A Breast Cancer Review: Through the Eyes of the Doctor, Nurse, and Patient

Broken yet Brave: Arabic Women's Experience of a Breast Cancer Diagnosis

INTRODUCTION

Breast cancer is the most common cancer in Arabic women and is often diagnosed in advanced stages, resulting in an increased likelihood of requiring a mastectomy. Despite this, there is a lack of contemporary literature exploring Arabic women's experiences of breast cancer and its sequelae.

METHOD

Semi-structured interviews were conducted between 2019 and 2022 of Arabic women diagnosed with breast cancer. Data were analyzed using thematic analysis as described by Braun and Clark.

RESULTS

Two main themes were identified: (a) Broken yet brave describes participants' experiences when diagnosed and (b) Making decisions about treatment and experiences of support detailing their lack of decision-making autonomy and perceptions of support.

DISCUSSION

Arabic women believe in the concept of fate and faith, and their cultural conditioning is to prioritize family over themselves, often with limited support. They lack autonomy in decision-making due to the patriarchal society they live in.

Ameliorative effect of zinc oxide-chitosan conjugates on the anticancer activity of cisplatin: Approach for breast cancer treatment

Breast cancer is the second most prevalent cancer affecting both males and females, comprising nearly 30 % of all cancer cases. While chemotherapeutic agents, such as cisplatin (Cis), have proven successful in cancer treatment, concerns persist regarding their efficacy and the potentially dangerous side effects. Consequently, there is a crucial and ongoing need to develop approaches that minimize side effects associated with chemotherapy. In the present work, various types of nanoparticles (NPs) were synthesized and loaded with Cis. Cis was conjugated with nanocarriers such as zinc oxide (ZnO), ZnO modified with mandelic acid and graphene oxide (GO), chitosan (CS), and CS modified with ZnO and GO to enhance the selectivity of Cis towards cancer cells. Zeta potentials and particles size were assessed using electrophoretic light scattering and dynamic light scattering. NPs were characterized using transmission electron microscopy, Fourier-transform infrared spectroscopy, and X-ray diffraction. The impact of standalone Cis as well as its nanoconjugated form on the behavior of MCF-7 cell line was investigated using WST-1 cell proliferation and apoptosis/necrosis assays. Experimental findings revealed that among the various NPs tested, ZnO, and CS NPs exhibited the highest loading percentage of Cis, surpassing the loading percentages achieved with other NPs. Cytotoxicity assay showed the enhanced effect of Cis when conjugated with ZnO and CS NPs. Flow cytometry-based assays and confocal microscopy confirmed that ZnO/Cis and CS/Cis induced apoptosis. The cisplatin-nanocomplex exhibited a descending order of early apoptosis and late apoptosis in the following order: ZnO, Cis, CS, ZnO-M, CS-GO, ZnO-GO, CS-ZnO, and CS-ZnO, Cis, CS, CS-GO, ZnO-M, ZnO, ZnO-GO, respectively. None of the nanoparticle complexes displayed a significant percentage of necrotic cells, with the highest percentage reaching 4.65 % in the case of CS-GO/Cis.

Data-based modeling of breast cancer and optimal therapy

Excessive accumulation of β-catenin proteins is a vital driver in the development of breast cancer. Many clinical assessments incorporating immunotherapy with targeted mRNA of β-catenin are costly endeavor. This paper develops novel mathematical models for different treatments by invoking available clinical data to calibrate models, along with the selection and evaluation of therapy strategies in a faster manner with lower cost. Firstly, in order to explore the interactions between cancer cells and the immune system within the tumor microenvironment, we construct different types of breast cancer treatment models based on RNA interference technique and immune checkpoint inhibitors, which have been proved to be an effective combined therapy in pre-clinical trials associated with the inhibition of β-catenin proteins to enhance intrinsic anti-tumor immune response. Secondly, various techniques including MCMC are adopted to estimate multiple parameters and thus simulations in agreement with experimental results sustain the validity of our models. Furthermore, the gradient descent method and particle swarm algorithm are designed to optimize therapy schemes to inhibit the growth of tumor and lower the treatment cost. Considering the mechanisms of drug resistance in vivo, simulations exhibit that therapies are ineffective resulting in cancer relapse in the prolonged time. For this reason, parametric sensitivity analysis sheds light on the choice of new treatments which indicate that, in addition to inhibiting β-catenin proteins and improving self-immunity, the injection of dendritic cells promoting immunity may provide a novel vision for the future of cancer treatment. Overall, our study provides witness of principle from a mathematical perspective to guide clinical trials and the selection of treatment regimens.

