Current State of Breast Cancer Diagnosis, Treatment, and Theranostics

Electrochemical biosensors for early detection of breast cancer

Breast cancer continues to be a significant contributor to global cancer deaths, particularly among women. This highlights the critical role of early detection and treatment in boosting survival rates. While conventional diagnostic methods like mammograms, biopsies, ultrasounds, and MRIs are valuable tools, limitations exist in terms of cost, invasiveness, and the requirement for specialized equipment and trained personnel. Recent shifts towards biosensor technologies offer a promising alternative for monitoring biological processes and providing accurate health diagnostics in a cost-effective, non-invasive manner. These biosensors are particularly advantageous for early detection of primary tumors, metastases, and recurrent diseases, contributing to more effective breast cancer management. The integration of biosensor technology into medical devices has led to the development of low-cost, adaptable, and efficient diagnostic tools. In this framework, electrochemical screening platforms have garnered significant attention due to their selectivity, affordability, and ease of result interpretation. The current review discusses various breast cancer biomarkers and the potential of electrochemical biosensors to revolutionize early cancer detection, making provision for new diagnostic platforms and personalized healthcare solutions.

Theranostics: aptamer-assisted carbon nanotubes as MRI contrast and photothermal agent for breast cancer therapy

Breast cancer is one of the leading causes of death among women globally, making its diagnosis and treatment challenging. The use of nanotechnology for cancer diagnosis and treatment is an emerging area of research. To address this issue, multiwalled carbon nanotubes (MWCNTs) were ligand exchanged with butyric acid (BA) to gain hydrophilic character. The successful functionalization was confirmed by FTIR spectroscopy. Surface morphology changes were observed using SEM, while TEM confirmed the structural integrity of the MWCNTs after functionalization. Particle size, zeta potential, and UV spectroscopy were also performed to further characterize the nanoparticles. The breast cancer aptamer specific to Mucin-1 (MUC-1) was then conjugated with the functionalized MWCNTs. These MWCNTs successfully targeted breast cancer cells (MDA-MB-231) as examined by cellular uptake studies and exhibited a reduction in cancer-induced inflammation, as evidenced by gene transcription (qPCR) and protein expression (immunoblotting) levels. Immunoblot and confocal-based immunofluorescence assay (IFA) indicated the ability of CNTs to induce photothermal cell death of MDA-MB-231 cells. Upon imaging, cancer cells were effectively visualized due to the MWCNTs' ability to act as magnetic resonance imaging (MRI) contrast agents. Additionally, MWCNTs demonstrated photothermal capabilities to eliminate bound cancer cells. Collectively, our findings pave the way for developing aptamer-labeled MWCNTs as viable "theranostic alternatives" for breast cancer treatment.

MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer

BACKGROUND AND AIMS

Preoperative prediction of axillary lymph node (ALN) burden in patients with early-stage breast cancer is pivotal for individualised treatment. This study aimed to develop a MRI radiomics model for evaluating the ALN burden in early-stage breast cancer and to provide biological interpretability to predictions by integrating radiogenomic data.

METHODS

This study retrospectively analyzed 1211 patients with early-stage breast cancer from four centers, supplemented by data from The Cancer Imaging Archive (TCIA) and Duke University (DUKE). MRI radiomic features were extracted from dynamic contrast-enhanced MRI images and an ALN burden-related radscore was constructed by the backpropagation neural network algorithm. Clinical and combined models were developed, integrating ALN-related clinical variables and radscore. The Kaplan-Meier curve and log-rank test were used to assess the prognostic differences between the predicted high- and low-ALN burden groups in both Center I and DUKE cohorts. Gene set enrichment and immune infiltration analyses based on transcriptomic TCIA and TCIA Breast Cancer dataset were used to investigate the biological significance of the ALN-related radscore.

RESULTS

The MRI radiomics model demonstrated an area under the curve of 0.781-0.809 in three validation cohorts. The predicted high-risk population demonstrated a poorer prognosis (log-rank P < .05 in both cohorts). Radiogenomic analysis revealed migration pathway upregulation and cell differentiation pathway downregulation in the high radscore groups. Immune infiltration analysis confirmed the ability of radiological features to reflect the heterogeneity of the tumor microenvironment.

CONCLUSIONS

The MRI radiomics model effectively predicted the ALN burden and prognosis of early-stage breast cancer. Moreover, radiogenomic analysis revealed key cellular and immune patterns associated with the radscore.

Patient journey and timeliness of care for patients with breast cancer in Africa: a scoping review protocol

INTRODUCTION

Cancer is the leading cause of death worldwide, with breast cancer being one of the most commonly diagnosed types. Low-income and middle-income countries account for nearly half of all breast cancer cases and related fatalities. In Africa, mortality rates are higher and survival rates are lower compared with developed countries. Timeliness of care is a critical aspect of healthcare, but various studies and healthcare systems use different criteria and methods to measure it. Assessing the breast cancer care pathway and understanding the determinants of delayed care are essential for effective interventions. Therefore, this scoping review aims to evaluate the methods used to measure the timeliness of breast cancer care, identify specific points in the care pathway where delays are most frequently reported, and examine the factors affecting the timeliness of breast cancer care in Africa.

METHODS AND ANALYSIS

We will conduct this scoping review using the Arksey and O'Malley framework endorsed by the Joanna Briggs Institute. A scoping review of articles written in English concerning the timeliness of breast cancer care in the African context will be undertaken. Six electronic databases (MEDLINE, EMBASE, CINAHL, SCOPUS, WEB Of SCIENCE and PsycINFO) will be searched to identify published literature on timeliness of breast care in Africa. Two reviewers will independently screen the articles at both the abstract and full-text stages, guided by predetermined inclusion and exclusion criteria. The full texts of identified studies will be further examined and charted using a data extraction form guided by the Model of Pathways to Treatment framework. Publications describing the time to diagnosis and its associated factors in the contexts of breast cancer will be considered for inclusion, with no restrictions based on date of publication. Studies that are published in languages other than English and that do not focus on the timeliness of care or time-related aspects within the care pathway will be excluded. Evidence will be narratively synthesised and analysed.

ETHICS AND DISSEMINATION

Ethical approval is not needed as this scoping review does not involve collecting data from human participants. The results produced from this review will be submitted to a scientific peer-reviewed journal for publication and will be presented at scientific meetings.

Clinical applications of volatilomic assays

The study of metabolomics is revealing immense potential for diagnosis, therapy monitoring, and understanding of pathogenesis processes. Volatilomics is a subcategory of metabolomics interested in the detection of molecules that are small enough to be released in the gas phase. Volatile compounds produced by cellular processes are released into the blood and lymph, and can reach the external environment through different pathways, such as the blood-air interface in the lung that are detected in breath, or the blood-water interface in the kidney that leads to volatile compounds detected in urine. Besides breath and urine, additional sources of volatile compounds such as saliva, blood, feces, and skin are available. Volatilomics traces its roots back over fifty years to the pioneering investigations in the 1970s. Despite extensive research, the field remains in its infancy, hindered by a lack of standardization despite ample experimental evidence. The proliferation of analytical instrumentations, sample preparations and methods of volatilome sampling still make it difficult to compare results from different studies and to establish a common standard approach to volatilomics. This review aims to provide an overview of volatilomics' diagnostic potential, focusing on two key technical aspects: sampling and analysis. Sampling poses a challenge due to the susceptibility of human samples to contamination and confounding factors from various sources like the environment and lifestyle. The discussion then delves into targeted and untargeted approaches in volatilomics. Some case studies are presented to exemplify the results obtained so far. Finally, the review concludes with a discussion on the necessary steps to fully integrate volatilomics into clinical practice.

