Breast Cancer; Discovery of Novel Diagnostic Biomarkers, Drug Resistance, and Therapeutic Implications

Exploring New Frontiers: Alternative Breast Cancer Treatments Through Glycocalyx Research

Breast cancer (BC) treatment is developing toward more precise and personalized care through the approval of different comprehensive approaches. Clinical practice emphasizes significant patient-to-patient variability in treatment response among patients, even those with similar clinical and biological profiles. Recent studies have demonstrated that the glycocalyx is an essential organelle that plays an important role in many cellular processes and can be a promising target for treatment. The glycocalyx of cancer cells is a key component influencing the interaction between the tumor and the immune system. Glycan modifications attached to glycoproteins and glycolipids are a common characteristic of the transition to malignancy. We review how the specific structure and function of the glycocalyx are regulated at the molecular level, contribute to immune evasion, and can be overcome by using both traditional drugs and combination therapies, as well as drugs not previously used in standard cancer treatments, to address treatment resistance associated with glycocalyx alterations. Trial Registration: ClinicalTrials.gov identifier: NCT00770354, NCT00925548, NCT01731587, NCT00088413, NCT00179309, NCT00986609, NCT05812326, NCT04020575, NCT05239143, NCT01279603, and NCT03562637.

CircRNA_0044556 affects the sensitivity of triple-negative breast cancer cells to paclitaxel by regulating miR-665

CircRNAs have been implicated in the development of resistance in triple-negative breast cancer (TNBC). However, the association between circRNA_0044556 and paclitaxel (PTX) resistance in TNBC is still limited. Therefore, the purpose of this study was to investigate the effect of circRNA_0044556 on biological function and PTX resistance in TNBC cells. PTX-resistant TNBC cells (MDA-MB-231/PTX) were obtained by continuously exposing MDA-MB-231 cells to increasing paclitaxel levels. The expression levels of circRNA_0044556 and miR-665 were measured by qRT-PCR. The regulatory relationship between miR-665 and circRNA_0044556 was verified by biological information website analysis and double-luciferase reporter gene detection experiments. MTT assay, clone assay, flow cytometry and Western blot analysis were used to evaluate the influence of cell biological function. Elevated circRNA_0044556 was observed in TNBC, and paclitaxel increased the expression of circRNA_0044556 in TNBC cells. In TNBC, circRNA_0044556 acted as a ceRNA for miR-665. In addition, low expression of circRNA_0044556 combined with miR-665 inhibited the proliferation of TNBC cells and paclitaxel-resistant TNBC cells while inducing cell death. Our study demonstrated that the downregulation of circRNA_0044556 inhibits the malignant progression of TNBC cells and paclitaxel resistance via miR-665. Thus, circRNA_0044556 may be a potential therapeutic target for PTX-resistance TNBC.

Regulation of PEST-containing nuclear proteins in cancer cells: implications for cancer biology and therapy

The PEST-containing nuclear protein (PCNP) is a nuclear protein involved in the regulation of cell cycle progression, protein degradation, and tumorigenesis. PCNP contains a PEST sequence, a polypeptide structural motif rich in proline (P), glutamic acid (E), serine (S), and threonine (T), which serves as a proteolytic recognition signal. The degradation of specific proteins via the PEST sequence plays a crucial role in modulating signaling pathways that control cell growth, differentiation, apoptosis, and stress responses. PCNP is primarily degraded through the ubiquitin-proteasome system (UPS) and the calpain pathway, with phosphorylation of threonine and serine residues further accelerating its degradation. The ubiquitination of PCNP by the ring finger protein NIRF in an E3 ligase-dependent manner is well documented, along with its involvement in the MAPK and PI3K/AKT/mTOR signaling pathways. Additionally, PCNP is implicated in p53-mediated cell cycle arrest and apoptosis, which are essential for inhibiting tumor growth. To explore the role of PCNP in cancer, this review examines its effects on cell growth, differentiation, proliferation, and apoptosis in lung adenocarcinoma, thyroid cancer, ovarian cancer, and other malignancies derived from glandular epithelial cells. By focusing on PCNP and its regulatory mechanisms, this study provides a scientific basis for further research on the biological functions of the PEST sequence in tumor development and cancer progression.

Toward In Vivo Cancer Detection: X-Ray Scattering on Thick Phantom Samples

As the number of new breast cancer cases grows around the world, there is an unmet need for fast, accurate, and low-cost methods of early cancer detection. It was previously shown that X-ray scattering on lipid molecules can provide the necessary structural biomarker. However, these measurements were performed on small ex vivo samples, and to ensure the progress to in vivo diagnostics, the approach should be extended to larger tissues. We use the phantom fat samples to establish such a procedure. In the obtained X-ray scattering patterns, we observe the characteristic features for the inter-fatty-acid molecular distance. The large size of the samples led to the peak broadening; however, the features remain visible up to 10 cm in thickness. The experimental data are in excellent agreement with the Monte Carlo simulations based on the form factors obtained from the small samples. Our results usher the way for the in vivo monitoring of the structural biomarkers of breast cancer.

Recent advancements in nanomaterial-based biosensors for diagnosis of breast cancer: a comprehensive review

Researchers have found that mutations in the BRCA gene associated with breast cancer have a 40-50% chance of being associated with high risk for hereditary breast cancer (BC). Therefore, detecting BRCA1 is crucial for genetic analysis, early detection, and clinical treatment of BC. Traditional detection methods for BRCA1 include high-performance liquid chromatography (HPLC), single-strand conformation polymorphism assays (SSCP), PCR, real-time PCR, and DNA sequencing. However, these methods are limited by cost, analysis time, and complexity. Therefore, it is necessary to develop an ultrasensitive, fast, low-cost, simple method for BRCA1 detection. In recent years, various BC biosensing strategies have been investigated, including optical, electrical, electrochemical, and mechanical biosensing. In particular, the high sensitivity and short detection times of electrochemical biosensors make them suitable for recognizing BC biomarkers. Additionally, the sensitivity of electrochemical biosensors can be increased by incorporating nanomaterials. In this regard, the main focus of the present study is the introduction of common methods for diagnosing the BRCA-1/2 genes. In addition to introducing biosensors as an efficient tool, it also discusses the latest and most significant biosensors developed for detecting the BRCA gene.

Electrochemical capacitance-based aptasensor for HER2 detection

The overexpression of Human Epidermal Growth Factor Receptor 2 (HER2) protein is specifically related to tumor cell proliferation in breast cancers. Its presence in biological serum samples indicates presence or progression of cancer, becoming a promise biomarker. However, their detection needs a simple and high accuracy platform. In this study, we report the develop and optimization of a simple highly sensitive electrochemical platform for HER2. Gold electrode surface was modified with a self-assembled monolayer composed by DNA aptamer, 6-(ferrocenyl) hexanethiol and 6-mercapto-1-hexanethiol. Electrochemical impedance spectroscopy was used to quantify the changes in capacitance on the interface due to the presence ferrocene, whether acting as a redox charge or its behavior under different HER2 concentration in PBS and undiluted human serum. As a result, the approach allows detection of HER2 with a limit of detection of 3.61 pg/mL, 12.28 nF sensitivity per decade and a linear range from 1 pM to 1 [Formula: see text]M in serum. This electrochemical aptasensor can be applied to different arrays for aptamer screening and has a significant importance to interaction study of biological systems.

