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Stomatitis is a class effect associated with the inhibition of mTOR and is associated with everolimus therapy for breast cancer. Topical steroids might reduce stomatitis incidence and severity, and the need for dose reductions and interruptions of everolimus. Anecdotal use of topical steroid oral prophylaxis has been reported in patients with breast cancer. We aimed to assess dexamethasone-based mouthwash for prevention of stomatitis in patients with breast cancer. This US-based, multicentre, single-arm, phase 2 prevention study enrolled women aged 18 years and older with postmenopausal status who had histologically or cytologically confirmed metastatic hormone receptor-positive, HER2-negative breast cancer. Beginning on day 1 of cycle 1, patients received everolimus 10 mg plus exemestane 25 mg daily, with 10 mL of alcohol-free dexamethasone 0·5 mg per 5 mL oral solution (swish for 2 min and spit, four times daily for 8 weeks). After 8 weeks, dexamethasone mouthwash could be continued for up to eight additional weeks at the discretion of the clinician and patient. The primary endpoint was incidence of grade 2 or worse stomatitis by 8 weeks assessed in the full analysis set (patients who received at least one dose of everolimus and exemestane and at least one confirmed dose of dexamethasone mouthwash) versus historical controls from the BOLERO-2 trial (everolimus and exemestane treatment in patients with hormone receptor-positive advanced breast cancer who were not given dexamethasone mouthwash for prevention of stomatitis). This trial is registered at ClinicalTrials.gov, number NCT02069093. Between May 28, 2014, and Oct 8, 2015, we enrolled 92 women; 85 were evaluable for efficacy. By 8 weeks, the incidence of grade 2 or worse stomatitis was two (2%) of 85 patients (95% CI 0·29–8·24), versus 159 (33%) of 482 patients (95% CI 28·8–37·4) for the duration of the BOLERO-2 study. Overall, 83 (90%) of 92 patients had at least one adverse event. The most frequently reported grade 3 and 4 adverse events in the safety set were hyperglycaemia (seven [8%] of 92 patients), rash (four [4%]), and dyspnoea (three [3%]). Serious adverse events were reported in 20 (22%) patients; six (7%) were deemed treatment related, with dyspnoea (three [3%]) and pneumonia (two [2%]) reported most frequently. 12 (13%) of 92 patients had adverse events suspected to be related to treatment that led to discontinuation of everolimus and exemestane (the most common were rash, hyperglycaemia, and stomatitis, which each affected two [2%] patients). Prophylactic use of dexamethasone oral solution substantially reduced the incidence and severity of stomatitis in patients receiving everolimus and exemestane and could be a new standard of oral care for patients receiving everolimus and exemestane therapy. Novartis Pharmaceuticals Corporation.

Background Our group previously published data showing that patients could be stratified by constructed molecular subtype with respect to locoregional recurrence (LRR)-free survival after neoadjuvant chemotherapy and breast-conserving therapy (BCT). That study predated use of trastuzumab for human epidermal growth factor receptor 2 (HER2)-positive patients. The current study was undertaken to determine the impact of subtype and response to therapy in a contemporary cohort. Methods Clinicopathologic data from 751 breast cancer patients who received neoadjuvant chemotherapy (with trastuzumab if HER2 + ) and BCT from 2005 to 2012 were identified. Hormone receptor (HR) and HER2 status were used to construct molecular subtypes: HR + /HER2 − ( n  = 369), HR + /HER2 + ( n  = 105), HR − /HER2 + ( n  = 58), and HR − /HER2 − ( n  = 219). Actuarial rates of LRR were determined by the Kaplan–Meier method and compared by the log-rank test. Multivariate analysis was performed to determine factors associated with LRR. Results The pathologic complete response (pCR) rates by subtype were as follows: 16.5 % (HR + /HER2 − ), 45.7 % (HR + /HER2 + ), 72.4 % (HR − /HER2 + ), and 42.0 % (HR − /HER2 − ) ( P  < 0.001). Median follow-up was 4.6 years. The 5-year LRR-free survival rate for all patients was 95.4 %. Five-year LRR-free survival rates by subtype were 97.2 % (HR + /HER2 − ), 96.1 % (HR + /HER2 + ), 94.4 % (HR − /HER2 + ), and 93.4 % (HR − /HER2 − ) ( P  = 0.44). For patients with HR − /HER2 + disease, the LRR-free survival rates were 97.4 and 86.7 % for those who did and those who did not experience pCR, respectively. For patients with HR − /HER2 − disease, the LRR-free survival rates were 98.6 % (pCR) versus 89.9 % (no pCR). On multivariate analysis, the HR − /HER2 − subtype, clinical stage III disease, and failure to experience a pCR were associated with LRR. Conclusions Patients undergoing BCT after neoadjuvant chemotherapy have excellent rates of 5-year LRR-free survival that are affected by molecular subtype and by response to neoadjuvant chemotherapy.

