Awarded CEP Pilots

2021: Fitzpatrick | Zhao; Renewal: Dinh
2020: Dinh | Wieland; Renewal: Ong
2019: Iyer | Ong;   Renewals: Bayliss/Hill | Rogus-PuliaWitek
2018: Bayliss/Hill  |  Rogus-Pulia
2017: Baschnagel  |  Gitter  |  Morris  |  Russell  |  Witek

2021 awards

Megan Fitzpatrick, MD, headshot

Megan Fitzpatrick, MD

Assistant Professor
Department of Pathology and Laboratory Medicine
Transcriptome and protein expression analysis of head and neck versus vulvar HPV-related and independent squamous lesions
Abstract

Immunotherapy is a cancer therapy designed to stimulate the body’s immune system to better recognize and fight cancer. However, not all patients will respond to immunotherapy and some may even experience potentially life-threatening adverse events. We propose to study the expression of a novel biomarker (stress keratin 17) that could help clinicians better predict which patients will respond to immunotherapy. We will use novel molecular technologies to examine the tumors and stress keratin 17 expression in relation to response to immunotherapy. Our study will support further large-scale validation studies of stress keratin 17 across solid tumors treated with immunotherapy.

Shuang Zhao, MD, PhD Headshot

Shuang (George) Zhao, MD, PhD

Assistant Professor
Department of Human Oncology
Pilot Study to Develop a Novel RNA-seq Liquid Biopsy for H&N Cancer 
Abstract

Precision medicine harnesses sequencing technology to identify what makes a particular tumor “tick”, and in turn, allows physicians to treat patients with drugs that specifically target their tumor. The hope is to match the right treatment with the right patient at the right time. However, a major challenge in head and neck cancer as well as other cancer types is that a piece of the tumor must be extracted from the patient in order for tests to be run. This is not always easy to do, especially in patients with more advanced cancers where surgery is not a good treatment option. A biopsy specifically to get a tumor sample for testing carries risk for the patient for a complication. At the University of Wisconsin Carbone Cancer Center Circulating Biomarker Core, we have developed a new type of “liquid” biopsy which only requires a tube of blood, from which tumor cells are isolated. This makes it possible to routinely collect samples to create and test new research approaches. In our proposal, we seek to apply our unique technology to patients with head and neck cancer in order to create biomarkers for treatment response and resistance. Successful completion of this proposal will provide the data needed to move our work in to clinical trials and improve our ability to tailor our treatments to each individual patient.

2020 awards

Headshot of Huy Dinh, PhD, assistant professor of oncology

Huy Dinh, PhD

Assistant Professor
Department of Oncology
Defining myeloid landscape of head and neck cancer in humans and preclinical mouse model
Abstract

Immunotherapy has revolutionized cancer treatment for late-staged head and neck (HNC) cancer patients. However, the majority of patients still do not respond, which could be improved by understanding the complexity and diversity of immune cells in the head and neck tumor ecosystem. Myeloid cells are white blood cells that play important pro- and anti-tumoral roles in cancer. In this proposal, we aim to identify the unique myeloid cell types that could only be found in the blood and tumor of cancer patients. The anticipated discovery in humans will be further studied using HNC mouse models to define their biological functions. Those cell types will potentially have clinical impacts such as new targets for immunotherapy or biomarkers to predict cancer progression and therapy response. We will employ multi-disciplinary approaches including cancer biology, immunology and bioinformatics for this project and collaborate with HNC clinicians at UW to translate basic findings to clinical relevance. The project will generate pilot data for federal grant applications to contribute to HNC translational research at UW-Madison.

