The study aimed to identify the pivotal genes and pathways involved in prostate cancer metastasis. Using the expression profile dataset GSE7930, downloaded from the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) between primary and highly metastatic prostate cell samples were screened, followed by functional analysis and tumor associated genes (TAG) screening. Protein-protein interaction (PPI) network of DEGs was constructed and module analysis was performed. The expression of DEGs and pathway related genes were evaluated by PCR analysis and the migra- tion ability of prostate tumor cells was observed after FABP4-siRNA blocking. Upregulated FABP4 and GK were signifi- cantly enriched in the PPAR signaling pathway, whereas downregulated IGFBP3 and THBS1 were involved in p53 signaling pathway. Among the identified DEGs, 4 downregulated genes (IGFBP3, NPP4B, THBS1, and PCDH1) and 2 upregulated genes (GJA1 and TUSC3) were TAGs. The module was associated with focal adhesion, ECM-receptor interaction, p53 signaling, and gap junction pathways with the hub node GJA1. After FABP4 silencing by siRNAs in LNcap and metastatic DU-145 cells, the numbers of migrated cells were all significantly declined. The expressions of IGFBP3, TP53 and PPAR were significantly lower in DU-145 cells than in LNcap cells. In conclusion, FABP4, IGFBP3, THBS1, and GJA1 were determined to be potential markers of prostate cancer cell metastasis, and P53, PPAR and gap junction pathways were found to play important roles in prostate cancer cell metastasis. This study may provide helpful guidelines for clinical management.

Background: Kidney Renal Clear cell carcinoma (KIRC) is a major concern in the urinary system. A lot of researches were focused on Chromatin Regulators (CRs) in tumors. In this study, CRs-related lncRNAs (CRlncRNAs) were investigated for their potential impact on the prognosis of KIRC and the immune microenvironment.Methods: The TCGA database was used to obtain transcriptome and related clinical information. CRs were obtained from previous studies, whereas CRlncRNAs were obtained by differential and correlation analysis. We screened the lncRNAs for the signature construction using regression analysis and LASSO regression analysis. The effectiveness of the signature was evaluated using the Kaplan-Meier (K-M) curve and Receiver Operating Characteristic curve (ROC). Additionally, we examined the associations between the signature and Tumor Microenvironment (TME), and the efficacy of drug therapy. Finally, we further verified whether these lncRNAs could affect the biological function of KIRC cells by functional experiments such as CCK8 and transwell assay.Results: A signature consisting of 8 CRlncRNAs was constructed to predict the prognosis of KIRC. Quantitative Real-Time PCR verified the expression of 8 lncRNAs at the cell line and tissue level. The signature was found to be an independent prognostic indicator for KIRC in regression analysis. This signature was found to predict Overall Survival (OS) better for patients in the subgroups of age, gender, grade, stage, M, N0, and T. Furthermore, a significant correlation was found between riskScore and immune cell infiltration and immune checkpoint. Finally, we discovered several drugs with different IC50 values in different risk groups using drug sensitivity analysis. And functional experiments showed that Z97200.1 could affect the proliferation, migration and invasion of KIRC cells.Conclusion: Overall, the signature comprised of these 8 lncRNAs were reliable prognostic biomarkers for KIRC. Moreover, the signature had significant potential for assessing the immunological landscape of tumors and providing individualized treatment.

Bladder cancer (BLCA) is the 10th most common form of cancer worldwide. Currently, the response rate of BLCA patients to novel immunotherapy and immune checkpoint inhibitor (ICI) treatment is around 30% or less. Therefore, there is an urgent clinical demand to understand the regulation of immune function in BLCA patients. LncRNAs are known to play fundamental roles in the regulation of the immune system in the tumor microenvironment. In this report, we performed a comprehensive analysis to identify immune-related lncRNAs (IRLs) in BLCA patients using The Cancer Genome Atlas (TCGA) databases. BLCA patients were divided into five TME subtypes. Subtype HMIE was strongly related to survival and high anti-tumor activity of patients. Through a four-step analysis, we identified 34 IRLs as subtype HMIE related lncRNAs (HMIE-lncs).The correlation analysis with immune cell infiltration and target gene pathway enrichment showed that 34 HMIE-lncs were correlated with immune cell activation and tumor cell killing. Among them, 24 lncRNAs were related to good prognosis. We constructed a risk model to predict BLCA. Cross tumor validation was performed, and the results showed that the 34 HMIE-lncs identified in the BLCA patients in this study were highly expressed in the immune-favorable TME subtype (IE) in most of the other cancer types.