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Background: Clear-cell renal cell carcinoma (ccRCC) is one of prevalent kidney malignancies with an unfavorable prognosis. There is a need for a robust model to predict ccRCC patient survival and guide treatment decisions. Methods: RNA-seq data and clinical information of ccRCC were obtained from the TCGA and ICGC databases. Expression profiles of genes related to natural killer (NK) cells were collected from the Immunology Database and Analysis Portal database. Key NK cell-related genes were identified using consensus clustering algorithms to classify patients into distinct clusters. A NK cell-related risk model was then developed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression to predict ccRCC patient prognosis. The relationship between the NK cell-related risk score and overall survival, clinical features, tumor immune characteristics, as well as response to commonly used immunotherapies and chemotherapy, was explored. Finally, the NK cell-related risk score was validated using decision tree and nomogram analyses. Results: ccRCC patients were stratified into 3 molecular clusters based on expression of NK cell-related genes. Significant differences were observed among the clusters in terms of prognosis, clinical characteristics, immune infiltration, and therapeutic response. Furthermore, six NK cell-related genes (DPYSL3, SLPI, SLC44A4, ZNF521, LIMCH1, and AHR) were identified to construct a prognostic model for ccRCC prediction. The high-risk group exhibited poor survival outcomes, lower immune cell infiltration, and decreased sensitivity to conventional chemotherapies and immunotherapies. Importantly, the quantitative real-time polymerase chain reaction (qRT-PCR) confirmed significantly high DPYSL3 expression and low SLC44A4 expression in ACHN cells. Finally, the decision tree and nomogram consistently show the dramatic prediction performance of the risk score on the survival outcome of the ccRCC patients. Conclusions: The six-gene model based on NK cell-related gene expression was validated and found to accurately mirror immune microenvironment and predict clinical outcomes, contributing to enhanced risk stratification and therapy response for ccRCC patients.

Background: Clear cell renal cell carcinoma (ccRCC) is characterized as one of the most common types of urological cancer with high degrees of malignancy and mortality. Due to the limited effectiveness of existing traditional therapeutic methods and poor prognosis, the treatment and therapy of advanced ccRCC patients remain challenging. Tryptophan metabolism has been widely investigated because it significantly participates in the malignant traits of multiple cancers. The functions and prognostic values of tryptophan metabolism-related genes (TMR) in ccRCC remain virtually obscure. Methods: We employed the expression levels of 40 TMR genes to identify the subtypes of ccRCC and explored the clinical characteristics, prognosis, immune features, and immunotherapy response in the subtypes. Then, a model was constructed for the prediction of prognosis based on the differentially expressed genes (DEGs) in the subtypes from the TCGA database and verified using the ICGC database. The prediction performance of this model was confirmed by the receiver operating characteristic (ROC) curves. The relationship of Risk Score with the infiltration of distinct tumor microenvironment cells, the expression profiles of immune checkpoint genes, and the treatment benefits of immunotherapy and chemotherapy drugs were also investigated. Results: The two subtypes revealed dramatic differences in terms of clinical characteristics, prognosis, immune features, and immunotherapy response. The constructed 6-gene-based model showed that the high Risk Score was significantly connected to poor overall survival (OS) and advanced tumor stages. Furthermore, increased expression of CYP1B1, KMO, and TDO2 was observed in ccRCC tissues at the translation levels, and an unfavorable prognosis for these patients was also found. Conclusion: We identified 2 molecular subtypes of ccRCC based on the expression of TMR genes and constructed a prognosis-related model that may be used as a powerful tool to guide the prediction of ccRCC prognosis and personalized therapy. In addition, CYP1B1, KMO, and TDO2 can be regarded as the risk prognostic genes for ccRCC.

