Neoadjuvant radiotherapy in ER+, HER2+, and triple-negative -specific breast cancer based humanized tumor mice enhances anti-PD-L1 treatment efficacy.

Pre-operative radiation therapy is not currently integrated into the treatment protocols for breast cancer. However, transforming immunological "cold" breast cancers by neoadjuvant irradiation into their "hot" variants is supposed to elicit an endogenous tumor immune defense and, thus, enhance immunotherapy efficiency. We investigated cellular and immunological effects of sub-lethal, neoadjuvant irradiation of ER pos., HER2 pos., and triple-negative breast cancer subtypes in-vitro and in-vivo in humanized tumor mice (HTM). This mouse model is characterized by a human-like immune system and therefore facilitates detailed analysis of the mechanisms and efficiency of neoadjuvant, irradiation-induced "in-situ vaccination", especially in the context of concurrently applied checkpoint therapy. Similar to clinical appearances, we observed a gradually increased immunogenicity from the luminal over the HER2-pos. to the triple negative subtype in HTM indicated by an increasing immune cell infiltration into the tumor tissue. Anti-PD-L1 therapy divided the HER2-pos. and triple negative HTM groups into responder and non-responder, while the luminal HTMs were basically irresponsive. Irradiation alone was effective in the HER2-pos. and luminal subtype-specific HTM and was supportive for overcoming irresponsiveness to single anti-PD-L1 treatment. The treatment success correlated with a significantly increased T cell proportion and PD-1 expression in the spleen. In all subtype-specific HTM combination therapy proved most effective in diminishing tumor growth, enhancing the immune response, and converted non-responder into responder during anti-PD-L1 therapy. In HTM, neoadjuvant irradiation reinforced anti-PD-L1 checkpoint treatment of breast cancer in a subtype -specific manner. According to the "bench to bedside" principle, this study offers a vital foundation for clinical translating the use of neoadjuvant irradiation in the context of checkpoint therapy.

A dosiomics model for prediction of radiation-induced acute skin toxicity in breast cancer patients: machine learning-based study for a closed bore linac.

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals. METHODS: Dosiomics features extracted using Pyradiomics tool (v3.0.1), along with treatment plan-derived dose volume histograms (DVHs), and patient-specific treatment-related (PTR) data of breast cancer patients were used for modeling. Clinical scoring was done using the Common Terminology Criteria for Adverse Events (CTCAE) V4.0 criteria for skin-specific symptoms. The 52 breast cancer patients were grouped into AST 2 + (CTCAE ≥ 2) and AST 2 - (CTCAE < 2) toxicity grades to facilitate AST modeling. They were randomly divided into training (70%) and testing (30%) cohorts. Multiple prediction models were assessed through multivariate analysis, incorporating different combinations of feature groups (dosiomics, DVH, and PTR) individually and collectively. In total, seven unique combinations, along with seven classification algorithms, were considered after feature selection. The performance of each model was evaluated on the test group using the area under the receiver operating characteristic curve (AUC) and f1-score. Accuracy, precision, and recall of each model were also studied. Statistical analysis involved features differences between AST 2 - and AST 2 + groups and cutoff value calculations. RESULTS: Results showed that 44% of the patients developed AST 2 + after Tomotherapy. The dosiomics (DOS) model, developed using dosiomics features, exhibited a noteworthy improvement in AUC (up to 0.78), when spatial information is preserved in the dose distribution, compared to DVH features (up to 0.71). Furthermore, a baseline ML model created using only PTR features for comparison with DOS models showed the significance of dosiomics in early AST prediction. By employing the Extra Tree (ET) classifiers, the DOS + DVH + PTR model achieved a statistically significant improved performance in terms of AUC (0.83; 95% CI 0.71-0.90), accuracy (0.70), precision (0.74) and sensitivity (0.72) compared to other models. CONCLUSIONS: This study confirmed the benefit of dosiomics-based ML in the prediction of AST. However, the combination of dosiomics, DVH, and PTR yields significant improvement in AST prediction. The results of this study provide the opportunity for timely interventions to prevent the occurrence of radiation induced AST.

Biological effects of intraoperative radiation therapy: histopathological changes and immunomodulation in breast cancer patients.

