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Background: Some evidence suggests that women with pregnancy-associated breast cancers (PABC) have a worse outcome compared with historical controls. However, young age is a worse prognostic factor independently, and women with PABC tend to be young. The purpose of the current study was to compare locoregional recurrence (LRR), distant metastases (DM), and overall survival (OS) in young patients with PABC and non-PABC.Methods: Data for 668 breast cancers in 652 patients agedResults: The median follow-up for all living patients was 114 months. Patients who developed PABC had more advanced T classification, N classification, and stage group (all P<.04) compared with patients with non-PABC. Patients with PABC had no statistically significant differences in 10-year rates of LRR (23.4% vs 19.2%; P=.47), DM (45.1% vs 38.9%; P=.40), or OS (64.6% vs 64.8%; P=.60) compared with patients with non-PABC. For those patients who developed breast cancer during pregnancy, any treatment intervention during pregnancy provided a trend toward improved OS compared with delaying evaluation and treatment until after delivery (78.7% vs 44.7%; P=.068).Conclusions: Young patients with PABC had no statistically significant differences in LRR, DM, or OS compared with those with non-PABC; however, pregnancy contributed to a delay in breast cancer diagnosis, evaluation, and treatment. Primary care and reproductive physicians should be aggressive in the workup of breast symptoms in the pregnant population to expedite diagnosis and allow multidisciplinary treatment. [ABSTRACT FROM AUTHOR]

Purpose: Sleep disturbances are common in patients with breast cancer, but comprehensive evaluations with patient-reported outcomes (PRO) and sleep evaluation with polysomnography (PSG) are lacking. This study describes sleep disruption using PROs and PSG to identify underlying sleep disorders., Methods: A retrospective review of patients with breast cancer undergoing formal sleep evaluation from 4/1/2009 to 7/31/2014 was performed. Clinical characteristics, PROs using Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS), and PSG data were reviewed., Results: 404 patients were identified with 43% early, 30% locally advanced and 17% metastatic disease. PSQI revealed poor sleep in 75%, and ESS demonstrated daytime sleepiness in 55%. Sleep aid use was reported by 39%, and pain medication use in 22%. Most patients (50.2%) had multiple sleep disorders. Insomnia (54.5%) was the most frequent sleep disorder, followed closely by obstructive sleep apnea (OSA) (53.7%). PSG was performed in 74%. Multivariate analysis linked poor sleep to use of sleep aids [OR 7.7, 95% CI 3.9 to 15.2], anxiety disorder [OR 4.8, 95% CI 1.7 to 14.0], and metastatic disease [OR 2.8, 95% CI 1.1 to 6.6]. Daytime sleepiness correlated with known diagnosis of OSA [OR 1.9, 95% CI 1.0 to 3.3] and sleep aid use [OR 0.6, 95% CI 0.4 to 0.9]., Conclusions: Poor sleep was associated with sleep aid use, anxiety disorder and metastatic disease. Insomnia was the most common sleep disorder, followed by OSA (mostly mild). Education about sleep health and proactive screening for sleep symptoms would be beneficial in patients with breast cancer., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: Talazoparib monotherapy in patients with germline BRCA-mutated, early-stage triple-negative breast cancer (TNBC) showed activity in the neoadjuvant setting in the phase II NEOTALA study (NCT03499353). These biomarker analyses further assessed the mutational landscape of the patients enrolled in the NEOTALA study., Methods: Baseline tumor tissue from the NEOTALA study was tested retrospectively using FoundationOne ® CDx. To further hypothesis-driven correlative analyses, agnostic heat-map visualizations of the FoundationOne ® CDx tumor dataset were used to assess overall mutational landscape and identify additional candidate predictive biomarkers of response., Results: All patients enrolled (N = 61) had TNBC. In the biomarker analysis population, 75.0% (39/52) and 25.0% (13/52) of patients exhibited BRCA1 and BRCA2 mutations, respectively. Strong concordance (97.8%) was observed between tumor BRCA and germline BRCA mutations, and 90.5% (38/42) of patients with tumor BRCA mutations evaluable for somatic-germline-zygosity were predicted to exhibit BRCA loss of heterozygosity (LOH). No patients had non-BRCA germline DNA damage response (DDR) gene variants with known/likely pathogenicity, based on a panel of 14 non-BRCA DDR genes. Ninety-eight percent of patients had TP53 mutations. Genomic LOH, assessed continuously or categorically, was not associated with response., Conclusion: The results from this exploratory biomarker analysis support the central role of BRCA and TP53 mutations in tumor pathobiology. Furthermore, these data support assessing germline BRCA mutational status for molecular eligibility for talazoparib in patients with TNBC., (© 2024. The Author(s).)

