Precision Oncology and Genomically Guided Radiation Therapy: A Report From the American Society for Radiation Oncology/American Association of Physicists in Medicine/National Cancer Institute Precision Medicine Conference

Development and validation of a radiosensitivity model to evaluate radiotherapy benefits in pan-cancer

Radiotherapy, one of the most fundamental cancer treatments, is confronted with the dilemma of treatment failure due to radioresistance. To predict the radiosensitivity and improve tumor treatment efficiency in pan-cancer, we developed a model called Radiation Intrinsic Sensitivity Evaluation (RISE). The RISE model was built using cell line-based mRNA sequencing data from five tumor types with varying radiation sensitivity. Through four cell-derived datasets, two public tissue-derived cohorts, and one local cohort of 42 nasopharyngeal carcinoma patients, we demonstrated that RISE could effectively predict the level of radiation sensitivity (area under the ROC curve [AUC] from 0.666 to 1 across different datasets). After the verification by the colony formation assay and flow cytometric analysis of apoptosis, our four well-established radioresistant cell models successfully proved higher RISE values in radioresistant cells by RT-qPCR experiments. We also explored the prognostic value of RISE in five independent TCGA cohorts consisting of 1137 patients who received radiation therapy and found that RISE was an independent adverse prognostic factor (pooled multivariate Cox regression hazard ratio [HR]: 1.84, 95% CI 1.39-2.42; p < 0.01). RISE showed a promising ability to evaluate the radiotherapy benefit while predicting the prognosis of cancer patients, enabling clinicians to make individualized radiotherapy strategies in the future and improve the success rate of radiotherapy.

Hypoxia-Directed Treatment of Human Papillomavirus-Related Oropharyngeal Carcinoma

PURPOSE

Standard curative-intent chemoradiotherapy for human papillomavirus (HPV)-related oropharyngeal carcinoma results in significant toxicity. Since hypoxic tumors are radioresistant, we posited that the aerobic state of a tumor could identify patients eligible for de-escalation of chemoradiotherapy while maintaining treatment efficacy.

METHODS

We enrolled patients with HPV-related oropharyngeal carcinoma to receive de-escalated definitive chemoradiotherapy in a phase II study (ClinicalTrials.gov identifier: NCT03323463). Patients first underwent surgical removal of disease at their primary site, but not of gross disease in the neck. A baseline 18F-fluoromisonidazole positron emission tomography scan was used to measure tumor hypoxia and was repeated 1-2 weeks intratreatment. Patients with nonhypoxic tumors received 30 Gy (3 weeks) with chemotherapy, whereas those with hypoxic tumors received standard chemoradiotherapy to 70 Gy (7 weeks). The primary objective was achieving a 2-year locoregional control (LRC) of 95% with a 7% noninferiority margin.

RESULTS

One hundred fifty-eight patients with T0-2/N1-N2c were enrolled, of which 152 patients were eligible for analyses. Of these, 128 patients met criteria for 30 Gy and 24 patients received 70 Gy. The 2-year LRC was 94.7% (95% CI, 89.8 to 97.7), meeting our primary objective. With a median follow-up time of 38.3 (range, 22.1-58.4) months, the 2-year progression-free survival (PFS) and overall survival (OS) rates were 94% and 100%, respectively, for the 30-Gy cohort. The 70-Gy cohort had similar 2-year PFS and OS rates at 96% and 96%, respectively. Acute grade 3-4 adverse events were more common in 70 Gy versus 30 Gy (58.3% v 32%; P = .02). Late grade 3-4 adverse events only occurred in the 70-Gy cohort, in which 4.5% complained of late dysphagia.

CONCLUSION

Tumor hypoxia is a promising approach to direct dosing of curative-intent chemoradiotherapy for HPV-related carcinomas with preserved efficacy and substantially reduced toxicity that requires further investigation.

Therapeutic Approaches to Increase the Survival Rate of Cancer Patients in the Younger and Older Population

Various developments have been observed in the treatment of cancer patients, such as higher survival rates and better treatment outcomes. However, expecting similar outcomes in older patients remains a challenge. The main reason for this conclusion is the exclusion of older people from clinical trials for cancer drugs, as well as other factors, such as comorbidity, side effects, age-related frailties and their willingness to undergo multiple treatments. However, the discovery of new techniques and drug combinations has led to a significant improvement in the survival of the elderly population after the onset of the disease. On the other hand, cancer treatments have not become more complex for the younger population when compared to the older population, as the younger population tends to respond well to treatment trials and their physiological conditions are stable in response to treatments. In summary, this review correlates recent cancer treatment strategies and the corresponding responses and survival outcomes of older and younger patients.

Genomic Tumor Correlates of Clinical Outcomes Following Organ-Sparing Chemoradiation Therapy for Bladder Cancer

PURPOSE

There is an urgent need for biomarkers of radiation response in organ-sparing therapies. Bladder preservation with trimodality therapy (TMT), consisting of transurethral tumor resection followed by chemoradiation, is an alternative to radical cystectomy for muscle-invasive bladder cancer (MIBC), but molecular determinants of response are poorly understood.

