Tumor markers of breast cancer: New prospectives

WS2 nanosheets-based electrochemical biosensor for highly sensitive detection of tumor marker miRNA-4484

In this paper, a few-layer WS2 nanosheets-based electrochemical biosensor was fabricated for the highly sensitive detection of breast cancer tumor marker miRNA-4484. Firstly, few-layer WS2 nanosheets were prepared by shear stripping and characterized by SEM, TEM, AFM and UV spectrophotometer. After modification of few-layer WS2 nanosheets on the electrode surface, the miRNA probe was fixed on the few-layer WS2 nanosheets by polycytosine (PolyC). Then short-chain miRNA containing PolyC was used as the blocking agent to close the excess active sites on the surface of WS2 nanosheets to complete the fabrication of the sensor biosensing interface. Finally, the current changes caused by the specific binding of miRNA-4484 to the probe were analyzed by differential pulse voltammetry (DPV). The results showed that the sensor had a good linear relationship for the detection of miRNA-4484 in the concentration range of 1 aM-100 fM, and the detection limit was as low as 1.61 aM. In addition, the electrochemical sensor had excellent selectivity, stability and reproducibility. The artificial sample tests indicated that the developed biosensors have the potential for clinical application in the future.

Associations of stem cell markers CD44, CD24 and ALDH1A1 with mammographic breast density in women with benign breast biopsies

BACKGROUND

We examined associations of CD44, CD24 and ALDH1A1 breast stem cell markers with mammographic breast density (MBD), a well-established breast cancer (BCa) risk factor.

METHODS

We included 218 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on BCa risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was done on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as percent of positively stained cells for each marker out of the total cell count. MBD was assessed with computer-assisted techniques. Generalised linear regression was used to examine the associations of each marker with square root-transformed percent density (PD), absolute dense and non-dense areas (NDA), adjusted for BCa risk factors.

RESULTS

Stromal CD44 and ALDH1A1 expression was positively associated with PD (≥ 10% vs. <10% β = 0.56, 95% confidence interval [CI] [0.06; 1.07] and β = 0.81 [0.27; 1.34], respectively) and inversely associated with NDA (β per 10% increase = -0.17 [-0.34; -0.01] and β for ≥10% vs. <10% = -1.17 [-2.07; -0.28], respectively). Epithelial CD24 expression was inversely associated with PD (β per 10% increase = -0.14 [-0.28; -0.01]. Stromal and epithelial CD24 expression was positively associated with NDA (β per 10% increase = 0.35 [0.2 × 10-2; 0.70] and β per 10% increase = 0.34 [0.11; 0.57], respectively).

CONCLUSION

Expression of stem cell markers is associated with MBD.

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.

Proteases, a powerful biochemical tool in the service of medicine, clinical and pharmaceutical

Proteases, enzymes that hydrolyze peptide bonds, have various applications in medicine, clinical applications, and pharmaceutical development. They are used in cancer treatment, wound debridement, contact lens cleaning, prion degradation, biofilm removal, and fibrinolytic agents. Proteases are also crucial in cardiovascular disease treatment, emphasizing the need for safe, affordable, and effective fibrinolytic drugs. Proteolytic enzymes and protease biosensors are increasingly used in diagnostic and therapeutic applications. Advanced technologies, such as nanomaterials-based sensors, are being developed to enhance the sensitivity, specificity, and versatility of protease biosensors. These biosensors are becoming effective tools for disease detection due to their precision and rapidity. They can detect extracellular and intracellular proteases, as well as fluorescence-based methods for real-time and label-free detection of virus-related proteases. The active utilization of proteolytic enzymatic biosensors is expected to expand significantly in biomedical research, in-vitro model systems, and drug development. We focused on journal articles and books published in English between 1982 and 2024 for this study.

The Role of Circulating MicroRNAs in the Prediction of Response to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer in the Indian Population

INTRODUCTION

MicroRNAs (miRNAs) are known to play an important role in cancer cell proliferation, susceptibility of cancer cells to chemotherapy, and patient survival. Identifying miRNAs that can predict response to chemotherapy in locally advanced breast cancer (LABC), the most common variant, can help to choose appropriate drug regimens to suit the epigenetic profile of individual patients.

OBJECTIVE

To investigate the expression of the differentially expressed miRNAs identified by next-generation sequencing from a pilot study involving cases and controls, in peripheral blood mononuclear cells (PBMC) of patients with LABC during the course of neoadjuvant chemotherapy (NAC) and determine their role in response to chemotherapy.

METHODS

This study included 30 newly diagnosed LABC patients. Peripheral blood from every participant was collected before the start of chemotherapy, at the end of the third cycle, and at the end of the seventh cycle of NAC. Based on the results of a pilot study in a similar population with suitable controls, four differentially expressed miRNAs namely miR-24-2, miR-192-5p, miR-3609, and miR-664b-3p were considered to be validated in this study. The expression of these four miRNAs was examined by qRT-PCR, and their association with response to chemotherapy was analyzed.

RESULT

 A significant change in the expression of miR-192-5p was found in responders (p = 0.001) over a period of seven cycles and the difference between the expression of miR-24-2 from baseline to the seventh cycle of NAC was higher in responders while compared to the non-responders (p < 0.05).

CONCLUSION

miR-192-5p and miR-24-2 were identified as predictive biomarkers for response to NAC in south Indian patients with LABC.

Cellulose Nanofibrils of High Immunoaffinity for Efficient Enrichment of Small Extracellular Vesicles

Extracellular vesicles (EVs), crucial in facilitating the transport of diverse molecular cargoes for intercellular communication, have shown great potential in diagnostics, therapeutics, and drug delivery. The challenge of developing effective preparation methods for EVs is heightened by their intrinsic heterogeneity and complexity. Here, a novel strategy for high EV enrichment is developed by utilizing EV-affinitive-modified cellulose nanofibrils. Specifically, modified cellulose with rich carboxyl groups has outstanding dispersing properties, able to be dispersed into cellulose nanofibrils in solution. These cellulose nanofibrils are utilized as scaffolds for the immobilization of EV-affinitive antibody of CD63 by chemical conjugation. The CD63-modified nanofibrils demonstrate a superior EV capture efficiency of 86.4% compared with other reported methods. The high performance of this system is further validated by the efficient capture of EVs from biological blood plasma, allowing the detection of bioactive markers from EV-derived miRNAs and proteins. The authors envision that these modified cellulose nanofibrils of enhanced capability on EV enrichment will open new avenues in various biomedical applications.

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics

INTRODUCTION

Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment.

CONTENT

In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack.

SUMMARY AND OUTLOOK

We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Association of microRNA-21 expression with breast cancer subtypes and its potential as an early biomarker

Breast cancer has become the most diagnosed cancer worldwide in 2020 with high morbidity and mortality rates. The alarming increase in breast cancer incidence has sprung many researchers to focus on developing novel screening tests to identify early breast cancer which will allow clinicians to provide timely and effective treatments. With much evidence supporting the notion that the deregulation of miRNAs (a class of non-coding RNA) greatly contributes to cancer initiation and progression, the promising role of miRNAs as cancer biomarkers is gaining traction in the research world. Among the upregulated miRNAs identified in breast carcinogenesis, miR-21 was shown to be significantly expressed in breast cancer tissues and bodily fluids of breast cancer patients. Therein, this review paper aims to provide an overview of breast cancer, the role and significance of miR-21 in breast cancer pathogenesis, and its potential as a breast cancer biomarker. The paper also discusses the current types of tumor biomarkers and their limitations, the presence of miR-21 in extracellular vesicles and plasma, screening methods available for miRNA detection along with some challenges faced in developing diagnostic miR-21 testing for breast cancer to provide readers with a comprehensive outlook based on using miR-21 in clinical settings.

