Search

Abstract Background The causal relationship between breast cancer (BC) and the oral microbiome remains unclear. In this case–control study, using two‐sample Mendelian randomization (MR), we thoroughly explored the relationship between the oral microbiome and BC in the East Asian population. Methods Genetic summary data related to oral microbiota and BC were collected from genome‐wide association studies involving participants of East Asian descent. MR estimates were generated by conducting various analyses. Sequencing data from a case–control study were used to verify the validity of these findings. Results MR analysis revealed that 30 tongue and 37 salivary bacterial species were significantly associated with BC. Interestingly, in both tongue and salivary microbiomes, we observed the causal effect of six genera, namely, Aggregatibacter, Streptococcus, Prevotella, Haemophilus, Lachnospiraceae, Oribacterium, and Solobacterium, on BC. Our case–control study findings suggest differences in specific bacteria between patients with BC and healthy controls. Moreover, sequencing data confirmed the MR analysis results, demonstrating that compared with the healthy control group, the BC group had a higher relative abundance of Pasteurellaceae and Streptococcaceae but a lower relative abundance of Bacteroidaceae. Conclusions Our MR analysis suggests that the oral microbiome exerts a causative effect on BC risk, supported by the sequencing data of a case–control study. In the future, studies should be undertaken to comprehensively understand the complex interaction mechanisms between the oral microbiota and BC.

Abstract Background Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown. Methods Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner. Results We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients. Conclusions Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification. Graphical Abstract

Abstract. Background:. Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. Methods:. In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan–Meier analysis, receiver operating characteristic curve (ROC). Results:. A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes (CKMT1B, SMR3B, and OR11M1P) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. Conclusions:. A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.

Abstract Background Due to the rarity of PBL and the lack of large-scale studies, the prognostic value of IPI in PBL was controversial. Especially in the rituximab era, the ability of IPI to stratify prognosis in patients receiving immunochemotherapy was severely reduced. Then revised IPI (R-IPI) and National Comprehensive Cancer Network IPI (NCCN-IPI) were introduced. The present study aimed to evaluate the prognostic value of IPI and the other IPIs in patients with PBL in a Chinese population. Methods We performed a multicenter retrospective study of 71 patients with PBL from 3 institutions in China. The Kaplan–Meier method and log-rank tests were used for the survival analysis. Cox regression analysis was performed to evaluate the prognostic factors. Subgroup analysis was performed to assess the prognostic significance of IPI scores, R-IPI scores, and NCCN-IPI scores. Results The median follow-up was 4.7 years (0.7–21.8 years). The 5-year progression-free survival (PFS) and overall survival (OS) rates were 90.2% and 96.3%. In the multivariate analysis, only IPI scores and radiotherapy were significantly associated with OS and PFS (P 0.05). Conclusions Our study confirms the prognostic value of IPI in patients with PBL, but the predictive value of IPI proved to be relatively low with the addition of the rituximab. The R-IPI and NCCN-IPI can accurately assess the high and low-risk groups of PBL patients but were insufficient to evaluate the intermediate risk group.

BackgroundPrevious observational studies have showed that certain psychiatric disorders may be linked to breast cancer risk, there is, however, little understanding of relationships between mental disorders and a variety of breast diseases. This study aims to investigate if mental disorders influence the risks of overall breast cancer, the two subtypes of breast cancer (ER+ and ER-), breast benign tumors and breast inflammatory diseases.MethodsDuring our research, genome-wide association study (GWAS) data for seven psychiatric disorders (schizophrenia, major depressive disorder, bipolar disorder, post-traumatic stress disorder, panic disorder, obsessive-compulsive disorder and anorexia nervosa) from the Psychiatric Genomics Consortium (PGC) and the UK Biobank were selected, and single-nucleotide polymorphisms (SNPs) significantly linked to these mental disorders were identified as instrumental variables. GWAS data for breast diseases came from the Breast Cancer Association Consortium (BCAC) as well as the FinnGen consortium. We performed two-sample Mendelian randomization (MR) analyses and multivariable MR analyses to assess these SNPs’ effects on various breast diseases. Both heterogeneity and pleiotropy were evaluated by sensitivity analyses.ResultsWhen the GWAS data of psychiatric disorders were derived from the PGC, our research found that schizophrenia significantly increased the risks of overall breast cancer (two-sample MR: OR 1.05, 95%CI [1.03-1.07], p = 3.84 × 10−6; multivariable MR: OR 1.06, 95%CI [1.04-1.09], p = 2.34 × 10−6), ER+ (OR 1.05, 95%CI [1.02-1.07], p = 5.94 × 10−5) and ER- (two-sample MR: OR 1.04, 95%CI [1.01-1.07], p = 0.006; multivariable MR: OR 1.06, 95%CI [1.02-1.10], p = 0.001) breast cancer. Nevertheless, major depressive disorder only showed significant positive association with overall breast cancer (OR 1.12, 95%CI [1.04-1.20], p = 0.003) according to the two-sample MR analysis, but not in the multivariable MR analysis. In regards to the remainder of the mental illnesses and breast diseases, there were no significant correlations. While as for the data from the UK Biobank, schizophrenia did not significantly increase the risk of breast cancer.ConclusionsThe correlation between schizophrenia and breast cancer found in this study may be false positive results caused by underlying horizontal pleiotropy, rather than a true cause-and-effect relationship. More prospective studies are still needed to be carried out to determine the definitive links between mental illnesses and breast diseases.

