Review of Breast Cancer Pathologigcal Image Processing

Identification of a glycolysis-related miRNA Signature for Predicting Breast cancer Survival

Breast cancer (BC) is a common type of cancer and has a poor prognosis. In this study, we collected the mRNA and miRNA expression profiles of BC patients were obtained from The Cancer Genome Atlas (TCGA) to explore a novel prognostic strategy for BC patients using bioinformatics tools. We found that six glycolysis-related miRNAs (GRmiRs, including hsa-mir-1247, hsa-mir148b, hsa-mir-133a-2, has-mir-1307, hsa-mir-195 and hsa-mir-1258) were correlated with prognosis of BC samples. The risk score model was established based on 6 prognosis-associated GRmiRs. The outcome of high risk group was significantly poorer. Cox regression analysis showed that risk score was an independent prognostic factor. Differentially expressed genes identified between high and low risk groups were mainly enriched in inflammation and immune-related signaling pathways. The proportion of infiltration of 12 kinds of immune cells in high and low risk groups were significantly different. Risk score was closely associated with many immune indexes. Multiple DEGRGs and miRNAs were associated with drugs. In conclusion, glycolysis-related miRNA signature effectively predicts BC prognosis.

The influence of body image on psychological symptomatology in breast cancer women undergoing intervention: a pre-post study

Introduction

Body image concerns related to breast cancer surgery may challenge patients' quality of life and their treatment outcomes, thus representing a key aspect to be assessed in the psycho-oncological settings. The present longitudinal study is aimed to (1) investigate the association between preoperative body image and postoperative psychological symptoms in breast cancer patients; (2) explore the impact of pre-/post-surgery variation in body image on psychological symptomatology.

Methods

N = 72 women undergoing breast cancer surgery were preoperatively screened (T1) using the Body Uneasiness Test (BUT) and were assessed postoperatively (T2) using the Symptom Checklist-90 Revised (SCL-90-R) and re-administered the BUT. Spearman's correlation was used to investigate the relationship between age, preoperative body image and postoperative psychological symptoms, and variation in body image. To predict post-surgical psychological symptomatology, two separated multiple regression models were used to evaluate preoperative body image and its variation after surgery controlling for covariates (i.e., education; intervention type). P significance was set as 0.05 for all analyses and adjusted for multiple comparisons.

Results

At T1, anxiety in relation to body image scores emerged as the most frequently experienced psychological symptomatology after surgery (all adjusted p < 0.05). Significant correlations were observed between all SCL-90-R scores at T2 and avoidance behaviors and depersonalization scores at T1. The associations were most significantly strong for somatization, depression, anxiety, and hostility (all adjusted p < 0.05). However, change in body image between pre- and post-intervention was not associated with psychological symptomatology at T2 (all adjusted p > 0.05). Pre-surgery body avoidance was significantly associated with post-intervention psychological symptoms (SOMβ = 0.453, p = 0.0001; DEPβ = 0.507, p = 0.0001; AXβ = 0.459, p = 0.0001; HOSβ = 0.410, p=. 0001). However, increased weight phobia between pre- and post-surgery was statistically associated with increased somatization, anxiety, depression and hostility at T2 (βSOM = 0.439, p = 0.0001; βDEP = 0.454, p = 0.0001; βANX = 0.471, p = 0.0001).

Discussion

Overall, pre-/post-intervention body concerns were significantly associated with primary psychological symptoms in breast cancer patients undergoing surgery. Higher levels of body avoidance and weight phobia were significantly associated with the primary psychological dimensions assessed. As body concerns might act as quality-of-life predictors, their evaluation is crucial in fostering patients' well-being and treatment adherence.

