Research Departments & Organizations
My group's current research focuses on cancer immunology, genetics and systems biology. We develop and utilize a wide variety of modern biology and engineering 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 to study the genetic, epigenetic, cellular and immunological bases of cancer oncogenesis, metastasis, immunity and treatment.
Extensive Research Description
Our research focuses on systems biology of cancer and other fundamental problems of medicine. Currently, the lab seeks to understand the genetic and immunological bases of cancer biology and treatment, using an open set of modern toolbox including large-scale computation, high-throughput screening, genomics, in vivo CRISPR/Cas9-mediated genome editing, bioengineering, live imaging, immune engineering and animal models. Some examples of projects are listed below; while lab members are also strongly encouraged to innovate new ideas with their own creativity.
1. High-through put in vivo genetic screen and mapping functional cancer genome atlases
Cancer genomics initiatives have charted the genomic landscapes of human cancers. While some mutations were found in classical oncogenes and tumor suppressors, many others have not been previously implicated in cancer. My group developed direct high-throughput in vivo mapping of functional variants in an autochthonous mouse model of cancer. Our screens and deep variant analysis revealed the functional consequence of multiple variants with various degree of competitive selection that drive tumorigenesis in immunocompetent mice. These studies provide a new powerful platform for functional interrogation of cancer genome variants in an autochthonous manner, and direct identification of novel functional drivers in vivo.
1.1 Chow RD*, Guzman CD*, Wang G*, Schmidt F*, Youngblood MW, Ye L, Errami Y, Dong MB, Martinez MA, Zhang S, Renauer P, Bilguvar K, Gunel M, Sharp PA, Zhang F, Platt RJ @, Chen S @. AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma. Nature Neuroscience, 20, 1329–1341 (2017) doi:10.1038/nn.4620) Aug 14. PMID: 28805815
1.2 Wang G*, Chow RD*, Ye L, Guzman CD, Dai X, Dong MB, Zhang F, Sharp PA, Platt RJ@, and Chen S@. Mapping a Functional Cancer Genome Atlas of Tumor Suppressors in Mouse Liver Using AAV-CRISPR Mediated Direct in vivo Screening. (2018) Science Advances. Feb 28;4(2):eaao5508. doi: 10.1126/sciadv.aao5508. PMID: 29503867
1.3 Chow RD and Chen S@. Cancer CRISPR screens in vivo. Trends In Cancer. 2018 May;4(5):349-358. doi: 10.1016/j.trecan.2018.03.002.. Review. PMID: 29709259 (Cover story)
1.4 Chow RD and Chen S@. Sno-derived RNAs are prevalent molecular markers of cancer immunity. Oncogene, 2018 DOI - 10.1038/s41388-018-0420-z
2. Precision modeling of cancer with CRISPR mediated in vivo gene editing
The major challenge of studying cancer mutations in animal models is the conflict between the complexity of the cancer genome and the technical demand in generating targeted alleles. We previously developed a CRISPR-based genetically engineered mouse model (CGEMM) of several cancer types. By co-targeting combinations of key tumor suppressor genes and oncogenes, we developed methods to induce liver cancer (Xue*, Chen*, Yin* et al. 2014) and lung adenocarcinoma (Platt*, Chen* et al. 2014). These studies and systems opened new paths for direct modeling of virtually any mutations and all possible combinations of oncogenes and tumor suppressor genes - facilitating the rapid development of novel disease models, testing combinations of mutations with strong or subtle phenotypes, genotype-specific drug response, and systematic screening of novel factors.