Whether or not bacteria exist in the placenta is a controversial issue. In the present study, bacteria in the placenta and blood of pregnant mice were evaluated after administration of Enterococcus faecalis, Lactobacillus reuteri, Lactococcus lactis, Lactobacillus johnsonii, Streptococcus thoraltensis, and Staphylococcus epidermidis. Results showed that 57.14–85.71 ​% of the placentas and 71.43%–100 ​% of the blood samples positively existed spherical and/or rod-shaped bacteria. All collected placentas treated with or without propidium monoazide were shown to harbor various bacteria using the denaturing gradient gel electrophoresis (DGGE) method. Moreover, E. faecalis and L. lactis were characterized as the dominant and common bacteria in each group. Our results prove the existence of bacteria in the placenta and blood of pregnant mice, which provides clues for researchers to study the role of these bacteria on host health and the development of the fetus.

In the 21st century, the incidence of preterm birth has continued to increase. According to statistics, preterm birth accounts for 5%–18% of all births worldwide, and 70%–75% of perinatal deaths are related to preterm birth. Preterm birth is not only a cardiopulmonary defect for the baby, but also has a negative impact on the mother's health. Many studies have shown that vaginal microecological dysbiosis-related diseases are the most common causes of preterm birth, such as bacterial vaginosis (BV), vulvovaginal candidiasis (VVC), group B streptococcal (GBS) infections and other infectious diseases. Therefore, we have a review of the deeper understanding of the links and mechanisms between vaginal microecological dysbiosis-related diseases and preterm birth. In addition, timely restoration of vaginal microecology through microbial therapy become the key to prevent and reduce the incidence of preterm birth.

Infertility is one of the most common reproductive system diseases, and no effective method is available for its treatment. Although in vitro fertilization (IVF) has been widely used to enhance the clinical pregnancy outcome of infertility, the unsatisfied pregnancy rate with unknown reasons is obtained. To identify the possible cause of IVF failure, 555 patients were enrolled in the present study to determine their relevant clinical characteristics and vaginal microbiota. Our results indicated that the age and endometrium thickness significantly affected the pregnancy success rate of pregnant patients (P group) and non-pregnant patients (NP group) receiving IVF, and high values of luteinizing hormone, estrogen and progesterone were observed from P group. Furthermore, the Partial Least Squares Discriminant Analysis (PLS-DA) indicated a different microbial composition in P group and NP group, and a higher microbial abundance had been identified in non-pregnant patients compared with pregnant patients. At phylum level, a higher abundance of Firmicutes and Proteobacteria, and a lower abundance of Actinobacteria, Fusobacteria, and Bacteroidetes were obtained in pregnant patients compared with non-pregnant patients. At genus level, a lower abundance of the probiotic Lactobacillus, and higher abundance of pathogens Gardnerella and Prevotella were identified from non-pregnant patients. Therefore, the disordered microbiota, characterizing by the reduction of probiotics and overgrowth of pathogens in non-pregnant patients, may be used as a potential indicator for a higher IVF failure rate.

Tooth brushing is necessary to maintain oral health. Little research has been carried out to explore microbial diversity in toothbrushes and to study the potential impact of these bacteria on human health. In the present study, 20 participants were enrolled, and the microbial diversity in their oral cavity and toothbrushes was investigated using high-throughput sequencing. Our results indicate that 1,136 and 976 operational taxonomic units (OTUs) were obtained from groups CB (samples from toothbrushes of participants using traditional Chinese medicinal toothpaste) and AB (samples from toothbrushes of those using antibacterial toothpaste), respectively. The pathogens Acinetobacter baumannii, Staphylococcus aureus, and Candida albicans were identified on toothbrushes. The presence of these pathogens increases the chance for the host to get infectious diseases, neurodegenerative diseases, cardiovascular diseases, and cancers. Moreover, our in vitro results indicate that traditional Chinese medicinal toothpaste and antibacterial toothpaste can not only inhibit the growth of pathogens but also markedly inhibit the growth of probiotics Lactobacillus salivarius and Streptococcus salivarius. Therefore, the inhibitory effect of toothpaste on probiotics, together with the existence of pathogens in toothbrushes, indicates a potential risk of tooth brushing for people in a sub-healthy state.

Diabetes has steadily increased in the past few decades and causes huge influences on human health care and socioeconomic development, and drugs with minimal or no side effects for diabetes are imminent. In the present study, probiotic combination containing five selected probiotics were used to treat diabetes, the high glucose consumption capability and sound probiotic characteristics in vitro showed that the probiotics could consume all glucose within 24 h, and could tolerate low potential of hydrogen (pH) (pH = 2) and high bile salt concentration (0.3%), and they also had sound oxidation resistance [2,2-diphenyl-1-picrylhydrazyl (DPPH),∙O2−, OH, Fe2+ chelation, and the reducing powers] and antibacterial activity, highly adhere to HT-29 cells and markedly reduced the chance for pathogens to adhere to HT-29 cell (p