Breast Cancer Heterogeneity

Molecular Basis of Breast Tumor Heterogeneity

Breast cancer (BC) is a profoundly heterogenous disease, with diverse molecular, histological, and clinical variations. The intricate molecular landscape of BC is evident even at early stages, illustrated by the complexity of the evolution from precursor lesions to invasive carcinoma. The key for therapeutic decision-making is the dynamic assessment of BC receptor status and clinical subtyping. Hereditary BC adds an additional layer of complexity to the disease, given that different cancer susceptibility genes contribute to distinct phenotypes and genomic features. Furthermore, the various BC subtypes display distinct metabolic demands and immune microenvironments. Finally, genotypic-phenotypic correlations in special histologic subtypes of BC inform diagnostic and therapeutic approaches, highlighting the significance of thoroughly comprehending BC heterogeneity.

The clinicopathological significance of BRI3BP in women with invasive breast cancer

Background

Invasive breast cancer (BC) is a highly life-threatening disease affecting women world-wide. While its early identification may benefit the provision of more effective therapies, several BC-associated factors may influence BC patients' therapeutic outcomes. Therefore, identifying novel prognostic and therapeutic targets for invasive BC can help with accurate prognosis and therapy-related decisions. The BRI3 binding protein (BRI3BP) gene was found to be a principal gene in invasive BC cohorts using artificial neural network (ANN) techniques. Thus, this study aimed to evaluate the clinicopathological significance of BRI3BP at the transcriptomic and proteomic levels in invasive BC.

Methods

Two transcriptomic BC cohorts, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; n=1,980) and The Cancer Genome Atlas (TCGA; n=854), were used to evaluate BRI3BP expression at the mRNA level. Formalin-fixed paraffin-embedded (FFPE) tissues from an invasive BC cohort (n=100) were also used to evaluate BRI3BP expression at the protein level via immunohistochemistry. The association between BRI3BP expression, clinicopathological characteristics, and patient outcomes was evaluated.

Results

In both METABRIC and TCGA cohorts, high expression of BRI3BP was significantly associated with aggressive tumor features such as high histological grade, large tumor size, and lymph vascular invasion (LVI) positivity. At the protein level, high BRI3BP expression was associated with high histological grade, hormone receptor negativity, high expression of Ki67, and poor outcome.

Conclusions

This study revealed the prognostic significance of BRI3BP in invasive BC patients. Further functional assessment is needed to confirm the biological role of BRI3BP in BC.

FAHD1 and mitochondrial metabolism: a decade of pioneering discoveries

This review consolidates a decade of research on fumarylacetoacetate hydrolase domain containing protein 1 (FAHD1), a mitochondrial oxaloacetate tautomerase and decarboxylase with profound implications in cellular metabolism. Despite its critical role as a regulator in mitochondrial metabolism, FAHD1 has remained an often-overlooked enzyme in broader discussions of mitochondrial function. After more than 12 years of research, it is increasingly clear that FAHD1's contributions to cellular metabolism, oxidative stress regulation, and disease processes such as cancer and aging warrant recognition in both textbooks and comprehensive reviews. The review delves into the broader implications of FAHD1 in mitochondrial function, emphasizing its roles in mitigating reactive oxygen species (ROS) levels and regulating complex II activity, particularly in cancer cells. This enzyme's significance is further highlighted in the context of aging, where FAHD1's activity has been shown to influence cellular senescence, mitochondrial quality control, and the aging process. Moreover, FAHD1's involvement in glutamine metabolism and its impact on cancer cell proliferation, particularly in aggressive breast cancer subtypes, underscores its potential as a therapeutic target. In addition to providing a comprehensive account of FAHD1's biochemical properties and structural insights, the review integrates emerging hypotheses regarding its role in metabolic reprogramming, immune regulation, and mitochondrial dynamics. By establishing a detailed understanding of FAHD1's physiological roles and therapeutic potential, this work advocates for FAHD1's recognition in foundational texts and resources, marking a pivotal step in its integration into mainstream metabolic research and clinical applications in treating metabolic disorders, cancer, and age-related diseases.

Prognostic Significance of DSCC1, a Biomarker Associated with Aggressive Features of Breast Cancer

Background and Objectives: Invasive breast cancer (BC) was traditionally investigated visually, and no technique could identify the key molecular drivers of patient survival. However, essential molecular drivers of invasive BC have now been discovered using innovative genomic, transcriptomic, and proteomic methodologies. Nevertheless, few evaluations of the prognostic factors of BC in Saudi Arabia have been performed. Evaluating the biomarkers associated with the development of early-stage BC could help determine the risk of metastasis and guide treatment decisions. In a previous study, using large BC cohorts and artificial neural network techniques, DNA replication and sister chromatid cohesion 1 (DSCC1) was found to be one of the principal genes in invasive BC samples. To date, no studies have addressed the prognostic significance of DSCC1 in invasive BC and its association with aggressive tumor behavior. This research aimed to address this gap. Materials and Methods: The association of clinicopathological features and patient outcomes with DSCC1 expression at the mRNA level was assessed using the Molecular Taxonomy Breast Cancer International Consortium (METABRIC; n = 1980) and The Cancer Genome Atlas (TCGA; n = 854) cohorts. DSCC1 was also evaluated at the protein level using immunohistochemistry on samples from invasive BC patients (n = 100) presenting to King Abdul Aziz Specialist Hospital in Saudi Arabia. The association of clinicopathological parameters (including patient age, tumor grade, tumor size, and patient outcome) with protein level was also evaluated. Results: In both METABRIC and TCGA cohorts, high expression of DSCC1 was significantly associated with high histological grade, large tumor size, lymphovascular invasion positivity, and hormone receptor negativity (all p < 0.001). A high DSCC1 mRNA level was associated with poor outcomes (p < 0.001 for METABRIC, p = 0.23 for TCGA). At the protein level, high DSCC1 expression was associated with high histological grade (p = 0.001), lymph node presence (p = 0.008), hormone receptor negativity (p = 0.005), high Ki67 expression (p = 0.036), and shorter survival (p = 0.008). Conclusions: This study confirmed the prognostic significance of DSCC1 in invasive BC patients. DSCC1 could be a therapeutic target in BC cases with poor outcomes.

