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Breast cancer (BrC) is one of the most common causes of death among women worldwide. Images of the breast (mammography or ultrasound) may show an anomaly that represents early indicators of BrC. However, accurate breast image interpretation necessitates labor-intensive procedures and highly skilled medical professionals. As a second opinion for the physician, deep learning (DL) tools can be useful for the diagnosis and classification of malignant and benign lesions. However, due to the lack of interpretability of DL algorithms, it is not easy to understand by experts as to how to predict a label. In this work, we proposed multitask U-Net Saliency estimation and DL model-based breast lesion segmentation and classification using ultrasound images. A new contrast enhancement technique is proposed to improve the quality of original images. After that, a new technique was proposed called UNET-Saliency map for the segmentation of breast lesions. Simultaneously, a MobileNetV2 deep model is fine-tuned with additional residual blocks and trained from scratch using original and enhanced images. The purpose of additional blocks is to reduce the number of parameters and better learning of ultrasound images. Training is performed from scratch and extracted features from the deeper layers of both models. In the later step, a new cross-entropy controlled sine-cosine algorithm is developed and selected best features. The main purpose of this step is the reduction of irrelevant features for the classification phase. The selected features are fused in the next step by employing a serial-based Manhattan Distance (SbMD) approach and classified the resultant vector using machine learning classifiers. The results indicate that a wide neural network (W-NN) obtained the highest accuracy of 98.9% and sensitivity rate of 98.70% on the selected breast ultrasound image dataset. The comparison of the proposed method accuracy is conducted with state-of-the-art (SoArt) techniques which show the improved performance.

This study aims to develop a safe and effective multi-parameter MRI-based molecular subtype prediction model for breast cancer, emphasizing the advantages of this multi-parameter approach over single-parameter models. This study retrospectively collected and organized MRI data from 318 breast cancer patients at Liaoning Provincial Cancer Hospital, including dynamic contrast-enhanced MRI (DCE-MRI, abbreviated as DCE), diffusion weighted MRI (DWI-MRI, abbreviated as DWI), T1-weighted MRI (T1WI-MRI, abbreviated as T1WI), and T2-weighted MRI (T2WI-MRI, abbreviated as T2WI). The dataset includes 57 cases of Luminal A type, 162 cases of Luminal B type, 46 cases of human epidermal growth factor receptor-2 (HER-2) overexpression type, and 53 cases of triple-negative type. Predictive models were established using four single-parameter MRI methods and seven multi-parametric MRI methods, employing quantitative feature extraction. Model performance was evaluated through the area under the curve (AUC) and balanced accuracy (BA). In the single-parameter MRI models, the T2WI-MRI model demonstrated the best predictive performance for four-class classification, with average AUC and BA values of 0.794 and 0.518, respectively. In contrast, the multi-parameter model combining DWI+T2WI exhibited even better performance, with these metrics reaching 0.823 and 0.565, respectively. The multi-parameter feature fusion model for breast cancer molecular subtypes prediction, utilizing DWI+T2WI, exhibited superior BA and AUC values compared to models based solely on single-parameter MRI. It showed enhanced predictive capabilities for Luminal A, Luminal B, HER-2 overexpression, and triple-negative subtypes. Therefore, the multi-parameter MRI-based model offers improved predictive performance over single-parameter models.