A smartphone-based electrochemical POCT for CEA based on signal amplification of Zr6MOFs

Carcinoembryonic antigen (CEA) is a biomarker of high expression in cancer cells. Highly sensitive and selective detection of CEA holds significant clinical value in the diagnosis, monitoring and efficacy evaluation of malignant tumors. In this work, a smartphone-based electrochemical point-of-care testing (POCT) platform for the detection of CEA was developed based on a Zr6MOF signal amplification strategy. Ferrocene labeled DNA strands (Fc-DNA) were immobilized on Zr6MOFs to form a Fc-DNA/Zr6MOF signal probe. Double-stranded DNA (dsDNA) formed by complementary DNA (cDNA) and CEA aptamer was assembled on a screen-printed electrode via an Au-S bond. When CEA was added, the aptamer specifically bound with CEA, resulting in the exposure of cDNA. Then, Fc-DNA/Zr6MOF signal probes were introduced on the electrode surface through hybridization between Fc-DNA and cDNA. The detection of CEA was realized by measuring the electrochemical response of Fc. The POCT device was made by connecting a modified electrode with a smartphone through a Sensit Smart USB flash disk. Due to the signal amplification of Zr6MOFs, this POCT platform exhibited high sensitivity, wide linear range, and low detection limit for CEA detection. The developed POCT platform has been used for the detection of CEA in actual human serum samples with satisfactory results.

Achieving enhanced sensitivity and accuracy in carcinoembryonic antigen (CEA) detection as an indicator of cancer monitoring using thionine/chitosan/graphene oxide nanocomposite-modified electrochemical immunosensor

The current study has focused on electrochemical immunosensing of carcinoembryonic antigen (CEA) employing an immobilized antibody on a thionine, chitosan, or graphene oxide nanocomposite modified glassy carbon electrode (anti-CEA/THi-CS-GO/GCE) as an indicator of cancer monitoring. THi-CS-GO nanocomposites were made using ultrasonication, and analyses of their morphology and crystal structure using SEM, FTIR, and XRD showed that thionine and chitosan molecules were intercalated with stacking interactions with both the top and bottom of GO nanosheets. Electrochemical experiments revealed anti-CEA, THi-CS-GO/GCE to have exceptional sensitivity and selectivity towards CEA compounds. The detection limit value was established to be 0.8 pg/mL when it was discovered that variations in the decrease peak current were directly proportional to the logarithm concentration of CEA over a wide range from 10-3 to 104 ng/mL. Results of testing the immunosensor's application capability for detecting CEA in a sample of human serum show that ELISA and DPV results are very congruent. The produced immunosensor demonstrated adequate immunosensor precision in determining CEA in prepared genuine samples of human serum and clinical applications.

Shape complementarity processes for ultrashort-burst sensitive M13-PEG-WS2-powered MCF-7 cancer cell sensors

Biomarkers have the potential to be utilized in disease diagnosis, prediction and monitoring. The cancer cell type is a leading candidate for next-generation biomarkers. Although traditional digital biomolecular sensor (DBS) technology has shown to be effective in assessing cell-based interactions, low cell-population detection of cancer cell types is extremely challenging. Here, we controlled the electrical signature of a two-dimensional (2D) nanomaterial, tungsten disulfide (WS2), by utilizing a combination of the Phage-integrated Polymer and the Nanosheet (PPN), viz., the integration of the M13-conjugated polyethylene glycol (PEG) and the WS2, through shape-complementarity phenomena, and developed a sensor system, i.e., the Phage-based DBS (P-DBS), for the specific, rapid, sensitive detection of clinically-relevant MCF-7 cells. The P-DBS attains a detection limit of 12 cells per μL, as well as a contrast of 1.25 between the MCF-10A sample signal and the MCF-7 sample signal. A reading length of 200 μs was further achieved, along with a relative cell viability of ∼100% for both MCF-7 and MCF-10A cells and with the PNN. Atomistic simulations reveal the structural origin of the shape complementarity-facilitated decrease in the output impedance of the P-DBS. The combination of previously unreported exotic sensing materials and digital sensor design represents an approach to unlocking the ultra-sensitive detection of cancer cell types and provides a promising avenue for early cancer diagnosis, staging and monitoring.

Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning

Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models were developed to estimate the risk of site-specific DM following local-regional therapy. This retrospective study cohort included 175 patients diagnosed with invasive BC who later developed DM. Clinicopathological information was collected for analysis. Outcome variables were the first site of metastasis (brain, bone or visceral) and the time interval (months) to developing DM. Multivariate statistical analysis and ML-based multivariable gradient boosting machines identified factors associated with these outcomes. Machine learning models predicted the site of DM, demonstrating an area under the curve of 0.74, 0.75, and 0.73 for brain, bone and visceral sites, respectively. Overall, most patients (57%) developed bone metastases, with increased odds associated with estrogen receptor (ER) positivity. Human epidermal growth factor receptor-2 (HER2) positivity and non-anthracycline chemotherapy regimens were associated with a decreased risk of bone DM, while brain metastasis was associated with ER-negativity. Furthermore, non-anthracycline chemotherapy alone was a significant predictor of visceral metastasis. Here, clinicopathologic and treatment variables used in ML prediction models predict the first site of metastasis in BC. Further validation may guide focused patient-specific surveillance practices.

Obesity Associated with Prediabetes Increases the Risk of Breast Cancer Development and Progression-A Study on an Obese Rat Model with Impaired Glucose Tolerance

Patients with comorbidities of obesity and diabetes are recognized to be at high risk of breast cancer development and face worse breast cancer outcomes. Though several reports showed the reinforced link between obesity, diabetes, and prediabetes with breast cancer, the underlying molecular mechanisms are still unknown. The present study aimed to investigate the underlying molecular link between increased risks of breast cancer due to coincident diabetes or obesity using a spontaneous obese rat model with impaired glucose tolerance (WNIN/GR-Ob rat). A single dose of solubilized DMBA suspension (40 mg/kg body weight) was orally administered to the animals at the age of 60 days to induce breast tumors. The tumor incidence, latency period, tumor frequency, and tumor volume were measured. Histology, immunohistochemistry, and immunoblotting were performed to evaluate the tumor morphology and expression levels of signal molecules. The development of mammary tumors in GR-Ob rats was characterized by early onset and shorter latency periods compared to control lean rats. While 62% of obese rats developed breast tumors, tumor development in lean rats was only 21%. Overexpression of ER, PR, Ki67, and p53 markers was observed in tumor tissues of obese rats in comparison with lean rats. The levels of the hallmarks of cell proliferation and angiogenesis involved in IGF-1/PI3K/Akt/GSK3β/β-catenin signaling pathway molecules were upregulated in obese rat breast tumors compared to lean rats. Furthermore, obesity with prediabetes is associated with changes in IGF-1 signaling and acts on PI3K/Akt/GSK3β/β-catenin signaling, which results in rapid cell proliferation and development of breast tumors in obese rats than the lean rats. These results indicate that tumor onset and development were faster in spontaneous obese rat models with impaired glucose tolerance than in their lean counterparts.

Vaccines in Breast Cancer: Challenges and Breakthroughs

Breast cancer is a problem for women's health globally. Early detection techniques come in a variety of forms ranging from local to systemic and from non-invasive to invasive. The treatment of cancer has always been challenging despite the availability of a wide range of therapeutics. This is either due to the variable behaviour and heterogeneity of the proliferating cells and/or the individual's response towards the treatment applied. However, advancements in cancer biology and scientific technology have changed the course of the cancer treatment approach. This current review briefly encompasses the diagnostics, the latest and most recent breakthrough strategies and challenges, and the limitations in fighting breast cancer, emphasising the development of breast cancer vaccines. It also includes the filed/granted patents referring to the same aspects.

