Breast cancer incidence and mortality in women in China: temporal trends and projections to 2030

Comparative analysis of dosimetry and predictive somatotype parameters of prone and supine whole-breast irradiation among Chinese women after breast-conserving surgery

Purpose

Finding a better treatment position (prone or supine) for whole-breast irradiation for Chinese female patients diagnosed with breast cancer by identify the associations between predictive somatotype parameters and dosimetric gains.

Materials and methods

Two volumetric-modulated arc therapy (VMAT) plans were deployed for whole-breast irradiation in supine and prone position with a total dose of 50 Gy in 25 fractions. Dose-volume parameters were compared and analysed both in the target volume and organs at risk, and equivalent uniform dose-based figure-of-merit (fEUD) models were further used to quantitatively evaluate the overall merits of the two plans. Body shape parameters, including body mass index (BMI), body surface area (BSA), breast shape, cup size, bust size and chest size, were collected. Anatomic features such as the central heart distance (CHD) were measured on supine CT. Spearman’s correlation analysis, receiver operating characteristic (ROC) curve analysis, and the linear regression models were conducted.

Results

Doses to the heart and left anterior descending coronary artery (LADCA) are greater in left-sided breast cancer (BC) patients in the prone position than in the supine position, and the opposite was true for right-sided BC patients (p<0.001). 19 of 63 patients (5 left-sided and 14 right-sided BC) achieved greater benefit from the prone position according to the fEUD score. Right-sided BC patients with a bust size ≥92.25 cm, drop-type breasts and cup size ≥B are very likely to benefit from prone-position radiotherapy. The CHD is significantly positively associated with △fEUD among right-sided BC patients (rho=0.506, p=0.004). Using a cut-off point of 2.215, the CHD had 71.4% sensitivity and 81.2% specificity in predicting a successful prone plan.

Conclusions

Right-sided BC patients had better dosimetric gain in the prone position than left-sided BC patients. The CHD is an especially good and novel predictor that could help to select prone-benefitting right-sided BC patients.

Mammogram classification based on a novel convolutional neural network with efficient channel attention

Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in mammogram remains a challenge due to low signal-to-noise ratio (SNR) and physiological characteristics. Many researchers achieved excellent performance in detecting mammographic images by inputting region of interest (ROI) annotations while ROI annotations require a great quantity of manual labor, time and resources. We propose a two-stage method that combines images preprocessing and model optimization to address the aforementioned challenges. Firstly, we propose the breast database preprocess (BDP) method to preprocess INbreast then we get INbreast†. The only label we need is benign or malignant label of one mammogram, not manual labeling such as ROI annotations. Secondly, we apply focal loss to ECA-Net50 which is an improved model based on ResNet50 with efficient channel attention (ECA) module. Our method can adaptively extract the key features of mammograms, meanwhile solving the problem of hard-to-classify samples and unbalanced categories. The AUC value of our method on INbreast† is 0.960, accuracy is 0.929, Recall is 0.928. The precision of our method on INbreast† is 0.883 which improved by 0.254 compared to ResNet50. In addition, we use Grad-CAM to visualize the effect of our model. The visualized heatmaps extracted by our method can focus more on lesion regions. Both numerical and visualized experiments demonstrate that our method achieves satisfactory performance.

The prevalence and genetic disorders spectrum of thalassemia among breast cancer patients in Jiangxi province, China

