The radiosensitivity of brain metastases based upon primary histology utilizing a multigene index of tumor radiosensitivity

Prediction of radiologic outcome-optimized dose plans and post-treatment magnetic resonance images: A proof-of-concept study in breast cancer brain metastases treated with stereotactic radiosurgery

Background and purpose

Information in multiparametric Magnetic Resonance (mpMR) images is relatable to voxel-level tumor response to Radiation Treatment (RT). We have investigated a deep learning framework to predict (i) post-treatment mpMR images from pre-treatment mpMR images and the dose map ("forward models"), and, (ii) the RT dose map that will produce prescribed changes within the Gross Tumor Volume (GTV) on post-treatment mpMR images ("inverse model"), in Breast Cancer Metastases to the Brain (BCMB) treated with Stereotactic Radiosurgery (SRS).

Materials and methods

Local outcomes, planning computed tomography (CT) images, dose maps, and pre-treatment and post-treatment Apparent Diffusion Coefficient of water (ADC) maps, T1-weighted unenhanced (T1w) and contrast-enhanced (T1wCE), T2-weighted (T2w) and Fluid-Attenuated Inversion Recovery (FLAIR) mpMR images were curated from 39 BCMB patients. mpMR images were co-registered to the planning CT and intensity-calibrated. A 2D pix2pix architecture was used to train 5 forward models (ADC, T2w, FLAIR, T1w, T1wCE) and 1 inverse model on 1940 slices from 18 BCMB patients, and tested on 437 slices from another 9 BCMB patients.

Results

Root Mean Square Percent Error (RMSPE) within the GTV between predicted and ground-truth post-RT images for the 5 forward models, in 136 test slices containing GTV, were (mean ± SD) 0.12 ± 0.044 (ADC), 0.14 ± 0.066 (T2w), 0.08 ± 0.038 (T1w), 0.13 ± 0.058 (T1wCE), and 0.09 ± 0.056 (FLAIR). RMSPE within the GTV on the same 136 test slices, between the predicted and ground-truth dose maps, was 0.37 ± 0.20 for the inverse model.

Conclusions

A deep learning-based approach for radiologic outcome-optimized dose planning in SRS of BCMB has been demonstrated.

A genomic score to predict local control among patients with brain metastases managed with radiation

BACKGROUND

Clinical predictors of local recurrence following radiation among patients with brain metastases (BrM) provide limited explanatory power. We developed a DNA-based signature of radiotherapeutic efficacy among patients with BrM to better characterize recurrence risk.

METHODS

We identified 570 patients with 1487 BrM managed with whole-brain (WBRT) or stereotactic radiation therapy at Brigham and Women's Hospital/Dana-Farber Cancer Institute (2013-2020) for whom next-generation sequencing panel data (OncoPanel) were available. Fine/Gray's competing risks regression was utilized to compare local recurrence on a per-metastasis level among patients with versus without somatic alterations of likely biological significance across 84 genes. Genes with a q-value ≤ 0.10 were utilized to develop a "Brain-Radiation Prediction Score" ("Brain-RPS").

RESULTS

Genomic alterations in 11 (ATM, MYCL, PALB2, FAS, PRDM1, PAX5, CDKN1B, EZH2, NBN, DIS3, and MDM4) and 2 genes (FBXW7 and AURKA) were associated with decreased or increased risk of local recurrence, respectively (q-value ≤ 0.10). Weighted scores corresponding to the strength of association with local failure for each gene were summed to calculate a patient-level RPS. On multivariable Fine/Gray's competing risks regression, RPS [1.66 (1.44-1.91, P < .001)], metastasis-associated edema [1.60 (1.16-2.21), P = .004], baseline size [1.02 (1.01-1.03), P < .001] and receipt of WBRT without local therapy [4.04 (2.49-6.58), P < .001] were independent predictors of local failure.

CONCLUSIONS

We developed a genomic score to quantify local recurrence risk following brain-directed radiation. To the best of our knowledge, this represents the first study to systematically correlate DNA-based alterations with radiotherapeutic outcomes in BrM. If validated, Brain-RPS has potential to facilitate clinical trials aimed at genome-based personalization of radiation in BrM.

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.

Molecular Radiobiology in Non-Small Cell Lung Cancer: Prognostic and Predictive Response Factors

Simple Summary

The identification of prognostic and predictive gene signatures of response to cancer treatment (radiotherapy) could help in making therapeutic decisions in patients affected by NSCLC. There are multiple proposals for gene signatures that attempt to predict survival or predict response to treatment (not radiotherapy), but they mainly focus on early stages or metastasis at diagnosis. In contrast, there have been few studies that raise these predictive and/or prognostic elements in nonmetastatic locally advanced stages, where treatment with ionizing radiation plays an important role. In this work, we review in depth previous works discovering the prognostic and predictive response factors in non-small cell lung cancer, specially focused on non-deeply studied radiation-based therapy.

