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    Multidisciplinary Treatment and Clinical Innovation of Breast Cancer-Commentary
    Current status, challenges and innovative approaches of multidisciplinary treatment for breast cancer
    YU Zhigang, ZHENG Chao
    Journal of Shandong University (Health Sciences). 2025, 63(1):  1-9.  doi:10.6040/j.issn.1671-7554.0.2025.0036
    Abstract ( 150 )   PDF (1784KB) ( 62 )   Save
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    With the rising incidence of breast cancer, the multidisciplinary treatment(MDT)mode has become an important strategy for optimizing breast cancer diagnosis and treatment. This article analyzes the current status of breast cancer diagnosis and treatment in Shandong Province and comprehensively examines the implementation of MDT and the major challenges it faces, including the inadequacy of subspecialties, insufficient data sharing capabilities, uneven resource allocation, and the low enthusiasm of medical staff and patient participation. By summarizing Shandong Provinces experiences in the localized practice of the MDT mode, a series of innovative pathways suitable for national conditions are proposed, including standardizing treatment processes, building efficient information sharing platforms, strengthening patient follow-up and support systems, and deepening professional alliances and regional cooperation networks. Furthermore, by integrating the latest research in the fields of molecular biology, radiomics, and artificial intelligence in breast cancer, the prospects of multidisciplinary collaboration and modern technology in breast cancer diagnosis and treatment are explored, highlighting the role of digital healthcare transformation and precision medicine in promoting personalized treatment, aiming to provide theoretical support and practical references for breast cancer diagnosis and treatment in our country.
    Expert Consensus
    Shandong Province expert consensus on multidisciplinary treatment of breast cancer(2024 edition)
    Journal of Shandong University (Health Sciences). 2025, 63(1):  10-16.  doi:10.6040/j.issn.1671-7554.0.2024.0289
    Abstract ( 138 )   PDF (849KB) ( 54 )   Save
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    As the most common malignant tumor occured in women, breast cancer has posed a serious threat to health and brought a heavy burden on medical services. Although individualized treatment has made great progress, there was still a gap in overall survival of breast cancer patients between China and western countries. In addition, the prevalence was higher in Shandong Province. Breast cancer has entered the era of individualised comprehensive treatment. By professional synergy and breaking down professional barriers, multidisciplinary treatment(MDT)mode has been proven to improve survival, enhance quality of life and narrow the gap. Although the concept of MDT has been widely accepted by specialists, there is no standardised process and standard for MDT in breast cancer. Based on the above background, combined with evidence-based medicine, Multidisciplinary Joint Committee on Breast Disease of Shandong Provincial Medical Association, after discussion and voting, formed Shandong Province expert consensus on multidisciplinary treatment of breast cancer(2024 edition), which integrated the relevant studies worldwide and combined with clinical practice. This consensus aims to promote the homogenization level of MDT and to improve the standard of diagnosis and treatment of breast cancer in Shandong Province.
    Review
    Progress in the study of trastuzumab-induced cardiotoxicity in HER2-positive breast cancer patients
    CHENG Yueqi, WANG Fei, YU Lixiang, ZHENG Chao, YU Zhigang
    Journal of Shandong University (Health Sciences). 2025, 63(1):  17-24.  doi:10.6040/j.issn.1671-7554.0.2025.0035
    Abstract ( 131 )   PDF (2082KB) ( 39 )   Save
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    Trastuzumab is a humanised monoclonal antibody that targets the human epidermal growth factor receptor 2(HER2)and has shown significant efficacy in the clinical treatment of HER2-positive breast cancer. However, its clinical use may lead to cardiotoxicity issues such as reduction in left ventricular ejection fraction(LVEF), congestive heart failure(CHF)and arrhythmias. The aim of this article is to review current research on trastuzumab-induced cardiotoxicity in the treatment of HER2-positive breast cancer and strategies for monitoring and preventing cardiotoxicity. The aim is to provide a basis for selecting future directions in basic research and optimising clinical management strategies for the use of trastuzumab.