EXPERIMENTAL DESIGN

We characterized genomic and transcriptomic features correlated with long-term response in a single institution cohort of patients with MIBC homogeneously treated with TMT. Pretreatment tumors from 76 patients with MIBC underwent whole-exome sequencing; 67 underwent matched transcriptomic profiling. Molecular features were correlated with clinical outcomes including modified bladder-intact event-free survival (mBI-EFS), a composite endpoint that reflects long-term cancer control with bladder preservation.

RESULTS

With a median follow-up of 74.6 months in alive patients, 37 patients had favorable long-term response to TMT while 39 had unfavorable long-term response. Tumor mutational burden was not associated with outcomes after TMT. DNA damage response gene alterations were associated with improved locoregional control and mBI-EFS. Of these alterations, somatic ERCC2 mutations stood out as significantly associated with favorable long-term outcomes; patients with ERCC2 mutations had significantly improved mBI-EFS [HR, 0.15; 95% confidence interval (CI), 0.06-0.37; P = 0.030] and improved BI-EFS, an endpoint that includes all-cause mortality (HR, 0.33; 95% CI, 0.15-0.68; P = 0.044). ERCC2 mutant bladder cancer cell lines were significantly more sensitive to concurrent cisplatin and radiation treatment in vitro than isogenic ERCC2 wild-type cells.

CONCLUSIONS

Our data identify ERCC2 mutation as a candidate biomarker associated with sensitivity and long-term response to chemoradiation in MIBC. These findings warrant validation in independent cohorts.

Real World and Public Health Perspectives of Intraoperative Radiotherapy in Early-Stage Breast Cancer: A Multidisciplinary Analysis Beyond the Statistical Facts

Breast conservation therapy (BCT) (usually a lumpectomy plus radiotherapy (RT)) has become a standard alternative to radical mastectomy in early-stage breast cancers with equal, if not higher, survival rates. The established standard of the RT component of the BCT had been about six weeks of Monday through Friday external beam RT to the whole breast (WBRT). Recent clinical trials have shown that partial breast radiation therapy (PBRT) to the region surrounding the lumpectomy cavity with shorter courses can result in equal local control, survival, and slightly improved cosmetic outcomes. Intraoperative RT (IORT) wherein RT is administered at the time of operation for BCT to the lumpectomy cavity as a single-fraction RT is also considered PBRT. The advantage of IORT is that weeks of RT are avoided. However, the role of IORT as part of BCT has been controversial. The extreme views go from "I will not recommend to anyone" to "I can recommend to all early-stage favorable patients." These divergent views are due to difficulty in interpreting the clinical trial results. There are two modalities of delivering IORT, namely, the use of low-energy 50 kV beams or electron beams. There are several retrospective, prospective, and two randomized clinical trials comparing IORT versus WBRT. Yet, the opinions are divided. In this paper, we try to bring clarity and consensus from a highly broad-based multidisciplinary team approach. The multidisciplinary team included breast surgeons, radiation oncologists, medical physicists, biostatisticians, public health experts, nurse practitioners, and medical oncologists. We show that there is a need to more carefully interpret and differentiate the data based on electron versus low-dose X-ray modalities; the randomized study results have to be extremely carefully dissected from biostatistical points of view; the importance of the involvement of patients and families in the decision making in a very transparent and informed manner needs to be emphasized; and the compromise some women may be willing to accept between 2-4% potential increase in local recurrence (as interpreted by some of the investigators in IORT randomized studies) versus mastectomy. We conclude that, ultimately, the choice should be that of women with detailed facts of the pros and cons of all options being presented to them from the angle of patient/family-focused care. Although the guidelines of various professional societies can be helpful, they are only guidelines. The participation of women in IORT clinical trials is still needed, and as genome-based and omics-based fine-tuning of prognostic fingerprints evolve, the current guidelines need to be revisited. Finally, the use of IORT can help rural, socioeconomically, and infrastructure-deprived populations and geographic regions as the convenience of single-fraction RT and the possibility of breast preservation are likely to encourage more women to choose BCT than mastectomy. This option can also likely lead to more women choosing to get screened for breast cancer, thus enabling the diagnosis of breast cancer at an earlier stage and improving the survival outcomes.

Radiogenomics in lung cancer: Where are we?

Huge technological and biomedical advances have improved the survival and quality of life of lung cancer patients treated with radiotherapy. However, during treatment planning, a probability that the patient will experience adverse effects is assumed. Radiotoxicity is a complex entity that is largely dose-dependent but also has important intrinsic factors. One of the most studied is the genetic variants that may be associated with susceptibility to the development of adverse effects of radiotherapy. This review aims to present the current status of radiogenomics in lung cancer, integrating results obtained in association studies of SNPs (single nucleotide polymorphisms) related to radiotherapy toxicities. We conclude that despite numerous publications in this field, methodologies and endpoints vary greatly, making comparisons between studies difficult. Analyzing SNPs from the candidate gene approach, together with the study in cohorts limited by the sample size, has complicated the possibility of having validated results. All this delays the incorporation of genetic biomarkers in predictive models for clinical application. Thus, from all analysed SNPs, only 12 have great potential as esophagitis genetic risk factors and deserve further exploration. This review highlights the efforts that have been made to date in the radiogenomic study of radiotoxicity in lung cancer.