Abstract

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide, generating huge economic and social impacts that have not slowed in recent years. Oncological treatment for this neoplasm usually includes surgery, chemotherapy, treatments on molecular targets and ionizing radiation. The prognosis in terms of overall survival (OS) and the different therapeutic responses between patients can be explained, to a large extent, by the existence of widely heterogeneous molecular profiles. The identification of prognostic and predictive gene signatures of response to cancer treatment, could help in making therapeutic decisions in patients affected by NSCLC. Given the published scientific evidence, we believe that the search for prognostic and/or predictive gene signatures of response to radiotherapy treatment can significantly help clinical decision-making. These signatures may condition the fractions, the total dose to be administered and/or the combination of systemic treatments in conjunction with radiation. The ultimate goal is to achieve better clinical results, minimizing the adverse effects associated with current cancer therapies.

A Six-Gene Prognostic and Predictive Radiotherapy-Based Signature for Early and Locally Advanced Stages in Non-Small-Cell Lung Cancer

Simple Summary

The search for prognostic and/or predictive gene signatures of the response to radiotherapy treatment can significantly aid clinical decision making. These signatures can condition the fractionation, the total dose to be administered, and/or the combination of systemic treatments and radiation. The ultimate goal is to achieve better clinical results, as well as to minimize the adverse effects associated with current cancer therapies. To this end, we analyzed the intrinsic radiosensitivity of 15 NSCLC lines and found the differences in gene expression levels between radiosensitive and radioresistant lines, resulting in a potentially applicable six-gene signature in NSCLC patients. The six-gene signature had the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received.

Abstract

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death worldwide, generating an enormous economic and social impact that has not stopped growing in recent years. Cancer treatment for this neoplasm usually includes surgery, chemotherapy, molecular targeted treatments, and ionizing radiation. The prognosis in terms of overall survival (OS) and the disparate therapeutic responses among patients can be explained, to a great extent, by the existence of widely heterogeneous molecular profiles. The main objective of this study was to identify prognostic and predictive gene signatures of response to cancer treatment involving radiotherapy, which could help in making therapeutic decisions in patients with NSCLC. To achieve this, we took as a reference the differential gene expression pattern among commercial cell lines, differentiated by their response profile to ionizing radiation (radiosensitive versus radioresistant lines), and extrapolated these results to a cohort of 107 patients with NSCLC who had received radiotherapy (among other therapies). We obtained a six-gene signature (APOBEC3B, GOLM1, FAM117A, KCNQ1OT1, PCDHB2, and USP43) with the ability to predict overall survival and progression-free survival (PFS), which could translate into a prediction of the response to the cancer treatment received. Patients who had an unfavorable prognostic signature had a median OS of 24.13 months versus 71.47 months for those with a favorable signature, and the median PFS was 12.65 months versus 47.11 months, respectively. We also carried out a univariate analysis of multiple clinical and pathological variables and a bivariate analysis by Cox regression without any factors that substantially modified the HR value of the proposed gene signature.

Genomic identification of sarcoma radiosensitivity and the clinical implications for radiation dose personalization

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Soft tissue sarcomas have traditionally been treated with a one-size fits all approach, despite a wide range of histologies and clinical outcomes.

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The radiosensitivity index has demonstrated that soft tissue sarcomas are in general radioresistant, however exhibit a wide range of radiosensitivity.

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These differences in radiosensitivity are associated with decreased locoregional control in patients with radioresistant histologies.

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Using the radiosensitivity index we identify specific histologies of soft tissue sarcoma that may be more radioresistant, and suggest a genomic-based radiation dosing framework.

Background

Soft-tissue sarcomas (STS) are heterogeneous with variable response to radiation therapy (RT). Utilizing the radiosensitivity index (RSI) we estimated the radiobiologic ratio of lethal to sublethal damage (α/β), genomic-adjusted radiation dose(GARD), and in-turn a biological effective radiation dose (BED).

Methods

Two independent cohorts of patients with soft-tissue sarcoma were identified. The first cohort included 217 genomically-profiled samples from our institutional prospective tissue collection protocol; RSI was calculated for these samples, which were then used to dichotomize the population as either highly radioresistant (HRR) or conventionally radioresistant (CRR). In addition, RSI was used to calculate α/β ratio and GARD, providing ideal dosing based on sarcoma genomic radiosensitivity. A second cohort comprising 399 non-metastatic-STS patients treated with neoadjuvant RT and surgery was used to validate our findings.