    Clinical Research
    Lentivirus vector-mediated Gag-Caspase-8 induces apoptosis and S-phase arrest in triple-negative breast cancer primary cells
    WANG Min, LI Xiping, TAN Jun, QIU Mei, HOU Zeyu, TIAN Ying, LUO Hongying, FAN Chaowen, QI Ling, YU Qi, XIE Wei
    Journal of Shandong University (Health Sciences). 2025, 63(1):  25-34.  doi:10.6040/j.issn.1671-7554.0.2024.1107
    Abstract ( 101 )   PDF (16885KB) ( 59 )   Save
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    Objective To investigate the effects and mechanisms of Gag-Caspase-8-containing lentivirus-like particles on the proliferation, migration, cell cycle, and apoptosis in primary triple-negative breast cancer(TNBC)cells. Methods Three clinical specimens of human breast cancer were collected, and primary cells were cultured using an improved tissue block culture method. The cultured cells were identified as high-purity triple-negative breast cancer primary cells through HE staining, immunohistochemistry, and immunofluorescence. Lentiviral transduction was employed to construct virus-like particles(VLPs)carrying Gag-Caspase-8. The cells were divided into the PBS group, Gag-VLPs group, and Gag-CASP8-VLPs group. Cell proliferation was assessed by MTT assay, cell migration was evaluated by scratch assay, apoptosis was detected by AO/EB staining and flow cytometry, and the expression of apoptosis-related proteins was examined by Western blotting. Results Clinical tumor specimens were confirmed as breast cancer tissues by HE staining. Immunohistochemistry revealed high expression of CA153 in the primary breast cancer cells, with a purity of approximately 98% based on the proportion of positive cells. Immunofluorescence analysis showed that HER2, ER, and PR were all negatively expressed, confirming the cultured cells as high-purity triple-negative human breast cancer primary cells. Western blotting detected the expression of the lentiviral vector-specific marker P24 in both Gag-VLPs and Gag-CASP8-VLPs, indicating successful packaging of lentivirus-like particles. Upon intervention with Gag-CASP8-VLPs for 24 and 48 hours, compared to PBS and Gag-VLPs controls, inverted microscopy observed cellular shrinkage, reduced size, decreased adherence, and increased floating cells. MTT assays demonstrated significant inhibition of cell growth in the Gag-CASP8-VLPs group(P<0.01), with time-dependent effects. Wound healing assays showed significant inhibition of cell migration(P<0.05). Flow cytometry revealed a significant increase in S-phase cells(P<0.01), indicating cell cycle arrest at the S phase. AO/EB staining and flow cytometry detected induced apoptosis in the Gag-CASP8-VLPs group(P<0.01). Western blotting results indicated significantly increased expressions of Gag-Caspase-8, Pro caspase-8, Active caspase-8, and Caspase-3(P<0.01), demonstrating that lentivirus-mediated Gag-Caspase-8 effectively enters and activates downstream apoptotic executioner Caspase-3 in triple-negative human breast cancer primary cells, leading to their apoptosis. Conclusion Lentivirus-mediated Gag-Caspase-8 can deliver activated Caspase-8 into primary TNBC cells, induce apoptosis through activation of caspase-3, arrest cells at the S phase, and inhibit cell proliferation and migration.