Characterization of Breast Cancer Intra-Tumor Heterogeneity Using Artificial Intelligence

Intra-tumor heterogeneity (ITH) is a fundamental characteristic of breast cancer (BC), influencing tumor progression, prognosis, and therapeutic responses. However, the complexity of ITH in BC makes its accurate characterization challenging. This study leverages deep learning (DL) techniques to comprehensively evaluate ITH in early-stage luminal BC and provide a nuanced understanding of its impact on tumor behavior and patient outcomes. A large cohort (n = 2561) of early-stage luminal BC was evaluated using whole slide images (WSIs) of hematoxylin and eosin-stained slides of excision specimens. Morphological features of both the tumor and stromal components were meticulously annotated by a panel of pathologists in a subset of cases. A DL model was applied to develop an algorithm to assess the degree of heterogeneity of various morphological features per individual case utilizing defined patches. The results of extracted features were used to generate an overall heterogeneity score that was correlated with the clinicopathological features and outcome. Overall, 162 features were quantified and a significant positive correlation between these features was identified. Specifically, there was a significant association between a high degree of intra-tumor heterogeneity and larger tumor size, poorly differentiated tumors, highly proliferative tumors, tumors of no special type (NST), and those with low estrogen receptor (ER) expression. When all features are considered in combination, a high overall heterogeneity score was significantly associated with parameters characteristic of aggressive tumor behavior, and it was an independent predictor of poor patient outcome. In conclusion, DL models can be used to accurately decipher the complexity of ITH and provide extra information for outcome prediction.

The impact of hsa-miR-1972 on the expression of von Willebrand factor in breast cancer progression regulation

Background

Breast cancer (BC) is one of most frequent female malignancies that poses multiple challenges in treatment and prevention. This study aimed to explore the role of miRNAs and their target genes during the BC progression.

Methods

Based on the BC data (113 normal and 1,118 tumor samples) from the TCGA-BRCA dataset, a single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the cancer migration scores, and weighted gene co-expression network analysis (WGCNA) were performed using the WGCNA R package, with a focus on the set of genes associated with cancer migration. Key modules and hub genes related to cell migration and signaling pathways were identified. Survival analysis of hub genes was conducted using the survminer R package, and prediction of regulatory miRNAs were performed to analyze their impact on BC prognosis. In addition, the BC cell lines MCF-7 and MDA-MB-231 were used to further explore the effect of hsa-miR-1972 mimics on the gene expression and angiogenic factor regulation.

Results

The study classified important modules (MEblue, MEmagenta, MEpink, and MEfloralwhite) associated with cell migration and identified three hub genes, namely, MRPL20, COL4A1 and VWF. Survival analysis showed that certain hub genes with a low expression were related to a poor prognosis, whereas low-expressed COL4A1 and VWF were related to better survival outcomes. We also found that hsa-miR-1972 mimics significantly downregulated critical genes involved in BC metastasis and angiogenesis and effectively inhibited the proliferation of BC cell lines, showing a strong therapeutic potential. Manipulation of VWF expression in cells overexpressing hsa-miR-1972 had significant effects on the malignant markers and angiogenic factors, suggesting a novel therapeutic direction for BC treatment.

Conclusion

Our study highlighted the complex interplay of genetic factors in BC progression as well as the therapeutic potential of targeting specific miRNAs and their related hub genes. These findings provided novel insights into the pathogenesis of BC and suggested new direction for the therapeutic development for the cancer.

Radiomics Analysis of Intratumoral and Various Peritumoral Regions From Automated Breast Volume Scanning for Accurate Ki-67 Prediction in Breast Cancer Using Machine Learning

RATIONALE AND OBJECTIVES

Current radiomics research primarily focuses on intratumoral regions and fixed peritumoral areas, lacking optimization for accurate Ki-67 prediction. This study aimed to develop machine learning (ML) models to analyze radiomic features from Automated Breast Volume Scanning (ABVS) images of different peritumoral region sizes to identify the optimal size for accurate preoperative Ki-67 prediction.

MATERIALS AND METHODS

A total of 668 breast cancer patients were enrolled and divided into training (486) and testing (182) cohorts. In the training cohort, ML models were developed for intratumoral and peritumoral regions (2, 4, 6, 8, and 10 mm). Relevant Ki-67 features for each ROI were identified, and different models were compared to determine the optimal one. These models were validated using a testing cohort to find the most accurate peritumoral region for Ki-67 prediction. SHAP (Shapley Additive Explanations) analysis was performed to identify key radiomic features from the optimal model.