Results

Based on the RSI of the sample cohort, 84% would historically be considered radioresistant. We identified a HRR subset that had a significant difference in the RSI, and clinically a lower tumor response to radiation (2.4% vs. 19.4%), 5-year locoregional-control (76.5% vs. 90.8%), and lower estimated α/β (3.29 vs. 5.98), when compared to CRR sarcoma. Using GARD, the dose required to optimize outcome in the HRR subset is a BED_α/β=3.29 of 97 Gy.

Conclusions

We demonstrate that on a genomic scale, that although STS is radioresistant overall, they are heterogeneous in terms of radiosensitivity. We validated this clinically and estimated an α/β ratio and dosing that would optimize outcome, personalizing dose.

Will the Use of Biomarkers Improve Bladder Cancer Radiotherapy Delivery?

Advances in the field of cancer biology and molecular techniques have led to a better understanding of the molecular underpinnings driving cancer development and outcomes. Simultaneously, advances in imaging have allowed for improved sensitivity in initial staging, radiotherapy planning and follow-up of numerous cancers. These two phenomena have led to the development of biomarkers that can guide therapy in multiple malignancies. In bladder cancer, there is extensive ongoing research into the identification of biomarkers that can help tailor personalised approaches for treatment based on the intrinsic tumour biology. However, the delivery of bladder cancer radiotherapy as part of trimodality therapy currently has a paucity of biomarkers to guide treatment. Here we summarise the existing literature and ongoing investigations into potential predictive and prognostic molecular and imaging biomarkers that may one day guide selection for utilisation of radiotherapy as part of trimodality therapy, guide selection of the radiosensitising agent, guide radiation dose and target, and guide surveillance for recurrence after trimodality therapy.

Timing of Adjuvant Fractionated Stereotactic Radiosurgery Affects Local Control of Resected Brain Metastases

PURPOSE

For resected brain metastases (BMs), stereotactic radiosurgery (SRS) is often offered to minimize local recurrence (LR). Although the aim is to deliver SRS within a few weeks of surgery, a variety of socioeconomic, medical, and procedural issues can cause delays. We evaluated the relationship between timing of postoperative SRS and LR.

METHODS AND MATERIALS

We retrospectively identified a consecutive series of patients with BM managed with resection and SRS or fractionated SRS at our institution from 2012 to 2018. We assessed the correlation of time to SRS and other demographic, disease, and treatment variables with LR, local recurrence-free survival, distant recurrence, distant recurrence-free survival, and overall survival.

RESULTS

A total of 133 patients met inclusion criteria. The median age was 64.5 years. Approximately half of patients had a single BM, and median BM size was 2.9 cm. Gross total resection was achieved in 111 patients (83.5%), and more than 90% of patients received fractionated SRS. The median time to SRS was 37.0 days, and the LR rate was 16.4%. Time to SRS was predictive of LR. The median time from surgery to SRS was 34.0 days for patients without LR versus 61.0 days for those with LR (P < .01). The LR rate was 2.3% with SRS administered ≤4 weeks postoperatively, compared with 23.6% if SRS was administered >4 weeks postoperatively (P < .01). Local recurrence-free survival was also improved for patients who underwent SRS at ≤4 weeks (P = .02). Delayed SRS was also predictive of distant recurrence (P = .02) but not overall survival.

CONCLUSIONS

In this retrospective study, the strongest predictor of LR after postoperative SRS for BM was time to SRS, and a cutoff of 4 weeks was a reliable predictor of recurrence. These findings merit investigation in a prospective, randomized trial.

Radiotherapy for unresectable locally advanced non-small cell lung cancer: a narrative review of the current landscape and future prospects in the era of immunotherapy

Significant recent advances have occurred in the use of radiation therapy for locally advanced non-small cell lung cancer (LA-NSCLC). In fact, the past few decades have seen both therapeutic gains and setbacks in the evolution of radiotherapy for LA-NSCLC. The PACIFIC trial has heralded a new era of immunotherapy and has raised important questions for future study, such as the future directions of radiation therapy for LA-NSCLC in the era of immunotherapy. Modern radiotherapy techniques such as three-dimensional (3D) conformal radiotherapy and intensity-modulated radiotherapy (IMRT) provide opportunities for improved target conformity and reduced normal-tissue exposure. However, the low-dose radiation volume brought by IMRT and its effects on the immune system deserve particular attention when combing radiotherapy and immunotherapy. Particle radiotherapy offers dosimetric advantages and exhibits great immunoregulatory potential. With the ongoing improvement in particle radiotherapy techniques and knowledge, the combination of immunotherapy and particle radiotherapy has tremendous potential to improve treatment outcomes. Of particular importance are questions on the optimal radiation schedule in the settings of radio-immunotherapy. Strategies for the reduction of the irradiated field such as involved-field irradiation (IFI) and omission of clinical target volume (CTV) hold promise for better preservation of immune function while not compromising locoregional and distant control. In addition, different dose-fractionation regimens can have diverse effects on the immune system. Thus, prospective trials are urgently needed to establish the optimal dose fractionation regimen. Moreover, personalized radiotherapy which allows the tailoring of radiation dose to each individual's genetic background and immune state is of critical importance in maximizing the benefit of radiation to patients with LA-NSCLC.