Purpose: Radiation therapy is an underinvestigated tool for priming the immune system in intact human breast cancers. We sought here to investigate if a preoperative radiation therapy boost delivered was associated with a significant change in tumor-infiltrating lymphocytes (TILs) in the tumor in estrogen receptor positive, HER2Neu nonamplified breast cancers., Methods and Materials: A total of 20 patients were enrolled in a phase 2 clinical trial and received either 7.5 Gy × 1 fraction or 2 Gy × 5 fractions, completed 6 to 8 days before surgery. Percent stromal TILs were evaluated on hematoxylin and eosin-stained samples. Short-term safety was assessed based on time to surgery, toxicities, and cosmesis up to 6 months after boost., Results: Stromal TIL increased 6 to 8 days after completion of boost radiation therapy (median 3.0 [IQR, 1.0-6.5]) before radiation therapy versus median 5.0 (IQR, 1.5-8.0) after radiation therapy, P = .0037. Zero grade ≥3 toxicities up to 6 months after boost were experienced. In all, 94% (16/17) patients with 6-month follow-up cosmetic assessment after breast conservation had good-excellent cosmesis by physician assessment., Conclusion: In this phase 2 trial, preoperative radiation therapy boost resulted in a short-term increase in stromal TIL with minimal toxicities. Preoperative breast radiation therapy appears to be safe and may be a feasible means for priming the tumor microenvironment., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: We tested the ability of [ 18 F] fluorthanatrace (FTT), a radiolabeled analog of poly(ADP-ribose) polymerase (PARP)-1 inhibitors, to demonstrate target engagement on positron emission tomography (PET) scans from patients with newly diagnosed primary breast cancer receiving the PARP inhibitor (PARPi) talazoparib., Methods: Seven patients with germline BRCA1/2 pathogenic variants underwent [ 18 F]FTT PET-computed tomography scanning at baseline, and five underwent repeat scanning 14 days after talazoparib initiation. Maximum uptake on PET was quantified in the primary tumor, involved nodes, contralateral pectoralis muscle, and lumbar vertebra body level 3, and compared between the two time points., Results: Blocking of [ 18 F]FTT was observed on the second scan. Potentially strong but nonsignificant correlations were found between changes in tumor volume (on ultrasound at 1 month v baseline) and percentage changes in tumor-to-muscle uptake ratio at 14 days from baseline (Spearman rank correlation coefficient r = 1; P = .083); and between the highest-grade hematologic toxicity and baseline bone marrow-to-muscle (B/M) uptake ratio ( r = 0.72; P = .068) and percentage change in B/M ratio at 14 days from baseline ( r = 0.87; P = .058)., Conclusion: We conclude that [ 18 F]FTT can image target engagement by PARPi, but larger studies are needed to determine whether [ 18 F]FTT uptake can predict response to PARPi and whether uptake of [ 18 F]FTT in bone marrow may be an early predictor of hematologic toxicity.

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., (© 2024. The Author(s).)

Luminal androgen receptor (LAR)-enriched triple-negative breast cancer (TNBC) is a distinct subtype. The efficacy of AR inhibitors and the relevant biomarkers in neoadjuvant therapy (NAT) are yet to be determined. We tested the combination of the AR inhibitor enzalutamide (120 mg daily by mouth) and paclitaxel (80 mg/m 2 weekly intravenously) (ZT) for 12 weeks as NAT for LAR-enriched TNBC. Eligibility criteria included a percentage of cells expressing nuclear AR by immunohistochemistry (iAR) of at least 10% and a reduction in sonographic volume of less than 70% after four cycles of doxorubicin and cyclophosphamide. Twenty-four patients were enrolled. Ten achieved a pathologic complete response or residual cancer burden-I. ZT was safe, with no unexpected side effects. An iAR of at least 70% had a positive predictive value of 0.92 and a negative predictive value of 0.97 in predicting LAR-enriched TNBC according to RNA-based assays. Our data support future trials of AR blockade in early-stage LAR-enriched TNBC., Competing Interests: Declaration of interests B.L. served a consultancy/advisory role for Celcuity, Natera, Daichi-Sankyo, Novartis, Pfizer, and AstraZeneca; received honoraria from Puma Biotechnology, Novartis, and Pfizer; received grant/research funding from Genentech, Takeda, Merck, Celcuity, Eli Lilly, Puma Biotechnology, and Calithera Therapeutics; and received funding from NCI, DOD, CPRIT, Hope Foundation, and Adopt-A-Scientist. C.Y. has received research funding (to the institution) from Genentech, Gilead, BostonGene, Sanofi, Amgen, Pfizer, Astellas, and Novartis and has served on advisory boards for Gilead. W.F.S. is a co-inventor of US patent no. 11,459,617 “Targeted measure of transcriptional activity related to hormone receptors” issued on 10/4/2022 (applicant proprietor: University of Texas MD Anderson Cancer Center, licensed to Delphi Diagnostics, Inc.) and has co-founder equity from Delphi Diagnostics, Inc. A.M.T. is related by marriage to an employee of Eli Lilly. D.T. has received research support (to the institution) from Novartis, Pfizer, and Polyphor and has served as a consultant to AstraZeneca, GlaxoSmithKline, Gilead, Oncopep, Pfizer, Novartis, AMBRX, Personalis, Sermonix, Stemline-Menarini, and Puma Biotechnology. S.L.M. is currently employed by Eli Lilly (previously employed by MD Anderson at the time the study was conducted). J.K.L. has received grant or research support from Novartis, Medivation/Pfizer, Genentech, GSK, EMDSerono, AstraZeneca, Medimmune, Zenith, and Jounce; participated in Speaker’s Bureau for MedLearning, Physician’s Education Resource, Prime Oncology, Medscape, and Clinical Care Options; received honoraria from UpToDate; and served on advisory committees or review panels for AstraZeneca, Ayala, Pfizer (all uncompensated), NCCN, ASCO, NIH, PDQ, the SITC Breast Committee, and the SWOG Breast Committee., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

A clinical trial was conducted to assess the feasibility of enrolling patients with Stage II or III hormone receptor positive (HR+)/HER2-negative breast cancer to pre-operative dual PD-L1/CTLA-4 checkpoint inhibition administered prior to neoadjuvant chemotherapy (NACT). Eight eligible patients were treated with upfront durvalumab and tremelimumab for two cycles. Patients then received NACT prior to breast surgery. Seven patients had baseline and interval breast ultrasounds after combination immunotherapy and the responses were mixed: 3/7 patients experienced a ≥30% decrease in tumor volume, 3/7 a ≥30% increase, and 1 patient had stable disease. At the time of breast surgery, 1/8 patients had a pathologic complete response (pCR). The trial was stopped early after 3 of 8 patients experienced immunotherapy-related toxicity or suspected disease progression that prompted discontinuation or a delay in the administration of NACT. Two patients experienced grade 3 immune-related adverse events (1 with colitis, 1 with endocrinopathy). Analysis of the tumor microenvironment after combination immunotherapy did not show a significant change in immune cell subsets from baseline. There was limited benefit for dual checkpoint blockade administered prior to NACT in our study of 8 patients with HR+/HER2-negative breast cancer.

