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Purpose Breast cancer (BC) remains a serious health threat for women due to its high incidence and the trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) could play important roles in various biological processes involved in the pathogenesis of BC. The present study aimed to identify potential prognostic biomarkers associated with BC. Methods Here, original gene expression profiles of patients with BC was downloaded from The Cancer Genome Atlas (TCGA) database. TargetScan, miRDB, and miRTarBase databases were used to predict the target genes of prognostic-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs), and Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers. Results A total of 218 DEMs and 2222 DEGs were extracted in which eight miRNAs were associated with prognosis, and 278 target DEGs were screened out incorporated into functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, five hub genes (CXCL12, IGF1, LEF1, MMP1, and RACGAP1) were observed as potential biomarkers for BC prognosis through survival analysis. Conclusion We performed a distinctive correlation analysis of miRNA-mRNA in BC patients, and identified eight miRNAs and five hub genes may be effective biomarkers for the prognosis of BC patients.

Recent studies have reported mixed results on the association between the pro-inflammatory dietary index and risk of breast cancer. We perform this comprehensive meta-analysis to figure out whether high dietary inflammatory index (DII) score is a risk factor for the occurrence of breast cancer. We comprehensively searched the PubMed, EMBASE and Cochrane databases to identify included studies updated to September 12, 2017. All studies that reported risk estimates by comparing the highest DII score to the lowest were assessed. A total of seven observational studies were identified: three case controls and four cohorts, involving 319,993 participants. Overall, the meta-analysis reported that individuals with the highest DII score were associated with a 25% increased risk of breast cancer versus those with the lowest DII score (relative risk [RR] = 1.25; 95% confidence interval [CI] 1.09–1.44; I2 = 82.7%, p = 0.000). Upon stratified analysis, significant positive associations remained for postmenopausal women (RR = 1.15; 95% CI 1.02–1.30; p = 0.020), case-control studies (RR = 1.68; 95% CI 1.13–2.49; p = 0.010), Asia (RR = 2.30; 95% CI 1.7–3.12; p = 0.0031) and Europe (RR = 1.26; 95% CI 1.01–1.58; p = 0.0477). When analysed on hormonal receptor status, 36% increased risk was explored for hormone-receptor negative. This meta-analysis suggested that more pro-inflammatory diets (higher DII scores) are associated with increased breast cancer incidence. However, the research is not about significant associations but about moderate effect sizes.

Background/purpose Cancer immunotherapy has revolutionized the clinical treatment of several tumors. Immune infiltration has been found to be closely related to clinical prognosis, but it shows limited activity in breast cancer (BC). Therefore, this study aimed to explore the infiltration pattern of immune cells in BC, and to find potential prognostic markers and new therapeutic targets.Patients and methods We downloaded the immune genome data of BC from the Cancer Genome Atlas (TCGA), and analyzed the tumor- infiltrating immune cells (TIICs) in BC for the first time using the CIBERSORT algorithm. The aim of this study was to assess the proportions of 22 immune cell subsets in BC and examine the correlation between each TIIC and overall survival (OS) as well as clinical characteristics.Results The results indicated that: (1) there was a significant difference between the immune infiltration spectrum of cancerous and adjacent tissues, with M2 macrophages, M0 macrophages, and CD4 + T cells being highly expressed in BC; (2) CD8 + T cells were positively correlated with activated CD4 + memory T cells and negatively correlated with M0 macrophages, and M2 macrophages was inversely correlated with M1 macrophages, T cells regulatory, T cells CD8; (3) T cells, macrophages and BC TNM stage, age, clinical stage were correlated (P < 0.05); and (4) high expression of M2 macrophage markers could be an independent biomarker of poor prognosis and a potential therapeutic target for BC.Conclusion This study provides a new research method for the systematic study of immune cells in the BC tumor microenvironment, and provides theoretical guidance for further experiments to verify M2 macrophages and T cell subsets as a potential target for immunotherapy and prognosis.