Personalized medicine in radiation oncology and radiation sensitivity index: Pathbreaking genomic way to define the role of radiation in cancer management

ABSTRACTS

The technological developments associated with the branch of Radiation Oncology have been directed towards precise delivery of the dose, leading to improved survival in various solid malignancies. Radiation therapy as a treatment modality, is an integral component of more than half of the diagnosed malignancies. In spite of the role of adaptive radiation therapy evolving over the last decade, the fundamental question remains as to the difference in radiation response between individuals. Recently, the role of the radiosensitivity index has emerged, which has shown immense potential in the development of biologically driven tumor radiation therapy. The role of these novel methods of genome-based molecular assays needs to be explored to help in decision-making between radical treatment options for various malignancies and reduce the associated toxicity burden. In this article, we explore the current evidence available for various malignancy sites and provide a comprehensive review of the predictive values of various molecular markers available and their impact on the radiosensitivity index.

Improving Patients’ Life Quality after Radiotherapy Treatment by Predicting Late Toxicities

Simple Summary

Over 50% of patients with cancer will receive radiotherapy treatment. Five to ten percent of patients who received radiotherapy will develop side effects. Identifying these patients before treatment start would allow for treatment modification to minimize these effects and improve the life quality of these patients. Our team developed a test, which allows predicting these secondary effects before starting the treatment. This will help in proposing personalized treatments to improve the outcome. This review presents how this test is performed, its results, as well as its modification in order to be used in hospitals.

Abstract

Personalized treatment and precision medicine have become the new standard of care in oncology and radiotherapy. Because treatment outcomes have considerably improved over the last few years, permanent side-effects are becoming an increasingly significant issue for cancer survivors. Five to ten percent of patients will develop severe late toxicity after radiotherapy. Identifying these patients before treatment start would allow for treatment adaptation to minimize definitive side effects that could impair their long-term quality of life. Over the last decades, several tests and biomarkers have been developed to identify these patients. However, out of these, only the Radiation-Induced Lymphocyte Apoptosis (RILA) assay has been prospectively validated in multi-center cohorts. This test, based on a simple blood draught, has been shown to be correlated with late radiation-induced toxicity in breast, prostate, cervical and head and neck cancer. It could therefore greatly improve decision making in precision radiation oncology. This literature review summarizes the development and bases of this assay, as well as its clinical results and compares its results to the other available assays.

Outcomes After Breast Radiation Therapy in a Diverse Patient Cohort With a Germline BRCA1/2 Mutation

PURPOSE

BRCA1/2 pathogenic variant (PV) mutations confer radiation sensitivity preclinically, but there are limited data regarding breast cancer outcomes after radiation therapy (RT) among patients with documented BRCA1/2 PV mutations versus no PV mutations.

METHODS AND MATERIALS

This retrospective cohort study included women with clinical stage I-III breast cancer who received definitive surgery and RT and underwent BRCA1/2 genetic evaluation at the The University of Texas MD Anderson Cancer Center. Rates of locoregional recurrence (LRR), disease-specific death (DSD), toxicities, and second cancers were compared by BRCA1/2 PV status.

RESULTS

Of the 2213 women who underwent BRCA1/2 testing, 63% self-reported their race as White, 13.6% as Black/African American, 17.6% as Hispanic, and 5.8% as Asian/American Indian/Alaska Native; 124 had BRCA1 and 100 had BRCA2 mutations; and 1394 (63%) received regional nodal RT. The median follow-up time for all patients was 7.4 years (95% confidence interval [CI], 7.1-7.7 years). No differences were found between the groups with and without BRCA1/2 PV mutations in 10-year cumulative incidences of LRR (with mutations: 11.6% [95% CI, 7.0%-17.6%]; without mutations: 6.6% [95% CI, 5.3%-8.0%]; P = .466) and DSD (with mutations: 12.3% [95% CI, 8.0%-17.7%]; without mutations: 13.8% [95% CI, 12.0%-15.8%]; P = .716). On multivariable analysis, BRCA1/2 status was not associated with LRR or DSD, but Black/African American patients (P = .036) and Asians/American Indians/Alaska Native patients (P = .002) were at higher risk of LRR compared with White patients, and Black/African American patients were at higher risk of DSD versus White patients (P = .004). No in-field, nonbreast second cancers were observed in the BRCA1/2 PV group. Rates of acute and late grade ≥3 radiation-related toxicity in the BCRA1/2 PV group were 5.4% (n = 12) and 0.4% (n = 1), respectively.

CONCLUSIONS

Oncologic outcomes in a diverse cohort of patients with breast cancer who had a germline BRCA1/2 PV mutation and were treated with RT were similar to those of patients with no mutation, supporting the use of RT according to standard indications in patients with a germline BRCA1/2 PV mutation.

Do We Need a New Approach to Cancer Biology Education for Radiation Oncology Residents?

Traditional radiation oncology biology courses largely focus on radiation biology and oncology as needed for passing the boards. Changes in the landscape of oncology necessitate a broader scope. Radiotherapy is an important component of cancer care. Approximately 70% of all cancer patients receive radiotherapy during the course of their disease. With the revolution in precision medicine that is unfolding, genomics, proteomics, metabolomics, and microbiomics are being ever more integrated into the treatment of cancer. Comprehensive knowledge of cancer biology beyond traditional radiation biology is essential for future advances in radiotherapy and unavoidable for radiation oncology trainees. The importance of a newly designed curriculum to impart broader knowledge to future radiation oncologists is emphasized in this report. A paradigm shift in the approach to the traditional radiation biology course is required to train residents for the future of oncology.