Purpose: The PI3K pathway is frequently altered in triple-negative breast cancer (TNBC). Limited cell line and human data suggest that TNBC tumors characterized as mesenchymal (M) and luminal androgen receptor (LAR) subtypes have increased incidence of alterations in the PI3K pathway. The impact of PI3K pathway alterations across TNBC subtypes is poorly understood., Methods: Pretreatment tumor was evaluated from operable TNBC patients enrolled on a clinical trial of neoadjuvant therapy (NAT; A Robust TNBC Evaluation fraMework to Improve Survival [ClinicalTrials.gov identifier: NCT02276443]). Tumors were characterized into seven TNBC subtypes per Pietenpol criteria (basal-like 1, basal-like 2, immunomodulatory, M, mesenchymal stem-like, LAR, and unstable). Using whole-exome sequencing, RNA sequencing, and immunohistochemistry for PTEN, alterations were identified in 32 genes known to activate the PI3K pathway. Alterations in each subtype were associated with pathologic response to NAT., Results: In evaluated patients (N = 177), there was a significant difference in the incidence of PI3K pathway alterations across TNBC subtypes ( P < .01). The highest incidence of alterations was seen in LAR (81%), BL2 (79%), and M (62%) subtypes. The odds ratio for pathologic complete response (pCR) in the presence of PIK3CA mutation, PTEN mutation, and/or PTEN loss was highest in the LAR subtype and lowest in the M subtype, but these findings did not reach statistical significance. Presence of PIK3CA mutation was associated with pCR in the LAR subtype ( P = .02)., Conclusion: PI3K pathway alteration can affect response to NAT in TNBC, and targeted agents may improve outcomes, particularly in patients with M and LAR TNBC.

Background: Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST)., Purpose: To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST., Study Type: Prospective., Population: Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR)., Field Strength/sequence: 3.0 T/reduced field of view single-shot echo-planar DTI sequence., Assessment: Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery., Statistical Tests: Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant., Results: 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm 2 /s)., Data Conclusion: Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC., Evidence Level: 1 TECHNICAL EFFICACY: Stage 4., (© 2024 International Society for Magnetic Resonance in Medicine.)

Early prediction of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) patients could help oncologists select individualized treatment and avoid toxic effects associated with ineffective therapy in patients unlikely to achieve pathologic complete response (pCR). The objective of this study is to evaluate the performance of radiomic features of the peritumoral and tumoral regions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired at different time points of NAST for early treatment response prediction in TNBC. This study included 163 Stage I-III patients with TNBC undergoing NAST as part of a prospective clinical trial (NCT02276443). Peritumoral and tumoral regions of interest were segmented on DCE images at baseline (BL) and after two (C2) and four (C4) cycles of NAST. Ten first-order (FO) radiomic features and 300 gray-level-co-occurrence matrix (GLCM) features were calculated. Area under the receiver operating characteristic curve (AUC) and Wilcoxon rank sum test were used to determine the most predictive features. Multivariate logistic regression models were used for performance assessment. Pearson correlation was used to assess intrareader and interreader variability. Seventy-eight patients (48%) had pCR (52 training, 26 testing), and 85 (52%) had non-pCR (57 training, 28 testing). Forty-six radiomic features had AUC at least 0.70, and 13 multivariate models had AUC at least 0.75 for training and testing sets. The Pearson correlation showed significant correlation between readers. In conclusion, Radiomic features from DCE-MRI are useful for differentiating pCR and non-pCR. Similarly, predictive radiomic models based on these features can improve early noninvasive treatment response prediction in TNBC patients undergoing NAST., Competing Interests: KKH serves on the medical advisory boards for ArmadaHealth and AstraZeneca and receives research funding from Cairn Surgical, Eli Lilly and Company, and Lumicell. K-PH is currently receiving research funding from Siemens Healthineers and has received research funding from GE. JKL received grant or research support from Novartis, Medivation/Pfizer, Genentech, GSK, EMD-Serono, AstraZeneca, Medimmune, Zenith, and Merck; participated in the Speaker’s Bureau for MedLearning, Physicians’ Education Resource, Prime Oncology, Medscape, Clinical Care Options, and Medpage and receives royalty from UpToDate and Certis. DT declares research contracts with Pfizer, Novartis, and Ployphor and is a consultant of AstraZeneca, GlaxoSmithKline, OncoPep, Gilead, Novartis, Pfizer, Personalis, and Sermonix. WY receives royalties from Elsevier. GR receives research funding from GE Healthcare. JM is an inventor of United States patents licensed to Siemens Healthineers and GE Healthcare and is a consultant for C4 Imaging. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Panthi, Mohamed, Adrada, Boge, Candelaria, Chen, Hunt, Huo, Hwang, Korkut, Lane, Le-Petross, Leung, Litton, Pashapoor, Perez, Son, Sun, Thompson, Tripathy, Valero, Wei, White, Xu, Yang, Zhou, Yam, Rauch and Ma.)