Molecular Mechanisms of circKIF4A in Breast Cancer Progression

AIM

Breast cancer (BC) is the most frequently diagnosed malignancy worldwide, necessitating continued research into its molecular mechanisms. Circular RNAs (circRNAs) are increasingly recognized for their role in various cancers, including BC. This study explores the role of circRNA kinesin family member 4A (circKIF4A) in BC progression and its underlying molecular mechanisms.

METHODS

BC cell lines were cultured, and circKIF4A expression was knocked down. Cell viability, proliferation, migration, and invasion were assessed using the Cell Counting Kit-8, colony formation assay, and Transwell assays. The expression of circKIF4A, miR-874-3p, and glycerophosphodiester phosphodiesterase domain-containing 5 (GDPD5) was quantified using qRT-PCR and Western blot analysis. Subcellular fractionation was performed to localize circKIF4A within the cell. The interactions between circKIF4A and miR-874-3p, as well as between miR-874-3p and GDPD5, were evaluated using RNA pull-down and dual-luciferase assays. Rescue experiments were conducted with miR-874-3p inhibition or GDPD5 overexpression to confirm the mechanistic pathway.

RESULTS

circKIF4A was found to be upregulated in BC cells. Its knockdown significantly inhibited cell proliferation, migration, and invasion. circKIF4A acts as a sponge for miR-874-3p, reducing its expression. miR-874-3p targets and suppresses GDPD5, a key regulator in BC cell growth. Silencing miR-874-3p or overexpressing GDPD5 reversed the tumor-suppressive effects of circKIF4A knockdown.

CONCLUSION

circKIF4A promotes BC cell proliferation and invasiveness by regulating the miR-874-3p/GDPD5 axis. These findings highlight a potential therapeutic target in BC and contribute to the understanding of circRNA involvement in cancer progression.

Specific microbiome patterns and their association with breast cancer: the intestinal microbiota as a potential biomarker and therapeutic strategy

Breast cancer (BC) is one of the most diagnosed cancers in women. Based on histological characteristics, they are classified as non-invasive, or in situ (tumors located within the milk ducts or milk lobules) and invasive. BC may develop from in situ carcinomas over time. Determining prognosis and predicting response to treatment are essential tools to manage this disease and reduce its incidence and mortality, as well as to promote personalized therapy for patients. However, over half of the cases are not associated with known risk factors. In addition, some patients develop resistance to treatment and relapse. Therefore, it is necessary to identify new biomarkers and treatment strategies that improve existing therapies. In this regard, the role of the microbiome is being researched as it could play a role in carcinogenesis and the efficacy of BC therapies. This review aims to describe specific microbiome patterns associated with BC. For this, a literature search was carried out in PubMed database using the MeSH terms "Breast Neoplasms" and "Gastrointestinal Microbiome", including 29 publications. Most of the studies have focused on characterizing the gut or breast tissue microbiome of the patients. Likewise, studies in animal models and in vitro that investigated the impact of gut microbiota (GM) on BC treatments and the effects of the microbiome on tumor cells were included. Based on the results of the included articles, BC could be associated with an imbalance in the GM. This imbalance varied depending on molecular type, stage and grade of cancer, menopause, menarche, body mass index, and physical activity. However, a specific microbial profile could not be identified as a biomarker. On the other hand, some studies suggest that the GM may influence the efficacy of BC therapies. In addition, some microorganisms and bacterial metabolites could improve the effects of therapies or influence tumor development.

System biology analysis of miRNA-gene interaction network reveals novel drug targets in breast cancer

Breast cancer is a heterogeneous disease that is ranked as one of the most common cancers worldwide. Currently, although there are existing molecules such as progesterone receptor and estrogen receptor for breast cancer treatment, discovering more effective drug targets is still in urgent need. In this study, we have obtained six sequencing datasets of breast cancer from GEO database and identified a set of differentially expressed molecules, including 67 miRNAs and 133 genes. Function enrichment analysis by miRPathDB database indicated that targets of 11 miRNAs could be enriched in breast cancer pathway with a p-value ≤ .05. A special miRNA-gene interaction network was constructed for analysis of the progression of breast cancer. We then ranked the importance of each molecule (i.e. miRNA and gene) by their node centrality indexes in the network and selected the top 10% of molecules. The statistical analysis of these molecules showed three miRNAs (hsa-miR-1275, hsa-miR-2392, hsa-miR-3141) have significant effects on the prognosis and survival of patients. By searching for potential drugs in Drugbank database, we have identified four candidates (phenethyl isothiocyanate, amuvatinib, theophylline, trifluridine) for targeting these genes. In conclusion, we believe that these drugs and their analogs could be used in the targeted therapy of breast cancer in the future.

Bio-Pathological Functions of Posttranslational Modifications of Histological Biomarkers in Breast Cancer

Proteins are the most common types of biomarkers used in breast cancer (BC) theranostics and management. By definition, a biomarker must be a relevant, objective, stable, and quantifiable biomolecule or other parameter, but proteins are known to exhibit the most variate and profound structural and functional variation. Thus, the proteome is highly dynamic and permanently reshaped and readapted, according to changing microenvironments, to maintain the local cell and tissue homeostasis. It is known that protein posttranslational modifications (PTMs) can affect all aspects of protein function. In this review, we focused our analysis on the different types of PTMs of histological biomarkers in BC. Thus, we analyzed the most common PTMs, including phosphorylation, acetylation, methylation, ubiquitination, SUMOylation, neddylation, palmitoylation, myristoylation, and glycosylation/sialylation/fucosylation of transcription factors, proliferation marker Ki-67, plasma membrane proteins, and histone modifications. Most of these PTMs occur in the presence of cellular stress. We emphasized that these PTMs interfere with these biomarkers maintenance, turnover and lifespan, nuclear or subcellular localization, structure and function, stabilization or inactivation, initiation or silencing of genomic and non-genomic pathways, including transcriptional activities or signaling pathways, mitosis, proteostasis, cell-cell and cell-extracellular matrix (ECM) interactions, membrane trafficking, and PPIs. Moreover, PTMs of these biomarkers orchestrate all hallmark pathways that are dysregulated in BC, playing both pro- and/or antitumoral and context-specific roles in DNA damage, repair and genomic stability, inactivation/activation of tumor-suppressor genes and oncogenes, phenotypic plasticity, epigenetic regulation of gene expression and non-mutational reprogramming, proliferative signaling, endocytosis, cell death, dysregulated TME, invasion and metastasis, including epithelial-mesenchymal/mesenchymal-epithelial transition (EMT/MET), and resistance to therapy or reversal of multidrug therapy resistance. PTMs occur in the nucleus but also at the plasma membrane and cytoplasmic level and induce biomarker translocation with opposite effects. Analysis of protein PTMs allows for the discovery and validation of new biomarkers in BC, mainly for early diagnosis, like extracellular vesicle glycosylation, which may be considered as a potential source of circulating cancer biomarkers.

Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank

The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank's longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10-8) gene-disease relationships alongside 182 gene-disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene-disease prioritization. All extracted gene-disease associations and incident disease predictive biomarkers are publicly available ( http://milton.public.cgr.astrazeneca.com ).

Exploring Canine Mammary Cancer through Liquid Biopsy: Proteomic Profiling of Small Extracellular Vesicles

(Background). Canine mammary tumors (CMTs) have emerged as an important model for understanding pathophysiological aspects of human disease. Liquid biopsy (LB), which relies on blood-borne biomarkers and offers minimal invasiveness, holds promise for reflecting the disease status of patients. Small extracellular vesicles (SEVs) and their protein cargo have recently gained attention as potential tools for disease screening and monitoring. (Objectives). This study aimed to isolate SEVs from canine patients and analyze their proteomic profile to assess their diagnostic and prognostic potential. (Methods). Plasma samples were collected from female dogs grouped into CMT (malignant and benign), healthy controls, relapse, and remission groups. SEVs were isolated and characterized using ultracentrifugation (UC), nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Proteomic analysis of circulating SEVs was conducted using liquid chromatography-mass spectrometry (LC-MS). (Results). While no significant differences were observed in the concentration and size of exosomes among the studied groups, proteomic profiling revealed important variations. Mass spectrometry identified exclusive proteins that could serve as potential biomarkers for mammary cancer. These included Inter-alpha-trypsin inhibitor heavy chain (ITIH2 and ITI4), phosphopyruvate hydratase or alpha enolase (ENO1), eukaryotic translation elongation factor 2 (eEF2), actin (ACTB), transthyretin (TTR), beta-2-glycoprotein 1 (APOH) and gelsolin (GSN) found in female dogs with malignant tumors. Additionally, vitamin D-binding protein (VDBP), also known as group-specific component (GC), was identified as a protein present during remission. (Conclusions). The results underscore the potential of proteins found in SEVs as valuable biomarkers in CMTs. Despite the lack of differences in vesicle concentration and size between the groups, the analysis of protein content revealed promising markers with potential applications in CMT diagnosis and monitoring. These findings suggest a novel approach in the development of more precise and effective diagnostic tools for this challenging clinical condition.

The endogenous association among MMP2/miR-1248/Circ_0087558/miR-643/ MAP2K6 axis can contribute to brain metastasis in basal-like subtype of breast cancer

Brain metastasis in basal-like breast cancer poses a significant challenge in cancer management due to its aggressive nature and limited treatment options. This study conducted a comprehensive analysis to explore the potential role of circular RNAs (circRNAs) as members of endogenous networks in developing breast cancer brain metastasis. Here, we utilized RNA sequencing data from primary breast cancer and brain metastasis tissue with basal-like subtype (n = 11). After quality controlling and preprocessing of fastq files, gene expression of mRNA and circRNAs were extracted from matched samples and normalized. Then, we employed the weighted gene co-expression network analysis approach to identify brain metastasis-associated circRNA modules ( S p e a r m a n Correlation > 0.5 , P - value < 0.05 ). Moreover, we found five protein-coding genes of PHLDA1, SLC12A2, MMP2, RGP1, and MAP2K6, significantly upregulated in brain metastatic tissues compared to primary breast cancer ( FDR < 0.05 ). These genes were enriched in the "GnRH signaling pathway" and "Fluid shear stress and atherosclerosis" pathways ( FDR < 0.05 ). Next, to explore the potential interactions between circRNAs and protein-coding genes, we reconstructed a competing endogenous RNA (ceRNA) network using mutual miRNAs between the circRNA module and upregulated mRNAs. Notably, we could detect two axes of circ_0087558/miR-604/MMP2 and MMP2/miR-1248/Circ_0087558/miR-643/MAP2K6 in ceRNA network. In conclusion, the identified circRNA-miRNA-mRNA axes might be therapeutic targets or diagnostic biomarkers for this challenging subtype of breast cancer. However, due to the small number of samples, further experimental validations are essential.

Analysis of human epidermal growth factor receptor 2 interaction on aptamer-probed interdigitated electrode for breast cancer diagnosis

Breast cancer has been reported to be high in its incidence with women, and early identification of breast cancer helps to improve and provide an effective treatment. Tumor markers are active substances; in particular, human epidermal growth factor receptor 2 (HER2) is over-expressed at the level of 20%-30%. This research work developed a highly sensitive HER2 biosensor on the interdigitated electrode (IDE) by using aptamer as a detection probe. To enhance the analytical performances, aptamer was attached to the gold nanoparticle and immobilized on the IDE through a chemical linker [(3-aminopropyl)triethoxysilane]. On the aptamer conjugation, HER2 was quantified through current-volt measurements, and the limit of detection of HER2 was calculated as 1 pg/mL on a linear range from 0.1 to 3000 pg/mL at an R2 (regression coefficient) of 0.9657. Further, a selective performance with human serum increased the current responses by increasing HER2 concentrations. Specific experiments with control protein and complementary aptamer sequence failed to enhance the current responses. This HER2 biosensor reflects the occurrence of breast cancer at its lower abundance and helps to identify the associated complications.

Dysregulation of miR-122, miR-574 and miR-375 in Egyptian patients with breast cancer

BACKGROUND

The early detection of breast cancer (BC) is receiving global attention, creating an urgent need for more sensitive and comprehensive strategies for preventive intervention, therapy assessment, and prognosis prediction. Aberrant expression of miRNAs has been observed in various malignancies and may be potential targets for therapy. Our study aims to examine the expression profiles of miR-375, miR-574-3p, and miR-122 in the sera of Egyptian women with BC, benign breast lesions, and a control group. We hope to determine if these miRNAs can serve as minimally invasive biomarkers for BC.

METHODS

This is a case-control study in which 77 patients with newly diagnosed BC, 20 patients with benign breast tumors, and 30 normal healthy subjects as controls were recruited from the outpatient clinic of the National Cancer Institute. The assessment of miRNAs was conducted using RT-PCR (Applied Biosystems).

RESULTS

The expression level of miRNA-122 was significantly upregulated in the BC group, while the expression levels of miRNA-574 and miRNA-375 showed significant downregulation in BC patients. Serum miR-122 and miRNA-375 were able to distinguish breast cancer from the benign and control groups in ROC curve analysis, with AUCs of 0.786 and 0.796, respectively. Our results also showed that serum miR-122 and miR-574 are significant predictor variables in the multivariate analysis, after adjusting for age.