Introduction: Intraoperative radiation therapy (IORT) delivers a single accelerated radiation dose to the breast tumor bed during breast-conserving surgery (BCS). The synergistic biologic effects of simultaneous surgery and radiation remain unclear. This study explores the cellular and molecular changes induced by IORT in the tumor microenvironment and its impact on the immune response modulation. Methods: Patients with hormone receptor (HR)-positive/HER2-negative, ductal carcinoma in situ (DCIS), or early-stage invasive breast carcinoma undergoing BCS with margin re-excision were included. Histopathological evaluation and RNA-sequencing in the re-excision tissue were compared between patients with IORT (n=11) vs. non-IORT (n=11). Results: Squamous metaplasia with atypia was exclusively identified in IORT specimens (63.6%, p=0.004), mimicking DCIS. We then identified 1,662 differentially expressed genes (875 upregulated and 787 downregulated) between IORT and non-IORT samples. Gene ontology analyses showed that IORT was associated with the enrichment of several immune response pathways, such as inflammatory response, granulocyte activation, and T-cell activation (p<0.001). When only considering normal tissue from both cohorts, IORT was associated with intrinsic apoptotic signaling, response to gamma radiation, and positive regulation of programmed cell death (p<0.001). Using the xCell algorithm, we inferred a higher abundance of γδ T-cells, dendritic cells, and monocytes in the IORT samples. Conclusion: IORT induces histological changes, including squamous metaplasia with atypia, and elicits molecular alterations associated with immune response and intrinsic apoptotic pathways. The increased abundance of immune-related components in breast tissue exposed to IORT suggests a potential shift towards active immunogenicity, particularly immune-desert tumors like HR-positive/HER2-negative breast cancer.

Perceived control, self-management efficacy, and quality of life in patients treated with radiation therapy for breast cancer: a longitudinal study.

OBJECTIVE: This longitudinal study aims to examine the present state of perceived control, self-management efficacy, and overall quality of life (QoL) in patients with breast cancer undergoing radiotherapy, and gain insight into the dynamic trends and factors that influence the quality of life experienced by patients during the course of radiotherapy. METHODS: Participants completed the Cancer Experience and Efficacy Scale (CEES), Strategies Used by People to Promote Health (SUPPH), and Functional Assessment of Cancer Therapy- Breast (FACT-B). The data was analyzed using the software SPSS26.0. Repeated measures analysis of variance (ANOVA) and mixed-effects linear models were used to analyze trends in perceived control, self-management efficacy, and QoL at three-time points, as well as factors affecting QoL during radiotherapy. RESULTS: Perceived control and self-management efficacy were associated with QoL over the course of the radiotherapy. Self-management efficacy (ß = 0.30, P < 0.001), presence of chemotherapy (ß = 18.33, P = 0.024), and duration of illness (ß = 2.25, P = 0.028) had a positive effect on the change in QoL, while time (ß = - 2.95, P < 0.001), cancer experience (ß = - 0.46, P < 0.001), and type of medical insurance (ß = - 2.77, P = 0.021) had the negative effect on the change in QoL. CONCLUSION: The QoL, perceived control, and self-efficacy of patients with breast cancer show dynamic changes during radiotherapy. The higher the self-efficacy, the better the QoL, and the worse the QoL when the sense of disease control is poor. At the same time, more attention should be paid to the QoL of breast cancer radiotherapy patients with a long course of the disease, receiving chemotherapy, and different medical payment methods.

Automated treatment planning for whole breast irradiation with individualized tangential IMRT fields.

PURPOSES: This study aimed to develop and validate algorithms for automating intensity modulated radiation therapy (IMRT) planning in breast cancer patients, with a focus on patient anatomical characteristics. MATERIAL AND METHODS: We retrospectively selected 400 breast cancer patients without lymph node involvement for automated treatment planning. Automation was achieved using the Eclipse Scripting Application Programming Interface (ESAPI) integrated into the Eclipse Treatment Planning System. We employed three beam insertion geometries and three optimization strategies, resulting in 3600 plans, each delivering a 40.05 Gy dose in 15 fractions. Gantry angles in the tangent fields were selected based on a criterion involving the minimum intersection area between the Planning Target Volume (PTV) and the ipsilateral lung in the Beam's Eye View projection. ESAPI was also used to gather patient anatomical data, serving as input for Random Forest models to select the optimal plan. The Random Forest classification considered both beam insertion geometry and optimization strategy. Dosimetric data were evaluated in accordance with the Radiation Therapy Oncology Group (RTOG) 1005 protocol. RESULTS: Overall, all approaches generated high-quality plans, with approximately 94% meeting the acceptable dose criteria for organs at risk and/or target coverage as defined by RTOG guidelines. Average automated plan generation time ranged from 6 min and 37 s to 9 min and 22 s, with the mean time increasing with additional fields. The Random Forest approach did not successfully enable automatic planning strategy selection. Instead, our automated planning system allows users to choose from the tested geometry and strategy options. CONCLUSIONS: Although our attempt to correlate patient anatomical features with planning strategy using machine learning tools was unsuccessful, the resulting dosimetric outcomes proved satisfactory. Our algorithm consistently produced high-quality plans, offering significant time and efficiency advantages.