Background: The undetermined efficacy of the current standard-of-care neoadjuvant treatment, anthracycline/platinum-based chemotherapy, in patients with early-stage triple-negative breast cancer (TNBC) and germline BRCA mutations emphasizes the need for biomarker-targeted treatment, such as poly(ADP-ribose) polymerase inhibitors, in this setting. This phase II, single-arm, open-label study evaluated the efficacy and safety of neoadjuvant talazoparib in patients with germline BRCA1/2-mutated early-stage TNBC., Patients and Methods: Patients with germline BRCA1/2-mutated early-stage TNBC received talazoparib 1 mg once daily for 24 weeks (0.75 mg for moderate renal impairment) followed by surgery. The primary endpoint was pathologic complete response (pCR) by independent central review (ICR). Secondary endpoints included residual cancer burden (RCB) by ICR. Safety and tolerability of talazoparib and patient-reported outcomes were assessed., Results: Of 61 patients, 48 received ≥80% talazoparib doses, underwent surgery, and were assessed for pCR or progressed before pCR assessment and considered nonresponders. pCR rate was 45.8% (95% confidence interval [CI], 32.0%-60.6%) and 49.2% (95% CI, 36.7%-61.6%) in the evaluable and intent-to-treat (ITT) population, respectively. RCB 0/I rate was 45.8% (95% CI, 29.4%-63.2%) and 50.8% (95% CI, 35.5%-66.0%) in the evaluable and ITT population, respectively. Treatment-related adverse events (TRAE) were reported in 58 (95.1%) patients. Most common grade 3 and 4 TRAEs were anemia (39.3%) and neutropenia (9.8%). There was no clinically meaningful detriment in quality of life. No deaths occurred during the reporting period; 2 deaths due to progressive disease occurred during long-term follow-up (>400 days after first dose)., Conclusions: Neoadjuvant talazoparib monotherapy was active despite pCR rates not meeting the prespecified threshold; these rates were comparable to those observed with combination anthracycline- and taxane-based chemotherapy regimens. Talazoparib was generally well tolerated., Clinicaltrials.gov Identifier: NCT03499353., (© The Author(s) 2023. Published by Oxford University Press.)

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.

Objective: Risk-reducing therapy with selective estrogen receptor (ER) modulators and aromatase inhibitors reduce breast cancer risk. However, the effects are limited to ER-positive breast cancer. Therefore, new agents with improved toxicity profiles that reduce the risk in ER-negative breast cancers are urgently needed. The aim of this prospective, short-term, prevention study was to evaluate the effect of dasatinib, an inhibitor of the tyrosine kinase Src, on biomarkers in normal (but increased risk) breast tissue and serum of women at high risk for a second, contralateral primary breast cancer., Materials and Methods: Women with a history of unilateral stage I, II, or III ER-negative breast cancer, having no active disease, and who completed all adjuvant therapies were eligible. Patients underwent baseline fine-needle aspiration (FNA) of the contralateral breast and serum collection for biomarker analysis and were randomized to receive either no treatment (control) or dasatinib at 40 or 80 mg/day for three months. After three months, serum collection and breast FNA were repeated. Planned biomarker analysis consisted of changes in cytology and Ki-67 on breast FNA, and changes in serum levels of insulin-like growth factor 1 (IGF-1), IGF-binding protein 1, and IGF-binding protein 3. The primary objective was to evaluate changes in Ki-67 and secondary objective included changes in cytology in breast tissue and IGF-related serum biomarkers. Toxicity was also evaluated., Results: Twenty-three patients started their assigned treatments. Compliance during the study was high, with 86.9% (20/23) of patients completing their assigned doses. Dasatinib was well tolerated and no drug-related grade 3 and 4 adverse events were observed. Since only one patient met the adequacy criteria for the paired FNA sample, we could not evaluate Ki-67 level or cytological changes. No significant change in serum biomarkers was observed among the three groups., Conclusion: Dasatinib was well tolerated but did not induce any significant changes in serum biomarkers. The study could not fulfill its primary objective due to an inadequate number of paired FNA samples. Further, larger studies are needed to evaluate the effectiveness of Src inhibitors in breast cancer prevention., Competing Interests: Conflict of Interest: BA has received grant or research support from Susan G. Komen Breast Cancer Foundation. DY has received grant or research support from Susan G. Komen Breast Cancer Foundation and NIH/NCI. JKL received grant or research support from Medivation/Pfizer, Genentech, GSK, EMD-Sorono, Astra Zeneca, Zenith, Merck; participated in Speaker’s Bureau for MedLearning, Physician’s Education Resource, Clinical Care Options, WebMD, Tumor Board Tuesday, received Honoria from UpToDate; served on advisory committees or review panels for NCCN, ASCO, SITC Breast Committee. All other authors declare no relevant conflicts of interest., (©Copyright 2023 by the the Turkish Federation of Breast Diseases Societies / European Journal of Breast Health published by Galenos Publishing House.)

Purpose: The Standardized Definitions for Efficacy End Points (STEEP) criteria, established in 2007 and updated in 2021 (STEEP 2.0), provide standardized definitions of adjuvant breast cancer (BC) end points. STEEP 2.0 identified a need to separately address end points for neoadjuvant clinical trials. The multidisciplinary NeoSTEEP working group of experts was convened to critically evaluate and align neoadjuvant BC trial end points., Methods: The NeoSTEEP working group concentrated on neoadjuvant systemic therapy end points in clinical trials with efficacy outcomes-both pathologic and time-to-event survival end points-particularly for registrational intent. Special considerations for subtypes and therapeutic approaches, imaging, nodal staging at surgery, bilateral and multifocal diseases, correlative tissue collection, and US Food and Drug Administration regulatory considerations were contemplated., Results: The working group recommends a preferred definition of pathologic complete response (pCR) as the absence of residual invasive cancer in the complete resected breast specimen and all sampled regional lymph nodes (ypT0/Tis ypN0 per AJCC staging). Residual cancer burden should be a secondary end point to facilitate future assessment of its utility. Alternative end points are needed for hormone receptor-positive disease. Time-to-event survival end point definitions should pay particular attention to the measurement starting point. Trials should include end points originating at random assignment (event-free survival and overall survival) to capture presurgery progression and deaths as events. Secondary end points adapted from STEEP 2.0, which are defined from starting at curative-intent surgery, may also be appropriate. Specification and standardization of biopsy protocols, imaging, and pathologic nodal evaluation are also crucial., Conclusion: End points in addition to pCR should be selected on the basis of clinical and biologic aspects of the tumor and the therapeutic agent investigated. Consistent prespecified definitions and interventions are paramount for clinically meaningful trial results and cross-trial comparison.