Quantitative analysis of serum cell-free DNA as a predictive and prognostic marker in breast cancer patients

Introduction

According to the GLOBOCAN (Global Cancer Observatory) 2020 report, 13,028 new cases of breast cancer (19%) were diagnosed in the United States, and 6,783 of them succumbed to the disease, making it the most common cancer among women. The clinical stage at the time of diagnosis is one of the most significant survival predictors in breast cancer. With delayed illness detection comes a lower survival rate. The prognosis of breast cancer may be predicted using circulating cell-free DNA (cfDNA), a non-invasive diagnosis technique.

Objective

This study aimed to determine the most sensitive and effective method for detecting changes in cfDNA levels and for using cfDNA as a diagnostic and prognostic marker of breast cancer.

Methods

The potential function of serum cfDNA levels as a marker for early breast cancer diagnosis was investigated using UV spectrophotometric, fluorometric, and real-time qPCR assays.

Results

This research suggests that the most successful way to measure the amount of cfDNA described decades ago could be used as a "liquid biopsy" to track cancer in real time. The RT-qPCR (ALU115) method produced the most statistically significant results (p=0.000). At the threshold concentration of 395.65 ng/ml of cfDNA, the ROC curve reflects the maximum AUC= 0.7607, with a sensitivity of 0.65 and specificity of 0.80.

Conclusion

For a preliminary assessment of total circulating cfDNA, a combination of all of the above techniques will be most efficacious. Based on our results, we conclude that the RT-qPCR technique combined with fluorometric measurement can identify a statistically significant difference in cfDNA levels between cohorts of breast cancer patients and healthy controls.

CXC ELR-Positive Chemokines as Diagnostic and Prognostic Markers for Breast Cancer Patients

As the most common type of malignant lesison, breast cancer is a leading challenge for clinicians. Currently, diagnosis is based on self-examination and imaging studies that require confirmation by tissue biopsy. However, there are no easily accessible diagnostic tools that can serve as diagnostic and prognostic markers for breast cancer patients. One of the possible candidates for such markers is a group of chemokines that are closely implicated in each stage of tumorigenesis. Many researchers have noted the potential of this molecule group to become tumor markers and have tried to establish their clinical utility. In this work, we summarize the results obtained by scientists on the usefulness of the ELR-positive CXC group of chemokines in ancillary diagnosis of breast cancer.

Reagentless Electrochemical Detection of Tumor Biomarker Based on Stable Confinement of Electrochemical Probe in Bipolar Silica Nanochannel Film

The development of simple and probe-integrated aptamer sensors for the electrochemical detection of tumor biomarkers is of great significance for the diagnosis of tumors and evaluation of prognosis. In this work, a probe-integrated aptamer sensor is demonstrated based on the stable confinement of an electrochemical probe in a bipolar nanochannel film, which can realize the reagentless electrochemical detection of the tumor biomarker carcinoembryonic antigen (CEA). To realize the stable immobilization of a large amount of the cationic electrochemical probe methylene blue (MB), a two-layer silica nanochannel array (SNF) with asymmetric charge was grown on the supporting electrode from bipolar SNF (bp-SNF). The inner SNF is negatively charged (n-SNF), and the outer-layer SNF is positively charged (p-SNF). The dual electrostatic interaction including the electrostatic adsorption from n-SNF and the electrostatic repulsion from p-SNF achieve the stable confinement of MB in bp-SNF. The recognitive interface is fabricated by the covalent immobilization of the CEA aptamer on the outer surface of bp-SNF, followed by the blocking of non-specific binding sites. Owing to the stable and abundant immobilized probes and highly specific aptamer interface, the developed aptamer sensor enables the sensitive detection of CEA in the range of 1 pg/mL to 1 μg/mL with a low limit of detection (LOD, 0.22 pg/mL, S/N = 3). Owing to the high selectivity and stability of the developed biosensor, reagentless electrochemical detection of CEA in serum was realized.

A Comprehensive Review on Electrochemical Nano Biosensors for Precise Detection of Blood-Based Oncomarkers in Breast Cancer

Breast cancer (BC), one of the most common and life-threatening cancers, has the highest incidence rate among women. Early diagnosis of BC oncomarkers is considered the most effective strategy for detecting and treating BC. Finding the type and stage of BC in women as soon as possible is one of the greatest ways to stop its incidence and negative effects on medical treatment. The development of biosensors for early, sensitive, and selective detection of oncomarkers has recently attracted much attention. An electrochemical nano biosensor (EN) is a very suitable option for a powerful tool for cancer diagnosis. This comprehensive review provides information about the prevalence and pathobiology of BC, recent advances in clinically available BC oncomarkers, and the most common electrochemical nano biosensors for point-of-care (POC) detection of various BC oncomarkers using nanomaterial-based signal amplification techniques.

Carbohydrate polymer-based nanocomposites for breast cancer treatment

Breast cancer is known as the most common invasive malignancy in women with the highest mortality rate worldwide. This concerning disease may be presented in situ (relatively easier treatment) or be invasive, especially invasive ductal carcinoma which is highly worrisome nowadays. Among several strategies used in breast cancer treatment, nanotechnology-based targeted therapy is currently being investigated, as it depicts advanced technological features able of preventing drugs' side effects on normal cells while effectively acting on tumor cells. In this context, carbohydrate polymer-based nanocomposites have gained particular interest among the biomedical community for breast cancer therapy applications due to their advantage features, including abundance in nature, biocompatibility, straightforward fabrication methods, and good physicochemical properties. In this review, the physicochemical properties and biological activities of carbohydrate polymers and their derivate nanocomposites were discussed. Then, various methods for the fabrication of carbohydrate polymer-based nanocomposites as well as their application in breast cancer therapy and future perspectives were discussed.

The Role of 68 Ga-FAPI PET/CT in Detection of Metastatic Lobular Breast Cancer

PURPOSE

Invasive lobular breast cancer (ILC) may be hard to detect using conventional imaging modalities and usually shows less avidity to 18 F-FDG PET/CT. 68 Ga-fibroblast activation protein inhibitor (FAPI) PET/CT has shown promising results in detecting non- 18 F-FDG-avid cancers. We aimed to assess the feasibility of detecting metastatic disease in patients with non- 18 F-FDG-avid ILC.

METHODS

This prospective study included patients with metastatic ILC, infiltrative to soft tissues, which was not 18 F-FDG avid. The patients underwent 68 Ga-FAPI PET/CT for evaluation, which was correlated with the fully diagnostic CT performed at the same time.

RESULTS

Seven women (aged 57 ± 10 years) were included. Among the 30 organs and structures found to be involved by tumor, the number of findings observed by FAPI PET/CT was significantly higher than that observed by CT alone ( P = 0.022), especially in infiltrative soft tissue and serosal locations.

CONCLUSIONS

This small pilot trial suggests a role for 68 Ga-FAPI PET/CT in ILC, which needs to be confirmed by subsequent trials.