Correlations of Imaging and Therapy in Breast Cancer Based on Molecular Patterns: An Important Issue in the Diagnosis of Breast Cancer

Breast cancer is a global health issue affecting countries worldwide, imposing a significant economic burden due to expensive treatments and medical procedures, given the increasing incidence. In this review, our focus is on exploring the distinct imaging features of known molecular subtypes of breast cancer, underlining correlations observed in clinical practice and reported in recent studies. The imaging investigations used for assessment include screening modalities such as mammography and ultrasonography, as well as more complex investigations like MRI, which offers high sensitivity for loco-regional evaluation, and PET, which determines tumor metabolic activity using radioactive tracers. The purpose of this review is to provide a better understanding as well as a revision of the imaging differences exhibited by the molecular subtypes and histopathological types of breast cancer.

Integrating intratumoral and peritumoral radiomics with deep transfer learning for DCE-MRI breast lesion differentiation: A multicenter study comparing performance with radiologists

PURPOSE

To conduct the fusion of radiomics and deep transfer learning features from the intratumoral and peritumoral areas in breast DCE-MRI images to differentiate between benign and malignant breast tumors, and to compare the diagnostic accuracy of this fusion model against the assessments made by experienced radiologists.

MATERIALS AND METHODS

This multi-center study conducted a retrospective analysis of DCE-MRI images from 330 women diagnosed with breast cancer, with 138 cases categorized as benign and 192 as malignant. The training and internal testing sets comprised 270 patients from center 1, while the external testing cohort consisted of 60 patients from center 2. A fusion feature set consisting of radiomics features and deep transfer learning features was constructed from both intratumoral (ITR) and peritumoral (PTR) areas. The Least absolute shrinkage and selection operator (LASSO) based support vector machine was chosen as the classifier by comparing its performance with five other machine learning models. The diagnostic performance and clinical usefulness of fusion model were verified and assessed through the area under the receiver operating characteristics (ROC) and decision curve analysis. Additionally, the performance of the fusion model was compared with the diagnostic assessments of two experienced radiologists to evaluate its relative accuracy. The study strictly adhered to CLEAR and METRICS guidelines for standardization to ensure rigorous and reproducible methods.

RESULTS

The findings show that the fusion model, utilizing radiomics and deep transfer learning features from the ITR and PTR, exhibited exceptional performance in classifying breast tumors, achieving AUCs of 0.950 in the internal testing set and 0.921 in the external testing set. This performance significantly surpasses that of models relying on singular regional radiomics or deep transfer learning features alone. Moreover, the fusion model demonstrated superior diagnostic accuracy compared to the evaluations conducted by two experienced radiologists, thereby highlighting its potential to support and enhance clinical decision-making in the differentiation of benign and malignant breast tumors.

CONCLUSION

The fusion model, combining multi-regional radiomics with deep transfer learning features, not only accurately differentiates between benign and malignant breast tumors but also outperforms the diagnostic assessments made by experienced radiologists. This underscores the model's potential as a valuable tool for improving the accuracy and reliability of breast tumor diagnosis.

Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

Lost in Translation: Multilingual Analysis of Online Breast Cancer Information

INTRODUCTION

Patients use the internet to learn more about health conditions. Non-English-speaking patients may face additional challenges. The quality of online breast cancer information, the most common cancer in women, is uncertain. This study aims to examine the quality of online breast cancer information for English and non-English-speaking patients.

METHODS

Three search engines were queried using the terms: "how to do a breast examination," "when do I need a mammogram," and "what are the treatment options for breast cancer" in English, Spanish, and Chinese. For each language, 60 unique websites were included and classified by type and information source. Two language-fluent reviewers evaluated website quality using the Journal of American Medical Association benchmark criteria (0-4) and the DISCERN tool (1-5), with higher scores representing higher quality. Scores were averaged for each language. Health On the Net code presence was noted. Inter-rater reliability between reviewers was assessed.

RESULTS

English and Spanish websites most commonly originated from US sources (92% and 80%, respectively) compared to Chinese websites (33%, P < 0.001). The most common website type was hospital-affiliated for English (43%) and foundation/advocacy for Spanish and Chinese (43% and 45%, respectively). English websites had the highest and Chinese websites the lowest mean the Journal of American Medical Association (2.2 ± 1.4 versus 1.0 ± 0.8, P = 0.002) and DISCERN scores (3.5 ± 0.9 versus 2.3 ± 0.6, P < 0.001). Health On the Net code was present on 16 (8.9%) websites. Inter-rater reliability ranged from moderate to substantial agreement.

CONCLUSIONS

The quality of online information on breast cancer across all three languages is poor. Information quality was poorest for Chinese websites. Improvements to enhance the reliability of breast cancer information across languages are needed.

An Innovative Thermal Imaging Prototype for Precise Breast Cancer Detection: Integrating Compression Techniques and Classification Methods

Breast cancer detection at an early stage is crucial for improving patient survival rates. This work introduces an innovative thermal imaging prototype that incorporates compression techniques inspired by mammography equipment. The prototype offers a radiation-free and precise cancer diagnosis. By integrating compression and illumination methods, thermal picture quality has increased, and the accuracy of classification has improved. Essential components of the suggested thermography device include an equipment body, plates, motors, pressure sensors, light sources, and a thermal camera. We created a 3D model of the gadget using the SolidWorks software 2020 package. Furthermore, the classification research employed both cancer and normal images from the experimental results to validate the efficacy of the suggested system. We employed preprocessing and segmentation methods on the obtained dataset. We successfully categorized the thermal pictures using various classifiers and examined their performance. The logistic regression model showed excellent performance, achieving an accuracy of 0.976, F1 score of 0.977, precision of 1.000, and recall of 0.995. This indicates a high level of accuracy in correctly classifying thermal abnormalities associated with breast cancer. The proposed prototype serves as a highly effective tool for conducting initial investigations into breast cancer detection, offering potential advancements in early-stage diagnosis, and improving patient survival rates.

Economics of Antibody Drug Conjugates (ADCs): Innovation, Investment and Market Dynamics

PURPOSE OF REVIEW

This review aims to explore the intricate interplay between scientific advancements and economic considerations in the development, production, and commercialization of Antibody Drug Conjugates (ADCs). The focus is on understanding the challenges and opportunities at this unique intersection, highlighting how scientific innovation and economic dynamics mutually influence the trajectory of ADCs in the pharmaceutical landscape.

RECENT FINDINGS

There has been a significant increase in interest and investment in the development of ADCs. Initially focused on hematological malignancies, ADCs are now being researched for use in treating solid tumors as well. Pharmaceutical companies are heavily investing to broaden the range of indications for which ADCs can be effective. According to a report from the end of 2023, the global ADCs market grew from USD 1.4 billion in 2016 to USD 11.3 billion in 2023, with projections estimating a value of USD 23.9 billion by 2032, growing at a CAGR of 10.7%. ADCs represent a promising class of biopharmaceuticals in oncology, with expanding applications beyond hematological malignancies to solid tumors. The significant growth in the ADC market underscores the impact of scientific and economic factors on their development. This review provides valuable insights into how these factors drive innovation and commercialization, shaping the future of ADCs in cancer treatment.

Global burden and attributable risk factors of breast cancer in young women: historical trends from 1990 to 2019 and forecasts to 2030 by sociodemographic index regions and countries

Background

Breast cancer in young women (BCY) is much less common but has significant health sequelae and societal costs. We aimed to evaluate the global and regional burden of breast cancer in women aged 15-39 years from 1990 to 2019.

Methods

We collected detailed data on breast cancer from the Global Burden of Disease Study 2019 (GBD 2019) Data Resources. The age-standardised incidence rate (ASIR), age-standardised mortality rate (ASMR), age-standardised disability-adjusted life years rate (ASDR), and estimated annual percentage change (EAPC) were used to assess the disease burden of BCY. The Bayesian Age-Period-Cohort model was used to forecast disease burden from 2020 to 2030.