2.1 Xue W*, Chen S*, Yin H*, Tammela T, Papagiannakopoulos T, Joshi NS, Cai W, Yang G, Bronson R, Crowley DG, Zhang F, Anderson DG, Sharp PA, Jacks T. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature. 2014 Oct 16;514(7522):380-4. doi: 10.1038/nature13589. PMID: 25119044
2.2 Platt RJ*, Chen S*, Zhou Y, Yim MJ, Swiech L, Kempton HR, Dahlman JE, Parnas O, Eisenhaure TM, Jovanovic M, Graham DB, Jhunjhunwala S, Heidenreich M, Xavier RJ, Langer R, Anderson DG, Hacohen N, Regev A, Feng G, Sharp PA, Zhang F. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell. 2014 Oct 9;159(2):440-55. doi: 10.1016/j.cell.2014.09.014. PMID: 25263330; (Cover story)
3. Genome-wide in vivo screen of cancer drivers and therapeutic targets
The most devastating hallmark of the cancer cells is that they evolve to become invasive and metastatic. Understanding how cancer cells become metastatic, how they disseminate through circulation, and how the circulating tumor cells seed new micro-tumors is a key to treat the disease. The goal is to systematically identify and characterize causal genetic and epigenetic alterations in metastasis. Our approach is to perform systematic genetic screens in mouse models to identify metastasis regulators. We will design and construct CRISPR libraries generating loss-of-function or gain-of-function alterations in the genome or the epigenome. We will perform genome-scale and focused mutagenesis followed by high-throughput sequencing to identify novel genes of interest, validate by individual knockout/activation and rescue/reversal, then investigate the molecular function and cellular mechanism underlying their roles the metastatic processes. The phenotypic effects of the mutant in various steps of metastases will be tested: intravasation, survival during circulation, traveling through vasculature, extravasation, inducing angiogenesis as micrometastases, capillary co-option, or colonization growth.
3.1 Chen S*, Sanjana NE*, Zheng K, Shalem O, Lee K, Shi X, Scott DA, Song J, Pan JQ, Weissleder R, Lee H, Zhang F, Sharp PA. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell. 2015 Mar 12;160(6):1246-60. doi: 10.1016/j.cell.2015.02.038. PMID: 25748654; (* = co-first authors) (Selected as Best of Cell 2015)
4. Development of novel biotechnologies
The lab also exerts strong interests in development of novel technologies to enable new paths of discoveries, such as new ways to manipulate the genome, the transcriptome, the proteome, as well as control of cellular behaviors in vivo. Examples below demonstrated creative works by lab members. Students are welcomed as new innovators of the crew.
Ryan D. Chow, Guangchuan Wang, Adan Codina, Lupeng Ye, Sidi Chen @. Mapping in vivo genetic interactomics through Cpf1 crRNA array screening. BioRxiv (2017) doi: https://doi.org/10.1101/153486 (@ = corresponding author)
Ye L, Wang C, Hong L, Sun N, Chen D, Chen S, Han F. Programmable DNA repair with CRISPRa/i enhanced homology-directed repair efficiency with a single Cas9. Cell Discov. 2018 Jul 24;4:46. doi: 10.1038/s41421-018-0049-7. eCollection 2018. PubMed PMID: 30062046
Chow RD, Kim HR, Chen S. Programmable sequential mutagenesis by inducible Cpf1 crRNA array inversion. Nat Commun. 2018 May 15;9(1):1903. doi: 10.1038/s41467-018-04158-z. PubMed PMID: 29765043
Pyzocha NK, Chen S. Diverse Class 2 CRISPR-Cas Effector Proteins for Genome Engineering Applications. ACS Chem Biol. 2018 Feb 16;13(2):347-356. doi: 10.1021/acschembio.7b00800. Epub 2017 Dec 5. PubMed PMID: 29121460.
5. Cancer immunity
Each tumor contains not only cancer cells, but also various infiltrating cell types of the host, including tumor stromal cells and immune cells. Immunotherapy, which harnesses the body’s own immune system to combat the disease, has been strikingly effective in inducing durable responses across multiple cancer types. However, only a subset of the patients responds to immunotherapy such as checkpoint blockade or adoptive T cell transfer. This is because, at least in part, cancer immunity is a complex problem. Almost every tumor is interacting with a distinct set of immune cells, forming highly dynamic signaling network between cancer cells and immune cells. We have only seen the tip of the immunotherapeutic iceberg; 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 for improved immunotherapy.
Example on-going directions:
5.1 Tumor-intrinsic factors that modulate checkpoint blockade efficacy
5.2 Genetic regulation of T cells
5.3 Immune components and regulation in the microenvironment of brain tumors, such as GBM
5.3 Innate immune cells in oncology, such as macrophage and dendritic cells
5.5 Engineering of immune cells and the immunological machinery
5.6 Development of novel immunotherapies
We seek highly motivated students and postdoctoral fellows to work on exciting on-going directions especially cancer immunology and technology development. These multi-year projects are funded by NIH and other awards to support highly innovative scientific research with rigorous experimentation and analyses.