Outcomes and the Role of Primary Histology Following LINAC-based Stereotactic Radiation for Sarcoma Brain Metastases

OBJECTIVES

The brain is a rare site for sarcoma metastases. Sarcoma's radioresistance also makes standard whole-brain radiotherapy less appealing. We hypothesize that stereotactic radiation techniques (stereotactic radiosurgery [SRS]/stereotactic fractionated radiotherapy [FSRT]) may provide effective local control.

MATERIALS AND METHODS

This single-institution retrospective analysis evaluated our experience with linear acceleator-based SRS/FSRT for sarcoma brain metastases. Time to event analysis was estimated via Kaplan-Meier. Univariable/multivariable Cox regression analyses followed to assess the impact of patient and disease characteristics on outcomes.

RESULTS

Between 2003 and 2018, 24 patients were treated with 34 courses of SRS/FSRT to 58 discrete lesions. The median age at first treatment was 57 years (range: 25 to 87 y). Majority of patients had concurrent lung metastases (n=21; 88%), diagnosed spindle cell sarcoma (n=15; 25%) or leiomyosarcoma (n=12; 21%) histology, and were treated with either SRS (n=43; median dose=19 Gy, range: 15 to 24 Gy) or FSRT (n=17; 3/5 fractions, median dose=25 Gy, range: 25 to 35 Gy). With a median follow-up after brain metastasis of 7.3 months, the 6 month/12 month local control, distant brain control, and overall survival of 89%/89%, 59%/34%, and 50%/38%, respectively. All local failures were of primary spindle cell histology (P<0.001), which was associated with poorer distant control (hazard ratio=25.8, 95% confidence interval: 3.1-536.4; P=0.003) on univariable analysis, and OS (hazard ratio=7.1, 95% confidence interval: 2.0-26.1; P=0.003) on multivariable analysis.

CONCLUSIONS

This is the largest patient cohort with sarcoma brain metastases treated with SRS/FSRT, it provides durable local control, despite a reputation for radioresistance. Further prospective evidence is required to determine the impact of primary histology on control and survival following brain metastasis diagnosis.

Precision radiotherapy for non-small cell lung cancer

Precision medicine is becoming the standard of care in anti-cancer treatment. The personalized precision management of cancer patients highly relies on the improvement of new technology in next generation sequencing and high-throughput big data processing for biological and radiographic information.

Systemic precision cancer therapy has been developed for years. However, the role of precision medicine in radiotherapy has not yet been fully implemented. Emerging evidence has shown that precision radiotherapy for cancer patients is possible with recent advances in new radiotherapy technologies, panomics, radiomics and dosiomics.

This review focused on the role of precision radiotherapy in non-small cell lung cancer and demonstrated the current landscape.

Modeling precision genomic-based radiation dose response in rectal cancer

Aim: Genomic-based risk stratification to personalize radiation dose in rectal cancer. Patients & methods: We modeled genomic-based radiation dose response using the previously validated radiosensitivity index (RSI) and the clinically actionable genomic-adjusted radiation dose. Results: RSI of rectal cancer ranged from 0.19 to 0.81 in a bimodal distribution. A pathologic complete response rate of 21% was achieved in tumors with an RSI <0.31 at a minimal genomic-adjusted radiation dose of 29.76 when modeling RxRSI to the commonly prescribed physical dose of 50 Gy. RxRSI-based dose escalation to 55 Gy in tumors with an RSI of 0.31-0.34 could increase pathologic complete response by 10%. Conclusion: This study provides a theoretical platform for development of an RxRSI-based prospective trial in rectal cancer.

