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.
Hematopoietic stem cells (HSCs) are responsible for the lifelong regeneration of the blood and bone marrow. During the lifetime of an individual, genetic mutations can occur in HSCs that slightly alter their properties, potentially leading to diseases of excessive or deficient production of blood cells. When myeloid cells are chronically affected, these conditions fall into two main categories called myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS). These disorders are the most common blood cancers in adults with ~20,000 new cases diagnosed each year in the United States. While these diseases themselves present significant problems such as excessive bleeding and more susceptibility to infections, in a significant number of these patients the disease transforms to a leukemia that is much more difficult to treat and rapidly proves fatal (typically about five months). It is important to identify the genetic processes associated with progression of MDS and MPN to leukemia to improve treatment of these patients. I believe we have identified a new pathway that facilitates this process by identifying a gene that is genetically mutated specifically in the leukemia phase of the disease, but not the preceding MPN phase. The goals of this work are to develop new models to understand these processes, and to identify factors to improve the treatment outcomes of such patients. As there are no effective therapies for these patients that progress to leukemia, any findings that improve the diagnosis and treatment of these patients would represent a significant advance in this field.
Triple negative breast cancer (TNBC) is aggressive and has a poor prognosis. Currently, chemotherapy is the only treatment option. Therefore there is unmet need to identify novel therapeutic targets for TNBC. Acquired resistance to targeted therapy, a newer treatment type with drugs targeting specific molecules necessary for tumor growth, poses another major clinical problem. We have recently identified a major mechanism that TNBC cells utilize to promote tumor growth. This proposal aims at deciphering this mechanism in cancer growth and drug resistance, as well as discovering novel therapeutic targets for TNBC.
Akt1, Akt2 and Akt3 are a “family” of proteins with both overlapping and unique functions. Akt plays critical roles in tumor growth, and a number of drugs targeting Akt are being tested in clinical trials. Our recent findings indicate that Akt3 has an increased expression in ~30% of TNBC. Importantly, Akt3, but not Akt1/2, is critical for regulating TNBC growth. Moreover, Akt3 is implicated in drug resistance to Akt inhibitors. We propose that Akt3 regulates tumor growth and resistance by activating specific downstream targets and upregulating receptors on cell surface. To identify novel Akt3 targets, we will use a discovery-based proteomics approach. For drug resistance study, we will analyze Akt3 signaling in tumor samples, and test if certain receptor inhibitors effectively eliminate resistant cells. In the short term, our results will provide rational combination treatment strategy to combat drug resistant breast tumors. In the long term, we anticipate developing effective therapeutics targeting Akt3 or its substrates to treat TNBC.
Prostate cancer is the second leading cause of cancer-related death in American men, resulting in 29,480 fatalities last year. Death from prostate cancer most frequently occurs following the development of resistance to first- or second-line androgen deprivation therapy (ADT). As such, there is a critical need to discover early drivers of ADT resistance to help guide selection of patients for earlier intensification of therapy.
The majority of cancer biomarker research has focused, to date, on protein-coding genes, which are pieces of DNA that are converted to RNA and then converted to protein. Our team instead focuses on investigating long noncoding RNAs (lncRNAs), which are pieces of DNA that are converted to RNA but are not further converted to protein. These lncRNAs, which function as RNAs instead of proteins, represent an underexplored, but crucial, area of cancer biology. Our team recently identified over 45,000 novel lncRNAs, and determined that several lncRNAs, including one named SChLAP1, were better indicators of disease progression than conventional protein-coding genes.
Based on our initial findings, we hypothesize that lncRNAs serve as important mediators of treatment resistance in prostate cancer. The goals of this application are: 1) to investigate the mechanism by which our top candidate lncRNA, SChLAP1, promotes ADT resistance and 2) to determine if SChLAP1 and other lncRNAs can serve as predictive biomarkers to guide therapy selection in patients with aggressive prostate cancer, using tumor samples from a phase III clinical trial.