Background: Recent advances have been made in targeting the phosphoinositide 3-kinase pathway in breast cancer. Phosphatase and tensin homolog (PTEN) is a key component of that pathway., Objective: To understand the changes in PTEN expression over the course of the disease in patients with triple-negative breast cancer (TNBC) and whether PTEN copy number variation (CNV) by next-generation sequencing (NGS) can serve as an alternative to immunohistochemistry (IHC) to identify PTEN loss., Methods: We compared PTEN expression by IHC between pretreatment tumors and residual tumors in the breast and lymph nodes after neoadjuvant chemotherapy in 96 patients enrolled in a TNBC clinical trial. A correlative analysis between PTEN protein expression and PTEN CNV by NGS was also performed., Results: With a stringent cutoff for PTEN IHC scoring, PTEN expression was discordant between pretreatment and posttreatment primary tumors in 5% of patients ( n  = 96) and between posttreatment primary tumors and lymph node metastases in 9% ( n  = 33). A less stringent cutoff yielded similar discordance rates. Intratumoral heterogeneity for PTEN loss was observed in 7% of the patients. Among pretreatment tumors, PTEN copy numbers by whole exome sequencing ( n  = 72) were significantly higher in the PTEN-positive tumors by IHC compared with the IHC PTEN-loss tumors ( p  < 0.0001). However, PTEN-positive and PTEN-loss tumors by IHC overlapped in copy numbers: 14 of 60 PTEN-positive samples showed decreased copy numbers in the range of those of the PTEN-loss tumors., Conclusion: Testing various specimens by IHC may generate different PTEN results in a small proportion of patients with TNBC; therefore, the decision of testing one versus multiple specimens in a clinical trial should be defined in the patient inclusion criteria. Although a distinct cutoff by which CNV differentiated PTEN-positive tumors from those with PTEN loss was not identified, higher copy number of PTEN may confer positive PTEN, whereas lower copy number of PTEN would necessitate additional testing by IHC to assess PTEN loss., Trial Registration: NCT02276443., (© The Author(s), 2023.)

Purpose To determine if a radiomics model based on quantitative maps acquired with synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). Materials and Methods In this prospective study, 181 women diagnosed with stage I-III TNBC were scanned with a SyMRI sequence at baseline and at midtreatment (after four cycles of NAST), producing T1, T2, and proton density (PD) maps. Histopathologic analysis at surgery was used to determine pathologic complete response (pCR) or non-pCR status. From three-dimensional tumor contours drawn on the three maps, 310 histogram and textural features were extracted, resulting in 930 features per scan. Radiomic features were compared between pCR and non-pCR groups by using Wilcoxon rank sum test. To build a multivariable predictive model, logistic regression with elastic net regularization and cross-validation was performed for texture feature selection using 119 participants (median age, 52 years [range, 26-77 years]). An independent testing cohort of 62 participants (median age, 48 years [range, 23-74 years]) was used to evaluate and compare the models by area under the receiver operating characteristic curve (AUC). Results Univariable analysis identified 15 T1, 10 T2, and 12 PD radiomic features at midtreatment that predicted pCR with an AUC greater than 0.70 in both the training and testing cohorts. Multivariable radiomics models of maps acquired at midtreatment demonstrated superior performance over those acquired at baseline, achieving AUCs as high as 0.78 and 0.72 in the training and testing cohorts, respectively. Conclusion SyMRI-based radiomic features acquired at midtreatment are potentially useful for identifying early NAST responders in TNBC. Keywords: MR Imaging, Breast, Outcomes Analysis ClinicalTrials.gov registration no. NCT02276443 Supplemental material is available for this article. © RSNA, 2023 See also the commentary by Houser and Rapelyea in this issue.

We trained and validated a deep learning model that can predict the treatment response to neoadjuvant systemic therapy (NAST) for patients with triple negative breast cancer (TNBC). Dynamic contrast enhanced (DCE) MRI and diffusion-weighted imaging (DWI) of the pre-treatment (baseline) and after four cycles (C4) of doxorubicin/cyclophosphamide treatment were used as inputs to the model for prediction of pathologic complete response (pCR). Based on the standard pCR definition that includes disease status in either breast or axilla, the model achieved areas under the receiver operating characteristic curves (AUCs) of 0.96 ± 0.05, 0.78 ± 0.09, 0.88 ± 0.02, and 0.76 ± 0.03, for the training, validation, testing, and prospective testing groups, respectively. For the pCR status of breast only, the retrained model achieved prediction AUCs of 0.97 ± 0.04, 0.82 ± 0.10, 0.86 ± 0.03, and 0.83 ± 0.02, for the training, validation, testing, and prospective testing groups, respectively. Thus, the developed deep learning model is highly promising for predicting the treatment response to NAST of TNBC.Clinical Relevance- Deep learning based on serial and multiparametric MRIs can potentially distinguish TNBC patients with pCR from non-pCR at the early stage of neoadjuvant systemic therapy, potentially enabling more personalized treatment of TNBC patients.

High stromal tumor-infiltrating lymphocytes (sTILs) are associated with improved pathologic complete response (pCR) in triple-negative breast cancer (TNBC). We hypothesize that integrating high sTILs and additional clinicopathologic features associated with pCR could enhance our ability to predict the group of patients on whom treatment de-escalation strategies could be tested. In this prospective early-stage TNBC neoadjuvant chemotherapy study, pretreatment biopsies from 408 patients were evaluated for their clinical and demographic features, as well as biomarkers including sTILs, Ki-67, PD-L1 and androgen receptor. Multivariate logistic regression models were developed to generate a computed response score to predict pCR. The pCR rate for the entire cohort was 41%. Recursive partitioning analysis identified ≥20% as the optimal cutoff for sTILs to denote 35% (143/408) of patients as having high sTILs, with a pCR rate of 59%, and 65% (265/408) of patients as having low sTILs, with a pCR rate of 31%. High Ki-67 (cutoff > 35%) was identified as the only predictor of pCR in addition to sTILs in the training set. This finding was verified in the testing set, where the highest computed response score encompassing both high sTILa and high Ki-67 predicted a pCR rate of 65%. Integrating Ki67 and sTIL may refine the selection of early stage TNBC patients for neoadjuvant clinical trials evaluating de-escalation strategies.