Background: Thalassemia is a common inherited hematological disease with genetic disorders characterized by imbalanced synthesis of the globin chains. Due to the improvement of treatment methods, patients with thalassemia can survive for a long time. Therefore, it is not uncommon for patients with thalassemia suffering from malignant tumors. However, there are quite few reports on thalassemia patients complicated with breast cancer. Herein, we try to investigate the prevalence and genetic disorders spectrum of thalassemia in patients with breast cancer. Methods: Blood routing tests and serum ferritin analysis were conducted in 1887 breast cancer patients treated in the department of radiation oncology during 1 April 2020 and 30 March 2022. The suspected thalassemia carriers with small mean corpuscular volume (MCV), mean corpuscular hemoglobin content (MCH) or mean corpuscular hemoglobin concentration (MCHC) but the concentration of serum ferritin within normal limits were further investigated by polymerase chain reaction (PCR) and flow through hybridization gene chip to detect common mutations of α-globin and β-globin genes using Thalassemia Geno Array Diagnostic Kit. The prevalence and genetic mutation spectrum of thalassemia among breast cancer patients were analyzed. Results: Four hundred and eighty-nine suspected thalassemia carriers were detected by complete blood cell counts and serum ferritin analysis among 1887 breast cancer patients. One hundred and seven cases (5.7%) were identified as carriers of thalassemia, of which 55 cases (51.4%) were α-thalassemia, 50 cases (46.7%) were β-thalassemia, and 2 cases (1.9%) were co-inheritance of α-thalassemia and β-thalassemia simultaneously. In α-thalassemia, the most prevalent genotype is -SEA/αα; as for β-thalassemia, βIVS-II-654/β is the most common genotype. The degree of anemia is more severe in β-thalassemia than in α-thalassemia. Conclusion: This is the first comprehensive molecular epidemiological investigation on thalassemia among breast cancer patients. Our data indicated that thalassemia was not uncommon in breast cancer patients. The physicians should have the knowledge to avoid misdiagnosis as iron deficiency anemia.

Effects of Structured Expressive Writing on Quality of Life and Perceived Self-Care Self-Efficacy of Breast Cancer Patients Undergoing Chemotherapy in Central China: A Randomized Controlled Trial

Expressive writing is a supportive psychological intervention allowing an individual to disclose and express their deepest thoughts and feelings related to personal traumatic experiences through writing. Previous studies suggested that expressive writing could promote the physical and mental health of cancer patients. The current study was conducted to evaluate the effect of expressive writing based on the theory of cognitive adaptation (TCA) on the quality of life and self-care self-efficacy in patients with breast cancer undergoing chemotherapy. A sample of 82 Chinese women receiving chemotherapy for breast cancer was randomly assigned to an experimental group (four 20 min writing activities focusing on emotional disclosure) or a control group (no writing activities). The quality of life (QoL) and self-care self-efficacy were assessed at baseline, 2 weeks, 4 weeks, and 6 weeks after the intervention, respectively. The sociodemographic characteristics, QoL, and self-care self-efficacy at baseline were comparable between the two groups. Repeated-measures ANOVA revealed significant effects of the time×group (F = 3.65, p < 0.05) on the QoL and significant effects of time (F = 4.77, p <0.05) on self-care self-efficacy. Compared with the control group, the QoL in the intervention group showed a significant and temporary increase at 2 weeks after the intervention (mean difference = −7.56, p < 0.05). As a low-cost and easily delivered psychological intervention, expressive writing is recommended to reduce stress when there is a lack of available emotional support.

Comparison of the tumor immune microenvironment phenotypes in different breast cancers after neoadjuvant therapy

Neoadjuvant therapy (NAT) treats early-stage breast cancers, especially triple-negative breast cancers (TNBCs). NAT improves pathological complete response (pCR) rates for different breast cancer patients. Recently, immune checkpoint inhibitors that target programmed death 1 (PD-1) or programmed death ligand 1 (PD-L1) in combination with NAT have shown antitumor activity in patients with early breast cancer. However, the tumor immune microenvironment (TME) in different subtypes of breast cancers, like TNBC, hormone receptor-positive (HR+), and human epidermal growth factor receptor 2 amplified (HER2+) and its changes by NAT remain to be fully characterized. We analyzed pre-NAT tumor biopsies from TNBC (n = 27), HR+ (n = 24), and HER2+ (n = 30) breast cancer patients who received NAT, followed by surgery. The different immune makers (PD-1, PD-L1, CD3, and CD8) of tumor-infiltrating lymphocytes (TILs) were identified with immunofluorescence-based microenvironment analysis. TILs within cancer parenchyma (iTILs) and in cancer stroma (sTILs) were counted separately. We found that PD-L1+ cells in tumor and stroma were significantly higher in TNBC patients than in others. PD-L1+ sTILs were significantly higher in pCR than in non-pCR patients of all the subtypes. The infiltration scores of B-cell memory, T-cell CD4+ memory activated, T-cell follicular helper, and Macrophage M0 and M1 were relatively higher in TNBC patients, indicating immunoreactive TME in TNBC. Analysis of TCGA-BRCA RNA-seq indicated that PD-L1 was highly expressed in TNBC patients compared with HR+ and HER2+ patients. Higher PD-L1 expression in TNBC patients was associated with significantly longer overall survival (OS). Our results demonstrated that PD-L1 expression level of iTILs and sTILs is highest in TNBC among breast cancers. TNBC patients had significantly different immunoreactive TME compared with HR+ and HER2+ patients, suggesting potentially favorable outcomes for immunotherapy in these patients. Also, PD-L1+ could be a powerful predictor of pCR in TNBC patients after NAT.

