Tumors consist not only of cancer cells, but also stromal and immune cells that constitute the tumor microenvironment (TME). Cancer cells can take on dramatically different properties based on the microenvironment. The clinical impact of the TME is only becoming appreciated in recent years. In many different cancer types, including breast cancer (BC), tumors with higher stromal fractions portend worse clinical outcomes. In contrast, tumors infiltrated by CD8 T cells have better clinical outcomes. Hence, tumors behave differently based on the collective behavior of the microenvironment. We will leverage biotechnology advances in sequencing single cells to better understand the important determinants of the coevolution between the adaptive immune response and the tumor. By tracking the spatial geometry of cells in tumor samples we hope to better understand the TME and ultimately determine which genetic factors can be best exploited for therapeutic intervention.
Funded in Collaboration With Stand Up To Cancer (SU2C)
The last two decades have seen the development of increasingly effective cancer therapies that target different aspects of tumors cells, including uncontrolled growth/survival, evasion of the immune system, hyper-activated signaling pathways and dysregulated gene expression programs. In a subset of cancers, including non-small cell lung cancer (NSCLC) with mutations in the epidermal growth factor receptor (EGFR), these therapies can lead to dramatic tumor regressions in a significant number of patients. However, in the majority of EGFR mutant lung cancer patients who respond to anti-cancer therapies, relapse usually occurs preventing long-term cures. We propose to investigate the reasons why cancer cells become resistant to treatment. We believe a tumor is made up of a number of different types of cells that can each respond differently to treatment. We hope to uncover and understand these differences by looking at genomic data taken from patients who are biopsied before treatment, during response to treatment, and when resistance emerges. We are also interested in understanding the role the immune system plays during cancer treatment. We’d like to understand if the tumor has developed ways to evade the immune system, and how we can promote the patient’s own immune system to fight back against the cancer. It is our hope that combining traditional drug treatment with newer immunotherapies will provide greater tumor regressions. Our goal is to create a deeper understanding of the make-up of a tumor in order to identify novel therapies to expand the survival of patients with NSCLC.
Funded in Collaboration With Stand Up To Cancer (SU2C)
The so called targeted therapies are effective in tumors that strictly depend on a given protein or cellular signaling (the target) for growth and survival. Hyperactivation of the PI3K pathway is frequent in breast cancers and its pharmacologic inhibition showed clinical responses. However, these molecules alone cannot elicit a durable inhibition of tumor growth because the tumor can adapt and compensate the inhibition of the pathway.
Thus, targeting these compensatory mechanisms in combination with the PI3K pathway would in principle lead to stronger and more durable antitumor activity.
In this proposal we aim to validate in the laboratory theoretical predictions of successful drug combinations. These predictions are obtained from mathematical models developed from what is currently known about the perturbations of the PI3K/AKT signaling network in response to different inhibitors of the pathway. In addition, we plan to test therapeutic combinations based on genomic analyses from tissue samples of breast cancer patients treated with PI3K inhibitors.
Taken together, our results should provide the rationale to test novel and more effective therapeutic options for patients with hyperactivation of the PI3K pathway.
Funded in Collaboration With Stand Up To Cancer (SU2C)
Pancreatic ductal adenocarcinoma (PDAC) is a frequent cause of cancer death in the United States; it currently is the fourth most common cause of cancer death and is expected to become the second most common cause of cancer death within the next five years. Unlike virtually all other major cancers, pancreas cancer is both increasing in incidence and has shown essentially no improvement in five year survival over the past two decades. The exceptional lethality of pancreas cancer is multifactorial, resulting from an intrinsically aggressive biology, lack of effective means of early detection, and poor responsiveness to systemic chemotherapy. Clearly novel approaches to this disease are needed.
Although there have been anecdotal reports of responses to immune-based therapies in pancreas cancer, activation of cellular immunity using checkpoint inhibitors, vaccine strategies and transfer of genetically modified T cells has not been shown to be generally effective. We have assembled a team of physicians, cancer immunobiologists, computational biophysicists, and engineers to better understand the unique immunological microenvironment of pancreatic cancer, develop the technologies needed to take advantage of therapeutic vulnerabilities, and to form a multi-institutional clinical consortium to readily implement these strategies to help change the course of this deadly disease.
Funded in Collaboration With Stand Up To Cancer (SU2C)
The study encompasses multiple directions. First, genome of cancer cells acquires mutations at a higher rate compared to benign cells. Some of these novel mutations affect proteins synthesized within the cell, and these modified proteins (tumor neoantigens) may interact with immune system. We identify these novel neoantigens and study their interaction with immune cells in the tumor microenvironment. The other direction is quantification of non-coding RNAs, in particular, some repeat RNAs, expressed by cancer cells. We focus on the mechanisms of expression of these RNAs, their immunogenic properties and their interaction with tumor microenvironment. Understanding these topics would open the door towards unleashing immune response against pancreatic tumors.