Students: Interested students may contact Dr. Chen via Yale email.
Postdocs: Postdoc candidates may apply by email (firstname.lastname@example.org).
Requirements: PhD in immunology, cancer immunology or equivalent.
Application shall include a statement of previous work with publication links, and future research interests.
Postgraduates: Postgrad candidates may apply by email (email@example.com).
Requirements: Bachelor degree in biology, bioengineering, biomedical science, chemistry, or similar.
For details please refer to Chen lab website. Yale University is an equal opportunity employer.
AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma.
Chow RD, Guzman CD, Wang G, Schmidt F, Youngblood MW, Ye L, Errami Y, Dong MB, Martinez MA, Zhang S, Renauer P, Bilguvar K, Gunel M, Sharp PA, Zhang F, Platt RJ, Chen S. AAV-mediated direct in vivo CRISPR screen identifies functional suppressors in glioblastoma. Nature Neuroscience 2017, 20:1329-1341. 2017
Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis.
Chen S, Sanjana NE, Zheng K, Shalem O, Lee K, Shi X, Scott DA, Song J, Pan JQ, Weissleder R, Lee H, Zhang F, Sharp PA. Genome-wide CRISPR screen in a mouse model of tumor growth and metastasis. Cell 2015, 160:1246-60. 2015
CRISPR-Cas9 knockin mice for genome editing and cancer modeling.
Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR, Dahlman JE, Parnas O, Eisenhaure TM, Jovanovic M, Graham DB, Jhunjhunwala S, Heidenreich M, Xavier RJ, Langer R, Anderson DG, Hacohen N, Regev A, Feng G, Sharp PA, Zhang F. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 2014, 159:440-55. 2014
CRISPR-mediated direct mutation of cancer genes in the mouse liver.
Xue W, Chen S, Yin H, Tammela T, Papagiannakopoulos T, Joshi NS, Cai W, Yang G, Bronson R, Crowley DG, Zhang F, Anderson DG, Sharp PA, Jacks T. CRISPR-mediated direct mutation of cancer genes in the mouse liver. Nature 2014, 514:380-4. 2014
Global microRNA depletion suppresses tumor angiogenesis.
Chen S, Xue Y, Wu X, Le C, Bhutkar A, Bell EL, Zhang F, Langer R, Sharp PA. Global microRNA depletion suppresses tumor angiogenesis. Genes & Development 2014, 28:1054-67. 2014
New genes as drivers of phenotypic evolution.
Chen S, Krinsky BH, Long M. New genes as drivers of phenotypic evolution. Nature Reviews. Genetics 2013, 14:645-60. 2013
Reshaping of global gene expression networks and sex-biased gene expression by integration of a young gene.
Chen S, Ni X, Krinsky BH, Zhang YE, Vibranovski MD, White KP, Long M. Reshaping of global gene expression networks and sex-biased gene expression by integration of a young gene. The EMBO Journal 2012, 31:2798-809. 2012
Frequent recent origination of brain genes shaped the evolution of foraging behavior in Drosophila.
Chen S, Spletter M, Ni X, White KP, Luo L, Long M. Frequent recent origination of brain genes shaped the evolution of foraging behavior in Drosophila. Cell Reports 2012, 1:118-32. 2012
New genes in Drosophila quickly become essential.
Chen S, Zhang YE, Long M. New genes in Drosophila quickly become essential. Science (New York, N.Y.) 2010, 330:1682-5. 2010
Diverse Class 2 CRISPR-Cas Effector Proteins for Genome Engineering Applications.
Pyzocha NK, Chen S. Diverse Class 2 CRISPR-Cas Effector Proteins for Genome Engineering Applications. ACS Chemical Biology 2018, 13:347-356. 2018
Mapping a functional cancer genome atlas of tumor suppressors in mouse liver using AAV-CRISPR-mediated direct in vivo screening.
Wang G, Chow RD, Ye L, Guzman CD, Dai X, Dong MB, Zhang F, Sharp PA, Platt RJ, Chen S. Mapping a functional cancer genome atlas of tumor suppressors in mouse liver using AAV-CRISPR-mediated direct in vivo screening. Science Advances 2018, 4:eaao5508. 2018