Histology of Luminal Breast Cancer

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

Contrast-enhanced ultrasound for the preoperative prediction of pathological characteristics in breast cancer

Objective

We aimed to investigate the value of contrast-enhanced ultrasound (CEUS) in the preoperative prediction of the histological grades and molecular subtypes of breast cancer.

Methods

A total of 183 patients with pathologically confirmed breast cancer were included. Contrast enhancement patterns and quantitative parameters were compared in different groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of CEUS in the preoperative prediction of pathological characteristics, including histologic grade and molecular subtypes.

Results

Heterogeneous enhancement, perfusion defects, and peripheral radial vessels were mostly observed in higher histologic grade (grade III) breast cancer. Heterogeneous enhancement and perfusion defect were the most effective indicators for grade III breast cancer, with the areas under the ROC curve of 0.768 and 0.756, respectively. There were significant differences in the enhancement intensity, post-enhanced margin, perfusion defects, and peripheral radial vessel among the different molecular subtypes of breast cancer (all P < 0.01). Perfusion defects and clear edge after enhancement were the best qualitative criteria for the diagnosis of HER-2 overexpressed and triple-negative breast cancers, and the corresponding areas under the ROC curves were 0.804 and 0.905, respectively. There were significant differences in PE, WiR, WiPI, and WiWoAUC between grade III vs grade I and II breast cancer (P < 0.05). PE, WiR, WiPI, and WiWoAUC had good efficiency in the diagnosis of high-histologic-grade breast cancer. PE had the highest diagnostic efficiency in Luminal A, while WiPI had the highest diagnostic efficiency in Luminal B subtype breast cancer, and the areas under the ROC curve were 0.825 and 0.838, respectively. WiWoAUC and WiR were the most accurate parameters for assessing triple-negative subtype breast cancers, and the areas under the curve were 0.932 and 0.922, respectively.

Conclusion

Qualitative and quantitative perfusion analysis of contrast-enhanced ultrasound may be useful in the non-invasive prediction of the histological grade and molecular subtypes of breast cancers.

Prognostic significance of grade of malignancy based on histopathological differentiation and Ki-67 in pancreatic ductal adenocarcinoma

OBJECTIVE

Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation. Ki-67, an indicator of cellular proliferation, has been used for tumor grading and classification in breast cancer and neuroendocrine tumors. However, its prognostic significance in pancreatic ductal adenocarcinoma (PDAC) remains uncertain.

METHODS

Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled, and relevant prognostic factors were examined. Grade of malignancy (GOM), a novel index based on histopathological differentiation and Ki-67, is proposed, and its clinical significance was evaluated.

RESULTS

The optimal threshold for Ki-67 was determined to be 30%. Patients with a Ki-67 expression level > 30% rather than ≤ 30% had significantly shorter 5-year overall survival (OS) and recurrence-free survival (RFS). In multivariate analysis, both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS. The GOM was used to independently stratify OS and RFS into 3 tiers, regardless of TNM stage and other established prognostic factors. The tumor-node-metastasis-GOM stage was used to stratify survival into 5 distinct tiers, and surpassed the predictive performance of TNM stage for OS and RFS.

CONCLUSIONS

Ki-67 is a valuable prognostic indicator for PDAC. Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.

Construction and Validation of a Novel Nomogram for Predicting the Risk of Metastasis in a Luminal B Type Invasive Ductal Carcinoma Population

Background

Postoperative distant metastasis is the main cause of death in breast cancer patients. We aimed to construct a nomogram to predict the risk of metastasis of luminal B type invasive ductal carcinoma.

Methods

We applied the data of 364 luminal B type breast cancer patients between 2008 and 2013. Patients were categorized into modeling group and validation group randomly (1:1). The breast cancer metastasis nomogram was developed from the logistic regression model using clinicopathological variables. The area under the receiver-operating characteristic curve (AUC) was calculated in modeling group and validation group to evaluate the predictive accuracy of the nomogram.

