Kidney renal clear cell carcinoma (KIRC) has high morbidity and gradually increased in recent years, and the rate of progression once relapsed is high. At present, owing to lack of effective prognosis predicted markers and post-recurrence drug selection guidelines, the prognosis of KIRC patients is greatly affected. Necroptosis is a regulated form of cell necrosis in a way that is independent of caspase. Induced necroptosis is considered an effective strategy in chemotherapy and targeted drugs, and it can also be used to improve the efficacy of immunotherapy. Herein, we quantified the necroptosis landscape of KIRC patients from The Cancer Genome Atlas (TCGA) database and divided them into two distinct necroptosis-related patterns (C1 and C2) through the non-negative matrix factorization (NMF) algorithm. Multi-analysis revealed the differences in clinicopathological characteristics and tumor immune microenvironment (TIME). Then, we constructed the NRG prognosis signature (NRGscore), which contained 10 NRGs (PLK1, APP, TNFRSF21, CXCL8, MYCN, TNFRSF1A, TRAF2, HSP90AA1, STUB1, and FLT3). We confirmed that NRGscore could be used as an independent prognostic marker for KIRC patients and performed excellent stability and accuracy. A nomogram model was also established to provide a more beneficial prognostic indicator for the clinic. We found that NRGscore was significantly correlated with clinicopathological characteristics, TIME, and tumor mutation burden (TMB) of KIRC patients. Moreover, NRGscore had effective guiding significance for immunotherapy, chemotherapy, and targeted drugs.

The morbidity of bladder cancer (BLCA) is high and has gradually elevated in recent years. BLCA is also characterized by high recurrence and high invasiveness. Due to the drug resistance and lack of effective prognostic indicators, the prognosis of patients with BLCA is greatly affected. Iron metabolism is considered to be a pivot of tumor occurrence, progression, and tumor microenvironment (TME) in tumors, but there is little research in BLCA. Herein, we used univariate COX regression analysis to screen 95 prognosis-related iron metabolism-related genes (IMRGs) according to transcription RNA sequencing and prognosis information of the Cancer Genome Atlas (TCGA) database. TCGA-BLCA cohort was clustered into four distinct iron metabolism patterns (C1, C2, C3, and C4) by the non-negative matrix factorization (NMF) algorithm. Survival analysis showed that C1 and C3 patterns had a better prognosis. Gene set variant analysis (GSVA) revealed that C2 and C4 patterns were mostly enriched in carcinogenic and immune activation pathways. ESTIMATE and single sample gene set enrichment analysis (ssGSEA) also confirmed the level of immune cell infiltration in C2 and C4 patterns was significantly elevated. Moreover, the immune checkpoint genes in C2 and C4 patterns were observably overexpressed. Studies on somatic mutations showed that the tumor mutation burden (TMB) of C1 and C4 patterns was the lowest. Chemotherapy response assessment revealed that C2 pattern was the most sensitive to chemotherapy, while C3 pattern was the most insensitive. Then we established the IMRG prognosis signature (IMRGscore) by the least absolute shrinkage and selection operator (LASSO), including 13 IMRGs (TCIRG1, CTSE, ATP6V0A1, CYP2C8, RNF19A, CYP4Z1, YPEL5, PLOD1, BMP6, CAST, SCD, IFNG, and ASIC3). We confirmed IMRGscore could be utilized as an independent prognostic indicator. Therefore, validation and quantification of iron metabolism landscapes will help us comprehend the formation of the BLCA immunosuppressive microenvironment, guide the selection of chemotherapeutic drugs and immunotherapy, and predict the prognosis of patients.

Calcium/calmodulin-dependentprotein kinase II inhibitor I (CAMK2N1) as one of the tumor suppressor genes is significantly downregulated in prostate cancer (PCa). Reduced expression of CAMK2N1 is positively correlated with PCa progression. However, the mechanisms of CAMK2N1 downregulation in PCa are still unclear. The promoter region of CAMK2N1 contains a large number of CG loci, providing the possibility for DNA methylation. Consequently, we hypothesized that DNA methylation can result in the reduced expression of CAMK2N1 in PCa. In the presented study, the DNA methylation level of CAMK2N1 in prostate cells and clinical specimens was determined by bisulfite sequencing (BS), pyrosequencing, and in silico analysis. Results showed that CAMK2N1 was highly methylated in PCa cells and tissues compared to normal prostate epithelial cells and nonmalignant prostate tissues, which was associated with the clinicopathological characteristics in PCa patients. Afterwards, we explored the expression of CAMK2N1 and its DNA methylation level by qRT-PCR, western blot, BS, and methylation-specific PCR in PCa cells after 5-Aza-CdR treatment or DNMT1 genetic modification, which demonstrated that the reduced expression of CAMK2N1 can be restored by 5-Aza-CdR treatment via demethylation. Moreover, DNMT1 formed a positive feedback loop with CAMK2N1 in PCa cells. The expression of CAMK2N1 was downregulated by DNMT1-mediated DNA methylation, which reversely induced DNMT1 expression through activating AKT or ERK signaling pathway. Finally, functional assays including wound healing, invasion, and migration assay, as well as the xenograft model in nude mice indicated that CAMK2N1 inhibited the invasion, migration, and proliferation of PCa cells and these effects were reversed by DNMT1 overexpression. In conclusion, DNMT1-mediated hypermethylation of CAMK2N1 not only downregulates the gene expression but also promotes the progression of PCa.

Peng H, et al. World J Mens Health. 2024 Jan;42:e18. https://doi.org/10.5534/wjmh.230192

Prostate cancer (PCa) has a high incidence rate, mortality rate, and biochemical recurrence (BCR) rate. 7-Methylguanosine (m7G), as one of the RNA modifications, has been considered to be actively involved in cancer-related translation disorders in recent years. Therefore, we first used The Cancer Genome Atlas (TCGA) database to identify prognosis and m7G-related long non-coding RNAs (lncRNAs). Then we randomly divided the samples into the training set and test set and then constructed and verified the m7G lnRNA prognostic model (m7Gscore) by the least absolute shrinkage and selection operator (LASSO) regression analysis. The m7Gscore has been proved to be an independent marker of BCR-free survival in patients with PCa. Furthermore, the m7Gscore was significantly correlated with the tumor immune microenvironment (TIME) and somatic mutation of PCa patients and had the potential to be an indicator for the selection of drug treatment. We also clustered TCGA cohort into three m7G-related patterns (C1, C2, and C3). The Kaplan–Meier survival analysis revealed that C1 had the best BCR-free survival and C3 had the worst. The TIME was also significantly distinct among the three m7G-related patterns. According to the TIME characteristics of the patterns, we defined C1, C2, and C3 as immune-desert phenotype, immune-inflamed phenotype, and immune-excluded phenotype, respectively.

Phosphodiesterase-5 inhibitors (PDE5-i) have been widely used in clinical practice for the treatment of erectile dysfunction (ED). However, due to its suboptimal therapeutic effects and side effects, it is necessary to develop new medicines for ED treatment. Botanical drugs have been widely investigated as potential ED treatment drugs and have shown promising therapeutic effects. This review summarized 34 studies, including five botanical drugs with PDE5 inhibitory activity, seven botanical drugs without PDE5 inhibitory activity, and six mixed botanical drugs. The results of clinical studies regarding the aforementioned botanical drugs and relevant mechanisms are summarized in this study. It is necessary to conduct high-quality clinical trials to verify the dosage, targeted patients and therapeutic effects, and further pharmacology experiments are also needed to identify the active compounds.