Tumour and normal tissue radiosensitivity

The place of personalized treatments is highly increasing in medical and radiation oncology. During the last decades, a huge number of assays have been developed to predict responses of normal tissues and tumours. These tests have not yet been included into daily clinical practice but the recent developments of radiation oncology are paving the way of personalized strategies including the risk of tumour recurrence and normal tissue reactions. Concerning tumor radiosensitivity prediction, no test are currently used, even if the radiosensitivity index and the genome-based model for adjusting radiotherapy dose assays seem the most promising with level II of evidence. Commercial developments are under progress. Concerning normal tissue radiosensitivity prediction, single nucleotide polymorphims of prostate cancer patients and radiation-induced CD8 T-lymphocyte apoptosis breast and prostate assays are of level I of evidence. They can be proposed before the beginning of radiotherapy in order to propose personalized treatments according to both risks of tumour and normal tissue radiosensitivity. Commercial developments are also under way.

Clinical and Preclinical Outcomes of Combining Targeted Therapy With Radiotherapy

In the era of precision medicine, radiation medicine is currently focused on the precise delivery of highly conformal radiation treatments. However, the tremendous developments in targeted therapy are yet to fulfill their full promise and arguably have the potential to dramatically enhance the radiation therapeutic ratio. The increased ability to molecularly profile tumors both at diagnosis and at relapse and the co-incident progress in the field of radiogenomics could potentially pave the way for a more personalized approach to radiation treatment in contrast to the current ‘‘one size fits all’’ paradigm. Few clinical trials to date have shown an improved clinical outcome when combining targeted agents with radiation therapy, however, most have failed to show benefit, which is arguably due to limited preclinical data. Several key molecular pathways could theoretically enhance therapeutic effect of radiation when rationally targeted either by directly enhancing tumor cell kill or indirectly through the abscopal effect of radiation when combined with novel immunotherapies. The timing of combining molecular targeted therapy with radiation is also important to determine and could greatly affect the outcome depending on which pathway is being inhibited.

A Novel Approach for the Discovery of Biomarkers of Radiotherapy Response in Breast Cancer

Radiotherapy (RT) is an important treatment modality for the local control of breast cancer (BC). Unfortunately, not all patients that receive RT will obtain a therapeutic benefit, as cancer cells that either possess intrinsic radioresistance or develop resistance during treatment can reduce its efficacy. For RT treatment regimens to become personalised, there is a need to identify biomarkers that can predict and/or monitor a tumour's response to radiation. Here we describe a novel method to identify such biomarkers. Liquid chromatography-mass spectrometry (LC-MS) was used on conditioned media (CM) samples from a radiosensitive oestrogen receptor positive (ER⁺) BC cell line (MCF-7) to identify cancer-secreted biomarkers which reflected a response to radiation. A total of 33 radiation-induced secreted proteins that had higher (up to 12-fold) secretion levels at 24 h post-2 Gy radiation were identified. Secretomic results were combined with whole-transcriptome gene expression experiments, using both radiosensitive and radioresistant cells, to identify a signature related to intrinsic radiosensitivity. Gene expression analysis assessing the levels of the 33 proteins showed that 5 (YBX3, EIF4EBP2, DKK1, GNPNAT1 and TK1) had higher expression levels in the radiosensitive cells compared to their radioresistant derivatives; 3 of these proteins (DKK1, GNPNAT1 and TK1) underwent in-lab and initial clinical validation. Western blot analysis using CM samples from cell lines confirmed a significant increase in the release of each candidate biomarker from radiosensitive cells 24 h after treatment with a 2 Gy dose of radiation; no significant increase in secretion was observed in the radioresistant cells after radiation. Immunohistochemistry showed that higher intracellular protein levels of the biomarkers were associated with greater radiosensitivity. Intracellular levels were further assessed in pre-treatment biopsy tissues from patients diagnosed with ER⁺ BC that were subsequently treated with breast-conserving surgery and RT. High DKK1 and GNPNAT1 intracellular levels were associated with significantly increased recurrence-free survival times, indicating that these two candidate biomarkers have the potential to predict sensitivity to RT. We suggest that the methods highlighted in this study could be utilised for the identification of biomarkers that may have a potential clinical role in personalising and optimising RT dosing regimens, whilst limiting the administration of RT to patients who are unlikely to benefit.

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.

Breast cancer radiotherapy: What physicians need to know in the era of the precision medicine

Breast cancer is the most common cancer in women worldwide and encompasses a broad spectrum of diseases in one with significant epidemiological, clinical, and biological heterogeneity, which determines a different natural history and prognostic profile. Although classical tumour staging (TNM) still provides valuable information, the current reality is that the clinicians must consider other biological and molecular factors that directly influence treatment decision-making. The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. This knowledge has brought with it a major impact regarding surgical and systemic management and has been practice-changing, but it has also created significant uncertainties regarding how best integrate the radiotherapy treatment into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualised treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. The aim of the present review is to clarify the meaning of this term and to critically evaluate its role and impact on contemporary breast cancer radiotherapy.