A New Co(II)-coordination Polymer: Fluorescence Performances, Loaded with Paclitaxel-hydrogel on Breast Cancer and Molecular Docking Study

In the current context of the increasing incidence of breast cancer, we aim to develop an efficient drug carrier for breast cancer by constructing an innovative complex consisting of a metal-organic framework (MOF) and a hydrogel. The aim of this initiative is to provide new ideas and tools for breast cancer treatment strategies through scientific research, so as to address the current challenges in breast cancer treatment. In the present study, by employment of a new Co(II)-based coordination polymer with the chemical formula of [Co(H2O)(CH3OH)L]n (1) (H2L = 5-(1 H-tetrazol-5-yl)nicotinic acid) was solvothermally synthesized by reaction of Co(NO3)2·6H2O a mixed solvent of MeOH and water. The characteristics of ligand-based absorption and emission, as unveiled by ultraviolet and fluorescence spectroscopy tests, offer insights into the distinctive electronic transitions and structural features originating from the ligand in compound 1. Using natural polysaccharide hyaluronic acid (HA) and carboxymethyl chitosan (CMCS) as raw materials, HA/CMCS hydrogels were successfully prepared by chemical method and their internal morphology was studied by scanning electron microscopy. Using paclitaxel as a drug model, we further designed and synthesized a novel metal gel particle-loaded paclitaxel drug and evaluated its inhibitory effect on breast cancer cells. Finally, the hypothesized interactions between the complex and the receptor have been confirmed through molecular docking simulation, and multiple polar interactions have been verified, which further proves the potential anti-cancer capability and excellent bioactivity. Based on this, this composite material prepared from a novel Co(II)-coordinated polymer with paclitaxel hydrogel could provide a useful pathway for the identification and treatment of breast cancer.

tsRNA: A Promising Biomarker in Breast Cancer

tRNA-derived small RNAs (tsRNAs) are a novel class of non-coding small RNAs, generated from specific cleavage sites of tRNA or pre-tRNA. tsRNAs can directly participate in RNA silencing, transcription, translation, and other processes. Their dysregulation is closely related to the occurrence and development of various cancers. Breast cancer is one of the most common and fastest-growing malignant tumors in humans. tsRNAs have been found to be dysregulated in breast cancer, serving as a new target for exploring the pathogenesis of breast cancer. They are also considered new tumor markers, providing a basis for diagnosis and treatment. This article reviews the generation, classification, mechanism of action, function of tsRNAs, and their biological effects and related mechanisms in breast cancer, in the hope of providing a new direction for the diagnosis and treatment of breast cancer.

Effects of psychological intervention on negative emotions and psychological resilience in breast cancer patients after radical mastectomy

Breast cancer (BC)is the most common malignant tumor in women, and the treatment process not only results in physical pain but also significant psychological distress in patients. Psychological intervention (PI) has been recognized as an important approach in treating postoperative psychological disorders in BC patients. It has been proven that PI has a significant therapeutic effect on post-operative psychological disorders, improving patients' negative emotions, enhancing their psychological resilience, and effectively enhancing their quality of life and treatment compliance.

Thyroid Hormone Changes Correlate to Combined Breast Cancer with Primary Thyroid Cancer

Background

Breast cancer and thyroid cancer are two prevalent malignancies in women, and a potential association between the two diseases has been suggested.

Methods

This retrospective case-control study was conducted involving 97 patients with breast cancer and thyroid cancer (BC-TC group) and 97 age-matched patients with breast cancer alone (BC group). Thyroid hormone levels, including triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH), were analyzed in healthy controls, BC patients, and BC-TC patients.

Results

BC-TC patients exhibited a higher rate of estrogen receptor (ER) and progesterone receptor (PR) positivity compared to BC patients. Serum T3 levels were significantly decreased in BC and BC-TC patients compared to healthy controls. However, there was no significant difference in T3 levels between BC and BC-TC patients. Serum TSH levels were significantly higher in BC-TC patients compared to BC patients.

Conclusion

ER positivity, PR positivity, and serum TSH levels greater than 4.45 mU/L were independent risk factors for primary thyroid cancer in breast cancer patients.