Objective: This study aims to explore the use of machine learning algorithms for predicting disease classification. Methods: An integrated algorithm (KPLSKELM) was proposed in this study. The algorithm employed kernel principal component analysis to transform the original data into a high-dimensional feature space, thereby enhancing its linear separability. It used the sparrow search algorithm (SSA) to optimize the weight matrix and parameters of the kernel extreme learning machine (KELM). The algorithm incorporated a Gaussian perturbation search mechanism to refine the population initialization strategy so as to mitigate the issues of poor convergence rate and susceptibility to local optima in the later SSA iterations. Lévy flight perturbations were introduced during the foraging search process of the sparrow population to guide the population in moving appropriate step sizes, thereby increasing the diversity of the spatial search. The proposed method was experimentally validated using a binary classification breast cancer dataset collected by Dr. William H. Wolberg from a Wisconsin hospital in the United States and a multiclass classification dataset of electrocardiographic recordings during childbirth. Multiple metrics were adopted to evaluate the classification performance. Results: The accuracy and F1_score of the KELM model remained relatively low across different percentages of the training set, although a recall of 1.0000 was consistently achieved. Both the SSA-improved KELM and the Lévy-improved SSA-optimized KELM algorithms exhibited better performance in terms of the comprehensive metric F1_score and improved with the increase in the percentage of the training set. The KPLSKELM model outperformed others in all metrics, with accuracy, precision, recall, and F1_score approaching or reaching the highest levels when using 90% of the training set. Conclusions: The proposed method demonstrated excellent performance in various disease prediction tasks, holding high practical application value. It provided a reference for further assisting clinicians in making more precise treatment decisions.

Today, due to the problem of environmental pollution, water, and other factors have caused many dangerous diseases, including cancer. According to recent statistics, breast cancer is one of the leading diseases in women, and this disease tends to increase more and more. To detect and diagnose the disease, doctors perform many examinations: self-examination, clinical examination, X-ray, ultrasound screening, etc., in which X-ray is a highly effective method. This study proposes an approach to detecting and classifying breast cancer on an X-ray dataset using a refined Vision Transformer (ViT), ViT-B32. The considered dataset contains about 7000 X-ray images from patients aged 27 to 90, labeled as malignant, benign, or normal. As presented in scenarios, the study yielded positive results, with 91% to 94% in ACC and F1-score metrics. Furthermore, it has shown that the results obtained for breast cancer detection on X-ray images using the fine-tuned ViT architecture outperformed CNN models such as VGG16, MobileNet, Xception, ResNet50, and some state-of-the-art approaches.

The texaphyrins are prototypical metal-coordinating expanded porphyrins. They represent a burgeoning class of pharmacological agents that show promise for an array of medical applications. Currently, two different water-soluble lanthanide texaphyrins, namely motexafin gadolinium (Gd-Tex, 1) and motexafin lutetium (Lu-Tex, 2), are involved in multi-center clinical trials for a variety of indications. The first of these agents, XCYTRIN^® (motexafin gadolinium) Injection, is being evaluated as a potential X-ray radiation enhancer in a randomized Phase III clinical trial in patients with brain metastases. The second, in various formulations, is being evaluated as a photosensitizer for use in: (i) the photodynamic treatment of recurrent breast cancer (LUTRIN^® Injection; now in Phase IIb clinical trials); (ii) photoangioplastic reduction of atherosclerosis involving peripheral and coronary arteries (ANTRIN^® Injection; now in Phase II and Phase I clinical trials, respectively); and (iii) light-based age-related macular degeneration (OPTRIN™ Injection; currently under Phase II clinical evaluation), a vision-threatening disease of the retina. In this article, these developments, along with fundamental aspects of the underlying chemistry are reviewed.

DESMAI is a framework for helping experts in breast cancer diagnosis. It allows experts to explore digital mammographic image databases according to a certain topology criteria when they need to decide whether a sample is benign or malignant. In this way, they are provided with complementary information to enhance their interpretations and predictions. The core of the application is a SOMCBR system, which is variant of a Case-Based Reasoning system featured by organizing the case memory using a Self-Organizing Map. The article presents a strategy for improving the SOMCBR reliability thanks to the relations between cases and clusters. The approach is successfully applied in DESMAI for estimating, if it is possible, the class of the recovered mammographies.

Development of a number of diseases like cardiovascular diseases and cancer has been related with abnormalities of certain trace elements in some tissues. The purpose of this study was to investigate the levels of trace elements in breast cancer patients in comparison with healthy controls. Particle induced X-ray emission (PIXE) technique was employed to measure the hair trace element concentrations in 30 cancer patients and 30 healthy controls. A 2.2 MeV proton beam was employed to excite the biological samples. The concentrations of Fe and Cu ($p<0.05$) in the hair of cancer patients were found to be higher compared to those of healthy controls, while the concentration of Zn ($p<0.05$) was found to be lower. No significant difference was observed for sulfur concentration between the two groups. Also, no meaningful difference was observed in the concentrations of K, Ca, Ti as well as ratios of Cu/Zn and Cu/Fe in the hair of the two groups ($p<0.05$). These abnormalities could potentially be used as a means of breast cancer screening in women.

