Modeling of Lung Adenocarcinoma Tumorigenesis Using Recombinase-Driven Sequential Gene Mutations
Abstract
Rationale: Lung cancer is characterized by a heavy mutation rate: tumors have over six mutations that make actual changes in protein products per one million DNA bases. However, current lung cancer models are very inefficient in accounting for the complexity of the mutational landscape. Here, we propose to establish a highly scalable platform, called the tandem Gene Perturbation Cassette (GPC) gene circuit, that generates multiple genetic perturbations whose temporal order is precisely controlled by drug treatment. Our gene circuit uses Cas9 and single guide RNAs (sgRNAs) to generate insertion/deletion mutations in key tumor suppressor genes in normal lung cells. The temporal order of the mutations made by sgRNAs is ensured by a series of chemically induced recombinase reactions that excise sequences containing sgRNA to lead the way for the next sgRNA to be expressed. This proposal addresses the Fiscal Year 2017 Area of Emphasis “Understand the molecular mechanisms of initiation and progression to clinically significant lung cancer.” This proposal will optimize and validate the tandem GPC gene circuit and apply it for identifying and modeling sequential mutations in K-RasG12D mutated lung adenocarcinoma. We will optimize sgRNAs and recombinases for the efficient, sequential generation of mutations relevant to cancer. We will then generate pooled tandem GPC libraries carrying all possible permutations of gene perturbations and deliver this library to normal bronchial and small airway epithelial cells for xenograft (implantation) in immunocompromised mice. GPC barcodes isolated from the xenografted tumors will be read by next-generation sequencing to identify the specific sequence of gene perturbations that gave rise to the tumor. This platform is innovative because of these two features: 1) Temporal Control: Timing of the next gene perturbation can be controlled by ligand treatment. Therefore, the platform is robustly controlled. 2) Scalability: This gene circuit is controlled by alternating treatment with two different ligands. Therefore, this gene circuit can indefinitely induce a long array of sequential gene mutations, as long as distinct recombinases are available. More than a dozen different recombinases have been reported to date. Applicability: These findings should reveal the temporal order of mutations that occur as normal epithelial cells evolve to advanced lung adenocarcinoma. We envision the tandem GPC circuit as a major breakthrough impacting basic research on lung cancer and lung cancer therapy, as well as clinical practice, as these circuits offer a unique, highly scalable cancer model that spans early to late tumorigenesis and enables the temporal order of gene perturbations to be determined in clinically relevant lung cancer subtypes. Lung cancer is major health concern for military Veterans. This proposal will benefit patients, especially those with early stages of lung cancer, by enabling a more accurate prediction of the course of the disease at diagnosis. By profiling existing gene mutations and elucidating the temporal order of gene perturbations in lung cancer, we would be able to predict future disease progression and the next mutational “hotspot” so that pre-emptive measures to prevent tumor progression could be rationally designed. Our knowledge of the sequence of mutations in K-RasG12D mutated lung adenocarcinoma, once validated in the clinic, can immediately be applied to cancer diagnosis, and we expect that our findings can directly benefit patients within a decade.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810513
Entities
People
- Timothy K. Lu
Organizations
- Massachusetts Institute of Technology
- United States Army