MicroRNAs (miRNA), small noncoding RNA molecules, are endogenous regulators of gene expression that have been implicated in the pathogenesis of various diseases such as cancer and arthritis. The aim of this study was to explore the biological function of microRNA-16-5p (miR-16-5p) and the molecular mechanism in osteoarthritis (OA). MiRNA targets were identified using bioinformatics. Using real-time PCR, the expression of miR-16-5p and SMAD3 in cartilage specimens was determined in 10 patients with knee OA and in 10 traumatic amputees (control). Functional analysis of miR-16-5p in chondrocytes was performed at both mRNA and protein levels after miRNA transfection. A luciferase reporter assay was used to verify interaction between miRNA and target mRNA. Expression of miR-16-5p was significantly higher in OA cartilages than in healthy cartilages. The data from the reporter assay and western blots indicated that miR-16- 5p regulated SMAD3 expression. Functional analysis showed that miR-16-5p could reduce expression of type IIcollagen and aggrecan while inducing expression of matrix metalloproteinases and ADAMTS; however, miR-16-5p inhibition could reverse these effects. Our results indicate that miR-16-5p is an important regulator of SMAD3 expression in human chondrocytes and may contribute to the development of OA.

Primary platinum-based chemoresistance occurs in approximately one-third of patients with serous ovarian cancer (SOC); however, traditional clinical indicators are poor predictors of chemoresistance. So we aimed to identify novel genes as predictors of primary platinum-based chemoresistance. Gene expression microarray analyses were performed to identify the genes related to primary platinum resistance in SOC on two discovery datasets (GSE51373, GSE63885) and one validation dataset (TCGA). Univariate and multivariate analyses with logistic regression were performed to evaluate the predictive values of the genes for platinum resistance. Machine learning algorithms (linear kernel support vector machine and artificial neural network) were applied to build prediction models. Univariate and multivariate analyses with Cox proportional hazards regression and log-rank tests were used to assess the effects of these gene signatures for platinum resistance on prognosis in two independent datasets (GSE9891, GSE32062). AGGF1 and MFAP4 were found highly expressed in patients with platinum-resistant SOC and independently predicted platinum resistance. Platinum resistance prediction models based on these targets had robust predictive power (highest AUC: 0.8056, 95% CI: 0.6338-0.9773; lowest AUC: 0.7245, 95% CI: 0.6052-0.8438). An AGGF1- and MFAP4-centered protein interaction network was built, and hypothetical regulatory pathways were identified. Enrichment analysis indicated that aberrations of extracellular matrix may play important roles in platinum resistance in SOC. High AGGF1 and MFAP4 expression levels were also related to shorter recurrence-free and overall survival in patients with SOC after adjustment for other clinical variables. Therefore, AGGF1 and MFAP4 are potential predictive biomarkers for response to platinum-based chemotherapy and survival outcomes in SOC.

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A number of studies revealed that CCNE1 copy number amplification and overexpression (on mRNA or protein expression level) were associated with prognosis of diverse cancers, however, the results were inconsistent among studies. So we conducted this systematic review and meta-analysis to investigate the prognostic values of CCNE1 amplification and overexpression in cancer patients. PubMed, Cochrane library, Embase, CNKI and WanFang database (last update by February 15, 2018) were searched for literatures. A total of 20 studies were included and 5 survival assessment parameters were measured in this study, which included overall survival (OS), progression free survival (PFS), recurrence free survival (RFS), cancer specific survival (CSS) and distant metastasis free survival (DMFS). Pooled analyses showed that CCNE1 amplification might predict poor OS (HR=1.59, 95% CI: 1.05-2.40, p=0.027) rather than PFS (HR=1.49, 95% CI: 0.83-2.67, p=0.177) and RFS (HR=0.982, 95% CI: 0.2376-4.059, p=0.9801) in various cancers; CCNE1 overexpression significantly correlated with poor OS (HR=1.52, 95% CI: 1.05-2.20, p=0.027), PFS (HR=1.20, 95% CI: 1.07-1.34, p=0.001) and DMFS (HR=1.62, 95% CI: 1.09-2.40, p=0.017) rather than RFS (HR=1.68, 95% CI: 0.81-3.50, p=0.164) and CSS (HR=1.54, 95% CI: 0.74-3.18, p=0.246). On the whole, these results indicated CCNE1 amplification and overexpression were associated with poor survival of patients with cancer, suggesting that CCNE1 might be an effective prognostic signature for cancer patients.

Osteosarcoma (OS) is the most common primary bone malignancy, predominately affecting children and adolescents. Due to the introduction of chemotherapy, the 5-year survival rate of OS patients has dramatically improved to 60-70%. Unfortunately, OS patients with recurrence or metastatic disease have less than a 20% chance of long-term survival, despite aggressive therapies. In this study, we aimed to identify gene expression patterns associated with metastasis and recurrence in order to identify potential biomarkers with prognostic power. We found that high expression of polyglutamine tract-binding protein 1 ( PQBP1 ) and low expression of phosphoenolpyruvate carboxykinase 2 ( PCK2 ) were related to a high probability of recurrence and metastasis in OS patients and also predicted shorter recurrence-free survival (RFS) and metastasis-free survival (MFS) after adjustment for other clinical variables. Prediction models based on the combination of PQBP1 and PCK2 expression had good and robust predictive power for recurrence and metastasis. A PQBP1 and PCK2-centered protein interaction network was built, and the hypothetical regulatory path between them was identified and termed the PQBP1-SF3A2-UBA52-PCK2 axis. Gene enrichment analysis indicated that aberrations of metabolism might play an important role in recurrence and metastasis in OS patients. Accordingly, PQBP1 and PCK2 are crucial for recurrence and metastasis in OS, and these findings provide a molecular basis for the exploitation of diagnostic and therapeutic strategies for overcoming recurrence and metastasis in OS.

Although co-culture of paddy fields with aquatic animals is lucrative, the ecological impacts of high-protein content entering the agricultural soil via animal pellet feed and feces have not been well studied. Moreover, the effects of dietary protein on soils and soil microbes remain unclear. To elucidate this, we examined soil bacterial and fungal community composition and temporal changes in paddy fields subjected to different protein-content diets via 16S/18S rRNA gene amplicon sequencing analysis with a high-throughput next-generation sequencer. MiSeq sequencing revealed that protein content significantly impacted fungal community structure. High-protein diets reduced bacterial community diversity and relative abundance in both July and October. The phylum-level bacterial taxonomic composition was not affected by diet treatment, while in fungi, a major phylum-level shift was evident. Hierarchically clustered analysis showed that high-protein diets significantly reduced the relative abundance of Brevundimonas in both July and October. Saprotrophic macrofungal diversity was negatively related to dietary protein content. Considering microbial community structure and environmental factors, ca. 15% protein content is appropriate for the rice-crab co-culture system that we studied.

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