CONCLUSIONS

Our findings suggest that miR-122 may act as an onco-microRNA, while miR-574 and miR-375 may have a main tumour suppressor role. The studied miRNAs may serve as minimally invasive biomarkers for cases of breast cancer and as promising potential therapeutic targets for breast cancer.

Identification of Potential Breast Cancer Stem Cell Biomarkers in the Secretome Using a Network Interaction Approach Analysis

BACKGROUND

Breast cancer stem cells (BCSCs) play a role in the high rates of resistance, recurrence, and metastasis. The precise biomarkers of BCSCs can assist effectively in identifying cancer, assessing prognosis, diagnosing, and monitoring therapy. The aim of this study was to give a complete analysis for predicting specific biomarkers of BCSCs.

METHODS

We aggregated profile datasets in this work to shed light on the underlying critical genes and pathways of BCSCs. We obtained two expression profiling by array datasets (GSE7513 and GSE7515) from the Gene Expression Omnibus (GEO) database to identify biomarkers in BCSCs. Enrichr was used to do functional analysis, including gene ontology (GO) and reactome pathway. Furthermore, the protein-protein interaction (PPI) of these differential expression genes (DEGs) was visualized using Cytoscape with the search tool for the retrieval of interacting genes (STRING). The hub genes in the PPI network were chosen for further investigation.

RESULTS

We identified 65 up-regulated and 190 down- regulated DEGs and the GO enrichment analysis revealed that these DEGs were enriched in biological process related to tumorigenesis and stemness, including alter the extracellular matrix's physicochemical properties, cytoskeletal reorganisation, adhesion, motility, migration, growth, and survival. The Reactome analysis indicated that these DEGs were also involved in modulating function of ECM, regulation cancer metabolism and angiogenesis, tumor growth, proliferation, and metastasis.

CONCLUSION

Our bioinformatic study revealed that FYN, INADL, OCLN, F11R, and TOP2A were potential biomarker panel of BCSCs from secretome.

Exploratory drug discovery in breast cancer patients: A multimodal deep learning approach to identify novel drug candidates targeting RTK signaling

Breast cancer, a highly formidable and diverse malignancy predominantly affecting women globally, poses a significant threat due to its intricate genetic variability, rendering it challenging to diagnose accurately. Various therapies such as immunotherapy, radiotherapy, and diverse chemotherapy approaches like drug repurposing and combination therapy are widely used depending on cancer subtype and metastasis severity. Our study revolves around an innovative drug discovery strategy targeting potential drug candidates specific to RTK signalling, a prominently targeted receptor class in cancer. To accomplish this, we have developed a multimodal deep neural network (MM-DNN) based QSAR model integrating omics datasets to elucidate genomic, proteomic expression data, and drug responses, validated rigorously. The results showcase an R2 value of 0.917 and an RMSE value of 0.312, affirming the model's commendable predictive capabilities. Structural analogs of drug molecules specific to RTK signalling were sourced from the PubChem database, followed by meticulous screening to eliminate dissimilar compounds. Leveraging the MM-DNN-based QSAR model, we predicted the biological activity of these molecules, subsequently clustering them into three distinct groups. Feature importance analysis was performed. Consequently, we successfully identified prime drug candidates tailored for each potential downstream regulatory protein within the RTK signalling pathway. This method makes the early stages of drug development faster by removing inactive compounds, providing a hopeful path in combating breast cancer.

Biomarker-specific biosensors revolutionise breast cancer diagnosis

Breast cancer is the most common cancer among women across the globe. In order to treat breast cancer successfully, it is crucial to conduct a comprehensive assessment of the condition during its initial stages. Although mammogram screening has long been a common method of breast cancer screening, high rates of type I error and type II error results as well as radiation exposure have always been of concern. The outgrowth cancer mortality rate is primarily due to delayed diagnosis, which occurs most frequently in a metastatic III or IV stage, resulting in a poor prognosis after therapy. Traditional detection techniques require identifying carcinogenic properties of cells, such as DNA or RNA alterations, conformational changes and overexpression of certain proteins, and cell shape, which are referred to as biomarkers or analytes. These procedures are complex, long-drawn-out, and expensive. Biosensors have recently acquired appeal as low-cost, simple, and super sensitive detection methods for analysis. The biosensor approach requires the existence of biomarkers in the sample. Thus, the development of novel molecular markers for diverse forms of cancer is a rising complementary affair. These biosensor devices offer two major advantages: (1) a tiny amount of blood collected from the patient is sufficient for analysis, and (2) it could help clinicians swiftly select and decide on the best therapy routine for the individual. This review will include updates on prospective cancer markers and biosensors in cancer diagnosis, as well as the associated detection limitations, with a focus on biosensor development for marker detection.

Recent Contributions of Mass Spectrometry-Based "Omics" in the Studies of Breast Cancer

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Multiplex electrochemical sensing platforms for the detection of breast cancer biomarkers

Herein, advancements in electroanalytical devices for the simultaneous detection of diverse breast cancer (BC) markers are demonstrated. This article identifies several important areas of exploration for electrochemical diagnostics and highlights important factors that are pivotal for the successful deployment of novel bioanalytical devices. We have highlighted that the limits of detection (LOD) reported for the multiplex electrochemical biosensor can surpass the sensitivity displayed by current clinical standards such as ELISA, FISH, and PCR. HER-2; a breast cancer marker characterised by increased metastatic potential, more aggressive development, and poor clinical outcomes; can be sensed with a LOD of 0.5 ng/ml using electrochemical multiplex platforms, which falls within the range of that measured by ELISA (from picogram/ml to nanogram/ml). Electrochemical multiplex biosensors are reported with detection limits of 0.53 ng/ml and 0.21 U/ml for MUC-1 and CA 15-3, respectively, or 5.8 × 10-3 U/ml for CA 15-3 alone. The sensitivity of electrochemical assays is improved when compared to conventional analysis of MUC-1 protein which is detected at 11-12 ng/ml, and ≤30 U/ml for CA 15-3 in the current clinical blood tests. The LOD for micro-ribonucleic acid (miRNA) biomarkers analyzed by electrochemical multiplex assays were all notedly superior at 9.79 × 10-16 M, 3.58 × 10-15 M, and 2.54 × 10-16 M for miRNA-155, miRNA-21, and miRNA-16, respectively. The dogma in miRNA testing is the qRT-PCR method, which reports ranges in the ng/ml level for the same miRNAs. Breast cancer exosomes, which are being explored as a new frontier of biosensing, have been detected electrochemically with an LOD of 103-108 particles/mL and can exceed detection limits seen by the tracking and analysis of nanoparticles (∼ 107 particles/ml), flow cytometry, Western blotting and ELISA, etc. A range of concentration at 78-5,000 pg/ml for RANKL and 16-1,000 pg/ml for TNF is reported for ELISA assay while LOD values of 2.6 and 3.0 pg/ml for RANKL and TNF, respectively, are demonstrated by the electrochemical dual immunoassay platform. Finally, EGFR and VEGF markers can be quantified at much lower concentrations (0.01 and 0.005 pg/ml for EGFR and VEGF, respectively) as compared to their ELISA assays (EGRF at 0.31-20 ng/ml and VEGF at 31.3-2,000 pg/ml). In this study we hope to answer several questions: (1) Are the limits of detection (LODs) reported for multiplex electrochemical biosensors of clinical relevance and how do they compare to well-established methods like ELISA, FISH, or PCR? (2) Can a single sensor electrode be used for the detection of multiple markers from one blood drop? (3) What mechanism of electrochemical biosensing is the most promising, and what technological advancements are needed to utilize these devices for multiplex POC detection? (4) Can nanotechnology advance the sensitive and selective diagnostics of multiple BC biomarkers? (5) Are there preferred receptors (antibody, nucleic acid or their combinations) and preferred biosensor designs (complementary methods, sandwich-type protocols, antibody/aptamer concept, label-free protocol)? (6) Why are we still without FDA-approved electrochemical multiplex devices for BC screening?

