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Virotherapy for Malignant Gliomas
Award Name:ASPIRE Award
Organization:Malignant gliomas are deadly brain tumors that resist almost all anti-cancer therapies. Some gliomas harbor harmful genetic mutations that make the tumors invisible to the immune cells that normally provide a first line of defense against cancer. The Amankulor lab at the University of Pittsburgh Medical Center is researching a novel therapy that uses viruses engineered to destroy gliomas in two ways: by directly killing infected glioma cells, and by promoting the recognition and destruction of glioma cells by the immune system, all while leaving healthy brain cells intact. If successful, this research could one day lead to a targeted anti-cancer treatment for malignant gliomas.
Project:Investigator: Nduka Amankulor, MD, University of Pittsburgh Medical Center
Investigating A New Drug Target in Pancreatic Ductal Adenocarcinoma (PDAC)
Organization:There is a dearth of effective therapies for pancreatic cancer, which is expected to be the second leading cause of cancer deaths by 2030. Researchers in the Cantley lab at Weill Cornell School of Medicine and the Lyssiotis lab at the University of Michigan are exploring whether inhibition of a metabolic enzyme can suppress the growth of a class of genetically vulnerable pancreatic tumors without harming healthy tissue. This research may lead to the development of targeted small-molecule drugs for pancreatic cancer and other cancers that possess this same genetic sensitivity to metabolic inhibition.
Project:Investigators: Lewis C. Cantley, PhD, Weill Cornell School of Medicine; Costas A. Lyssiotis, PhD, University of Michigan
Untangling the Connection Between Stress and Metastatic Cancer
Organization:Cancer cells that spread beyond the original tumor can remain dormant for many years before overriding the body's natural defenses to proliferate in other tissues. Stress has long been suspected to stimulate the growth of dormant cancer cells, leading to the formation of new tumors in different parts of the body (a process known as metastasis). Researchers in the Egeblad lab at Cold Spring Harbor Laboratory are now investigating the stress response and its effects on metastasis in a mouse model of cancer. They expect this research will lead to drugs that can prevent metastasis by interfering with the stress response or stimulating the immune system to keep dormant tumor cells in check.
Project:Investigator: Mikala Egeblad, PhD, Cold Spring Harbor Laboratory
Priming Cancer Cells for Detection by the Immune System
Organization:Our immune systems are designed to flag and destroy potential threats, including pathogenic bacteria and viruses, as well as cancerous tumors that form when the body's own cells accumulate mutations that cause uncontrolled growth. Many cancers, however, develop the ability to evade detection by the immune system. Researchers in the Shokat lab at UCSF aim to discover drug-like small molecules that can stimulate immune cells to more efficiently recognize tumor cells with mutant variants of KRAS, a gene that drives many difficult-to-treat cancers. They hope that this strategy will one day lead to drugs that unmask tumor cells with this and other common mutations and allow the immune system to eliminate them.
Project:Investigator: Kevan Shokat, PhD, UCSF
Using Smartphones and Wearables for Early Detection of Central Nervous System (CNS) Tumors
Organization:For the 80,000 patients diagnosed with brain and central nervous system cancers each year, most of the provision of care rests on subjective, discontinuous data collected at discrete time intervals. To address this limitation, a coalition of researchers led by Dr. Stephen Friend of 4YouandMe will test the feasibility of using smart devices and health tracking apps to detect symptoms in brain cancer patients. They will conduct an observational study of 100 high-risk patients and use the wealth of data collected to develop a model of disease progression. Using each patient's own smartphone and small wearable devices in conjunction with health apps that collect, compile, and transmit data directly to clinicians, the coalition will be able to semi-continuously monitor changes in everything from gait to mental health to sleep. They expect analysis of the data will reveal patterns of symptoms that are missed by traditional patient monitoring. These insights could enable doctors to detect tumors early, before symptoms become noticeably severe, and to closely monitor and adjust treatments in patients with advanced disease.