Breast cancer is a common malignant tumor of which pathogenic genes are widely studied. Since gene pairs are considered as biomarkers to identify cancer patients, in this paper, we use information theory to study the collaboration features of gene pairs. The measure of synergy based on mutual information (MI) is introduced to determine whether genes collaborate with each other in breast cancer. Part mutual information (PMI) is introduced to further select collaborative genes and construct a synergy network, which overcomes the shortage of MI. Furthermore, a dual network of synergy network is constructed and structural indices are calculated to identify vital genes. By decision tree and support vector machine, synergy is considered as a suitable index and dual network with PMI improves the accuracy of cancer identification. This method can be extended to identify other biological phenomenon and find collaborative genes as biomarkers.

The study examined the pattern of and factors associated with use of alternative medicine (AM) among Chinese breast cancer patients. An analytical, cross-sectional survey of 352 breast cancer patients from two breast cancer centers was conducted in 1997. Amongst the respondents, the usage rate of alternative medicine was 27.8%. Factors forming the use of AM included being young to middle-aged, having higher education and a belief that AM would enhance orthodox treatment. A substantial proportion of Chinese breast cancer patients use AM besides conventional medicine. There is a need to integrate AM with conventional medicine to improve the service provision for cancer patients.

Breast cancer is the most common cancer among women worldwide. Discomfort and fatigue are usually arisen from anticancer therapy such as surgery, radiotherapy, chemotherapy, hormonal therapy, or combination therapy, because of the suppressed immunological functions. Yunzhi (Coriolus versicolor) can modulate various immunological functions in vitro, in vivo, and in human clinical trials. Danshen (Salvia miltiorrhiza) has been shown to benefit the circulatory system by its vasodilating and anti-dementia activity. The purpose of this clinical trial was to evaluate the immunomodulatory effects of Yunzhi-Danshen capsules in post-treatment breast cancer patients. Eighty-two patients with breast cancer were recruited to take Yunzhi [50 mg/kg body weight, 100% polysaccharopeptide (PSP)] and Danshen (20 mg/kg body weight) capsules every day for a total of 6 months. EDTA blood samples were collected every 2 months for the investigation of immunological functions. Flow cytometry was used to assess the percentages and absolute counts of human lymphocyte subsets in whole blood. Plasma level of soluble interleukin-2 receptor (sIL-2R) was measured by enzyme-linked immunosorbent assay (ELISA). Results showed that the absolute counts of T-helper lymphocytes (CD4+), the ratio of T-helper (CD4+)/T suppressor and cytotoxic lymphocytes (CD8+), and the percentage and the absolute counts of B-lymphocytes were significantly elevated in patients with breast cancer after taking Yunzhi-Danshen capsules, while plasma sIL-2R concentration was significantly decreased (all p < 0.05). Therefore, the regular oral consumption of Yunzhi-Danshen capsules could be beneficial for promoting immunological function in post-treatment of breast cancer patients.

The purpose of this study was to explore the effect of Chan-Chuang qigong on symptoms distress and psychological distress of breast cancer patients who underwent chemotherapy. A quasi-experimental design was adopted. Subjects were recruited from breast cancer outpatients receiving chemotherapy at an 1800-bed medical center in Taipei, Taiwan. Of these subjects, 35 were assigned to the control group and 32 to the experimental group in which Chan-Chuang qigong was administered. Assignment was not random. The instruments included a 21-item symptom distress scale and psychological distress with the symptom checklist-90-revised. Data of the symptoms and psychological distress were collected on the day before chemotherapy as baseline values, and also collected on days 8, 15 and 22 of chemotherapy. The results showed that the overall severity of symptom distress in the experimental group was significantly lower than the control group on day 22 (p < 0.05). The symptoms with significant improvement included pain, numbness, heartburn and dizziness (p < 0.05). With regard to psychological distress, the difference of overall severity between the two groups was not statistically significant (p > 0.05). However, the items of "unwillingness to live" (p < 0.05) and "hopelessness about the future" (p < 0.05) were significantly improved in the experimental group. In conclusion, Chan-Chuang qigong had the effect of attenuating the symptom distress and probably some part of the psychological distress of chemotherapy patients.