Impact of evidence-based nursing on postoperative psychological state, quality of life, and function of affected limbs in breast cancer patients: An observational study

To analyze the effect of evidence-based nursing on postoperative psychological state, quality of life, and function of affected limbs in breast cancer (BC) patients. This study is a retrospective analysis. The clinical data of 122 BC patients in our hospital were selected and divided into evidence-based group and routine group according to different nursing programs. Patients in evidence-based group received evidence-based nursing, and patients in the conventional group received routine nursing intervention. The acceptance level of BC diagnosis in evidence-based group was significantly higher than that in the conventional group, showing statistical significance (P < .05). After intervention, Self-rating Anxiety Scale and Self-rating Depression Scale scores of both groups were significantly reduced, and the Self-rating Anxiety Scale and Self-rating Depression Scale scores in evidence-based group were significantly lower than those in conventional group, showing statistically significant difference (P < .05); Self-Esteem Scale scores were significantly increased in both groups after intervention, and the scores in evidence-based group were significantly higher than those in conventional group, showing statistically significant difference (P < .05). After intervention, in evidence-based group, the proportion of patients without edema was significantly increased, while the proportion of patients with mild, moderate and severe edema was significantly decreased, exhibiting statistically significant difference (P < .05). After intervention, the circumference difference of the healthy side and the affected side decreased significantly, which was much lower in evidence-based group, showing statistically significant difference (P < .05). After intervention, range of motion of the upper limbs increased significantly between the 2 groups, which was much higher in evidence-based group, exhibiting statistical significance (P < .05). The scores of quality of life (role, emotion, body, cognition and society dimension) in evidence-based group were higher than those in conventional group, exhibiting statistically significant difference (P < .05). Evidence-based nursing can develop more targeted nursing measures according to patients' problems, thus effectively promoting the recovery of upper limb function of BC patients after surgery.

Copper Chaperone for Superoxide Dismutase Subtypes as a Prognostic Marker in Luminal B Breast Cancer

Background

Copper chaperone for superoxide dismutase (CCS) is an essential component of the oxidation-reduction system. In breast cancer cells, CCS expression is highly up-regulated, which contributes to cellular proliferation and migration. Breast cancer is a multifaceted disease with different tumor prognoses and responses to clinical treatments, which may be associated with multiple molecular subtypes of CCS.

Methods

The CCS expression patterns in breast cancer were investigated by TNMplot, cBioPortal, and HPA network database. The correlation of CCS expression with clinicopathological parameters was analyzed using the UALCAN database. The Cancer Genome Atlas (TCGA) data set was used to analyze the Clinical characteristics of CCS in luminal B patients. The bc-GenExMiner database was used to analyze the effects of BReast-CAncer susceptibility gene (BRCA)1/2, TP53 mutation status, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER) expression on CCS expression. The survival curves and prognostic value of CCS in luminal B breast cancer were performed through Kaplan-Meier curves, univariate and multivariate Cox regression using the PrognoScan, bc-GenExMiner, and Clinical bioinformatics analysis platform.

Results

We found that CCS expression was associated with patient age, race, ER, and PR status. We also discovered that BRCA1/2 mutations had an effect on CCS expression. The luminal B subtype had the highest CCS expression, which was linked to poor survival compared with other subtypes. In addition, Kaplan-Meier curve analysis showed that luminal B patients with high CCS mRNA expression showed a poor survival and the CCS gene is an independent predictor of outcome in patients with luminal B breast cancer by univariate and multivariate Cox regression.

Conclusions

Our findings emphasize the significant expression of CCS in luminal B breast cancer and its potential as an autonomous prognostic determinant for this specific molecular subtype. These findings suggest that CCS holds promise as a prospective marker for the treatment of luminal B breast cancer.

