Explore the vast range of titles available.

Despite advances in breast cancer diagnosis and treatment, many patients still fail therapy, resulting in disease progression, recurrence, and reduced overall survival. Historically, much focus has been put on the intrinsic subtyping based in the presence (or absence) of classical immunohistochemistry (IHC) markers such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-related protein (HER2). However, it is widely understood that tumors are composed of heterogeneous populations of cells with a hierarchical organization driven by cancer stem cells (CSCs). In breast tumors, this small population of cells displaying stem cell properties is known as breast CSCs (BCSCs). This rare population exhibit a CD44+/CD24−/low phenotype with high ALDH activity (ALDH+), and possesses higher tolerability to chemotherapy, hormone therapy, and radiotherapy and is able to reproduce the bulk of the tumor after reduction of cell populations sensitive to first-line therapy leading to disease relapse. In this review, we present special attention to BCSCs with future directions in the establishment of a therapy targeting this population. Drugs targeting the main BCSCs signaling pathways undergoing clinical trials are also summarized.

The microenvironment of a cancer stem cell (CSC) niche is often found in coexistence with cancer-associated fibroblasts (CAFs). Here, we show the first in-depth analysis of the interaction between primary triple-negative breast cancer stem cells (BCSCs) with fibroblasts. Using 2D co-culture models with specific seeding ratios, we identified stromal fibroblast aggregation at the BCSC cluster periphery, and, on closer observation, the aggregated fibroblasts was found to encircle BCSC clusters in nematic organization. In addition, collagen type I and fibronectin accumulation were also found at the BCSC–stromal periphery. MACE-Seq analysis of BCSC-encapsulating fibroblasts displayed the transformation of stromal fibroblasts to CAFs and the upregulation of fibrosis regulating genes of which the Interferon Regulatory Factor 6 (IRF6) gene was identified. Loss of function experiments with the IRF6 gene decreased fibroblast encapsulation around BCSC clusters in 2D co-cultures. In BCSC xenografts, fibroblast IRF6 expression led to an increase in the stromal area and fibroblast density in tumors, in addition to a reduction in necrotic growth. Based on our findings, we propose that fibroblast IRF6 function is an important factor in the development of the stromal microenvironment and in sustaining the BCSC tumor niche.

Triple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer that lacks targeted therapy options, and patients diagnosed with TNBC have poorer outcomes than patients with other breast cancer subtypes. Emerging evidence suggests that breast cancer stem cells (BCSCs), which have tumor-initiating potential and possess self-renewal capacity, may be responsible for this poor outcome by promoting therapy resistance, metastasis, and recurrence. TNBC cells have been consistently reported to display cancer stem cell (CSC) signatures at functional, molecular, and transcriptional levels. In recent decades, CSC-targeting strategies have shown therapeutic effects on TNBC in multiple preclinical studies, and some of these strategies are currently being evaluated in clinical trials. Therefore, understanding CSC biology in TNBC has the potential to guide the discovery of novel therapeutic agents in the future. In this review, we focus on the self-renewal signaling pathways (SRSPs) that are aberrantly activated in TNBC cells and discuss the specific signaling components that are involved in the tumor-initiating potential of TNBC cells. Additionally, we describe the molecular mechanisms shared by both TNBC cells and CSCs, including metabolic plasticity, which enables TNBC cells to switch between metabolic pathways according to substrate availability to meet the energetic and biosynthetic demands for rapid growth and survival under harsh conditions. We highlight CSCs as potential key regulators driving the aggressiveness of TNBC. Thus, the manipulation of CSCs in TNBC can be a targeted therapeutic strategy for TNBC in the future.

[This corrects the article DOI: 10.3389/fphar.2023.1150774.].

[This corrects the article DOI: 10.3389/fphar.2023.1150774.].

Phosphoethanolamine (pEtN) cellulose is a naturally occurring modified cellulose produced by several Enterobacteriaceae. The minimal components of the E. coli cellulose synthase complex include the catalytically active BcsA enzyme, a hexameric semicircle of the periplasmic BcsB protein, and the outer membrane (OM)-integrated BcsC subunit containing periplasmic tetratricopeptide repeats (TPR). Additional subunits include BcsG, a membrane-anchored periplasmic pEtN transferase associated with BcsA, and BcsZ, a periplasmic cellulase of unknown biological function. While cellulose synthesis and translocation by BcsA are well described, little is known about its pEtN modification and translocation across the cell envelope. We show that the N-terminal cytosolic domain of BcsA positions three BcsG copies near the nascent cellulose polymer. Further, the semicircle’s terminal BcsB subunit tethers the N-terminus of a single BcsC protein in a trans-envelope secretion system. BcsC’s TPR motifs bind a putative cello-oligosaccharide near the entrance to its OM pore. Additionally, we show that only the hydrolytic activity of BcsZ but not the subunit itself is necessary for cellulose secretion, suggesting a secretion mechanism based on enzymatic removal of translocation incompetent cellulose. Lastly, protein engineering introduces cellulose pEtN modification in orthogonal cellulose biosynthetic systems. These findings advance our understanding of pEtN cellulose modification and secretion. Enterobacteriaceae modify cellulose with lipid-derived pEtN groups to promote biofilm cohesion. Here, using structural and biochemical analyses, the authors provide further insights into the molecular interactions of BcsA, BcsG, BcsB, and BcsC facilitating pEtN modification and secretion of cellulose.