Long non‐coding RNAs (lncRNAs), which competitively bind miRNAs to regulate target mRNA expression in the competing endogenous RNAs (ceRNAs) network, have attracted increasing attention in breast cancer research. We aim to find more effective therapeutic targets and prognostic markers for breast cancer. LncRNA, mRNA and miRNA expression profiles of breast cancer were downloaded from TCGA database. We screened the top 5000 lncRNAs, top 5000 mRNAs and all miRNAs to perform weighted gene co‐expression network analysis. The correlation between modules and clinical information of breast cancer was identified by Pearson's correlation coefficient. Based on the most relevant modules, we constructed a ceRNA network of breast cancer. Additionally, the standard Kaplan‐Meier univariate curve analysis was adopted to identify the prognosis of lncRNAs. Ultimately, a total of 23 and 5 modules were generated in the lncRNAs/mRNAs and miRNAs co‐expression network, respectively. According to the Green module of lncRNAs/mRNAs and Blue module of miRNAs, our constructed ceRNA network consisted of 52 lncRNAs, 17miRNAs and 79 mRNAs. Through survival analysis, 5 lncRNAs (AL117190.1, COL4A2‐AS1, LINC00184, MEG3 and MIR22HG) were identified as crucial prognostic factors for patients with breast cancer. Taken together, we have identified five novel lncRNAs related to prognosis of breast cancer. Our study has contributed to the deeper understanding of the molecular mechanism of breast cancer and provided novel insights into the use of breast cancer drugs and prognosis.

Fubin Feng,1 Tingting Zhang,2 Fang Yin,3 Cun Liu,2 Jing Zhuang,1 Lingyu Qi,2 Xue Wang,4 Jia Li,5 Lu Wang,1 Jinhui Tian,6 Changgang Sun1,7 1Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, China; 2College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China; 3Department of Pediatrics, Weifang People’s Hospital, Weifang, Shandong Province, China; 4Department of Medicine, Qingdao University, Qingdao, Shandong Province, China; 5Department of Oncology, Weifang Medical University, Weifang, Shandong Province, China; 6Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, Gansu Province, China; 7Department of Oncology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China Purpose: Numerous HER2-targeted therapy clinical trials have demonstrated efficacy and safety in the first-line treatment of metastatic breast cancer (MBC). However, the direct or indirect comparison of these drugs is unclear. This network meta-analysis can solve this issue to some extent. Materials and methods: PubMed, Embase, and the Cochrane Library were searched for Phase II/III randomized controlled trials (RCTs) on metastatic HER2-positive breast cancer for first-line treatment up to December 16, 2017. Paired meta-analyses were performed to compare the regimens directly with the TP (trastuzumab plus taxane) regimen. Bayesian network meta-analysis was used to synthesize available evidence of direct or indirect comparison. Results: The database search identified 1,935 articles, among which 13 articles (10 RCTs) were eligible for the analysis involving 5,177 patients treated with 11 different regimens. The progression-free survival (PFS) in the Bayesian network meta-analysis suggested that the PTP (pertuzumab and trastuzumab plus taxane) regimen had the highest probability to be the preferred treatment (surface under the cumulative ranking [SUCRA]: 0.967) followed by the TPC (carboplatin and trastuzumab plus taxane) regimen (SUCRA: 0.923). The PTP regimen (SUCRA: 0.926) was similarly preferred for overall survival (OS). For objective response rate (ORR), the PTC regimen might be the optimal treatment (SUCRA: 0.935), followed by the PTP regimen. Conclusion: Overall, PTP might be the optimal first-line treatment for HER-2-positive MBC to improve the PFS and OS. Meanwhile, TPC might be most effective treatment in terms of the ORR. Regarding safety, the two regimens showed acceptable grade 3 or greater hematologic toxicity and heart failure. Keywords: breast cancer, metastasis, HER2-positive, HER2-targeted agents, network meta-analysis, randomized controlled trial