A randomized phase II study using mitomycin (MMC)/cisplatin (DDP) regimen with or without Kanglaite (KLT, a traditional Chinese medicine) as salvage treatment was conducted to exploit KLT's potential effects on patients with advanced breast cancer (ABC). Triweekly regimen consisted of mitomycin (8 mg/m²) administered intravenously on day 1, and cisplatin (25 mg/m²) intravenously on days 1 to 3. KLT (100 ml) was given intravenously per day on days 1 to 14 every 3 weeks. Between April 2006 and July 2007, 60 patients with a median age of 48 years were randomized into MMC/DDP with or without KLT treatment. In all, the objective response rate (ORR) was 17.5%. There were no significant differences between experimental and control treatments in terms of ORR (14.3% vs. 20.7%, p = 0.730), clinical benefit rates (24.1% vs. 28.6%, p = 0.468), median time to progression (TTP; 3.63 vs. 4.0, p = 0.872), and overall survival (OS; 7.17 vs. not reached, p = 0.120). The median TTP for patients with complete or partial responses was 6.0 months, but only 2.1 months for patients with stable or progressive disease (SD or PD; p = 0.028). While the median OS for patients who obtained clinical benefit from chemotherapy was not reached, that of patients with SD of no more than 6 months or PD was only 7.17 months (p = 0.004). There is no additional benefit when KLT is added to the MMC/DDP doublet in the management of ABC. Patients who obtained clinical benefit from chemotherapy had a longer TTP and OS.

Matrine, one of the main components extracted from a traditional Chinese herb, Sophora flavescens Ait, has displayed anti-cancer activity in several types of cancer cells. This study aims to evaluate the therapeutic benefits of matrine on primary and metastatic breast cancer. Matrine inhibited the viability of and induced apoptosis in human MCF-7 and mouse 4T1 breast cancer cells in a dose-dependent manner in vitro as shown by MTT assay, flow cytometry and laser scanning confocal microscopy. Administration of matrine inhibited the growth of primary tumors and their metastases to lungs and livers, in a dose-dependent manner, in a highly metastatic model of 4T1 breast cancer established in syngeneic Balb/c mice. Tumors from matrine-treated mice had a smaller proliferation index, shown by immunostaining with an anti-Ki-67 antibody, a greater apoptosis index, shown by TUNEL-staining, and a less microvessel density, shown by immunostaining with an anti-CD31 A antibody, compared to the controls. Western blot analysis of tumoral homogenates indicated that matrine therapy reduced the ratio of Bcl-2/Bax, downregulated the expressions of VEGF and VEGFR-2, and increased the activation of caspase-3 and caspase-9. This study suggests matrine may be a potent agent, from a natural resource, for treating metastatic breast cancer because of its anti-apoptotic, anti-proliferative and anti-angiogenic activities.

Oridonin, a natural tetracycline diterpenoid isolated from Chinese herb Rabdosia rubescens, has been reported to be a potent cytotoxic agent against a wide variety of tumors. However, its effect on highly metastatic breast cancer cells has not been addressed. In this study, we investigated the effects of oridonin on growth, migration and invasion of highly-metastatic human breast cancer cells. Our results showed that oridonin induced potent growth inhibition on human breast cancer cells MCF-7 and MDA-MB-231 in a time- and dose-dependent manner. According to the flow cytometric analysis, oridonin suppressed MCF-7 cell growth by cell cycle arrest at the G2/M phase and caused accumulation of MDA-MB-231 cells in the Sub-G1 phase. The induced apoptotic effect of oridonin was further confirmed by a morphologic characteristics assay and TUNEL assay. Oridonin triggered the reduction of Bcl-2/Bax ratio, caspase-8, NF-κB (p65), IKKα, IKKβ, phospho-mTOR, and increased expression level of cleaved PARP, Fas and PPARγ in a time-dependent manner. Immunofluorescent analysis showed that γH2AX-containing nuclear foci were significant in oridonin-treated MDA-MB-231 cells. Meanwhile, oridonin significantly suppressed MDA-MB-231 cell migration and invasion, decreased MMP-2/MMP-9 activation and inhibited the expression of Integrin β1 and FAK. In conclusion, oridonin inhibited the growth and induced apoptosis in breast cancer cells, which might be related to DNA damage and activation of intrinsic or extrinsic apoptotic pathways. Moreover, oridonin also inhibited tumor invasion and metastasis in vitro possibly via decreasing the expression of MMPs and regulating the Integrin β1/FAK pathway in MDA-MB-231 cells.