Crosstalk between Hypoxia and Extracellular Matrix in the Tumor Microenvironment in Breast Cancer

Even though breast cancer is the most diagnosed cancer among women, treatments are not always successful in preventing its progression. Recent studies suggest that hypoxia and the extracellular matrix (ECM) are important in altering cell metabolism and tumor metastasis. Therefore, the aim of this review is to study the crosstalk between hypoxia and the ECM and to assess their impact on breast cancer progression. The findings indicate that hypoxic signaling engages multiple mechanisms that directly contribute to ECM remodeling, ultimately increasing breast cancer aggressiveness. Second, hypoxia and the ECM cooperate to alter different aspects of cell metabolism. They mutually enhance aerobic glycolysis through upregulation of glucose transport, glycolytic enzymes, and by regulating intracellular pH. Both alter lipid and amino acid metabolism by stimulating lipid and amino acid uptake and synthesis, thereby providing the tumor with additional energy for growth and metastasis. Third, YAP/TAZ signaling is not merely regulated by the tumor microenvironment and cell metabolism, but it also regulates it primarily through its target c-Myc. Taken together, this review provides a better understanding of the crosstalk between hypoxia and the ECM in breast cancer. Additionally, it points to a role for the YAP/TAZ mechanotransduction pathway as an important link between hypoxia and the ECM in the tumor microenvironment, driving breast cancer progression.

Umbilical cord mesenchymal stem cells and breast cancer: a good therapeutic candidate or not? A minireview

Breast cancer (BC), as the most common cancer among women, affects a great number of subjects around the world. This heterogenic disease is divided into several types and subtypes, and each subtype has various phenotypes and genotypes. Against BC, several options have been proposed, such as surgery, radiotherapy, and chemotherapeutic agents. However, these approaches may have detrimental effects on health and life quality of patients. Hence, harnessing a therapeutic tool with high effectiveness and low side effects is required. Recently, mesenchymal stem cells (MSCs) have created a new window to treat various disorders, like cancer, and among these, umbilical cord (UC)-derived MSCs have acquired much interest due to their advantages. Therefore, in this narrative review, the influences of UC-derived MSCs on BC were reviewed and summarized with a focus on the molecular mechanisms involved in its pathogenesis and treatment.

Burden, trends, and risk factors for breast cancer in China from 1990 to 2019 and its predictions until 2034: an up-to-date overview and comparison with those in Japan and South Korea

BACKGROUND

The difference in epidemiological characteristics of breast cancer (BC) across countries is valuable for BC management and prevention. The study evaluated the up-to-date burden, trends, and risk factors of BC in China, Japan and South Korea during 1990-2019 and predicted the BC burden until 2034.

METHODS

Data on incident cases, deaths, disability-adjusted life-years (DALYs) and age-standardized rate (ASR) of BC were extracted from the Global Burden of Disease Study 2019. Trend analysis and prediction until 2034 were conducted by estimated annual percentage change and a Bayesian age-period-cohort model, respectively. Besides, the attributable burden to BC risk factors was also estimated.