Project:Investigators: Stephen Friend, MD, PhD, 4YouandMe (Principal); Anna Goldenberg, PhD, The Hospital for Sick Children (SickKids) Research Institute / University of Toronto; Marzyeh Ghassemi, PhD, Vector Institute/University of Toronto; Luca Foschini, PhD, Evidation; et al
Using Blood Biomarkers to Aid App-Based Cancer Monitoring
Organization:The data collected by smartphones and wearables will be even more powerful when combined with information about patients' molecular markers of cancer. Toward this goal, researchers in the Heath lab at the Institute for Systems Biology are collecting and analyzing in-depth measurements of blood biomarkers in the patients monitored for symptom detection using smart technologies by Stephen Friend and colleagues. Working together, both teams expect that tracking the trajectory of these physical markers will allow them to calibrate the output from devices and lead to algorithms that optimally connect both types of data for early screening and surveillance of high-risk patients.
Project:Investigator: James Heath, PhD, Institute for Systems Biology
Using Artificial Intelligence to Predict Interactions between Immune and Tumor Cells
Organization:Understanding how immune cells and tumor cells will interact is critically important for forecasting patient outcomes for immunotherapy. The Baras lab at Johns Hopkins University is designing artificial intelligence-based algorithms that can identify how mutations are most likely to be presented by tumor cells given a patient's unique genetic make-up and predict how well immune cells will be able to detect them. These algorithms may lead to improved prognoses of individual patients and a better understanding of how each patient will respond to treatment.
Project:Investigator: Alexander Baras, MD, PhD, Johns Hopkins University
Artificial Intelligence Assisted MRI Screening for Pediatric Cancers
Organization:Whole body magnetic resonance imaging (wbMRI) is an important tool for screening children with a genetic predisposition for cancer. However, the images can be difficult to interpret, and early stage cancers are often missed. The Goldenberg lab at the SickKids Research Institute in Toronto, in collaboration with researchers at the University of Pennsylvania and Children's Hospital of Pennsylvania, is developing an AI-based tool that improves wbMRI screening for at-risk children and overcomes current limitations to using AI in the pediatric cancer setting. They expect that this tool will enable more sensitive early detection of pediatric cancers at medical institutions worldwide.
Project:Investigators: Anna Goldenberg, PhD, SickKids Research Institute/University of Toronto (Principal); Andrea Doria, MD, Hospital for Sick Children; Casey S. Greene, PhD, University of Pennsylvania; L. J. States, MD, Children's Hospital of Pennsylvania
Detailed, Automated 3D Imaging of Pancreatic Cancers and Precancers
Organization:Pancreatic cancer is an aggressive disease that readily spreads to other organs, particularly the liver. Researchers in the Fereidouni and Levenson labs at UC Davis have teamed up with leading experts in pancreatic cancer at Johns Hopkins University to develop a fully automated 3D microscopy technique that can be used to image pancreatic tumors and nearby blood vessels, enabling closer study of the invasion of small veins into tumors. They expect that this will lead to a better understanding of the poor prognosis for pancreatic cancer patients and provide cancer researchers with a precise and affordable tool to study tumor anatomy.
Project:Investigators: Richard Levenson, MD, University of California, Davis (Co-Principal); Farzad Fereidouni, PhD, University of California, Davis (Co-Principal); Ralph Hruban, MD, Johns Hopkins University; Denis Wirtz, PhD, Johns Hopkins University; Laura Wood, MD, PhD, Johns Hopkins University; Pei-Hsun Wu, PhD, Johns Hopkins University
Detecting Novel Cancer Mutations That Change the Genome's 3D Structure
Organization:Mutations in the region of the genome that are important for the 3D structure of chromosomes are likely critical for cancer growth, but nevertheless poorly understood. Researchers in the Ma lab at Carnegie Mellon University and the Van Allen lab at the Dana Farber Cancer Institute are developing machine learning algorithms trained to detect mutations that are likely to affect the genome's 3D structure. This technology will pave the way to a new understanding of the influence of these mutations on tumor proliferation, clinical outcomes, and patient responses to existing and emerging therapeutics.