    Expression of circ_0000144 in breast cancer and its effect on the proliferation, migration and invasion ability of breast cancer cells
    ZHANG Jie, ZHANG Fangfang, WANG Jingnan, LI Zeyu, SONG Ying, LI Na
    Journal of Shandong University (Health Sciences). 2025, 63(1):  35-42.  doi:10.6040/j.issn.1671-7554.0.2024.0570
    Abstract ( 112 )   PDF (7595KB) ( 48 )   Save
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    Objective To explore the expression of circ_0000144 in breast cancer tissues and its effect on the proliferation, apoptosis, migration and invasion abilities of breast cancer cells. Methods Quantitative real-time polymerase chain reaction(RT-qPCR)experiments were performed to detect the expression level of circ_0000144 in 49 breast cancer tissues and paired paracancerous normal breast tissue specimens and to analyze the relationship between the expression level of circ_0000144 and the clinicopathological characteristics of breast cancer patients. Normal breast epithelial cells MCF-10A were used as the control, and circ_0000144 expression was detected in breast cancer cell lines(T47D, MCF-7, MDA-MB-231)by RT-qPCR. MCF-7 cells were used as the study object, and the transfected si-circ_0000144 group was set up as the experimental group(si-circ_0000144 group), the transfected si-NC group was set as the saline control group(si-NC group), and a blank control group(Control group)was set at the same time. The cells were cultured with conventional medium without any transfection operation. The abilities of cell proliferation, migration and invasion in breast cancer cells were detected by CCK-8, clone formation assay, flow cytometry, scratch assay and Transwell assay, and the protein expressions of CyclinD1, p21, Bax, Bcl-2, E-cadherin and N-cadherin were detected by Western blotting. Results The expression of circ_0000144 in breast cancer tissues was significantly elevated compared with that in normal tissues adjacent to the cancer(P<0.001), and was closely positively associated with TNM stage and lymph node metastasis(P=0.003, P=0.007). The expressions of circ_0000144 were up-regulated in breast cancer cell lines compared to normal breast epithelial cells MCF-10A(P<0.001). Compared with the Control group or si-NC group, the si-Circ_0000144 group showed reduced abilities of proliferate, migrate and invade(all P<0.001), elevated apoptosis rate(both P<0.001), decreased expression levels of CyclinD1, Bcl-2 and N-cadherin proteins(all P<0.001), and increased expression levels of p21, Bax and E-cadherin proteins(all P<0.001). Conclusion circ_0000144 is highly expressed in breast cancer tissues and cell lines. Down-regulation of circ_0000144 can hinder breast cancer cell proliferation, migration and invasion, and promote its apoptosis. circ_0000144 may become a molecular target for breast cancer treatment.
    VTCN1 causes poor prognosis and endocrine therapy resistance in HR+ breast cancer
    SONG Yawen, GUO Liantao, KONG Deguang, SUN Shengrong
    Journal of Shandong University (Health Sciences). 2025, 63(1):  43-59.  doi:10.6040/j.issn.1671-7554.0.2024.1177
    Abstract ( 85 )   PDF (29152KB) ( 29 )   Save
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    Objective To investigate the mechanisms associated with endocrine therapy resistance in hormone receptor-positive(particularly Luminal A subtype)breast cancer, for overcoming clinical treatment challenges and improving patient outcomes. Methods Bioinformatics techniques were used to identify differential expression genes between endocrine therapy-sensitive and drug-resistant patients. Through pan-cancer analysis, Kaplan-Meier survival analysis, protein interaction network construction, correlation analysis with tumor-infiltrating immune cells, and in vitro cell experiments, the potential mechanisms underlying the role of the target gene were speculated and validated. Results VTCN1 attenuated the anticancer effect of Tamoxifen in MCF7 and T47D cells. This gene might alter the tumor microenvironment, particularly the tumor immune microenvironment, through regulatory factors such as Notch4, Slug, Sox2, LAG3, and PD-L1, promote epithelial-mesenchymal transition(EMT)and affect hormone receptor expression, ultimately lead to Tamoxifen resistance. Conclusion VTCN1 regulates the tumor microenvironment through EMT-related factors, thereby contributing to endocrine therapy resistance in hormone receptor-positive breast cancer.