RESULTS

In 2019, the number of BC incident cases, deaths and DALYs in China were 375,484, 96,306 and 2,957,453, respectively. The ASR of incidence increased, while that of death and DALYs decreased for Chinese females and Japanese and South Korean males during 1990-2019. High body-mass-index (BMI) was the largest contributor to Chinese female BC deaths and DALYs, while alcohol use was the greatest risk factor for Japanese and South Korean as well as Chinese males. The incident cases and deaths were expected to continue increase during 2020-2034 (except for Japanese female incident cases).

CONCLUSIONS

China had the greatest burden of BC among the three countries. Incident cases and deaths of BC were projected to increase over the next 15 years in China, particularly among Chinese males. Effective prevention and management strategies are urgently necessary for BC control in China.

Deep learning based on ultrasound images assists breast lesion diagnosis in China: a multicenter diagnostic study

BACKGROUND

Studies on deep learning (DL)-based models in breast ultrasound (US) remain at the early stage due to a lack of large datasets for training and independent test sets for verification. We aimed to develop a DL model for differentiating benign from malignant breast lesions on US using a large multicenter dataset and explore the model's ability to assist the radiologists.

METHODS

A total of 14,043 US images from 5012 women were prospectively collected from 32 hospitals. To develop the DL model, the patients from 30 hospitals were randomly divided into a training cohort (n = 4149) and an internal test cohort (n = 466). The remaining 2 hospitals (n = 397) were used as the external test cohorts (ETC). We compared the model with the prospective Breast Imaging Reporting and Data System assessment and five radiologists. We also explored the model's ability to assist the radiologists using two different methods.

RESULTS

The model demonstrated excellent diagnostic performance with the ETC, with a high area under the receiver operating characteristic curve (AUC, 0.913), sensitivity (88.84%), specificity (83.77%), and accuracy (86.40%). In the comparison set, the AUC was similar to that of the expert (p = 0.5629) and one experienced radiologist (p = 0.2112) and significantly higher than that of three inexperienced radiologists (p < 0.01). After model assistance, the accuracies and specificities of the radiologists were substantially improved without loss in sensitivities.

CONCLUSIONS

The DL model yielded satisfactory predictions in distinguishing benign from malignant breast lesions. The model showed the potential value in improving the diagnosis of breast lesions by radiologists.

COMT rs737865 mediates chemobrain in breast cancer patients with various levels of Ki-67

Previous findings have indicated that catechol-O-methyltransferase (COMT) may be a genetic risk factor for chemobrain. However, the mediation of chemobrain by COMT polymorphisms in breast cancer patients with various levels of Ki-67 remains unknown. The current research assessed the genetic risk across COMT genotypes for chemobrain in breast cancer patients with various levels of Ki-67. Breast cancer patients (65 with Ki-67<14%, 75 with Ki-67>14%) completed cognitive tests before and after adjuvant chemotherapy, and three single-nucleotide polymorphisms (SNPs) of COMT (rs165599, rs4680, rs737865) were genotyped from peripheral blood. Lower cognitive test results in breast cancer patients were displayed in those before chemotherapy. Furthermore, the event-based prospective memory (EBPM) scores of patients in the Ki-67>14% group were worse than those in the patients in the Ki-67<14% group after chemotherapy (z=-7.51, P<0.01), but the time-based prospective memory (TBPM) scores of the two groups were not significantly different. The COMT rs737865 A/G genotype was associated with memory protection (codominant model: adjusted odds ratio (OR)=0.135, 95% CI=0.026-0.706, P=0.018), and A/G genotype carriers exhibited better performance on the EBPM test than the A/A genotype. Levels of Ki-67 were likely to be associated with EBPM decline in breast cancer patients. Taken together, COMT rs737865 polymorphisms are a potential genetic risk factor for chemobrain in breast cancer patients with various levels of Ki-67.

Using an Improved Residual Network to Identify PIK3CA Mutation Status in Breast Cancer on Ultrasound Image

Background

The detection of phosphatidylinositol-3 kinase catalytic alpha (PIK3CA) gene mutations in breast cancer is a key step to design personalizing an optimal treatment strategy. Traditional genetic testing methods are invasive and time-consuming. It is urgent to find a non-invasive method to estimate the PIK3CA mutation status. Ultrasound (US), one of the most common methods for breast cancer screening, has the advantages of being non-invasive, fast imaging, and inexpensive. In this study, we propose to develop a deep convolutional neural network (DCNN) to identify PIK3CA mutations in breast cancer based on US images.