Results

From 1990 to 2019, significant increases in ASIR were found for BCY (EAPC = 0.59, 95% confidence interval (CI) = 0.5 to 0.68), whereas decreases in ASMR (EAPC = -0.41, 95% CI = -0.53 to -0.3) and ASDR (EAPC = -0.35, 95% CI = -0.46 to -0.24). Across countries with varying sociodemographic indexes (SDI), all regions showed an upward trend in BCY morbidity, except for countries with a high SDI. While mortality and DALYs rates have decreased in countries with high, high-middle, and middle SDI, they have increased in countries with low-middle and low SDI. Countries with lower SDIs are projected to bear the greatest burden of BCY over the next decade, including both low and low-middle categories. Alcohol use was the main risk factor attributed to BCY deaths in most countries, while exposure to second hand smoke was the predominant risk factor for BCY deaths in middle and low-middle SDI countries.

Conclusions

The burden of breast cancer in young women is on the rise worldwide, and there are significant regional differences. Countries with a low-middle or low SDI face even more challenges, as they experienced a more significant and increasing BCY burden than countries with higher SDIs.

Public neoantigens in breast cancer immunotherapy (Review)

Among women globally, breast cancer is the most prevalent cancer and the leading cause of cancer‑related death. Interestingly, though genetic mutations contribute to the disease, <15% of women diagnosed with breast cancer have a family history of the disease, suggesting a prevalence of sporadic genetic mutations in breast cancer development. In the rapidly rising field of cancer genomics, neoantigen‑based immunotherapy has come to the fore. The investigation of novel proteins arising from unique somatic mutations or neoantigens have opened a new pathway for both individualized and public cancer treatments. Because they are shared among individuals with similar genetic changes, public neoantigens provide an opportunity for 'off‑the‑shelf' anticancer therapies, potentially extending the benefits to a wider patient group. The present review aimed to highlight the role of shared or public neoantigens as therapeutic targets for patients with breast cancer, emphasizing common hotspot mutations of certain genes identified in breast cancer. The clinical utilization of public neoantigen‑based therapies for breast cancer treatment were also discussed.

Alginate-Chitosan Biodegradable and Biocompatible Based Hydrogel for Breast Cancer Immunotherapy and Diagnosis: A Comprehensive Review

Breast cancer is the most common type of cancer and the second leading cause of cancer-related mortality in females. There are many side effects due to chemotherapy and traditional surgery, like fatigue, loss of appetite, skin irritation, and drug resistance to cancer cells. Immunotherapy has become a hopeful approach toward cancer treatment, generating long-lasting immune responses in malignant tumor patients. Recently, hydrogel has received more attention toward cancer therapy due to its specific characteristics, such as decreased toxicity, fewer side effects, and better biocompatibility drug delivery to the particular tumor location. Researchers globally reported various investigations on hydrogel research for tumor diagnosis. The hydrogel-based multilayer platform with controlled nanostructure has received more attention for its antitumor effect. Chitosan and alginate play a leading role in the formation of the cross-link in a hydrogel. Also, they help in the stability of the hydrogel. This review discusses the properties, preparation, biocompatibility, and bioavailability of various research and clinical approaches of the multipolymer hydrogel made of alginate and chitosan for breast cancer treatment. With a focus on cases of breast cancer and the recovery rate, there is a need to find out the role of hydrogel in drug delivery for breast cancer treatment.

Recent development of azole-sulfonamide hybrids with the anticancer potential

Cancer exhibits heterogeneity that enables adaptability and remains grand challenges for effective treatment. Chemotherapy is a validated and critically important strategy for the treatment of cancer, but the emergence of multidrug resistance which may lead to recurrence of disease or even death is a major hurdle for successful chemotherapy. Azoles and sulfonamides are important anticancer pharmacophores, and azole-sulfonamide hybrids have the potential to simultaneously act on dual/multiple targets in cancer cells, holding great promise to overcome drug resistance. This review outlines the current scenario of azole-sulfonamide hybrids with the anticancer potential, and the structure-activity relationships as well as mechanisms of action are also discussed, covering articles published from 2020 onward.

Extracellular vesicle-mediated drug delivery in breast cancer theranostics

Breast cancer (BC) continues to be a significant global challenge due to drug resistance and severe side effects. The increasing prevalence is alarming, requiring new therapeutic approaches to address these challenges. At this point, Extracellular vesicles (EVs), specifically small endosome-released nanometer-sized EVs (SEVs) or exosomes, have been explored by literature as potential theranostics. Therefore, this review aims to highlight the therapeutic potential of exosomes in BC, focusing on their advantages in drug delivery and their ability to mitigate metastasis. Following the review, we identified exosomes' potential in combination therapies, serving as miRNA carriers and contributing to improved anti-tumor effects. This is evident in clinical trials investigating exosomes in BC, which have shown their ability to boost chemotherapy efficacy by delivering drugs like paclitaxel (PTX) and doxorubicin (DOX). However, the translation of EVs into BC therapy is hindered by various challenges. These challenges include the heterogeneity of EVs, the selection of the appropriate parent cell, the loading procedures, and determining the optimal administration routes. Despite the promising therapeutic potential of EVs, these obstacles must be addressed to realize their benefits in BC treatment.

Assessing the use of the triglyceride-glycemic index (TyG), neutrophil-lymphocyte Ratio (NLR), and platelet-lymphocyte Ratio (PLR) in distinguishing benign and malignant tumors among patients with complaints of breast mass

Introduction

Breast cancer is a prevalent global health concern characterized by uncontrolled cell growth in breast tissue. In 2020, approximately 2.3 million cases were reported worldwide, with 162,468 new cases and 87,090 fatalities documented in India in 2018. Early diagnosis is crucial for reducing mortality. Our study focused on the use of markers such as the triglyceride-glycemic index and hematological markers to distinguish between benign and malignant breast masses.

Methods

A prospective cross-sectional study included female patients with breast mass complaints. The target sample size was 200. Data collection included medical history, clinical breast examination, mammography, cytological assessment via fine-needle aspiration cytology (FNAC), and blood sample collection. The analyzed parameters included neutrophil-to-lymphocyte Ratio (NLR), platelet-to-lymphocyte Ratio (PLR), and triglyceride-glycemic index (TyG). Histopathological examination confirmed the FNAC results. Statistical analysis including propensity score matching, Kolmogorov-Smirnov tests, Mann-Whitney U tests, receiver's operator curve (ROC) analysis, and logistic regression models was conducted using SPSS and R Software. Additional validation was performed on 25 participants.

Results

This study included 200 participants. 109 had benign tumors and 91 had malignant tumors. Propensity score matching balanced covariates. NLR did not significantly differ between the groups, while PLR and TyG index differed significantly. NLR correlated strongly with the breast cancer stage, but not with the BI-RADS score. PLR and TyG index showed moderate positive correlations with the BI-RADS score. ROC analysis was used to determine the optimal cutoff values for PLR and TyG index. Logistic regression models combining PLR and TyG index significantly improved malignancy prediction.

Conclusions

TyG index and PLR show potential as adjunctive markers for distinguishing breast masses. NLR correlated with cancer stage but not lesion type. Combining TyG and PLR improves prediction, aiding clinical decisions, but large-scale multicenter trials and long-term validation are required for clinical implementation.

Effect of contrast agent on T2-weighted fat-suppressed imaging and diffusion-weighted imaging in the diagnosis of breast tumors

Background

Although previous studies have shown that the injection of contrast agents can improve image quality, the specific impact of this on T2-weighted fat-suppressed (T2 FS) and diffusion-weighted imaging (DWI) sequences in the diagnosis of breast cancer remains incompletely understood. In particular, there is insufficient research on how contrast agents affect the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values within these sequences, and how these changes influence the diagnosis of benign and malignant breast tumors.

