivo. This novel mechanistic insight provides a critical rationale for clinical treatment of brain metastases using vigabatrin (Schnepp et al. Cancer Res. 2017). We have also implemented a hybrid screening approach– combining RNA-profiling of temporal transcriptome changes during metastatic adaption, with a rapid forward genetic screen using a Drosophila tumor metastasis model – to unbiasedly identify functionally important mechanisms driving brain metastatic adaptation (Nat Commun. 2020 Jun 15;11(1):3017. doi: 10.1038/s41467-020-16832-2. BioRxiv 666750. [Full text].)
Mechanisms of primed brain metastatic niche in promoting brain metastasis progression
We employ brain tissue clearing and SMART3D imaging analysis approach to dissect the brain astrocyte, microglia, and blood vessel changes in response to brain metastatic colonization (
How do systemic factors regulate the pre-metastatic niche?
We have broad interests in anything related to the tumor microenvironment, particularly, the metastatic brain microenvironment, using functional genomics, genetic mouse model, and single cell sequencing approaches, Here are some questions we are asking:
1) How do systemic treatments/changes, e.g. aging, chemo treatment, and gut dysbiosis, profoundly modulate the body’s immune surveillance system and influence the metastatic niche?
2) What’s the role of the meningeal/lymphatic system in the immune regulation of metastasis?
3) How can we more effectively model the “aged” tissue microenvironment in vivo?
4) How can we exploit the spatial features of the tumor immune interface to specifically deliver drugs or imaging contrast agents?