Background: N6-methyladenosine (m6A)–modified long noncoding RNAs (m6A-lncRNAs) have been proven to be involving in regulating tumorigenesis, invasion, and metastasis for a variety of tumors. The present study aimed to screen lncRNAs with m6A modification and investigate their biological signatures and prognostic values in kidney renal clear cell carcinoma (KIRC).Materials and Methods: lncRNA-seq, miRNA-seq, and mRNA-seq profiles of KIRC samples and the clinical characteristics of corresponding patients were downloaded from The Cancer Genome Atlas (TCGA). The R package “edgeR” was utilized to perform differentially expressed analysis on these profiles to gain DElncRNAs, DEmiRNAs, and DEmRNAs, respectively. The results of intersection of DElncRNAs and m6A-modified genes were analyzed by the weighted gene co-expression network analysis (WGCNA) to screen hub m6A-lncRNAs. Then, WGCNA was also used to construct an lncRNA-miRNA-mRNA (ceRNA) network. The Cox regression analysis was conducted on hub m6A-lncRNAs to construct the m6A-lncRNAs prognostic index (m6AlRsPI). Receiver operating characteristic (ROC) curve was used to assess the predictive ability of m6AlRsPI. The m6AlRsPI model was tested by internal and external cohorts. The molecular signatures and prognosis for hub m6A-lncRNAs and m6AlRsPI were analyzed. The expression level of hub m6A-lncRNAs in KIRC cell lines were quantified by qRT-PCR.Results: A total of 21 hub m6A-lncRNAs associated with tumor metastasis were identified in the light of WGCNA. The ceRNA network for 21 hub m6A-lncRNAs was developed. The Cox regression analysis was performed on the 21 hub m6A-lncRNAs, screening two m6A-lncRNAs regarded as independent prognostic risk factors. The m6AlRsPI was established based on the two m6A-lncRNAs as follows: (0.0006066 × expression level of LINC01820) + (0.0020769 × expression level of LINC02257). The cutoff of m6AlRsPI was 0.96. KM survival analysis for m6AlRsPI showed that the high m6AlRsPI group could contribute to higher mortality. The area under ROC curve for m6AlRsPI for predicting 3- and 5-year survival was 0.760 and 0.677, respectively, and the m6AlRsPI was also tested. The mutation and epithelial–mesenchymal transition (EMT) analysis for m6AlRsPI showed that the high m6AIRsPI group had more samples with gene mutation and had more likely caused EMT. Finally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for mRNAs interacted with the two m6A-lncRNAs, showing they were involved in the process of RNA splicing and regulation of the mRNA surveillance pathway. qRT-PCR analysis showed that the two m6A-lncRNAs were upregulated in KIRC.Conclusion: In the present study, hub m6A-lncRNAs were determined associated with metastasis in KIRC, and the ceRNA network demonstrated the potential carcinogenic regulatory pathway. Two m6A-lncRNAs associated with the overall survival were screened and m6AlRsPI was constructed and validated. Finally, the molecular signatures for m6AlRsPI and the two m6A-lncRNAs were analyzed to investigate the potential modulated processes in KIRC.

BackgroundmRNA vaccines are a novel technology that provide a potential strategy for cancer treatment. However, few studies exist that are focused on the application and development of mRNA vaccines in bladder cancer (BLCA). Therefore, this study filtered candidate antigens and specific mRNA-suitable populations in BLCA via comprehensive multi-omics analysis.MethodsClinical information, follow-up information, and gene expression profiles were obtained from the TCGA and GEO databases. Somatic mutation and DNA copy number variation of BLCA were visualized by cBioPortal. Significant survival genes were analyzed by GEPIA2. TIMER was used to evaluate the connection between candidate antigens and infiltration of antigen-presenting cells. Consensus clustering analysis was performed to identify immune subtypes using the ConsensusClusterPlus package. The Monocle package was used to visualize the immune landscapes of each BLCA patient. Weighted gene co-expression network analysis (WGCNA) was used to identify key genes for mRNA vaccines.ResultsAP2S1, P3H4, and RAC3 were identified as candidate tumor-specific antigens for BLCA. Three immune subtypes were classified based on immune-related gene expression profiles. Patients with the BCS2 subtype were characterized as immune “cold” and exhibited upregulation of immunogenic cell death modulators, whereas patients with BCS1 and BCS3 were immune “hot” and had upregulation of immune checkpoints. Interestingly, patients with the BCS2 subtype had a better prognosis than other subtypes. The immune landscapes of each patient were visualized and revealed the heterogeneity within the BCS1 subtype. Finally, 13 key immune genes were identified.ConclusionsAP2S1, P3H4, and RAC3 were identified as candidate tumor-specific antigens, and patients with the BCS2 and BCS1A subtypes were identified as candidate populations for mRNA vaccines. In summary, this study provides novel insights and a theoretical basis for mRNA vaccine development in BLCA and other malignancies.

