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Abstract Background Over the past decade, the adoption of screening programs, digital mammography, and magnetic resonance imaging (MRI) has increased early-stage breast cancer diagnosis rates. Mortality rates have decreased due to early detection and improved treatments, including personalized therapies. Accelerated partial-breast irradiation (APBI) is emerging as a convenient and effective treatment for some patients, with studies exploring its preoperative use. Preoperative APBI, especially with MRI guidance, offers improved tumor targeting and potentially reduced side effects. Magnetic Resonance Imaging-Guided Single-Fraction Pre-Operative Radiotherapy for Early-Stage Breast Cancer (RICE trial) aims to assess the feasibility and efficacy of MRI-guided single-dose radiotherapy (RT) for early-stage breast cancer. Methods The RICE study is a prospective, single-arm study evaluating single-fraction preoperative, APBI treatment for patients with early-stage breast cancer using a magnetic resonance imaging linear accelerator (MRI linac). Eligible patients enrolled in this study will have a core biopsy to confirm estrogen receptor-positive and HER2-negative sub-type. RT planning will use a planning computed tomography (CT) co-registered with a MRI with the patient in either the supine or prone position. For the diagnostic workup, [18F] fluorodeoxyglucose positron emission tomography/CT ([18F] FDG PET/CT) and [18F] fluoroestradiol positron emission tomography/CT ([18F] FES PET/CT) will be performed prior to treatment. Thirty patients will receive a single ablative RT dose of 21 Gray to the tumor. Pre-treatment and post-treatment MRI scans will be acquired at baseline and 5 weeks post-RT respectively. Breast-conserving surgery will be scheduled for 6 weeks after APBI treatment using the MRI linac. The primary study endpoint is the successful administration of a single fraction of preoperative breast RT under the guidance of an MRI linac. Secondary endpoints include evaluating the utility of MRI, [18F] FDG PET/CT, and [18F] FES PET/CT as a non-invasive method for assessing treatment response in patients undergoing single-fraction preoperative APBI. Conclusion The RICE trial represents a significant step in breast cancer treatment, offering insights that could lead to treatment protocols with minimized RT appointments and enhanced patient outcomes. Trial registration This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR). Registered 31st of May 2021. Registration number: ACTRN12621000659808 .

Purpose: We previously demonstrated that 12 months of aromatase inhibitor (AI) treatment was not associated with a difference in body compositi on or other markers of cardiometabolic health when compared to controls. Here we report on the pre-planned extension of the study. The pre-specified primary hypothesis was that AI therapy for 24 months would lead to increased visceral adipose tissue (VAT) area when compared to controls. Methods: We completed a 12-month extension to our prospective 12-month cohort study of 52 women commencing AI treatment (median age 64.5 years) and 52 women with breast pathology not requiring endocrine therapy (63.5 years). Our primary outcome of interest was VAT area. Secondary and exploratory outcomes included other measures of body composition, hepatic steatosis, measures of atherosclerosis and vascular reactivity. Using mixed models and the addition of a fourth time point, we increased the number of study observations by 79 and were able to rigorously determine the treatment effect. Results: Among study completers (AI = 39, controls = 40), VAT area was comparable between groups over 24 months, the mean-adjusted difference was −1.54 cm2 (95% CI: −14.9; 11.9, P = 0.79). Both groups demonstrated parallel and continuous increa ses in VAT area over the observation period that did not diverge or change between groups. No statistically significant difference in our secondary and expl oratory outcomes was observed between groups. Conclusions: While these findings provide reassurance that short-to-medium-term exposure to AI therapy is not associated with metabolically adverse changes when compared to controls, risk evolution should be less focussed on the AI-asso ciated effect and more on the general development of cardiovascular risk over time.

Abstract Background Malignant pleural effusions (MPEs) are a common complication of advanced cancers, particularly those adjacent to the pleura, such as lung and breast cancer. The pathophysiology of MPE formation remains poorly understood, and although MPEs are routinely used for the diagnosis of breast cancer patients, their composition and biology are poorly understood. It is difficult to distinguish invading malignant cells from resident mesothelial cells and to identify the directionality of interactions between these populations in the pleura. There is a need to characterize the phenotypic diversity of breast cancer cell populations in the pleural microenvironment, and investigate how this varies across patients. Methods Here, we used single‐cell RNA‐sequencing to study the heterogeneity of 10 MPEs from seven metastatic breast cancer patients, including three Miltenyi‐enriched samples using a negative selection approach. This dataset of almost 65 000 cells was analysed using integrative approaches to compare heterogeneous cell populations and phenotypes. Results We identified substantial inter‐patient heterogeneity in the composition of cell types (including malignant, mesothelial and immune cell populations), in expression of subtype‐specific gene signatures and in copy number aberration patterns, that captured variability across breast cancer cell populations. Within individual MPEs, we distinguished mesothelial cell populations from malignant cells using key markers, the presence of breast cancer subtype expression patterns and copy number aberration patterns. We also identified pleural mesothelial cells expressing a cancer‐associated fibroblast‐like transcriptomic program that may support cancer growth. Conclusions Our dataset presents the first unbiased assessment of breast cancer‐associated MPEs at a single cell resolution, providing the community with a valuable resource for the study of MPEs. Our work highlights the molecular and cellular diversity captured in MPEs and motivates the potential use of these clinically relevant biopsies in the development of targeted therapeutics for patients with advanced breast cancer.