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.

Elucidating the susceptibility to breast cancer: an in-depth proteomic and transcriptomic investigation into novel potential plasma protein biomarkers

Objectives: This study aimed to identify plasma proteins that are associated with and causative of breast cancer through Proteome and Transcriptome-wide association studies combining Mendelian Randomization. Methods: Utilizing high-throughput datasets, we designed a two-phase analytical framework aimed at identifying novel plasma proteins that are both associated with and causative of breast cancer. Initially, we conducted Proteome/Transcriptome-wide association studies (P/TWAS) to identify plasma proteins with significant associations. Subsequently, Mendelian Randomization was employed to ascertain the causation. The validity and robustness of our findings were further reinforced through external validation and various sensitivity analyses, including Bayesian colocalization, Steiger filtering, heterogeneity and pleiotropy. Additionally, we performed functional enrichment analysis of the identified proteins to better understand their roles in breast cancer and to assess their potential as druggable targets. Results: We identified 5 plasma proteins demonstrating strong associations and causative links with breast cancer. Specifically, PEX14 (OR = 1.201, p = 0.016) and CTSF (OR = 1.114, p < 0.001) both displayed positive and causal association with breast cancer. In contrast, SNUPN (OR = 0.905, p < 0.001), CSK (OR = 0.962, p = 0.038), and PARK7 (OR = 0.954, p < 0.001) were negatively associated with the disease. For the ER-positive subtype, 3 plasma proteins were identified, with CSK and CTSF exhibiting consistent trends, while GDI2 (OR = 0.920, p < 0.001) was distinct to this subtype. In ER-negative subtype, PEX14 (OR = 1.645, p < 0.001) stood out as the sole protein, even showing a stronger causal effect compared to breast cancer. These associations were robustly supported by colocalization and sensitivity analyses. Conclusion: Integrating multiple data dimensions, our study successfully pinpointed plasma proteins significantly associated with and causative of breast cancer, offering valuable insights for future research and potential new biomarkers and therapeutic targets.

A novel coiled-coil domain containing-related gene signature for predicting prognosis and treatment effect of breast cancer

PURPOSE

Breast cancer (BRCA) is a prevalent tumor worldwide. The association between the coiled-coil domain-containing (CCDC) protein family and different tumors has been established. However, the prognostic significance of this protein family in breast cancer remains uncertain.

METHODS

Gene expression and clinical data were obtained from the TCGA, METABRIC, and GEO databases. Prognosis genes were identified using univariate Cox and LASSO Cox regression, leading to the establishment of a prognostic signature. Subsequently, the risk model was conducted based on survival and clinical feature analyses, and a nomogram for prognosis prediction was developed. Furthermore, analyses of biological function, immune characteristics, and drug sensitivity were performed. Finally, single-cell sequencing data were utilized to uncover the expression patterns of genes in the risk model.

RESULTS

Five genes were identified and utilized for risk modeling. The model demonstrated excellent prognostic value as indicated by ROC and Kaplan-Meier analysis. The high-risk group exhibited shorter survival time and higher likelihood of recurrence. Functional annotation indicated a correlation between the risk score and immune pathways. Conversely, the low-risk group displayed a greater enrichment in immune pathways and exhibited more active immune microenvironment characteristics. Additionally, drug sensitivity analysis using both public and our sequencing data revealed that the risk model possessed a broad range of predictive values.

CONCLUSIONS

We have developed a gene signature and have verified that patients with low-risk are more likely to have better prognosis and respond positively to therapy. This finding offers a valuable point of reference for BRCA individualized treatment.

Clinical Impact of New Treatment Strategies for HER2-Positive Metastatic Breast Cancer Patients with Resistance to Classical Anti-HER Therapies

HER2-positive breast cancer accounts for 15-20% of all breast cancer cases. This subtype is characterized by an aggressive behavior and poor prognosis. Anti-HER2 therapies have considerably improved the natural course of the disease. Despite this, relapse still occurs in around 20% of patients due to primary or acquired treatment resistance, and metastasis remains an incurable disease. This article reviews the main mechanisms underlying resistance to anti-HER2 treatments, focusing on newer HER2-targeted therapies. The progress in anti-HER2 drugs includes the development of novel antibody-drug conjugates with improvements in the conjugation process and novel linkers and payloads. Moreover, trastuzumab deruxtecan has enhanced the efficacy of trastuzumab emtansine, and the new drug trastuzumab duocarmazine is currently undergoing clinical trials to assess its effect. The combination of anti-HER2 agents with other drugs is also being evaluated. The addition of immunotherapy checkpoint inhibitors shows some benefit in a subset of patients, indicating the need for useful biomarkers to properly stratify patients. Besides, CDK4/6 and tyrosine kinase inhibitors are also included in the design of new treatment strategies. Lapitinib, neratinib and tucatinib have been approved for HER2-positive metastasis patients, however clinical trials are currently ongoing to optimize combined strategies, to reduce toxicity, and to better define the useful setting. Clinical research should be strengthened along with the discovery and validation of new biomarkers, as well as a deeper understanding of drug resistance and action mechanisms.

Proteome-wide Profiling of Asymmetric Dimethylated Arginine in Human Breast Tumors

Arginine methylation catalyzed by protein arginine methyltransferases (PRMTs) is a prevalent post-translational modification (PTM) that regulates diverse cellular processes. Aberrant expression of type I PRMTs that catalyze asymmetric arginine dimethylation (ADMA) is often found in cancer, though little is known about the ADMA status of substrate proteins in tumors. Using LC-MS/MS along with pan-specific ADMA antibodies, we performed global mapping of ADMA in five patient-derived xenograft (PDX) tumors representing different subtypes of human breast cancer. In total, 403 methylated sites from 213 proteins were identified, including 322 novel sites when compared to the PhosphositesPlus database. Moreover, using peptide arrays in vitro, approximately 70% of the putative substrates were validated to be methylated by PRMT1, PRMT4, and PRMT6. Notably, when compared with our previously identified ADMA sites from breast cancer cell lines, only 75 ADMA sites overlapped between cell lines and PDX tumors. Collectively, this study provides a useful resource for both PRMT and breast cancer communities for further exploitation of the functions of PRMT dysregulation during breast cancer progression.

