Identification of functional lncRNAs in atrial fibrillation based on RNA sequencing.

BACKGROUND: Atrial fibrillation (AF) is one of the most common arrhythmia contributing to serious conditions such as stroke and heart failure. Recent studies demonstrated that long noncoding RNAs (lncRNAs) were related to cardiovascular disease. However, the molecular mechanisms of AF are not fully clear. This study intended to discover lncRNAs that are differentially expressed in AF compared with controls and evaluate the potential functions of these lncRNAs. METHODS: Ninety-seven patients (49 patients with AF and 48 patients without AF) were included in this study. Among these patients, leucocyte suspensions of 3 AF patients and 3 controls were sent for RNA-seq analysis to select differentially expressed lncRNA and mRNA. Different lncRNA expressions were validated in another samples (46 AF patients and 45 controls). Gene ontology (GO) enrichment analysis was conducted to annotate the function of selected mRNAs. Alternative splicing (AS) analysis was performed and a lncRNA-mRNA network was also constructed. The receiver operating characteristics (ROC) curve was used to evaluate diagnostic values. Logistic regression analysis was utilized to assess the risk or protective factor of AF. RESULTS: A total of 223 mRNAs and 105 lncRNAs were detected in AF patients compared with controls. Total 4 lncRNAs (LINC01781, AC009509.2, AL662844.3, AL662844.4) associated with AF were picked out for validation in another samples by quantitative real-time PCR (qRT-PCR), detecting that upregulated AC009509.2 and downregulated LINC01781 in AF patients. Multivariate logistic regression analysis illustrated that left atrial diameter (OR 1.201; 95% CI 1.093-1.320; P=0.000) and AC009509.2 (OR 1.732; 95% CI 1.092-2.747; P=0.020) were related to AF respectively. ROC curve showed that AC009509.2, LINC01781 and left atrial diameter (LAD) were predictors of AF. For LINC01781, the area under the curve (AUC) was 0.654 (95% CI 0.541-0.767, P=0.0113). For AC009509.2, the AUC was 0.710 (95% CI 0.599-0.822, P=0.0005). Bioinformatic methods (GO enrichment, AS analysis and lncRNA-mRNA network construction) were performed to reveal the role of lncRNAs. CONCLUSIONS: This study discussed differentially expressed lncRNA and their potential interaction with mRNA in AF. LncRNA AC009509.2 could be a new potential biomarker for AF prediction.

Immune microenvironment and clinical feature analyses based on a prognostic model in lymph node-positive breast cancer.

Background: If lymph node metastasis occurs in breast cancer patients, the disease can progress rapidly. Based on the infiltrative immune cells of breast cancer patients with lymph node positivity, we constructed the LNPRS for selecting prognostic predictors. Methods: The LNPRS was established and the predictive value of the LNPRS was verified by independent testing cohorts. A nomogram was also established to confirm the therapeutic guidance significance of the LNPRS. The correlation of the LNPRS with tumor mutation burden, immune microenvironment score, immune checkpoints, the proportion of tumor-infiltrating immune cells, and GSEA and GSVA enrichment pathways were also evaluated. Results: In the training cohort, the overall survival of breast cancer patients who had high LNPRS was shorter than that of patients who had low LNPRS (7.98 years versus 20.42 years, P-value< 8.16E-11). The AUC values for 5-, 10-, and 15-years were 0.787, 0.739, and 0.800, respectively. The ability to predict prognosis for the LNPRS was also tested in 3 independent testing cohorts. Furthermore, the predictive value of the LNPRS for chemotherapy and immunotherapy was also proven. The GSEA and GSVA showed that the LNPRS was closely related to the activation of T and B lymphocytes and IFN-γ secretion. Moreover, breast cancer patients with low LNPRS had higher TME scores than those with high LNPRS. Conclusion: We can conclude that the LNPRS is a robust prognostic biomarker in breast cancer patients with positive lymph nodes and may be helpful for patients to make a clinical decision.

Peroxiredoxin-1 Overexpression Attenuates Doxorubicin-Induced Cardiotoxicity by Inhibiting Oxidative Stress and Cardiomyocyte Apoptosis.

Background. Previous research has shown that peroxiredoxin 1 (Prdx1) is an important modulator of physiological and pathophysiological cardiovascular events. This study is aimed at investigating the role and underlying mechanism of Prdx1 in doxorubicin- (DOX-) induced cardiotoxicity. Cardiac-specific expression of Prdx1 was induced in mice, and the mice received a single dose of DOX (15 mg/kg) to generate cardiotoxicity. First, our study demonstrated that Prdx1 expression was upregulated in the heart and in cardiomyocytes after DOX treatment. Second, we provided direct evidence that Prdx1 overexpression ameliorated DOX-induced cardiotoxicity by attenuating oxidative stress and cardiomyocyte apoptosis. Mechanistically, we found that DOX treatment increased the phosphorylation level of apoptosis signal-regulating kinase-1 (ASK1) and the downstream protein p38 in the heart and in cardiomyocytes, and these effects were decreased by Prdx1 overexpression. In contrast, inhibiting Prdx1 promoted DOX-induced cardiac injury via the ASK1/p38 pathway. These results suggest that Prdx1 may be an effective therapeutic option to prevent DOX-induced cardiotoxicity.