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Background: Renal cell carcinoma (RCC) is the predominant type of malignant tumor in kidney cancer. Finding effective biomarkers, particularly those based on the tumor immune microenvironments (TIME), is critical for the prognosis and diagnosis of RCC. Increasing evidence has revealed that long non-coding RNAs (lncRNAs) play a crucial role in cancer immunity. However, the comprehensive landscape of immune infiltration-associated lncRNAs and their potential roles in the prognosis and diagnosis of RCC remain largely unexplored.Methods: Based on transcriptomic data of 261 RCC samples, novel lncRNAs were identified using a custom pipeline. RCC patients were classified into different immune groups using unsupervised clustering algorithms. Immune-related lncRNAs were obtained according to the immune status of RCC. Competing endogenous RNAs (ceRNA) regulation network was constructed to reveal their functions. Expression patterns and several tools such as miRanda, RNAhybrid, miRWalk were used to define lncRNAs-miRNAs-mRNAs interactions. Univariate Cox, LASSO, and multivariate Cox regression analyses were performed on the training set to construct a tumorigenesis-immune-infiltration-related (TIR)-lncRNA signature for predicting the prognosis of RCC. Independent datasets involving 531 RCC samples were used to validate the TIR-lncRNA signature.Results: Tens of thousands of novel lncRNAs were identified in RCC samples. Comparing tumors with controls, 1,400 tumorigenesis-related (TR)-lncRNAs, 1269 TR-mRNAs, and 192 TR-miRNAs were obtained. Based on the infiltration of immune cells, RCC patients were classified into three immune clusters. By comparing immune-high with immune-low groups, 241 TIR-lncRNAs were identified, many of which were detected in urinary samples. Based on lncRNA-miRNA-mRNA interactions, we constructed a ceRNA network, which included 25 TR-miRNAs, 28 TIR-lncRNAs, and 66 TIR-mRNAs. Three TIR lncRNAs were identified as a prognostic signature for RCC. RCC patients in the high-risk group exhibited worse OS than those in the low-risk group in the training and testing sets (p < 0.01). The AUC was 0.9 in the training set. Univariate and multivariate Cox analyses confirmed that the TIR-lncRNA signature was an independent prognostic factor in the training and testing sets.Conclusion: Based on the constructed immune-related lncRNA landscape, 241 TIR-lncRNAs were functionally characterized, three of which were identified as a novel TIR-lncRNA signature for predicting the prognosis of RCC.

Objectives • This study aimed to explore the clinical characteristics of patients with prostate cancer with prostate-specific antigen (PSA) concentrations of less than 4 ng/mL (normal PSA) to provide clinical insights regarding diagnosis and treatment. Methods • We recruited 35 patients with prostate cancer with normal PSA who were admitted to Xi’an People’s Hospital from January 2013 to January 2018, and further determined their clinical characteristics, serum PSA concentration, prostate volume, tumor pathology, surgical margins, seminal vesicle invasion, lymph node metastasis, Gleason score, TNM staging, risk classification, and survival, and described the patients’ interventions and treatments. All patients and their families signed informed consent forms before enrollment. Results • In our study, we observed a 3-year survival rate of 77.14% for patients with prostate cancer and normal PSA concentrations. This outcome can be attributed to several clinical characteristics, including the absence of obvious clinical presentation, a high detection rate of seminal vesicle invasion, as well as high Gleason scores and risk levels. The primary outcome, 3-year survival rate, reflects the long-term prognosis of this specific patient subgroup. We also conducted correlation analyses to better understand the relationships between these clinical characteristics and patient survival. [ABSTRACT FROM AUTHOR]