Uveal melanoma is the most common primary intraocular tumor with a poor prognosis. Currently, treatment for UVM is limited, and the development of drug resistance and tumor recurrence are common. Therefore, it is important to identify new prognostic biomarkers of UVM and explore their role in the tumor microenvironment. Pyroptosis is a way of cell programmed death, and related research is in full throttle. However, the role of pyroptosis in UVM is unclear. In this study, we constructed the prognosis model of pyroptosis-related genes of UVM. This model can accurately guide the prognosis of UVM, and different groups differ in immune infiltration. We further verified our results in cell experiments. To some extent, our study can provide new ideas for the diagnosis and treatment of UVM.

Cancer is one of the serious diseases that endanger human health and bring a heavy burden to world economic development. Although the current targeted therapy and immunotherapy have achieved initial results, the emergence of drug resistance shows that the existing research is far from enough. In recent years, the tumor microenvironment has been found to be an important condition for tumor development and has profound research value. The SLC16 family is a group of monocarboxylic acid transporters involved in cancer metabolism and the formation of the tumor microenvironment. However, there have been no generalized cancer studies in the SLC16 family. In this study, we conducted a pan-cancer analysis of the SLC16 family. The results showed that multiple members of the SLC16 family could be used as prognostic indicators for many tumors, and were associated with immune invasion and tumor stem cells. Therefore, the SLC16 family has extensive exploration value in the future.

Background: Autophagy inhibits tumorigenesis by limiting inflammation. Various lncRNAs are associated with tumour biological processes, including lung adenocarcinoma (LUAD), but the role of autophagyrelated lncRNAs (ARlncRNAs) in LUAD has not been fully elucidated. Thus, this study aimed to construct a prognostic signature based on ARlncRNAs for LUAD. Methods:The RNA-seq (FPKM) data and clinical information of LUAD patients were downloaded fromThe Cancer Genome Atlas (TCGA) database. After differentially expressed lncRNAs in tumour and normal groups were identified, cox regression analyses were performed to construct a prognostic signature which was then assessed through independent prognostic analysis and functional enrichment analysis. Moreover, based on the mRNAs co-expressed with the ARlncRNAs, several potential small molecule drugs were explored in the Connectivity map (Cmap).Results: A signature consisting of seven ARlncRNAs (FAM83A−AS1, LINC01116, ILF3-DT, EBLN3P, AL161785.1, AC092279.1 and AC026355.2) was constructed to predict overall survival (OS) for LUAD.The signature was identified to be independent by the cox regression analysis and obtained the largest area under the curve (AUC =0.721) in the ROC. Six small molecule drugs (MS-275, methotrexate, desipramine, benzbromarone, rifampicin and doxazosin) were selected from Cmap.Conclusions: A novel ARlncRNA signature for LUAD prognostic prediction was constructed, which had better efficacy than the TNM stage and used to propose potential therapeutic regimens for LUAD patients.