A sensitive electrochemiluminescence immunosensor for the detection of CA15-3 based on CeO2/Pt/rGO as a novel co-reaction accelerator

In this work, we successfully constructed a label-free electrochemiluminescence (ECL) immunosensor for the detection of breast cancer marker antigen (CA15-3). In particular, 3,4,9,10-perylenetetracarboxylic acid (PTCA) is cleverly attached to the surface of silica spheres as a luminophore (NH₂-SiO₂-PTCA), which greatly alleviates the disadvantage of PTCA anti-induced aggregated luminescence and improves the ECL performance. Furthermore, Pt nanoparticles were used to dope CeO₂ and introducing reduced graphene oxide (rGO) to prepare CeO₂/Pt/rGO composites as a novel co-reaction accelerator. Among them, Pt nanoparticles were used to improve the electrical conductivity of CeO₂, and the use of rGO as a substrate allows for a more uniform dispersion of CeO₂ to increase the catalytic surface area, which effectively improves the performance of the co-reaction accelerator and thus increasing the ECL intensity of the PTCA/S₂O₈^2- system. Under the optimal conditions, the designed ECL immunosensor showed satisfactory results in the determination of CA15-3 with a linear range of 12.00 mU mL^-1 - 120.00 U mL^-1 and a low detection limit of 1.348 mU mL^-1. Importantly, the resulting biosensor has good stability, high sensitivity and reliable reproducibility, suggesting its potential application in clinical research.

Carcinoembryonic Antigen, Carbohydrate Antigen 19-9, Cancer Antigen 125, Prostate-Specific Antigen and Other Cancer Markers: A Primer on Commonly Used Cancer Markers

Cancer markers are molecules produced by cancer cells which may serve to identify the presence of cancer. Cancer markers can be differentiated as serum-based, radiology-based and tissue-based, and are one of the most important tools in diagnosing, staging and monitoring of treatment of many cancers. The most used cancer markers are serum cancer markers due to its relative ease and lower cost of testing. However, serum cancer markers have poor mass screening utilization due to poor positive predictive value. Several markers such as prostate-specific antigen (PSA), beta-human chorionic gonadotropin (B-hCG), alpha-fetoprotein (AFP), and lactate dehydrogenase (LDH) are used to aid in diagnosis of cancer in cases of high suspicion. Serum markers such as carcinoembryonic antigen (CEA), AFP, carbohydrate antigen 19-9 (CA 19-9), and 5-hydroxyindoleacetic acid (5-HIAA) play a significant role in assessing disease prognosis as well as response to treatment. This work reviews the role of some of the biomarkers in the diagnosis and treatment of cancer.

Detection of IL-1β, VEGF and IL-4 with their novel genetic variations in breast cancer patients

Interleukin-1β (IL-1β), vascular endothelial growth factor (VEGF), and IL-4 serum levels and new genetic mutations in breast cancer (BC) patients were assessed in the current study. The serum levels of the examined cytokines in 40 BC patients and 40 control subjects were assessed using the ELISA technique. In order to identify genotype variants of the IL-1β, IL-4, and VEGF genes in 40 Formalin Fixed Paraffin Embedded (FFPE) samples with BC and 10 FFPE samples from healthy women's breast tissue, Sanger sequencing was used. According to this study, BC patients had significantly lower serum concentrations of IL-4 and significantly higher quantities of the tumor markers, CA15-3, IL-1β, and VEGF. In terms of genotype alterations, a total of 21 mutations in three trialed genes (eight in IL-1β, 10 in IL-4, and three in VEGF) were found in BC patients. The results of the current investigation suggested that angiogenesis and the development of BC may be significantly influenced by the genetic differences and higher levels of the examined cytokines.

CA 15-3, CRP, and LDH correlates with prognostic parameters in canine mammary neoplasms

The identification of putative prognostic factors in canine mammary neoplasms (CMNs) has been focused on tissue-specific biomarkers, but the serum biomarkers, including cancer antigen 15-3 (CA 15-3), c-reactive protein (CRP), and lactate dehydrogenase (LDH) have been demonstrated to display clinical application in cases of CMNs. The aim of the study was to evaluate the levels of these serum biomarkers and their association with well-established prognostic factors in CMNs. Samples from 15 female canines with CMNs and 15 clinically healthy ones were collected. The results were evaluated using the Tukey's, Pearson, or Spearman tests. The cut-off point, sensitivity, specificity, and area under curve (AUC) were evaluated using the receiver operating characteristic (ROC) curve analysis in a logistic regression model (P<0.05). The levels of CA 15-3, CRP and LDH were significantly higher in the serum of female dogs with CMNs compared to the healthy ones. Moreover, these factors were positively correlated with ulceration, tumor size, histopathological grade, metastatic lymph node, and clinical staging. Female dogs with CMNs were found to exhibit highest serum levels of CA 15-3, CRP, and LDH. Therefore, they can be applied to improve the efficacy of the diagnosis and prognostic evaluation in casas of CMNs.

Non-steroidal anti-inflammatory drugs and biomarkers: A new paradigm in colorectal cancer

Colorectal cancer is a sporadic, hereditary, or familial based disease in its origin, caused due to diverse set of mutations in large intestinal epithelial cells. Colorectal cancer (CRC) is a common and deadly disease that accounts for the 4^th worldwide highly variable malignancy. For the early detection of CRC, the most common predictive biomarker found endogenously are KRAS and ctDNA/cfDNA along with SEPT9 methylated DNA. Early detection and screening for CRC are necessary and multiple methods can be employed to screen and perform early diagnosis of CRC. Colonoscopy, an invasive method is most prevalent for diagnosing CRC or confirming the positive result as compared to other screening methods whereas several non-invasive techniques such as molecular analysis of breath, urine, blood, and stool can also be performed for early detection. Interestingly, widely used medicines known as non-steroidal anti-inflammatory drugs (NSAIDs) to reduce pain and inflammation have reported chemopreventive impact on gastrointestinal malignancies, especially CRC in several epidemiological and preclinical types of research. NSAID acts by inhibiting two cyclooxygenase enzymes, thereby preventing the synthesis of prostaglandins (PGs) and causing NSAID-induced apoptosis and growth inhibition in CRC cells. This review paper majorly focuses on the diversity of natural and synthetic biomarkers and various techniques for the early detection of CRC. An approach toward current advancement in CRC detection techniques and the role of NSAIDs in CRC chemoprevention has been explored systematically. Several prominent governing mechanisms of the anti-cancer effects of NSAIDs and their synergistic effect with statins for an effective chemopreventive measure have also been discussed in this review paper.

Mesenchymal-endothelial nexus in breast cancer spheroids induces vasculogenesis and local invasion in a CAM model

Interplay between non-cancerous cells (immune, fibroblasts, mesenchymal stromal cells (MSC), and endothelial cells (EC)) has been identified as vital in driving tumor progression. As studying such interactions in vivo is challenging, ex vivo systems that can recapitulate in vivo scenarios can aid in unraveling the factors impacting tumorigenesis and metastasis. Using the synthetic tumor microenvironment mimics (STEMs)-a spheroid system composed of breast cancer cells (BCC) with defined human MSC and EC fractions, here we show that EC organization into vascular structures is BC phenotype dependent, and independent of ERα expression in epithelial cancer cells, and involves MSC-mediated Notch1 signaling. In a 3D-bioprinted model system to mimic local invasion, MDA STEMs collectively respond to serum gradient and form invading cell clusters. STEMs grown on chick chorioallantoic membrane undergo local invasion to form CAM tumors that can anastomose with host vasculature and bear the typical hallmarks of human BC and this process requires both EC and MSC. This study provides a framework for developing well-defined in vitro systems, including patient-derived xenografts that recapitulate in vivo events, to investigate heterotypic cell interactions in tumors, to identify factors promoting tumor metastasis-related events, and possibly drug screening in the context of personalized medicine.

