Research Plan – Radiation Oncology

The below comprises a summary of key aspects of the Research Plan for the Department of Radiation Oncology. It provides an overview of some of Moffitt’s research strengths as well as descriptions of some of the research foci within our program. Information about our residents’/fellows’ research output is available as well. 

The Department of Radiation Oncology at Moffitt Cancer Center aspires to become a national and international leader in the next revolution in the field. There are multiple components of this evolution/revolution: personalized or precision medicine based upon unique genetic signatures and novel dosing methodologies, integration of immunotherapy and radiation therapy into a new paradigm of disease management, characterizing the interaction between tumor radiocurability and underlying viral infections, novel investigations of the root cause of racial and other disparities that open doors to new strategies to overcome these disparities, and a wide spectrum of clinical trials exploring timely strategies to improve outcomes in both purely therapeutic as well as integrative approaches. Being the only therapeutic department at Moffitt that participates in the management of all human cancers, we have a unique opportunity to create a thematic research plan that has the potential for broad impact on the field. 

The basis of the personalized approach and precision medicine is clear: the integration of omic-based features to personalize radiation dose and fractionation. Over the last several decades, innovation in radiation oncology has been driven by technological advances in engineering and computer science that have allowed the more precise delivery of radiation. However, exploiting the biological differences between individuals that influence the therapeutic benefit of radiation therapy is an unexplored frontier. At Moffitt, we have a confluence of resources that if appropriately leveraged will result in the first program in genomic radiation therapy with the potential of clinical impact within a reasonable timeframe (5 years). The overarching theme of this research strategic plan is to leverage the unique resources at Moffitt to develop a rational approach to exploit individual biology-based differences to customize radiation treatment parameters. 

The basis of the initiatives in tumor immunotherapy and radiation therapy lies in dispelling the myth that radiation therapy is purely a loco-regional treatment. While the loco-regional tumor control provided by radiation therapy is a core premise, we have come to learn that radiation therapy can contribute to the management of metastatic disease. The use of stereotactic radiation therapy for oligometastatic disease can be curative. We are now in an era of enormous advancement in tumor immunotherapy, with a growing arsenal of compounds with targeted effect and significant response. This opens the door to combine the effects of radiation therapy on local tumor as well as on the immune system as a whole, in novel combined therapy strategies for patients with systemic metastases. 

Disparities research is a core interest of any NCI Designated Comprehensive Cancer Center, including Moffitt. Our Department has a faculty member with strong research relationships in Ghana and he has initiated an organized program to examine the genetic basis for disparities in outcomes for African-American men with prostate cancer. This will serve as a foundation for broadening the portfolio of activity in Disparities research in the Department and at Moffitt overall, and foster Team Science with Cancer Epidemiology, Population Science, Disparities as well as other Clinical Departments. 

The interaction of viral infection and tumor response to radiotherapy is another frontier that remains unexplored. There is significant clinical data that suggests that tumors associated with viral infections are highly and uniquely radiocurable. For example, HPV-associated tumors such as oropharyngeal and anal cancers, EBV associated nasopharyngeal cancer, polyomavirus-associated Merkel Cell cancer, all have some of the highest rates of radiocurability in the solid tumor literature. In addition, these tumors demonstrate, as a group, highly sensitive scores based on our genomic signature of radiosensitivity (RSI). With the presence of Anna Giuliano at Moffitt, it is a natural fit to develop a research group aimed at understanding the interactions between viral infections and tumor response to radiation therapy.