Acute rejection (AR) can lead to allograft dysfunction following renal transplantation, despite immunosuppressive treatments. Accumulating evidence points out a role for epigenetic modification in immune responses. However, the mechanism and contribution of DNA methylation in allograft survival remain unclear. In this study, we followed up patients who successively experienced end‐stage renal disease, renal transplantation with allograft function or dysfunction, and hemodialysis. Peripheral blood mononuclear cells were collected at different time points for analysis of the DNA methylation. Epigenetic modifier analysis was also performed to explore its effect of methylation in a mouse model of AR. Compared with the allograft‐stable cohort, patients who experienced AR‐induced allograft dysfunction demonstrated more changes in methylation patterns. Pathway analysis revealed that the hypermethylated areas in the allograft dysfunction group were associated with genes related to the mechanistic target of rapamycin (mTOR) signaling pathway. Moreover, in the mouse AR model, treatment with the DNA methyltransferase inhibitor—decitabine regulated the Th1/2/17/regulatory T cell (Treg cell) immune response via its demethylating role in the suppressing the activity of the mTOR pathway, which ultimately ameliorated renal allograft‐related inflammatory injuries. These results revealed that changes in methylation accompany AR‐induced allograft dysfunction after renal transplantation. Epigenetics may provide new insights into predicting and improving allograft survival. Whole‐genome bisulfite sequencing explores epigenetic changes in renal transplant recipients, revealing enhanced hypermethylation of genes enriched in immune‐related pathways.

Jasmonate (JA) regulates various plant defense and developmental processes. The F-box protein CORONATINE INSENSITIVE 1 (COI1) perceives JA signals to mediate diverse plant responses including male fertility, root growth, anthocyanin accumulation, and defense against abiotic and biotic stresses. In this study, we carried out genetic, physiological and biochemical analysis on a series of coi1mutant alleles, and found that different amino acid mutations in COI1 distinctively affect JA-regulated male fertility in Arabidopsis. All the JA responses are disrupted by the COI1 mutations W467* in coi1-1, Q343* (coi1-6), G369E (coi1-4), G98D (coi1-5), G155E (coi1-7), D452A (coi1-9) and L490A (coi1-10), though the coi1-5mutant (COI1G98D) contains adequate COI1 protein (∼60% of wild-type). Interestingly, the low basal level of COI1E543Kin the coi1-8mutant (∼10% of wild-type COI1 level) is sufficient for maintaining male fertility (∼50% of wild-type fertility); the coi1-2mutant with low level of COI1L245F(∼10% of wild-type) is male sterile under normal growth condition (22°C) but male fertile (∼80% of wild-type fertility) at low temperature (16°C); however, both coi1-2and coi1-8are defective in the other JA responses (root growth, anthocyanin accumulation, and plant response to the pathogen PstDC3000 infection).

Leukocyte telomere length shortening is a characteristic of premature senescence, a process that can be accelerated by oxidative stress. In general, patients with end-stage renal disease undergoing regular hemodialysis (HD) are repeatedly exposed to oxidative stress. Patients undergoing HD tend to have cardiovascular diseases associated with oxidative stress and inflammation. Therefore, we assumed that telomere length is associated with HD vintage and the degree of vascular calcification.

ABSTRACTThe phytohormones gibberellin (GA) and jasmonate (JA) regulate various aspects of plant development, growth and defense. Previous studies showed that both DELLA repressors in GA pathway and JA-ZIM domain (JAZ) proteins in JA pathway interact with and repress the WD-repeat/bHLH/MYB transcriptional complex to inhibit trichome initiation, and GA and JA respectively induce DELLAs and JAZs degradation to synergistically enhance trichome formation. In this study, we showed that the DELLA protein RGA and JAZ1 competitively bind to ENHANCER OF GLABRA3 (EGL3), a bHLH component of the WD-repeat/bHLH/MYB complex. GA and JA differently affect the expression and protein stability of the components of the WD-repeat/bHLH/MYB complex, and EGL3 and GL3 repress the expression of JAZgenes as a feedback. The novel findings help to understand the mechanism of the WD-repeat/bHLH/MYB complex in GA/JA-regulated trichome formation.