Lung adenocarcinoma (LUAD) is one of the most malignant tumor types worldwide.

Cancer stem cells (CSCs) are responsible for the migration and recurrence of cancer progression. Small nucleolar RNAs (snoRNAs) play important roles in tumor development. However, how snoRNAs contribute to the regulation of the stemness of ovarian CSCs (OCSCs) remains unclear. In the present study, we found that SNORA72 was significantly upregulated in OVCAR-3 spheroids (OS) and CAOV-3 spheroids (CS) with the OCSC characteristics attained by serum-free culture in a suspension of OVCAR-3 (OV) and CAOV-3 (CA) cells. The overexpression of SNORA72 increased self-renewal abilities and migration abilities in OV and CA cells and upregulated the expressions of the stemness markers Nanog, Oct4, and CD133. In addition, the ectopic expression of SNORA72 can elevate the messenger RNA (mRNA) and protein expression levels of Notch1 and c-Myc in parental cells. The opposite results were observed in SNORA72-silenced OCSCs. Moreover, we found that Notch1 knockdown inversed the migration abilities and self-renewal abilities raised by overexpressing SNORA72. In summary, stemness transformation of ovarian cancer cells can be activated by SNORA72 through the Notch1/c-Myc pathway. This study introduces a novel therapeutic strategy for improving the treatment efficiency of ovarian cancer.

Background: Increasing studies have suggested that aberrant expression of microRNAs might play essential roles in the progression of cancers. In this study, we sought to construct a high-specific and superior microRNAs signature to improve the survival prediction of colon adenocarcinoma (COAD) patients. Methods:The genome-wide miRNAs, mRNA and lncRNA expression profiles and corresponding clinical information of COAD were collected from the TCGA database. Differential expression analysis, Kaplan-Meier curve and timedependent ROC curve were calculated and performed using R software and GraphPad Prism7. Univariate and multivariate Cox analysis was performed to evaluate the prognostic ability of signature. Functional enrichment analysis was analyzed using STRING database. Results:We identified ten prognosis-related microRNAs, including seven risky factors (hsa-miR-197, hsa-miR-32, hsa-miR-887, hsa-miR-3199-2, hsa-miR-4999, hsa-miR-561, hsa-miR-210) and three protective factors (hsa-miR-3917, hsa-miR-3189, hsa-miR-6854). The Kaplan-Meier survival analysis showed that the patients with high risk score had shorter overall survival (OS) in test series. And the similar results were observed in both validation and entire series. The time-dependent ROC curve suggested this signature have high accuracy of OS for COAD. The Multivariate Cox regression analysis and stratification analysis suggested that the ten-microRNA signature was an independent factor after being adjusted with other clinical characteristics. In addition, we also found microRNA signature have higher AUC than other signature. Furthermore, we identified some miRNA-target genes that affect lymphatic metastasis and invasion of COAD patients. Conclusion:In this study, we established a ten-microRNA signature as a potentially reliable and independent biomarker for survival prediction of COAD patients.

No abstract

Background: Alternative splicing (AS) is a pervasive and vital mechanism involved in the progression of various cancer. Studies confirm the importance of prognostic value of AS events in tumor patients, but systematic analysis of AS in triple-negative breast cancer (TNBC) is still lacking. Methods: Information from 115 TNBC patients from the Cancer Genome Atlas (TCGA) database were extracted. And we performed a comprehensive analysis of whole-genome AS events with corresponding clinical information to evaluate the roles of seven AS patterns. Prognostic analyses were performed with predictive models and splicing network built for TNBC patients. Results: Among 28,744 mRNA AS events in 20,353 genes, we detected 1,428 AS in 138 important survival genes related to the overall survival of TNBC patients event. Through functional and pathway enrichment analysis, we found that these genes are involved in ubiquitin-mediated proteolytic pathways. At 1800 days overall survival, the area under the ROC curve for prognostic signatures was 0.8. It shows that this model is very effective in differentiating patient prognosis. The use of Spearman's test to establish a potential regulatory network between survival-related AS events and abnormal SF indicates a clear trend in the role of SF in TNBC. Conclusions: In summary, we established a reliable and powerful TNBC prognostic signature. A splicing network that could be its underlying mechanism was discovered. Keywords: Alternative splicing; Triple-negative breast cancer; Prognosis; Splicing factor