FGF1 Protects MCF-7 Cells against Taltobulin through Both the MEKs/ERKs and PI3K/AKT Signaling Pathway

Breast cancer is a widespread and complex disease characterized by abnormal signaling pathways that promote tumor growth and progression. Despite significant medical advances and the development of increasingly effective therapies for breast cancer, drug resistance and reduced sensitivity to prior therapies remain persistent challenges. Dysregulation of growth factors such as FGFs and EGF and their receptors is a contributing factor to reduced response to treatment, promoting cell survival and proliferation, metastasis, EMT or increased expression of ABC transporters. Our study demonstrates a protective role for FGF1 in MCF-7 breast cancer cells against taltobulin-induced cytotoxicity, mediated by activation of its receptors and compares its activity to EGF, another growth factor involved in breast cancer development and progression. The mechanisms of action of these two proteins are different: FGF1 exerts its effects through the activation of both ERKs and AKT, whereas EGF acts only through ERKs. FGF1 action in the presence of the drug promotes cell viability, reduces apoptosis and increases cell migration. Although EGF and its receptors have received more attention in breast cancer research to date, our findings highlight the key role played by FGFs and their receptors in promoting drug resistance to tubulin polymerization inhibitors in FGFR-positive tumors.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Advances in Electrochemical Biosensor Technologies for the Detection of Nucleic Acid Breast Cancer Biomarkers

Breast cancer is the second leading cause of cancer deaths in women worldwide; therefore, there is an increased need for the discovery, development, optimization, and quantification of diagnostic biomarkers that can improve the disease diagnosis, prognosis, and therapeutic outcome. Circulating cell-free nucleic acids biomarkers such as microRNAs (miRNAs) and breast cancer susceptibility gene 1 (BRCA1) allow the characterization of the genetic features and screening breast cancer patients. Electrochemical biosensors offer excellent platforms for the detection of breast cancer biomarkers due to their high sensitivity and selectivity, low cost, use of small analyte volumes, and easy miniaturization. In this context, this article provides an exhaustive review concerning the electrochemical methods of characterization and quantification of different miRNAs and BRCA1 breast cancer biomarkers using electrochemical DNA biosensors based on the detection of hybridization events between a DNA or peptide nucleic acid probe and the target nucleic acid sequence. The fabrication approaches, the biosensors architectures, the signal amplification strategies, the detection techniques, and the key performance parameters, such as the linearity range and the limit of detection, were discussed.

Metformin and long non-coding RNAs in breast cancer

Breast cancer (BC) is the second most common cancer and cause of death in women. In recent years many studies investigated the association of long non-coding RNAs (lncRNAs), as novel genetic factors, on BC risk, survival, clinical and pathological features. Recent studies also investigated the roles of metformin treatment as the firstline treatment for type 2 diabetes (T2D) played in lncRNAs expression/regulation or BC incidence, outcome, mortality and survival, separately. This comprehensive study aimed to review lncRNAs associated with BC features and identify metformin-regulated lncRNAs and their mechanisms of action on BC or other types of cancers. Finally, metformin affects BC by regulating five BC-associated lncRNAs including GAS5, HOTAIR, MALAT1, and H19, by several molecular mechanisms have been described in this review. In addition, metformin action on other types of cancers by regulating ten lncRNAs including AC006160.1, Loc100506691, lncRNA-AF085935, SNHG7, HULC, UCA1, H19, MALAT1, AFAP1-AS1, AC026904.1 is described.

End-of-neoadjuvant treatment circulating microRNAs and HER2-positive breast cancer patient prognosis: An exploratory analysis from NeoALTTO

Background

The absence of breast cancer cells in surgical specimens, i.e., pathological complete response (pCR), is widely recognized as a favorable prognostic factor after neoadjuvant therapy. In contrast, the presence of disease at surgery characterizes a prognostically heterogeneous group of patients. Here, we challenged circulating microRNAs (miRNAs) at the end of neoadjuvant therapy as potential prognostic biomarkers in the NeoALTTO study.

Methods

Patients treated within the trastuzumab arm (i.e., pre-operative weekly trastuzumab for 6 weeks followed by the addition of weekly paclitaxel for 12 weeks; post-operative FEC for 3 cycles followed by trastuzumab up to complete 1 year of treatment) were randomized into a training (n= 54) and testing (n= 72) set. RT-PCR-based high-throughput miRNA profile was performed on plasma samples collected at the end of neoadjuvant treatment of both sets. After normalization, circulating miRNAs associated with event free survival (EFS) were identified by univariate and multivariate Cox regression model.

Results

Starting from 23 circulating miRNAs associated with EFS in the training set, we generated a 3-circulating miRNA prognostic signature consisting of miR-185-5p, miR-146a-5p, miR-22-3p, which was confirmed in the testing set. The 3-circulating miRNA signature showed a C-statistic of 0.62 (95% confidence interval [95%CI] 0.53-0.71) in the entire study cohort. By resorting to a multivariate Cox regression model we found a statistical significant interaction between the expression values of miR-194-5p and pCR status (p.interaction =0.005) with an estimate Hazard Ratio (HR) of 1.83 (95%CI 1.14- 2.95) in patients with pCR, and 0.87 (95%CI 0.69-1.10) in those without pCR. Notably, the model including this interaction along with the abovementioned 3-circulating miRNA signature provided the highest discriminatory capability with a C-statistic of 0.67 (95%CI 0.58-0.76).

Conclusions

Circulating miRNAs are informative to identify patients with different prognosis among those with heterogeneous response after trastuzumab-based neoadjuvant treatment, and may be an exploitable tool to select candidates for salvage adjuvant therapy.

Glypican-3 Differentiates Intraductal Carcinoma and Paget's Disease from Other Types of Breast Cancer

Background and Objectives: breast cancer remains the most common health burden affecting females worldwide. Despite developments in breast cancer diagnostic approaches and treatment strategies, the clinical management of metastatic breast cancer remains challenging. Thus, there is a need to identify new biomarkers and novel drug targets for breast cancer diagnosis and therapy. Recently, aberrant glypican-3 (GPC3) expression in cancers has gained considerable interest in cancer research. The studies, however, have yielded contradictory results about GPC3 expression in breast cancer. Therefore, the current study aims to analyse GPC3 expression across a large panel of different breast cancer subtypes. Materials and Methods: GPC3 expression was immunohistochemically evaluated in 230 breast cancer patients along with eight normal tissues and its associations to clinical and demographic characteristics, as well as immunohistochemical biomarkers for breast cancer. Moreover, a public database consisting of breast cancer patients' survival data and GPC3 gene expression information was used to assess the prognostic value of GPC3 in the survival of breast cancer patients. Results: GPC3 expression was only characterised in 7.5% of different histological breast cancer subtypes. None of the normal breast tissues displayed GPC3 expression. Interestingly, all cases of Paget's disease, as well as 42.9% of intraductal and 16.7% of mucinous carcinomas were found to have GPC3 expression, where it was able to significantly discriminate Paget's disease and intraductal carcinoma from other breast cancer subtypes. Importantly, GPC3 expression was found more often in tumours that tested positive for the expression of hormone receptors and human epidermal growth factor receptor 2 (HER2), indicating more favourable histological subtypes of breast cancer. Consequently, longer relapse-free survival (RFS) was significantly correlated with higher GPC3 mRNA expression. Conclusions: Our study proposes that GPC3 is a promising breast cancer subtype-specific biomarker. Moreover, GPC3 may have the potential to be a molecular target for the development of new therapeutics for specific subtypes of breast cancer.

