Head and neck squamous carcinoma (HNSC) is the most prevalent malignancy of the head and neck regions. Long noncoding RNAs (lncRNAs) are vital in tumorigenesis regulation. However, the role of lncRNAs in HNSC requires further exploration. Herein, through bioinformatic assays using The Cancer Genome Atlas (TCGA) datasets, rapid amplification of cDNA ends (RACE) assays, and RNA-FISH, we revealed that a novel cytoplasmic transcript, HNSC-associated transcript 1 (HNSCAT1, previously recognized as linc01269), was downregulated in tumor samples and advanced tumor stages and was also associated with favorable outcomes in HNSC. Overexpression of HNSCAT1 triggered treatment efficacy in HNSCs both in vivo and in vitro. More importantly, through high-throughput transcriptome analysis (RNA-seq, in NODE database, OEZ007550), we identified KRT80, a tumor suppressor in HNSC, as the target of HNSCAT1. KRT80 expression was modulated by lncRNA HNSCAT1 and presented a positive correlation in tumor samples ( R = 0.52 , p < 0.001 ). Intriguingly, we identified that miR-1245 simultaneously interacts with KRT80 and HNSCAT1, which bridges the regulatory function between KRT80 and HNSCAT1. Conclusively, our study demonstrated that lncRNA HNSCAT1 functions as a necessary tumor inhibitor in HNSC, which provides a novel mechanism of lncRNA function and provides alternative targets for the diagnosis and treatment of HNSC.
Nowadays, the compound fine-blanking forming process is one of the most important processes to produce complicate multifunctional parts without subsequent machining. However, the big die-roll occurs in the sharp area is a common problem in this process. In this paper, the method with negative punch-die clearance was proposed to solve this problem by comparing three feasible plans. In addition, the influence on the process with different value of the negative punch-die clearance was studied by the finite element method (FEM). The results of this study verified that the process with suitable value of the negative punch-die clearance can result in significant decrease of the die-roll size. The relationship between the material flow near the region of die-roll and the punch-die clearance was also clarified.
Purpose: To externally validate the performance of the S-GRAS score and a model from the SEER database in a Chinese cohort of patients with adrenocortical carcinoma (ACC). Methods: We first developed a model using data from the SEER database, after which we retrospectively reviewed 51 ACC patients hospitalized between 2013 and 2018, and we finally validated the model and S-GRAS score in this Chinese cohort. Results: Patient age at diagnosis, tumor size, TNM stage, and radiotherapy were used to construct the model, and the Harrell’s C-index of the model in the training set was 0.725 (95%CI: 0.682-0.768). However, the 5-year AUC of the model in the validation cohort was 0.598 (95%CI: 0.487-0.708). The 5-year AUC of the ENSAT stage was 0.640 (95%CI: 0.543-0.737), but the Kaplan-Meier curves of stage I and II overlapped in the validation cohort. The resection status (P=0.066), age (P=0.68), Ki67 (P=0.69), and symptoms (P=0.66) did not have a significant impact on cancer-specific survival in the validation cohort. In contrast, the S-GRAS score group showed better discrimination (5-year AUC: 0.683, 95%CI: 0.602-0.764) than the SEER model or the ENSAT stage. Conclusion: The SEER model showed favorable discrimination and calibration ability in the training set, but it failed to distinguish patients with various prognoses in our institution. In contrast, the S-GRAS score could effectively stratify patients with different outcomes.
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