RESULTS

The Extreme Gradient Boosting (XGBoost) model for the intratumoral region combined with the 6 mm peritumoral region achieved the highest predictive accuracy, with an AUC of 0.957 in the training cohort and 0.920 in the testing cohort. Calibration curves confirmed reliability, and decision curve analysis demonstrated the highest net benefit. SHAP indicated that 6 mm peritumoral radiomic features are more significant than intratumoral features.

CONCLUSION

The XGBoost model using ABVS-derived radiomic features from both the intratumoral and 6 mm peritumoral regions provides the most accurate preoperative Ki-67 prediction.

Nottingham prognostic x (NPx): a risk stratification tool in ER-positive HER2-negative breast cancer: a validation study

AIMS

In this study, we validate the use of Nottingham Prognostic x (NPx), consisting of tumour size, tumour grade, progesterone receptor (PR) and Ki67 in luminal BC.

MATERIALS AND METHODS

Two large cohorts of luminal early-stage BC (n = 2864) were included. PR and Ki67 expression were assessed using full-face resection samples using immunohistochemistry. NPx was calculated and correlated with clinical variables and outcome, together with Oncotype DX recurrence score (RS), that is frequently used as a risk stratifier in luminal BC.

RESULTS

In the whole cohort, 38% of patients were classified as high risk using NPx which showed significant association with parameters characteristics of aggressive tumour behaviour and shorter survival (P < 0.0001). NPx classified the moderate Nottingham Prognostic Index (NPI) risk group (n = 1812) into two distinct prognostic subgroups. Of the 82% low-risk group, only 3.8% developed events. Contrasting this, 14% of the high-risk patients developed events during follow-up. A strong association was observed between NPx and Oncotype Dx RS (P < 0.0001), where 66% of patients with intermediate risk RS who had subsequent distant metastases also had a high-risk NPx.

CONCLUSION

NPx is a reliable prognostic index in patients with luminal early-stage BC, and in selected patients may be used to guide adjuvant chemotherapy recommendations.

Outcomes of De Novo Oligometastatic Breast Cancer Treated With Surgery of Primary and Metastasis Directed Radiotherapy

OBJECTIVES

With sensitive imaging for breast cancer, the question arises whether present-day oncologists treat dOMBC with palliative systemic therapy (ST), which, a few years earlier, would have been treated with curative intent. We retrospectively analyzed outcomes of dOMBC treated with curative intent using a combination of surgery, metastasis-directed radiotherapy (RT), and adjuvant/neoadjuvant ST and have also explored the possible role of total lesional glycolysis of metastases and p53 immunohistochemistry in predicting outcomes.

METHODS

Data were collected from a prospectively maintained database using electronic medical records and Radiation Oncology Information System. In the study, dOMBC was defined as up to 3 metastatic sites, all amenable to treatment with ablative RT and primary and axillary disease amenable to curative surgery. Patients were treated with surgery, ST, and RT.

RESULTS

Patients underwent either breast conservation surgery or modified radical mastectomy. Patients were treated with 6 to 8 cycles of chemotherapy in the neoadjuvant and/or adjuvant setting. Hormone receptor-positive patients received either tamoxifen or aromatase inhibitors. Trastuzumab was offered to Her-2-neu receptor-positive patients. RT included locoregional RT and metastases-directed ablative body RT. The median progression-free survival was 39 months (95% CI: -28.7 to 50.1 mo). Two and 3 year estimated disease-free survival (DFS) was 79% and 60.5%, respectively. The median overall survival was not reached. The estimated 3-year overall survival was 87.3%. Total lesional glycolysis of metastases score and p53 status did not affect DFS.

CONCLUSION

Combination treatment of surgery, metastases-directed ablative RT, and ST may provide prolonged DFS in dOMBC.

Enhancing Ki-67 Prediction in Breast Cancer: Integrating Intratumoral and Peritumoral Radiomics From Automated Breast Ultrasound via Machine Learning

RATIONALE AND OBJECTIVES

Traditional Ki-67 evaluation in breast cancer (BC) via core needle biopsy is limited by repeatability and heterogeneity. The automated breast ultrasound system (ABUS) offers reproducibility but is constrained to morphological and echoic assessments. Radiomics and machine learning (ML) offer solutions, but their integration for improving Ki-67 predictive accuracy in BC remains unexplored. This study aims to enhance ABUS by integrating ML-assisted radiomics for Ki-67 prediction in BC, with a focus on both intratumoral and peritumoral regions.

MATERIALS AND METHODS

A retrospective analysis was conducted on 936 BC patients, split into training (n = 655) and testing (n = 281) cohorts. Radiomics features were extracted from intra- and peritumoral regions via ABUS. Feature selection involved Z-score normalization, intraclass correlation, Wilcoxon rank sum tests, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator logistic regression. ML classifiers were trained and optimized for enhanced predictive accuracy. The interpretability of the optimized model was further augmented by employing Shapley additive explanations (SHAP).

RESULTS

Of the 2632 radiomics features in each patient, 15 were significantly associated with Ki-67 levels. The support vector machine (SVM) was identified as the optimal classifier, with area under the receiver operating characteristic curve values of 0.868 (training) and 0.822 (testing). SHAP analysis indicated that five peritumoral and two intratumoral features, along with age and lymph node status, were key determinants in the predictive model.