Potential Impact of Preoperative Circulating Biomarkers on Individual Escalating/de-Escalating Strategies in Early Breast Cancer

The research on non-invasive circulating biomarkers to guide clinical decision is in wide expansion, including the earliest disease settings. Several new intensification/de-intensification strategies are approaching clinical practice, personalizing the treatment for each patient. Moreover, liquid biopsy is revealing its potential with multiple techniques and studies available on circulating biomarkers in the preoperative phase. Inflammatory circulating cells, circulating tumor cells (CTCs), cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), and other biological biomarkers are improving the armamentarium for treatment selection. Defining the escalation and de-escalation of treatments is a mainstay of personalized medicine in early breast cancer. In this review, we delineate the studies investigating the possible application of these non-invasive tools to give a more enlightened approach to escalating/de-escalating strategies in early breast cancer.

The Clinical Utility of Droplet Digital PCR for Profiling Circulating Tumor DNA in Breast Cancer Patients

Breast cancer is the most common cancer affecting women worldwide. It is a malignant and heterogeneous disease with distinct molecular subtypes, which has prognostic and predictive implications. Circulating tumor DNA (ctDNA), cell-free fragmented tumor-derived DNA in blood plasma, is an invaluable source of specific cancer-associated mutations and holds great promise for the development of minimally invasive diagnostic tests. Furthermore, serial monitoring of ctDNA over the course of systemic and targeted therapies not only allows unparalleled efficacy assessments but also enables the identification of patients who are at risk of progression or recurrence. Droplet digital PCR (ddPCR) is a powerful technique for the detection and monitoring of ctDNA. Due to its relatively high accuracy, sensitivity, reproducibility, and capacity for absolute quantification, it is increasingly used as a tool for managing cancer patients through liquid biopsies. In this review paper, we gauge the clinical utility of ddPCR as a technique for mutational profiling in breast cancer patients and focus on HER2, PIK3CA, ESR1, and TP53, which represent the most frequently mutated genes in breast cancers.

Classic and New Markers in Diagnostics and Classification of Breast Cancer

Simple Summary

With ever-increasing incidence, breast cancer is considered a most diagnosed type of cancer among women worldwide. Breast cancer arises through malignant transformation of ductal or lobular cells in female (or male) breast and the genetic, phenotypic and morphological heterogeneity has an effect on tumour’s behaviour, thereby instigating a need for individual personalized therapy. A traditional assessment of tumour’s characteristics involves a biopsy and histological analysis of a tumour tissue, and in recent years has been accompanied by analysis of molecular biomarkers to enhance the results. In this work we aimed to thoroughly investigate the latest data in this field of study and give a comprehensive review of novel molecular biomarkers of breast cancer and methodologies used to analyse them.

Abstract

Breast cancer remains the most frequently diagnosed form of female’s cancer, and in recent years it has become the most common cause of cancer death in women worldwide. Like many other tumours, breast cancer is a histologically and biologically heterogeneous disease. In recent years, considerable progress has been made in diagnosis, subtyping, and complex treatment of breast cancer with the aim of providing best suited tumour-specific personalized therapy. Traditional methods for breast cancer diagnosis include mammography, MRI, biopsy and histological analysis of tumour tissue in order to determine classical markers such as estrogen and progesterone receptors (ER, PR), cytokeratins (CK5/6, CK14, C19), proliferation index (Ki67) and human epidermal growth factor type 2 receptor (HER2). In recent years, these methods have been supplemented by modern molecular methodologies such as next-generation sequencing, microRNA, in situ hybridization, and RT-qPCR to identify novel molecular biomarkers. MicroRNAs (miR-10b, miR-125b, miR145, miR-21, miR-155, mir-30, let-7, miR-25-3p), altered DNA methylation and mutations of specific genes (p16, BRCA1, RASSF1A, APC, GSTP1), circular RNA (hsa_circ_0072309, hsa_circRNA_0001785), circulating DNA and tumour cells, altered levels of specific proteins (apolipoprotein C-I), lipids, gene polymorphisms or nanoparticle enhanced imaging, all these are promising diagnostic and prognostic tools to disclose any specific features from the multifaceted nature of breast cancer to prepare best suited individualized therapy.

Mass Spectrometry-Based Proteomics of Human Milk to Identify Differentially Expressed Proteins in Women with Breast Cancer versus Controls

It is thought that accurate risk assessment and early diagnosis of breast cancer (BC) can help reduce cancer-related mortality. Proteomics analysis of breast milk may provide biomarkers of risk and occult disease. Our group works on the analysis of human milk samples from women with BC and controls to investigate alterations in protein patterns of milk that could be related to BC. In the current study, we used mass spectrometry (MS)-based proteomics analysis of 12 milk samples from donors with BC and matched controls. Specifically, we used one-dimensional (1D)-polyacrylamide gel electrophoresis (PAGE) coupled with nanoliquid chromatography tandem MS (nanoLC-MS/MS), followed by bioinformatics analysis. We confirmed the dysregulation of several proteins identified previously in a different set of milk samples. We also identified additional dysregulations in milk proteins shown to play a role in cancer development, such as Lactadherin isoform A, O-linked N-acetylglucosamine (GlcNAc) transferase, galactosyltransferase, recoverin, perilipin-3 isoform 1, histone-lysine methyltransferase, or clathrin heavy chain. Our results expand our current understanding of using milk as a biological fluid for identification of BC-related dysregulated proteins. Overall, our results also indicate that milk has the potential to be used for BC biomarker discovery, early detection and risk assessment in young, reproductively active women.

