Lung and pancreatic cancers are leading causes of cancer deaths in the United States and worldwide. Patients with lung or pancreatic cancer survive only few months after diagnosis and over 90% succumb to the disease. These cancers are also some of the few malignancies for which survival has not improved substantially over the past 25 years and there is currently no effective treatment for patients suffering from lung and pancreatic cancer.
The main challenge is to identify novel therapeutic targets in cancer cells to guide the development of new efficacious drugs and immunotherapeutic approaches in cancer patients. The vast majority of lung and pancreatic tumors display mutations in a gene called KRAS. Activation of KRAS by these mutations confers a survival advantage to cancer cells, signaling them to grow indefinitely, and making them resistant to current therapeutic approaches including immunotherapy. Our overarching goals are to better understand the signaling networks driving the growth of KRAS mutant pancreatic and lung cancer cells and thus to identify novel therapeutic options for this dismal disease. We aim to understand tumor cells’ capacity to evolve and “re-wire” their signaling networks to evade immunological response.
Our research strives to explain why tumors often rapidly become resistant to chemo or targeted therapy and not responsive to immunotherapy. We use this knowledge to design combination therapies, which are several treatments delivered at the same time or sequentially. Combination therapies may have a stronger effect to prevent or delay the appearance of resistant tumors. Similarly, two drugs targeting different pathways may allow a decrease in the dose for each drug, limiting toxicity while retaining efficacy. Our goal is to identify candidate drug targets whose combination with current therapeutics can improve efficacy and/or decrease side effects.
Our approach is to use emerging technologies to engineer highly efficacious chimeric antigen receptor T lymphocytes (CAR T cells) by conducting CRSPR/Cas9 genetic screens and big-data bioinformatics meta-analysis to identify molecular factors that will facilitate CAR T cells: trafficking to cancer site, survival in hostile cancer environment, and recruitment of other immune cells to tumor. Our results are rapidly explored using our modular genetic engineering systems to create a novel superior CAR T cells. Using our research platform, we can test numerous conditions that boost the ability of CAR T cells to penetrate and survive in cancer tissue and recruit new immune cells into cancer site.
Our advanced techniques allow us to pair these fine-tuned improvements with innovative Chimeric Antigen Receptors that we generated against multiple targets to allow CAR T-cells to recognize pancreatic and lung cancer cells. To enable rapid pre-clinical testing of our discoveries we have optimized methods of generating CAR T cells from animals. Animal CAR T cells faithfully recapitulate human counterparts and enable us to use immunologically proficient genetically engineered animal models of human cancers as a platform to accelerate testing of the most efficacious therapeutic conditions.
Our goal is to guide the development of precision medicine clinical trials through the following projects:
- Systematic identification of new cancer therapeutic targets and drug synergies
- Dynamic drug-disease response investigation
- Novel approaches to block the effects of oncogene activation in pancreatic and lung cancers
- Next generation CRISPR/Cas9-based mouse model to enable pharmacogenetic screens
- Enhancing efficacy of engineered CAR T-cell therapy for pancreatic and lung cancers
Protein synthesis fuels pancreatic and lung cancer progression
Upregulation of protein synthesis is a hallmark of many oncogene-driven tumors and is essential to sustain cancer cell growth.
We have recently identified METTL13 as a novel lysine methyltransferase and demonstrated that METTL13 dimethylation of eEF1A (eukaryotic elongation factor 1A) at lysine 55 is utilized by pancreatic and lung cancers to increase translational output and promote tumorigenesis. METTL13-catalyzed eEF1A methylation increases eEF1A’s intrinsic GTPase activity and protein production in cells. METTL13 deletion dramatically reduce neoplastic growth in mouse models and in patient-derived xenografts (PDXs) from primary pancreatic and lung tumors. Together, our work uncovers a mechanism by which lethal cancers become dependent on the METTL13-eEF1AK55me2 axis to meet their elevated protein synthesis requirement and suggest the METTL13–eEF1AK55me2 axis as a potential therapeutic target in pancreatic and lung cancer
( Cell, 2019)
Enhancing efficacy of engineered CAR T-cell therapy for pancreatic and lung cancer
Pancreatic and lung cancers respond poorly to traditional chemotherapy and radiation therapy whereas surgery is limited only to a small fraction of patients. Recently, immunotherapy that enlists and strengthen the power of a patient’s immune system to attack tumors—has emerged as potent cancer treatment modality. However, the first generation of immunotherapies based on so called “checkpoint blockade” largely fail to improve the outcome of patients with pancreatic and lung cancer.