CONCLUSION

Integrating ML with ABUS-based radiomics effectively enhances Ki-67 prediction in BC, demonstrating the SVM model's strong performance with both radiomics and clinical factors.

Clinical and economic outcomes of adding [18F]FES PET/CT in estrogen receptor status identification in metastatic and recurrent breast cancer in the US

BACKGROUND AND OBJECTIVES

Correct identification of estrogen receptor (ER) status in breast cancer (BC) is crucial to optimize treatment; however, standard of care, involving biopsy and immunohistochemistry (IHC), and other diagnostic tools such as 2-deoxy-2-[18F]fluoro-D-glucose or 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), can yield inconclusive results. 16α-[18F]fluoro-17β-fluoroestradiol ([18F]FES) can be a powerful tool, providing high diagnostic accuracy of ER-positive disease. The aim of this study was to estimate the budget impact and cost-effectiveness of adding [18F]FES PET/CT to biopsy/IHC in the determination of ER-positive status in metastatic (mBC) and recurrent breast cancer (rBC) in the United States (US).

METHODS

An Excel-based decision tree, combined with a Markov model, was developed to estimate the economic consequences of adding [18F]FES PET/CT to biopsy/IHC for determining ER-positive status in mBC and rBC over 5 years. Scenario A, where the determination of ER-positive status is carried out solely through biopsy/IHC, was compared to scenario B, where [18F]FES PET/CT is used in addition to biopsy/IHC.

RESULTS

The proportion of true positive and true negative test results increased by 0.2 to 8.0 percent points in scenario B compared to scenario A, while re-biopsies were reduced by 94% to 100%. Scenario B resulted in cost savings up to 142 million dollars.

CONCLUSIONS

Adding [18F]FES PET/CT to biopsy/IHC may increase the diagnostic accuracy of the ER status, especially when a tumor sample cannot be obtained, or the risk of a biopsy-related complication is high. Therefore, adding [18F]FES PET/CT to biopsy/IHC would have a positive impact on US clinical and economic outcomes.

The therapeutic effect of traditional Chinese medicine on breast cancer through modulation of the Wnt/β-catenin signaling pathway

Breast cancer, the most prevalent malignant tumor among women globally, is significantly influenced by the Wnt/β-catenin signaling pathway, which plays a crucial role in its initiation and progression. While conventional chemotherapy, the standard clinical treatment, suffers from significant drawbacks like severe side effects, high toxicity, and limited prognostic efficacy, Traditional Chinese Medicine (TCM) provides a promising alternative. TCM employs a multi-targeted therapeutic approach, which results in fewer side effects and offers a high potential for effective treatment. This paper presents a detailed analysis of the therapeutic impacts of TCM on various subtypes of breast cancer, focusing on its interaction with the Wnt/β-catenin signaling pathway. Additionally, it explores the effectiveness of both monomeric and compound forms of TCM in the management of breast cancer. We also discuss the potential of establishing biomarkers for breast cancer treatment based on key proteins within the Wnt/β-catenin signaling pathway. Our aim is to offer new insights into the prevention and treatment of breast cancer and to contribute to the standardization of TCM.

Rapid autopsies to enhance metastatic research: the UPTIDER post-mortem tissue donation program

Research on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per patient from its first 20 patients. In a dedicated experiment, we show the mild impact of increasing time after death on RNA quality, transcriptional profiles and immunohistochemical staining in tumor tissue samples. We show that this impact can be counteracted by organ cooling. We successfully generated ex vivo models from tissue and liquid biopsies from distinct histological subtypes of breast cancer. We anticipate these and future findings of UPTIDER to elucidate mechanisms of disease progression and treatment resistance and to provide tools for the exploration of precision medicine strategies in the metastatic setting.

FOXC1 and SOX10 in Estrogen Receptor-Low Positive/HER2-Negative Breast Cancer: Potential Biomarkers for the Basal-like Phenotype Prediction

CONTEXT.—

Breast cancer with low (1%-10%) estrogen receptor (ER) expression (ER-low positive) constitutes a small portion of invasive breast cancers, and the treatment strategy for these tumors remains debatable.

OBJECTIVE.—

To characterize the features and outcomes of ER-low positive patients, and clarify the clinical significance of FOXC1 and SOX10 expression in ER-low positive/HER2-negative tumors.

DESIGN.—

Among 9082 patients diagnosed with primary invasive breast cancer, the clinicopathologic features of those with ER-low positive breast cancer were characterized. FOXC1 and SOX10 mRNA levels were analyzed in ER-low positive/HER2-negative cases from public data sets. The expression of FOXC1 and SOX10 in ER-low positive/HER2-negative tumors was evaluated by immunohistochemistry.

RESULTS.—

The clinicopathologic study of ER-low positive tumors indicated more aggressive characteristics compared with those tumors with ER >10%, while they had more overlapping features with ER-negative tumors irrespective of the HER2 status. The intrinsic molecular subtype of ER-low positive cases with high FOXC1 and SOX10 mRNA expression was more likely to be nonluminal. Among the ER-low positive/HER2-negative tumors, 56.67% (51 of 90) and 36.67% (33 of 90) were positive for FOXC1 and SOX10, respectively, which was significantly positively correlated with CK5/6 expression. In addition, the survival analysis demonstrated no significant difference between patients who received and who did not receive endocrine therapy.

