Synthetic Tumor Recruited Immunocellular Therapy (STRICT) for Lung Cancer
Abstract
Objective: Our work addresses the area of emphasis, "identify innovative strategies for prevention and treatment of early and/or localized lung cancer." Current therapeutic approaches for lung cancer fail to prevent cancer relapse, thus limiting patient survival. Our strategy, Synthetic Tumor Recruited Immuno-Cellular Therapy (STRICT), makes use of the body s own immune system to kill primary tumors and to prevent recurrence. Our artificial gene circuits will be specifically activated in lung cancer cells. These circuits will co-opt the cancer cells to attract immune cells (T cells), which will destroy the tumors. By inducing long-term immune memory, STRICT has the potential to be effective against cancer relapses, thus helping to enhance long-term survival. Rationale: Lung cancer can often be lethal despite early detection due to failures in conventional therapy, recurrence, and metastasis. Thus, there is an urgent need for novel, safe, and effective therapies. Existing immunotherapies often work by distinguishing cancer cells from normal ones based on cancer-cell-specific signatures on their cell surfaces. However, these signatures are hard to find for most tumors, thus limiting the applicability of immunotherapy. Furthermore, current T-cell immunotherapy requires labor-intensive and costly engineering of patient-specific cells for each individual patient. We intend to develop novel therapies in which T cells (part of the patient s immune system) are recruited to kill cancer cells based on intracellular signatures that are easier to identify and target than extracellular ones. Highly engineered DNA sequences (gene circuits), delivered systemically, will be turned on only within cancer cells and not in normal cells. Cancer cells will respond to the activated gene circuit by producing immune-modulating proteins, such as Surface T-cell Engagers (STEs) and other molecules that can recruit and activate immune cells. T cells will be recruited by the STEs to kill the tumor cells. It is not only those cancer cells harboring the gene circuit that will be killed; STRICT will elicit an extended immune response, killing even those cancer cells that do not have the gene circuits and establishing long-lasting protection against metastases and recurrent cancer. Safety switches in the circuits will enable physicians to modulate the circuits or shut them off if needed. STRICT can be further optimized via combinations with other cancer therapies. Aim 1: We will engineer synthetic gene circuits to specifically display and express immune modulators in order to recruit T cells to kill tumors. We will validate the effectiveness of these gene circuits in vitro and in vivo. Aim 2: We will test the ability of STRICT to eliminate primary, recurrent, and metastatic lung cancer via systemic administration. We will optimize STRICT to maximize efficacy, to prevent tumor relapse via long-term immune memory, and to prepare for future preclinical and clinical trials. Who Will Be Helped and How: This work will benefit lung cancer patients regardless of stage, but especially those with metastatic or relapsing disease, with a new and potentially powerful therapy to be used alone or with other therapies. STRICT provides a powerful and customizable platform for building effective and highly targeted treatments against difficult-to-treat lung cancers. Potential Clinical Applications, Benefits, and Risks: STRICT has the potential to become a new therapy for lung cancer. Benefits include highly effective treatments and long-lasting protection against cancer relapse and metastasis. Risks include the difficulty of finding a suitable delivery vehicle. We worked with Prof. Artzi at the Massachusetts Institute of Technology (MIT), a gene delivery expert, to deliver STRICT circuits to ovarian cancer, and we will leverage this experience here. Our lab has deep expertise in designing synthetic gene circuits to detect cancer cells
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 07, 2017
- Source ID
- W81XWH1710159
Entities
People
- Timothy K. Lu
Organizations
- Massachusetts Institute of Technology
- United States Army