Purpose: Neoadjuvant anti-PD-(L)1 therapy improves the pathological complete response (pCR) rate in unselected triple-negative breast cancer (TNBC). Given the potential for long-term morbidity from immune-related adverse events (irAEs), optimizing the risk-benefit ratio for these agents in the curative neoadjuvant setting is important. Suboptimal clinical response to initial neoadjuvant therapy (NAT) is associated with low rates of pCR (2-5%) and may define a patient selection strategy for neoadjuvant immune checkpoint blockade. We conducted a single-arm phase II study of atezolizumab and nab-paclitaxel as the second phase of NAT in patients with doxorubicin and cyclophosphamide (AC)-resistant TNBC (NCT02530489)., Methods: Patients with stage I-III, AC-resistant TNBC, defined as disease progression or a < 80% reduction in tumor volume after 4 cycles of AC, were eligible. Patients received atezolizumab (1200 mg IV, Q3weeks × 4) and nab-paclitaxel (100 mg/m 2 IV,Q1 week × 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezolizumab (1200 mg IV, Q3 weeks, × 4). A two-stage Gehan-type design was employed to detect an improvement in pCR/residual cancer burden class I (RCB-I) rate from 5 to 20%., Results: From 2/15/2016 through 1/29/2021, 37 patients with AC-resistant TNBC were enrolled. The pCR/RCB-I rate was 46%. No new safety signals were observed. Seven patients (19%) discontinued atezolizumab due to irAEs., Conclusion: This study met its primary endpoint, demonstrating a promising signal of activity in this high-risk population (pCR/RCB-I = 46% vs 5% in historical controls), suggesting that a response-adapted approach to the utilization of neoadjuvant immunotherapy should be considered for further evaluation in a randomized clinical trial., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The phase I first-in-human study ENGAGE-1 evaluated the humanized IgG1 OX40 agonistic monoclonal antibody GSK3174998 alone (Part 1 (P1)) or in combination with pembrolizumab (Part 2 (P2)) in patients with advanced solid tumors., Methods: GSK3174998 (0.003-10 mg/kg) ± pembrolizumab (200 mg) was administered intravenously every 3 weeks using a continuous reassessment method for dose escalation. Primary objectives were safety and tolerability; secondary objectives included pharmacokinetics, immunogenicity, pharmacodynamics, and clinical activity., Results: 138 patients were enrolled (45 (P1) and 96 (P2, including 3 crossovers)). Treatment-related adverse events occurred in 51% (P1) and 64% (P2) of patients, fatigue being the most common (11% and 24%, respectively). No dose-toxicity relationship was observed, and maximum-tolerated dose was not reached. Dose-limiting toxicities (P2) included Grade 3 (G3) pleural effusion and G1 myocarditis with G3 increased troponin. GSK3174998 ≥0.3 mg/kg demonstrated pharmacokinetic linearity and >80% receptor occupancy on circulating T cells; 0.3 mg/kg was selected for further evaluation. Limited clinical activity was observed for GSK3174998 (P1: disease control rate (DCR) ≥24 weeks 9%) and was not greater than that expected for pembrolizumab alone (P2: overall response rate 8%, DCR ≥24 weeks 28%). Multiplexed immunofluorescence data from paired biopsies suggested that increased infiltration of natural killer (NK)/natural killer T (NKT) cells and decreased regulatory T cells (Tregs) in the tumor microenvironment may contribute to clinical responses: CD16+CD56-CD134+ NK /NKT cells and CD3+CD4+FOXP3+CD134+ Tregs exhibited the largest magnitude of change on treatment, whereas CD3+CD8+granzyme B+PD-1+CD134+ cytotoxic T cells were the least variable. Tumor gene expression profiling revealed an upregulation of inflammatory responses, T-cell proliferation, and NK cell function on treatment with some inflammatory cytokines upregulated in peripheral blood. However, target engagement, evidenced by pharmacologic activity in peripheral blood and tumor tissue, did not correlate with clinical efficacy. The low number of responses precluded identifying a robust biomarker signature predictive of response., Conclusions: GSK3174998±pembrolizumab was well tolerated over the dose range tested and demonstrated target engagement. Limited clinical activity does not support further development of GSK3174998±pembrolizumab in advanced cancers., Trial Registration Number: NCT02528357., Competing Interests: Competing interests: SP-V is a principal/subinvestigator of clinical trials for AbbVie, Adaptimmune, Adlai Nortye USA Inc, Aduro Biotech, Agios Pharmaceuticals, Amgen, Argenx BVBA, Arno Therapeutics, Astex Pharmaceuticals, AstraZeneca A, Aveo, Basilea Pharmaceutica International Ltd, Bayer Healthcare AG, BBB Technologies BV, Beigene, BicycleTx Ltd, Bioalliance Pharma, Blueprint Medicines, Boehringer Ingelheim, Boston Pharmaceuticals, Bristol Myers Squibb, Celgene Corporation, Chugai