Drug resistance remains an on-going challenge in breast cancer chemotherapy. Combination of two or more drugs is an effective strategy to access context-specific multiple targets and overcome undesirable toxicity that is almost inevitable in single-drug chemotherapy. Many plant food-derived polyphenolic compounds have been proven to modulate many key factors responsible for cancer drug resistance, which makes them a promising group of low toxicity candidates for reversing cancer resistance. In this study, we analyzed the combination effect of two chemopreventive polyphenols, curcumin (Cur) and epigallocatechin-3-gallate (EGCG), in combating resistant breast cancer. Our present results showed that EGCG significantly enhanced the growth inhibition and apoptosis in both doxorubicin (DOX)-sensitive and resistant MCF-7 cells induced by Cur. The mechanism may be related to the further activation of caspase-dependent apoptotic signaling pathways and the enhanced cellular incorporation of Cur by inhibiting P-glycoprotein (P-gp) pump function. Moreover, Cur and EGCG in combination could enhance the toxicity of DOX and increase the intracellular level of DOX in resistant MCF-7 cells. Our findings with this practical combination of Cur and EGCG encourage us to move on to a promising strategy for successful treatment of human breast cancer resistance by combining two low-toxic chemotherapeutic agents from diet.

Acupuncture is used to treat a variety of symptoms and conditions associated with cancer and cancer treatments. The present study was performed to evaluate the feasibility of providing acupuncture in the hospital setting for breast cancer patients and to evaluate the short-term effect of acupuncture on stress, anxiety, and pain. This was an open label study conducted at Mayo Clinic Hospital, Methodist and Saint Marys Campus, Rochester, Minnesota. A total of 20 adult breast cancer patients undergoing mastectomy and/or breast reconstruction were recruited and offered daily acupuncture intervention beginning postoperative day 1 and continuing for the duration of the hospital stay. Outcome measures included the Symptom Visual Analog Scale (VAS) and Satisfaction Question and Was-it-Worth-it (WIWI) Questionnaire. It was found that acupuncture is a feasible option for postoperative breast cancer patients. In addition, it can significantly decrease the levels of anxiety (p = 0.0065), tension/muscular discomfort (p < 0.001) and pain (p = 0.023). The association between acupuncture and relaxation was found to be statistically borderline (p = 0.053). This feasibility study showed that acupuncture can be integrated into a busy postsurgical clinical practice. These results also suggest that acupuncture may be an important intervention in the postoperative setting for breast cancer patients.

Breast cancer (BC) is the most frequently diagnosed type of cancer all over the world. Angiogenesis, a physiological or pathological process characterized by the sprouting of new blood vessels from existing vessels, plays a vital role in tumor nutrition. In this work, we used JSI-124 (Cucurbitacin I), a selective JAK/STAT3 signaling pathway inhibitor, to investigate the role of STAT3 in tumor angiogenesis of a human BC cell line in vitro. JSI-124 inhibited cell viability, proliferation, adhesion, migration and tube formation of a human BC cell line MDA-MB-468. After transfection with pMXs-Stat3C, a dominant active mutant, the inhibitory effects of JSI-124 on MDA-MB-468 were abolished. Furthermore, JSI-124 reduced the phosphorylation of STAT3. These results suggested that JSI-124 inhibited tumor angiogenesis of the human BC cell line in vitro through the reduction of STAT3 phosphorylation. In addition, JSI-124 could reduce VEGF transcription and secretion, suggesting that JSI-124 is also involved in the inhibition of the VEGF autocrine loop in the tumor microenvironment.

