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Aim: This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）., Background: Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery., Methods: A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined., Results: Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1-19.1), compared to those who did achieve breast pCR, P < 0.001., Conclusion: For cN2 TN or HER2+ breast cancer patients who achieve breast pCR following NAT, consideration could be given to downstaging and performing an axillary SLNB or TAD., Competing Interests: Conflicts of interest Not declared., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: The prediction of axillary lymph node status after neoadjuvant chemotherapy (NAC) becoming critical because of the advocation of the de-escalation of axillary management. We investigate associated factors of axillary upstaging in clinical node-negative (cN0) breast cancer patients receiving NAC to develop and validate an accurate prediction nomogram., Methods: We retrospectively analyzed 1892 breast cancer patients with stage of cT1-3N0 treated by NAC and subsequent surgery between 2010 and 2020 in twenty hospitals across China. Patients randomly divided into a training set and validation set (3:1). Univariate and multivariate logistic regression analysis were performed, after which a nomogram was constructed and validated., Results: In total, pathologic node negativity (ypN0) achieved in 1406 (74.3%) patients and another 486 (25.7%) patients upstaged to pathologic node positive (ypN+). Breast pathologic complete response (bpCR) was achieved in 445 (23.5%) patients and non-bpCR in 1447 (76.5%) patients. A nomogram was established by ER, tumor histology, HER2 status, cycle of NAC treatment, and the bpCR, which were confirmed by multivariate logistic analysis as independent predictors of nodal upstaging in the training cohort (n = 1419). The area under the receiver operating characteristic curve (AUC) of the training cohort and validation cohort (n = 473) were 0.73 (95% CI 0.693-0.751) and 0.77 (95% CI 0.723-0.812) respectively., Conclusion: We present a nomogram with a nationwide large sample data which can effectively predict axillary upstaging after neoadjuvant chemotherapy to give better advice for individualized axillary lymph node management of breast cancer., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the breast cancer subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment show that the blue module genes engaged in cell cycle, DNA replication, p53 signaling pathway, and pathway in cancer. According to the connectivity analysis and survival analysis, 8 out of 96 hub genes were filtered and have shown the highest expression in basal-like breast cancer. Furthermore, the hub genes were validated by the external datasets and quantitative real-time PCR (qRT-PCR). In summary, hub genes of Cyclin E1 (CCNE1), Centromere Protein N (CENPN), Checkpoint kinase 1 (CHEK1), Polo-like kinase 1 (PLK1), DNA replication and sister chromatid cohesion 1 (DSCC1), Family with sequence similarity 64, member A (FAM64A), Ubiquitin Conjugating Enzyme E2 C (UBE2C) and Ubiquitin Conjugating Enzyme E2 T (UBE2T) may serve as the prognostic markers for different subtypes of breast cancer., (© 2021 The Author(s).)

Background: Breast cancer is the most frequently diagnosed cancer in women worldwide. When treated by chemotherapy and/or radiotherapy, there are various non-pharmacological adjuvant therapies (NPATs) recommended for helping the patients with breast cancer alleviate multiple side effects induced by chemotherapy and/or radiotherapy and improve quality of life (QoL). However, the existing evidence does not suggest the therapy with the best effectiveness among a variety of NPATs. This study is to compare the effectiveness of different NPATs on QoL in the patients with breast cancer using Bayesian network meta-analysis (NMA)., Methods and Analysis: We will conduct a comprehensive search strategy in the relevant databases (MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, World Health Organization (WHO), International Clinical Trials Registry Platform (ICTRP) search portal (http://apps.who.int/trialsearch/Default.aspx), Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wan Fang Data). The random or quasi-random controlled trails that compare different NPATs in patient with breast cancer who received the chemotherapy and/or radiotherapy will be included. We only focus on the outcome of QoL which can be assessed by a series of tools. The risk of bias for included studies will be appraised using the Cochrane Collaboration's tool for assessing risk of bias. The standard pairwise meta-analysis and a Bayesian NMA will be conducted., Ethics and Dissemination: Ethical approval and patient consent are not required since this is an NMA based on published studies. We will submit our NMA to a peer-reviewed journal for publication., Prospero Registration Number: CRD42017078143.

Breast cancer is one of the most prevalent malignancies and the leading cause of cancer‑associated mortality in women worldwide and in China. Everolimus (C53H83NO14) is an efficient anti-cancer drug for breast cancer which targets mammalian target of rapamycin (mTOR). The present study investigated the inhibitory effects of everolimus on breast cancer cells and an MCF‑7‑bearing mouse model. The potential mechanism of the everolimus‑mediated decrease in growth and aggressiveness of breast cancer cells was reported. Results demonstrated that everolimus significantly inhibited breast cancer cell growth, migration and invasion. It was demonstrated that everolimus induced apoptosis through decreasing B cell lymphoma (Bcl)‑2 and Bcl‑w and increasing caspase‑3 and caspase‑8 expression levels in breast cancer cells. It was observed that everolimus decreased phosphoinositide 3‑kinase (PI3K), protein kinase B (AKT) and mTOR expression levels in breast cancer cells. Results additionally demonstrated that PI3 K overexpression prevented that everolimus‑mediated inhibition of growth and aggressiveness in MCF‑7 cells. In vivo assays demonstrated that everolimus treatment markedly inhibited tumor growth in the MCF‑7 bearing mouse model. Overall, these data indicate that everolimus inhibits growth and aggressiveness of breast cancer cells through the PI3K/AKT/mTOR signaling pathways, suggesting the PI3K/AKT/mTOR signaling pathway may act as a therapeutic target for the treatment of human cancer.