Materials and Methods

We retrospectively collected 312 patients with pathologically confirmed breast cancer who underwent genetic testing. All US images (n=800) of breast cancer patients were collected and divided into the training set (n=600) and test set (n=200). A DCNN-Improved Residual Network (ImResNet) was designed to identify the PIK3CA mutations. We also compared the ImResNet model with the original ResNet50 model, classical machine learning models, and other deep learning models.

Results

The proposed ImResNet model has the ability to identify PIK3CA mutations in breast cancer based on US images. Notably, our ImResNet model outperforms the original ResNet50, DenseNet201, Xception, MobileNetv2, and two machine learning models (SVM and KNN), with an average area under the curve (AUC) of 0.775. Moreover, the overall accuracy, average precision, recall rate, and F1-score of the ImResNet model achieved 74.50%, 74.17%, 73.35%, and 73.76%, respectively. All of these measures were significantly higher than other models.

Conclusion

The ImResNet model gives an encouraging performance in predicting PIK3CA mutations based on breast US images, providing a new method for noninvasive gene prediction. In addition, this model could provide the basis for clinical adjustments and precision treatment.

Effect of estradiol as a continuous variable on breast cancer survival by menopausal status: a cohort study in China

High levels of circulating estradiol (E2) are associated with increased risk of breast cancer, whereas its relationship with breast cancer prognosis is still unclear. We evaluated the effect of E2 concentration on survival endpoints among 8766 breast cancer cases diagnosed between 2005 and 2017 from the Tianjin Breast Cancer Cases Cohort. Levels of serum E2 were measured in pre-menopausal and post-menopausal women. Multivariable-adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) between quartile of E2 levels and overall survival (OS) and progression-free survival (PFS) of breast cancer. The penalized spline was then used to test for non-linear relationships between E2 (continuous variable) and survival endpoints. 612 deaths and 982 progressions occurred over follow-up through 2017. Compared to women in the quartile 3, the highest quartile of E2 was associated with reduced risk of both PFS in pre-menopausal women (HR 1.79, 95% CI 1.17-2.75, P = 0.008) and OS in post-menopausal women (HR 1.35, 95% CI 1.04-1.74, P = 0.023). OS and PFS in pre-menopausal women exhibited a nonlinear relation ("L-shaped" and "U-shaped", respectively) with E2 levels. However, there was a linear relationship in post-menopausal women. Moreover, patients with estrogen receptor-negative (ER-negative) breast cancer showed a "U-shaped" relationship with OS and PFS in pre-menopausal women. Pre-menopausal breast cancer patients have a plateau stage of prognosis at the intermediate concentrations of E2, whereas post-menopausal patients have no apparent threshold, and ER status may have an impact on this relationship.

BUSnet: A Deep Learning Model of Breast Tumor Lesion Detection for Ultrasound Images

Ultrasound (US) imaging is a main modality for breast disease screening. Automatically detecting the lesions in US images is essential for developing the artificial-intelligence-based diagnostic support technologies. However, the intrinsic characteristics of ultrasound imaging, like speckle noise and acoustic shadow, always degenerate the detection accuracy. In this study, we developed a deep learning model called BUSnet to detect the breast tumor lesions in US images with high accuracy. We first developed a two-stage method including the unsupervised region proposal and bounding-box regression algorithms. Then, we proposed a post-processing method to enhance the detecting accuracy further. The proposed method was used to a benchmark dataset, which includes 487 benign samples and 210 malignant samples. The results proved the effectiveness and accuracy of the proposed method.

