Radiation Oncology and Imaging
Program Overview
The Radiation Oncology and Imaging Program (ROIP) is a comprehensive program that brings together radiation biologists, imaging scientists, medical physicists, bioengineers, radiation oncologists and radiologists. The mission of the program is to foster research which integrates clinical, basic science and engineering approaches:
- to increase the local control of tumors by radiation therapy while minimizing side effects, and
- to develop and evaluate novel imaging approaches and imaging biomarkers for localized and disseminated cancer.
The program will utilize rigorous and, ideally, quantitative approaches to facilitate and enhance the following:
- Detection, diagnosis and biologic staging of cancer to guide treatment strategies
- Early response assessment and prediction of long-term clinical outcome to allow for adaptive treatment
- Assess the effects of treatment on the function of normal tissue and organs
- Understand mechanisms of tumor response and normal tissue injury from radiation therapy
- Train future physicians and scientists with diverse, complementary expertise who will serve as the next generation of leaders in cancer imaging and therapy.
Specific Aims
The Specific Aims of the ROIP are to foster research interactions that stimulate the integration of basic science, bioengineering, and clinical trials:
- to increase the local control of tumors by radiation therapy while minimizing side effects; and
- to develop and evaluate novel imaging methods and imaging biomarkers for localized and disseminated cancer.
Program Themes
To accomplish these goals, the Themes of the Program are:
- to understand the mechanisms of tumor and normal tissue response to radiation; and
- to develop and apply imaging methods for the detection and staging of cancer and for image-guided therapy and response assessment.
Focus Groups:
Theme 1: The program will utilize a multi-disciplinary approach to understand the mechanisms of tumor response to radiation therapy and normal tissue injury from radiation.
Focus Area 1: Cells, Tissues and Tumor Response to Radiation
Focus Area 2: Clinical Trials of Radiation Therapy
Theme 2: Quantitative approaches to imaging methods for detection and staging of cancer, for image-guided therapy, and for early and late response assessment
Focus Area 1: Pre-Clinical Imaging
Focus Area 2: Clinical Imaging to Detect, Stage and Treat Cancer
Leadership Bio
David Kirsch, MD, PhD, serves as leader of the Radiation Oncology and Imaging Program. He is the Barbara Levine University Professor and a Professor in the Departments of Radiation Oncology and Pharmacology & Cancer Biology. Dr. Kirsch is a practicing radiation oncologist at Duke University Medical Center. He is the vice chair for basic and translational research in Radiation Oncology. A nationally-recognized expert in the care of patients with bone and soft tissue sarcomas, he currently serves as the chair of the Developmental Therapeutics Committee for the Sarcoma Alliance for Research through Collaboration (SARC). The Kirsch laboratory utilizes innovative genetically engineered mouse models to study mechanisms of tumor response to radiation, radiation-induced cancer, and normal tissue injury from radiation. In addition, the laboratory utilizes these mouse models to study sarcoma metastasis to the lung and intra-operative molecular imaging. Dr. Kirsch's research has been recognized by the National Cancer Institute for outstanding productivity and exceptional accomplishment with an R35 Outstanding Investigator Award.
Dr. Kirsch held an IND for a novel protease-activated fluorescent imaging agent, which was successfully tested in a phase I clinical trial at Duke. He will be the PI of a multi-institutional randomized clinical trial testing the combination of the immune check point inhibitor pembrolizumab and radiation therapy for high-risk extremity soft tissue sarcoma.
Nimmi Ramanujam, PhD, is the Robert W. Carr Professor of Biomedical Engineering, a faculty member in the Global Health Institute, Department of Pharmacology and Cell Biology at Duke University. Dr. Ramanujam is an innovator, educator, and entrepreneur. Her mission is to develop technology that will have a wide-reaching impact in women’s health. She directs the Center for Global Women’s Health Technologies at Duke where she empowers trainees at Duke and beyond to create impactful solutions to improve the lives of women and girls globally. Dr. Ramanujam’s research focuses on breast and cervical cancer. Her goals are to design innovations that enable complex referral services often reserved for hospitals to be accessible at the community/primary care level, develop technologies to see and treat women with early stage disease in one visit and to develop tools that will make cancer treatment more effective and efficient.
Manisha Palta, MD, has recently joined the leadership team of ROIP. As vice chair for clinical research in the Department of Radiation Oncology, she leads innovative clinical trials and oversees the clinical research infrastructure in Radiation Oncology.