Breast Cancer Survivors' Satisfaction and Information Recall of Telehealth Survivorship Care Plan Appointments During the COVID-19 Pandemic

OBJECTIVES

To examine patient satisfaction and information recall after telehealth breast cancer survivorship visits with a nurse practitioner.

SAMPLE & SETTING

Female survivors of breast cancer after their first visit with a nurse practitioner in the outpatient survivorship clinic post-treatment.

METHODS & VARIABLES

Participants included female survivors who were originally diagnosed with stage 0-III breast cancer and have since completed an initial telehealth appointment to review the survivorship care plan. Survivors were invited to complete a 20-question electronic survey about their satisfaction and recall of visit information.

RESULTS

62 participants completed the survey and indicated an overall high level of satisfaction with telehealth survivorship appointments. Most recalled key survivorship information from the visit and felt the appropriate amount of information was discussed. Overall satisfaction was significantly correlated with the length and convenience of the appointment, and the personal manner and technical skills of the nurse practitioner. Survivors' age was not associated with significant differences in overall satisfaction.

IMPLICATIONS FOR NURSING

Telehealth for initial survivorship visits demonstrated high satisfaction with telehealth and the overall visit as a low-cost intervention to treat symptoms.

Development and evaluation of a teleoncology system for breast cancer during the COVID-19 pandemic

Background: The present study describes the steps of developing a hybrid teleoncology system to provide treatment plans for breast cancer patients. Materials & methods: This research was conducted in four stages, including developing a proposal for experts, identifying and analyzing system requirements, designing a prototype and implementing and evaluating the final version of the hybrid teleoncology system. Results: The results of the usability evaluation showed that the users evaluated the system at a good level and, in practice, the implemented system was perceived to be useful by specialists in providing treatment plans for cancer patients. Conclusion: The hybrid teleoncology system is a practical alternative to traditional methods for providing treatment plans to breast cancer patients.

Theranostic Interpolation of Genomic Instability in Breast Cancer

Breast cancer is a diverse disease caused by mutations in multiple genes accompanying epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance results in genomic instability. Theranostic has the potential to foretell and estimate therapy response, contributing a valuable opportunity to modify the ongoing treatments and has developed new treatment strategies in a personalized manner. “Omics” technologies play a key role while studying genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics, metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many effective results. Several diverse tools are used to investigate genomic instability and underlying mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the implications of computational biology regarding mutational and pathway analyses, identification of prognostic markers, and the development of strategies for precision medicine. We also review different technologies required for the investigation of genomic instability in breast cancer cells, including recent therapeutic and preventive advances in breast cancer.

Folic acid-doxorubicin polymeric nanocapsules: A promising formulation for the treatment of triple-negative breast cancer

Breast cancer is the most common cancers among women and is one of the main causes of morbidity and mortality in this population. In this study, we aimed to conjugate doxorubicin (DOX), a drug widely used in cancer chemotherapy, and folic acid (FA), a ligand targeted for cancer therapy, to lipid-core nanocapsules (LNC), and evaluate the efficacy of the nanoformulation against triple-negative breast cancer (TNBC) MDA-MB-231 cells that overexpress folate receptors (FRs). We performed cell viability assays, quantitative real-time PCR (qRT-PCR), cell migration assay, and clonogenic assay, as well as measured the levels of nitric oxide (NO) generated and cellular uptake. The results showed that the nanoformulation reduced cell viability. The results of qRT-PCR analysis revealed that the nanoformulation induced apoptosis of MDA-MB-231 cells. The mRNA expression levels of Cat and MnSod were increased when the nanoformulation was compared to the doxorubicin solution. Furthermore, the nanoformulation significantly decreased the migration of breast cancer cells in vitro and inhibited colony formation. Additionally, the expression of iNOS in MDA-MB-231 cells was higher when the nanoformulation was used compared to the doxorubicin solution. Cellular uptake was observed after incubating the MDA-MB-231 cells with the fluorescent-labeled nanoformulation. In conclusion, we developed a promising nanoformulation for the treatment of TNBC. Further studies are necessary to demonstrate the in vivo efficacy of this formulation.

