Accumulated evidence indicates that miR-455-5p functions as tumor suppressor in the progression of various cancers. However, the mechanism through which miR-455-5p influences the tumorigenesis of human prostate cancer (PCa) remains undetermined. In this study, reanalysis of data obtained from the Memorial Sloan Kettering Cancer Center showed that miR-455-5p can be used as biomarker for PCa diagnosis and predictor of poor prognosis. Functional assays indicated that miR-455-5p overexpression could suppress cellular proliferation, inhibit tumor growth, and trigger apoptosis by activating and cleaving caspase 3. We experimentally verified that miR-455-5p negatively regulated the C–C motif chemokine receptor 5 (CCR5). Overall, our data demonstrate that miR-455-5p suppressed PCa cellular proliferation and induced cell apoptosis by downregulating CCR5. Thus, miR-455-5p may be considered a new therapeutic strategy for PCa.

Background METTL14, as one of N6-methyladenosine (m6A) related genes, has been found to be associated with promoting tumorigenesis in different types of cancers. This study was aimed to investigate the prognostic value of METTL14 in clear cell renal cell carcinoma (ccRCC). Methods We collected ccRCC patients’ clinicopathological parameters information and 13 m6A related genes expression from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to investigate whether METTL14 could serve as an independent factor correlated with overall survival (OS). Gene Set Enrichment Analysis (GSEA) was carried out to identify METTL14-related signaling pathways. Moreover, a risk score (RS) was calculated to predict the prognosis of ccRCC. Quantitative real-time PCR (qRT-PCR) was also utilized to verify the expression of METTL14 in clinical specimens. Results Differently expressed m6A related genes were identified between ccRCC tissues and normal tissues. Therein, METTL14 was lowly expressed in ccRCC tissues and verified by qRT-PCR (all p < 0.01). Survival analysis indicated that high expression of METTL14 was associated with better OS (p = 1e−05). GSEA results revealed that high METTL14 expression was enriched in ERBB pathway, MAPK pathway, mTOR pathway, TGF-β pathway and Wnt pathway. Moreover, METTL14 was proved to be an independent prognostic factor by means of univariate and multivariate Cox regression analyses. Nomogram integrating both the METTL14 expression and clinicopathologic variables was also established to provide clinicians with a quantitative approach for predicting survival probabilities of ccRCC. Furthermore, a METTL14-based riskscore (RS) was developed with significant OS (p = 6.661e−16) and increased AUC of 0.856. Besides, significant correlated genes with METTL14 were also provided. Conclusions Our results indicated that METTL14 could serve as a favorable prognostic factor for ccRCC. Moreover, this study also provided a prognostic signature to predict prognosis of ccRCC and identified METTL14-related signaling pathways.

Background: This study was designed to establish a sensitive prognostic model based on apoptosis-related genes to predict overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC).Methods: Obtaining the expression of apoptosis-related genes and associated clinical parameters from online datasets (The Cancer Genome Atlas, TCGA), their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by internal and external databases (both TCGA and ArrayExpress).Results: A total of nine apoptosis-related genes (SLC27A2, TNFAIP2, IFI44, CSF2, IL4, MDK, DOCK8, WNT5A, APP) were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in both the internal and external datasets of OS (all p &lt; 0.05) and verified their expressions by qRT-PCR. Moreover, we conducted the Receiver Operating Characteristic (ROC), finding the area under the ROC curves (AUCs) were all above 0.70 which indicated that riskScore was a stable independent prognostic factor (p &lt; 0.05). Furthermore, prognostic nomograms were established to figure out the relationship between 1-, 3- and 5-year OS and individual parameters for ccRCC patients. Additionally, survival analyses indicated that our riskScore worked well in predicting OS in subgroups of age, gender, grade, stage, T, M, N0, White (all p &lt; 0.05), except for African, Asian and N1 (p &gt; 0.05). We also explored its association with immune infiltration and applied cMap database to seek out highly correlated small molecule drugs.Conclusion: Our study successfully constructed a prognostic model containing nine hub apoptosis-related genes for ccRCC, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

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