Centers and Labs
The Kirsch Lab: The Kirsch Lab uses sophisticated genetically engineered mouse models, cellular and molecular biology and biochemistry to study cancer and radiation biology. Our research ranges from fundamental basic questions into the mechanisms by which tumor suppressor genes prevent cancer to translational projects that focus on mechanisms of metastasis, tumor response to radiation therapy and normal tissue injury from radiation. In a collaborative environment, we work together to make discoveries and strive to translate our research into clinical trials for patients with cancer.
The Ramanujam Lab: The Center for Global Women's Health Technologies focuses its work in women's health on translational and laboratory research of relevance to breast and cervical cancer. Use the buttons below to learn more about our work in cervical pre-cancer imaging, breast cancer imaging, and cancer ablation.
The Mowery Lab: The Mowery Lab utilizes genetically engineered mouse models, patient-derived samples and molecular biology techniques to study head and neck cancer development and progression, as well as the interplay between radiation therapy and the immune system in sarcoma and head and neck cancer. We have a particular interest in understanding the molecular underpinnings of radiation resistance in head and neck squamous cell carcinoma and immune dysregulation in the tumor microenvironment. Our overarching goal is to translate scientific discoveries from the bench to the bedside to advance the care and improve the quality of life for patients with cancer.
The Li Lab: Research in the Li lab is roughly divided into the following three areas: (1) Molecular mechanisms of tumor response to therapy and approaches to enhance treatment efficacy, with special emphasis on skin cancer such as melanoma and squamous cell carcinoma where current treatment outcomes are dismal; (2) Stem cell regenerative medicine, we will conduct research to investigate novel mechanisms of stem cell biology so that knowledge gained can be translated into regenerative medicine; (3) Mechanisms of carcinogenesis, with emphasis on skin cancers, so that better strategies could be devised to prevent and treat these cancers
Scientific Highlights
This study analyzes the incidence of opioid-associated deaths in cancer survivors vs the general population in the US from 2006 through 2016 using National Center for Health Statistics death certificate data.
Pilocytic astrocytoma (PA), the most common childhood brain tumor, is a low-grade glioma with a single driver BRAF rearrangement. Here, we perform scRNAseq in six PAs using methods that enabled detection of the rearrangement.
Biocompatible gold nanoparticles designed to absorb light at wavelengths of high tissue transparency have been of particular interest for biomedical applications. The ability of such nanoparticles to convert absorbed near-infrared light to heat and induce highly localized hyperthermia has been shown to be highly effective for photothermal cancer therapy, resulting in cell death and tumor remission in a multitude of preclinical animal models. Here we report the initial results of a clinical trial in which laser-excited gold-silica nanoshells (GSNs) were used in combination with magnetic resonance-ultrasound fusion imaging to focally ablate low-intermediate-grade tumors within the prostate.
Diffuse intrinsic pontine glioma (DIPG) kills more children than any other type of brain tumor. Despite clinical trials testing many chemotherapeutic agents, palliative radiotherapy remains the standard treatment. Here, we utilized Cre/loxP technology to show that deleting Ataxia telangiectasia mutated (Atm) in primary mouse models of DIPG can enhance tumor radiosensitivity.
Novel approaches are needed to boost the efficacy of immune checkpoint blockade (ICB) therapy. Ataxia telangiectasia mutated (ATM) protein plays a central role in sensing DNA double-stranded breaks (DSBs) and coordinating their repair. Recent data indicated that ATM might be a promising target to enhance ICB therapy.
Despite its success in achieving the long-term survival of 10-30% of treated individuals, immune therapy is still ineffective for most patients with cancer1,2. Many efforts are therefore underway to identify new approaches that enhance such immune 'checkpoint' therapy3-5 (so called because its aim is to block proteins that inhibit checkpoint signalling pathways in T cells, thereby freeing those immune cells to target cancer cells). Here we show that inhibiting PCSK9-a key protein in the regulation of cholesterol metabolism6-8-can boost the response of tumours to immune checkpoint therapy, through a mechanism that is independent of PCSK9's cholesterol-regulating functions.
Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited prospective studies investigating the clinical impact of ML in health care. The objective of this study was to determine whether ML can identify high-risk patients and direct mandatory twice-weekly clinical evaluation to reduce acute care visits during treatment.