As the most common modification of RNA, N6-methyladenosin (m6A) has been confirmed to be involved in the occurrence and development of various cancers. However, the relationship between m6A and castration resistance prostate cancer (CRPC), has not been fully studied. By m6A-sequencing of patient cancer tissues, we identified that the overall level of m6A in CRPC was up-regulated than castration sensitive prostate cancer (CSPC). Based on the analysis of m6A-sequencing data, we found m6A modification level of HRas proto-oncogene, GTPase (HRAS) and mitogen-activated protein kinase kinase 2 (MEK2 or MAP2K2) were enhanced in CRPC. Specifically, tissue microarray analysis and molecular biology experiments confirmed that METTL3, an m6A “writer” up-regulated after castration, activated the ERK pathway to contribute to malignant phenotype including ADT resistance, cell proliferation and invasion. We revealed that METTL3-mediated ERK phosphorylation by stabilizing the transcription of HRAS and positively regulating the translation of MEK2. In the Enzalutamide-resistant (Enz-R) C4-2 and LNCap cell line (C4-2R, LNCapR) established in the current study, the ERK pathway was confirmed to be regulated by METTL3. We also found that applying antisense oligonucleotides (ASOs) to target the METTL3/ERK axis can restore Enzalutamide resistance in vitro and in vivo. In conclusion, METTL3 activated the ERK pathway and induced the resistance to Enzalutamide by regulating the m6A level of critical gene transcription in the ERK pathway.

Background and Aim. Although a strong antitumor effect of lenvatinib has been noted for patients with unresectable hepatocellular carcinoma (HCC), its efficacy requires improvement. It is imperative to seek therapeutic strategies that combine Lenvatinib with other anticancer agents. In this study, we investigated the anticancer effect of combining lenvatinib with alisertib, aurora A kinase (AURKA) target drug, against HCC in vitro and in vivo. Methods. Immunohistochemical staining, sequencing, and genetic analysis of liver cancer tissues were performed. The antitumor efficacy of single-agent or combination treatment was measured by cell counting kit-8 assay and colony formation assays. Their antiproliferative and apoptosis activity is evaluated by cell cycle analyses and wound healing assays. The DNA-related proteins were also measured by Western blotting and immunohistochemical staining. The HepG2 xenograft model was used to detect the effects of lenvatinib-alisertib on the antitumor activity. Results. AURKA was found to be upregulated in HCC tissues (77.3%, 17/22). Combined alisertib and lenvatinib treatment significantly enhanced the inhibition of proliferation and migration in HepG2 and Hep3B cell lines compared to single-agent treatments (all P s < 0.01 ). Alisertib alone or in combination with lenvatinib demonstrated a significant increase in the percentage of super-G2 cells (lenvatinib 1 μM vs. lenvatinib 1 μM + alisertib 0.1 μM 8.84 ± 0.84 vs. 34.0 ± 1.54 , P < 0.001 ). Discontinuous spindles and missegregated chromosomes in HCC cells treated with alisertib in combination with lenvatinib were observed. We further revealed that combined treatment inhibited the expression of DNA damage pathway proteins compared to those of single-agent treatments. In nude mice, combined administration of alisertib combined with lenvatinib significantly enhanced the suppression of tumor growth and induced apoptosis (all P s < 0.01 ). Conclusions. Our findings provide evidence for the possible use of alisertib in combination with lenvatinib in the treatment of HCC for better therapeutic outcomes.

Background To evaluate the clinicopathologic value of morphological growth patterns of small renal cell carcinoma (sRCC) and determine the actual demand for taking a rim of healthy parenchyma to avoid positive SM. Methods Data was collected from 560 sRCC patients who underwent laparoscopic surgeries from May 2010 to October 2017. One hundred forty-nine cases received nephron-sparing surgery (NSS) and others received radical nephrectomy (RN). All specimens were analyzed separately by two uropathologists, and three morphological growth patterns were identified. The presence of pseudocapsule (PC), surgical margins (SM), and other routine variables were recorded. The relationship between growth patterns and included variables was measured by the χ2 test and Fisher’s exact probability test. Survival outcomes were evaluated by Kaplan-Meier method and the log-rank test. Results The median age of patients was 63.2 years old and the mean tumor diameter was 3.0 cm. Four hundred eighty (85.7%) cases were clear cell RCC and 541 (96.6%) cases were at the pT1a stage. Peritumoral PC was detected in 512 (92.5%) specimens, and the ratio of tumor invasion in PC in infiltration pattern increased obviously than that of the other growth patterns. Similarly, the pT stage was significantly correlated with the infiltration pattern as well. One hundred forty-nine patients underwent NSS and 3 (2.0%) of them showed positive SM after operation. Statistical differences of the 5-year overall survival (OS) and the cancer-specific survival (CSS) existed between different morphological growth patterns, PC status, and pT stages. Conclusions Morphological growth patterns of sRCC might be used as a potential biomarker to help operate NSS to avoid the risk of positive SM. How to distinguish different morphological growth patterns before operation and the effectiveness of the growth pattern as a novel proposed parameter to direct NSS in sRCC patients deserves further exploration.