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Breast cancer stem cells (BCSCs) are unique in their ability to undergo unlimited self-renewal, an essential process in breast cancer recurrence following metastatic dormancy. Emergent metastatic lesions were subjected to microarray analysis, which identified 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (Pfkfb3) as a differentially expressed gene coupled to metastatic recurrence. Here, we report that elevated Pfkfb3 expression correlates with the appearance of aggressive breast cancers and reduces relapse-free survival, as well as enhances BCSC self-renewal and metastatic outgrowth. We observe an inverse relationship between Pfkfb3 expression and autophagy, which reduces Pfkfb3 expression and elicits cellular dormancy. Targeted depletion of Atg3, Atg7, or p62/sequestosome-1 to inactivate autophagy restores aberrant Pfkfb3 expression in dormant BCSCs, leading to their reactivation of proliferative programs and outgrowth. Moreover, Pfkfb3 interacts physically with autophagy machinery, specifically the UBA domain of p62/sequestosome-1. Importantly, disrupting autophagy and this event enables Pfkfb3 to drive dormant BCSCs and metastatic lesions to recur. Cancer cells can use autophagy as a mechanism of surviving from external stresses. Here, the authors show that Pfkfb3, a glycolytic gene, is expressed in metastatic breast cancer cells but not in dormant cells that demonstrate features of autophagy.

The vast majority of image-detected breast abnormalities are diagnosed by percutaneous core needle biopsy (CNB) in contemporary practice. For frankly malignant lesions diagnosed by CNB, the standard practice of excision and multimodality therapy have been well-defined. However, for high-risk and selected benign lesions diagnosed by CNB, there is less consensus on optimal patient management and the need for immediate surgical excision. Here we outline the arguments for and against the practice of routine surgical excision of commonly encountered high-risk and selected benign breast lesions diagnosed by CNB. The entities reviewed include atypical ductal hyperplasia, atypical lobular hyperplasia, lobular carcinoma in situ, intraductal papillomas, and radial scars. The data in the peer-reviewed literature confirm the benefits of a patient-centered, multidisciplinary approach that moves away from the reflexive “yes” or “no” for routine excision for a given pathologic diagnosis.

Purpose Metaplastic breast cancer (MBC) is a rare, aggressive variant of breast cancer, with limited data available regarding treatment and outcomes. This study aims to review patients with MBC treated at our tertiary care institution with an emphasis on the role of treatment modality and histologic classification. Methods With IRB-approval, we queried our pathology database for patients with MBC diagnosis. All cases were re-evaluated by dedicated breast pathologists and confirmed as MBC breast cancer. Patient demographics, clinical/pathologic histology, and treatment were analyzed with respect to outcomes including local–regional recurrence (LRR), distant metastasis (DM), and overall survival (OS). Univariate and multivariate Cox proportional hazards models were performed to evaluate the impact on outcomes. Kaplan–Meier methods estimated survival. Results We evaluated 113 patients with MBC diagnosed between 2002 and 2013. Median age was 61 years and median pathologic tumor size 2.5 cm; 76 (67%) were ER/PR/Her2 negative, 83 (74%) grade 3. Median follow-up was 38 months. 47 (42%) underwent breast conservation therapy (BCT), 66 (58%) had mastectomy, 61 (54%) underwent adjuvant radiation (RT), and 85 (75%) had chemotherapy. At 2 and 5 years, the LRR/DM/OS rates were 12%/15%/90% and 21%/35%/69%, respectively. On Cox regression analysis, only adjuvant RT correlated with reduced LRR [RR 3.1 (1.13–9.88), p  = 0.027], while chemotherapy, type of surgery, and T-N stage did not. Only T-stage ( p  = 0.008) correlated with DM, however chemotherapy, RT, surgery type, and N-stage were not. Univariate analysis demonstrated histologic subtype did not significantly correlate with local ( p  = 0.54) or distant ( p  = 0.83) disease control. Conclusions This study represents among the largest institutional experiences in the outcomes of MBC. At this time, there does not appear to be a clear histologic subset of MBC which has significantly different clinical outcomes from the other subtypes. Although limited in its sample size, this study shows RT remains important in local–regional control.