Forecast of peak attainment and imminent decline after 2017 of oral cancer incidence in men in Taiwan

Oral cancer is the fourth most common cancer among men in Taiwan. The age-standardized incidence rate of oral cancer among men in Taiwan has increased since 1980 and became six times greater in 2014. To enable effective public health planning for oral cancer, research on the projection of oral cancer burden is essential. We conducted an age-period-cohort analysis on the incidence of oral cancer among men in Taiwan from 1997 to 2017 and extrapolated the trend to 2025. We found that the period trends for young adults aged between 25 and 44 have already peaked before 2017; the younger, the earlier, and then the trends declined. The cohort trends have peaked roughly at the 1972 birth cohort and then declined for all ages. Despite the increasing trend in the age-standardized incidence rate for oral cancer among men in Taiwan from 1997 to 2017, we forecast a peak attained, an imminent decline after 2017, and a decrease of 8.4% in age-standardized incidence rate from 2017 to 2025. The findings of this study contribute to developing efficient and comprehensive strategies for oral cancer prevention and control.

The global, regional, and national disease burden of breast cancer attributable to low physical activity from 1990 to 2019: an analysis of the Global Burden of Disease Study 2019

BACKGROUND

To assess the spatiotemporal variation in female breast cancer attributable to low physical activity (LPA) at a global scale from 1990 to 2019, which is essential to promote physical activity, as well as prevent and control breast cancer.

METHODS

The number of deaths and disability-adjusted life years (DALYs), and the corresponding age-standardized rates (ASMR and ASDR) of LPA-related breast cancer in 204 countries and territories from 1990 to 2019 were retrieved from the Global Burden of Disease Study 2019 to measure the related breast cancer burden by age and region. The estimated annual percentage change (EAPC) was calculated to quantify the secular trend in breast cancer burden rates.

RESULTS

From 1990 to 2019, globally, both breast cancer deaths and DALYs attributable to LPA nearly doubled, although the corresponding ASMR and ASDR decreased slightly, with EAPC of -0.46 (95% confidence interval: -0.52, -0.40) and -0.44 (95% confidence interval: -0.49, -0.39), respectively. The LPA-related breast cancer burden varied considerably across the world, with the highest-burden rates in Oceania, Tropical Latin America and Caribbean, and the fastest growth in North Africa and Middle East. The ASMR and ASDR showed a logarithmic association with the Socio-demographic Index, and a temporally upward trend in most of 204 countries regardless of the Socio-demographic Index or the ASMR in 1990.

CONCLUSIONS

Despite a decline in LPA-related breast cancer burden achieved in many countries during the last 3 decades like Bermuda, Myanmar, USA and China, an increase still occurred in most of 204 countries and territories, such as Solomon Islands, Equatorial Guinea, Japan and India. The findings can bring greater awareness to the importance of promoting physical activity for the local government to control the attributable breast cancer burden.

Clinical and genomic analyses of neuroendocrine neoplasms of the breast

Breast neuroendocrine neoplasms (NENs) constitute a rare histologic subtype that includes both neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs). In this study, we aimed to gain insight into the clinical and molecular characteristics of NENs of the breast. NEN and paired distant normal fresh tissues and clinicopathological data were obtained from 17 patients with NENs, and clinicopathological data were collected from 755 patients with invasive breast carcinomas of no special type (IBCs-NST). We compared the clinicopathological characteristics of NENs and IBCs-NST and performed whole-exome sequencing (WES) of both NEN and paired normal tissues. Compared with the IBC-NST patients, the NEN patients had a higher mean age, lower clinical stage, and lower pathological nodal (pN) stage (P < 0.001, P < 0.001, and P = 0.017, respectively). The most frequently mutated gene in NENs was KMT2C (3/17, 17.6%). NENs had copy number variations (CNVs) of 8q, 11q, and 17q amplification and 17q and 11q deletion and harbored the following specific genes related to tumorigenesis: (i) suppressor genes with loss of heterozygosity (LOH) such as ACE (2/17, 11.8%); (ii) tumor driver genes such as GATA3 (2/17, 11.8%); and (iii) susceptibility genes such as MAP3K4 (17/17, 100%) and PDE4DIP (17/17, 100%). The oncogenic/likely oncogenic mutations of NETs in PI3K pathway genes (50.0%, 18.2%; P < 0.001) and MAPK signaling pathway genes (83.3%, 18.2%; P = 0.035) affected higher proportions than those of NECs. In conclusion, this study provides certain clinical and molecular evidence supporting NENs as a distinct subtype of breast cancer and provides some potential molecular features for distinguishing NETs from NECs.