Chondroitin Sulfate Proteoglycan 4 as a Marker for Aggressive Squamous Cell Carcinoma

Chondroitin sulfate (CS) proteoglycan 4 (CSPG4) is a cell surface proteoglycan that is currently under investigation as a marker of cancer malignancy, and as a potential target of anticancer drug treatment. CSPG4 acts as a driver of tumourigenesis by regulating turnover of the extracellular matrix (ECM) to promote tumour cell invasion, migration as well as inflammation and angiogenesis. While CSPG4 has been widely studied in certain malignancies, such as melanoma, evidence is emerging from global gene expression studies, which suggests a role for CSPG4 in squamous cell carcinoma (SCC). While relatively treatable, lack of widely agreed upon diagnostic markers for SCCs is problematic, especially for clinicians managing certain patients, including those who are aged or infirm, as well as those with underlying conditions such as epidermolysis bullosa (EB), for which a delayed diagnosis is likely lethal. In this review, we have discussed the structure of CSPG4, and quantitatively analysed CSPG4 expression in the tissues and pathologies where it has been identified to determine the usefulness of CSPG4 expression as a diagnostic marker and therapeutic target in management of malignant SCC.

Early and isolated breast cancer metastasis to the pituitary: A case report and systematic review

Background:

Pituitary metastases (PMs) arising from breast cancer tend to occur many years following initial diagnosis, and after other systemic metastasis have been identified. Survival is generally considered to be poor. However, there are cases where patients present with an isolated metastatic lesion in the pituitary. Survival in this subset of patients has not been evaluated. We present a case of isolated PM that presented two years after initial diagnosis of breast cancer. We performed a systematic review of 38 breast cancer patients with PM. We report presentation, treatment strategy, and outcomes of breast cancer metastasis to the pituitary and highlight cases of isolated PM.

Case Description:

A 39 year old female presented with complaints of headache and polydipsia two years after diagnosis with breast cancer. Systemic workup was unremarkable, but brain imaging identified an isolated PM. Transsphenoidal debulking was performed with adjuvant radiation therapy (RT) targeted to the sellar region. Unfortunately, she passed away 9 months later from systemic progression.

Conclusion:

A total of 38 patients were included systematic review. Of these, 13 had isolated PM. Prevalent signs/ symptoms included visual disturbance, diabetes insipidus (DI), and hypothalamic dysfunction. Patients treated with surgical resection and adjuvant chemotherapy (ChT), or RT had better survival than those treated with resection alone. Patients that receive treatment for isolated PM may survive for many years without progression or recurrence.

Surface modified Genistein phytosome for Breast Cancer Treatment: In-vitro Appraisal, Pharmacokinetics, and In-vivo Antitumor Efficacy

Based on phytosomes advantages over liposomes, hyaluronic acid (HA) with/out pegylated phospholipid was used to develop surface-modified genistein (Gen) phytosome as Gen pegylated hyaluophytosomes (G-PHA) and Gen hyaluophytosomes (G-HA) as novel delivery systems for breast cancer treatment. In this study, in-vitro characterization of G-HA and G-PHA shows PS 144.2 ±1.266 nm and 220.3 ±2.51 nm, ZP -30.9 ±0.75 and -32.06 ±0.305 respectively. Morphological elucidation shows HA covers the surface of G-HA and the presence of a transparent layer of PEG surrounding G-PHA. In-vitro release shows a significant slow Gen release from G-HA, and G-PHA compared to Gen solution and Gen phytosomes. In-vivo bioavailability data shows improvement in bioavailability for G-HA and G-PHA compared to Gen suspension (AUC_0- T: :3.563 ±0.067, 2.092 ±0.058, 0.374 ±0.085 µg/ml*h respectively). Therapeutic evaluation of the prepared targeted formulations was carried out by subcutaneous injection in an EAC-induced breast cancer model in mice. G-HA and G-PHA show a promising chemotherapeutic effect in terms of lowering the tumor size and tumor biomarkers (CEA: -34.6, -44.7 & CA15.3: -77.8, -81.6 respectively). This reduction in their values compared to Gen phytosomes, Gen suspension, and the control group is attributed to high Gen accumulation at the target organ owing to targeting properties of HA that are used in phytosomal surface modification in G-HA. Additionally, the presence of MPEG₂₀₀₀-DSPE in G-PHA tends to improve interstitium lymphatic drainage following SC administration, resulting in maximizing the therapeutic benefits of breast cancer despite the difference in pharmacokinetics behavior compared to G-HA. These formulations can be further studied for metastatic breast cancer.

Gene expressions and their significance in organoid cultures obtained from breast cancer patient-derived biopsies

Gene expression changes are one of the hallmarks of malignant cells and such changes in specific genes have been identified for a variety of human cancers. Such an association in gene expression changes becomes very significant for breast cancers due to the genetic heterogeneity seen in such cancers. It is due to such genetic implication that breast cancers are classified into several subtypes; based on the expression and the magnitude of expression of estrogen and progesterone receptor genes. Changes in the expression of ERBB2, ESR1, PLAU, MUC1, PGR, and TP53 are implicated in breast cancers. Of the various models available for cancer research, organoid cultures from patient-derived biopsies are being considered as the most relevant for invitro testing. Organoid cultures derived from patient biopsies mitigate several limitations of other commonly available models such as cancer cell lines. Such organoids retain the functional physiology of solid tumors which include gene expression. Also, utilizing patient derived organoids for in vitro testing paves way for personalized medicine which greatly enhances the effectiveness of cancer therapy for individuals. We present the genes implicated in breast cancers, the ways in which organoids can be derived from breast cancer biopsies and their applications for gene expression studies.

New quinoxalin-2(1H)-one-derived VEGFR-2 inhibitors: Design, synthesis, in vitro anticancer evaluations, in silico ADMET, and docking studies

More than 70% of cancer patients who are treated with chemotherapeutics do not show a durable response. As part of the global plan seeking new effective chemotherapeutics, here, we report the synthesis and in vitro and computational studies of new lenvatinib and sorafenib analog quinoxalines as vascular endothelial growth factor receptor II (VEGFR-2) tyrosine kinase inhibitors. The central quinolone and pyridine moieties of the Food and Drug Administration-approved anticancer agents lenvatinib and sorafenib were replaced with the versatile quinoxaline scaffold that has been exploited for developing potent cytotoxic agents. With some minor structural optimizations, all the other pharmacophoric features of lenvatinib and sorafenib were maintained. Accordingly, three new sets of quinoxalines were synthesized to evaluate their activity against liver, colorectal, and breast malignancies. The results obtained in the in vitro cytotoxicity evaluation study revealed the superior activity of three derivatives (20, 25, and 29) compared with that of doxorubicin and sorafenib. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling and docking of 20, 25, and 29 into the VEGFR-2 receptor were also performed. Results of in silico studies showed the potential of the designed compounds to bind effectively with a number of key residues. The obtained in vitro cytotoxic activity and ADMET profiles of compounds 20, 25, and 29 suggested that they should be subjected to further structural optimizations to develop new candidates in cancer treatment protocols.

AKR1B10 as a Potential Novel Serum Biomarker for Breast Cancer: A Pilot Study

Background

Aldo-keto reductase 1B10 (AKR1B10) is a secretory protein that is upregulated in breast cancer.

Objective

This case-controlled pilot study evaluated the serum level of AKR1B10 in healthy women and patients with a localized or metastatic breast cancer.

Methods

AKR1B10 levels were measured by ELISA and IHC in several patient cohorts.

Results

Our data showed that serum AKR1B10 was significantly elevated in patients with localized (6.72 ± 0.92 ng/ml) or metastatic (7.79 ± 1.13 ng/ml) disease compared to cancer-free healthy women (1.69 ± 0.17 ng/ml) (p<0.001); the serum AKR1B10 was correlated with its expression in tumor tissues, but not with the tumor burden, molecular subtypes or histological stages. After surgical removal of primary tumors, the serum AKR1B10 was rapidly decreased within 3 days and plateaued at a level similar to that of healthy controls in most patients. ROC curve analysis suggested the optimal diagnostic cut-off value of serum AKR1B10 at 3.456 ng/ml with AUC 0.9045 ± 0.0337 (95% CI 0.8384 - 0.9706), sensitivity 84.75% (95% CI 73.01% to 92.78%), and specificity 93.88% (95% CI 83.13% to 98.72%).