Tumors adapt their phenotypes during growth and in response to therapies through dynamic changes in cellular processes. Connexin proteins enable such dynamic changes during development, and their dysregulation leads to disease states. The gap junction communication channels formed by connexins have been reported to exhibit tumor-suppressive functions, including in triple-negative breast cancer (TNBC). However, we find that connexin 26 (Cx26) is elevated in self-renewing cancer stem cells (CSCs) and is necessary and sufficient for their maintenance. Cx26 promotes CSC self-renewal by forming a signaling complex with the pluripotency transcription factor NANOG and focal adhesion kinase (FAK), resulting in NANOG stabilization and FAK activation. This FAK/NANOG-containing complex is not formed in mammary epithelial or luminal breast cancer cells. These findings challenge the paradigm that connexins are tumor suppressors in TNBC and reveal a unique function for Cx26 in regulating the core self-renewal signaling that controls CSC maintenance. Connexin proteins are usually considered as tumor suppressors. Here, the authors show that connexin 26 (Cx26) regulates the self-renewal of breast cancer stem cells via a ternary complex with FAK and NANOG.

Background Breast cancer subtypes Luminal A and Luminal B are classified by the expression of PAM50 genes and may benefit from different treatment strategies. Machine learning models based on H&E images may contain features associated with subtype, allowing early identification of tumors with higher risk of recurrence. Methods H&E images (n = 630 ER+/HER2-breast cancers) were pixel-level segmented into epithelium and stroma. Convolutional neural network and multiple instance learning were used to extract image features from original and segmented images. Patient-level classification models were trained to discriminate Luminal A versus B image features in tenfold cross-validation, with or without grade adjustment. The best-performing visual classifier was incorporated into envisioned diagnostic protocols as an alternative to genomic testing (PAM50). The protocols were then compared in time-to-recurrence models. Results Among ER+/HER2-tumors, the image-based protocol differentiated recurrence times with a hazard ratio (HR) of 2.81 (95% CI: 1.73–4.56), which was similar to the HR for PAM50 (2.66, 95% CI: 1.65–4.28). Grade adjustment did not improve subtype prediction accuracy, but did help balance sensitivity and specificity. Among high grade participants, sensitivity and specificity (0.734 and 0.474, respectively) became more similar (0.732 and 0.624, respectively) in grade-adjusted models. The original and epithelium-specific images had similar performance and highest accuracy, followed by stroma or binarized images showing only the epithelial-stromal interface. Conclusions Given low rates of genomic testing uptake nationally, image-based methods may help identify ER+/HER2-patients who could benefit from testing.

BackgroundThe PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited.MethodsWe evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples.ResultsTechnical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity.ConclusionThe PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2–4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008–2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Importance The COVID‐19 pandemic led to reductions in primary care and cancer screening visits, which may delay detection of some cancers. The impact on incidence has not been fully quantified. We examined change in cancer incidence to determine how the COVID‐19 pandemic may have altered the characteristics of cancers diagnosed among women. Methods This study included female patients aged ≥18 years and diagnosed with breast (n = 9489), colon (n = 958), pancreatic (n = 669), or uterine (n = 1991) cancer at three hospitals in North Carolina. Using interrupted time series, we compared incidence of cancers diagnosed between March 2020 and November 2020 (during pandemic) with cancers diagnosed between January 2016 and February 2020 (pre‐pandemic). Results During the pandemic, incidence of breast and uterine cancers was significantly lower than expected compared to pre‐pandemic (breast—18%, p = 0.03; uterine −20%, p = 0.05). Proportions of advanced pathologic stage and hormone receptor‐negative breast cancers, and advanced clinical stage and large size uterine cancers were more prevalent during the pandemic. No significant changes in incidence were detected for pancreatic (−20%, p = 0.08) or colon (+14%, p = 0.30) cancers. Conclusion and Relevance In women, the COVID‐19 pandemic resulted in a significant reduction in the incidence of breast and uterine cancers, but not colon or pancreatic cancers. A change in the proportion of poor prognosis breast and uterine cancers suggests that some cancers that otherwise would have been diagnosed at an earlier stage will be detected in later years. Continued analysis of long‐term trends is needed to understand the full impact of the pandemic on cancer incidence and outcomes. Breast and uterine cancer incidence was significantly lower than expected during the first months of the pandemic, suggesting that a significant number of breast and uterine cancers went undiagnosed during that time. Delayed diagnosis of cancers with better prognostic features may result in a shift to less treatable cancers diagnosed in subsequent years.