    Machine learning model based on mammography and DCE-MRI to predict pathological complete response after neoadjuvant therapy in breast cancer: a dual center research
    LIU Jingjing, PANG Jing, ZHAO Xiaodan, LIN Xin, FU Min, CHEN Jingjing
    Journal of Shandong University (Health Sciences). 2025, 63(1):  60-72.  doi:10.6040/j.issn.1671-7554.0.2024.1296
    Abstract ( 116 )   PDF (7769KB) ( 32 )   Save
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    Objective To investigate the value of machine learning models based on mammography and dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in predicting pathological complete response(pCR)in breast cancer patients after neoadjuvant therapy(NAT). Methods A retrospective analysis of 396 breast cancer patients who underwent NAT followed by surgery from August 2016 to July 2023 at the Affiliated Hospital of Qingdao University(Institution 1)and Yantai Yuhuangding Hospital(Institution 2)was performed. A total of 320 patients from Institution 1 were randomly divided into a training set and a validation set in a ratio of 7∶3, and 76 patients from Institution 2 served as an independent external validation set. Regions of interest(ROI)were delineated on pre-NAT mammography and DCE-MRI images, followed by feature extraction and feature selection. The radiomics model was constructed using the support vector machine(SVM)algorithm. Clinical features underwent univariate and multivariate analyses, and statistically significant independent predictors were used to construct the clinical model. The comprehensive model integrating the radiomics signature and clinical predictors was constructed using the SVM algorithm. The performance of the models was evaluated using the area under the receiver operating characteristic(AUC)curve, accuracy, sensitivity, specificity, and F1-score. The calibration efficiency of the predictive models was evaluated by drawing calibration curves and decision curve analysis(DCA)was performed to evaluate the clinical utility of the predictive models. Results The combined radiomics model demonstrated better predictive performance than the clinical model, mammography radiomics model and MRI radiomics model, with AUCs of 0.899, 0.850, and 0.765 in the training, validation, and external validation sets, respectively. The comprehensive model showed the best predictive performance, with AUCs of 0.918, 0.856, and 0.795 in the training, validation, and external validation sets, respectively. The comprehensive model exhibited good calibration ability and clinical benefit. The Delong test showed statistically significant difference between the clinical model and the comprehensive model(P<0.05). Conclusion Machine learning models based on mammography and DCE-MRI effectively predict pCR in breast cancer patients after NAT, and demonstrate preferable predictive performance.
    Combined models based on preoperative ultrasound, inflammatory indicators and ultrasound radiomics for predicting axillary lymph node metastasis of breast cancer
    SUN Jing, YANG Ruimin, WANG Cong, ZHANG Yue, LUO Bing
    Journal of Shandong University (Health Sciences). 2025, 63(1):  73-80.  doi:10.6040/j.issn.1671-7554.0.2024.0810
    Abstract ( 126 )   PDF (4267KB) ( 18 )   Save
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    Objective To investigate the value of models based on preoperative ultrasound characteristics, inflammatory indicators and ultrasound radiomics features in predicting axillary lymph node(ALN)metastasis of breast cancer. Methods The breast ultrasound images and clinical data of 175 breast cancer patients were retrospectively analyzed. The 3D Slicer software was used to outline the region of interest and extract the radiomics features. The interclass correlation coefficient, Pearson correlation coefficients and recursive feature elimination were used to select the features. After the radiomics score(Radscore)was calculated, the radiomics model was constructed. The clinical model was constructed by screening clinical risk factors through univariate and multivariate Logistic regression, and then the Radscore was added to construct a combined prediction model. The predictive efficacy and clinical value of the models were assessed with the receiver operating characteristic(ROC)curve, calibration curve, and decision curve. Results Eighteen radiomics features were included in the radiomics model, and tumor size, ultrasound ALN status and platelet to lymphocyte ratio(PLR)were included in the clinical model. The tumor size, ultrasound ALN status, PLR and Radscore were included in the combined prediction model. The combined prediction model had the highest prediction efficacy. In the training and validation sets, the area under the curve(AUC)of the combined prediction model were 0.935 and 0.858, respectively. Conclusion The combined prediction model based on tumor size, ultrasound ALN status, inflammatory indicator PLR and ultrasound radiomics is effective in predicting ALN metastasis in breast cancer patients.