A rapidly emerging new immunotherapy approach is called adoptive cell transfer (ACT): collecting and using patients’ own immune cells to treat their cancer. There are several types of ACT but, thus far, the one that has advanced the furthest in clinical development is called CAR T cell therapy - based on the expression of a chimeric antigen receptor (CAR) in T cells. Until recently, the use of CAR T-cell therapy has been restricted to small clinical trials in patients with advanced blood cancers. In 2017, two CAR T-cell therapies were approved by the FDA for childhood leukemia and advanced lymphomas. However, CAR T cell therapy showed limited success in treating solid tumors, especially lung and pancreatic cancers due to (1) poor trafficking to the tumor from the bloodstream; (2) limited survival, expansion and activation inside the tumor and (3) inability to recruit other tumor killing immune cells.
Our research aims to successfully eliminate these roadblocks by applying systemic CRSPR/Cas9 genetic screens and performing in-depth big-data bioinformatics meta-analysis to identify key molecular signals that drive CAR T cell efficacy like enhancing expansion and limiting exhaustion. Leading way to successful and long-lasting elimination of antigen-positive cancer cells as well as ‘epitope spreading’ engaging endogenous T cells with reactivity against additional tumor neoantigens clearing antigen negative tumor cells.
Systematic identification of new cancer therapeutic targets and drug synergies
Tumor cells’ capacity to evolve and “re-wire” their signaling networks in response to therapy can explain why tumors often rapidly become resistant to therapy. This observation has led to the idea of combination therapies: several treatments delivered at the same time or sequentially may have a stronger effect to prevent or delay the appearance of resistant tumors; similarly, two drugs targeting different pathways may allow a decrease in the dose for each drug, limiting toxicity while retaining efficacy.
Our goal is to identify candidate drug targets whose combination with current therapeutics can improve efficacy and/or decrease side effects.
Recently, we have investigated a novel epigenetic therapy based on co-inhibition of BET proteins and HDACs, which synergistically suppresses pancreatic and lung cancer progression and maintenance. Our research, for the first time we showed sustained cancer regression in the animal and human models of the most aggressive lung and pancreatic cancers (Nature Medicine, 2015).
Dynamic drug-disease response investigation
The limitations of static analysis of tumor tissues at a single
terminal endpoint are especially apparent in the context of
therapeutic studies, in which the dynamic response to treatment is of
particular consequence e.g. cancer relapse. In addition, such studies
are limited by the need for large numbers of samples (cost and time
consuming) to overcome increased intra-group variance. We propose to
mitigate the effects of tumor heterogeneity by retrieving tissue
samples from the same tumor at multiple time points.
Our main approach is to utilize genetically engineered mouse models of pancreatic cancer, which, despite the uniformity of initiating mutations, acquire secondary mutations and/or undergo molecular “re-wiring” in response to treatment.
We developed the “mouse clinic” approach utilizing pre-clinical mouse models integrated with Magnetic Resonance Imaging (MRI) to perform real-time analysis of tumor volume and composition in mouse models. That allows precise study of tumor progression and response to therapy (Nature Medicine, 2015).
Novel approaches to block the effects of oncogene activation in pancreatic and lung cancers
Our recent work has revealed promising mechanisms that may serve as candidates for therapeutic intervention in cancers driven by mutant KRAS signaling.
In our 2013 Nature publication, we used a small cell-permeable peptide to disrupt the cascade of enzymes that propagate tumorigenic signals from mutant KRAS (Nature Medicine, 2013).
We also made the novel discovery of the mechanism of action of lysine methyltransferase SMYD3 in regulation of KRAS signaling, which was previously unrecognized. Inhibition of the SMYD3 enzyme, which enhances the effects of mutant KRAS in cancer cells hampers tumor growth (Nature, 2014).
Similarly we have identified another lysine methyltransferases SMYD2 as critical and non-redundant regulator of KRAS signaling (Genes and Development, 2016).
Next generation CRISPR/Cas9-based mouse model to enable pharmacogenetic screens
The variability in treatment responses and narrow therapeutic index of anticancer drugs are some of the key challenges oncologists face.
In collaboration with Jacks Lab (MIT), we have pioneered the use of the CRISPR/Cas9 system in vivo to enable rapid, flexible, and scalable investigation of gene function in an animal model that faithfully recapitulates human disease, including response to immunotherapy (Nature Medicine, 2015).
This method enables new comprehensive ways to combine mouse models and next-generation sequencing approaches to identify the dynamic interplay between specific tumor genotypes and the response to therapy.
The rapid generation of mouse models will not only help to decipher basic molecular mechanisms but also enables semi-high throughput approaches to target identification and drug validation in pancreatic cancer.