Background The optimal sequence of endocrine therapy in a neoadjuvant setting for hormone receptor-positive (HR+) breast cancer is unclear. Our study evaluated the efficacy and acceptability of neoadjuvant endocrine therapy for HR+ breast cancer. Methods We identified studies based on titles and abstracts that were published before 22 June 2018 in the following databases: PubMed, EMBASE, and the Cochrane Library. Eligible studies were randomised controlled trials with at least one arm that evaluated the effectiveness of one or a combination of anastrozole, letrozole, palbociclib, tamoxifen, fulvestrant, abemaciclib, everolimus, gefitinib, ribociclib, taselisib, and exemestane. We pooled effect sizes using the odds ratio (OR) and corresponding 95% credibility interval (95% CrI). The primary outcomes were response rate and treatment completion. Results Our network meta-analysis included 3,306 participants and 16 eligible studies, which assessed 15 treatments. In terms of response rates, compared with letrozole combined therapy, tamoxifen was associated with a significant reduction in response rate (OR, 0.34; 95% CrI, 0.13-0.85; OR, 0.32; 95% CrI, 0.13-0.80; OR, 0.26; 95% CrI, 0.09-0.83; and OR, 0.30; 95% CrI, 0.09-0.96; for letrozole plus everolimus, letrozole plus taselisib, letrozole plus zoledronic acid, and letrozole plus lapatinib, respectively). Based on the surface under the cumulative ranking curves ranking, letrozole plus zoledronic acid was associated with the highest rate of response (87.6%), followed by letrozole plus lapatinib (85.2%), and letrozole plus taselisib (79.3%). Conclusions Ultimately, our study established that letrozole plus zoledronic acid may be an optimal treatment based on its current rank in a neoadjuvant setting for HR+ breast cancer.

Background Breast cancer (BRCA) is the most prevalent cancer that threatens female health. A growing body of evidence has demonstrated the non-negligible effects of messenger RNAs (mRNAs) on biological processes involved in cancers; however, there is no definite conclusion regarding the role of mRNAs in predicting the prognosis of BRCA patients. Materials and methods We systematically screened the mRNA expression landscape and clinical data of samples from the Cancer Genome Atlas (TCGA). Univariate Cox analysis and robust likelihood-based survival analysis were conducted to identify key mRNAs associated with BRCA. Furthermore, risk scores based on multivariate Cox analysis divided the training set into high-risk and low-risk groups. ROC analysis determined the optimal cut-off point for patient classification of risk levels. The prognostic model was additionally validated in the testing set and complete dataset. Finally, we plotted the survival curves for the mRNAs used in our model. Results We obtained the original expression data of 13,617 mRNAs from a total of 1088 samples. After comprehensive survival analysis, the four-mRNA (ACSL1, OTUD3, PKD1L2, and WISP1) prognosis risk assessment model was constructed. Furthermore, the area under cure (AUC) was 0.834, indicating that the model was meaningful and reasonable. In each dataset, analysis based on the four-mRNA signature risk score indicated that the survival status of the group with high risk score was worse than that of the group with low risk scores. Patients with strong mRNA expression of OTUD3, PKD1L2, and WISP1 tended to have good prognosis, whereas patients with high ACSL1 expression tended to have poor prognosis. Conclusion In summary, we constructed a four-mRNA prognosis risk assessment model for BRCA. The newly developed model offers more possibilities for assessing prognosis and guiding the selection of better treatment strategies for BRCA.

