National Cancer Institute
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University of California, San Francisco PS-OP

San Francisco, CA

Overview | Investigators

Overview

City of Hope

Project Name

Understanding breast cancer progression as a defect in the mechanics of tissue self-organization

Project Website

https://www.gartnerlab.ucsf.edu

List of Collaborating Institutions

University of California San Francisco
California Institute of Technology
City of Hope

Project Description

A progressive breakdown in the bilayered structure of the mammary epithelium is the hallmark of all breast cancers, but the structural change that occurs between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of particular importance because it represents a major inflection point in risk for patients. Breast cancers originate in the inner luminal layer of the mammary epithelium, where transformed luminal epithelial cells (LEP) proliferate to fill the ducts and lobules in DCIS. Surprisingly, LEP in DCIS have acquired all the necessary genetic aberrations to invade, but remain constrained within the tissue by an intact outer myoepithelial (MEP) layer—a group of cells that forms a dynamic barrier blocking access of the in situ tumor to the basement membrane (BM, the specialized extracellular matrix (ECM) that surrounds the mammary epithelium).

Translocation of transformed LEP past the MEP layer has been proposed as the rate-limiting step in progression to IDC. Here, we aim to identify the physical and molecular changes that must occur in LEP to facilitate this structural transition. We approach this challenge through the lens of mammary epithelial self-organization. We hypothesize the existence of a rate-limiting structural intermediate during the progression of DCIS to IDC, where LEP translocate into the MEP layer, next to the BM. We propose a statistical mechanical framework for understanding how perturbations to the mechanics and dynamics of tumor cells facilitate the formation of this intermediate and propose to test this concept using complementary in vitro and in vivo experimental systems: using organoids reconstituted from human reduction mammoplasty tissues and genetically engineered mouse models.

Our long-term goal is to reveal the changes that promote and inhibit progression from DCIS to IDC. Better physical and molecular predictors of progression would benefit DCIS patients who would otherwise be over-treated, as only a third of DCIS cases progress to IDC. Further, blocking LEP translocation would represent a therapeutic strategy to prevent breast cancer progression.

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Investigators

Zev Gartner, Ph.D.

Zev Gartner, Ph.D.
Dr. Gartner is working to understand the principles governing the self-organization of human tissues, with the goal of engineering tissues for regenerative medicine and stabilizing tissues for cancer prevention. Dr. Gartner completed his undergraduate studies in Chemistry at UC Berkeley where he worked as a Beckman Fellow with Dr. Yeon-Kyun Shin. He received a PhD in Chemical Biology as a National Science Foundation Graduate Research Fellow with David Liu at Harvard University, and completed training as Jane Coffin Childs Postdoctoral Fellow with Carolyn Bertozzi at UC Berkeley. He is currently a Professor in the Department of Pharmaceutical Chemistry at the University of California, San Francisco and co-director of the NSF Center for Cellular Construction. His work has been honored with the NIH New Innovator Award and the DOD Era of Hope Scholars award. He was selected among the Popular Science “Brilliant 10” in 2015 and as a Chan/Zuckerberg Biohub investigator in 2017.

 

Matt Thomson, Ph.D.

Matt Thomson, Ph.D.
Matt Thomson is an Assistant Professor of Computational Biology at Caltech. His group applies mathematical modeling and data analysis methods to study self-organization in biological systems at the molecular, cellular and tissue scale. Matt received his AB in Physics and PhD in Biophysics from Harvard University. Following graduate school, Matt was an independent fellow at UCSF. Matt was awarded the Merrimack Prize in Systems Biology in 2016 and a 2019 Packard Fellowship for his contributions.

 

Mark Labarge, Ph.D.

Mark Labarge, Ph.D.
Dr. LaBarge’s work is focused on development of primary human cell culture systems and bioengineered microenvironment to model epithelial tissues with a goal of better understanding how normal breast tissue becomes more susceptible to cancer with age. Dr. LaBarge completed his undergraduate studies in Genetics at UC Davis where he worked with Areina van Bruggen in using biological controls to prevent plant pathogens. He received a PhD in Molecular Pharmacology with Helen Blau at Stanford University, and completed training as an American Cancer Society Postdoctoral Fellow with Mina Bissell at the Lawrence Berkeley National Laboratory. He is currently a Professor in the Department of Population Sciences at the Beckman Research Institute at City of Hope ,and associate-director of the Center for Cancer and Aging. His work has been honored with the NIH Transition Award and the DOD Era of Hope Scholars award.

 

Andrei Goga, Ph.D.

Andrei Goga, M.D., Ph.D.
Andrei Goga, MD, PhD - Professor, Vice-Chair, UCSF Dept. of Cell & Tissue Biology and Dept. of Medicine. Dr. Goga is a physician-scientist, basic lab investigator as well as a practicing breast medical oncologist, whose lab is focused on studies of oncogene signaling and the identification of new therapeutic strategies to target currently undrugable oncogenes. We have expertise using conditional transgenic models of various cancers and various patient-derived xenograft models to uncover new mechanisms of tumorigenesis. Aggressive invasive cancers contribute to metastasis, which remains the single greatest challenge that cancer patients face today, with nearly 90% of cancer- related mortality attributable to progressive metastatic disease. To address this challenge, our research group seeks to understand the functional consequences of tumor heterogeneity, determine how diverse tumor cells interact to elicit emergent properties for metastasis, and to identify new therapeutic targets.

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