Results

The multivariate logistic regression analysis showed that tumor size, No. of the positive level 1 axillary lymph nodes, human epidermal growth factor receptor 2 (HER2) status and Ki67 index were the independent predictors of the breast cancer metastasis. The AUC values of the modeling group and the validation group were 0.855 and 0.818, respectively. The nomogram had a well-fitted calibration curve. The positive and negative predictive values were 49.3% and 92.7% in the modeling group, and 47.9% and 91.0% in the validation group. Patients who had a score of 60 or more were thought to have a high risk of breast cancer metastasis.

Conclusions

The nomogram has a great predictive accuracy of predicting the risk of breast cancer metastasis. If patients had a score of 60 or more, necessary measures, like more standard treatment methods and higher treatment adherence of patients, are needed to take to lower the risk of metastasis and improve the prognosis.

Layer-by-layer coated calcium carbonate nanoparticles for targeting breast cancer cells

Breast cancer is resistant to conventional treatments due to the specific tumour microenvironment, the associated acidic pH and the overexpression of receptors that enhance cells tumorigenicity. Herein, we optimized the synthesis of acidic resorbable calcium carbonate (CaCO3) nanoparticles and the encapsulation of a low molecular weight model molecule (Rhodamine). The addition of ethylene glycol during the synthetic process resulted in a particle size decrease: we obtained homogeneous CaCO3 particles with an average size of 564 nm. Their negative charge enabled the assembly of layer-by-layer (LbL) coatings with surface-exposed hyaluronic acid (HA), a ligand of tumour-associated receptor CD44. The coating decreased Rhodamine release by two-fold compared to uncoated nanoparticles. We demonstrated the effect of nanoparticles on two breast cancer cell lines with different aggressiveness - SK-BR-3 and the more aggressive MDA-MB-231 - and compared them with the normal breast cell line MCF10A. CaCO3 nanoparticles (coated and uncoated) significantly decreased the metabolic activity of the breast cancer cells. The interactions between LbL-coated nanoparticles and cells depended on HA expression on the cell surface: more particles were observed on the surface of MDA-MB-231 cells, which had the thickest endogenous HA coating. We concluded that CaCO3 nanoparticles are potential candidates to carry low molecular weight chemotherapeutics and deliver them to aggressive breast cancer sites with an HA-abundant pericellular matrix.

The impact of microRNAs on the resistance of breast cancer subtypes to chemotherapy

Breast cancer (BC) formation is primarily influenced by genetics, epigenetics and environmental factors. Aberrant Genetics and epigenetics leads to a condition known as heterogeneity. The heterogeneity of BC can be divided into several subtypes. Among the epigenetic factors, microRNAs (miRNAs) have been shown to play a crucial role in the development and progression of malignancies. These small non-coding RNAs regulate gene expression through a variety of mechanisms, resulting in either mRNA degradation or translation repression. As miRNAs directly control many proteins, genetic anomalies affect tumor metastasis, apoptosis, proliferation, and cell transportation. Consequently, miRNA dysregulations contribute not only in cancer development but also in invasiveness, proliferation rate and more importantly, drug response. Findings mostly indicate subtype-specified identical miRNA profile in BC. Among the BC subtypes, TNBC, HER2 + and luminal are the most resistant to therapy, respectively. Therapy resistance is greatly associated with miRNA expression profile. Hence, concentration of miRNA is the first marker of its role in chemotherapy response. Overexpressed miRNAs may disrupt drug efflux transporters and decrease the drug accumulation in cell. While down-regulated miRNAs which mediate drug resistance processes are mostly correlated with poor treatment response. Moreover, other mechanisms in which miRNAs play crucial roles in chemoresistance such as cell receptor mediations, dysregulation by environmental factors, DNA defects, etc. Recently, several miRNA-based treatments have shown promising results in cancer treatment. Inhibition of up-regulated miRNAs is one of these therapeutic approaches whilst transfecting cell with down-regulated miRNAs also show promising results. Moreover, drug-resistance could also be determined while in the pre-treatment phase via expression levels of miRNAs. Therefore, miRNAs provide intriguing insights and challenges in overcoming chemoresistance. In this article, we have discussed how miRNAs regulate breast cancer subtypes-specific chemoresistance.