Methods

Breast magnetic resonance images (MRI) were obtained from 178 consecutive patients on a 3T scanner. The SNR and CNR of lesions on T2 FS sequence were calculated before and after contrast agent injection and compared. Differences between pre- and post-contrast ADC in identifying different tumor types were compared using the Kruskal-Wallis H-test and the paired comparison test. The accuracy of ADC values between pre- and post-contrast in distinguishing benign and malignant breast masses was assessed using receiver operating characteristic (ROC) curves.

Results

The SNR and CNR of T2 FS sequence increased after contrast injection, and especially for invasive cancer and benign tumor, the increase was significant. For DWI, there was a slight increase or decrease of ADC values after contrast injection, but the ADC values before and after contrast had a similar effect in identifying different types of tumors. In the ROC curve analysis for assessing benign and malignant breast tumors, the area under the curve (AUC) before and after contrast showed similar results.

Conclusions

Contrast agent injection can improve the SNR and CNR of T2 FS sequence, thus providing higher quality images for the diagnosis of breast lesions. Furthermore, injection of contrast agent had little effect on the ability of ADC values to identify different types of lesions and both ADC values before and after the contrast agent were able to distinguish between benign and malignant tumors with almost the same accuracy.

Adding quantitative T1rho-weighted imaging to conventional MRI improves specificity and sensitivity for differentiating malignant from benign breast lesions

OBJECTIVES

To investigate the feasibility of T1rho-weighted imaging in differentiating malignant from benign breast lesions and to explore the additional value of T1rho to conventional MRI.

MATERIALS AND METHODS

We prospectively enrolled consecutive women with breast lesions who underwent preoperative T1rho-weighted imaging, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) between November 2021 and July 2023. The T1rho, apparent diffusion coefficient (ADC), and semi-quantitative parameters from DCE-MRI were obtained and compared between benign and malignant groups. The diagnostic performance was analyzed and compared using receiver operating characteristic (ROC) curves and the Delong Test.

RESULTS

This study included 113 patients (74 malignant and 39 benign lesions). The mean T1rho value in the benign group (92.61 ± 22.10 ms) was significantly higher than that in the malignant group (72.18 ± 16.37 ms) (P < 0.001). The ADC value and time to peak (TTP) value in the malignant group (1.13 ± 0.45 and 269.06 ± 106.01, respectively) were lower than those in the benign group (1.57 ± 0.45 and 388.30 ± 81.13, respectively) (all P < 0.001). T1rho combined with ADC and TTP showed good diagnostic performance with an area under the curve (AUC) of 0.896, a sensitivity of 81.0%, and a specificity of 87.1%. The specificity and sensitivity of the combination of T1rho, ADC, and TTP were significantly higher than those of the combination of ADC and TTP (87.1% vs. 84.6%, P < 0.005; 81.0% vs. 77.0%, P < 0.001).

CONCLUSION

T1rho-weighted imaging was a feasible MRI sequence for differentiating malignant from benign breast lesions. The combination of T1rho, ADC and TTP could achieve a favorable diagnostic performance with improved specificity and sensitivity, T1rho could serve as a supplementary approach to conventional MRI.

PI3K/AKT Signaling Pathway Mediated Autophagy in Oral Carcinoma - A Comprehensive Review

Oral cancer is the most heterogeneous cancer at clinical and histological levels. PI3K/AKT/mTOR pathway was identified as one of the most commonly modulated signals in oral cancer, which regulates major cellular and metabolic activity of the cell. Thus, various proteins of PI3K/AKT/mTOR pathway were used as therapeutic targets for oral cancer, to design more specific drugs with less off-target toxicity. This review sheds light on the regulation of PI3K/AKT/mTOR, and its role in controlling autophagy and associated apoptosis during the progression and metastasis of oral squamous type of malignancy (OSCC). In addition, we reviewed in detail the upstream activators and the downstream effectors of PI3K/AKT/mTOR signaling as potential therapeutic targets for oral cancer treatment.

Advancing Breast Cancer Research Through Collaborative Computing: Harnessing Google Colab for Innovation

This investigation explores the potential efficacy of machine learning algorithms (MLAs), particularly convolutional neural networks (CNNs), in distinguishing between benign and malignant breast cancer tissue through the analysis of 1000 breast cancer images gathered from Kaggle.com, a domain of publicly accessible data. The dataset was meticulously partitioned into training, validation, and testing sets to facilitate model development and evaluation. Our results reveal promising outcomes, with the developed model achieving notable precision (92%), recall (92%), accuracy (92%), sensitivity (89%), specificity (96%), an F1 score of 0.92, and an area under the curve (AUC) of 0.944. These metrics underscore the model's ability to accurately identify malignant breast cancer images. Because of limitations such as sample size and potential variations in image quality, further research, data collection, and integration of theoretical models in a real-world clinical setting are needed to expand the reliability and generalizability of these MLAs. Nonetheless, this study serves to highlight the potential use of artificial intelligence models as supporting tools for physicians to utilize in breast cancer detection.

Impact of SSO-ASTRO Margin Guidelines on Re-excision Rate in Breast-conserving Surgery: A Single-center Experience

Introduction

Breast-conserving surgery (BCS) has been historically linked with a high rate of re-excision. To address this issue, the Society of Surgical Oncology (SSO) and the American Society for Radiation Oncology (ASTRO) developed consensus guidelines in 2014 to standardize practices and improve clinical outcomes for BCS patients. In our tertiary cancer care hospital, we assessed the impact of these guidelines on the re-excision rate following BCS.

Materials and Methods

We conducted a retrospective study on breast cancer patients who underwent BCS at the Shaukat Khanum Memorial Cancer Hospital and Research Centre in Lahore, Pakistan. The study compared the re-excision rate before the implementation of the SSO-ASTRO consensus guidelines (November 2015-July 2017) and after the implementation (January 2018-August 2019). Margins were considered positive if "ink on tumor" was present and negative if "no ink on tumor" was present. Fisher's exact test or Chi-square test was used to compare the re-excision rates between the pre- and post-guideline periods.

Results

A total of 919 patients were identified, with 533 from the pre-guideline period and 386 from the post-guideline period. Of the 919 patients, 31 with ductal carcinoma in situ (DCIS) were excluded from the re-excision analysis because the guidelines were not implemented on the DCIS. Furthermore, the overall rate of re-excision in our data was 4.3%. The re-excision rate decreased from 71.1% to 28.9% (P ≤ 0.05) following the adoption of the guidelines. We observed a statistically significant decrease in the re-excision rate after implementing the SSO-ASTRO guidelines.

Conclusion

Implementation of the SSO-ASTRO margin guidelines led to a notable decrease in the overall re-excision rate in our data set. These findings suggest that continued adherence to the guidelines may lead to a further reduction in the re-excision rate in the future.

Aptamer-Based Recognition of Breast Tumor Cells: A New Era for Breast Cancer Diagnosis

Breast cancer is one of the leading causes of death among women worldwide and can be classified into four major distinct molecular subtypes based on the expression of specific receptors. Despite significant advances, the lack of biomarkers for detailed diagnosis and prognosis remains a major challenge in the field of oncology. This study aimed to identify short single-stranded oligonucleotides known as aptamers to improve breast cancer diagnosis. The Cell-SELEX technique was used to select aptamers specific to the MDA-MB-231 tumor cell line. After selection, five aptamers demonstrated specific recognition for tumor breast cell lines and no binding to non-tumor breast cells. Validation of aptamer specificity revealed recognition of primary and metastatic tumors of all subtypes. In particular, AptaB4 and AptaB5 showed greater recognition of primary tumors and metastatic tissue, respectively. Finally, a computational biology approach was used to identify potential aptamer targets, which indicated that CSKP could interact with AptaB4. These results suggest that aptamers are promising in breast cancer diagnosis and treatment due to their specificity and selectivity.