CONCLUSIONS.—

ER-low positive breast cancers biologically overlap more with ER-negative tumors. ER-low positive/HER2-negative cases demonstrate a high rate of FOXC1 or SOX10 expression, and these cases might be better categorized as a basal-like phenotype/subtype. FOXC1 and SOX10 testing may be used for the intrinsic phenotype prediction for ER-low positive/HER2-negative patients.

Correlation Between miR-497-5p Expression With Clinicopathological Characteristics and Prognosis in Patients With Breast Cancer

Breast cancer (BC) comprises multiple biological and histologic properties. MicroRNAs show key functions in cancer prognosis. This paper explored the relationship between miR-497-5p with clinicopathological characteristics and prognosis in BC. Cancer tissues and normal adjacent tissues (NATs) were collected from 140 included patients with BC. The clinical baseline data, including age, tumor size, pathologic grade, clinical stage, modified Scraff-Bloom-Richardson grade, and lymph node metastasis, were recorded. miR-497-5p expression in cancer tissues and NAT was determined by reverse transcription-quantitative polymerase chain reaction. Patients with BC were followed up for 5 years to record their survival. Patients were divided into the miR-497-5p low expression and high expression groups to assess the correlation between miR-497-5p expression with clinicopathological characteristics and overall survival of patients. The role of miR-497-5p as an independent risk factor for death was further analyzed by a multivariate Cox regression model. miR-497-5p was downregulated in BC tissues than NAT. Tumor size, clinical stage, and lymph node metastasis showed significant differences among patients with high and low miR-497-5p expression levels. Patients with BC with low miR-497-5p expression presented decreased survival. Lowly-expressed miR-497-5p was an independent risk factor for death in patients. Collectively, cancer tissue miR-497-5p low expression increases the risk of death and serves as an independent risk factor for death in patients with BC.

Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

Breast tumor-on-chip: from the tumor microenvironment to medical applications

With the development of microfluidic technology, tumor-on-chip models have gradually become a new tool for the study of breast cancer because they can simulate more key factors of the tumor microenvironment compared with traditional models in vitro. Here, we review up-to-date advancements in breast tumor-on-chip models. We summarize and analyze the breast tumor microenvironment (TME), preclinical breast cancer models for TME simulation, fabrication methods of tumor-on-chip models, tumor-on-chip models for TME reconstruction, and applications of breast tumor-on-chip models and provide a perspective on breast tumor-on-chip models. This review will contribute to the construction and design of microenvironments for breast tumor-on-chip models, even the development of the pharmaceutical field, personalized/precision therapy, and clinical medicine.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

MicroRNAs as Molecular Biomarkers for the Characterization of Basal-like Breast Tumor Subtype

Breast cancer is a heterogeneous disease highlighted by the presence of multiple tumor variants and the basal-like breast cancer (BLBC) is considered to be the most aggressive variant with limited therapeutics and a poor prognosis. Though the absence of detectable protein and hormonal receptors as biomarkers hinders early detection, the integration of genomic and transcriptomic profiling led to the identification of additional variants in BLBC. The high-throughput analysis of tissue-specific micro-ribonucleic acids (microRNAs/miRNAs) that are deemed to have a significant role in the development of breast cancer also displayed distinct expression profiles in each subtype of breast cancer and thus emerged to be a robust approach for the precise characterization of the BLBC subtypes. The classification schematic of breast cancer is still a fluid entity that continues to evolve alongside technological advancement, and the transcriptomic profiling of tissue-specific microRNAs is projected to aid in the substratification and diagnosis of the BLBC tumor subtype. In this review, we summarize the current knowledge on breast tumor classification, aim to collect comprehensive evidence based on the microRNA expression profiles, and explore their potential as prospective biomarkers of BLBC.

The Clinical and Biological Significance of Estrogen Receptor-Low Positive Breast Cancer

Estrogen receptor (ER) status in breast cancer (BC) is determined using immunohistochemistry (IHC) with nuclear expression in ≥1% of cells defined as ER-positive. BC with 1%-9% expression (ER-low-positive), is a clinically and biologically unique subgroup. In this study, we hypothesized that ER-low-positive BC represents a heterogeneous group with a mixture of ER-positive and ER-negative tumor, which may explain their divergent clinical behavior. A large BC cohort (n = 8171) was investigated and categorized into 3 groups: ER-low-positive (1%-9%), ER-positive (≥10%), and ER-negative (<1%) where clinicopathological and outcome characteristics were compared. A subset of ER-low-positive cases was further evaluated using IHC, RNAscope, and RT-qPCR. PAM50 subtyping and ESR1 mRNA expression levels were assessed in ER-low-positive cases within The Cancer Genome Atlas data set. The reliability of image analysis software in assessment of ER expression in the ER-low-positive category was also assessed. ER-low-positive tumors constituted <2% of BC cases examined and showed significant clinicopathological similarity to ER-negative tumors. Most of these tumors were nonluminal types showing low ESR1 mRNA expression. Further validation of ER status revealed that 45% of these tumors were ER-negative with repeated IHC staining and confirmed by RNAscope and RT-qPCR. ER-low-positive tumors diagnosed on needle core biopsy were enriched with false-positive ER staining. BCs with 10% ER behaved similar to ER-positive, rather than ER-negative or low-positive BCs. Moderate concordance was found in assessment of ER-low-positive tumors, and this was not improved by image analysis. Routinely diagnosed ER-low-positive BC includes a proportion of ER-negative cases. We recommend repeat testing of BC showing 1%-9% ER expression and using a cutoff ≥10% expression to define ER positivity to help better inform treatment decisions.