Purpose AE37 and GP2 are HER2 derived peptide vaccines. AE37 primarily elicits a CD4+ response while GP2 elicits a CD8+ response against the HER2 antigen. These peptides were tested in a large randomized trial to assess their ability to prevent recurrence in HER2 expressing breast cancer patients. The primary analyses found no difference in 5-year overall disease-free survival (DFS) but possible benefit in subgroups. Here, we present the final landmark analysis. Methods In this 4-arm, prospective, randomized, single-blinded, multi-center phase II trial, disease-free node positive and high-risk node negative breast cancer patients enrolled after standard of care therapy. Six monthly inoculations of vaccine (VG) vs. control (CG) were given as the primary vaccine series with 4 boosters at 6-month intervals. Demographic, safety, immunologic, and DFS data were evaluated. Results 456 patients were enrolled; 154 patients in the VG and 147 in CG for AE37, 89 patients in the VG and 91 in CG for GP2. The AE37 arm had no difference in DFS as compared to CG, but pre-specified exploratory subgroup analyses showed a trend towards benefit in advanced stage ( p  = 0.132, HR 0.573 CI 0.275–1.193), HER2 under-expression ( p  = 0.181, HR 0.756 CI 0.499–1.145), and triple-negative breast cancer ( p  = 0.266, HR 0.443 CI 0.114–1.717). In patients with both HER2 under-expression and advanced stage, there was significant benefit in the VG ( p  = 0.039, HR 0.375 CI 0.142–0.988) as compared to CG. The GP2 arm had no significant difference in DFS as compared to CG, but on subgroup analysis, HER2 positive patients had no recurrences with a trend toward improved DFS ( p  = 0.052) in VG as compared to CG. Conclusions This phase II trial reveals that AE37 and GP2 are safe and possibly associated with improved clinical outcomes of DFS in certain subgroups of breast cancer patients. With these findings, further evaluations are warranted of AE37 and GP2 vaccines given in combination and/or separately for specific subsets of breast cancer patients based on their disease biology.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently standard of care for TNBC with 50-60% of patients achieving pathologic complete response (pCR). We investigated ability of deep learning (DL) on dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging acquired early during NAST to predict TNBC patients’ pCR status in the breast. During the development phase using the images of 130 TNBC patients, the DL model achieved areas under the receiver operating characteristic curves (AUCs) of 0.97 ± 0.04 and 0.82 ± 0.10 for the training and the validation, respectively. The model achieved an AUC of 0.86 ± 0.03 when evaluated in the independent testing group of 32 patients. In an additional prospective blinded testing group of 48 patients, the model achieved an AUC of 0.83 ± 0.02. These results demonstrated that DL based on multiparametric MRI can potentially differentiate TNBC patients with pCR or non-pCR in the breast early during NAST.