Moffitt Cancer Center has the unique resources available to make the vision within this research plan a reality. This confluence of resources is unique and provides the institution a unique advantage over others. The specific resources that we envision play a central role in the development of genomic radiation therapy include:

1. Genomic Expertise – in recent studies we have developed RSI, a molecular signature of tumor radiosensitivity that has been clinically-validated as an RT-specific biomarker in over 2,200 patients. Importantly, the signature has been validated in 8 different disease sites, suggesting that the biological networks that regulate response to RT are shared across disease sites and not specific to any parpticular histology. RSI is at the center of our strategy to develop genomic-based radiation dosing, using a novel approach that normalizes RT dose to the expected tumor effect.
2. Total Cancer Care (TCC) – the availability of this resource is critical to the success of the strategy. This database has already played a role in the initial clinical validation of RSI. We now have a “SPOKE” within TCC that fits the specific needs of radiation oncology researchers. Currently, we have generated RSIs for over 16,000 patients in TCC. Further characterizing this population and integrating radiation-specific parameters (i.e treatment planning, radiation dose etc.) will create the largest genomic database for radiation oncology in the world. However more importantly is that we have demonstrated that we can utilize the database to develop technologies that can be integrated into the clinical decision-making process. Finally, we expect that the combination of RSI as a guide to identifying radiophenotype will allow the genetic characterization of radioresistance.
3. Integrated Mathematical Oncology (IMO) – historically, radiation oncology has been tied to mathematical modeling. All current radiation dose and fractionation approaches are based on the linear quadratic model of tumor response. Two members of the IMO are experts in the linear quadratic model. The linear quadratic model has resulted in dose and fractionation protocols that have been demonstrated safe and effective. However, in our view, a fundamental flaw of the model is that it assumes that tumor response to radiation is uniform. With the development of RSI, we have for the first time an opportunity to account for the heterogeneity of tumor radiosensitivity. Building on the highly successful linear quadratic model, our strategy develops novel parameters that will allow the normalization of dose to the genomic characteristics of the tumor. We think this will be the next revolution in the field.
4. Immunology expertise – a fundamental theme in this plan is the integration of immune strategies and RT in both mechanistic studies and novel clinical trials. The existing expertise at Moffitt in Immunology is central to the development of these strategies.
5. Viral Oncology – This is one of the core strengths of the center. Several viral-associated cancers including oropharynx (HPV), cervix (HPV) and nasopharynx (EBV) are also highly radiocurable, begging the question of whether there is any causal relationship between the viral infection and the tumor response to radiation. With the presence of Anna Giuliano at Moffitt, it is a natural fit to develop a research team aimed at understanding the interactions between viral infections and tumor response to radiation therapy.
6. ORIEN – The development of this collaboration to accelerate translating discoveries into clinical care will play a central part in the strategy. Our vision calls for the development of clinical trials that will test novel approaches to customize radiation treatment parameters based on omic characteristics. The ORIEN network could be an effective vehicle to accelerate the successful completion of these trials
7. Health Literacy – Affiliations are being built with USF and elsewhere within Moffitt to further clarify the role of Health Literacy on treatment compliance. Our team has previously demonstrated a disconnect between the reading comprehension levels required for radiotherapy consent forms and the comprehension levels of the patients to whom they are directed. We hypothesize this disconnect is even greater in Moffitt’s multicultural environment. This provides a practical contributor to Health Disparities on a social scale. 

Execution Strategy 

Developing Informatics-based Approaches to Optimize, Personalize and Adapt Radiation Dose and Fractionation

We believe that RSI provides unique information that will change how we treat patients with radiation therapy. Optimizing radiation dosing utilizing genomics has enormous clinical potential. RT, using standard and uniform dosing has been shown to impact survival in multiple disease sites. Since approximately 900,000 individuals in the United States receive RT every year, any small benefit provided by dose optimization can impact cancer-related outcomes significantly.

Normalizing Radiation Dose Using Genomic Features (RSI): Genomic-Adjusted Radiotherapy Dose (GARD)

Currently, radiation therapy doses are normalized to the amount of radiation dose absorbed by tissue. The novelty introduced by RSI is that it can identify predicted differences in the therapeutic effect of radiation between patients. Thus, our first strategy in integrating genomics to radiation dosing includes the development of an approach to normalize dose using RSI. In this approach, we are determining the actual dose required to deliver an effective dose that will have the highest probability of tumor control. We can also estimate at an individual level the potential benefit for dose increments in a particular individual.