Amorphophalli Rhizoma inhibits breast cancer growth, proliferation, migration, and invasion via the PI3K/AKT pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Amorphophalli Rhizoma (APR) is widely used as an adjuvant treatment for advanced and metastatic triple-negative breast cancer (TNBC), but its effects, potential active ingredients, and mechanism of action on estrogen receptor-positive (ER+) and human epidermal growth factor receptor-positive (HER2+) breast cancer cells were not reported.

AIM OF THE STUDY

The present study investigated the effects and mechanism of APR on ER+ and HER2+ breast cancer cells.

MATERIALS AND METHODS

Rotary evaporation was used to prepare different extracts of APR. Cell activity was assessed using the cell counting kit-8 (CCK-8) method. Wound healing assays were used to assess cell migration, and a cell invasion assay was performed using a Transwell chamber with Matrigel matrix. A xenograft model was used to analyze the inhibitory effects of APR on tumor growth. Bioinformatics analyses were used to explore the potential mechanism of APR in breast cancer. RT-qPCR and Western blotting were performed to reveal the molecular mechanism.

RESULTS

The ethyl acetate extract of APR showed the strongest tumor inhibitory effect on ER+ and HER2+ breast cancer cells compared to petroleum ether or N-butanol extracts. APR inhibited ER+ and HER2+ breast cancer cell growth, proliferation, migration, and invasion via the phosphatidylinositol-3 kinase (PI3K)/AKT pathway.

CONCLUSIONS

APR had a significant inhibitory effect on ER+ and HER2+ breast cancer cells via the PI3K/AKT signaling pathway. Therefore, APR may be useful for preventing ER+ and HER2+ breast tumor growth, proliferation, migration, and invasion.

Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules

BACKGROUND

The incidence rate of breast cancer has exceeded that of lung cancer, and it has become the most malignant type of cancer in the world. BI-RADS 4 breast nodules have a wide range of malignant risks and are associated with challenging clinical decision-making.

AIM

To explore the diagnostic value of artificial intelligence (AI) automatic detection systems for BI-RADS 4 breast nodules and to assess whether conventional ultrasound BI-RADS classification with AI automatic detection systems can reduce the probability of BI-RADS 4 biopsy.

METHODS

A total of 107 BI-RADS breast nodules confirmed by pathology were selected between June 2019 and July 2020 at Hwa Mei Hospital, University of Chinese Academy of Sciences. These nodules were classified by ultrasound doctors and the AI-SONIC breast system. The diagnostic values of conventional ultrasound, the AI automatic detection system, conventional ultrasound combined with the AI automatic detection system and adjusted BI-RADS classification diagnosis were statistically analyzed.

RESULTS

Among the 107 breast nodules, 61 were benign (57.01%), and 46 were malignant (42.99%). The pathology results were considered the gold standard; furthermore, the sensitivity, specificity, accuracy, Youden index, and positive and negative predictive values were 84.78%, 67.21%, 74.77%, 0.5199, 66.10% and 85.42% for conventional ultrasound BI-RADS classification diagnosis, 86.96%, 75.41%, 80.37%, 0.6237, 72.73%, and 88.46% for automatic AI detection, 80.43%, 90.16%, 85.98%, 0.7059, 86.05%, and 85.94% for conventional ultrasound BI-RADS classification with automatic AI detection and 93.48%, 67.21%, 78.50%, 0.6069, 68.25%, and 93.18% for adjusted BI-RADS classification, respectively. The biopsy rate, cancer detection rate and malignancy risk were 100%, 42.99% and 0% and 67.29%, 61.11%, and 1.87% before and after BI-RADS adjustment, respectively.

CONCLUSION

Automatic AI detection has high accuracy in determining benign and malignant BI-RADS 4 breast nodules. Conventional ultrasound BI-RADS classification combined with AI automatic detection can reduce the biopsy rate of BI-RADS 4 breast nodules.