Project:Investigators: Jian Ma, PhD, Carnegie Mellon University (Principal); Eliezer Van Allen, MD, and Felix Dietlein, MD, PhD, Dana-Farber Cancer Institute
New Imaging Methods for Identifying Structural Differences in Cancer Cells
Organization:Tumor heterogeneity presents a major challenge in predicting outcomes and appropriate therapies for cancer patients. Different tumor cells may have distinct physical characteristics. Electron cryotomography (ECT) has unrivaled power to produce 3D images of cells and tissues at unprecedented spatial resolution. Researchers at Carnegie Mellon University led by Robert F. Murphy and Min Xu and at the University of Pennsylvania led by Yi-Wei Chang are developing machine learning methods that can be used in combination with ECT to distinguish differences between cancer cell types and determine whether those differences can be correlated with disease progression and treatment outcomes.
Project:Investigators: Robert F. Murphy, PhD, Carnegie Mellon University (Principal); Min Xu, PhD, Carnegie Mellon University; Yi-Wei Chang, PhD, University of Pennsylvania
Advanced DNA Sequencing for Uncovering Novel Inheritable Carcinogenic Mutations
Organization:Many heritable cancers have no known genetic causes. This is in part because standard DNA sequencing technologies do not normally detect an entire class of mutations called structural variations (SVs). Researchers in the Schatz lab at Johns Hopkins University and the Van Allen lab at the Dana-Farber Cancer Institute have developed a genetic sequencing technology specifically designed to detect SVs and are using it to find harmful SVs in a cohort of families that have high rates of unexplained cancer. They expect this will lead to an immediate improvement in screening and diagnostics for heritable cancers, allowing doctors to intervene earlier by identifying those at heightened risk for disease.
Project:Investigators: Michael Schatz, PhD, Johns Hopkins University (Principal); Eliezer Van Allen, MD, Dana-Farber Cancer Institute
Unraveling the Mechanistic Link Between Chronic Inflammation, Chromosome Instability and Cancer
Organization:Patients with chronic inflammation from conditions such as inflammatory bowel disease are at increased risk for developing a variety of cancers including colorectal cancer (CRC). Utilizing advanced model systems such as 3-dimensional organoids, a team at Johns Hopkins University is aiming to dissect the process through which chronic inflammation in the colon promotes CRC development. These mechanistic insights will be critical for enabling early medical intervention and ultimately prevention of chronic inflammatory disease-associated cancers.
Project:Investigators: Rong Li, PhD (Principal Investigator); Harry Benjamin Larman, PhD; and Tatianna Larman, MD, Johns Hopkins University School of Medicine.
Machine Learning to Predict the Progression of Cancer and Treatment Effectiveness
Organization:Researchers at the Massachusetts Institute of Technology are developing machine learning and artificial intelligence algorithms that could accurately predict a cancer patient's disease progression and the likelihood that a particular treatment would be effective. The team aims to develop methods that apply broadly across cancers and that will enable personalization a patient's treatment.
Project:Investigator: David Sontag, PhD, Massachusetts Institute of Technology
Catalyzing Precision Medicine Through Prospective, High-Throughput Characterization of Cancer Variants
Organization:While precision medicine holds great promise for cancer patients, the impact to date has been limited to patients for whom the disease- and treatment-relevant functions of their specific tumor mutations are known. Researchers at the Broad Institute and Dana-Farber Cancer Institute aim to address that limitation by leveraging newly developed technologies to perform robust gene variant characterization efforts and establish a foundational data set that can enable precision medicine for all patients, even those with rare mutations.
Project:Investigators: William C. Hahn, MD, PhD (Principal Investigator), Broad Institute and Dana-Farber Cancer Institute; James Neal, PhD, Broad Institute
A Systems Biology Approach to the Tumor Microenvironment Using Zebrafish
Organization:A group at Memorial Sloan Kettering Cancer Center is using zebrafish to visualize cancer metastasis. Toward this goal, they are analyzing human tumors to identify cell types in the metastatic ecosystem, recreating this ecosystem in a multiplexed fluorescent zebrafish model, and perturbing the model with CRISPR technology to interrogate the interactions between cancer and somatic cells. This project will lead to novel insights into cancer biology and potentially uncover new cancer drug targets.
