Background: Long non‐coding RNAs (lncRNAs) have critical functions within esophageal squamous cell carcinoma (ESCC). However, the function and mechanism underlying ESCC‐associated lncRNA‐1 (ESCCAL‐1) in ESCC tumorigenesis have not been well clarified.Methods: ESCCAL‐1, miR‐590 and LRP6 were quantified using qRT‐PCR. Cell viability, migration and invasion abilities were measured using CCK‐8 assay and transwell assays. The protein pression was determined with western blot assay. The xenograft model assays were used to examine the impact of ESCCAL‐1 on tumorigenic effect in vivo. Direct relationships among ESCCAL‐1, miR‐590 and LRP6 were confirmed using dual‐luciferase reporter assays.Results: The present work discovered the ESCCAL‐1 up‐regulation within ESCC. Furthermore, ESCCAL‐1 was found to interact with miR‐590 and consequently restrict its expression. Functionally, knocking down ESCCAL‐1 or over‐expressing miR‐590 hindered ESCC cell growth, invasion, and migration in vitro. Moreover, inhibition of miR‐590 could reverse the effect of knockdown of ESCCAL‐1 on cells. Importantly, it was confirmed that LRP6 was miR‐590’s downstream target and LRP6 over‐expression also partly abolished the role of miR‐590 overexpression in ESCC cells.Conclusion: We have uncovered a novel regulatory network comprising aberrant interaction of ESCCAL‐1/miR‐590/LRP6 participated in ESCC progression.

The present work aimed to establish a new model to accurately estimate overall survival (OS) as well as cancer-specific survival (CSS) of osteosarcoma. Osteosarcoma cases were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017 and randomized as training or validation sets. Then, the OS- and CSS-related variables were discovered through multivariate Cox regression analysis to develop new nomograms to predict the 1-, 3- and 5-year OS and CSS. Besides, consistency index (C-index), decision curve analysis (DCA), along with calibration curve were adopted for assessing the predicting ability of our constructed nomograms after calibrating for 1-, 3- and 5-year OS and CSS. Altogether, 1727 osteosarcoma cases were enrolled in the present study and randomly divided as training (n = 1149, 70%) or validation (n = 576, 30%) set. As shown by univariate as well as multivariate Cox regression analyses, age, grade, T stage, M stage, surgery, chemotherapy, and histological type were identified to be the adverse factors to independently predict OS and CSS among the osteosarcoma cases. Besides, based on results of multivariate Cox regression analysis, we constructed the OS and CSS prediction nomograms. The C-index in training set was 0.806 (95% CI 0.769–0.836) for OS nomogram and 0.807 (95% CI 0.769–0.836) for CSS nomogram. In the meantime, C-index value in validation set was 0.818 (95% CI 0.789–0.847) for OS nomogram, while 0.804 (95% CI 0.773–0.835) for CSS nomogram. Besides, those calibration curves regarding the 3- and 5-year CSS of our constructed nomogram were highly consistent between the predicted values and the measurements in the training set as well as the external validation set. Our constructed nomogram outperformed the TNM stage in prediction. Our constructed nomogram is facile, creditable, and feasible; it efficiently predicts OS and CSS for osteosarcoma cases and can assist clinicians in assessing the prognosis for individuals and making decisions.