Insights into the theranostic value of precision medicine on advanced radiotherapy to breast cancer

Breast cancer is the most common cancer in women worldwide. "Breast cancer" encompasses a broad spectrum of diseases (i.e., subtypes) with significant epidemiological, clinical, and biological heterogeneity. Each of these subtypes has a different natural history and prognostic profile. Although tumour staging (TNM classification) still provides valuable information in the overall management of breast cancer, the current reality is that clinicians must consider other biological and molecular factors that directly influence treatment decision-making, including extent of surgery, indication for chemotherapy, hormonal therapy, and even radiotherapy (and treatment volumes). The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. While these changes have been extremely positive in terms of surgical and systemic management, they have also created significant uncertainties concerning integration of local and locoregional radiotherapy into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances. Beyond the evident technological advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualized treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. Although precision medicine has been much discussed in the last five years or so, the concept remains somewhat ambiguous, and it often appear to be used as a "catch-all" term. The present review aims to clarify the meaning of this term and, more importantly, to critically evaluate the role and impact of precision medicine on breast cancer radiotherapy. Finally, we will discuss the current and future of precision medicine in radiotherapy.

Development and Validation of a Genomic Tool to Predict Seminal Vesicle Invasion in Adenocarcinoma of the Prostate

PURPOSE

Pretreatment estimates of seminal vesicle invasion (SVI) are challenging and significantly influence the management of prostate cancer. We sought to improve current models to predict SVI through the development of an SVI prediction genomic signature.

PATIENTS AND METHODS

A total of 15,889 patients who underwent radical prostatectomy (RP) with available baseline clinical, pathology, and transcriptome data were retrieved from the GRID registry (ClinicalTrials.gov identifier: NCT02609269) and other retrospective cohorts. These data were divided into a training (n = 6,766), test (n = 3,363), and two validation (n = 5,062 and 698) cohorts. Multivariable logistic regression was performed to assess the predictive effect of the genomic SVI (gSVI) classifier in the presence of established nomograms (Partin Tables and Memorial Sloan Kettering Cancer Center [MSKCC]).

RESULTS

In the training cohort, univariable filtering identified 2,132 genes that were differentially expressed between RP tumors with and without SVI. Model parameters were tuned to maximize the area under the curve (AUC) in the testing cohort, resulting in a logistic generalized linear model with 581 genes. The gSVI model scores range from 0 to 1. In the first validation set, gSVI showed superior discrimination of patients with and without SVI at RP compared with other prognostic signatures trained to predict distant metastasis or clinical recurrence. Of the 698 patients in the second validation set, gSVI combined with the MSKCC nomogram had a superior AUC (0.86) compared with either nomogram individually (0.81).

CONCLUSION

The gSVI represents a novel and validated expression signature to predict the presence of SVI before treatment with surgery. This genomic tool adds discriminatory power to existing clinical predictive nomograms and may help with pretreatment counseling and decision making.

A Pilot Study of Cardiac MRI in Breast Cancer Survivors After Cardiotoxic Chemotherapy and Three-Dimensional Conformal Radiotherapy

PURPOSE/OBJECTIVES

Node-positive breast cancer patients often receive chemotherapy and regional nodal irradiation. The cardiotoxic effects of these treatments, however, may offset some of the survival benefit. Cardiac magnetic resonance (CMR) is an emerging modality to assess cardiac injury. This is a pilot trial assessing cardiac damage using CMR in patients who received anthracycline-based chemotherapy and three-dimensional conformal radiotherapy (3DCRT) regional nodal irradiation using heart constraints.

MATERIALS AND METHODS

Node-positive breast cancer patients (2000-2008) treated with anthracycline-based chemotherapy and 3DCRT regional nodal irradiation (including the internal mammary chain nodes) with heart ventricular constraints (V25 < 10%) were invited to participate. Cardiac tissues were contoured and analyzed separately for whole heart (pericardium) and for combined ventricles and left atrium (myocardium). CMR obtained ventricular function/dimensions, late gadolinium enhancement (LGE), global longitudinal strain (GLS), and extracellular volume fraction (ECV) as measures of cardiac injury and/or early fibrosis. CMR parameters were correlated with dose-volume constraints using Spearman correlations.

RESULTS

Fifteen left-sided and five right-sided patients underwent CMR. Median diagnosis age was 50 (32-77). No patients had baseline cardiac disease before regional nodal irradiation. Median time after 3DCRT was 8.3 years (5.2-14.4). Median left-sided mean heart dose (MHD) was 4.8 Gy (1.1-11.2) and V25 was 5.7% (0-12%). Median left ventricular ejection fraction (LVEF) was 63%. No abnormal LGE was observed. No correlations were seen between whole heart doses and LVEF, LV mass, GLS, or LV dimensions. Increasing ECV did not correlate with increased heart or ventricular doses. However, correlations between higher LV mass and ventricular mean dose, V10, and V25 were seen.

CONCLUSION

At a median follow-up of 8.3 years, this cohort of node-positive breast cancer patients who received anthracycline-based chemotherapy and regional nodal irradiation had no clinically abnormal CMR findings. However, correlations between ventricular mean dose, V10, and V25 and LV mass were seen. Larger corroborating studies that include advanced techniques for measuring regional heart mechanics are warranted.