Decoding the IL-33/ST2 Axis: Its Impact on the Immune Landscape of Breast Cancer

Interleukin-33 (IL-33) has emerged as a critical cytokine in the regulation of the immune system, showing a pivotal role in the pathogenesis of various diseases including cancer. This review emphasizes the role of the IL-33/ST2 axis in breast cancer biology, its contribution to cancer progression and metastasis, its influence on the tumor microenvironment and cancer metabolism, and its potential as a therapeutic target. The IL-33/ST2 axis has been shown to have extensive pro-tumorigenic features in breast cancer, starting from tumor tissue proliferation and differentiation to modulating both cancer cells and anti-tumor immune response. It has also been linked to the resistance of cancer cells to conventional therapeutics. However, the role of IL-33 in cancer therapy remains controversial due to the conflicting effects of IL-33 in tumorigenesis and anti-tumor response. The possibility of targeting the IL-33/ST2 axis in tumor immunotherapy, or as an adjuvant in immune checkpoint blockade therapy, is discussed.

Breast Cancer Surrogate Subtype Classification Using Pretreatment Multi-Phase Dynamic Contrast-Enhanced Magnetic Resonance Imaging Radiomics: A Retrospective Single-Center Study

This study aimed to explore the potential of multi-phase dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomics for classifying breast cancer surrogate subtypes. This retrospective study analyzed 360 breast cancers from 319 patients who underwent pretreatment DCE-MRI between January 2015 and January 2019. The cohort consisted of 33 triple-negative, 26 human epidermal growth factor receptor 2 (HER2)-positive, 109 luminal A-like, 144 luminal B-like HER2-negative, and 48 luminal B-like HER2-positive lesions. A total of 1781 radiomic features were extracted from manually segmented breast cancers in each DCE-MRI sequence. The model was internally validated and selected using ten times repeated five-fold cross-validation on the primary cohort, with further evaluation using a validation cohort. The most successful models were logistic regression models applied to the third post-contrast subtraction images. These models exhibited the highest area under the curve (AUC) for discriminating between luminal A like vs. others (AUC: 0.78), luminal B-like HER2 negative vs. others (AUC: 0.57), luminal B-like HER2 positive vs. others (AUC: 0.60), HER2 positive vs. others (AUC: 0.81), and triple negative vs. others (AUC: 0.83). In conclusion, the radiomic features extracted from multi-phase DCE-MRI are promising for discriminating between breast cancer subtypes. The best-performing models relied on tissue changes observed during the mid-stage of the imaging process.

Prognostic influences of B-cell lymphoma 2-positive expression on late recurrence in breast cancer

Purpose

B-cell lymphoma 2 (BCL2) has an antiapoptotic role, however, has resulted in it being a powerful favorable prognostic factor in breast cancer. Several studies revealed BCL2 is strongly associated with a lower rate of early recurrence after initial treatment in breast cancer patients, but study of a prolonged effect after 5 years is lacking. We investigated BCL2 as a prognostic factor in breast cancer in comparison to early and late recurrence.

Methods

We retrieved data from 2,198 patients with primary breast cancer who underwent surgical treatment and adjuvant treatment at the breast cancer center between 2005 and 2015. Each molecular subtype was classified, and Ki-67 and BCL2 were also assessed by immunohistochemistry. BCL2 and the association between molecular subtypes were assessed in early and late recurrences, respectively. Five-year postrecurrence survival and BCL2 were also assessed.

Results

The BCL2-positive group was associated with favorable clinicopathologic characteristics. The time to recurrence was significantly longer in the BCL2-positive group (P = 0.035). Late recurrence after 5 years was higher in the BCL2-positive group (P = 0.029). In multivariate survival analysis, tumor size and BCL2-positive expression were the only independent prognostic factors for late recurrence (P = 0.004). In the patients with recurrence, 5-year postrecurrence survival was significantly higher in the BCL2-positive group (P < 0.001).

Conclusion

Our result showed that prognosis was better in BCL2-positive patients compared to BCL2-negative patients at late recurrence. We suggested that BCL2 expression could be used as a marker to help determine additional adjuvant therapy or extended hormone therapy in hormone-dependent breast cancer.

Metronomic Chemo-Endocrine Therapy (FulVEC) as a Salvage Treatment for Patients with Advanced, Treatment-Refractory ER+/HER2-Breast Cancer-A Retrospective Analysis of Consecutive Patients Data

BACKGROUND

Breast cancer, with 2.3 million new cases and 0.7 million deaths every year, represents a great medical challenge worldwide. These numbers confirm that approx. 30% of BC patients will develop an incurable disease requiring life-long, palliative systemic treatment. Endocrine treatment and chemotherapy administered in a sequential fashion are the basic treatment options in advanced ER+/HER2- BC, which is the most common BC type. The palliative, long-term treatment of advanced BC should not only be highly active but also minimally toxic to allow long-term survival with the optimal quality of life. A combination of metronomic chemotherapy (MC) with endocrine treatment (ET) in patients who failed earlier lines of ET represents an interesting and promising option.