The Japanese breast cancer society clinical practice guidelines for radiation treatment of breast cancer, 2022 edition.

The Breast Cancer Clinical Practice Guidelines, organized by the Japanese Breast Cancer Society (JBCS), were published in 2022. We present the English version of the Radiation Therapy (RT) section of the guidelines. The JBCS formed a task force to update the 2018 version of the JBCS Clinical Practice Guidelines. The Background Questions (BQs) contain the standard treatments for breast cancer in clinical practice, whereas the Clinical Questions (CQs) address daily clinical questions that remain controversial. Future Research Questions (FRQs) explore the subjects that are considered important issues, despite there being insufficient data for inclusion as CQs. The task force selected the 12 BQs, 8 CQs, and 6 FRQs for the RT section. For each CQ, systematic literature reviews and meta-analyses were conducted according to the Minds Manual for Guideline Development 2020, version 3.0. The recommendations, strength of recommendation, and strength of evidence for each CQ were determined based on systematic reviews and meta-analyses, and finalized by voting at the recommendation decision meeting.

A comparative study in left-sided breast cancer treated with moderate deep inspiratory breath hold versus free breathing.

BACKGROUND: The moderate deep inspiratory breath hold (mDIBH) is a modality famed for cardiac sparing. Prospective studies based on this are few from the eastern part of the world and India. We intend to compare the dosimetry between mDIBH and free-breathing (FB) plans. METHODS: Thirty-two locally advanced left breast cancer patients were taken up for the study. All patients received a dose of 50 Gy in 25 fractions to the chest wall/intact breast, followed by a 10-Gy boost to the lumpectomy cavity in the case of breast conservation surgery. All the patients were treated in mDIBH using active breath coordinator (ABC). The data from the two dose volume histograms were compared regarding plan quality and the doses received by the organs at risk. Paired t-test was used for data analysis. RESULTS: The dose received by the heart in terms of V5, V10, and V30 (4.55% vs 8.39%) and mean dose (4.73 Gy vs 6.74 Gy) were statistically significant in the ABC group than that in the FB group (all p-values < 0.001). Also, the dose received by the LADA in terms of V30 (19.32% vs 24.87%) and mean dose (32.99 Gy vs 46.65 Gy) were significantly less in the ABC group. The mean treatment time for the ABC group was 20 min, while that for the free-breathing group was 10 min. CONCLUSIONS: Incorporating ABC-mDIBH for left-sided breast cancer radiotherapy significantly reduces the doses received by the heart, LADA, and left and right lung, with no compromise in plan quality but with an increase in treatment time.

Deep learning for high-resolution dose prediction in high dose rate brachytherapy for breast cancer treatment.

Objective.Monte Carlo (MC) simulations are the benchmark for accurate radiotherapy dose calculations, notably in patient-specific high dose rate brachytherapy (HDR BT), in cases where considering tissue heterogeneities is critical. However, the lengthy computational time limits the practical application of MC simulations. Prior research used deep learning (DL) for dose prediction as an alternative to MC simulations. While accurate dose predictions akin to MC were attained, graphics processing unit limitations constrained these predictions to large voxels of 3 mm × 3 mm × 3 mm. This study aimed to enable dose predictions as accurate as MC simulations in 1 mm × 1 mm × 1 mm voxels within a clinically acceptable timeframe.Approach.Computed tomography scans of 98 breast cancer patients treated with Iridium-192-based HDR BT were used: 70 for training, 14 for validation, and 14 for testing. A new cropping strategy based on the distance to the seed was devised to reduce the volume size, enabling efficient training of 3D DL models using 1 mm × 1 mm × 1 mm dose grids. Additionally, novel DL architecture with layer-level fusion were proposed to predict MC simulated dose to medium-in-medium (Dm,m). These architectures fuse information from TG-43 dose to water-in-water (Dw,w) with patient tissue composition at the layer-level. Different inputs describing patient body composition were investigated.Main results.The proposed approach demonstrated state-of-the-art performance, on par with the MCDm,mmaps, but 300 times faster. The mean absolute percent error for dosimetric indices between the MC and DL-predicted complete treatment plans was 0.17% ± 0.15% for the planning target volumeV100, 0.30% ± 0.32% for the skinD2cc, 0.82% ± 0.79% for the lungD2cc, 0.34% ± 0.29% for the chest wallD2ccand 1.08% ± 0.98% for the heartD2cc.Significance.Unlike the time-consuming MC simulations, the proposed novel strategy efficiently converts TG-43Dw,wmaps into preciseDm,mmaps at high resolution, enabling clinical integration.