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.

Genomics models in radiotherapy: From mechanistic to machine learning

Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.

Precision Medicine and the Role of Biomarkers of Radiotherapy Response in Breast Cancer

Radiotherapy remains an important treatment modality in nearly two thirds of all cancers, including the primary curative or palliative treatment of breast cancer. Unfortunately, largely due to tumor heterogeneity, tumor radiotherapy response rates can vary significantly, even between patients diagnosed with the same tumor type. Although in recent years significant technological advances have been made in the way radiation can be precisely delivered to tumors, it is proving more difficult to personalize radiotherapy regimens based on cancer biology. Biomarkers that provide prognostic or predictive information regarding a tumor's intrinsic radiosensitivity or its response to treatment could prove valuable in helping to personalize radiation dosing, enabling clinicians to make decisions between different treatment options whilst avoiding radiation-induced toxicity in patients unlikely to gain therapeutic benefit. Studies have investigated numerous ways in which both patient and tumor radiosensitivities can be assessed. Tumor molecular profiling has been used to develop radiosensitivity gene signatures, while the assessment of specific intracellular or secreted proteins, including circulating tumor cells, exosomes and DNA, has been performed to identify prognostic or predictive biomarkers of radiation response. Finally, the investigation of biomarkers related to radiation-induced toxicity could provide another means by which radiotherapy could become personalized. In this review, we discuss studies that have used these methods to identify or develop prognostic/predictive signatures of radiosensitivity, and how such assays could be used in the future as a means of providing personalized radiotherapy.

The Implications of Genetic Testing on Radiation Therapy Decisions: A Guide for Radiation Oncologists

The advent of affordable and rapid next-generation DNA sequencing technology, along with the US Supreme Court ruling invalidating gene patents, has led to a deluge of germline and tumor genetic variant tests that are being rapidly incorporated into clinical cancer decision-making. A major concern for clinicians is whether the presence of germline mutations may increase the risk of radiation toxicity or secondary malignancies. Because scarce clinical data exist to inform decisions at this time, the American Society for Radiation Oncology convened a group of radiation science experts and clinicians to summarize potential issues, review relevant data, and provide guidance for adult patients and their care teams regarding the impact, if any, that genetic testing should have on radiation therapy recommendations. During the American Society for Radiation Oncology workshop, several main points emerged, which are discussed in this manuscript: (1) variants of uncertain significance should be considered nondeleterious until functional genomic data emerge to demonstrate otherwise; (2) possession of germline alterations in a single copy of a gene critical for radiation damage responses does not necessarily equate to increased risk of radiation-induced toxicity; (3) deleterious ataxia-telangiesctasia gene mutations may modestly increase second cancer risk after radiation therapy, and thus follow-up for these patients after indicated radiation therapy should include second cancer screening; (4) conveying to patients the difference between relative and absolute risk is critical to decision-making; and (5) more work is needed to assess the impact of tumor somatic alterations on the probability of response to radiation therapy and the potential for individualization of radiation doses. Data on radiosensitivity related to specific genetic mutations is also briefly discussed.

An open invitation to join the Pediatric Proton/Photon Consortium Registry to standardize data collection in pediatric radiation oncology

OBJECTIVE

The Pediatric Proton/Photon Consortium Registry (PPCR) is a comprehensive data registry composed of pediatric patients treated with radiation. It was established to expedite outcomes-based research. The attributes which allow the PPCR to be a successful collaboration are reviewed.

METHODS AND MATERIALS

Current eligibility criteria are radiotherapy patients < 22 years treated at one of the 15 US participating institutions. Detailed health and treatment data are collected about the disease presentation and treatment exposures, and annually thereafter, in REDCap (Research Electronic Data Capture). DICOM (Digital Imaging and Communications in Medicine) imaging and radiation plans are collected through MIM/MIMcloud. An optional patient-reported quality-of-life (PedsQL) study is administered at 10 sites.

RESULTS

Accrual started October 2012 with 2,775 participants enrolled as of 25 July 2019. Most patients, 62.0%, were treated for central nervous system (CNS) tumors, the most common of which are medulloblastoma (n = 349), ependymoma (n = 309), and glial/astrocytoma tumors (n = 279). The most common non-CNS diagnoses are rhabdomyosarcoma (n = 284), Ewing's sarcoma (n = 153), and neuroblastoma (n = 130). While the majority of participants are US residents, 18.7% come from 36 other countries. Over 685 patients participate in the PedsQL study.

CONCLUSIONS

The PPCR is a valuable research platform capable of answering countless research questions that will ultimately improve patient care. Centers outside of the USA are invited to participate directly or may engage with the PPCR to align data collection strategies to facilitate large-scale international research.

ADVANCES IN KNOWLEDGE

For investigators looking to carry out research in a large pediatric oncology cohort or interested in registry work, this paper provides an updated overview of the PPCR.

Assessing the Training and Research Environment for Genomics, Bioinformatics, and Immunology in Radiation Oncology

PURPOSE

To assess radiation oncologists' perceptions of training and research opportunities in the fields of genomics, bioinformatics, and immunology.