Talimogene laherparepvec (T-VEC) is an immunotherapy that generates local tumor lysis and systemic antitumor immune response. We studied the efficacy of intratumoral administration of T-VEC as monotherapy for inoperable locoregional recurrence of breast cancer. T-VEC was injected intratumorally at 10 6 PFU/mL on day 1 (cycle 1), 10 8 PFU/mL on day 22 (cycle 2), and 10 8 PFU/mL every 2 weeks thereafter (cycles ≥ 3). Nine patients were enrolled, 6 with only locoregional disease and 3 with both locoregional and distant disease. No patient completed the planned 10 cycles or achieved complete or partial response. The median number of cycles administered was 4 (range, 3–8). Seven patients withdrew prematurely because of uncontrolled disease progression, 1 withdrew after cycle 3 because of fatigue, and 1 withdrew after cycle 4 for reasons unrelated to study treatment. Median progression-free survival and overall survival were 77 days (95% CI, 63–NA) and 361 days (95% CI, 240–NA). Two patients received 8 cycles with clinically stable disease as the best response. The most common grade 2 or higher adverse event was injection site reaction (n = 7, 78%). Future studies could examine whether combining intratumoral T-VEC with concurrent systemic therapy produces better outcomes.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPis) are used to treat BRCA-mutated (BRCAm) cancer patients; however, resistance has been observed. Therefore, biomarkers to indicate PARPi resistance and combination therapy to overcome that are urgently needed. We identified a high prevalence of activated FGF receptor 3 (FGFR3) in BRCAm triple-negative breast cancer (TNBC) cells with intrinsic and acquired PARPi resistance. FGFR3 phosphorylated PARP1 at tyrosine 158 (Y158) to recruit BRG1 and prolong chromatin-loaded MRE11, thus promoting homologous recombination (HR) to enhance PARPi resistance. FGFR inhibition prolonged PARP trapping and synergized with PARPi in vitro and in vivo. High-level PARP1 Y158 phosphorylation (p-Y158) positively correlated with PARPi resistance in TNBC patient-derived xenograft models, and in PARPi-resistant TNBC patient tumors. These findings reveal that PARP1 p-Y158 facilitates BRG1-mediated HR to resolve the PARP-DNA complex, and PARP1 p-Y158 may indicate PARPi resistance that can be relieved by combining FGFR inhibitors (FGFRis) with PARPis. In summary, we show that FGFRi restores PARP trapping and PARPi antitumor efficacy in PARPi-resistant breast cancer by decreasing HR through the PARP1 p-Y158/BRG1/MER11 axis, suggesting that PARP1 p-Y158 is a biomarker for PARPi resistance that can be overcome by combining FGFRis with PARPis.

Breast cancer has historically been a disease for which immunotherapy was largely unavailable. Recently, the use of immune checkpoint inhibitors (ICIs) in combination with chemotherapy for the treatment of advanced/metastatic triple-negative breast cancer (TNBC) has demonstrated efficacy, including longer progression-free survival and increased overall survival in subsets of patients. Based on clinical benefit in randomized trials, ICIs in combination with chemotherapy for the treatment of some patients with advanced/metastatic TNBC have been approved by the United States (US) Food and Drug Administration (FDA), expanding options for patients. Ongoing questions remain, however, about the optimal chemotherapy backbone for immunotherapy, appropriate biomarker-based selection of patients for treatment, the optimal strategy for immunotherapy treatment in earlier stage disease, and potential use in histological subtypes other than TNBC. To provide guidance to the oncology community on these and other important concerns, the Society for Immunotherapy of Cancer (SITC) convened a multidisciplinary panel of experts to develop a clinical practice guideline (CPG). The expert panel drew upon the published literature as well as their clinical experience to develop recommendations for healthcare professionals on these important aspects of immunotherapeutic treatment for breast cancer, including diagnostic testing, treatment planning, immune-related adverse events (irAEs), and patient quality of life (QOL) considerations. The evidence-based and consensus-based recommendations in this CPG are intended to give guidance to cancer care providers treating patients with breast cancer.

Triple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic complete response (pCR). We included 163 patients with stage I-III TNBC with multiparametric MRI at baseline and after 2 (C2) and 4 cycles of NAST. Seventy-eight patients (48%) had pCR, and 85 (52%) had non-pCR. Thirty-six multivariate models combining radiomic features from dynamic contrast-enhanced MRI and diffusion-weighted imaging had an area under the receiver operating characteristics curve (AUC) > 0.7. The top-performing model combined 35 radiomic features of relative difference between C2 and baseline; had an AUC = 0.905 in the training and AUC = 0.802 in the testing set. There was high inter-reader agreement and very similar AUC values of the pCR prediction models for the 2 readers. Our data supports multiparametric MRI-based radiomic models for early prediction of NAST response in TNBC.

Among patients with breast cancer and germline mutations in the BRCA DNA repair pathway genes, the poly(adenosine diphosphate–ribose) inhibitor talazoparib provided a significant benefit over standard chemotherapy with respect to progression-free survival.

Accurate tumor segmentation is required for quantitative image analyses, which are increasingly used for evaluation of tumors. We developed a fully automated and high-performance segmentation model of triple-negative breast cancer using a self-configurable deep learning framework and a large set of dynamic contrast-enhanced MRI images acquired serially over the patients’ treatment course. Among all models, the top-performing one that was trained with the images across different time points of a treatment course yielded a Dice similarity coefficient of 93% and a sensitivity of 96% on baseline images. The top-performing model also produced accurate tumor size measurements, which is valuable for practical clinical applications.