GARD is a transformation of RSI into a clinically-actionable parameter for use in the clinic. The mathematical transformation is based on the standard equation of the linear quadratic model for dose effect (E). This results in a value that reflects the predicted effect of RT in each individual patient. The clinical validation of GARD is ongoing, but initial studies show that GARD identifies threshold dose effect where the therapeutic benefit of RT might be optimized. The RSI/GARD discussion manuscript is in progress now; subsequent translational manuscripts are in process.

Imaging-based (Radiomics) Parameters to Estimate the Proliferation/Saturation Rate of a Tumor

Another approach to integrating individual tumor features into radiation therapy dosing being developed in the department is a measure of the proliferation/saturation index (PSI). Proliferation is one parameter that has been classically represented in the linear quadratic model and tumor re-population (re-growth of tumor between doses of radiation) is believed to be one of the main reasons for failure after RT. PSI is calculated based on information extracted from two independent imaging scans, taken at different time points prior to the initiation of treatment. Initial data suggests that PSI may be useful in identifying useful fractionation approaches for individual patients.

Adapting Radiation Therapy during Treatment

A feature of current empiric radiotherapy dosing is that treatment parameters (i.e dose per session, frequency of doses, technique etc.) are defined prior to initiation of treatment and are delivered over several weeks. We think that there is significant clinical potential to improve outcomes by adapting treatment parameters during treatment. However, except for clear clinical progression, there are no parameters that are routinely used to direct changes in treatment technique. Thus another central element of our plan is the development of novel metrics and tools that will allow the real-time evaluation of the success of a particular RT treatment regimen. Our approach exploits the large in-treatment imaging database available at Moffitt. It is routine for most patients treated with modern image-guided radiation therapy, to be imaged on a daily basis to confirm correct positioning of the field. Integrating these imaging-features into our novel patient-specific models has the potential to provide approaches that will allow the clinician to adapt their prescription with real-time clinical information. The imaging features can be clearly applied to similar models as the PSI approach described above. In addition, in-treatment changes in the RSI metric can be of importance. It is time to mine the imaging warehouse and use the data to develop a premise to adapt therapy.

Development of SPOKE with an Emphasis in Radiation Oncology

TCC has played a central role in the development of the genomic scientific strategy to understand individual differences in radiation sensitivity and its impact on clinical outcome. Currently, we have developed RSIs for over 16,000 patients, making this the largest genomic database for radiation oncology research in the world. A distinctive characteristic of this work is that we are moving into the phase of clinical translation with an approach where the genomic characteristics of a tumor can be acted on by the clinician. Given the importance that TCC and other public databases have played, we think it is vital that we customize TCC for radiation oncology users. This effort will occur in two areas. First, for the end-user and in collaboration with ISS, all clinical elements currently available for the 16,000 patients with known RSI will be readily available for radiation oncology users. Second, working on the back-end of data collection, we will work with IT to customize the collection of clinical elements that are unique to radiation oncology. These include radiation treatment planning parameters including total dose, dose per fraction, treatment time, DVHs for tumor and normal tissue etc. Connecting the genomic, imaging and radiation treatment planning space will be incredibly important in further developing our research program.

Executing Novel Clinical Trials through the ORIEN Network

One of the appealing angles of this strategy is that the research goals include the translation into clinical care. We expect that this effort will result in several clinical trials to test the customization of radiation dosing parameters, representing a novel landscape in clinical radiation oncology. The ideas that can be clinically-translated include dosing normalization using a genetic threshold defined by RSI and GAD (genomic adjusted dose), individualized fractionation based on proliferation/saturation index as well as adaptive approaches to radiation dose adjustment during treatment. The ORIEN network could potentially enhance the scope of this effort and provide an excellent vehicle to successfully translate these ideas into the clinic.