Application of decision tree-based ensemble learning in the classification of breast cancer

As a common screening and diagnostic tool, Fine Needle Aspiration Biopsy (FNAB) of the suspicious breast lumps can be used to distinguish between malignant and benign breast cytology. In this study, we first review published works on the classification of breast cancer where the machine learning and data mining algorithms have been applied by using the Wisconsin Breast Cancer Database (WBCD). This work then introduces useful new tools, based on Random Forest (RF) and Extremely Randomized Trees or Extra Trees (ET) algorithms to classify breast cancer. The RF and ET strategies use the decision trees as proper classifiers to attain the ultimate classification. The RF and ET approaches include four main stages: input identification, determination of the optimal number of trees, voting analysis, and final decision. The models implemented in this research consider important factors such as uniformity of cell size, bland chromatin, mitoses, and clump thickness as the input parameters. According to the statistical analysis, the proposed methods are able to classify the type of breast cancer accurately. The error analysis results reveal that the designed RF and ET models offer easy-to-use outcomes and the highest diagnostic performance, compared to previous tools/models in the literature for the WBCD classification. The highest and lowest magnitudes of relative importance are attributed to the uniformity of cell size and mitoses among the factors. It is expected that the RF and ET algorithms play an important role in medicine and health systems for screening and diagnosis in the near future.

Required Data Elements and Requirements of a Teleoncology System to Provide Treatment Plans for Patients with Breast Cancer

Background: Teleoncology refers to the use of telemedicine for remotely providing multiple specialized services in clinical oncology processes, including screening, diagnosis, treatment planning, consultation, supportive care, pathology, surgery, and follow-up services. Objectives: The aim of this study was to identify the required data elements and elicitation of requirements for developing a telemedicine system that aims at providing treatment plans for patients with breast cancer. Methods: In this study, the required data elements for the teleoncology system were identified through both the investigation of clinical guidelines and review of patients’ medical records. Identified data elements were determined by breast cancer specialists through the questionnaire. Besides, an interview method was applied to elicit the requirements of this system. Results: The identified data elements were categorized into 20 groups (e.g., clinical data, breast physical examinations, pathological results, tests, imaging results, etc.). From the 182 data elements included within the questionnaire, 125 were recognized to be necessary (n = 32, 100%). The lowest mean percentage were observed in magnesium blood test (Mg) (n = 21, 65.63%) and protein test (Pr) (n = 21, 65.63%). Other data elements with a minimum mean of 71.87% and a maximum mean of 100% were recognized necessary. In general, 2 major themes, 9 categories, and 45 related sub-categories were extracted from analyzing the findings of the interviews related to the system requirements. Conclusions: The findings of the present study can be used as a basis for developing teleoncology systems that aim at providing treatment plans for patients with breast cancer.

The aryl hydrocarbon receptor (AhR) as a breast cancer drug target

Breast cancer is the most common cancer in women, with more than 1.7 million diagnoses worldwide per annum. Metastatic breast cancer remains incurable, and the presence of triple-negative phenotypes makes targeted treatment impossible. The aryl hydrocarbon receptor (AhR), most commonly associated with the metabolism of xenobiotic ligands, has emerged as a promising biological target for the treatment of this deadly disease. Ligands for the AhR can be classed as exogenous or endogenous and may have agonistic or antagonistic activity. It has been well reported that agonistic ligands may have potent and selective growth inhibition activity in a number of oncogenic cell lines, and one (aminoflavone) has progressed to phase I clinical trials for breast cancer sufferers. In this study, we examine the current state of the literature in this area and elucidate the promising advances that are being made in hijacking the cytosolic-to-nuclear pathway of the AhR for the possible future treatment of breast cancer.

TiO2 nanotubes/reduced GO nanoparticles for sensitive detection of breast cancer cells and photothermal performance

In this study, we developed a simple and cost effective aptasensor based on TiO₂ nanotubes-reduced graphene oxide (TiO₂ nanotube-rGO) linked to MUC1 aptamers for ultrasensitive electrochemical detection of breast cancer cell (MCF-7). Moreover, the photothermal performance of nanohybrid TiO₂-rGO was investigated for cancer treatment. In this regard, after synthesize of TiO₂ nanotubes via anodization process, TiO₂ nanotubes-rGO hybrid was synthesized by UV assisted reduction of GO and subsequent TiO₂ nanotubes attachment to rGO sheets. The resultant hybrid could provide an excellent large surface area leading to improvement of suitable sites for MUC1 aptamer immobilization. Our results revealed that TiO₂-rGO aptasensor exhibited superior analytical performance for MCF-7 cell detection with the detection limit of 40 cells.ml^-1 within the detection range of 10³-10⁷ cells. ml^-1. In addition, the designed aptasensor was effectively applied to detect MUC1 marker in a real sample. Moreover, the TiO₂ nanotube-rGO hybrid nanoparticles revealed great photothermal performance exposed to NIR laser. It could be concluded that nanohybrid TiO₂-rGO would be a useful and beneficial platform for detection and treatment of breast cancer.