    Enhanced MRI-based subregional radiomics model can predict pathological complete response after neoadjuvant chemotherapy in breast cancer patients
    LI Yong, CUI Shujun, YANG Fei, ZHANG Fan, YIN Xiaoxia
    Journal of Shandong University (Health Sciences). 2025, 63(1):  81-89.  doi:10.6040/j.issn.1671-7554.0.2024.0558
    Abstract ( 93 )   PDF (5630KB) ( 10 )   Save
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    Objective To develop and validate a subregional radiomics model based on contrast-enhanced MRI to predict pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in breast cancer patients. Methods A total of 155 breast cancer patients who underwent NAC were retrospectively included, with 108 in the training set and 47 in the validation set. Subregion clustering was performed for each patients region of interest by using the K-means algorithm, and then high-dimensional radiomics features in the patients contrast-enhanced MRI were extracted using the Pyradiomics software package for each subregion. Mann-Whitney U test, Spearman correlation coefficient and least absolute shrinkage and selection operator(LASSO)algorithm were utilized for feature screening. The filtered optimal features were used to build each subregion single model in the training set by Logistic regression algorithm, and the same algorithm was used to fuse the subregion single models to build the subregion total model, which was visualized by using the nomogram, and the effectiveness of all models was verified in the validation set. Results The clinicopathological factors of the patients were not statistically different between the training and validation sets. The best clustering results for patients based on the K-means algorithm were 5 classes, and the area under curve(AUC)of the receiver operating characteristic(ROC)of the total subarea model built from the fusion of the 5 subarea single models in the training set and validation set was 0.898( 0.839-0.957)and 0.828(0.695-0.961), respectively. In the validation set, the ROC curves, clinical decision curves and calibration curves suggested that the subarea total model had better discriminative ability, calibration ability and clinical utility than the subarea single model. Conclusion The subregion total model can reveal tumor heterogeneity and help clinicians accurately predict pCR after NAC before treatment and has some ability to predict the post-treatment prognosis, highlighting the potential of artificial intelligence in improving individualized treatment for breast cancer patients.
    Clinical value of ultrasound radiomics based on peritumour-containing tissues in identifying benign and malignant breast nodules
    LU Xiaosong, YANG Ruimin, WANG Yicheng, ZHOU Haifeng, LUO Bing, LI Xiaoyu, LI Nana
    Journal of Shandong University (Health Sciences). 2025, 63(1):  90-98.  doi:10.6040/j.issn.1671-7554.0.2024.1064
    Abstract ( 113 )   PDF (7752KB) ( 11 )   Save
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    Objective To construct the radiomics model of ultrasound based on intratumoral and peritumoral 2 mm and 4 mm regions and to predict the clinical diagnostic value of these models in identifying benign and malignant breast nodules. Methods Retrospective collection of the ultrasound images of 220 female patients diagnosed as breast nodules by ultrasound were performed. The patients underwent surgery at the Frist Affiliated Hospital of Hebei North University. The breast nodule ultrasound images were randomly divided into a training set(n=154)and a test set(n=66)in a ratio of 7∶3. The region of interest(ROI)was outlined as the intratumoral group on the maximal section image of the breast nodule and automatically conformed to the outward extension of 2 mm and 4 mm, respectively, to obtain the peritumoral 2 mm group and peritumoral 4 mm group. The optimal imaging histological features of the intratumoral group, peritumoral 2 mm group and peritumoral 4 mm group were screened by LASSO regression to construct a Logistic regression models. The diagnostic efficacy of the models in the training set and test set were evaluated using AUC, sensitivity, specificity and Jordon index, and the statistical difference among the models were verified using Delong test. The predictive efficacy of radiomics models were assessed using calibration and decision curves. Results Among the three groups, the radiomics model of the peritumoral 4mm group had the best efficacy. The values of AUC in the intratumoral group, peritumoral 2 mm group and peritumoral 4 mm group in the training set were 0.886, 0.902, and 0.945, while those in the testing set were 0.793, 0.757, 0.901, respectively. In the training set, the values of AUC in the intratumoral group and the peritumoral 2 mm group were statistical different with that in the peritumoral 4 mm group(both P<0.05). The sensitivity, specificity and Yoden index of the peritumoral 4 mm group in the training set and test set were 0.927, 0.833, 0.760, and 0.879, 0.818, 0.697, respectively. Conclusion The ultrasound-based radiomics model of the peritumoral 4 mm group has better predictive value in identifying benign and malignant breast nodules compared to the intratumoral group and the peritumoral 2 mm group.