U.S. payer budget impact of using an AI-augmented cancer risk discrimination digital histopathology platform to identify high-risk of recurrence in women with early-stage invasive breast cancer

AIMS

Use of gene expression signatures to predict adjuvant chemotherapy benefit in women with early-stage breast cancer is increasing. However, high cost, limited access, and eligibility for these tests results in the adoption of less precise assessment approaches. This study evaluates the cost impact of PreciseDx Breast (PDxBr), an AI-augmented histopathology platform that assesses the 6-year risk of recurrence in early-stage invasive breast cancer patients to help improve informed use of adjuvant chemotherapy.

MATERIALS AND METHODS

A decision-tree Markov model was developed to compare the costs of treatment guided by standard of care (SOC) risk assessment (i.e. clinical diagnostic workup with or without Oncotype DX) versus PDxBr with SOC in a hypothetical cohort of U.S. women with early-stage invasive breast cancer. A commercial payer perspective compares costs of testing, adjuvant therapy, recurrence, adverse events, surveillance, and end-of-life care.

RESULTS

PDxBr use in prognostic evaluation resulted in savings of $4 million (M) in year one compared to current SOC in 1 M females members. Over 6-years, savings increased to $12.5 M. The per-treated patient costs in year one amounted to $19.5 thousand (K) for SOC and $16.9K for PDxBr.

LIMITATIONS

For simplicity, recurrence was not specified. We performed scenario analyses to account for variations in rates for local, regional, and distant recurrence. Second, a recurrent patient incurs the total cost of treated recurrence in the first year and goes back to remission or death. Third, CDK4/6i treatment is only incorporated in the recurrence costs but not in the first line of treatment for early-stage breast cancer due to limited data.

CONCLUSIONS

Sensitivity analyses demonstrated robust overall savings to changes in all variables in the model. The use of PDxBr to assess breast cancer recurrence risk has the potential to fill gaps in care and reduce costs when gene expression signatures are not available.

Targeting Breast Cancer with N-Acetyl-D-Glucosamine: Integrating Machine Learning and Cellular Assays for Promising Results

BACKGROUND

Breast cancer is a common cancer with high mortality rates. Early diagnosis is crucial for reducing the prognosis and mortality rates. Therefore, the development of alternative treatment options is necessary.

OBJECTIVE

This study aimed to investigate the inhibitory effect of N-acetyl-D-glucosamine (D-GlcNAc) on breast cancer using a machine learning method. The findings were further confirmed through assays on breast cancer cell lines.

METHODS

MCF-7 and 4T1 cell lines (ATCC) were cultured in the presence and absence of varying concentrations of D-GlcNAc (0.5 mM, 1 mM, 2 mM, and 4 mM) for 72 hours. A xenograft mouse model for breast cancer was established by injecting 4T1 cells into mammary glands. D-GlcNAc (2 mM) was administered intraperitoneally to mice daily for 28 days, and histopathological effects were evaluated at pre-tumoral and post-tumoral stages.

RESULTS

Treatment with 2 mM and 4 mM D-GlcNAc significantly decreased cell proliferation rates in MCF-7 and 4T1 cell lines and increased Fas expression. The number of apoptotic cells was significantly higher than untreated cell cultures (p < 0.01 - p < 0.0001). D-GlcNAc administration also considerably reduced tumour size, mitosis, and angiogenesis in the post-treatment group compared to the control breast cancer group (p < 0.01 - p < 0.0001). Additionally, molecular docking/dynamic analysis revealed a high binding affinity of D-GlcNAc to the marker protein HER2, which is involved in tumour progression and cell signalling.

CONCLUSION

Our study demonstrated the positive effect of D-GlcNAc administration on breast cancer cells, leading to increased apoptosis and Fas expression in the malignant phenotype. The binding affinity of D-GlcNAc to HER2 suggests a potential mechanism of action. These findings contribute to understanding D-GlcNAc as a potential anti-tumour agent for breast cancer treatment.

Understanding the mechanistic pathways and clinical aspects associated with protein and gene based biomarkers in breast cancer

Cancer is one of the most widespread and severe diseases with a huge mortality rate. In recent years, the second-leading mortality rate of any cancer globally has been breast cancer, which is one of the most common and deadly cancers found in women. Detecting breast cancer in its initial stages simplifies treatment, decreases death risk, and recovers survival rates for patients. The death rate for breast cancer has risen to 0.024 % in some regions. Sensitive and accurate technologies are required for the preclinical detection of BC at an initial stage. Biomarkers play a very crucial role in the early identification as well as diagnosis of women with breast cancer. Currently, a wide variety of cancer biomarkers have been discovered for the diagnosis of cancer. For the identification of these biomarkers from serum or other body fluids at physiological amounts, many detection methods have been developed. In the case of breast cancer, biomarkers are especially helpful in discovering those who are more likely to develop the disease, determining prognosis at the time of initial diagnosis and choosing the best systemic therapy. In this study we have compiled various clinical aspects and signaling pathways associated with protein-based biomarkers and gene-based biomarkers.

Active Gαi/o Mutants Accelerate Breast Tumor Metastasis via the c-Src Pathway

Constitutively active mutations in the Gαi2 and GαoA subunits of heterotrimeric G proteins have been found in various human cancers, including breast cancer, but their precise roles in tumor formation, progression, and metastasis remain poorly understood. This study focused on GαoAR243H and Gαi2R179C mutants in breast cancer. These mutants alone were insufficient to initiate mammary tumor formation in mice. However, when introduced into transgenic mouse models of breast cancer induced by Neu expression or PTEN loss, the Gαi2R179C mutant notably enhanced spontaneous lung metastasis, without affecting primary tumor initiation and growth. Ectopic expression of the GαoAR243H and Gαi2R179C mutants in tumor cells promoted cell migration in vitro and dissemination into multiple organs in vivo by activating the c-Src signaling pathway. These mutants activate c-Src through direct interaction, involving specific residues in the switch domains II of Gαi subunits, which only partially overlap with those involved in inhibiting adenylyl cyclases. This study uncovers a critical role of Gαi/o signaling in accelerating breast cancer metastasis through the c-Src pathway. These findings hold clinical significance as they may pave the way for personalized therapies targeting c-Src to inhibit breast cancer metastasis in patients with active Gαi/o mutations or elevated Gαi/o signaling.

Biomarkers in Cancer Detection, Diagnosis, and Prognosis

Biomarkers are vital in healthcare as they provide valuable insights into disease diagnosis, prognosis, treatment response, and personalized medicine. They serve as objective indicators, enabling early detection and intervention, leading to improved patient outcomes and reduced costs. Biomarkers also guide treatment decisions by predicting disease outcomes and facilitating individualized treatment plans. They play a role in monitoring disease progression, adjusting treatments, and detecting early signs of recurrence. Furthermore, biomarkers enhance drug development and clinical trials by identifying suitable patients and accelerating the approval process. In this review paper, we described a variety of biomarkers applicable for cancer detection and diagnosis, such as imaging-based diagnosis (CT, SPECT, MRI, and PET), blood-based biomarkers (proteins, genes, mRNA, and peptides), cell imaging-based diagnosis (needle biopsy and CTC), tissue imaging-based diagnosis (IHC), and genetic-based biomarkers (RNAseq, scRNAseq, and spatial transcriptomics).