Role of EGFR and FASN in breast cancer progression

Breast cancer (BC) emerged as one of the life-threatening diseases among females. Despite notable improvements made in cancer detection and treatment worldwide, according to GLOBACAN 2020, BC is the fifth leading cancer, with an estimated 1 in 6 cancer deaths, in a majority of countries. However, the exact cause that leads to BC progression still needs to be determined. Here, we reviewed the role of two novel biomarkers responsible for 50-70% of BC progression. The first one is epidermal growth factor receptor (EGFR) which belongs to the ErbB tyrosine kinases family, signalling pathways associated with it play a significant role in regulating cell proliferation and division. Another one is fatty acid synthase (FASN), a key enzyme responsible for the de novo lipid synthesis required for cancer cell development. This review presents a rationale for the EGFR-mediated pathways, their interaction with FASN, communion of these two biomarkers with BC, and improvements to overcome drug resistance caused by them.

Potential Antitumor Effect of α-Mangostin against Rat Mammary Gland Tumors Induced by LA7 Cells

In this study, the chemotherapeutic effect of α-mangostin (AM) was assessed in rats injected with LA7 cells. Rats received AM orally at 30 and 60 mg/kg twice a week for 4 weeks. Cancer biomarkers such as CEA and CA 15-3 were significantly lower in AM-treated rats. Histopathological evaluations showed that AM protects the rat mammary gland from the carcinogenic effects of LA7 cells. Interestingly, AM decreased lipid peroxidation and increased antioxidant enzymes when compared to the control. Immunohistochemistry results of the untreated rats showed abundant PCNA and fewer p53-positive cells than AM-treated rats. Using the TUNEL test, AM-treated animals had higher apoptotic cell numbers than those untreated. This report revealed that that AM lessened oxidative stress, suppressed proliferation, and minimized LA7-induced mammary carcinogenesis. Therefore, the current study suggests that AM has significant potential for breast cancer treatment.

Defining the Emergence of New Immunotherapy Approaches in Breast Cancer: Role of Myeloid-Derived Suppressor Cells

Breast cancer (BC) continues to be the most diagnosed tumor in women and a very heterogeneous disease both inter- and intratumoral, mainly given by the variety of molecular profiles with different biological and clinical characteristics. Despite the advancements in early detection and therapeutic strategies, the survival rate is low in patients who develop metastatic disease. Therefore, it is mandatory to explore new approaches to achieve better responses. In this regard, immunotherapy arose as a promising alternative to conventional treatments due to its ability to modulate the immune system, which may play a dual role in this disease since the relationship between the immune system and BC cells depends on several factors: the tumor histology and size, as well as the involvement of lymph nodes, immune cells, and molecules that are part of the tumor microenvironment. Particularly, myeloid-derived suppressor cell (MDSC) expansion is one of the major immunosuppressive mechanisms used by breast tumors since it has been associated with worse clinical stage, metastatic burden, and poor efficacy of immunotherapies. This review focuses on the new immunotherapies in BC in the last five years. Additionally, the role of MDSC as a therapeutic target in breast cancer will be described.

Glycosylated proteins with abnormal glycosylation changes are potential biomarkers for early diagnosis of breast cancer

Conventional cancer management relies on tumor type and stage for diagnosis and treatment, which leads to recurrence and metastasis and death in young women. Early detection of proteins in the serum aids diagnosis, progression, and clinical outcomes, possibly improving survival rate of breast cancer patients. In this review, we provided an insight into the influence of aberrant glycosylation on breast cancer development and progression. Examined literatures revealed that mechanisms underlying glycosylation moieties alteration could enhance early detection, monitoring, and therapeutic efficacy in breast cancer patients. This would serve as a guide for the development of new serum biomarkers with higher sensitivity and specificity, providing possible serological biomarkers for breast cancer diagnosis, progression, and treatment.

Characterization of Hormone Receptor and HER2 Status in Breast Cancer Using Mass Spectrometry Imaging

Immunohistochemical evaluation of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 status stratify the different subtypes of breast cancer and define the treatment course. Triple-negative breast cancer (TNBC), which does not register receptor overexpression, is often associated with worse patient prognosis. Mass spectrometry imaging transcribes the molecular content of tissue specimens without requiring additional tags or preliminary analysis of the samples, being therefore an excellent methodology for an unbiased determination of tissue constituents, in particular tumor markers. In this study, the proteomic content of 1191 human breast cancer samples was characterized by mass spectrometry imaging and the epithelial regions were employed to train and test machine-learning models to characterize the individual receptor status and to classify TNBC. The classification models presented yielded high accuracies for estrogen and progesterone receptors and over 95% accuracy for classification of TNBC. Analysis of the molecular features revealed that vimentin overexpression is associated with TNBC, supported by immunohistochemistry validation, revealing a new potential target for diagnosis and treatment.