Comparison of the diagnostic efficacy of mathematical models in distinguishing ultrasound imaging of breast nodules

This study compared the diagnostic efficiency of benign and malignant breast nodules using ultrasonographic characteristics coupled with several machine-learning models, including logistic regression (Logistics), partial least squares discriminant analysis (PLS-DA), linear support vector machine (Linear SVM), linear discriminant analysis (LDA), K-nearest neighbor (KNN), artificial neural network (ANN) and random forest (RF). The clinical information and ultrasonographic characteristics of 926 female patients undergoing breast nodule surgery were collected and their relationships were analyzed using Pearson's correlation. The stepwise regression method was used for variable selection and the Monte Carlo cross-validation method was used to randomly divide these nodule cases into training and prediction sets. Our results showed that six independent variables could be used for building models, including age, background echotexture, shape, calcification, resistance index, and axillary lymph node. In the prediction set, Linear SVM had the highest diagnosis rate of benign nodules (0.881), and Logistics, ANN and LDA had the highest diagnosis rate of malignant nodules (0.910~0.912). The area under the ROC curve (AUC) of Linear SVM was the highest (0.890), followed by ANN (0.883), LDA (0.880), Logistics (0.878), RF (0.874), PLS-DA (0.866), and KNN (0.855), all of which were better than that of individual variances. On the whole, the diagnostic efficacy of Linear SVM was better than other methods.

Enhancing the Breast Histopathology Image Analysis for Cancer Detection Using Variational Autoencoder

A breast tissue biopsy is performed to identify the nature of a tumour, as it can be either cancerous or benign. The first implementations involved the use of machine learning algorithms. Random Forest and Support Vector Machine (SVM) were used to classify the input histopathological images into whether they were cancerous or non-cancerous. The implementations continued to provide promising results, and then Artificial Neural Networks (ANNs) were applied for this purpose. We propose an approach for reconstructing the images using a Variational Autoencoder (VAE) and the Denoising Variational Autoencoder (DVAE) and then use a Convolutional Neural Network (CNN) model. Afterwards, we predicted whether the input image was cancerous or non-cancerous. Our implementation provides predictions with 73% accuracy, which is greater than the results produced by our custom-built CNN on our dataset. The proposed architecture will prove to be a new field of research and a new area to be explored in the field of computer vision using CNN and Generative Modelling since it incorporates reconstructions of the original input images and provides predictions on them thereafter.

Comprehensive Analysis Reveals PTK6 as a Prognostic Biomarker Involved in the Immunosuppressive Microenvironment in Breast Cancer

The significant mortality rate that is currently experienced by female breast cancer (BC) patients highlights the importance of locating potent and dependable biomarkers in BC patients. Over the past few years, a number of studies have demonstrated that PTK6 was dysregulated in a variety of cancers. However, its expression and the clinical importance it may have in patients with BC have not been explored. Based on datasets from the TCGA database and GTEx database, we studied the expressions and functions of PTK6 across 33 different kinds of cancer. In this study, we investigated the differential expression of PTK6 in tumor tissue compared to nontumor tissue as well as in various stages of cancer. ROC assays were used to conduct an investigation into the diagnostic potential of PTK6 in BC. After that, the Kaplan-Meier method, univariate analysis, and multivariate analysis were carried out in order to investigate the PTK6 gene's potential prognostic significance in patients with BC. ssGSEA was utilized in order to conduct an investigation of the immune infiltration. In this study, we discovered that the expressions of PTK6 were significantly raised in the majority of different types of malignancies, including BC. The diagnostic value of PTK6 expression was validated by ROC tests, demonstrating an AUC greater than 0.7. A positive PR, ER, and HER2 status was found to be related with high expression levels of PTK6. According to the results of a survival analysis, patients who had a high level of PTK6 expression had a shorter overall survival time than those who had a low level of PTK6 expression. Besides, we observed that PTK6 expressions were positively correlated with the abundance of NK CD56bright cells and Th17 cells and negatively correlated with that of Th1 cells, macrophages, B cells, T cells, aDC, DC, cytotoxic cells, Tem, TFH, NK CD56dim cells, Treg, and Tgd. In conclusion, PTK6 expression was found to be linked with the clinical phenotype of BC, and as a result, this finding may have consequences for the diagnosis, prognosis, and treatment of individuals with BC.