CD147 promotes breast cancer migration and invasion by inducing epithelial-mesenchymal transition via the MAPK/ERK signaling pathway

BACKGROUND

CD147, a transmembrane glycoprotein, has been implicated in various cancer-related processes but its role in breast cancer remains poorly understood. Herein, we investigated the expression of CD147 in different breast cancer cell lines and explored its functional roles, including migration, invasion, drug resistance and modulation of key proteins associated with cancer progression.

METHODS

The expression of CD147 was assessed in MCF-10 A, BT549, MDA-MB-231 and MCF-7 breast cancer cell lines using qRT-PCR and Western blotting, following which lyposome transfections were performed, leading overexpression of CD147 in BT549 cells and knockdown of CD147 in MCF-7 cells. Scratch assays and Transwell invasion and were performed to evaluate the cells' migration and invasion abilities. Sensitivity to 5-FU was determined via CCK-8 assays, and the expression of Snail1, E-cadherin, Vimentin, MMP-9 and the MAPK/ERK pathway were analyzed by qRT-PCR and Western blotting.

RESULTS

Compared with normal beast epithelial cells, CD147 was highly expressed in all breast cancer cell lines, with the highest overexpression observed in MCF-7 cells and the lowest overexpression observed in BT549 cells. Overexpression of CD147 in BT549 cells increased, migration, invasion, viability and resistance to 5-FU of BT549 cells, while CD147 knockdown in MCF-7 cells reduced these properties of MCF-7 cells. Furthermore, CD147 influenced the expression of Snail1, Vimentin, E-cadherin, and MMP-9, suggesting its involvement in epithelial-mesenchymal transition (EMT) regulation. The MAPK/ERK pathway was activated by CD147 in BT549 cells, as indicated by increased p-MEK/MEK ratio and p-ERK/ERK ratio. In contrast, CD147 silencing in MCF-7 cells resulted in reduced p-MEK/MEK ratio and p-ERK/ERK ratio.

CONCLUSION

In summary, our findings suggest CD147 as a potential therapeutic target in breast cancer treatment, particularly in cases where drug resistance and metastasis are concerns, worthy of further explorations.

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Fiber optic probe-based ATR-FTIR spectroscopy for rapid breast cancer detection: A pilot study

Breast cancer diagnosis is crucial for timely treatment and improved outcomes. This paper proposes a novel approach for rapid breast cancer diagnosis using optical fiber probe-based attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy from 750 to 4000 cm-1 . The technique enables direct analysis of tissue samples, eliminating the need for microtome sectioning and staining, thus saving time and resources. By capturing molecular fingerprint information, various machine-learning models were used to analyze the spectroscopic data to classify cancerous and non-cancerous tissues accurately. Comparing deparaffinized and paraffinized samples reveals the impact of sample preparation and experimental methods. The study demonstrates a strong correlation between the cancerous nature of a sample and its ATR-FTIR spectrum, suggesting its potential for breast cancer diagnosis (sensitivity of 74.2% and specificity of 78.3%). The proposed approach holds promise for integration into clinical operations, providing a rapid method for preliminary breast cancer diagnosis.

Network pharmacology-based strategy for predicting therapy targets of Ecliptae Herba on breast cancer

Breast cancer is a prevalent malignancy affecting women globally, characterized by significant morbidity and mortality rates. Ecliptae Herba is a traditional herbal medicine commonly used in clinical practice, has recently been found to possess antitumor properties. In order to explore the underlying material basis and molecular mechanisms responsible for the anti-breast cancer effects of Ecliptae Herba, we used network pharmacology and experimental verification. UPLC-MS/MS was utilized to identify compounds present in Ecliptae Herba. The active components of Ecliptae Herba and its breast cancer targets were screened using public databases. Hub genes were identified using the STRING and Metascape database. The R software was utilized for visual analysis of GO and KEGG pathways. The affinity of the hub targets for the active ingredients was assessed by molecular docking analysis, which was verified by experimental assessment. A total of 178 targets were obtained from the 10 active components of Ecliptae Herba, while 3431 targets associated with breast cancer were screened. There were 144 intersecting targets between the components and the disease. Targets with a higher degree, namely EGFR and TGFB1, were identified through the hub subnetwork of PPI. GO and KEGG analyses revealed that Ecliptae Herba plays an important role in multiple cancer therapeutic mechanisms. Moreover, molecular docking results showed that the core components had good binding affinity with key targets. Finally, it was confirmed that TGF-β1 might be a potential crucial target of Ecliptae Herba in the treatment of breast cancer by cytological experiments, and the TGF-β1/Smad signaling pathway might be an important pathway for Ecliptae Herba to exert its therapeutic effects. This study elucidated the active ingredients, key targets, and molecular mechanisms of Ecliptae Herba in the treatment of breast cancer, providing a scientific foundation and therapeutic mechanism for the prevention and treatment of breast cancer with Traditional Chinese medicine.

Breast Imaging Reporting and Data System and Contrast Enhancement Mammography: Lesion Conspicuity Likelihood of Malignancy and Relationship With Breast Tumor Receptor Status

RATIONALE AND OBJECTIVES

The new version of the Contrast Enhanced Mammography (CEM) Breast imaging Reporting and Data System (BIRADs) encourages investigations of a new enhancement descriptor: "Lesion Conspicuity" (LC). The study aims to assess the diagnostic performance and the relationship with the receptor profile of this new enhancement descriptor.

MATERIALS AND METHODS

Three hundred twenty-five patients with 381 breast lesions who underwent CEM before histological assessmentwere selected. Four radiologists, blinded to each other, categorized LC into the following levels: absent, low, moderate, and high. Considering moderate and high evaluations as predictive of malignancy, the diagnostic performance of CEM was calculated using histological results of the biopsy as the gold standard. The association between LC values and the receptor profile of the neoplasms was also evaluated.

RESULTS

The median age at the CEM examination was 50 years (IQR: 45-59). Considering the value of LC of the most experienced radiologist with the interpretation of Low Energy images (LE), we obtained a sensitivity (SE) of 91.9% (95% CI: 88.6%-95.2%) and a specificity (SP) of 67.2% (95% CI: 58.9%-75.5%). An association between "high" lesion conspicuity with ER/PgR not expressed (p = 0.025), with Ki-67>20% (p = 0.033), and with Grading G3 (p = 0.020) was observed.

CONCLUSION

The new feature of enhancement, "Lesion Conspicuity", demonstrated satisfactory performance in predicting the malignancy of lesions and significant correlation with the receptor profile of malignant breast neoplasms.

Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research

Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.

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

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

Synergistic Combination of Letrozole and Berberine in Ascorbic Acid-Stabilized AuNPs: A Promising Solution for Breast Cancer

Breast cancer is a deadly disease that affects countless women worldwide. The most conventional treatments for breast cancer, such as the administration of anticancer medications such as letrozole (LTZ), pose significant barriers due to the non-selective delivery and low bioavailability of cytotoxic drugs leading to serious adverse effects and multidrug resistance (MDR). Addressing these obstacles requires an innovative approach, and we propose a combined strategy that synergistically incorporates LTZ with berberine (BBR) into stabilised AuNPs coated with ascorbic acid (AA), known as LTZ-BBR@AA-AuNPs. The LTZ-BBR@AA-AuNPs, a novel combined drug delivery system, were carefully designed to maximise the entrapment of both LTZ and BBR. The resulting spherical nanoparticles exhibited remarkable efficiency in trapping these two compounds, with rates of 58% and 54%, respectively. In particular, the average hydrodynamic diameter of these nanoparticles was determined to be 81.23 ± 4.0 nm with a PDI value of only 0.286, indicating excellent uniformity between them. Furthermore, their zeta potential was observed to be -14.5 mV, suggesting high stability even under physiological conditions. The release profiles showed that after being incubated for about 24 h at pH levels ranging from acidic (pH = 5) to basic (pH = 7), the percentage released for both drugs ranged from 56-72%. This sustained and controlled drug release can reduce any negative side effects while improving therapeutic efficacy when administered directly to cancer. MDA-MB-231 cells treated with LTZ-BBR@AA-AuNPs for 48 h exhibited IC50 values of 2.04 ± 0.011 μg/mL, indicating potent cytotoxicity against cells. Furthermore, the nanoparticles demonstrated excellent stability throughout the duration of the treatment.