Project:Investigator: Richard White, MD, PhD, Memorial Sloan Kettering Cancer Center
Chemoproteomics-Enabled Covalent Ligand Discovery Platforms for Accessing Novel Druggable Modalities
Organization:Developing drugs that bind to many of the proteins known to play a role in cancer has proven to be an extraordinarily difficult challenge. Researchers at the University of California, Berkeley have identified candidate drug binding sites for a number of these proteins using novel chemical biology profiling techniques. The team is now building on this knowledge to screen for molecules that can bind these sites and serve as the starting point for the creation of new drugs to treat cancer.
Project:Investigator: Daniel Nomura, PhD, University of California, Berkeley
Delineating How Obesity Induces Chemoresistance in B-Acute Lymphoblastic Leukemia Cells
Organization:Researchers at Emory University School of Medicine believe factors secreted by fat cells in obese patients with leukemia could be hindering chemotherapy. Their goal is to determine which factors are cancer-protective and how they could be targeted to improve cancer therapy outcomes in obese cancer patients.
Project:Investigators: Curtis Henry, PhD (Principal Investigator) and Joshua Chandler, PhD, Emory University
Enhancing Cancer Immunotherapy through Pharmacological Inhibition of ER Stress Sensors
Organization:Some cancers may evade control by the patient's immune system through induction of severe Endoplasmic Reticulum (ER) stress in the infiltrating immune cells. A team at Weill Cornell Medicine is determining exactly how this process occurs and whether blocking the signaling pathways of the ER stress response could improve the effectiveness of cancer immunotherapies.
Project:Investigator: Juan Cubillos-Ruiz, PhD, Weill Cornell Medicine
Harnessing Innovations in Artificial Intelligence to Improve Breast Cancer Detection
Organization:Researchers at Johns Hopkins School of Medicine are developing new artificial intelligence technologies and methods for image integration to improve the sensitivity and specificity of breast cancer screening. These tools could significantly improve early breast cancer detection as well as reduce false alarms.
Project:Investigators: Lisa Mullen, MD (Principal Investigator); Susan Harvey, MD; and David Porter, PhD, Johns Hopkins University School of Medicine
Intracellular Paired Agent Imaging (iPAI) Enables Personalized Therapy Selection for Cancer Patients
Organization:Monitoring targeted drug interactions and the resultant intracellular signaling cascades is difficult and currently no methods exist for simultaneous measurement in live cells and tissues. A collaborative effort being led by the Oregon Health & Science University is developing a dynamic, fluorescence-based live cell imaging system platform that will ultimately enable use of a patient's own tissues to predict response to treatment. This method could serve as a highly effective platform for personalized medicine.
Project:Investigators: Summer Gibbs, PhD (Principal Investigator), Oregon Health & Science University; Kimberley Samkoe, PhD, Dartmouth College; and Kenneth Tichauer, PhD, Illinois Institute of Technology
Probing the Interrelationship of Microvascular Structural Adaptation, Vessel Co-Option, and Resistance to Anti-Angiogenesis Therapy in Microengineered Vessels
Organization:A team at The Ohio State University is creating a microfluidic model for visualization of cancer cells as they co-opt blood vessels in their environment, enabling them to survive without the need for new blood vessel formation. They also intend to determine how anti-angiogenesis therapies, which inhibit new blood vessel formation, affect this co-option process. Their work could lead to new targets that block tumor access to existing blood supplies and improve the effectiveness of anti-angiogenesis drugs.
