Sensing a global directional cue to orient cell growth is crucial in tissue morphogenesis. An anterior-posterior gradient of Wnt signaling controls the helical growth of feather branches (barbs), and thus the formation of bilateral feathers. However, it remains unclear how the keratinocytes sense this gradient and orient barb growth. Here, we show that in chicken, owing to feather branching, the global Wnt gradient is subdivided into periodic barbs. Within each barb, the anterior barbule plate cells tilt before the posterior cells. The core planar cell polarity gene is involved, as knockdown of its expression resulted in no cell shape change and no barb tilting. Furthermore, perturbation of the Wnt gradient leads to diffusive Prickle1 expression and loss of barb orientation. Finally, the asymmetric distribution of Wnt6/Fzd10 is coordinated by the apical-basal polarity of the barbule plate keratinocytes, which is in turn regulated by the Par3/aPKC machinery. Our data elucidate a new mechanism through which the global Wnt signaling gradient is interpreted locally to construct complex spatial forms.
Cumulative studies have shown that RNA binding proteins (RBPs) play an important role in numerous malignant tumors and are related to the occurrence and progression of tumors. However, the role of RBPs in kidney renal clear cell carcinoma (KIRC) is not fully understood. In this study, we first downloaded gene expression data and corresponding clinical information of KIRC from the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) database, respectively. A total of 137 differentially expressed RBPs (DERBPs) were then identified between normal and tumor tissue, including 38 downregulated and 99 upregulated RBPs. Nine RBPs (EIF4A1, RPL36A, EXOSC5, RPL28, RPL13, RPS19, RPS2, EEF1A2, and OASL) were served as prognostic genes and exploited to construct a prognostic model through survival analysis. Kaplan-Meier curves analysis showed that the low-risk group had a better survival outcome when compared with the high-risk group. The area under the curve (AUC) value of the prognostic model was 0.713 in the TCGA data set (training data set), 0.706 in the ICGC data set, and 0.687 in the GSE29609 data set, respectively, confirming a good prognostic model. The prognostic model was also identified as an independent prognostic factor for KIRC survival by performing cox regression analysis. In addition, we also built a nomogram relying on age and the prognostic model and internal validation in the TCGA data set. The clinical benefit of the prognostic model was revealed by decision curve analysis (DCA). Gene set enrichment analysis revealed several crucial pathways (ERBB signaling pathway, pathways in cancer, MTOR signaling pathway, WNT signaling pathway, and TGF BETA signaling pathway) that may explain the underlying mechanisms of KIRC. Furthermore, potential drugs for KIRC treatment were predicted by the Connectivity Map (Cmap) database based on DERBPs, including several important drugs, such as depudecin and vorinostat, that could reverse KIRC gene expression, which may provide reference for the treatment of KIRC. In summary, we developed and validated a robust nine-RBP signature for KIRC prognosis prediction. A nomogram with risk score and age can be applied to promote the individualized prediction of overall survival in patients with KIRC. Moreover, the two drugs depudecin and vorinostat may contribute to KIRC treatment.
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma (RCC). Despite the existing extensive research, the molecular and pathogenic mechanisms of ccRCC are elusive. We aimed to identify the immune-related lncRNA signature and molecular subtypes associated with ccRCC. By integrating 4 microarray datasets from Gene Expression Omnibus database, we identified 49 immune-related genes. The corresponding immune-related lncRNAs were further identified in the TCGA dataset. 12-lncRNAs prognostic and independent signature was identified through survival analysis and survival difference between risk groups was further identified based on the risk score. Besides, we identified 3 molecular subtypes and survival analysis result showed that cluster 2 has a better survival outcome. Further, ssGSEA enrichment analysis for the immune-associated gene sets revealed that cluster 1 corresponded to a high immune infiltration level. While cluster 2 and cluster 3 corresponded to low and medium immune infiltration level, respectively. In addition, we validated the 12-lncRNA prognostic signature and molecular subtypes in an external validation dataset from the ICGC database. In summary, we identified a 12-lncRNA prognostic signature which may provide new insights into the molecular mechanisms of ccRCC and the molecular subtypes provided a theoretical basis for personalized treatment by clinicians. Renal cell carcinoma (RCC) accounts for over 90% of all kidney cancer cases among human adults 1. Clear cell renal cell carcinoma (ccRCC) is the most common RCC histological subtype which responsible for 70-80% of RCC cases 2. Recent studies estimate that 102,000 patients succumb to ccRCC and 202,000 new cases are diagnosed annually throughout the globe 3. Besides, ccRCC has no clear symptoms in its early stages therefore can only be diagnosed in advanced stages 4. Despite interventions through chemotherapy and radiotherapy, ccRCC is prone to distant metastasis. These metastases occur in lung, bone, liver, distant lymph nodes, and renal vein 5. A few effective biomarkers, particularly in both early and advanced stages of ccRCC, have been identified. The recent version of the human genome annotation transcribes approximately 16,000 long non-coding RNAs (lncRNAs) responsible for 26.7% of the total genes (https ://www.genco degen es.org/human /) 6. lncRNAs are non-coding RNAs composed of about 200 nucleotides in length. They include the antisense lncRNAs, intronic transcripts, large intergenic noncoding RNAs (lincRNAs), promoter-associated lncRNAs, and UTR associated lncRNAs 7. Previous studies have revealed that lncRNA plays an important role in regulating gene expression, epigenetics, cell differentiation, and ontogeny 8,9. Additionally, studies have shown that massive aberrantly expressed
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