MicroRNA-506 ameliorates breast cancer-induced osteolytic bone metastasis via the NFATc-1 signaling pathway

Breast cancer is becoming a common life-threatening disease, especially in women, along with higher incidence and mortality. MicroRNA (miR)-506 was reported to participate in breast cancer progression, while the role of miR-506 in breast cancer-induced osteolytic bone metastasis is unclear. In the present study, we found significant downregulation of miR-506 in breast cancer tissues and cell lines. Overexpression of miR-506 notably reduced the proliferative, migratory and invasive rates of MCF7 and MDA-MB-231 cells, and reduced the production of inflammatory factors IL-6 and TNF-α in MCF7 cells. Moreover, overexpression of miR-506 obviously inhibited tumor growth in an in vivo animal model. In addition, overexpression of miR-560 efficiently attenuated breast cancer-induced osteolysis in vivo, which was characterized by increased bone volume/total volume (BT/TV), trabecular number (Tb. N), and trabecular thickness (Tb. Th), as well as the reduced trabecular separation (Tb. Sp). The nuclear factor of activated T cell cytoplasmic 1 (NFATc1) was identified as a downstream target of miR-506, and overexpression of miR-506 could inhibit breast cancer progression by targeting NFATc1. Furthermore, our results showed that NFATc-1 might participate in the inhibition of miR-506 on breast cancer-induced osteolysis. In conclusion, our findings provide insights into understanding the pathogenesis of breast cancer and breast cancer-induced osteolytic bone metastasis, and miR-506 might serve as a novel biomarker for this disease.

Recent advances in photothermal therapy-based multifunctional nanoplatforms for breast cancer

Breast cancer (BC) is one of the most common cancers in women worldwide; however, the successful treatment of BC, especially triple-negative breast cancer (TNBC), remains a significant clinical challenge. Recently, photothermal therapy (PTT), which involves the generation of heat under irradiation to achieve photothermal ablation of BC with minimal invasiveness and outstanding spatial–temporal selectivity, has been demonstrated as a novel therapy that can overcome the drawbacks of chemotherapy or surgery. Significantly, when combining PTT with chemotherapy and/or photodynamic therapy, an enhanced synergistic therapeutic effect can be achieved in both primary and metastatic BC tumors. Thus, this review discusses the recent developments in nanotechnology-based photothermal therapy for the treatment of BC and its metastasis to provide potential strategies for future BC treatment.

High mRNA Expression Levels of Heat Shock Protein Family B Member 2 (HSPB2) Are Associated with Breast Cancer Patients’ Relapse and Poor Survival

Small heat shock proteins (sHSPs) are ubiquitous ATP-independent chaperones that contribute to the maintenance of proteome integrity and functionality. Recent evidence suggests that sHSPs are ubiquitously expressed in numerous types of tumors and have been proposed to be implicated in oncogenesis and malignant progression. Heat shock protein family B member 2 (HSPB2) is a member of the sHSPs, which is found to be expressed, among others, in human breast cancer cell lines and constitutes an inhibitor of apical caspase activation in the extrinsic apoptotic pathway. In this study, we investigated the potential prognostic significance of HSPB2 mRNA expression levels in breast cancer, which represents the most frequent malignancy in females and one of the three most common cancer types worldwide. To this end, malignant breast tumors along with paired non-cancerous breast tissue specimens were used. HSPB2 expression levels were quantified in these two cohorts using a sensitive and accurate SYBR green-based quantitative real-time polymerase chain reaction (q-RT-PCR). Extensive biostatistical analyses were performed including Kaplan–Meier and Cox regression survival analyses for the assessment of the results. The significant downregulation of HSPB2 gene expression was revealed in breast tumors compared to their adjacent non-cancerous breast tissues. Notably, high HSPB2 mRNA expression predicts poor disease-free survival and overall survival of breast cancer patients. Multivariate Cox regression analysis revealed that HSPB2 mRNA overexpression is a significant predictor of poor prognosis in breast cancer, independent of other clinicopathological factors. In conclusion, high HSPB2 mRNA expression levels are associated with breast cancer patients’ relapse and poor survival.

Solid Self-Nano Emulsifying Nanoplatform Loaded with Tamoxifen and Resveratrol for Treatment of Breast Cancer

The solid self-nanoemulsifying drug delivery system (s-SNEDDS) is a growing platform for the delivery of drugs via oral route. In the present work, tamoxifen (TAM) was loaded in SNEDDS with resveratrol (RES), which is a potent chemotherapeutic, antioxidant, anti-inflammatory and P-gp inhibitor for enhancing bioavailability and to obtain synergistic anti-cancer effect against breast cancer. SNEDDS were developed using capmul MCM as oil, Tween 80 as surfactant and transcutol-HP as co-surfactant and optimized by central composite rotatable design. Neusilin US2 concentration was optimized for adsorption of liquid SNEDDS to prepare s-SNEDDS. The developed formulation was characterized and investigated for various in vitro and cell line comparative studies. Optimized TAM-RES-s-SNEDDS showed spherical droplets of a size less than 200 nm. In all in vitro studies, TAM-RES-s-SNEDDS showed significantly improved (p ˂ 0.05) release and permeation across the dialysis membrane and intestinal lumen. Moreover, TAM-RES-s-SNEDDS possessed significantly greater therapeutic efficacy (p < 0.05) and better internalization on the MCF-7 cell line as compared to the conventional formulation. Additionally, oral bioavailability of TAM from SNEDDS was 1.63 folds significantly higher (p < 0.05) than that of combination suspension and 4.16 folds significantly higher (p < 0.05) than TAM suspension. Thus, findings suggest that TAM- RES-s-SNEDDS can be the future delivery system that potentially delivers both drugs to cancer cells for better treatment.

Evaluation of Expressed MicroRNAs as Prospective Biomarkers for Detection of Breast Cancer

Background: Early detection and screening of breast cancer (BC) might help improve the prognosis of BC patients. This study evaluated the use of serum microRNAs (miRs) as non-invasive biomarkers in BC patients. Methods: Using quantitative real-time polymerase chain reaction, we evaluated the serum expression of four candidate miRs (miR-155, miR-373, miR-10b, and miR-34a) in 99 Egyptian BC patients and 40 healthy subjects (as a control). The miRs expression was correlated with clinicopathological data. In addition, the sensitivity and specificity of the miRs were determined using receiver operating characteristic (ROC) curve analysis. Results: Serum miR-155, miR-373, and miR-10b expression were significantly upregulated (p < 0.001), while serum miR-34a was downregulated (p < 0.00) in nonmetastatic (M0) BC patients compared to the control group. In addition, serum miR-155 and miR-10b were upregulated in BC patients with large tumor sizes and extensive nodal involvement (p < 0.001). ROC curve analysis showed high diagnostic accuracy (area under the curve = 1.0) when the four miRs were combined. Serum miR-373 was significantly upregulated in the human epidermal growth factor 2−negative (p < 0.001), estrogen receptor−positive (p < 0.005), and progesterone receptor (PR)-positive (p < 0.024) in BC patients, and serum miR-155 was significantly upregulated in PR-negative (p < 0.001) BC patients while both serum miR-155 and miR-373 were positively correlated with the tumor grade. Conclusions: Circulating serum miR-155, miR-373, miR-10b, and miR-34a are potential biomarkers for early BC detection in Egyptian patients and their combination shows high sensitivity and specificity.