RESUMO
BACKGROUND: Benign prostatic hyperplasia (BPH) is the most common disease in elderly men. There is increasing evidence that periodontitis increases the risk of BPH, but the specific mechanism remains unclear. This study aimed to explore the role and mechanism of the key periodontal pathogen Porphyromonas gingivalis (P. gingivalis) in the development of BPH. METHODS: The subgingival plaque (Sp) and prostatic fluid (Pf) of patients with BPH concurrent periodontitis were extracted and cultured for 16S rDNA sequencing. Ligature-induced periodontitis, testosterone-induced BPH and the composite models in rats were established. The P. gingivalis and its toxic factor P. gingivalis lipopolysaccharide (P.g-LPS) were injected into the ventral lobe of prostate in rats to simulate its colonization of prostate. P.g-LPS was used to construct the prostate cell infection model for mechanism exploration. RESULTS: P. gingivalis, Streptococcus oralis, Capnocytophaga ochracea and other oral pathogens were simultaneously detected in the Pf and Sp of patients with BPH concurrent periodontitis, and the average relative abundance of P. gingivalis was found to be the highest. P. gingivalis was detected in both Pf and Sp in 62.5% of patients. Simultaneous periodontitis and BPH synergistically aggravated prostate histological changes. P. gingivalis and P.g-LPS infection could induce obvious hyperplasia of the prostate epithelium and stroma (epithelial thickness was 2.97- and 3.08-fold that of control group, respectively), and increase of collagen fibrosis (3.81- and 5.02-fold that of control group, respectively). P. gingivalis infection promoted prostate cell proliferation, inhibited apoptosis, and upregulated the expression of inflammatory cytokines interleukin-6 (IL-6; 4.47-fold), interleukin-6 receptor-α (IL-6Rα; 5.74-fold) and glycoprotein 130 (gp130; 4.47-fold) in prostatic tissue. P.g-LPS could significantly inhibit cell apoptosis, promote mitosis and proliferation of cells. P.g-LPS activates the Akt pathway through IL-6/IL-6Rα/gp130 complex, which destroys the imbalance between proliferation and apoptosis of prostate cells, induces BPH. CONCLUSION: P. gingivalis was abundant in the Pf of patients with BPH concurrent periodontitis. P. gingivalis infection can promote BPH, which may affect the progression of BPH via inflammation and the Akt signaling pathway.
Assuntos
Interleucina-6 , Porphyromonas gingivalis , Hiperplasia Prostática , Receptores de Interleucina-6 , Masculino , Hiperplasia Prostática/complicações , Porphyromonas gingivalis/patogenicidade , Ratos , Humanos , Animais , Interleucina-6/análise , Interleucina-6/metabolismo , Próstata , Periodontite/complicações , Periodontite/microbiologia , Idoso , Pessoa de Meia-Idade , Ratos Sprague-Dawley , Modelos Animais de Doenças , Transdução de Sinais/fisiologiaRESUMO
BACKGROUND: This study aims to analyze breast cancer burden attributable to high body mass index (BMI) and high fasting plasma glucose (FPG) in China from 1990 to 2019. METHODS: Data were obtained from the Global Burden of Disease (GBD) study 2019. Deaths and disability-adjusted life years (DALYs) were used for attributable burden, and age-period-cohort (APC) model was used to evaluate the independent effects of age, period and birth cohort. RESULTS: In 2019, the age-standardized mortality and DALY rates of breast cancer attributable to high BMI were 1.107 (95% UI: 0.311, 2.327) and 29.990 (8.384, 60.713) per 100 000, and mortality and DALY rates attributable to high FPG were 0.519 (0.095, 1.226) and 13.662 (2.482, 32.425) per 100 000. From 1990 to 2019, the age-standardized mortality and DALY rates of breast cancer attributable to high BMI increased by 1.192% and 1.180%, and the trends of high FPG were not statistically significant. The APC results showed that the age effects of high BMI and high FPG-mortality and DALY rates increased, with the highest rates in the age group over 80 years. The birth cohort effects of high BMI showed "inverted V" shapes, while high FPG showed downward trends. CONCLUSIONS: Age was the main reason for the increase of attributable burden, and postmenopausal women were the high-risk groups. Therefore, targeted prevention measures should be developed to improve postmenopausal women's awareness and effectively reduce the prevalence of obesity and diabetes, thereby reducing the breast cancer burden caused by metabolic factors in China.
Assuntos
Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/mortalidade , China/epidemiologia , Pessoa de Meia-Idade , Adulto , Idoso , Índice de Massa Corporal , Fatores de Risco , Estudos Epidemiológicos , Glicemia/metabolismo , Carga Global da Doença , População do Leste AsiáticoRESUMO
Aberrant autophagy could promote cancer cells to survive and proliferate in prostate cancer (PCa). LncRNAs play key roles in autophagy regulatory network. We established a prognostic model, which autophagy-related lncRNAs (au-lncRNAs) were used as biomarkers to predict prognosis of individuals with PCa. Depending on au-lncRNAs from the Cancer Genome Atlas and the Human Autophagy Database, a risk score model was created. To evaluate the prediction accuracy, the calibration, Kaplan-Meier, and receiver operating characteristic curves were used. To clarify the biological function, gene set enrichment analyses (GSEA) were performed. Quantitative real-time PCR (qRT-PCR) was employed to determine the au-lncRNAs expression in PCa cell lines and healthy prostate cells for further confirmation. We identified five au-lncRNAs with prognostic significance (AC068580.6, AF131215.2, LINC00996, LINC01125 and LINC01547). The development of a risk scoring model required the utilization of multivariate Cox analysis. According to the model, we categorized PCa individuals into low- and high-risk cohorts. PCa subjects in the high-risk group had a worse disease-free survival rate than those in the low-risk group. The 1-, 3-, and 5-year periods had corresponding areas under curves (AUC) of 0.788, 0.794, and 0.818. The prognosis of individuals with PCa could be predicted by the model with accuracy. Further analysis with GSEA showed that the prognostic model was associated with the tumor microenvironment, including immunotherapy, cancer-related inflammation, and metabolic reprogramming. Four lncRNAs expression in PCa cell lines was greater than that in healthy prostate cells. The au-lncRNA prognostic model has significant clinical implications in prognosis of PCa patient.