Conclusions

These data indicate the potential value of serum AKR1B10 as a biomarker of breast cancer.

Expression of Stanniocalcin-1 as a Predictor of Recurrence in Breast Cancer Patients

Introduction: About 40% of breast cancer patients will experience a recurrence and the life expectancy will decrease from 95% to 40%. Stanniocalcin-1 is a biomarker that is thought to have potential as a risk factor for recurrence. Objective: To determine the role of Stanniocalcin-1 (STC1) expression as a risk factor for recurrence in breast cancer patients. Methods: Cross sectional observational study on breast cancer patients, assessed the clinicopathological character and seen whether the patient's condition had a recurrence. Immunohistochemical staining with STC1 antibody was performed on the patient's paraffin block. Reading of immunohistochemical preparations using the Allred score method by looking at 5 fields of view. Data analysis regarding the relationship between STC1 and recurrence was carried out using the Chi-Square test or Fisher's Exact test, then Logistic regression analysis was performed to determine the significant relationship between risk factors for recurrence. Results: Expression of STC1 was significantly different in patients who had recurrence and who did not experience recurrence (p= 0.000). There was a significant relationship between STC1 expression with age, tumor size, lymph node status, type of cancer, estrogen receptor status and stage at diagnosis. (p<0.005). Conclusion: It can be concluded that STC1 has a strong relationship with recurrence, so it has the potential to be used as a predictor of recurrence in breast cancer.

Detection of breast cancer by ATR-FTIR spectroscopy using artificial neural networks

In this study, three (3) neural networks (NN) were designed to discriminate between malignant (n = 78) and benign (n = 88) breast tumors using their respective attenuated total reflection Fourier transform infrared (ATR-FTIR) spectral data. A proposed NN-based sensitivity analysis was performed to determine the most significant IR regions that distinguished benign from malignant samples. The result of the NN-based sensitivity analysis was compared to the obtained results from FTIR visual peak identification. In training each NN models, a 10-fold cross validation was performed and the performance metrics-area under the curve (AUC), accuracy, positive predictive value (PPV), specificity rate (SR), negative predictive value (NPV), and recall rate (RR)-were averaged for comparison. The NN models were compared to six (6) machine learning models-logistic regression (LR), Naïve Bayes (NB), decision trees (DT), random forest (RF), support vector machine (SVM) and linear discriminant analysis (LDA)-for benchmarking. The NN models were able to outperform the LR, NB, DT, RF, and LDA for all metrics; while only surpassing the SVM in accuracy, NPV and SR. The best performance metric among the NN models was 90.48% ± 10.30% for AUC, 96.06% ± 7.07% for ACC, 92.18 ± 11.88% for PPV, 94.19 ± 10.57% for NPV, 89.04% ± 16.75% for SR, and 94.34% ± 10.54% for RR. Results from the proposed sensitivity analysis were consistent with the visual peak identification. However, unlike the FTIR visual peak identification method, the NN-based method identified the IR region associated with C-OH C-OH group carbohydrates as significant. IR regions associated with amino acids and amide proteins were also determined as possible sources of variability. In conclusion, results show that ATR-FTIR via NN is a potential diagnostic tool. This study also suggests a possible more specific method in determining relevant regions within a sample's spectrum using NN.

Nanotechnology-based approaches for effective detection of tumor markers: A comprehensive state-of-the-art review

As well-appreciated biomarkers, tumor markers have been spotlighted as reliable tools for predicting the behavior of different tumors and helping clinicians ascertain the type of molecular mechanism of tumorigenesis. The sensitivity and specificity of these markers have made them an object of even broader interest for sensitive detection and staging of various cancers. Enzyme-linked immunosorbent assay (ELISA), fluorescence-based, mass-based, and electrochemical-based detections are current techniques for sensing tumor markers. Although some of these techniques provide good selectivity, certain obstacles, including a low sample concentration or difficulty carrying out the measurement, limit their application. With the advent of nanotechnology, many studies have been carried out to synthesize and employ nanomaterials (NMs) in sensing techniques to determine these tumor markers at low concentrations. The fabrication, sensitivity, design, and multiplexing of sensing techniques have been uplifted due to the attractive features of NMs. Various NMs, such as magnetic and metal nanoparticles, up-conversion NPs, carbon nanotubes (CNTs), carbon-based NMs, quantum dots (QDs), and graphene-based nanosensors, hyperbranched polymers, optical nanosensors, piezoelectric biosensors, paper-based biosensors, microfluidic-based lab-on-chip sensors, and hybrid NMs have proven effective in detecting tumor markers with great sensitivity and selectivity. This review summarizes various categories of NMs for detecting these valuable markers, such as prostate-specific antigen (PSA), human carcinoembryonic antigen (CEA), alpha-fetoprotein (AFP), human chorionic gonadotropin (hCG), human epidermal growth factor receptor-2 (HER2), cancer antigen 125 (CA125), cancer antigen 15-3 (CA15-3, MUC1), and cancer antigen 19-9 (CA19-9), and highlights recent nanotechnology-based advancements in detection of these prognostic biomarkers.

The blood level of thioredoxin 1 as a supporting biomarker in the detection of breast cancer

BACKGROUND

There is a long-time unmet need for a means to detect breast cancer (BC) using blood. Although mammography is accepted as the gold standard for screening, a blood-based diagnostic can complement mammography and assist in the accurate detection of BC in the diagnostic process period of early diagnosis. We have previously reported the possible use of thioredoxin 1 (Trx1) in serum as a novel means to detect BC. In the present study, we validated the clinical utility of Trx1 to identify BC by testing sera from biopsy-confirmed cancer patients and women without cancer.

METHODS

We have generated monoclonal antibodies against Trx1 and developed an ELISA kit that can quantitate Trx1 in sera. The level of Trx1 was determined in each serum from women without cancer (n = 114), as well as in serum from patients with BC (n = 106) and other types of cancers (n = 74), including cervical, lung, stomach, colorectal, and thyroid cancer. The sera from BC patients were collected and classified by the subjects' age and cancer stage. In addition to the Trx1 levels of BC patients, several pathological and molecular aspects of BC were analyzed. Test results were retrospectively compared to those from mammography. Each test was duplicated, and test results were analyzed by ROC analysis, one-way ANOVA tests, and unpaired t-tests.

RESULTS

The mean level of Trx1 from women without cancer was 5.45 ± 4.16 (±SD) ng/ml, that of the other malignant cancer patient group was 2.70 ± 2.01 ng/ml, and that from the BC group was 21.96 ± 6.79 ng/ml. The difference among these values was large enough to distinguish BC sera from non-BC control sera with a sensitivity of 97.17% and specificity of 94.15% (AUC 0.990, p < 0.0001). Most Trx1 levels from BC patients' sera were higher than the cut-off value of 11.4 ng/ml regardless of age, stage, histological grade, type, and specific receptors' expression profile of BC. The level of Trx1 could rescue women from most cases of misread or incomplete mammography diagnoses.

CONCLUSION

These results indicated that the blood level of Trx1 could be an effective and accurate means to assist the detection of BC during the early diagnosis period.

