Sidi Chen, PhD

Assistant Professor

Research Interests

Cell Transformation, Neoplastic; Genetics; Immunity; Lung Neoplasms; Neoplasm Metastasis; Stem Cells; CRISPR-Cas Systems

Public Health Interests

Cancer genetics

Research Organizations

Faculty Research

Liver Center

Stem Cell Center, Yale

Yale Cancer Center: Genomics, Genetics, and Epigenetics

Research Summary

My group's current research focuses on cancer systems biology, in particular in vivo CRISPR/Cas9-mediated cancer modeling and genetic screening. In particular, we utilize a wide variety of modern biology and engineering tools including genome-wide CRISPR screens to study the genetic and epigenetic bases of tumorigenesis, angiogenesis, metastasis and cancer immunology. 

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 basis of cancer progression, 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 and animal models. Some examples of projects are listed below; while students are also strongly encouraged to innovate new ideas with their own creativity.


1. Modeling brain cancer with CRISPR/Cas9-mediated in vivo gene editing

Brain tumors constitute one of the most lethal cancer types, primarily due to the lack of effective treatments. An improved understanding of the genetic basis underlying the development and progression of brain cancer will be key to the identification and implementation of new approaches able to improve outcomes for this deadly disease. The goal is to systematically identify and characterize major genetic regulators in the processes of brain oncogenesis. We will perform in vivo modeling of genetic mutations and characterization of regulators in primary brain cancer. We will first build animal models of brain tumors, in particular glioma/glioblastoma, using conditional Cas9 transgenic mice to engineer combinations of specific mutations reflecting the genomic aberrations present in human patients. The specific tumor models will be built using cell-type-specific disruption of tumor suppressor genes such as p53, NF1, CDKN2A, PTEN, as well as targeted engineering of oncogenic mutations in EGFR, HRAS, IDH1, or in combinations due to their prevalence primary brain cancer in human. We will utilize these models to study the functional roles and phenotypic effects of patient mutations in brain cancer progression, and test the therapeutic response of brain cancer with a particular genotype. Radiation, chemotherapy, targeted therapy or immune therapy treatments will be administered to these mice and responses will be measured using live imaging modalities as well as histological and pathological analyses.


AAV mediated direct in vivo screen identifies functional suppressors in glioblastoma.

Ryan D. Chow*, Christopher Guzman*, Guangchuan Wang*, Florian Schmidt*, Mark Youngblood, Lupeng Ye, Youssef Errami, Matthew Dong, Michael Martinez, Sensen Zhang, Paul Renauer, Kaya Bilguvar, Murat Gunel, Phillip Sharp, Feng Zhang, Randall Platt @, Sidi Chen @.  Nature Neuroscience (2017) (@ corresponding author)


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.

Cell. 2014 Oct 9;159(2):440-55. 

 

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.

Nature. 2014 Oct 16;514(7522):380-4.


2. Genetic screening of cancer metastasis

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.

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. Cell. 2015 Mar 12;160(6):1246-60.

3. Function of non-coding RNAs in cancer progression

Genome-wide and vigorous case studies have converged on the fact that small non-coding RNAs are fundamental regulators of cancer. We are interested in the roles of these small RNAs in multiple hallmarks of cancer, such as proliferation, angiogenesis, metastasis and drug resistance. We will utilize a combination of molecular and genetic approaches to knockout or activate these non-coding RNAs and study their functions both in human cells and animal models.

 

Global microRNA depletion suppresses tumor angiogenesis.

Chen S*, Xue Y*, Wu X, Le C, Bhutkar A, Bell EL, Zhang F, Langer R, Sharp PA.

Genes Dev. 2014 May 15;28(10):1054-67.

 

4. Computational analysis of gene networks

Most biological processes are not governed by a single gene, in fact, they are regulated by complex networks. For instance, microRNAs regulate 60~80% of the protein-coding genes in the genome. One of the most important classes of microRNA target genes is transcription factor (TF). TFs are master regulators that control the expression of hundreds to thousands of genes by binding to their cis-regulatory elements in the genome. The nature of complex regulation involving microRNAs and TFs makes the understanding of the network challenging. Furthermore, gain or loss of new genetic elements can influence the network dynamics, which sometimes lead to strong phenotypes. We seek to dissect this network using an interdisciplinary approach, with a combination of in silico computation and experimental validation. We will build models of networks and test for hypothesis in cells, by genetic manipulations with gene editing, transcriptional repression and/or activation. Perturbations will be introduced into “modeled” and “real” networks, and readouts will be calculated or measured to test hypotheses of robustness, dynamics, fitness and evolution.

 

New genes as drivers of phenotypic evolution.

Chen S, Krinsky BH, Long M. Nat Rev Genet. 2013 Sep;14(9):645-60. doi: 10.1038/nrg3521. Review.

 

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.

 

6. 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)
 

Guangchuan Wang, Ryan D. Chow, Lupeng Ye, Christopher D. Guzman, Xiaoyun Dai, Matthew B. Dong, Feng Zhang, Phillip A. Sharp, Randall Platt @, Sidi Chen @. Pooled AAV-CRISPR Screen with Targeted Amplicon Sequencing. BioRxiv (2017) doi: https://doi.org/10.1101/153643 (@ corresponding author)



Selected Publications

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Contact Info

Sidi Chen, PhD
Lab Location
Sidi Chen LaboratoryWest Campus Integrative Science & Technology Center
850 West Campus Drive, Rm 314

West Haven, CT 06516
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Mailing Address
850 West Campus Drive
Integrated Science & Technology Center

West Haven, CT 06516

Curriculum Vitae

Chen Lab website