LINC01116 affects patient survival differently and is dissimilarly expressed in ER+ and ER- breast cancer samples

BACKGROUND

Breast cancer is the most commonly detected cancer and one of the leading causes of cancer mortality. Emerging evidence supports that aberrant expression of lncRNAs is correlated with tumor progression and various aspects of tumor development.

AIM

This study aimed to evaluate the expression pattern of LINC01116 in breast cancer tissues and investigate the impact of LINC01116 on patients' survival.

METHODS AND RESULTS

Microarray and qRT-PCR data analysis were performed, and the KM-plotter database was used in this study. In addition, the gain of function approach was performed to examine the effect of LINC01116 on breast cancer cells in-vitro. The results exhibited that LINC01116 is meaningfully upregulated in the ER+ tumor specimens compared to the ER- ones. Also, relative to normal tissues, the expression of LINC01116 in ER+ and ER- tumor tissues significantly increased and decreased, respectively. ROC curve analysis revealed the power of LINC01116 in distinguishing ER+ from ER- samples. Additionally, the Kaplan-Meier survival analysis showed that the LINC01116 expression positively correlates with survival probability in all as well as ER+ patients. However, this correlation was negative in ER- patients. Furthermore, our results showed that the overexpression of LINC01116 induces TGF-β signaling in ER- cells (MDA-MB-231), and microarray data analysis revealed that LINC01116 is significantly upregulated in 17β-Estradiol treated MCF7 cells.

CONCLUSION

In conclusion, our results suggest that LINC01116 can be a potential biomarker in distinguishing ER+ and ER- tissues and has different effects on patients' survival based on ER status by affecting TGF-β and ER signaling.

A review of FDA approved drugs and their formulations for the treatment of breast cancer

Breast cancer is one of the most diagnosed solid cancers globally. Extensive research has been going on for decades to meet the challenges of treating solid tumors with selective compounds. This article aims to summarize the therapeutic agents which are either being used or are currently under approval for use in the treatment or mitigation of breast cancer by the US FDA, to date. A structured search of bibliographic databases for previously published peer-reviewed research papers on registered molecules was explored and data was sorted in terms of various categories of drugs used in first line/adjuvant therapy for different stages of breast cancer. We included more than 300 peer-reviewed papers, including both research and reviews articles, in order to provide readers an useful comprehensive information. A list of 39 drugs are discussed along with their current status, dose protocols, mechanism of action, pharmacokinetics, possible side effects, and marketed formulations. Another interesting aspect of the article included focusing on novel formulations of these drugs which are currently in clinical trials or in the process of approval. This exhaustive review thus shall be a one-stop solution for researchers who are working in the areas of formulation development for these drugs.

Role of EGFR and FASN in breast cancer progression

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

Clinical diagnostic biomarker "circulating tumor cells" in breast cancer - a meta-analysis

Objective

Using meta-analysis, we evaluate circulating tumor cells(CTCs) as a potential diagnostic tool for breast cancer.

Methods

A document search was conducted using publicly available databases up to May 2021. Specific inclusion and exclusion criteria were formulated and summarize relevant data through literature types, research types, case populations, samples, etc. Subgroup analysis of documents based on regions, enrichment methods, and detection methods. The included research projects were evaluated using DeeKs' bias, and evaluation indicators such as specificity (SPE), sensitivity (SEN), diagnosis odds ratio (DOR) were used as evaluation indicators.

Results

16 studies on the use of circulating tumor cells to diagnose breast cancer were included in our meta-analysis. Overall sensitivity value was 0.50 (95%CI:0.48-0.52), specificity value was 0.93 (95%CI:0.92- 0.95), DOR value was 33.41 (95%CI:12.47-89.51), and AUC value was 0.8129.

Conclusion

In meta-regressions and subgroup analysis, potential heterogeneity factors were analyzed, but the source of heterogeneity is still unclear. CTCs, as a novel tumor marker, have a good diagnostic value, but its enrichment and detection methods still need to continue to be developed to improve detection accuracy. Therefore, CTCs can be used as an auxiliary means of early detection, which is helpful to the diagnosis and screening of breast cancer.

Afterglow/Photothermal Bifunctional Polymeric Nanoparticles for Precise Postbreast-Conserving Surgery Adjuvant Therapy and Early Recurrence Theranostic

Adjuvant whole-breast radiotherapy is essential for breast cancer patients who adopted breast-conserving surgery (BCS) to reduce the risk of local recurrences, which however suffer from large-area and highly destructive ionizing radiation-induced adverse events. To tackle this issue, an afterglow/photothermal bifunctional polymeric nanoparticle (APPN) is developed that utilizes nonionizing light for precise afterglow imaging-guided post-BCS adjuvant second near-infrared (NIR-II) photothermal therapy. APPN consists of a tumor cell targeting afterglow agent, which is doped with a NIR dye as an afterglow initiator and a NIR-II light-absorbing semiconducting polymer as a photothermal transducer. Such a design realizes precise afterglow imaging-guided NIR-II photothermal ablation of minimal residual breast tumor foci after BCS, thus achieving complete inhibition of local recurrences. Moreover, APPN enables early diagnosis and treatment of local recurrence after BCS. This study thus provides a nonionizing modality for precision post-BCS adjuvant therapy and early recurrence theranostic.

Linguistic analysis of plain language summaries and corresponding scientific summaries of Cochrane systematic reviews about oncology interventions

BACKGROUND

Cochrane plain language summaries (PLSs) are an important format to present high-quality healthcare evidence to patients with cancer and their families. They should be written in a way everyone can understand, since they serve as a tool in decision-making and present a bridge to overcome the gap between the healthcare users and professionals.

OBJECTIVE

The aim of the study was to assess the language characteristics of PLSs of Cochrane systematic reviews of oncology interventions in comparison with corresponding Cochrane scientific abstracts (SAs).

METHODS

In this cross-sectional study, we included all Cochrane PLSs and SAs of systematic reviews of oncology interventions available in the Cochrane Database of Systematic Reviews. We assessed text readability, measured using the Simple Measure of Gobbledygook (SMOG) index, and the prevalence of words related to different language tones (clout, authenticity, emotions and analytical tones). Two independent assessors categorized the conclusiveness of the efficacy of interventions into nine categories.

RESULTS

The overall median SMOG index for 275 PLSs was 13.0 (95% confidence interval [CI] 12.8-13.3). Readability scores did not differ across Cochrane Review Groups. SAs had a higher readability index than the corresponding PLSs (median = 16.6, 95% CI = 16.4-16.8). Regarding linguistic characteristics, PLSs were shorter than SAs, with less use of analytical tone, but more use of a positive emotional tone and authenticity. Overall, the 'Unclear' category of conclusiveness was the most common among all PLSs. Also, PLSs with 'No evidence' conclusions were the shortest and had the lowest SMOG index.

CONCLUSION

PLSs of Cochrane systematic reviews of oncological interventions have low readability and most give unclear conclusions about the efficacy of interventions. PLSs should be simplified so that patients and their families can benefit from appropriate health information on evidence synthesis. Further research is needed into reasons for unclear language to describe evidence from oncology trials.