Aloe-emodin (AE) is derived from Aloe vera and rhubarb (Rheum palmatum) and exhibits anticancer activities via multiple regulatory mechanisms in various cancers. AE can also enhance the anticancer efficacy of cisplatin, doxorubicin, docetaxel, and 5-fluorouracil; however, its effects remain poorly characterized. MCF-7, MDA-MB-231, MDA-MB-468, BT-474, and HCC-1954 breast cancer cell lines were treated with the indicated conditions of AE, and cell viability assays were performed. The expression levels of signaling proteins were determined by western blot analysis, intracellular reactive oxygen species (ROS), cell cycle distributions, and rates of apoptosis as estimated by flow cytometry. In comparison with other cells, MCF-7 cells were more sensitive to AE treatment; AE enhanced the cytotoxicity of 9$\mu$g/ml tamoxifen by reducing EGFR, ER$\alpha$, Ras, ERK, c-Myc, and mTOR protein expression and blocking PI3K and mTOR activation. Finally, although co-treatment of AE with tamoxifen increased intracellular ROS, there were no effects on cell cycle progression. Besides facilitating tamoxifen-induced cell death, AE also enhanced the antiproliferative activity of tamoxifen by blocking Ras/ERK and PI3K/mTOR pathways in breast cancer cells, thus demonstrating the chemosensitizing potential of AE.

Ginsenoside Rg3 is a key metabolite of ginseng and is known to inhibit cancer cell growth. However, the epigenetics of CpG methylation and its regulatory mechanism have yet to be determined. Genome-wide methylation analysis of MCF-7 breast cancer cells treated with Rg3 was performed to identify epigenetically regulated genes and pathways. The effect of Rg3 on apoptosis and cell proliferation was examined by a colony formation assay and a dye-based cell proliferation assay. The association between methylation and gene expression was monitored by RT-PCR and Western blot analysis. Genome-wide methylation analysis identified the “cell morphology”-related pathway as the top network. Rg3 induced late stage apoptosis but inhibited cell proliferation up to 60%. Hypermethylated TRMT1L, PSMC6 and NOX4 were downregulated by Rg3, while hypomethylated ST3GAL4, RNLS and KDM5A were upregulated. In accordance, downregulation of NOX4 by siRNA abrogated the cell growth effect of Rg3, while the effect was opposite for KDM5A. Notably, breast cancer patients with a higher expression of NOX4 and KDM5A showed poor and good prognosis of survival, respectively. In conclusion, Rg3 deregulated tumor-related genes through alteration of the epigenetic methylation level leading to growth inhibition of cancer cells.

Ginsenoside Rh2, a major bioactive ingredient abundant in red ginseng, has an antiproliferative effect on various cancer cells. In this study, we report a novel long noncoding RNA, C3orf67-AS1, which was identified as being hypermethylated at a CpG site of the promoter by Rh2 in MCF-7 cancer cells. Rh2-induced hypermethylation was responsible for the lower gene expression; the expression was recovered following treatment with a methyltransferase inhibitor, 5-aza-2^′-deoxycytidine. When C3orf67-AS1 was downregulated by a siRNA, the cell growth rate was decreased, demonstrating the RNA’s oncogenic activity. Accordingly, breast cancer patients showed a lower methylation and higher expression level of C3orf67-AS1. Within 800 kb flanking C3orf67-AS1 on the chromosome, eight genes were found, and four genes including C3orf67 (the sense strand gene of C3orf67-AS1) were downregulated by Rh2. In particular, C3orf67 was downregulated when C3orf67-AS1 was suppressed by a siRNA; however, the expression of C3orf67-AS1 was not affected by C3orf67. Taken together, this study identifies a novel noncoding RNA, C3orf67-AS1, of which the expression could be suppressed by Rh2 via promoter methylation, thereby mediating the anti-proliferative effect of the ginsenoside.