Breast cancer is one of the most frequently detected malignancies worldwide. It is responsible for more than 15% of all death cases caused by cancer in women. Breast cancer is a heterogeneous disease representing various histological types, molecular characteristics, and clinical profiles. However, all breast cancers are organized in a hierarchy of heterogeneous cell populations, with a small proportion of cancer stem cells (breast cancer stem cells (BCSCs)) playing a putative role in cancer progression, and they are responsible for therapeutic failure. In different molecular subtypes of breast cancer, they present different characteristics, with specific marker profiles, prognoses, and treatments. Recent efforts have focused on tackling the Wnt, Notch, Hedgehog, PI3K/Akt/mTOR, and HER2 signaling pathways. Developing diagnostics and therapeutic strategies enables more efficient elimination of the tumor mass together with the stem cell population. Thus, the knowledge about appropriate therapeutic methods targeting both “normal” breast cancer cells and breast cancer stem cell subpopulations is crucial for success in cancer elimination.

Purpose The Breast Cancer Surveillance Consortium (BCSC) model predicts risk of invasive breast cancer risk based on age, race, family history, breast density, and history of benign breast disease, including lobular carcinoma in situ (LCIS). However, validation studies for this model included few women with LCIS. We sought to evaluate the accuracy of the BCSC model among this cohort. Methods Women with LCIS diagnosed between 1983 and 2017 were identified from a prospectively maintained database. The BCSC score was calculated; those with prior breast cancer, unknown breast density, age < 35 years or > 74 years, or with history of chemoprevention use were excluded. The Kaplan–Meier method was used to estimate incidence rates. Time-dependent receiver operating characteristic (ROC) analysis was used to analyze the discriminative capacity of the model. Results 1302 women with LCIS were included. At a median follow-up of 7 years, 152 women (12%) developed invasive cancer (6 with bilateral disease). Cumulative incidences of invasive breast cancer were 7.1% (95% CI 5.6–8.7) and 13.3% (95% CI 10.9–15.6), respectively, and the median BCSC risk scores were 4.9 and 10.4, respectively, at 5 and 10 years. The median 10-year BCSC score was significantly lower than the 10–year Tyrer-Cuzick score (10.4 vs 20.8, p  < 0.001). The ROC curve scores (AUC) for BCSC at 5 and 10 years were 0.59 (95% CI 0.52–0.66) and 0.58 (95% CI 0.52–0.64), respectively. Conclusion The BCSC model has moderate accuracy in predicting invasive breast cancer risk among women with LCIS with fair discrimination for risk prediction between individuals.

Purpose Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC. Methods We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER). First, a matched lasso logistic regression model for estimating relative risks (RR) is developed. Then, it is combined with relevant hazard rates and attributable risks to obtain absolute risks. Six-fold cross-validation is used to internally validate CBCRisk-Black. We also compare CBCRisk-Black with CBCRisk, an existing CBC risk prediction model. Results The RR model uses data from BCSC on 744 Black women (186 cases). CBCRisk-Black has four risk factors (RR compared to baseline): breast density (2.13 for heterogeneous/extremely dense), family history of BC (2.28 for yes), first BC tumor size (2.14 for T3/T4, 1.56 for TIS), and age at first diagnosis of BC (1.41 for < 40). The area under the receiver operating characteristic curve (AUC) for 3- and 5-year predictions are 0.72 and 0.65 for CBCRisk-Black while those are 0.65 and 0.60 for CBCRisk. Conclusion CBCRisk-Black may serve as a useful tool to clinicians in counseling Black BC patients by providing a more accurate and personalized CBC risk estimate.

Purpose We evaluated self-report of decision quality and regret with breast cancer surgical treatment by pre-operative breast MRI use in women recently diagnosed with breast cancer. Methods We conducted a survey with 957 women aged 18 + with stage 0-III breast cancer identified in the Breast Cancer Surveillance Consortium. Participants self-reported receipt of pre-operative breast MRI. Primary outcomes were process measures in the Breast Cancer Surgery Decision Quality Instrument (BCS-DQI) (continuous outcome) and Decision Regret Scale (dichotomized outcome as any/none). Generalized estimating equations with linear and logit link were used to estimate adjusted associations between breast MRI and primary outcomes. All analyses were also stratified by breast density. Results Survey participation rate was 27.9% (957/3430). Study population was primarily > 60 years, White, college educated, and diagnosed with early-stage breast cancer. Pre-operative breast MRI was reported in 46% of women. A higher proportion of women who were younger age (< 50 years), commercially insured, and self-detected their breast cancer reported pre-operative breast MRI use. In adjusted analysis, pre-operative breast MRI use compared with no use was associated with a small but statistically significantly higher decision quality scores (69.5 vs 64.7, p-value = 0.043). Decision regret did not significantly differ in women who reported pre-operative breast MRI use compared with no use (54.2% v. 48.7%, respectively, p-value = 0.11). Study results did not vary when stratified by breast density for either primary outcome. Conclusions and relevance Breast MRI use in the diagnostic work-up of breast cancer does not negatively alter women’s perceptions of surgical treatment decisions in early survivorship. Clinical Trials Registration Number : NCT03029286.