Homotypic Entosis as a Potential Novel Diagnostic Marker in Breast Cancer

Homotypic entotic figures, which are a form of "cell-in-cell" structures, are considered a potential novel independent prognostic marker in various cancers. Nevertheless, the knowledge concerning the biological role of this phenomenon is still unclear. Since breast cancer cells are remarkably entosis-competent, we aimed to investigate and compare the frequency of entoses in a primary breast tumor and in its lymph node metastasis. Moreover, as there are limited data on defined molecular markers of entosis, we investigated entosis in correlation with classical breast cancer biomarkers used in routine pathomorphological diagnostics (HER2, ER, PR, and Ki67). In the study, a cohort of entosis-positive breast cancer samples paired into primary lesions and lymph node metastases was used. The inclusion criteria were a diagnosis of NOS cancer, lymph node metastases, the presence of entotic figures in the primary lesion, and/or lymph node metastases. In a selected, double-negative, HER2-positive NOS breast cancer case, entoses were characterized by a correlation between an epithelial-mesenchymal transition and proliferation markers. We observed that in the investigated cohort entotic figures were positively correlated with Ki67 and HER2, but not with ER or PR markers. Moreover, for the first time, we identified Ki67-positive mitotic inner entotic cells in clinical carcinoma samples. Our study performed on primary and secondary breast cancer specimens indicated that entotic figures, when examined by routine HE histological staining, present potential diagnostic value, since they correlate with two classical prognostic factors of breast cancer.

Targeting Breast Cancer: An Overlook on Current Strategies

Breast cancer (BC) is one of the most widely diagnosed cancers and a leading cause of cancer death among women worldwide. Globally, BC is the second most frequent cancer and first most frequent gynecological one, affecting women with a relatively low case-mortality rate. Surgery, radiotherapy, and chemotherapy are the main treatments for BC, even though the latter are often not aways successful because of the common side effects and the damage caused to healthy tissues and organs. Aggressive and metastatic BCs are difficult to treat, thus new studies are needed in order to find new therapies and strategies for managing these diseases. In this review, we intend to give an overview of studies in this field, presenting the data from the literature concerning the classification of BCs and the drugs used in therapy for the treatment of BCs, along with drugs in clinical studies.

Advanced Phytochemical-Based Nanocarrier Systems for the Treatment of Breast Cancer

As the world's most prevalent cancer, breast cancer imposes a significant societal health burden and is among the leading causes of cancer death in women worldwide. Despite the notable improvements in survival in countries with early detection programs, combined with different modes of treatment to eradicate invasive disease, the current chemotherapy regimen faces significant challenges associated with chemotherapy-induced side effects and the development of drug resistance. Therefore, serious concerns regarding current chemotherapeutics are pressuring researchers to develop alternative therapeutics with better efficacy and safety. Due to their extremely biocompatible nature and efficient destruction of cancer cells via numerous mechanisms, phytochemicals have emerged as one of the attractive alternative therapies for chemotherapeutics to treat breast cancer. Additionally, phytofabricated nanocarriers, whether used alone or in conjunction with other loaded phytotherapeutics or chemotherapeutics, showed promising results in treating breast cancer. In the current review, we emphasize the anticancer activity of phytochemical-instigated nanocarriers and phytochemical-loaded nanocarriers against breast cancer both in vitro and in vivo. Since diverse mechanisms are implicated in the anticancer activity of phytochemicals, a strong emphasis is placed on the anticancer pathways underlying their action. Furthermore, we discuss the selective targeted delivery of phytofabricated nanocarriers to cancer cells and consider research gaps, recent developments, and the druggability of phytoceuticals. Combining phytochemical and chemotherapeutic agents with nanotechnology might have far-reaching impacts in the future.

Potential Oral Anticancer Therapeutic Agents of Hexahydrocurcumin-Encapsulated Chitosan Nanoparticles against MDA-MB-231 Breast Cancer Cells

Hexahydrocurcumin-encapsulated chitosan nanoparticles (HHC-CS-NPs) were formulated by oil-in-water emulsification and ionotropic gelation and optimized using the Box-Behnken design. The particle size, zeta potential, and encapsulation efficiency of the optimized HHC-CS-NPs were 256 ± 14 nm, 27.3 ± 0.7 mV, and 90.6 ± 1.7%, respectively. The TEM analysis showed a spherical shape and a dense structure with a narrow size distribution. The FT-IR analysis indicated no chemical interaction between the excipients and the drugs in the nanoparticles, but the existence of the drugs was molecularly dispersed in the nanoparticle matrices. The drug release profile showed a preliminary burst release followed by a sustained release under simulated gastrointestinal (GI) and physiological conditions. A stability study suggested that the HHC-CS-NPs were stable under UV light, simulated GI, and body fluids. The in vitro bioaccessibility and bioavailability of the HHC-CS-NPs were 2.2 and 6.1 times higher than those of the HHC solution, respectively. The in vitro evaluation of the antioxidant, anti-inflammatory, and cytotoxic effects of the optimized HHC-CS-NPs demonstrated that the CS-NPs significantly improved the biological activities of HHC in radical scavenging, hemolysis protection activity, anti-protein denaturation, and cytotoxicity against MDA-MB-231 breast cancer cells. Western blot analysis showed that the apoptotic protein expression of Bax, cytochrome C, caspase-3, and caspase-9, were significantly up-regulated, whereas the anti-apoptotic protein Bcl-2 expression was down-regulated in the HHC-CS-NP-treated cells. Our findings suggest that the optimized HHC-CS-NPs can be further developed as an efficient oral treatment for breast cancer.

Active Gαi/o mutants accelerate breast tumor metastasis via the c-Src pathway

Constitutively active mutations in the Gαi2 and GαoA subunits of heterotrimeric G proteins have been identified in several human cancers including breast cancer, but their functional significance in tumorigenesis and metastasis has not been well characterized. In this study, we show that expression of the constitutively active GαoAR243H and Gαi2R179C mutants alone was insufficient to induce mammary tumor formation in mice. However, in transgenic mouse models of breast cancer induced by Neu expression or PTEN loss, we found that the Gαi2R179C mutant enhanced spontaneous lung metastasis while having no effect on primary tumor initiation and growth. Additionally, we observed that ectopic expression of the GαoAR243H and Gαi2R179C mutants in tumor cells promote cell migration in vitro as well as dissemination into multiple organs in vivo by activating c-Src signaling. Thus, our study uncovers a critical function of Gαi/o signaling in accelerating breast cancer metastasis via the c-Src pathway. This work is clinically significant, as it can potentially pave the way to personalized therapies for patients who present with active Gαi/o mutations or elevated Gαi/o signaling by targeting c-Src to inhibit breast cancer metastasis.

Aberrant promoter hypermethylation of miR-335 and miR-145 is involved in breast cancer PD-L1 overexpression

PD-L1 is one of the most important immune checkpoint molecules in breast cancer that plays an important role in suppressing the immune system when confronted with tumor cells and is regulated by various microRNAs. Among them, microRNA-335-3p and microRNA-145-5p, regulated by DNA methylation, have tumor suppressor activities. We studied the role of miR-335 and -145 on PD-L1 suppression in breast cancer. The expression of miR-355 and miR-145 was significantly downregulated in BC tissues and cell lines compared to their controls, and their downregulation was negatively correlated with PD-L1 overexpression. In-silico and luciferase reporter systems confirmed that miR-335 and -145 target PD-L1. In BC tissues and cell lines, cancer-specific methylation was found in CpG-rich areas upstream of miR-335 and-145, and up-regulation of PD-L1 expression was connected with hypermethylation (r = 0.4089, P = 0.0147, and r = 0.3373, P = 0.0475, respectively). The higher levels of miR-355 and -145 in BC cells induced apoptosis, arrested the cell cycle, and reduced proliferation significantly. In summary, we found that miR-335 and -145 are novel tumor suppressors inactivated in BC, and these miRs may serve as potential therapeutic targets for breast cancer treatment.