Understanding and enhancing the distinction between self and non/altered self
Dissecting and rewiring (multi)cellular circuits to uncover and develop immune-based/like mechanisms for disease treatment and prevention
The immune system has a remarkable ability to distinguish between healthy (self) and unhealthy (non/altered self) cells and eliminate only the latter. This process can depend on a single cell or millions of cells that transmit information to one another.
Using and developing genetic and genomic tools we aim to augment, redirect, and generate new types of immune responses to eliminate and reprogram “altered self” cells, including cancer, senescent, virally infected, and other types of dysfunctional disease driving cells.
How? By decoding and integrating mechanisms that have evolved for millions of years and are imprinted in immune and non-immune cells with mechanisms that we “evolve” and rationally design in the lab through synthetic biology and directed evolution.
Selected Publications
Mapping spatial organization and genetic cell-state regulators to target immune evasion in ovarian cancer Yeh*, Aguirre*, Laveroni*, et al., Nature Immunology (2024)
Mapping multicellular programs from single-cell profiles
Jerby and Regev, Nature Biotechnology (2022); Seminar and Voices on Cancer CellOpposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma.
Jerby et al., Nature Medicine (2021)A cancer cell program promotes T cell exclusion and resistance to checkpoint blockade.
Jerby et al., Cell (2018) 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 et al., Cell (2014)
Pan-cancer mapping of single CD8+ T cell profiles reveals a TCF1:CXCR6 axis regulating CD28 costimulation and anti-tumor immunity
Tooley*, Jerby*, et al. Cell Reports Medicine (2024)
Preprint Watch, Nature Reviews Immunology
Livnat Jerby
Assistant Professor
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
Recorded Seminars
Overview of our approach and cell engineering work.
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
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 outstanding researchers, graduate students, and future postdocs, who are highly motivated and have relevant research experience. To apply email your CV and a brief synopsis of your research experience and interests.