Mathematical oncology and it's application in non melanoma skin cancer - A primer for radiation oncology professionals

Cancers of the skin (the majority of which are basal and squamous cell skin carcinomas, but also include the rarer Merkel cell carcinoma) are overwhelmingly the most common of all types of cancer. Most of these are treated surgically, with radiation reserved for those patients with high risk features or anatomical locations less suitable for surgery. Given the high incidence of both basal and squamous cell carcinomas, as well as the relatively poor outcome for Merkel cell carcinoma, it is useful to investigate the role of other disciplines regarding their diagnosis, staging and treatment. Mathematical modelling is one such area of investigation. The use of mathematical modelling is a relatively recent addition to the armamentarium of cancer treatment. It has long been recognised that tumour growth and treatment response is a complex, non-linear biological phenomenon with many mechanisms yet to be understood. Despite decades of research, including clinical, population and basic science approaches, we continue to be challenged by the complexity, heterogeneity and adaptability of tumours, both in individual patients in the oncology clinic and across wider patient populations. Prospective clinical trials predominantly focus on average outcome, with little understanding as to why individual patients may or may not respond. The use of mathematical models may lead to a greater understanding of tumour initiation, growth dynamics and treatment response.

Is there a role for stereotactic radiotherapy in the treatment of renal cell carcinoma?

Renal cell carcinoma (RCC) has traditionally been regarded as radioresistant tumor based on preclinical data and negative clinical trials using conventional fractionated radiotherapy. However, there is emerging evidence that radiotherapy delivered in few fractions with high single-fraction and total doses may overcome RCC s radioresistance. Stereotactic radiotherapy (SRT) has been successfully used in the treatment of intra- and extracranial RCC metastases showing high local control rates accompanied by low toxicity. Although surgery is standard of care for non-metastasized RCC, a significant number of patients is medically inoperable or refuse surgery. Alternative local approaches such as radiofrequency ablation or cryoablation are invasive and often restricted to small RCC, so that there is a need for alternative local therapies such as stereotactic body radiotherapy (SBRT). Recently, both retrospective and prospective trials demonstrated that SBRT is an attractive treatment alternative for localized RCC. Here, we present a comprehensive review of the published data regarding SBRT for primary RCC. The radiobiological rationale to use higher radiation doses in few fractions is discussed, and technical aspects enabling the safe delivery of SBRT despite intra- and inter-fraction motion and the proximity to organs at risk are outlined.

[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.

The Future of Radiation Oncology in Soft Tissue Sarcoma

Radiotherapy (RT) is an important component of the treatment of soft tissue sarcomas (STS) and has been traditionally incorporated with a homogenous approach despite the reality that STS displays a known heterogeneity in clinicopathologic features and treatment outcomes. In this article, we explore the principle components of personalized medicine, including genomics, radiomics, and treatment response, along with their impact on the future of radiation therapy for STS. We propose a shift in the treatment paradigm for STS from a one-size-fits-all technique to one that implements the tenets of personalized medicine and includes the framework for a potential clinical trial technique in this heterogeneous disease.

Radiosensitivity of Lung Metastases by Primary Histology and Implications for Stereotactic Body Radiation Therapy Using the Genomically Adjusted Radiation Dose

INTRODUCTION

We assessed the radiosensitivity of lung metastases on the basis of primary histologic type by using a validated gene signature and model lung metastases for the gnomically adjusted radiation dose (GARD).

METHODS

Tissue samples were identified from our prospective observational protocol. The radiosensitivity index (RSI) 10-gene assay was run on samples and calculated alongside the GARD by using the previously published algorithms. A cohort of 105 patients with 137 lung metastases treated with stereotactic body radiation therapy (SBRT) at our institution was used for clinical correlation.

RESULTS

A total of 138 unique metastatic lung lesions from our institution's tissue biorepository were identified for inclusion. There were significant differences in the RSI of lung metastases on the basis of histology. In order of decreasing radioresistance, the median RSIs for the various histologic types of cancer were endometrial adenocarcinoma (0.49), soft-tissue sarcoma (0.47), melanoma (0.44), rectal adenocarcinoma (0.43), renal cell carcinoma (0.33), head and neck squamous cell cancer (0.33), colon adenocarcinoma (0.32), and breast adenocarcinoma (0.29) (p = 0.002). We modeled the GARD for these samples and identified the biologically effective dose necessary to optimize local control. The 12- and 24-month Kaplan-Meier rates of local control for radioresistant versus radiosensitive histologic types from our clinical correlation cohort after lung SBRT were 92%/87% and 100%, respectively (p = 0.02).

CONCLUSIONS

In this analysis, we have noted significant differences in radiosensitivity on the basis of primary histologic type of lung metastases and have modeled the biologically effective dose necessary to optimize local control. This study suggests that primary histologic type may be an additional factor to consider in selection of SBRT dose to the lung and that dose personalization may be feasible.