// Cun Liu 1, * , Lu Wang 1, * , Jinhui Tian 2 , Lijuan Liu 3 , Linxiang Guo 4 , Guowen Ge 5 , Liang Zheng 6 , Fubin Feng 3 , Jinmei Zhang 7 , Tingting Zhang 1 and Changgang Sun 3, 8 1 College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, Shandong, PR China 2 Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, Gansu, PR China 3 Department of Oncology, Weifang Traditional Chinese Hospital, Weifang 261041, Shandong Province, PR China 4 School of Foreign Language Education, Qingdao University, Qingdao 266071, Shandong, PR China 5 Clinical College, Weifang Medical University, Weifang 261000, Shandong, PR China 6 Department of Cardiovascular Medicine, Research Center for Translational Medicine, Dongfang Hospital, Tongji University, Shanghai 200000, PR China 7 Department of Endocrinology, Weifang Traditional Chinese Hospital, Weifang 261041, Shandong, PR China 8 Department of Oncology, Affiliated Hospital of Weifang Medical University, Weifang 261031, Shandong, PR China * These authors contributed equally to this work and are co-first authors Correspondence to: Changgang Sun, email: zhongliuyike@163.com Keywords: breast cancer; Parkinson's disease; meta-analysis; risk Received: October 11, 2017 Accepted: December 05, 2017 Published: January 02, 2018 ABSTRACT Objective: We performed a meta-analysis to explore the association between breast cancer and Parkinson’s disease (PD). Materials and Methods: Specific literature searches were performed systematically using PubMed, Cochrane Library and EMBASE. Studies about the related risk estimates of breast cancer and PD were included in the meta-analysis. Results: A total of 22 sets of research data from 16 studies were analyzed. The combined odds ratio (OR) of the results was 1.13 (95% CI: 1.09–1.17). When stratified by PD diagnosis time, the ORs for the occurrence of breast cancer before and after PD diagnosis were 0.99 (95% CI: 0.89–1.09) and 1.15 (95% CI: 1.10–1.20). Subgroup analysis showed that the ORs for the cohort studies and for Caucasians were 1.13 (95% CI: 1.09,1.08) and 1.13 (95% CI: 1.09–1.17), respectively. No statistically significant risk estimates were found for studies in Asian and mixed populations as well as for case-control studies ( P > 0.05). Conclusions: The current evidence demonstrates a positive correlation between breast cancer and PD, especially following a diagnosis of PD and in Caucasians. Further studies are needed to determine the pathophysiologic mechanisms of this relationship.

Increasing evidence showed that Toll-like receptors (TLR), key receptors in innate immunity, play a role in cancer progression and development but activation of different TLRs might exhibit the exact opposite outcome, antitumor or protumor effects. TLR function has been extensively studied in innate immune cells, so we investigated the role of TLR signaling in breast cancer epithelial cells. We found that TLR5 was highly expressed in breast carcinomas and that TLR5 signaling pathway is overly responsive in breast cancer cells. Interestingly, flagellin/TLR5 signaling in breast cancer cells inhibits cell proliferation and an anchorage-independent growth, a hallmark of tumorigenic transformation. In addition, the secretion of soluble factors induced by flagellin contributed to the growth-inhibitory activity in an autocrine fashion. The inhibitory activity was further confirmed in mouse xenografts of human breast cancer cells. These findings indicate that TLR5 activation by flagellin mediates innate immune response to elicit potent antitumor activity in breast cancer cells themselves, which may serve as a novel therapeutic target for human breast cancer therapy. Cancer Res; 71(7); 2466–75. ©2011 AACR.

Background Bone scanning (BS), liver ultrasonography (LUS), and chest radiography (CXR) are commonly recommended for baseline staging in patients with newly diagnosed breast cancer. The purpose of this study is to demonstrate whether these tests are indicated for specific patient subpopulation based on clinical staging and molecular subtype. Methods A retrospective study on 5406 patients with newly diagnosed breast cancer was conducted to identify differences in occurrence of metastasis based on clinical staging and molecular subtypes. All patients had been evaluated by BS, LUS and CXR at diagnosis. Results Complete information on clinical staging was available in 5184 patients. For stage I, II, and III, bone metastasis rate was 0%, 0.6% and 2.7%, respectively (P