Award Renewed in 2021

Headshot of Aaron Weiland, associate professor, Department of Surgery

Aaron Wieland, MD

Associate Professor
Department of Surgery
Biospecimen Collection of Patients with Squamous Cell Carcinomas of the Head and Neck (HNSCC) At the Time of Surgical Resection for Patient Specific in vitro modeling of Treatment Response
Abstract

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common worldwide cancer with more than 550,000 new diagnoses annually. In the United States, an estimated 53,260 new cases of cancer of the oral cavity and pharynx will be diagnosed, and 10,750 people will die from the disease. Despite ongoing research, survival rates for advanced head and neck cancers have remained essentially unchanged for several decades. Radiation and chemotherapy, the non-surgical standard of care, yields overall and progression free survival rates on the order of 50%. Conversely, approximately 50% of patients will manifest cancer recurrence. We lack the ability to accurately predict which patients are most likely to benefit from additional therapies such as immunotherapy, targeted molecular therapies or multiagent chemotherapy. The inability to stratify patients and guide treatment decisions in HNSCC is a major challenge to clinicians in the field and there is an urgent need for improved HNSCC disease models. Here we propose to collect HNSCC biospecimens at the time of surgical resection to aid in the development of HNSCC patient-specific research models and correlate clinical outcomes to the responses seen in HNSCC research models, such as that developed by the Beebe laboratory. The Beebe lab has developed a microscale 3D model that includes not only the tumor cells, but other important cells in the tumor environment such as white blood cells and connective tissue components.

2019 awards

Gopal Iyer, PhD

Gopal Iyer, PhD

Assistant Professor
Department of Human Oncology
Modulation of Transcriptional Coregulatory Bromodomain and Extraterminal Proteins in Head and Neck Squamous Cell Carcinoma
Abstract

Transcription co-regulators are often implicated in cancer through dysregulated chromatin dependent transcriptional signaling. This project will also explore mechanisms of oncogene and non-oncogenic addiction driven through modulation of BET proteins which would provide a genetic rationale for treatment of head and neck tumors.

Irene Ong, PhD

Irene Ong, PhD

Assistant Professor
Department of Biostatistics and Medical Informatics
Translating PARADIGM Differential Pathway Analysis of Head and Neck Cancer Subtypes to Direct Drug Treatment Strategies
Abstract

The overall goal of this proposal is to leverage the substantial progress from my recent collaboration with Drs. Tony Gitter, Paul Ahlquist, Peng Liu, and David Page in the development of a PARADIGM-based computational framework for integrating diverse molecular data from HNC patients to better understand the mechanism and differences in regulation of proteins between different subtypes of HNC, by utilizing it to uncover potential new drug treatment strategies. We will build on this important foundational analysis to achieve selected, high priority goals, and also briefly highlight other examples to illustrate the flexibility and numerous potential uses of our PARADIGM-based analysis tool.

In particular, using our innovative computational tools and existing diverse molecular data, we will:

  1. identify differentially expressed pathways and drug treatment strategies for HNC subtypes using existing diverse types of molecular data and cell line drug sensitivity data,
  2. identify probable treatment resistance mechanisms by analyzing diverse molecular data from UW HNC patients, SPORE-derived cell lines and patient-derived xenografts (PDXs) and suggest drug treatment strategies, and
  3. computationally prioritize drug targets from the results of Aims 1 and 2 for collaborative experimental analysis on cell lines or PDXs.

Award Renewed in 2020

2018 awards

 Adam Bayliss, PhD

Assistant Professor
Department of Human Oncology

Patrick Hill, PhD

Patrick Hill, PhD

Assistant Professor
Department of Human Oncology
Integration of Machine Learning into a Virtualized Trial Environment for Head and Neck Radiotherapy
Abstract

Using advances in the computational framework of our treatment planning system and basic elements of machine learning, we will characterize and enhance plan optimality in head and neck (HNC) treatment planning. This is the first time basic computational science in artificial intelligence is being applied to radiation therapy treatment planning in a comprehensive manner, from beam modeling, to plan optimization, to treatment delivery and adaptation. Clinical application will be ensured through development of a comprehensive HNC repository of patient radiotherapy data and working with HNC clinicians to create a simplified but extendable characterization of the diagnostic data, plan elements, and outcomes. The result will provide the necessary framework for testing many clinical hypotheses in a large computational environment and will be robust and extendable to other radiotherapy clinics. We will improve several key areas of HNC treatments via machine learning, including:

  • Plan Optimization: Knowledge-based learning algorithms will be applied to existing delivery techniques to provide patient-specific pre-planning optimization objectives. Machine learning will be tested and employed via the artificial intelligence algorithm in development by our vendor collaborators and compared with algorithms we would develop.
  • Robustness and Adaptation: Adapted data sets will be analyzed using data regression techniques to search for predictive adaptive elements. We will investigate using machine learning to enhance current abilities to account for patient movement, automatic incorporation of both on-treatment setup imaging (such as cone-beam and megavoltage CT) and diagnostic imaging (such as PET or MR) in conjunction with the optimization criteria affecting plan deliverability and robustness throughout treatment.
  • Machine Modeling: We will integrate machine learning techniques into the treatment planning system using commissioning data and continued training on future patient-specific quality assurance measurements to autonomously improve the planning model quality. The advent of advanced automation tools enables the creation of a HNC-specific accelerator and beam model that can accommodate site-specific plans to maximize delivery accuracy.

Award Renewed in 2019

Nicole Rogus-Pulia, PhD

Assistant Professor
Department of Medicine
Effects of Radiation Treatment on Oral Microbiota and Salivary Profiles in Patients with Head and Neck Cancer
Abstract

Radiation therapy (RT) commonly used to treat head and neck cancer (HNC) provides locoregional disease control with the goal of preserving vital functions of critical structures. Unfortunately, healthy tissues are still in the radiation field, leading to toxicities that include salivary dysfunction, mucositis and dysphagia. Malnutrition can result from oral discomfort combined with dysphagia. Dysphagia along with declining oral health also results in chronic aspiration of bacteria-laden saliva, liquid and food contributing to aspiration pneumonia. Oral dysbiosis, or disruption of the complex equilibrium of bacterial species in the oral cavity, occurs following RT and contributes to declines in oral health. Salivary dysfunction (decreased quantity and altered composition) along with dysphagia likely accelerates the development of oral dysbiosis post-RT. Approximately 50 percent of patients with HNC experience recurrence that may necessitate repeat RT, which further exacerbates these effects. While these toxicities have been documented following initial and repeated RT, their associations with oral microbial profile shifts post-RT have not been characterized. The purpose of this study is to determine the effects of radiation treatment (initial and repeated) on oral microbial diversity as it relates to salivary profiles, swallowing function, and quality of life outcomes.

We propose a prospective pre-post design study with two cohorts of patients with HNC recruited from the UW Head and Neck Oncology program. The first cohort will consist of 10 patients with a new diagnosis of HNC and planned initial RT. The other cohort will consist of 10 patients with recurrent HNC enrolled in SPORE Project 2 with a plan to receive external beam RT in combination with radiotherapeutic CLR 131. We will complete baseline and three-month post-treatment assessments for both cohorts. Outcomes will include oral microbial diversity, saliva quantity and composition, swallowing safety and biomechanics, oral health, xerostomia, level of oral intake, and quality of life. We will quantify and compare changes in oral microbial diversity post-RT between the two cohorts. We will examine associations among these outcomes and oral microbial diversity. These pilot data will support a NIH R-series application to assess the impact of these factors on pneumonia risk in patients with HNC receiving RT.

Award Renewed in 2019

2017 awards

Andrew Baschnagel, MD

Andrew Baschnagel, MD

Assistant Professor
Department of Human Oncology
The fibroblast growth factor receptors as targets for radiosensitization in head and neck squamous cell carcinomas
Abstract

Locally advanced human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) is typically treated with chemoradiation therapy. This approach results in a five-year overall survival rate of 30 to 50 percent. Identifying strategies and potential targets that enhance the effect of radiation could improve outcomes. Fibroblast growth factor receptors (FGFR)—a family of four transmembrane receptor tyrosine kinases that play a role in tumor progression and invasion—could be one such target. FGFRs are amplified in up to 17 percent of patients with HNSCC, and FGFR protein is overexpressed in up to 70 percent of HNSCC tumor samples. This overexpression is mainly seen in HPV-negative tumors. Our preliminary studies have shown that inhibiting FGFR leads to an enhanced radiation effect in an HNSCC animal model. This project will use in vitro and in vivo experiments to build on these findings.