The issues and challenges with cancer biomarkers

A biomarker is a measurable indicator used to distinguish precisely/objectively either normal biological state/pathological condition/response to a specific therapeutic intervention. The use of novel molecular biomarkers within evidence-based medicine may improve the diagnosis/treatment of disease, improve health outcomes, and reduce the disease's socio-economic impact. Presently cancer biomarkers are the backbone of therapy, with greater efficacy and better survival rates. Cancer biomarkers are extensively used to treat cancer and monitor the disease's progress, drug response, relapses, and drug resistance. The highest percent of all biomarkers explored are in the domain of cancer. Extensive research using various methods/tissues is carried out for identifying biomarkers for early detection, which has been mostly unsuccessful. The quantitative/qualitative detection of various biomarkers in different tissues should ideally be done in accordance with qualification rules laid down by the Early Detection Research Network (EDRN), Program for the Assessment of Clinical Cancer Tests (PACCT), and National Academy of Clinical Biochemistry. Many biomarkers are presently under investigation, but lacunae lie in the biomarker's sensitivity and specificity. An ideal biomarker should be quantifiable, reliable, of considerable high/low expression, correlate with the outcome progression, cost-effective, and consistent across gender and ethnic groups. Further, we also highlight that these biomarkers' application remains questionable in childhood malignancies due to the lack of reference values in the pediatric population. The development of a cancer biomarker stands very challenging due to its complexity and sensitivity/resistance to the therapy. In past decades, the cross-talks between molecular pathways have been targeted to study the nature of cancer. To generate sensitive and specific biomarkers representing the pathogenesis of specific cancer, predicting the treatment responses and outcomes would necessitate inclusion of multiple biomarkers.

Recent advances in biological detection with rolling circle amplification: design strategy, biosensing mechanism, and practical applications

Rolling circle amplification (RCA) is a simple and isothermal DNA amplification technique that is used to generate thousands of repeating DNA sequences using circular templates under the catalysis of DNA polymerase.

Multiplexed analysis of small extracellular vesicle-derived mRNAs by droplet digital PCR and machine learning improves breast cancer diagnosis

Breast cancer has become the leading cause of global cancer incidence and a serious threat to women's health. Accurate diagnosis and early treatment are of great importance to prognosis. Although clinically used diagnostic approaches can be used for cancer screening, accurate diagnosis of breast cancer is still a critical unmet need. Here, we report a 4-plex droplet digital PCR technology for simultaneous detection of four small extracellular vesicle (sEV)-derived mRNAs (PGR, ESR1, ERBB2 and GAPDH) in combination with machine learning (ML) algorithms to improve breast cancer diagnosis. We evaluate the diagnsotic results with and without the assistance of the ML models. The results indicate that ML-assisted analysis exhibits higher diagnostic performance even using a single marker for breast cancer diagnosis, and demonstrate improved diagnostic performance under the best combination of biomarkers and suitable ML diagnostic model. Therefore, multiple sEV-derived mRNAs analysis coupled with ML not only provides the best combination of markers for breast cancer diagnosis, but also significantly improves the diagnostic efficiency of breast cancer.

Three-dimensional porous calcium alginate fluorescence bead-based immunoassay for highly sensitive early diagnosis of breast cancer

A sensitive biosensor capable of detecting trace concentrations of several cancer biomarkers in clinical samples is critical for early detection of cancer because different cancer biomarkers may be expressed at different stages of cancer. Previous multiplex studies using microarrays or color-coded beads had limited multiplex detection in a single well, and difficulty in optimizing and unifying the incubation parameters for all tests made in different wells had posed challenges to small sample size and lengthened assay time. Herein, we proposed a novel approach to achieve multiplex analysis on a single three-dimensional porous calcium alginate bead. Because of the high surface area to volume ratio of the calcium alginate immuno-bead, the sensitivity and linear dynamic range of the as-proposed multiplex analysis method are significantly improved. Based on the direct sandwich immunoassay principle, dual-capturing antibodies were encapsulated into a single 3D porous calcium alginate bead as a proof-of-concept for multiplexity detection of serum-HER2 and serum-CA125 breast cancer biomarkers. High sensitivity was attained, with LODs of 0.004 ng mL^-1 for serum HER2, and 0.005 U mL^-1 for serum CA125, both of which are below the clinical cutoff values, enabling for early breast cancer diagnosis. Stability tests revealed that the 3D immuno-beads were stable at 4 °C and room temperature (25 °C) for at least 14 days. Most importantly, the results obtained using the developed system were in good agreement with those obtained using standard methods while analyzing real clinical samples. In addition, the analysis required only approximately 30 min, which was much less time than typical ELISA techniques. When endogenous interferences were introduced, no cross-reactivity was observed. We anticipate this approach to be potentially used in the multiplex assays and biosensors.

Evaluating the therapeutic potential of white button mushroom (Agaricus bisporus) against DMBA-induced breast cancer in Sprague Dawley rats

The current research work was designed to investigate the protective effects of white button mushroom (Agaricus bisporus) against 7,12-dimethylbenz[a]anthracene (DMBA)-induced breast cancer. Breast cancer was induced in rats by the administration of a single dose of 50 mg/kg DMBA via gavage. The rats were divided into four groups: G1 (negative control group), G2 (positive control group), G3 (rats receiving mushroom extract), and G4 (rats administered with doxorubicin). The mushroom extract significantly (p < .001) improved the activity of antioxidant enzymes in carcinogenic rats. Moreover, the mushroom extract also prevented the increase in the concentration of tumor biomarkers that are CEA, CA 15.3, and CRP in experimental rats. Liver function enzymes were also raised in G2 and G4 compared with G3. Besides, the RBCs and Hb were also reduced significantly in G4 while in G3. The mushroom extract effectively controlled the level of RBCs and Hb. An improvement in lipid profile was also measured in mushroom extract receiving rats. Conclusively, the mushroom extract alleviated DMBA-induced breast cancer potentially via improving antioxidants, reducing lipid peroxidation, and decreasing tumor biomarkers. PRACTICAL APPLICATIONS: The present research study examined the antitumor potential of white button mushroom. The mushroom effectively prevented the increase in tumor biomarkers, reduction in antioxidant enzymes, and increase in lipid peroxidation in rats with DMBA-induced breast cancer. The mushroom can be used as a potential source to prevent breast cancer and further research can be conducted to explore its anticancer mechanisms.

Impact of Breast Tumor Onset on Blood Count, Carcinoembryonic Antigen, Cancer Antigen 15-3 and Lymphoid Subpopulations Supported by Automatic Classification Approach: A Pilot Study

Background

Recent observations showed that systemic immune changes are detectable in case of breast cancer (BC). In this preliminary study, we investigated routinely measured peripheral blood (PB) parameters for malignant BC cases in comparison to benign breast conditions. Complete blood count, circulating lymphoid subpopulation, and serological carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) levels were considered.

Methods

A total of 127 female patients affected by malignant (n = 77, mean age = 63 years, min = 36, max = 90) BC at diagnosis (naïve patients) or benign breast conditions (n = 50, mean age = 33 years, min = 18, max = 60) were included in this study. For each patient, complete blood count and lymphoid subpopulations (T-helper, T-cytotoxic, B-, NK-, and NKT-cells) analysis on PB samples were performed. Hormonal receptor status, Ki-67 expression, and serological CEA and CA15-3 levels were assessed in the case of patients with malignant BC via statistical analysis.

Results

Women with malignant BC disclosed increased circulating T-helper lymphocytes and CD4/CD8 ratio in PB when compared to those affected by benign breast conditions (2.345 vs 1.894, P < .05 Wilcoxon rank-sum test). In the case of malignant BC patients, additive logistic regression method was able to identify malignant BC cases with increased CA15-3 levels (CA15-3 >25 UI/mL) via the hematocrit and neutrophils/lymphocytes ratio values. Moreover, in the case of women with aggressive malignant BC featured by high levels of Ki-67 proliferation marker, an increasing number of correlations were found among blood count parameters and lymphocytes subpopulations by performing a Spearman’s correlation analysis.

