Welcome to the Jerby Lab
Dissecting and targeting (multi)cellular immune circuits to uncover mechanisms and new interventions
Livnat Jerby-Arnon
Assistant Professor
(she/her); ljerby [at] stanford [dot] edu
Jeehyun Yoe, Ph.D.
Postdoctoral Fellow
Reece Villarin Akana
PhD Student, Cancer Biology
Young-Min Kim, Ph.D.
Postdoctoral Fellow
Dixian Zhu, Ph.D.
Postdoctoral Fellow
Olivia Laveroni
Research Assistant
Chang Sun, Ph.D.
Postdoctoral Fellow
Mike Tsai
PhD student, Cancer Biology
Yuxin Cai, Ph.D.
Postdoctoral Fellow
Christine Yiwen Yeh
MD/ PhD Student, BMI; co-advised by Sylvia Plevritis
Kristen Frombach
PhD student, Cancer Biology
Celeste Zesati Diaz
PhD student, Cancer Biology; co-advised by Jennifer Cochran
Karmen Aguirre
PhD Student, Cancer Biology
Soua Lee
Administrative Associate
Selected Publications & Preprints
Mapping ovarian cancer spatial organization uncovers immune evasion drivers at the genetic, cellular, and tissue level
Yeh*, Aguirre*, Laveroni*, et al., biorxiv (2023) *Equal contributionMapping multicellular programs from single-cell profiles
L. Jerby-Arnon and A. Regev, Nature Biotechnology (2022)
See Seminar and Voices on Cancer CellOpposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma.
Jerby-Arnon et al., Nature Medicine (2021)A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade.
Jerby-Arnon et al., Cell (2018)
See SeminarPerturb-Seq: Dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens.
Dixit et al., Cell (2016)Predicting cancer-specific vulnerability via data-driven detection of synthetic lethality.
Jerby-Arnon et al., Cell (2014)
Overview. We develop high-throughput, engineering-based approaches to: (1) dissect and target multicellular regulation at greater scale, resolution, and depth, focusing on the molecular mechanisms that govern innate and adaptive immune responses in cancer, (2) broaden the spectrum of immunomodulating interventions to trigger targeted immune responses in more effective and targeted ways, including antigen-independent modalities, (3) modify cells and groups of cells to augment or create new "synthetic" (multi)cellular circuits – allowing us to probe the “inner-workings” of multicellular processes and potentially form a basis for new types of disease treatment and prevention strategies.
Current efforts. Bringing together advances in genetic engineering, machine learning, and single-cell/spatial genomics, we study the interplay between cancer cells and cytotoxic lymphocytes, namely, CD8 T cells and NK cells. These types of cells are a very convenient model system, as we can modify them ex vivo, and then study them in vivo. We develop new multidisciplinary methods to identify regulators of cellular and tissue immunogenicity, and uncover mechanisms controlling lymphocyte activation/ suppression, recruitment, and infiltration.
Specific projects include: developing a multimodal perturb-seq system to identify key regulators of cancer-T-cell and cancer-NK interactions; mapping cancer-immune dynamics across time and space using emerging single-cell and spatial profiling technologies; and hybrid CRISPR-ML systems to identify combinatorial genetic perturbations to induce cytotoxic lymphocyte recruitment, infiltration and effector functions in the tumor microenvironment.
Recorded Seminars
Multicellular biology - recent computational method paper (Jerby and Regev, Nature Biotechnology 2022) and new directions
Digital science seminar series, BCH/HMS
https://www.youtube.com/watch?v=iBtzD0rKSdM&list=PLZH5lNty_E1pKKiMI_rGIRPwtAQgbRXpr&index=3&t=2831s**The cancer immune interplay at the cellular and tissue level - previous work in melanoma (Jerby et al., Cell 2018)
https://youtu.be/65Arj2wk5vI**From data to mechanisms: Machine learning to map and probe cellular circuits across scales Biomedical Informatics Seminar series, Stanford
https://youtu.be/CsTb3xfv5x4
**Log into YouTube with your Stanford email to access this content
Contact information
Department of Genetics
Stanford University
Biomedical Innovation Building (BMI)
240 Pasteur Dr, Palo Alto, CA 94304
Office phone: (650) 497-0294
Open positions
Job openings are available for motivated graduate students, postdocs, and research assistants, with relevant research experience. Such experience and opportunities can be either focused on (1) molecular and cell biology, immunology, and/or cancer biology, (2) algorithm design, statistics, programming, and machine learning; or (3) the combination of the two. To apply email your CV and a brief synopsis of your research experience and interests.