MATERIALS AND METHODS

A 13-item electronic survey was sent to 101 radiation oncology department chairs and administrators. A separate 30-item electronic survey was sent to 132 members of the American Society for Radiation Oncology Science Council as well as to 565 members of the Association of Residents in Radiation Oncology. Survey responses were collected, and results were analyzed using descriptive statistics.

RESULTS

Twenty-six department chairs and 91 general respondents submitted responses. Among general respondents, 69% were current trainees and 31% had completed training. The majority of respondents (92%) were affiliated with an academic/university main campus. Approximately half of respondents (43% to 53%) reported no prior formal training in bioinformatics, genomics, or immunology. More than half of department chairs (54% to 58%) and general respondents (57% to 63%) thought that current training opportunities in these areas were absolutely or moderately insufficient. A majority of respondents (53% to 65%) thought that additional training in these areas would provide opportunity for career advancement, and 80% could identify a current or future research project that additional training in these fields would allow them to pursue. More than half of respondents expressed interest in attending a formal training course, and the majority of department chairs (22 of 26 [85%]) reported that they would probably or definitely send trainees or faculty members to a formal training course.

CONCLUSION

Among radiation oncologists surveyed, there is a perceived lack of current training opportunities in bioinformatics, genomics, and immunology. A majority of respondents reported an interest in obtaining additional training in these areas and believed that training would provide opportunity for career advancement.

Toward a New Framework for Clinical Radiation Biology

Radiation biology has entered the era of precision oncology, and this article reviews time-tested factors that determine the effects of fractionated radiation therapy in a wide variety of tumor types and normal tissues: the association of tumor control with radiation dose, the importance of fractionation and overall treatment time, and the role of tumor hypoxia. Therapeutic gain can only be achieved if the increased tumor toxicity produced by biological treatment modifications is balanced against injury to early-responding and late-responding normal tissues. Developments in precision oncology and immuno-oncology will allow an emphasis on treatment individualization and predictive biomarker development.

Integrative Molecular Characterization of Resistance to Neoadjuvant Chemoradiation in Rectal Cancer

PURPOSE

Molecular properties associated with complete response or acquired resistance to concurrent chemotherapy and radiotherapy (CRT) are incompletely characterized.Experimental Design: We performed integrated whole-exome/transcriptome sequencing and immune infiltrate analysis on rectal adenocarcinoma tumors prior to neoadjuvant CRT (pre-CRT) and at time of resection (post-CRT) in 17 patients [8 complete/partial responders, 9 nonresponders (NR)].

RESULTS

CRT was not associated with increased tumor mutational burden or neoantigen load and did not alter the distribution of established somatic tumor mutations in rectal cancer. Concurrent KRAS/TP53 mutations (KP) associated with NR tumors and were enriched for an epithelial-mesenchymal transition transcriptional program. Furthermore, NR was associated with reduced CD4/CD8 T-cell infiltrates and a post-CRT M2 macrophage phenotype. Absence of any local tumor recurrences, KP/NR status predicted worse progression-free survival, suggesting that local immune escape during or after CRT with specific genomic features contributes to distant progression.

CONCLUSIONS

Overall, while CRT did not impact genomic profiles, CRT impacted the tumor immune microenvironment, particularly in resistant cases.

[Predictive assays for responses of tumors and normal tissues in radiation oncology]

The impact of curative radiotherapy depends mainly on the total dose delivered homogenously in the target volume. Tumor sensitivity to radiotherapy may be particularly inconstant depending on location, histology, somatic genetic parameters and the capacity of the immune system to infiltrate the tumor. In addition, the dose delivered to the surrounding healthy tissues may reduce the therapeutic ratio of many radiation treatments. In a same population treated in one center with the same technique, it appears that individual radiosensitivity clearly exists, namely in terms of late side effects that are in principle non-reversible. This review details the different radiobiological approaches that have been developed to better predict the tumor response but also the radiation-induced late effects.

Evolution of the Supermodel: Progress in Modelling Radiotherapy Response in Mice

Mouse models are essential tools in cancer research that have been used to understand the genetic basis of tumorigenesis, cancer progression and to test the efficacies of anticancer treatments including radiotherapy. They have played a critical role in our understanding of radiotherapy response in tumours and normal tissues and continue to evolve to better recapitulate the underlying biology of humans. In addition, recent developments in small animal irradiators have significantly improved in vivo irradiation techniques, allowing previously unimaginable experimental approaches to be explored in the laboratory. The combination of contemporary mouse models with small animal irradiators represents a major step forward for the radiobiology field in being able to much more accurately replicate clinical exposure scenarios. As radiobiology studies become ever more sophisticated in reflecting developments in the clinic, it is increasingly important to understand the basis and potential limitations of extrapolating data from mice to humans. This review provides an overview of mouse models and small animal radiotherapy platforms currently being used as advanced radiobiological research tools towards improving the translational power of preclinical studies.

