Current and Future Initiatives for Radiation Oncology at the National Cancer Institute in the Era of Precision Medicine

Improving the efficacy of combined radiotherapy and immunotherapy: focusing on the effects of radiosensitivity

Cancer treatment is gradually entering an era of precision, with multitude studies in gene testing and immunotherapy. Tumor cells can be recognized and eliminated by the immune system through the expression of tumor-associated antigens, but when the cancer escapes or otherwise suppresses immunity, the balance between cancer cell proliferation and immune-induced cancer cell killing may be interrupted, resulting in tumor proliferation and progression. There has been significant attention to combining conventional cancer therapies (i.e., radiotherapy) with immunotherapy as opposed to treatment alone. The combination of radio-immunotherapy has been demonstrated in both basic research and clinical trials to provide more effective anti-tumor responses. However, the absolute benefits of radio-immunotherapy are dependent on individual characteristics and not all patients can benefit from radio-immunotherapy. At present, there are numerous articles about exploring the optimal models for combination radio-immunotherapy, but the factors affecting the efficacy of the combination, especially with regard to radiosensitivity remain inconclusive. Radiosensitivity is a measure of the response of cells, tissues, or individuals to ionizing radiation, and various studies have shown that the radiosensitivity index (RSI) will be a potential biomarker for predicting the efficacy of combination radio-immunotherapy. The purpose of this review is to focus on the factors that influence and predict the radiosensitivity of tumor cells, and to evaluate the impact and predictive significance of radiosensitivity on the efficacy of radio-immunotherapy combination.

Development and validation of an immune-related gene signature for predicting the radiosensitivity of lower-grade gliomas

Radiotherapy is an important treatment modality for lower-grade gliomas (LGGs) patients. This analysis was conducted to develop an immune-related radiosensitivity gene signature to predict the survival of LGGs patients who received radiotherapy. The clinical and RNA sequencing data of LGGs were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Lasso regression analyses were used to construct a 21-gene signature to identify the LGGs patients who could benefit from radiotherapy. Based on this radiosensitivity signature, patients were classified into a radiosensitive (RS) group and a radioresistant (RR) group. According to the Kaplan–Meier analysis results of the TCGA dataset and the two CGGA validation datasets, the RS group had a higher overall survival rate than that of the RR group. This gene signature was RT-specific and an independent prognostic indicator. The nomogram model performed well in predicting 3-, and 5-year survival of LGGs patients after radiotherapy by this gene signature and other clinical factors (age, sex, grade, IDH mutations, 1p/19q codeletion). In summary, this signature is a powerful supplement to the prognostic factors of LGGs patients with radiotherapy and may provide an opportunity to incorporate individual tumor biology into clinical decision making in radiation oncology.

Radiation and Cancer Biology Educators of Radiation Oncology Residents and the Courses They Teach1

The purpose of this study was to characterize today's radiation and cancer biology educators of radiation oncology residents, and the biology courses they teach. An e-mail list of 133 presumptive resident biology educators was compiled, and they were invited to participate in a 46-item survey. Survey questions were designed to collect information about the educational and academic backgrounds of the educators, how they self-identify, characteristics of the courses they teach, the value that they assign to their teaching activities, their level of satisfaction with their courses and how they see these courses being taught in the future. Findings of this survey were compared and contrasted with prior surveys of biology educators (conducted 12 and 20 years ago, respectively), and with more recent surveys of radiation oncology residents and radiation oncology residency program directors conducted in 2018 and 2019. A total of 67 survey responses were received. Biology educators range in age, academic rank and years of teaching experience from junior (18%) to quite senior (45%). Only about 40% self-identify as radiation biologists, biophysicists or chemists, compared to 56% in 2001. The majority of the others consist of cancer biologists (15%), radiation oncologists (15%) and radiation oncology physician-scientists (16%). Educators prioritize their resident teaching as important or very important. Biology courses are widely variable in contact hours between programs and have not changed significantly over the past 20 years. About 75% of the courses are team-taught, including 15% involving multiple training programs. An average biology course consists of about 42% foundational ("classical") radiobiology, 28% clinical radiobiology and 28% cancer biology. While biology educators and radiation oncology program directors are highly satisfied with their biology courses, approximately a third of residents report being not very, or not at all, satisfied. That fewer biology educators are radiobiologists by training and their courses have remained quite variable in length and content over long periods point to the need for a consensus core curriculum for resident education in radiation and cancer biology. Both current educators and program directors also support making online teaching resources available, diversifying course instructors and consolidating biology teaching across multiple training programs.