Pharmaceutical Co, Cullinan-Apollo, Curevarc, Daiichi Sankyo, Debiopharm, Eisai, Eisai Limited, Eli Lilly, Exelixis, Faron Pharmaceuticals Ltd, Forma Tharapeutics, GamaMabs, Genentech, GSK, H3 Biomedicine, Hoffmann La Roche AG, Imcheck Therapeutics, Innate Pharma, Institut De Recherche Pierre Fabre, Iris Servier, Iteos Belgium SA, Janssen Cilag, Janssen Research Foundation, Kura Oncology, Kyowa Kirin Pharm. Dev, Lilly France, Loxo Oncology, Lytix Biopharma AS, Medimmune, Menarini Ricerche, Merck Sharp & Dohme Chibret, Merus, Molecular Partners AG, Nanobiotix, Nektar Therapeutics, Novartis Pharma, Octimet Oncology NV, Oncoethix, Oncopeptides, Onyx Therapeutics, Orion Pharma, Oryzon Genomics, Ose Pharma, Pfizer, Pharma Mar, Pierre Fabre Medicament, Plexxikon, Roche, Sanofi Aventis, Seattle Genetics, Sotio A.S, Syros Pharmaceuticals, Taiho Pharma, Tesaro, Turning Point Therapeutics, and Xencor outside the submitted work; non-financial support (drug supplied) from AstraZeneca, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, GSK, Medimmune, Merck, NH TherAGuiX, Pfizer, Roche; research funding from Boehringer Ingelheim, AstraZeneca, Roche, and Merck KGaA for projects unrelated to this manuscript. VL reports consulting for Takeda, Seattle Genetics, Bristol Myers Squibb, AstraZeneca, Guardant Health; research funding from GSK, Bristol Myers Squibb, Merck, Seattle Genetics. WR reports nothing to disclose. TMB reports consulting for Guardant Health, Loxo Pharmaceuticals, Pfizer, Exelixis, Blueprint Medicines, Foundation Medicine, Bayer, AstraZeneca, Ignyta, Moderna Therapeutics, Pfizer. Speakers Bureau: Bayer, Bristol Myers Squibb, and Lilly; research funding from Daiichi Sankyo, Medpacto, Inc., Incyte, Mirati Therapeutics, MedImmune, AbbVie, AstraZeneca, Leap Therapeutics, MabVax, Stemline Therapeutics, Merck, Lilly, GSK, Novartis, Pfizer, Genentech/Roche, Deciphera, Merrimack, Immunogen, Millennium Pharmaceuticals, Ignyta, Calithera Biosciences, Kolltan Pharmaceuticals, Principa Biopharma, Peleton, Immunocore, Aileron Therapeutics, Bristol Myers Squibb, Amgen, Moderna Therapeutics, Sanofi, Boehringer Ingelheim, Astellas Pharma, Five Prime Therapeutics, Jacobio, Top Alliance BioScience, Loxo, Janssen, Clovis Oncology, Takeda, Karyopharm Therapeutics, Onyx, Phosplatin Therapeutics, Foundation Medicine, and ARMO BioScience; personal expenses from Astellas Pharma, AstraZeneca, Celgene, Clovis Oncology, EMD Serono, Genentech, Lilly, Merck, Novartis, Pharmacyclics, Sysmex, and Pfizer. AHa reports research funding from Genentech/Roche, Merck, GSK, Bristol Myers Squibb, Novartis, Boston Biomedical, Boehringer Ingelheim, AstraZeneca/Medimmune Eisai; personal fees from Merck and GSK. DCC is a consultant for Nektar, Pfizer, Werewolf, and HUYA. FSH reports research funding from Bristol Myers Squibb and Novartis; receives personal fees from Bristol Myers Squibb, Merck, EMD Serono, Novartis, Surface, Compass Therapeutics, Apricity, Sanofi, Pionyr, Torque, Bicara, Checkpoint Therapeutics, Genentech/Roche, Bioentre, Gossamer, Iovance, Trillium, Catalym, Immunocore, Amgen, Kairos, Eisai, and Rheos. JHMS is a shareholder and part-time employee of Modra Pharmaceuticals BV and patent holder of oral taxanes; reports consulting for Debiopharm. JKL reports other from GSK, Novartis, Medivation/Pfizer, Genentech, EMD-Serono, AstraZeneca, Medimmune, Zenith, Ayala, UpToDate review panels for NCCN, ASCO, NIH PDQ, Medlearning, Physicians Education Resource, Prime Oncology, Medscape, Clinical Care Options, Medpage. SA reports advisory board participation for MSD, Sanofi, Roche, Bristol Myers Squibb, Pfizer; research support from Sanofi. KAA reports research funding (to institution) from Pfizer, AstraZeneca, Amgen, Trishula, GSK, Merck, and Eli Lilly. FO is a principal/subinvestigator of clinical trials for Amgen, AstraZeneca, Cytovation, GSK, Lilly, MSD, Revmed, Incyte, Boehringer Ingelheim, Bristol Myers Squibb, Roche/Genentech, Exelexis, Relay, and InterRNA. MM reports research funding from Alpine Immune Sciences, Arcus Biosciences, Arvinas, Ascentage Pharma Group, Bayer, Bicycle Therapeutics, BioMed Valley Discoveries, BioNTech, Dragonfly Therapeutics, EMD Serono, Epizyme, Erasca, Exelixis, Foghorn Therapeutics, Genentech, Gilead Sciences, GSK, IDEAYA Biosciences, Ikena Oncology, ImmVira Pharma, Infinity Pharmaceuticals, Jacobio Pharmaceuticals, Kechow Pharma, Kezar Life Sciences, Kinnate BioPharma, MedImmune, Mereo BioPharma, Metabomed, Moderna, NBE Therapeutics, Nektar, Novartis, Oncorus, PACT Pharma, Pfizer, Plexxikon, Prelude Therapeutics, Pyramid Biosciences, Regeneron, Sapience Therapeutics, Scholar Rock Seattle Genetics, Synthrox, Takeda Pharmaceuticals, Teneobio, Tempest Therapeutics, Tizona Therapeutics, TMUNITY Therapeutics, TopAlliance Biosciences, and Xilio. M; consulting/advisory role for Astellas