Award Renewed in 2018

Anthony Gitter, PhD

Anthony Gitter, PhD

Assistant Professor
Department of Biostatistics and Medical Informatics
Mortgridge Institute
Integrative, Multi-dimensional Bioinformatics Analysis of Head and Neck Cancers
Abstract

Head and neck cancer is typically treated with surgery, chemotherapy and/or radiation. But these standard treatments do not fully take into account differences among individual tumors. Understanding these differences could lead to more personalized treatment approaches. Genomic profiling—examining unique mutations within a tumor—has begun to reveal molecular features unique to different types of head and neck cancer. But several challenges must be addressed to realize the potential for meaningful personalized therapies. There is a need for comprehensive, integrative analysis of genetic, epigenetic and other changes in head and neck cancer. There is also a need to analyze interactions among molecules that lead to changes in a cell. In this project, we will develop computational tools to reveal the specific mechanisms that drive individual tumors and larger functional principles and pathway changes across head and neck cancer.

Award Renewed in 2018

Portrait Zachary Morris, MD, PhD

 Zachary Morris, MD, PhD

Assistant Professor
Department of Human Oncology
Development of syngeneic murine head and neck squamous cell carcinoma tumor models for testing in situ tumor vaccination therapeutic approaches
Abstract

In previous research, we explored a novel approach to increase anti-tumor immune response by combining radiation therapy and tumor-specific antibodies. We observed a cooperative anti-tumor interaction between these two established treatments in mouse models of melanoma and neuroblastoma. By combining a T cell checkpoint inhibitor with these two treatments we were able to elicit a potent “in situ” tumor vaccine response—a robust local reaction that drives a systemic anti-tumor immune response. For the current project, we will develop mouse models that will enable us to study the combined effects of radiation therapy, a tumor-specific antibody and T cell checkpoint blockade to treat head and neck squamous cell carcinoma.

Award Renewed in 2018

John Russell, PhD

John Russell, PhD

Associate Scientist
Department of Surgery
The effects of chemoradiation on the microenvironment of tongue muscles
Abstract

Chemoradiation (CRT) to treat head and neck cancer exposes normal tissues to radiation. This can cause significant side effects, including speech and swallowing difficulties. Very little research has been performed on underlying biological changes within muscles of the head and neck following radiation. Through this project, we hope to quantify how different dose fractionation schedules affect CRT-induced damage to tongue muscles. We also aim to determine the effect of chemoradiation on structural and functional changes in tongue muscles. Understanding the underlying causes for the swallowing abnormalities seen in individuals who have received CRT could enable better treatment.

Matthew Witek, MD

Matthew Witek, MD

Assistant Professor
Department of Human Oncology
PET-MRI assessment of early tumor response to predict outcomes of HPV-positive oropharynx cancer patients
Abstract

Historically, five-year overall survival of patients with locally advanced head and neck squamous cell carcinomas (HNSCC) has been 25 to 50 percent. This has limited the ability to study treatment side effects. However, patients with human papillomavirus (HPV)-induced oropharyngeal squamous cell carcinomas (OPSCC) have a relatively high overall survival rate (70 to 90 percent at three years). This makes them a favorable group of patients in which to study treatment-related side effects. In this project, we will use positron emission tomography-magnetic resonance imaging (PET-MRI) to monitor primary OPSCC tumor response during treatment following two weeks of chemoradiotherapy. Through this project, we hope to be able to predict outcomes. This could enable radiation dose de-escalation to reduce side effects while maintaining favorable overall response to treatment.

Project Extended in 2018

Award Renewed in 2019