Project:Investigator: Jonathan Song, PhD, The Ohio State University
Rational Design of Novel Combination Immunotherapies: Enhancing the Cytotoxic Activity of Chimeric Antigen Receptor T Cells
Organization:The adoptive cell transfer cancer treatment known as CAR T-cell therapy has achieved promising but varied success thus far in the clinic and is particularly poor at treating solid tumors. A team at the University of Pennsylvania is using high throughput screening technologies to find small molecule drugs that could be combined with CAR T cells to improve their tumor-killing properties.
Project:Investigators: Marco Ruella, MD (Principal Investigator); Sara Cherry, PhD; and Igor Brodsky, PhD, University of Pennsylvania
Short-Term 3D-Printing-Based Cultures of Metastatic Breast Cancer for Tailored Therapy Selection
Organization:The current guidelines for treatment selection in metastatic breast cancer do not help physicians predict the optimal therapeutic option for any specific patient. A team at the Netherlands Cancer Institute (NKI) is developing a 3D-printed matrix on which to grow metastatic cancer cells directly from patients that will help determine the response of those cells to treatments ex vivo. These efforts will lead to platforms for selecting therapies with a higher probability of success within days of sampling metastatic cells from patient tumors.
Project:Investigators: Wilbert Zwart, PhD (Principal Investigator), Netherlands Cancer Institute and Luis Solorio, PhD, Purdue University
Target Class Approach to Develop DUB Inhibitors
Organization:Investigators at the Dana-Farber Cancer Institute are taking a chemical biology approach to characterize covalent small molecule probes that target deubiquitinases (DUBs), enzymes that regulate many other proteins in a cell. Although inhibiting DUBs could provide a specific way to therapeutically modulate proteins in cancer, there are currently no approved drugs for this class of proteins.
Project:Investigators: Sara Buhrlage, PhD (Principal Investigator) and Jarrod Marto, PhD, Dana-Farber Cancer Institute
Targeted Third-Generation Sequencing of Methylated Circulating Tumor DNA to Enable Early Cancer Detection
Organization:A team at the University of Utah is optimizing the use of third-generation sequencing technology to detect cancer-specific methylation of tumor DNA in the blood. These efforts could lead to the development of more effective, non-invasive, and affordable diagnostics for early detection of cancer. Such diagnostics would allow physicians to intercept a patient's cancer at an earlier stage with better options for successful treatment.
Project:Investigators: Katherine Varley, PhD, University of Utah
Prospective Identification of Neoantigen-Specific T-Cell Receptors Using an Optimized Model System
Organization:A team at New York University aims to broaden the number of cancer patients who can benefit from adoptive cell transfer (ACT) immunotherapy. They are building an in vivo platform for the identification of T-cell receptors that recognize a patient's unique tumor neoantigens. This approach will provide the needed tools to engineer optimized T cells for personalized ACT immunotherapy.
Project:Investigators: Michelle Krogsgaard, Jef Boeke, and Jeffrey Weber, New York University School of Medicine
Ultra-Sensitive Detection of Circulating Tumor DNA through Genome-Wide Integration
Organization:Early-stage diagnosis and residual disease detection from standard blood samples would revolutionize cancer patient treatment and prognosis. Current screening methods are not sensitive enough to accurately determine the presence of cancer in patients with early-stage disease. A research team at Weill Cornell Medicine is developing a sensitive screening system that looks across the whole genome rather than at a limited number of genes for mutated DNA in blood plasma.
Project:Investigators: Dan Landau and Asaf Zviran, Weill Cornell Medical College
Abolishing Brachyury Function through Degradation
Award Name:Therapeutic Innovation Award, in partnership with Chordoma Foundation
Organization:Development of a PROteolysis TArgeting Chimera (PROTAC)-based drug candidate to degrade intracellular brachyury and abrogate its oncogenic function
Project:Investigators: Craig Crews, Yale University
Structure-Guided Drug Discovery for Brachyury Inhibitors
Organization:A cutting-edge structural biology approach to identify candidate small molecules that inhibit the function of the transcription factor brachyury
Project:Investigators: Opher Gileadi (University of Oxford), David Drewry (University of North Carolina), & Charles Lin (Baylor College of Medicine)
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