Human cancers harbor complex genomic alterations. Understanding the functional consequences of these alterations is key to developing personalized therapeutics for patients. However, tumors are composed of not only cancer cells but also various infiltrating cell types, and these intercellular interactions dictate numerous facets of tumor biology. Thus, functional cancer genomics necessitates the study of cancer in vivo, within the native micro-environmental context.

Our lab focuses on cancer immunology, genetics and systems biology. We develop and utilize a wide variety of modern tools, including in vivo gene editing and tumor modeling, genome-wide and focused CRISPR screens, immune engineering, high-density and high-dimensional genetic manipulations, and systems-level profiling. Using these tools, we seek to interrogate the genetic, epigenetic and immunological bases of cancer progression, metastasis, immunity and treatment.

Currently, our work follows along 5 threads:

1. Precision modeling of cancer with CRISPR mediated in vivo gene editing

The major challenge with studying cancer-associated mutations in animal models is the conflict between the complexity of the cancer genome and the technical challenges in generating multiple targeted alleles. We previously developed CRISPR-based genetically engineered mouse models (C-GEMMs) of several cancer types. By co-targeting combinations of key tumor suppressor genes and oncogenes, we successfully induced multi-hit liver cancer (Xue*, Chen*, Yin* et al. 2014) and lung adenocarcinoma (Platt*, Chen* et al. 2014). These studies have opened new avenues for limitless direct in vivo modeling of mutations found in cancer, thus facilitating the rapid development of novel disease models, investigations into combinatorial mutation phenotypes, elucidation of genotype-specific drug responses, and systematic screening of novel cancer genes.

2. High-throughput in vivo genetic screens to map a functional cancer genome atlas

Cancer genomics initiatives have now charted the genomic landscapes of human cancers. While some of these mutations were found in classical oncogenes and tumor suppressors, many others have not been previously implicated in cancer. Our lab developed an approach for high-throughput in vivo mapping of functional variants in autochthonous mouse models of cancer. These studies revealed the functional consequences of thousands of variants to drive brain (Chow*, Guzman*, Wang*, Schmidt* et al. 2017) and liver (Wang*, Chow* et al. 2018) tumorigenesis in immunocompetent mice. Our approach provides a powerful platform for functional interrogation of cancer variants within the native tissue site in vivo (Chow and Chen 2018).

3. Genome-wide in vivo screens of cancer drivers and therapeutic targets

The most devastating hallmark of cancer is its potential to become invasive and metastasize to distant organs. Understanding how cancer cells become metastatic, how they disseminate through circulation, and how the circulating tumor cells seed new micro-tumors is key to treating the disease. Our goal is to systematically identify and characterize causal genetic and epigenetic alterations driving metastasis. Towards this end, we have performed systematic genetic screens in mouse models to identify regulators of metastasis (Chen*, Sanjana* et al. 2015). Recently, we have also performed combinatorial genetic screens to investigate genetic interactions driving metastasis (Chow*, Wang*, Ye* et al., accepted).

4. Development of novel biotechnologies

Our lab is also interested in developing novel technologies to enable new pathways for scientific discovery, including new approaches for manipulating the genome, transcriptome, proteome, and more complex cellular behaviors in vivo. For instance, we developed a simple strategy for performing sequential mutagenesis of multiple genes, called Cpf1-Flip (Chow et al. 2018). We have also crafted a highly efficient approach for the generation of modular human CAR-T cells (Dai*, Park* et al., 2019). Furthermore, we pioneered the use of Cpf1/Cas12a for combinatorial in vivo genetic screens (Chow*, Wang*, Ye* et al., accepted).

5. Cancer immunity

Cancer immunotherapy, which harnesses the body’s own immune system to combat cancer, has been strikingly effective in inducing durable responses across multiple cancer types. However, only a subset of patients respond to current immunotherapy, such as checkpoint blockade or adoptive T cell transfer. This variability is due in large part to the complexity of cancer immunity. Tumor cells are constantly interacting with numerous immune cells, forming highly dynamic signaling networks between cancer and the immune system. It is likely that we have only seen the tip of the immunotherapeutic iceberg, and a rich repertoire of immunomodulatory factors still remains to be discovered. Our lab is interested in utilizing a combinatorial approach including gene editing and animal models to better understand tumor immunity, paving the road for new and improved immunotherapy modalities.

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