Mutational analysis of uterine cervical cancer that survived multiple rounds of radiotherapy

Radiotherapy is an essential component of cancer therapy. Despite advances in cancer genomics, the mutation signatures of radioresistant tumors have not yet been fully elucidated. To address this issue, we analyzed a unique set of clinical specimens from a uterine cervical cancer that repeatedly locally recurred after multiple rounds of radiotherapy. Exon sequencing of 409 cancer-related genes in the treatment-naïve tumor and the tumors that recurred after initial and secondary radiotherapy identified (i) activating mutations in PIK3CA and KRAS, and putative inactivating mutations in SMAD4, as trunk mutation signatures that persisted over the clinical course; and (ii) mutations in KMT2A, TET1, and NLRP1 as acquired mutation signatures observed only in recurrent tumors after radiotherapy. Comprehensive mining of published in vitro genomics data pertaining to radiosensitivity revealed that simultaneous mutations in KRAS and SMAD4, which have not been described previously in uterine cervical cancer, are associated with cancer cell radioresistance. The association between this mutation signature and radioresistance was validated by isogenic cell-based experiments. These results provide proof-of-principle for the analytical pipeline employed in this study, which explores clinically relevant mutation signatures for radioresistance, and demonstrate that this approach is worth pursuing with larger cohorts in the future.

Machine Learning and Radiogenomics: Lessons Learned and Future Directions

Due to the rapid increase in the availability of patient data, there is significant interest in precision medicine that could facilitate the development of a personalized treatment plan for each patient on an individual basis. Radiation oncology is particularly suited for predictive machine learning (ML) models due to the enormous amount of diagnostic data used as input and therapeutic data generated as output. An emerging field in precision radiation oncology that can take advantage of ML approaches is radiogenomics, which is the study of the impact of genomic variations on the sensitivity of normal and tumor tissue to radiation. Currently, patients undergoing radiotherapy are treated using uniform dose constraints specific to the tumor and surrounding normal tissues. This is suboptimal in many ways. First, the dose that can be delivered to the target volume may be insufficient for control but is constrained by the surrounding normal tissue, as dose escalation can lead to significant morbidity and rare. Second, two patients with nearly identical dose distributions can have substantially different acute and late toxicities, resulting in lengthy treatment breaks and suboptimal control, or chronic morbidities leading to poor quality of life. Despite significant advances in radiogenomics, the magnitude of the genetic contribution to radiation response far exceeds our current understanding of individual risk variants. In the field of genomics, ML methods are being used to extract harder-to-detect knowledge, but these methods have yet to fully penetrate radiogenomics. Hence, the goal of this publication is to provide an overview of ML as it applies to radiogenomics. We begin with a brief history of radiogenomics and its relationship to precision medicine. We then introduce ML and compare it to statistical hypothesis testing to reflect on shared lessons and to avoid common pitfalls. Current ML approaches to genome-wide association studies are examined. The application of ML specifically to radiogenomics is next presented. We end with important lessons for the proper integration of ML into radiogenomics.

Radio-pathomic Maps of Epithelium and Lumen Density Predict the Location of High-Grade Prostate Cancer

PURPOSE

This study aims to combine multiparametric magnetic resonance imaging (MRI) and digitized pathology with machine learning to generate predictive maps of histologic features for prostate cancer localization.

METHODS AND MATERIALS

Thirty-nine patients underwent MRI prior to prostatectomy. After surgery, tissue was sliced according to MRI orientation using patient-specific 3-dimensionally printed slicing jigs. Whole-mount sections were annotated by our pathologist and digitally contoured to differentiate the lumen and epithelium. Slides were co-registered to the T2-weighted MRI scan. A learning curve was generated to determine the number of patients required for a stable machine-learning model. Patients were randomly stratified into 2 training sets and 1 test set. Two partial least-squares regression models were trained, each capable of predicting lumen and epithelium density. Predicted density values were calculated for each patient in the test dataset, mapped into the MRI space, and compared between regions confirmed as high-grade prostate cancer.

RESULTS

The learning-curve analysis showed that a stable fit was achieved with data from 10 patients. Maps indicated that regions of increased epithelium and decreased lumen density, generated from each independent model, corresponded with pathologist-annotated regions of high-grade cancer.

CONCLUSIONS

We present a radio-pathomic approach to mapping prostate cancer. We find that the maps are useful for highlighting high-grade tumors. This technique may be relevant for dose-painting strategies in prostate radiation therapy.

Biological characterization of a novel in vitro cell irradiator

To evaluate the overall robustness of a novel cellular irradiator we performed a series of well-characterized, dose-responsive assays to assess the consequences of DNA damage. We used a previously described novel irradiation system and a traditional ¹³⁷Cs source to irradiate a cell line. The generation of reactive oxygen species was assessed using chloromethyl-H₂DCFDA dye, the induction of DNA DSBs was observed using the comet assay, and the initiation of DNA break repair was assessed through γH2AX image cytometry. A high correlation between physical absorbed dose and biologic dose was seen for the production of intracellular reactive oxygen species, physical DNA double strand breaks, and modulation of the cellular double stand break pathway. The results compared favorably to irradiation with a traditional ¹³⁷Cs source. The rapid, straightforward tests described form a reasonable approach for biologic characterization of novel irradiators. These additional testing metrics go beyond standard physics testing such as Monte Carlo simulation and thermo-luminescent dosimeter evaluation to confirm that a novel irradiator can produce the desired dose effects in vitro. Further, assessment of these biological metrics confirms that the physical handling of the cells during the irradiation process results in biologic effects that scale appropriately with dose.