Conclusions

This preliminary study confirms the ability of malignant BC to determine systemic modifications. The stratification of malignant BC cases according to the Ki-67 proliferation marker highlighted increasing detectable alterations in the periphery of women with aggressive BC. The advent of novel and more sensitive biomarkers, as well as deep immunophenotyping technologies, will provide additional insights for describing the relationship between tumor onset and peripheral alterations.

Application of a deep-learning technique to non-linear images from human tissue biopsies for shedding new light on breast cancer diagnosis

The development of label-free non-invasive techniques to be used as diagnostic tools in cancer research is of great importance for improving the quality of life for millions of patients. Previous studies have demonstrated that Third Harmonic Generation (THG) imaging could differentiate malignant from benign unlabeled human breast biopsies and distinguish the different grades of cancer. Towards the application of such technologies to clinic, in the present report, a deep learning technique was applied to THG images recorded from breast cancer tissues of grades 0, I, II and III. By the implementation of a convolutional neural network (CNN) model, the differentiation of malignant from benign breast tissue samples and the discrimination of the different grades of cancer in a fast and accurate way were achieved. The obtained results provide a step ahead towards the use of optical diagnostic tools in conjunction with the CNN image classifier for the reliable and rapid malignancy diagnosis in clinic.

Breast Cancer Aptamers: Current Sensing Targets, Available Aptamers, and Their Evaluation for Clinical Use in Diagnostics

Breast cancer is the most commonly occurring cancer in women worldwide, and the rate of diagnosis continues to increase. Early detection and targeted treatment towards histological type is crucial to improving outcomes, but current screening methods leave some patients at risk of late diagnosis. The risk of late diagnosis and progressed disease is of particular concern for young women as current screening methods are not recommended early in life. Aptamers are oligonucleotides that can bind with high specificity to target molecules such as proteins, peptides, and other small molecules. They are relatively cheap to produce and are invariable from batch to batch, making them ideal for use in large-scale clinical or screening programs. The use of aptamers for breast cancer screening, diagnosis, and therapeutics is promising, but comparison of these aptamers and their corresponding biomarkers for use in breast cancer is significantly lacking. Here, we compare the currently available aptamers for breast cancer biomarkers and their respective biomarkers, as well as highlight the electrochemical sensors that are in development.

Mannosylated polylactic-co-glycolic acid (MN-PLGA) nanoparticles induce potent anti-tumor immunity in murine model of breast cancer

Nanoparticle-based cancer immunotherapy is considered a novel and promising therapeutic strategy aimed at stimulating host immune responses against tumors. To this end, in the present study, mannan-decorated polylactic-co-glycolic acid (PLGA) nanoparticles containing tumor cell lysate (TCL) and poly riboinosinic polycytidylic acid (poly I:C) were used as antigen delivery systems to immunize breast tumor-bearing Balb/c mice. PLGA nanoparticles were fabricated employing a double emulsion solvent evaporation method. The formation of spherical and uniform nanoparticles (NPs) ranging 150-250 nm was detected by field emission scanning electron microscopy (FESEM) and dynamic light scattering (DLS). Four nanoformulation were used to treat mice and vaccination-induced immunological responses. Tumor regression and overall survival rate were evaluated in four experimental groups. Tumor cell lysate and poly I:C loaded mannan-decorated nanoparticles (TCL-Poly I:C) NP-MN caused a significant decrease in tumor growth and 2- to 3-fold improvement in survival times of the treated mice. The NPs with or without mannan decoration elicited stronger responses in terms of lymphocyte proliferation, delayed-type hypersensitivity and CD107a expression. Moreover, our data indicated that the production of IFN-γ and IL-2 increased while the production of IL-4 and IL-10 decreased in splenocytes culture supernatants. In the pathological evaluations, we found that necrosis and immune cells infiltration rate in the tumor tissue of the treated mice was elevated, while tumor cellularity and lung metastases significantly decreased in particular in the group that received (TCL-Poly I:C) NP-MN. Altogether, our findings suggested that the mannan-decorated PLGA NPs antigen delivery system had significant anti-tumor effects against the murine model of breast cancer and it could be considered as a step forward to human breast cancer immunotherapy.

Implications and pitfalls for cancer diagnostics exploiting extracellular vesicles

Early detection of cancer in order to facilitate timely therapeutic interventions is an unsolved problem in today's clinical diagnostics. Tumors are detected so far mostly after pathological symptoms have emerged (usually already in progressed disease states), within preventive screenings, or occasionally as incidental finding. The emergence of extracellular vesicle (EV) analytics in combination with liquid biopsy sampling opened a plethora of new possibilities for the detection of tumors (and other diseases). This review gives an overview of the diversity of currently known EV species and the relevant cargo molecules representing potential biomarkers to detect, identify and characterize tumor cells. A number of molecules reported in recent years to be valuable targets for different aspects of cancer diagnostics, are presented. Furthermore, we discuss (technical) challenges and pitfalls related to the various potential applications (screening, diagnosis, prognosis, monitoring) of liquid biopsy based EV analytics, and give an outlook to possible future directions of this emerging field in oncology.

Aptamer-based sensing of breast cancer biomarkers: a comprehensive review of analytical figures of merit

INTRODUCTION

Accurate determination of the aberrantly expressed biomarkers such as human epidermal growth factor receptor 2 (HER2), carcinoembryonic antigen (CEA), platelet-derived growth factor (PDGF), mucin 1 (MUC1), and vascular endothelial growth factor VEGF₁₆₅ have played an essential role in the clinical management of the breast cancer. Assessment of these cancer-specific biomarkers has conventionally relied on time-taking methods like the enzyme-linked immunosorbent assay and immunohistochemistry. However, recent development in the aptamer-based diagnostics has allowed developing tools that may substitute the conventional means of biomarker assessment in breast cancer. Adopting the aptamer-based diagnostic tools (aptasensors) to clinical practices will depend on their analytical performance on clinical samples.

AREAS COVERED

In this review, we provide an overview of the analytical merits of HER2, CEA, PDGF, MUC1, and VEGF₁₆₅ aptasensors. Scopus and Pubmed databases were searched for studies reporting aptasensor development for the listed breast cancer biomarkers in the past one decade. Linearity, detection limit, and response time are emphasized.

EXPERT OPINION

In our opinion, aptasensors have proven to be on a par with the antibody-based methods for detection of various breast cancer biomarkers. Though robust validation of the aptasensors on significant sample size is required, their ability to detect pathophysiological range of biomarkers suggest the possibility of future clinical adoption.

The Signal Transducer IL6ST (gp130) as a Predictive and Prognostic Biomarker in Breast Cancer

Novel biomarkers are needed to continue to improve breast cancer clinical management and outcome. IL6-like cytokines, whose pleiotropic functions include roles in many hallmarks of malignancy, rely on the signal transducer IL6ST (gp130) for all their signalling. To date, 10 separate independent studies based on the analysis of clinical breast cancer samples have identified IL6ST as a predictor. Consistent findings suggest that IL6ST is a positive prognostic factor and is associated with ER status. Interestingly, these studies include 4 multigene signatures (EndoPredict, EER4, IRSN-23 and 42GC) that incorporate IL6ST to predict risk of recurrence or outcome from endocrine or chemotherapy. Here we review the existing evidence on the promising predictive and prognostic value of IL6ST. We also discuss how this potential could be further translated into clinical practice beyond the EndoPredict tool, which is already available in the clinic. The most promising route to further exploit IL6ST's promising predicting power will likely be through additional hybrid multifactor signatures that allow for more robust stratification of ER+ breast tumours into discrete groups with distinct outcomes, thus enabling greater refinement of the treatment-selection process.