METHODS

The methodology includes retrospective data analyses of pretreated, metastatic ER+/HER2- BC (mBC) patients who were treated with the FulVEC regimen combining fulvestrant and MC (cyclophosphamide, vinorelbine, and capecitabine).

RESULTS

Thirty-nine previously treated (median 2 lines 1-9) mBC patients received FulVEC. The median PFS and OS were 8.4 and 21.5 months, respectively. Biochemical responses (CA-15.3 serum marker decline ≥50%) were observed in 48.7%, and any increase in CA-15.3 was observed in 23.1% of patients. The activity of FulVEC was independent of previous treatments with fulvestrant of cytotoxic components of the FulVEC regimen. The treatment was safe and well tolerated.

CONCLUSIONS

Metronomic chemo-endocrine therapy with FulVEC regimen represents an interesting option and compares favorably with other approaches in patients' refractory to endocrine treatments. A phase II randomized trial is warranted.

Obesity as a Risk Factor for Breast Cancer-The Role of miRNA

Breast cancer (BC) is the most common cancer diagnosed among women in the world, with an ever-increasing incidence rate. Due to the dynamic increase in the occurrence of risk factors, including obesity and related metabolic disorders, the search for new regulatory mechanisms is necessary. This will help a complete understanding of the pathogenesis of breast cancer. The review presents the mechanisms of obesity as a factor that increases the risk of developing breast cancer and that even initiates the cancer process in the female population. The mechanisms presented in the paper relate to the inflammatory process resulting from current or progressive obesity leading to cell metabolism disorders and disturbed hormonal metabolism. All these processes are widely regulated by the action of microRNAs (miRNAs), which may constitute potential biomarkers influencing the pathogenesis of breast cancer and may be a promising target of anti-cancer therapies.

Imaging for illuminating actionable pathways in breast cancer

PURPOSE OF REVIEW

Nuclear medicine has the potential to explore and illuminate several pathways in breast cancer (BC) offering different radiopharmaceuticals for positron emission tomography (PET) designed to target specific tumor characteristics. The aim of this critical review is to give an overview about emerging opportunities in PET imaging, underlining the future potential contribution in the management of BC patients.

RECENT FINDINGS

Beside 2-deoxy-2-[ 18 F]-fluoro- d -glucose (FDG), new generation tracers for PET imaging have been recently proposed to investigate specific characteristics in breast cancer, both targeting tumor cells and the tumor micro-environment (TME).

SUMMARY

FDG-PET is a procedure that received extensive clinical validation. However, its role in BC is still suboptimal due to the low-FDG avidity of specific tumor subtypes. Human epidermal growth receptor-2 and integrin targeted PET radiotracers might provide useful information selecting patients more likely to respond to target therapy. FluoroEstradiol (FES) is a FDA-approved PET radiotracer targeting the estrogen receptor (ER), useful to investigate metastatic ER+ patients, to assess in vivo ER heterogeneity and to evaluate hormonal therapy efficacy. Inhibitors of the fibroblast activation protein (FAPi) targeting the cancer-associated fibroblast can explore the TME with PET imaging. FAPi is also proposed a theranostic agent for radio-ligand therapy.

Impact of automated methods for quantitative evaluation of immunostaining: Towards digital pathology

Introduction

We sought to develop a novel method for a fully automated, robust quantification of protein biomarker expression within the epithelial component of high-grade serous ovarian tumors (HGSOC). Rather than defining thresholds for a given biomarker, the objective of this study in a small cohort of patients was to develop a method applicable to the many clinical situations in which immunomarkers need to be quantified. We aimed to quantify biomarker expression by correlating it with the heterogeneity of staining, using a non-subjective choice of scoring thresholds based on classical mathematical approaches. This could lead to a universal method for quantifying other immunohistochemical markers to guide pathologists in therapeutic decision-making.

Methods

We studied a cohort of 25 cases of HGSOC for which three biomarkers predictive of the response observed ex vivo to the BH3 mimetic molecule ABT-737 had been previously validated by a pathologist. We calibrated our algorithms using Stereology analyses performed by two experts to detect immunohistochemical staining and epithelial/stromal compartments. Immunostaining quantification within Stereology grids of hexagons was then performed for each histological slice. To define thresholds from the staining distribution histograms and to classify staining within each hexagon as low, medium, or high, we used the Gaussian Mixture Model (GMM).

Results

Stereology analysis of this calibration process produced a good correlation between the experts for both epithelium and immunostaining detection. There was also a good correlation between the experts and image processing. Image processing clearly revealed the respective proportions of low, medium, and high areas in a single tumor and showed that this parameter of heterogeneity could be included in a composite score, thus decreasing the level of discrepancy. Therefore, agreement with the pathologist was increased by taking heterogeneity into account.

Conclusion and discussion

This simple, robust, calibrated method using basic tools and known parameters can be used to quantify and characterize the expression of protein biomarkers within the different tumor compartments. It is based on known mathematical thresholds and takes the intratumoral heterogeneity of staining into account. Although some discrepancies need to be diminished, correlation with the pathologist's classification was satisfactory. The method is replicable and can be used to analyze other biological and medical issues. This non-subjective technique for assessing protein biomarker expression uses a fully automated choice of thresholds (GMM) and defined composite scores that take the intra-tumor heterogeneity of immunostaining into account. It could help to avoid the misclassification of patients and its subsequent negative impact on therapeutic care.

