Background: Pregnancy-associated breast cancer (PABC) is a special type of breast cancer that occurs during pregnancy and within 1 year after childbirth. With the rapid social development and the adjustment of reproductive policies in China, the average age of females at first childbirth is increasing, which is expected to lead to an increase in the incidence of PABC. This study aimed to accumulate clinical experience and to investigate and summarize the prevalence, diagnosis, and treatment of PABC based on large multicenter samples in China. Methods: According to the Chinese Society of Breast Surgery, a total of 164 patients with PABC in 27 hospitals from January 2016 to December 2018 were identified. The pregnancy status, clinicopathological features, comprehensive treatment methods, and outcomes were retrospectively analyzed. Survival curves were plotted using the Kaplan-Meier method. Results: A total of 164 patients of PABC accounted for 0.30% of the total number of cases in the same period; of which, 83 patients were diagnosed during pregnancy and 81 patients during lactation. The median age of PABC was 33 years (24–47 years). Stage I patients accounted for 9.1% (15/164), stage II 54.9% (90/164), stage III 24.4% (40/164), and stage IV 2.4% (4/164). About 9.1% (15/164) of patients were luminal A. Luminal B patients accounted the most (43.3% [71/164]). About 15.2% (25/164) of patients were human epidermal growth factor receptor 2 (Her-2) overexpression and 18.9% (31/164) of patients were triple-negative breast cancer. For pregnancy breast cancer, 36.1% (30/83) of patients received direct surgery and 20.5% (17/83) received chemotherapy during pregnancy. About 31.3% (26/83) chose abortion or induction of labor. The median follow-up time was 36 months (3–59 months); 11.0% (18/164) patients had local recurrence or distant metastasis and 3.0% (5/164) died. Conclusions: It is safe and feasible to standardize surgery and chemotherapy for PABC.

Background This study was aimed to explore the predictive ability of tumor infiltrating neutrophil (TIN) in patients with breast cancer treated with neoadjuvant chemotherapy (NACT). Furthermore, the significance of TIN’s dynamic change before and after NACT was investigated. Methods Between January 2004 and December 2017, a total of 133 patients with breast cancer who underwent NACT before surgery were enrolled in this retrospective cohort. Eighty-nine of them were able to get the core needle biopsy (CNB) samples and all the pathological samples after surgery were available. TIN was detected by immunohistochemical staining of CD66b. The optimal cut-off value was determined via receiver operating characteristic (ROC) curve analysis. The association of clinicopathologic characteristics and chemotherapy efficiency was analyzed using X2 test or Fisher’s exact test or t-test as appropriate, and the prognostic significances were assessed by univariate and multivariate analyses. Results Patients with higher TIN after NACT were confirmed to be significantly associated with worse prognosis (P = 0.002). After stratifying patients into two groups, high difference group was prone to have better chemotherapy efficiency (P < 0.001) and clinical outcome in both univariate (P = 0.002) and multivariate analyses (P = 0.003). Conclusions In this study, higher TIN after NACT was confirmed to be associated with breast cancer patients’ worse chemotherapy efficiency and shorter disease-free survival (DFS). Furthermore, the TIN’s dynamic change before and after NACT was firstly proved to be a more accurate predictive marker compared with TIN after NACT.

Background This study was aimed to establish the nomogram to predict patients’ axillary node status by using patients’ clinicopathological and tumor characteristic factors. Methods A total of 705 patients with breast cancer were enrolled in this study. All patients were randomly divided into a training group and a validation group. Univariate and multivariate ordered logistic regression were used to determine the predictive ability of each variable. A nomogram was performed based on the factors selected from logistic regression results. Receiver operating characteristic curve (ROC) analysis, calibration plots and decision curve analysis (DCA) were used to evaluate the discriminative ability and accuracy of the models. Results Logistic regression analysis demonstrated that CEA, CA125, CA153, tumor size, vascular-invasion, calcification, and tumor grade were independent prognostic factors for positive ALNs. Integrating all the predictive factors, a nomogram was successfully developed and validated. The C-indexes of the nomogram for prediction of no ALN metastasis, positive ALN, and four and more ALN metastasis were 0.826, 0.706, and 0.855 in training group and 0.836, 0.731, and 0.897 in validation group. Furthermore, calibration plots and DCA demonstrated a satisfactory performance of our nomogram. Conclusion We successfully construct and validate the nomogram to predict patients’ axillary node status by using patients’ clinicopathological and tumor characteristic factors.

BackgroundThis study aimed to construct a tumor microenvironment (TME)-related risk model to predict the overall survival (OS) of patients with breast cancer.MethodsGene expression data from The Cancer Genome Atlas was used as the training set. Differentially expressed gene analysis, prognosis analysis, weighted gene co-expression network analysis, Least Absolute Shrinkage and Selection Operator regression analysis, and Wald stepwise Cox regression were performed to screen for the TME-related risk model. Three Gene Expression Omnibus databases were used to validate the predictive efficiency of the prognostic model. The TME-risk-related biological function was investigated using the gene set enrichment analysis (GSEA) method. Tumor immune and mutation signatures were analyzed between low- and high-TME-risk groups. The patients’ response to chemotherapy and immunotherapy were evaluated by the tumor immune dysfunction and exclusion (TIDE) score and immunophenscore (IPS).ResultsFive TME-related genes were screened for constructing a prognostic signature. Higher TME risk scores were significantly associated with worse clinical outcomes in the training set and the validation set. Correlation and stratification analyses also confirmed the predictive efficiency of the TME risk model in different subtypes and stages of breast cancer. Furthermore, immune checkpoint expression and immune cell infiltration were found to be upregulated in the low-TME-risk group. Biological processes related to immune response functions were proved to be enriched in the low-TME-risk group through GSEA analysis. Tumor mutation analysis and TIDE and IPS analyses showed that the high-TME-risk group had more tumor mutation burden and responded better to immunotherapy.ConclusionThe novel and robust TME-related risk model had a strong implication for breast cancer patients in OS, immune response, and therapeutic efficiency.

Background Recurrent breast cancer occurs as a result of divergent gene expression in response to therapeutic intervention. A recent report showed that SOX11 , an embryogenic mammary transcription factor, is overexpressed in breast cancer. HER2 is also dysregulated in breast cancer stem cells; however, the relative expression of these two genes in recurrent breast cancer has not been investigated. Methods Mouse models of mild and advanced stage recurrent breast cancer were developed via implantation of different doses of 4T1 Luc2GFP cells. The cellular morphology of normal and recurrent breast cancer tissues was analyzed using standard histological methods. SOX11 , HER2 , and ALDH1 expression levels were analyzed via immunohistochemistry and western blotting. Results Histological analyses revealed that treatment with doxorubicin limited mild recurrent cancer but was ineffective against advanced stage recurrent cancers, as evidenced by increased cell proliferation. SOX11 was consistently overexpressed in mild and advanced stage breast cancers treated with doxorubicin, relative to HER2 , which exhibited reduced expression in response to doxorubicin treatment in both mild and advanced stage recurrent breast cancer. In advanced stage recurrent breast cancer, SOX11 expression was more readily observed across the cell surface and was correlated with the overexpression of the breast cancer stem cell marker ALDH1 . Conclusions These results show that SOX11 expression was directly associated with breast cancer stem cell populations. In contrast, HER2 expression was strongly associated with drug treatment effects, but was not correlated with breast cancer stem cell survival in recurrent breast cancer.