Radiation Oncology-Biology Integration Network (ROBIN)
Radiation therapy (RT) can dynamically induce molecular targets in tumors that are not seen at diagnosis and change them over the course of treatment. ROBIN will establish a collaborative, interdisciplinary effort to apply new knowledge about this complex biology to develop better therapies for people with cancer.
Radiation Oncology Background
History
- Since its inception as a cancer treatment more than100 years ago, radiation oncologists have relied on established methods to optimize RT for people with cancer. These methods involve multiple forms of radiation driven by physics and advanced engineering, as well as biological and modelling-focused approaches built on mathematical descriptions of tumor cells and normal tissue.
- The field of radiation oncology has embraced recently developed tools in genomics, molecular precision medicine, and big data, which have shown early promise to more accurately categorize patients for best initial treatment approach.
- The standard of care is to collect data from tumors at diagnosis or relapse, but these time points may not accurately capture how tumors adapt, resist, respond to, or are targeted by, treatment in the context of a patient’s full course of therapy.
Unmet Needs
- Approximately 50% of people with cancer receive RT as a component of their treatment; however, most of the foundational radiobiology research was conducted either in the pre-molecular or “omics” era and provides limited data on the biology of cancer and normal tissue during RT with or without other agents.
- Foundational, molecular research needs to characterize the biological basis of patient responses and outcomes to radiation (alone and in combination with systemic treatments), to enhance its ability to eradicate cancer cells and to lessen toxicity to normal tissues.
- The NCI Clinical Trials and Translational Research Advisory Committee (CTAC) Report on Radiation Oncology noted that a strong radiation research capacity and workforce to conduct translational and collaborative research are required to advance the field.
ROBIN Purpose
The ROBIN Notices of Funding Opportunity (RFA-CA-21-040; RFA-CA-22-046) invited investigators to:
- Apply new biological knowledge and methods to study standard of care RT and RT in combination with systemic drugs and other agents before, during, and after therapy.
- Establish the foundational biology in tumor and normal tissue based on the most modern biological methods to capture the full landscape of the “omics” of RT, because understanding the tumor’s biology over the course of treatment is important to determine if drug targets are unstable.
- Address hypothesis-based translational research knowledge gaps on the biological basis of the dynamic molecular responses in cancer patients who undergo RT. Data will be collected from tumors and normal surrounding tissue, before, during, and after treatment, so that the foundation data for standard therapy can further optimize a patient’s treatment.
ROBIN Goals
Centers will provide highly focused research capabilities that will:
- Test translational hypotheses that advance the understanding of mechanistic interactions, target dynamics, and biologic consequences of RT before, during, and after the course of RT with and without combinations of other agents.
- Collect longitudinally and spatially annotated research biospecimens prior to, during, and after RT to elucidate:
- toxicity and resistance signals that are more likely to develop early during treatment and could be preventable
- the development of new anti-cancer drug targets induced by the RT and any therapy-associated changes
- if a patient’s therapeutic strategy based on initial biological testing remains optimal for the patient
- Stimulate the development of radiation and combined modality trial concepts to be further developed in focused grants (R01s), program project grants (P01s), part of translational large scale grants (SPORE grants), or through the NCI’s Experimental Therapeutics Clinical Trials Network or NCI’s National Clinical Trials Network.
- Facilitate the development of a multidisciplinary workforce.
- Engage stakeholders with expertise to conduct studies in translational and preclinical research to inform clinical radiation oncology studies and leverage data science and informatics approaches.
ROBIN Members and Structure
ROBIN Center | Institution | PI or Point of Contact* | Histologies |
---|---|---|---|
Radiation Oncology-Biology Integration Network on Oligometastasis (ROBIN OligoMET) Center | University of Maryland Thomas Jefferson University | Phuoc Tran* Nicole Simone | Prostate |
Dynamics of Immune Response in Irradiated Rectal Cancer Center (ROBIN ImmunoRad Center) | Cornell University (Weill Medical College) Memorial Sloan Kettering Cancer Center University of Chicago | Silvia Formenti*
Joseph Deasy
Ralph Weichselbaum | Rectum |
Genomic and Microenvironmental Determinants, Temporal Dynamics, and Treatment Efficacy of Radiation-Based Combination Therapies Center (ROBIN Gen-Rad Center) | Cleveland Clinic Foundation Emory University | Timothy Chan*
David Yu | Head and Neck
Bladder |
MicroEnvironment and Tumor Effects Of Radiotherapy (METEOR) | Washington University | Julie Schwarz* Clifford Robinson | Pancreas Cervix |
Radiation Oncology at the Interface of Pediatric Cancer Biology and Data Science (KIDSROBIN) | Dana Farber Cancer Institute | Daphne Haas-Kogan* Franziska Michor | Neuroblastoma Diffuse Midline Glioma |
Molecular Characterization Patient Cohort
- Each grant has at least one central molecular characterization trial focused on longitudinal collection of biospecimens and multimodal data from patients prior to-, during treatment, and after RT.
- The molecular characterization cohorts will be designed as “small n, high-content” studies where each patient serves as their own control over the course of standard-of-care RT with an equal focus on tumor and normal tissue.
Supporting Cores
The U54s must have:
- At least two projects and standard cores (imaging/dosimetry, -omics, biospecimens, data sciences)
- Unique to ROBIN, a cross-training core whose focus is workforce development in accordance to the CTAC report on radiation oncology.
Integration of Data Science
- The network must focus on data science that integrates with modern data science methods and aligns with the NCI Cancer Research Data Commons, which is a unique contributor of multi-modal data at the intersection of cancer biology and radiation.
- Each center must have a dedicated Data Management Specialist position as key personnel within the relevant core.
Contacts
Dr. Jeffery Buchsbaum (jeff.buchsbaum@nih.gov) or Dr. Bhadrasain Vikram (vikramb@mail.nih.gov)