    Causal relationship between low grade serous ovarian cancer and breast cancer analyzed by Mendelian randomization
    YUAN Zonghuai, PAN Guangye, CHI Yuemei, AN Chuanguo, ZHANG Yonggang
    Journal of Shandong University (Health Sciences). 2025, 63(1):  99-107.  doi:10.6040/j.issn.1671-7554.0.2024.0935
    Abstract ( 225 )   PDF (8819KB) ( 85 )   Save
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    Objective To explore the causal relationship between low grade serous ovarian cancer(LGSOC)and breast cancer(BC). Methods The study employed a bidirectional two sample Mendelian randomization(MR)method, and utilized publicly available genetic data from genome-wide association studies in European populations, with single nucleotide polymorphisms(SNPs)as instrumental variables. The forward study used LGSOC as the exposure variable and BC as the outcome, while the reverse study used BC as the exposure variable and LGSOC as the outcome. In addition, subgroup analysis was conducted on four molecular subtypes of BC. Inverse variance weighted(IVW), MR Egger regression, weighted median, weighted model, and simple model were used to study the causal relationship between LGSOC and BC. The Cochrans Q test was used for heterogeneity of instrumental variables. The MR Egger intercept method was used to test horizontal pleiotropy. Results The positive study included 19 SNPs, and MR analysis showed a positive causal relationship between LGSOC and increased risk of BC(IVW: OR=1.05, 95%CI: 1.01-1.08, P=0.01). Subgroup analysis showed that LGSOC may have a causal relationship with estrogen receptor positive(ER+)BC(P=0.07). The reverse study included 95 SNPs, and the MR analysis results showed that there was no causal relationship between BC and increased risk of LGSOC(P>0.05). No significant heterogeneity or horizontal pleiotropy was found in both heterogeneity and pleiotropy tests(P>0.05). Conclusion There is a positive causal relationship between LGSOC and increased risk of BC in Europeans, which may increase the risk of ER+BC. The causal relationship between BC and increased risk of LGSOC is not supported.
    Current status of breast multidisciplinary treatment in 38 tertiary hospitals in Shandong Province, China
    AI Xiancheng, WANG Fei, ZHOU Wenzhong, YU Lixiang, ZHOU Fei, XIANG Yujuan, LI Liang, YU Zhigang
    Journal of Shandong University (Health Sciences). 2025, 63(1):  108-114.  doi:10.6040/j.issn.1671-7554.0.2024.0691
    Abstract ( 91 )   PDF (887KB) ( 26 )   Save
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    Objective To understand the development of breast multidisciplinary treatment(MDT)in tertiary hospitals in Shandong Province, and to promote the standardisation of MDT. Methods A simple random sampling was conducted on 38 tertiary hospitals in Shandong Province. A questionnaire survey was conducted to collect basic information on doctors, hospitals, MDT implementation, and MDT evaluation. The collected data underwent statistical analysis. Results A total of 35 hospitals(92.1%)established breast surgery services, while 17 and 13 established breast imaging and pathology subspecialties, respectively. It is noteworthy that 73.7% of the hospitals have been conducting MDTs for 3 to 10 years, and 47.4% were conducting weekly MDTs. All eight hospitals with well-established subspecialties had been conducting MDTs for more than five years, whereas only three hospitals without two major subspecialties had been conducting MDTs for more than five years. Hospitals with well-established subspecialties had a higher proportion of weekly MDTs. About 94.5% of the respondents believed that MDT optimised clinical diagnosis and treatment, 97.2% supported the establishment of an MDT database, but only 43.6% of hospitals have established a database. Furthermore, 88.2% of the respondents were satisfied with the MDT remuneration, and the difference in the distribution of the respondents satisfaction with different job titles was not statistically significant. Conclusion Breast MDT in tertiary hospitals in Shandong Province has developed earlier, but still needs to be improved continuously, and in the future, it needs to mobilise the enthusiasm of medical workers and further standardise and promote it.