Pharma, AstraZeneca, BicycleTX Limited, Castle Biosciences, Eisai, Ideaya Biosciences, iTeos, Pfizer, and Regeneron Pharmaceuticals. NS reports consulting/advisory role for Deciphera, AADi, Blueprint Medicines, Bayer, Epizyme, and Boehringer Ingelheim; research funding from GSK, Karyopharm, Deciphera, Ascentage Pharma, Daiichi Sankyo/Lilly, and AstraZeneca/MedImmune. SC is the principal/subinvestigator of clinical trials for AbbVie, Adaptimmune, Adlai Nortye USA Inc, Aduro Biotech, Agios Pharmaceuticals, Amgen, Astex Pharmaceuticals, AstraZeneca AB, Aveo, Basilea Pharmaceutica International Ltd, Bayer Healthcare AG, BBB Technologies BV, Beigene, BicycleTx Ltd, Blueprint Medicines, Boehringer Ingelheim, Boston Pharmaceuticals, Bristol Myers Squibb, Casi Pharmaceuticals, Inc, Celgene Corporation (a Bristol-Myers Squibb company), Cellcentric, Chugai Pharmaceutical Co, Cullinan-Apollo, Curevarc, Cytovasion, Daiichi Sankyo, Debiopharm, Eisai, Eli Lilly, Exelixis, Faron Pharmaceuticals Ltd, Forma Tharapeutics, GamaMabs, Genentech, GSK, H3 Biomedicine, Hoffmann La Roche AG, Imcheck Therapeutics, Incyte Corporation, Innate Pharma, Institut De Recherche Pierre Fabre, Iris Servier, Iteos Belgium SA, Janssen Cilag, Janssen Research Foundation, Janssen R&D LLC, Kura Oncology, Kyowa Kirin Pharm. Dev, Lilly France, Loxo Oncology, Medimmune, Menarini Ricerche, Merck, Merck Sharp & Dohme Chibret, Merrimack Pharmaceuticals, Merus, Molecular Partners AG, Nanobiotix, Nektar Therapeutics, Novartis Pharma, Octimet Oncology NV, Oncoethix, Oncopeptides, Orion Pharma, Genomics, Ose Pharma, Pfizer, Pharma Mar, Pierre Fabre Medicament, Relay Therapeutics, Inc, Roche, Sanofi Aventis, Seattle Genetics, Sotio, Syros Pharmaceuticals, Taiho Pharma, Tesaro, Transgene SA, Turning Point Therapeutics, and Xencor; reports research grants from AstraZeneca, Bristol Myers Squibb, Boehringer Ingelheim, GSK, INCA, Janssen Cilag, Merck, Pfizer, Roche, and Sanofi; reports non-financial support (drug supplied) from AstraZeneca, Bristol Myers Squibb, Boehringer Ingelheim, GSK, Medimmune, Merck, NH TherAGuiX, Pfizer, and Roche; reports honoraria from Amgen, Astellas, AstraZeneca, Bristol Myers Squibb, Eisai, Genmab, Janssen, Merck, Novartis and Roche; reports participation in advisory boards for Alderaan Biotechnology, Amgen, AstraZeneca, Avacta, Ellipses Pharma, Oncovita, Seagen, UltraHuman8; reports travel and congress support from AstraZeneca, Bristol Myers Squibb, Merck, Ose Pharma, Roche, Sotio. MA reports research funding (to institution) from Genentech, Nektar Therapeutics, Merck, GSK, Novartis, Jounce Therapeutics, Bristol Myers Squibb, Eli Lilly, Adaptimmune, Shattuck Lab, and Gilead. Advisory boards: GSK, Shattuck Lab, Bristol Myers Squibb, AstraZeneca; reports speaker fees from AstraZeneca, and Nektar Therapeutics. AS reports participation in advisory boards for Merck, Bristol Myers Squibb, Novartis, Oncorus, Janssen, Medison, and Immunocore; reports research support: Novartis, Bristol Myers Squibb, Symphogen AstraZeneca/Medimmune, Merck, Bayer, Surface Oncology, Northern Biologics, Janssen Oncology/Johnson & Johnson, Roche, Regeneron, Alkermes, Array Biopharma/Pfizer, GSK, Treadwell, and Amgen. OR reports employment with AstraZeneca; reports research funding from Merck; reports speaker for activities supported by educational grants from Bristol Myers Squibb and Merck; reports consulting for Merck, Celgene, Five Prime, GSK, Bayer, Roche/Genentech, Puretech, Imvax, Sobi, Boehringer Ingelheim; reports pending patent for “Methods of using pembrolizumab and trebananib”. EMP, CMA, HZ, HS, SAG, MW, KMY, NY, and AHo report employment with GSK. MJC is an employee of Merck and owns stock. EVS is an employee of Merck. AM has been a principal or coinvestigator of clinical trials using OX40-targeted agents and/or has provided consulting services for Roche/Genentech, AstraZeneca, Pfizer, GSK, HiFiBiO, Bristol Myers Squibb, Shattuck Labs. JW reports consulting for Merck, Genentech, AstraZeneca, GSK, Novartis, Nektar, Celldex, Incyte, Biond, ImCheck, Sellas, Evaxion and EMD Serono; reports participation in advisory boards for Bristol Myers Squibb (compensated), CytoMx, Incyte, ImCheck, Biond, Sellas, Instil Bio, OncoC4, and Neximmune; reports equity holdings in Biond, Evaxion, Instil Bio, OncoC4, and Neximmune; reports research support (to institution) from Bristol Myers Squibb, Merck, GSK, Moderna, Pfizer, Novartis, and AstraZeneca, Moffitt Cancer Center; reports patent for ipilimumab biomarker and tumor-infiltrating lymphocytes preparation and a PD-1 patent (Biodesix). JVH reports other from GSK, AstraZeneca, Checkmate Pharmaceuticals, Brightpath Biotherapeutics, Eli Lilly & Co, Kairos Venture Investments, Triptych Health Partners; reports patent with Spectrum Pharmaceuticals., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)