Funded in Collaboration with Stand Up To Cancer (SU2C)
Pancreatic ductal adenocarcinoma (PDAC) is a frequent cause of cancer death in the United States; it currently is the fourth most common cause of cancer death and is expected to become the second most common cause of cancer death within the next five years. Unlike virtually all other major cancers, pancreas cancer is both increasing in incidence and has shown essentially no improvement in five year survival over the past two decades. The exceptional lethality of pancreas cancer is multifactorial, resulting from an intrinsically aggressive biology, lack of effective means of early detection, and poor responsiveness to systemic chemotherapy. Clearly novel approaches to this disease are needed.
Although there have been anecdotal reports of responses to immune-based therapies in pancreas cancer, activation of cellular immunity using checkpoint inhibitors, vaccine strategies and transfer of genetically modified T cells has not been shown to be generally effective. We have assembled a team of physicians, cancer immunobiologists, computational biophysicists, and engineers to better understand the unique immunological microenvironment of pancreatic cancer, develop the technologies needed to take advantage of therapeutic vulnerabilities, and to form a multi-institutional clinical consortium to readily implement these strategies to help change the course of this deadly disease.
Despite decades of research, breast cancer still represents second most deadly malignancy for women in the United States. Furthermore, current therapeutic options can cause disfigurement and malaise, potentially reducing quality of life. Therapies that lead to durable remission with minimal side effects are urgently needed. We propose that an integrated approach to cancer research that considers both tumor heterogeneity and associated cells in the tumor microenvironment may reveal novel therapeutic approaches. A population of cancer cells, termed cancer stem cells, has been proposed to be resistant to therapies and lead to relapse. Very little work has examined the sensitivity of breast cancer stem cells to different methods of immune-mediated killing or their ability to suppress local immune responses. We first intend to ensure that the breast cancer stem cell population we plan to study is likely to be the chemoresistant population of cells in patients with breast cancer. We will then measure the sensitivity of these cells to different mechanisms of immune-mediated killing along with their ability to protect neighboring cells from attack by immune cells. We will identify how these breast cancer stem cells interact with the immune system in order to identify potential weaknesses that can be targeted clinically to sensitize breast cancer stem cells and their neighboring cancer cells to immunotherapy approaches.
Funded in Collaboration With Stand Up To Cancer (SU2C)
Decades of cancer research and therapeutic development have made it clear that achieving durable control of invasive solid tumors requires therapeutic combinations of a large number of drugs that target different elements within cancer cells. In aggressive cancers where cure is achievable (e.g., subtypes of leukemia and lymphoma), as many as 4-6+ drugs may be needed when administered as curative treatment to patients. This is because simpler drug combinations become ineffective due to the development of drug resistance by the tumor.
The guiding hypothesis of this project is that network-based models of cancer cell signaling together with evolutionary analyses and therapeutic data can identify a set of element within cancer cells that might eventually be exploited through therapeutic combinations to achieve a more durable control of cancer, even in the presence of tumor drug resistance. Specifically, we propose a theoretical framework that integrates so-called discrete dynamic network models and control theory with genomic evolutionary approaches. These models will be informed, tested, and iterated using experimental approaches applied to relevant cancer model systems. Based on its exemplary clinical need, we will focus on BRAF-mutant melanoma (skin cancer) and PIK3CA-mutant, estrogen receptor positive (ER+) breast cancer as initial tumor types in which to test and develop our approach. The final result will be a theoretical and experimentally validated approach that can in principle be generalized across many other therapeutic strategies.
Funded in Collaboration With Stand Up To Cancer (SU2C)
Clinical oncology has entered an era of personalized molecular diagnosis and targeted therapy. This means treatments are tailored to each patient based her tumor’s histopathological and genetic characteristics. Such personalized treatment often involves a combination of multiple active agents to treat one tumor. In estrogen receptor positive (ER+) breast cancers, the three most promising classes of treatments are hormonal therapy, PI3K pathway inhibitors and cell cycle inhibitors.
Although patients derive benefit from such treatment, for most of the advanced ER+ breast cancers, the tumors respond initially but then stop responding, which is called “resistance” to therapy. Unfortunately, this resistance results in death in most cases of advanced breast cancer. Treating these cases requires developing novel therapeutic strategies to overcome the resistance based on an understanding of the mechanisms of resistance.
In this project, we leverage the leading edge technology of high-throughput whole-genome screening to discover mechanisms of resistance to each of three classes of drugs and all of their combinations. We also characterize the identified genes and their function in a variety of breast cancer cell types and mouse models. The knowledge of resistance to treatment obtained through this project will guide our effort to design more effective combinational therapeutics to overcome resistance. Ultimately, this work will be translated to benefit most of the patients with ER+ breast cancers.
Funded in Collaboration with Stand Up To Cancer (SU2C)
Every cancer is unique pointing to the need for personalized medicine. In oncology, a fundamental challenge is to assign the right treatment to every patient due to cancers’ biological complexity and the lack of effective predictive biomarkers. At the Letai lab we developed a functional predictive assay called Dynamic BH3 Profiling to rapidly test different treatments prior to giving them to the patient. It has already been successfully proved as an excellent predictor in different types of cancer, including melanoma. We aim to combine sophisticated genomic analyses with this novel test to improve melanoma treatment, improving patients’ clinical outcome, clinical trials and drug development.
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