Radiation for inflammatory breast cancer: Updates.

Inflammatory breast cancer (IBC) is a diagnosis based on a constellation of clinical features of edema (peau d'orange) of a third or more of the skin of the breast with a palpable border and a rapid onset of breast erythema. Incidence of IBC has increased over time, although it still makes up only 1-4% of all breast cancer diagnoses. Despite recent encouraging data on clinical outcomes, the published local-regional control rates remain consistently lower than the rates for non-IBC. In this review, we focus on radiotherapy, provide a framework for multi-disciplinary care for IBC, describe local-regional treatment techniques for IBC; highlight new directions in the management of patients with metastatic IBC and offer an introduction to future directions regarding the optimal treatment and management of IBC.

Cost-effectiveness of intraoperative radiation therapy versus intensity-modulated radiation therapy for the treatment of early breast cancer: a disinvestment analysis.

BACKGROUND: Adjuvant radiotherapy represents a key component in curative-intent treatment for early-stage breast cancer patients. In recent years, two accelerated partial breast irradiation (APBI) techniques are preferred for this population in our organization: electron-based Intraoperative radiation therapy (IORT) and Linac-based External Beam Radiotherapy, particularly Intensity-modulated radiation therapy (IMRT). Recently published long-term follow-up data evaluating these technologies have motivated a health technology reassessment of IORT compared to IMRT. METHODS: We developed a Markov model to simulate health-state transitions from a cohort of women with early-stage breast cancer, after lumpectomy and adjuvant APBI using either IORT or IMRT techniques. The cost-effectiveness from a private health provider perspective was assessed from a disinvestment point of view, using life-years (LYs) and recurrence-free life-years (RFLYs) as measure of benefits, along with their respective quality adjustments. Expected costs and benefits, and the incremental cost-effectiveness ratio (ICER) were reported. Finally, a sensitivity and scenario analyses were performed to evaluate the cost-effectiveness using lower IORT local recurrence and metastasis rates in IORT patients, and if equipment maintenance costs are removed. RESULTS: IORT technology was dominated by IMRT in all cases (i.e., fewer benefits with greater costs). Despite small differences were found regarding benefits, especially for LYs, costs were considerably higher for IORT. For sensitivity analyses with lower recurrence and metastasis rates for IORT, and scenario analyses without equipment maintenance costs, IORT was still dominated by IMRT. CONCLUSIONS: For this cohort of patients, IMRT was, at least, non-inferior to IORT in terms of expected benefits, with considerably lower costs. As a result, IORT disinvestment should be considered, favoring the use of IMRT in these patients.

Proapoptotic effects of ceranib-2 in combination with radiation therapy on human breast cancer cells.

OBJECTIVE: Strategies for cancer therapy involve radiation therapy (RT), which accounts for about 40% of all cancer treatment types. As to current chemotherapeutics, cancer cells also develop resistance that remains a clinical problem, such as disease recurrence. Recent studies focused on understanding the molecular mechanisms of radiation-induced cell death. Conventional RT aims at treatment with a single fraction per day of 8-30 Gy per fraction. Radiotherapy increases intracellular ceramide levels that trigger cell death. Additionally, increasing intracellular ceramide by radiation may restore therapeutic sensitivity to cancer treatments. Drugs that inhibit ceramide-metabolizing enzymes like ceramidases are expected to be radiotherapy sensitizers. MATERIALS AND METHODS: In this research, we investigated the proapoptotic effects of SRS alone and in combination with ceranib-2, a ceramidase inhibitor in human breast adenocarcinoma cells. The molecular mechanism of action of RT and ceranib-2 was investigated on MCF-7 cells exposed to 13 µM ceranib-2 for 24 hours following 20 Gy radiation using MTT, radiotherapy, and annexin-V analyses. RESULTS: Results indicated that the dose of 20 Gy radiation induces apoptosis on human breast cancer cells with and without co-treatment with ceranib-2 by causing cytotoxicity in the cells. Based on the results of ceranib-2 exposure, it can be concluded that the mechanism of action may rely on an increase of intracellular ceramides, also called apoptotic lipids. CONCLUSIONS: The study results suggest that co-treatment of human breast adenocarcinoma cells with a ceramidase inhibitor, ceranib-2, and a high dose of radiation of 20 Gy exerted cytotoxicity and apoptosis and might be a solid, potent alternative to current therapy strategies.

Proton Beam Therapy for Breast Cancer.

Given the radiobiological and physical properties of the proton, proton beam therapy has the potential to be advantageous for many patients compared with conventional radiotherapy by limiting toxicity and improving patient outcomes in specific breast cancer scenarios.