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Breast cancer, the most frequent malignancy in women worldwide, is a heterogeneous group of diseases, characterized by distinct molecular aberrations. In precision medicine, radiation oncology for breast cancer aims at tailoring treatment according to tumor biology and each patient’s clinical features and genetics. Although systemic therapies are personalized according to molecular sub-type [i.e. endocrine therapy for receptor-positive disease and anti-human epidermal growth factor receptor 2 (HER2) therapy for HER2-positive disease] and multi-gene assays, personalized radiation therapy has yet to be adopted in the clinical setting. Currently, attempts are being made to identify prognostic and/or predictive factors, biomarkers, signatures that could lead to personalized treatment in order to select appropriate patients who might, or might not, benefit from radiation therapy or whose radiation therapy might be escalated or de-escalated in dosages and volumes. This overview focuses on what has been achieved to date in personalized post-operative radiation therapy and individual patient radiosensitivity assessments by means of tumor sub-types and genetics.

Real-world data for pediatric medulloblastoma: can we improve outcomes?

Medulloblastoma (MB) is a malignant embryonal tumor that develops especially in childhood, with overall survival (OS) at 5 years of up to 70%. The objective of this study is to analyze treatment delivery variables in a retrospective cohort and evaluate the impact of these treatment quality parameters on survival. From 2000 to 2018, 40 pediatric patients with medulloblastoma, treated according to current international protocols, were retrospectively analyzed. Treatment delivery quality indicators were analyzed including the extent of surgery, radiotherapy (RT) parameters, and chemotherapy variables, related with time and dose-intensity deviations. With a median follow-up of 74 months (range, 6-195), OS at 5 years was 74 ± 7%, 81 ± 8% for standard-risk, and 55 ± 16% for high-risk patients (p = 0.090). Disease-free survival at 5 years was not significantly affected by extent of surgery (p = 0.428) and RT-related variables such as surgery-RT interval (p = 0.776) neither RT duration (p = 0.172) or maintenance chemotherapy compliance (p = 0.634). Multivariate analysis identified risk groups predictive of worse DFS (p = 0.032) and leptomeningeal dissemination associated with inferior OS (p = 0.029).Conclusion: Treatment delivery optimization has improved survival rates of patients with MB. Despite this, in our study, we have not established a clear influence of the considered radiotherapy and chemotherapy treatment quality parameters on outcomes. What is Known: • Improvement in treatment modalities during the last decades has reached a 5-year OS of up to 70% in these patients. • Extent of resection and radiotherapy parameters such as interval between surgery-radiotherapy and radiotherapy duration has been described as probable survival prognostic factors. What is New: • Differences in medulloblastoma survival rates between prospective studies and retrospective series. • The impact on survival of the three main treatment variables, surgery, radiotherapy and chemotherapy, susceptible to improvement.

History and current perspectives on the biological effects of high-dose spatial fractionation and high dose-rate approaches: GRID, Microbeam & FLASH radiotherapy

The effects of various forms of ionising radiation are known to be mediated by interactions with cellular and molecular targets in irradiated and in some cases non-targeted tissue volumes. Despite major advances in advanced conformal delivery techniques, the probability of normal tissue complication (NTCP) remains the major dose-limiting factor in escalating total dose delivered during treatment. Potential strategies that have shown promise as novel delivery methods in achieving effective tumour control whilst sparing organs at risk involve the modulation of critical dose delivery parameters. This has led to the development of techniques using high dose spatial fractionation (GRID) and ultra-high dose rate (FLASH) which have translated to the clinic. The current review discusses the historical development and biological basis of GRID, microbeam and FLASH radiotherapy as advanced delivery modalities that have major potential for widespread implementation in the clinic in future years.

Pan-Cancer Analysis of Radiotherapy Benefits and Immune Infiltration in Multiple Human Cancers

Response to radiotherapy (RT) in cancers varies widely among patients. Therefore, it is very important to predict who will benefit from RT before clinical treatment. Consideration of the immune tumor microenvironment (TME) could provide novel insight into tumor treatment options. In this study, we investigated the link between immune infiltration status and clinical RT outcome in order to identify certain leukocyte subsets that could potentially influence the clinical RT benefit across cancers. By integrally analyzing the TCGA data across seven cancers, we identified complex associations between immune infiltration and patients RT outcomes. Besides, immune cells showed large differences in their populations in various cancers, and the most abundant cells were resting memory CD4 T cells. Additionally, the proportion of activated CD4 memory T cells and activated mast cells, albeit at low number, were closely related to RT overall survival in multiple cancers. Furthermore, a prognostic model for RT outcomes was established with good performance based on the immune infiltration status. Summarized, immune infiltration was found to be of significant clinical relevance to RT outcomes. These findings may help to shed light on the impact of tumor-associated immune cell infiltration on cancer RT outcomes, and identify biomarkers and therapeutic targets.