MicroRNA-550a is associated with muscle system conferring poorer survival for esophageal cancer.

Background Esophageal cancer (ESCA) is one of the most common cancers in the digestive tract. Approximately 300000 people on an average die of ESCA per year worldwide. The determination of key microRNAs for the prognosis of ESCA is of indispensable significance in the clinical treatment. Methods The differentially expressed microRNAs were screened by analyzing The Cancer Genome Atlas (TCGA) database. By using the survival data of the database, we analyzed correlation between patients' survival time and miR-550a expression levels. Differential expression analysis and gene set enrichment analysis were performed using the targeted data. Results It was found that patients with high miR-550a expression levels had shorter survival time. Data mining and signal pathway enrichment analysis of TCGA database showed that abnormal miR-550a expressions affected the recurrence of tumors by the muscle system regulation. Conclusions Through the proposed investigation, miR-550a is found to be a potential biomarker as well as non-coding therapeutic target for esophagus cancer. These results suggest that miR-550a may serve as a therapeutic target and predictor for ESCA survival.

An expression signature model to predict lung adenocarcinoma-specific survival.

BACKGROUND: The current TNM staging system plays a central role in lung adenocarcinoma (LUAD) prognosis. However, it may not adequately stratify the risk of tumor recurrence. With the aid of gene expression profiling, we identified 31 lncRNAs whose expressions in tumor tissues could be used as a risk indicator for the guidance of lung cancer therapy. This exploratory analysis may shed new light on identification of potential prognostic factors. MATERIALS AND METHODS: A survival prediction scoring model was developed from the data that are publicly available in The Cancer Genome Atlas (TCGA) LUAD RNA Sequencing dataset. Multivariate Cox regression analysis and Kaplan-Meier analysis were performed on a cohort of 254 stage I lung carcinoma patients with survival records. RESULTS: Our model indicates that the panels comprising 31 lncRNAs are highly associated with overall survival (OS): 18.9% (95% CI: 10.4%-34.5%) and 89.5% (95% CI: 80.7%-99.2%) for the high- and low-risk group, respectively. The specificity and sensitivity of the model are verified, which show that the area under receiver operating characteristic curve yields 0.881, meaning our model has good accuracy and it is feasible for further applications. CONCLUSION: The 31-lncRNA model might be able to predict OS in patients with LUAD with high accuracy. Its further applications in biomolecular experiments using clinical samples with independent cohorts of patients are needed to verify the results.

Detection of Rare Mutations in EGFR-ARMS-PCR-Negative Lung Adenocarcinoma by Sanger Sequencing.

PURPOSE: This study aimed to identify potential epidermal growth factor receptor (EGFR) gene mutations in non-small cell lung cancer that went undetected by amplification refractory mutation system-Scorpion real-time PCR (ARMS-PCR). MATERIALS AND METHODS: A total of 200 specimens were obtained from the First Affiliated Hospital of Guangzhou Medical University from August 2014 to August 2015. In total, 100 ARMS-negative and 100 ARMS-positive specimens were evaluated for EGFR gene mutations by Sanger sequencing. The methodology and sensitivity of each method and the outcomes of EGFR-tyrosine kinase inhibitor (TKI) therapy were analyzed. RESULTS: Among the 100 ARMS-PCR-positive samples, 90 were positive by Sanger sequencing, while 10 cases were considered negative, because the mutation abundance was less than 10%. Among the 100 negative cases, three were positive for a rare EGFR mutation by Sanger sequencing. In the curative effect analysis of EGFR-TKIs, the progression-free survival (PFS) analysis based on ARMS and Sanger sequencing results showed no difference. However, the PFS of patients with a high abundance of EGFR mutation was 12.4 months [95% confidence interval (CI), 11.6-12.4 months], which was significantly higher than that of patients with a low abundance of mutations detected by Sanger sequencing (95% CI, 10.7-11.3 months) (p<0.001). CONCLUSION: The ARMS method demonstrated higher sensitivity than Sanger sequencing, but was prone to missing mutations due to primer design. Sanger sequencing was able to detect rare EGFR mutations and deemed applicable for confirming EGFR status. A clinical trial evaluating the efficacy of EGFR-TKIs in patients with rare EGFR mutations is needed.

A community-based cross-sectional study of sleep quality in middle-aged and older adults.

BACKGROUND: Sleep quality has been widely studied among western countries. However, there is limited population-based evidence on insomnia in Chinese adult populations, especially in middle-aged and older adults. The aims of present study are to (1) examine the prevalence of poor sleep among Chinese middle-age and older adults, (2) compare the Pittsburgh Sleep Quality Index (PSQI) seven domain scores across different physical health statuses, (3) explore factors associated with insomnia. METHODS: A cross-sectional survey was conducted using a multi-instrument questionnaire. In total, 1563 residents aged 45 or older in the community were interviewed. The Chinese version of the PSQI was used to assess sleep quality while poor sleep was defined as a total PSQI score >5. Socio-demographic, lifestyle and physical health data were also collected. RESULTS: The prevalence of poor sleep among adults aged over 45 years was 20.67 %. Clusters logistic regression analysis identified that migrant workers, single marital status, lower education level, no physical exercise, illness within 2 weeks, and a higher total number of chronic diseases contribute to increased risk of poor sleep (P < 0.05). Among three clusters, physical health has the biggest independent contribution on sleep quality. CONCLUSIONS: Our results indicated that poor sleep was common in middle-aged and older adults. It was associated with identity of migrant worker, education level, exercise, illness within 2 weeks and number of chronic disease. Being ill within 2 weeks and having more chronic diseases were the major physical health-related factors contributing to poor sleep in the middle-aged and older people. Physical health may be a major determinant in sleep quality.