High Expression of Complement Component C7 Indicates Poor Prognosis of Breast Cancer and Is Insensitive to Taxane-Anthracycline Chemotherapy

Background

Breast cancer is the most commonly diagnosed cancer worldwide. However, the well-known biomarkers are not enough to meet the needs of precision medicine. Novel targets are desirable and highly valuable for improved patient survival. In this regard, we identified complement component C7 as one of the candidates based on data from the OCOMINE database.

Methods

C7 expression was examined by immunohistochemistry in 331 cases of invasive ductal carcinoma (IDC), 45 cases of ductal carcinoma in situ (DCIS), and 52 cases of non-neoplastic tissues adjacent to tumor. Then, C7 expression was further confirmed by Western blot analysis based on IDC specimens and non-neoplastic breast specimens. The relationship between the C7 expression and prognosis of breast cancer patients was analyzed in order to investigate the function of C7 in breast cancer patients. Meanwhile, we also analyzed the relationship between the C7 expression and prognosis of 149 patients treated with conventional TE (taxane and anthracycline)-based chemotherapy. Then, a cohort of patients (22 cases) treated with TE neoadjuvant chemotherapy was used to further confirm the relationship between the C7 expression and TE-based chemosensitivity.

Results

In our present study, we reported for the first time that C7 was an independent prognostic factor of breast cancer and C7 expression of IDC tissues was higher than non-neoplastic tissues adjacent to tumor and DCIS. In a cohort of 331 IDC patients, high expression of C7 indicated poor prognosis especially in the triple negative subtype and luminal B subtype. Furthermore, C7 was also a promoting factor for triple negative subtype patients to develop bone metastasis. Meanwhile, we provided the first evidence that patients with high C7 expression were insensitive to TE (taxane and anthracycline)-based chemotherapy by analyzing a cohort of 149 patients treated with TE-based chemotherapy and another cohort of 22 patients treated with TE neoadjuvant chemotherapy.

Conclusions

In summary, high expression of C7 may promote breast cancer development and might be insensitive to TE-based chemotherapy. Our present study laid a foundation to help clinicians improve the identification of patients for TE-based chemotherapy by C7 in the era of precision medicine.

Association of Preoperative Serum Levels of CEA and CA15-3 with Molecular Subtypes of Breast Cancer

Objectives

Molecular subtypes are employed as a guide for targeted treatment and important prognostic factors. This study focused on investigating the association of serum levels of CEA, CA15-3, and CA125 with clinicopathological characteristics of breast cancer to find prognostic markers for breast cancer and provide precise targeted therapy.

Materials and Methods

In this study, 961 breast cancer patients with preoperative serum levels of CEA, CA15-3, and CA125 and molecular subtypes were analyzed. Cut-off values of 5 ng/ml, 25 U/ml, and 35 U/ml were used for CEA, CA15-3, and CA125, respectively. The χ² test and Fisher exact test along with logistic multivariate regression analysis were performed for investigating the correlation of CEA, CA15-3, and CA125 serum levels with molecular subtypes and associated factors.

Results

An increase in the serum concentrations of CEA, CA15-3, and CA125 was discovered in 48 (4.99%), 54 (5.62%), and 55 (5.72%) breast cancer patients, respectively. Univariate analysis demonstrated that the levels of CEA (p < 0.01) and CA15-3 (p < 0.05) were significantly linked with molecular types of breast cancer. Moreover, patients having larger tumor size (p < 0.01, p < 0.0001, and p < 0.05, respectively) along with nodal metastasis (p < 0.05, p = 0.0001, and p < 0.05, respectively) exhibited higher rates of elevated CEA, CA15-3, and CA125 levels. Status of Her-2 positive (p < 0.01) had a significant connection with elevated CEA levels. Multivariate analysis further indicated that molecular subtypes were independent factors associated with CEA and CA15-3 levels. Also, Her-2 status was significantly and independently related to CEA levels.

Conclusion

Preoperative serum levels of CEA and CA15-3 were independently associated with molecular subtypes of breast cancer. CEA and CA15-3 might improve the prognostic prediction for patients with breast cancer and inform the selection of specific therapies. A further biological analysis is needed for investigating the relationship between Her-2 expression and CEA levels.