Pharmacological effects and mechanisms of bee venom and its main components: Recent progress and perspective

Bee venom (BV), a type of defensive venom, has been confirmed to have favorable activities, such as anti-tumor, neuroprotective, anti-inflammatory, analgesic, anti-infectivity effects, etc. This study reviewed the recent progress on the pharmacological effects and mechanisms of BV and its main components against cancer, neurological disorders, inflammatory diseases, pain, microbial diseases, liver, kidney, lung and muscle injury, and other diseases in literature during the years 2018-2021. The related target proteins of BV and its main components against the diseases include Akt, mTOR, JNK, Wnt-5α, HIF-1α, NF-κB, JAK2, Nrf2, BDNF, Smad2/3, AMPK, and so on, which are referring to PI3K/Akt/mTOR, MAPK, Wnt/β-catenin, HIF-1α, NF-κB, JAK/STAT, Nrf2/HO-1, TrkB/CREB/BDNF, TGF-β/Smad2/3, and AMPK signaling pathways, etc. Further, with the reported targets, the potential effects and mechanisms on diseases were bioinformatically predicted via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, disease ontology semantic and enrichment (DOSE) and protein-protein interaction (PPI) analyses. This review provides new insights into the therapeutic effects and mechanisms of BV and its main components on diseases.

Potential utility of miRNAs for liquid biopsy in breast cancer

Breast cancer (BC) remains the most prevalent malignancy due to its incidence rate, recurrence, and metastasis in women. Conventional strategies of cancer detection– mammography and tissue biopsy lack the capacity to detect the complete cancer genomic landscape. Besides, they often give false- positive or negative results. The presence of this and other disadvantages such as invasiveness, high-cost, and side effects necessitates developing new strategies to overcome the BC burden. Liquid biopsy (LB) has been brought to the fore owing to its early detection, screening, prognosis, simplicity of the technique, and efficient monitoring. Remarkably, microRNAs (miRNAs)– gene expression regulators seem to play a major role as biomarkers detected in the samples of LB. Particularly, miR-21 and miR-155 among other possible candidates seem to serve as favorable biomarkers in the diagnosis and prognosis of BC. Hence, this review will assess the potential utility of miRNAs as biomarkers and will highlight certain promising candidates for the LB approach in the diagnosis and management of BC that may optimize the patient outcome.

High AUF1 level in stromal fibroblasts promotes carcinogenesis and chemoresistance and predicts unfavorable prognosis among locally advanced breast cancer patients

Background

Locally advanced breast cancer (LABC), the most aggressive form of the disease, is a serious threat for women's health worldwide. The AU-rich RNA-binding factor 1 (AUF1) promotes the formation of chemo-resistant breast cancer stem cells. Thereby, we investigated the power of AUF1 expression, in both cancer cells and their stromal fibroblasts, as predictive biomarker for LABC patients’ clinical outcome following neoadjuvant treatment.

Methods

We have used immunohistochemistry to assess the level of AUF1 on formalin-fixed paraffin-embedded tissues. Immunoblotting was utilized to show the effect of AUF1 ectopic expression in breast stromal fibroblasts on the expression of various genes both in vitro and in orthotopic tumor xenografts. Cytotoxicity was evaluated using the WST1 assay, while a label-free real-time setting using the xCELLigence RTCA technology was utilized to assess the proliferative, migratory and invasive abilities of cells.

Results

We have shown that high AUF1 immunostaining (≥ 10%) in both cancer cells and their adjacent cancer-associated fibroblasts (CAFs) was significantly associated with higher tumor grade. Kaplan–Meier univariate analysis revealed a strong correlation between high AUF1 level in CAFs and poor patient’s survival. This correlation was highly significant in patients with triple negative breast cancer, who showed poor disease-free survival (DFS) and overall survival (OS). High expression of AUF1 in CAFs was also associated with poor OS of ER+/Her2− patients. Similarly, AUF1-positive malignant cells tended to be associated with shorter DFS and OS of ER+/Her2+ patients. Interestingly, neoadjuvant therapy downregulated AUF1 to a level lower than 10% in malignant cells in a significant number of patients, which improved both DFS and OS. In addition, ectopic expression of AUF1 in breast fibroblasts activated these cells and enhanced their capacity to promote, in an IL-6-dependent manner, the epithelial-to-mesenchymal transition and stemness processes. Furthermore, these AUF1-expressing cells enhanced the chemoresistance of breast cancer cells and their growth in orthotopic tumor xenografts.

Conclusions

The present findings show that the CAF-activating factor AUF1 has prognostic/predictive value for breast cancer patients and could represent a great therapeutic target in order to improve the precision of cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-022-01543-x.

Non-conventional and Investigational PET Radiotracers for Breast Cancer: A Systematic Review

Breast cancer is one of the most common malignancies in women, with high morbidity and mortality rates. In breast cancer, the use of novel radiopharmaceuticals in nuclear medicine can improve the accuracy of diagnosis and staging, refine surveillance strategies and accuracy in choosing personalized treatment approaches, including radioligand therapy. Nuclear medicine thus shows great promise for improving the quality of life of breast cancer patients by allowing non-invasive assessment of the diverse and complex biological processes underlying the development of breast cancer and its evolution under therapy. This review aims to describe molecular probes currently in clinical use as well as those under investigation holding great promise for personalized medicine and precision oncology in breast cancer.