Molecular subtypes based on DNA methylation predict prognosis in patients with renal clear cell carcinoma

Background:Tumor heterogeneity is closely related to the occurrence,progression and recurrence of renal clear cell carcinoma(ccRCC),making early diagnosis and effective treatment difficult.DNA methylation is an important regulator of gene expression and can affect tumor heterogeneity.Methods:In this study,we investigated the prognostic value of subtypes based on DNA methylation status in 506 ccRCC samples with paired clinical data from the TCGA database.Differences in DNA methylation levels were associated with differences in T,N and M categories,age,stage and prognosis.Finally,the samples were divided into the training group and the testing group according to 450K and 27K.Univariate and multivariate Cox regression analysis was used to construct the prediction model in the training group,and the model was verified and evaluated in the testing group.Results:By univariate Cox regression analysis,21,122 methylation sites and 6,775 CpG sites were identified as potential DNA methylation biomarkers for overall survival of ccRCC patients(P<0.05).3,050 CpG sites independently associated with prognosis were identified with T,N,M,stage and age as covariables.Consensus cluster of 3,050 potential prognostic methylation sites was used to identify different DNA methylation subsets of ccRCC for prognostic purposes.We performed functional enrichment analysis on these 3,640 genes and identified 75 significantly enriched pathways(P<0.05).We then researched the expression of methylated genes in subgroups.Verifing with the training set,suggesting that DNA methylation levels generally reflect the expression of these genes.Conclusion:Based on TCGA database and a series of bioinformatics methods,We identified prognostic specific methylation sites and established prognostic prediction models for ccRCC patients.This model helps to identify novel biomarkers,precision drug targets and disease molecular subtypes in patients with ccRCC.Therefore,this model may be useful in predicting the prognosis,clinical diagnosis and management of patients with different epigenetic subtypes of ccRCC.

A Novel Protein RLS1 with NB-ARM Domains Is Involved in Chloroplast Degradation during Leaf Senescence in Rice

Leaf senescence, a type of programmed cell death （PCD） characterized by chlorophyll degradation, is important to plant growth and crop productivity. It emerges that autophagy is involved in chloroplast degradation during leaf senescence. However, the molecular mechanism（s） involved in the process is not well understood. In this study, the genetic and physiological characteristics Of the rice rlsl （rapid leaf senescence 1） mutant were identified. The rlsl mutant developed small, yellow-brown lesions resembling disease scattered over the whole surfaces of leaves that displayed earlier senescence than those of wild-type plants. The rapid loss of chlorophyll content during senescence was the main cause of accelerated leaf senescence in rlsl. Microscopic observation indicated that PCD was misregulated, probably resulting in the accelerated degradation of chloroplasts in rlsl leaves. Map-based cloning of the RLS1 gene revealed that it encodes a pre- viously uncharacterized NB （nucleotide-binding site）-containing protein with an ARM （armadillo） domain at the carboxyl terminus. Consistent with its involvement in leaf senescence, RLS1 was up-regulated during dark-induced leaf senescence and down-regulated by cytokinin. Intriguingly, constitutive expression of RLS1 also slightly accelerated leaf senescence with decreased chlorophyll content in transgenic rice plants. Our study identified a previously uncharacterized NB-ARM protein involved in PCD during plant growth and development, providing a unique tool for dissecting possible autophagy- mediated PCD during senescence in plants.