The Wnt gene family encodes an evolutionarily conserved group of proteins that regulate cell growth, differentiation and stem cell self-renewal. Aberrant Wnt signaling in human breast tumors has been proposed as a driver of tumorigenesis, especially in the basal-like tumor subtype where canonical Wnt signaling is both enriched and predictive of poor clinical outcomes. The development of effective Wnt-based therapeutics, however, has been slowed in part by a limited understanding of the context-dependent nature with which these aberrations influence breast tumorigenesis. We previously reported that MMTV-Wnt1 mice, an established model for studying Wnt signaling in breast tumors, develop two subtypes of tumors by gene expression classification: Wnt1-EarlyEx and Wnt1-LateEx. Here, we extend this initial observation and show that Wnt1-EarlyEx tumors exhibit high expression of canonical Wnt, non-canonical Wnt, and EGFR signaling pathway signatures. Therapeutically, Wnt1-EarlyEx tumors showed a dynamic reduction in tumor volume when treated with an EGFR inhibitor. Wnt1-EarlyEx tumors had primarily Cd49fpos/Epcamneg FACS profiles, but it was not possible to serially transplant these tumors into wild-type FVB female mice. Conversely, Wnt1-LateEx tumors had a bloody gross pathology, which was highlighted by the presence of ‘blood lakes’ identified by H&E staining. These tumors had primarily Cd49fpos/Epcampos FACS profiles, but also contained a secondary Cd49fpos/Epcamneg subpopulation. Wnt1-LateEx tumors were enriched for activating Hras1 mutations and were capable of reproducing tumors when serially transplanted into wild-type FVB female mice. This study definitively shows that the MMTV-Wnt1 mouse model produces two phenotypically distinct subtypes of mammary tumors that differ in multiple biological aspects including sensitivity to an EGFR inhibitor.

PurposeTriple negative breast cancer (TNBC) is characterized by the presence of immune cells in the tumor microenvironment, however, the response to single-agent immune checkpoint inhibitor (ICI) therapy is modest. Preclinical models have demonstrated that intratumoral regulatory T cells (Tregs) dampen the antitumor response to ICI. We performed a single-arm phase II trial to evaluate the efficacy of a single low dose of cyclophosphamide (Cy) to deplete Tregs administered before initiating pembrolizumab.Patients and methods40 patients with pretreated metastatic TNBC were enrolled. The primary endpoints were progression-free survival (PFS) and change in peripheral blood Tregs after Cy. Secondary endpoints included overall response rate (ORR), duration of response, overall survival, treatment-related adverse events (AEs), and correlative evaluations.ResultsMedian PFS was 1.8 months, and the ORR was 21%. Tregs were not significantly decreased after Cy prior to ICI (−3.3%, p=0.19), and increased significantly after the first cycle of therapy (+21% between cycles 1 and 2, p=0.005). Immune-related AEs were similar to historical pembrolizumab monotherapy, and were associated with response to therapy (p=0.02). Patients with pretreatment tumors harboring increased expression of B cell metagene signatures and increased circulating B cell receptor repertoire diversity were associated with clinical response and immune-related toxicity (IRT).ConclusionsAmong patients with heavily pretreated TNBC, Cy prior to pembrolizumab did not significantly deplete Tregs, and in those with decreased numbers there was rapid recovery following therapy. Increased B cell gene expression in baseline samples was associated with clinical response and IRT.