Modulatory role of miRNAs in thyroid and breast cancer progression and insights into their therapeutic manipulation

Over the past few decades, thyroid cancer has become one of the most common types of endocrine cancer, contributing to an increase in prevalence. In the year 2020, there were 586,202 newly diagnosed cases of thyroid cancer around the world. This constituted approximately 3.0% of all patients diagnosed with cancer. The World Health Organization reported that there will be 2.3 million women receiving treatment for breast cancer in 2020, with 685,000. Despite the fact that carcinoma is one of the world's leading causes of death, there is still a paucity of information about its biology. MicroRNAs (miRNAs; miRs) are non-coding RNAs that can reduce gene expression by cleaving the 3' untranslated regions of mRNA. These factors make them a potential protein translation inhibitor. Diverse biological mechanisms implicated in the genesis of cancer are modulated by miRNA. The investigation of global miRNA expression in cancer showed regulatory activity through up regulation and down-regulation in several cancers, including thyroid cancer and breast cancer. In thyroid cancer, miRNA influences several cancers related signaling pathways through modulating MAPK, PI3K, and the RAS pathway. In breast cancer, the regulatory activity of miRNA was played through the cyclin protein family, protein kinases and their inhibitors, and other growth promoters or suppressors, which modulated cell proliferation and cell cycle progression. This article's goal is to discuss key miRNA expressions that are involved in the development of thyroid and breast cancer as well as their therapeutic manipulation for these two specific cancer types.

A deep learning model for breast ductal carcinoma in situ classification in whole slide images

The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pathologists using microscopes is limited in terms of human resources, it is necessary to develop new techniques that can rapidly and accurately diagnose large numbers of histopathological specimens. Computational pathology tools which can assist pathologists in detecting and classifying DCIS and IDC from whole slide images (WSIs) would be of great benefit for routine pathological diagnosis. In this paper, we trained deep learning models capable of classifying biopsy and surgical histopathological WSIs into DCIS, IDC, and benign. We evaluated the models on two independent test sets (n= 1382, n= 548), achieving ROC areas under the curves (AUCs) up to 0.960 and 0.977 for DCIS and IDC, respectively.

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.

Breast Cancer-Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies-An Updated Review

Simple Summary

Breast cancer is the most common cancer among women. It is estimated that 2.3 million new cases of BC are diagnosed globally each year. Based on mRNA gene expression levels, BC can be divided into molecular subtypes that provide insights into new treatment strategies and patient stratifications that impact the management of BC patients. This review addresses the overview on the BC epidemiology, risk factors, classification with an emphasis on molecular types, prognostic biomarkers, as well as possible treatment modalities.

Abstract

Breast cancer (BC) is the most frequently diagnosed cancer in women worldwide with more than 2 million new cases in 2020. Its incidence and death rates have increased over the last three decades due to the change in risk factor profiles, better cancer registration, and cancer detection. The number of risk factors of BC is significant and includes both the modifiable factors and non-modifiable factors. Currently, about 80% of patients with BC are individuals aged >50. Survival depends on both stage and molecular subtype. Invasive BCs comprise wide spectrum tumors that show a variation concerning their clinical presentation, behavior, and morphology. Based on mRNA gene expression levels, BC can be divided into molecular subtypes (Luminal A, Luminal B, HER2-enriched, and basal-like). The molecular subtypes provide insights into new treatment strategies and patient stratifications that impact the management of BC patients. The eighth edition of TNM classification outlines a new staging system for BC that, in addition to anatomical features, acknowledges biological factors. Treatment of breast cancer is complex and involves a combination of different modalities including surgery, radiotherapy, chemotherapy, hormonal therapy, or biological therapies delivered in diverse sequences.