Cancer derived exosomes are reported to promote metastatic dissemination. Here the authors show that cytokines in the tumor microenvironment bind to exosomes via glycosaminoglycan side chains of proteoglycans, and these exosomes are preferentially taken up by specific cell lineages and organs to promote metastasis.

Purpose: To determine the diagnostic parameters of breast ultrasound (US) in the setting of routine radiological surveillance after a diagnosis of breast cancer and evaluate costs of the inclusion of breast US as well as any survival benefit of US detected cases of recurrence in surveillance. Methods: 622 patients underwent breast cancer surgery and follow up at Austin Health from July 2009 to December 2015. Retrospective data analysis was performed to determine; diagnostic parameters, financial costs of US and survival outcomes of US detected cases of recurrence. Results: Patients underwent 1–9 years of breast cancer surveillance, with a median of 4.24 years. 390 (62.7%) patients underwent additional breast US surveillance to mammography. 232 (38.3%) fit criteria for use of additional breast US. 199 abnormal imaging episodes occurred, leading to 16 screen detected-cases of locoregional recurrence. US alone generated 107 abnormal images and found 9 cancers. US had a sensitivity of 44.1%, specificity of 95.2% and positive predictive value of 11.7% in comparison to mammography; 20.6%, 97.4% and 9.9% respectively. US had a biopsy rate of 4.0% and lead to an incremental cancer detection rate of 0.38%. The cost of incremental cancer found was $31,463.72 AUD. Survival outcomes based on method of detection of recurrence were insignificant (p value = 0.71). Conclusions: Breast US has a sensitivity of 44.1% and detected seven recurrences that were mammographically occult. Breast US has a similar PPV to mammography in surveillance. Breast US generated considerable biopsy rates and costs. Survival analysis was not able to detect any benefit of US detected cases of recurrence.

Abstract Background Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0–5-year and 5–10-year follow-up separately are more prognostic than a single signature optimised for 10 years. Methods Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2− samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2− tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0–10, 0–5 and 5–10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449. Results Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set. Conclusions The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2− breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected.

Unravelling the link between somatic mutation and prognosis in estrogen positive (ER+) breast cancer requires the use of long-term follow-up data. Here, combining archival formalin-fixed paraffin embedded tissue and targeted sequencing in three cohorts of ER+ breast cancer, the authors find associations with clinical outcome for NF1 frame-shift nonsense mutations, PIK3R1 mutation, and DDR1 mutations.

Inflammatory breast cancer is a rare, yet highly aggressive form of breast cancer, which accounts for less than 5% of all locally advanced presentations. The clinical presentation of inflammatory breast cancer often differs significantly from that of noninflammatory breast cancer; however, immunohistochemistry reveals few, if any, distinguishing features. The more aggressive triple-negative and HER2-positive breast cancer subtypes are overrepresented in inflammatory breast cancer compared with noninflammatory breast cancer, with a poorer prognosis in response to conventional therapies. Despite its name, there remains some controversy regarding the role of inflammation in inflammatory breast cancer. This review summarises the current molecular evidence suggesting that inflammatory signaling pathways are upregulated in this disease, including NF-κB activation and excessive IL-6 production among others, which may provide an avenue for novel therapeutics. The role of the tumor microenvironment, through tumor-associated macrophages, infiltrating lymphocytes, and cancer stem cells is also discussed, suggesting that these tumor extrinsic factors may help account for the differences in behavior between inflammatory breast cancer and noninflammatory breast cancer. While there are various novel treatment strategies already underway in clinical trials, the need for further development of preclinical models of this rare but aggressive disease is paramount.

The original version of this Article contained errors in the depiction of confidence intervals in the NF1 BCSS data illustrated in Figure 3b. These have now been corrected in both the PDF and HTML versions of the Article. The incorrect version of Figure 3b is presented in the associated Author Correction.