GNRH1 and LTB4R might be novel immune-related prognostic biomarkers in clear cell renal cell carcinoma (ccRCC)

Chronic cadmium exposure triggered ferroptosis by perturbing the STEAP3-mediated glutathione redox balance linked to altered metabolomic signatures in humans

Cadmium (Cd), a predominant environmental pollutant, is a canonical toxicant that acts on the kidneys. However, the nephrotoxic effect and underlying mechanism activated by chronic exposure to Cd remain unclear. In the present study, male mice (C57BL/6J, 8 weeks) were treated with 0.6 mg/L cadmium chloride (CdCl2) administered orally for 6 months, and tubular epithelial cells (TCMK-1 cells) were treated with low-dose (1, 2, and 3 μM) CdCl2 for 72 h (h). Our study results revealed that environmental Cd exposure triggered ferroptosis and renal dysfunction. Spatially resolved metabolomics enabled delineation of metabolic profiles and visualization of the disruption to glutathione homeostasis related to ferroptosis in mouse kidneys. Multiomics analysis revealed that chronic Cd exposure induced glutathione redox imbalance that depended on STEAP3-driven lysosomal iron overload. In particular, glutathione metabolic reprogramming linked to ferroptosis emerged as a metabolic hallmark in the blood of Cd-exposed workers. In conclusion, this study provides the first evidence indicating that chronic Cd exposure triggers ferroptosis and renal dysfunction that depend on STEAP3-mediated glutathione redox imbalance, greatly increasing our understanding of the metabolic reprogramming induced by Cd exposure in the kidneys and providing novel clues linking chronic Cd exposure to nephrotoxicity.

FAP promotes clear cell renal cell carcinoma progression via activating the PI3K/AKT/mTOR signaling pathway

OBJECTIVE

Herein, we aimed at exploring the FAP expression in clear cell renal cell carcinoma (ccRCC) along with its clinical implication.

METHODS

Using computational tools analysis of different freely accessible gene databases, the expression pattern, clinical importance, co-expressed genes, and signaling pathways of FAP in ccRCC were thoroughly investigated. FAP expression was examined in clinical ccRCC specimens through qRT-PCR, western blotting and immunohistochemistry. Furthermore, in vitro and in vivo experiments were carried out using flow cytometry, CCK-8, wound-healing and Transwell assays, as well as xenograft tumor model, respectively.

RESULTS

FAP levels were found to be significantly elevated in ccRCC based on bioinformatic data from public databases. Patients who exhibited higher expression levels of FAP had poorer prognoses, according to Kaplan-Meier analysis of survival data. In addition, diagnostic and prognostic value of FAP in ccRCC was figured out by ROC curve and prognostic nomogram model. In vitro study revealed that the over-expression FAP accelerated cell proliferation, migration as well as invasion, and suppressed cell apoptosis, but silencing of FAP had the opposite effect. FAP suppression reduced the PI3K/AKT/mTOR pathway's stimulation, whereas FAP up-regulation increased the stimulation of the pathway. Blocking the PI3K/AKT/mTOR signaling pathway with the dual PI3K/mTOR inhibitor BEZ235 repressesed cancer-promoting effect of FAP. Additionally, we found that the downregulation of FAP was effective at slowing tumor progression in vivo.

CONCLUSION

It is possible that FAP could be a reliable biomarker for the diagnosis and prognosis of ccRCC because of its role in the ccRCC progression via triggering the PI3K/AKT/mTOR signaling pathway.

Lipids as Targets for Renal Cell Carcinoma Therapy

Kidney cancer is among the top ten most common cancers to date. Within the kidney, renal cell carcinoma (RCC) is the most common solid lesion occurring. While various risk factors are suspected, including unhealthy lifestyle, age, and ethnicity, genetic mutations seem to be a key risk factor. In particular, mutations in the von Hippel-Lindau gene (Vhl) have attracted a lot of interest since this gene regulates the hypoxia inducible transcription factors HIF-1α and HIF-2α, which in turn drive the transcription of many genes that are important for renal cancer growth and progression, including genes involved in lipid metabolism and signaling. Recent data suggest that HIF-1/2 are themselves regulated by bioactive lipids which make the connection between lipids and renal cancer obvious. This review will summarize the effects and contributions of the different classes of bioactive lipids, including sphingolipids, glycosphingolipids, eicosanoids, free fatty acids, cannabinoids, and cholesterol to renal carcinoma progression. Novel pharmacological strategies interfering with lipid signaling to treat renal cancer will be highlighted.

Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor, and investigating the immunorelated genes is essential. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, an immunoprognosis model was constructed to identify four hub genes with moderate predictive values for the prognosis of ccRCC patients. These four genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltration could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of three hub genes were associated with tumor progression (P<0.1). In conclusion, four genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.

LTB4R Promotes the Occurrence and Progression of Clear Cell Renal Cell Carcinoma (ccRCC) by Regulating the AKT/mTOR Signaling Pathway

ccRCC is highly immunogenic, yet its underlying immune-related molecular mechanisms are unknown. Leukotriene B4 Receptor 1 (LTB4R), a novel immune-related gene associated in our previous research with the prognosis of ccRCC patients, has been found in many cancers; however, its potential mechanism in renal clear carcinoma is unclear. This study was conducted to investigate LTB4R's action mechanism in renal clear cell carcinoma. First, a CCK8 assay was performed to verify LTB4R's effect on the proliferation viability of renal clear cell carcinoma cells. Scratch and transwell assays verified LTB4R's effect on the migration and invasion ability of renal clear cell carcinoma cells. Flow cytometry validated LTB4R's effect on renal clear cell carcinoma cells' apoptosis and cell cycle. A Western blot assay was conducted to further investigate LTB4R's effect on apoptosis, cell cycle, EMT process, and AKT/mTOR signaling pathway in renal clear cell carcinoma at the protein level. In vitro experiments showed that LTB4R knockdown inhibited the proliferation, migration, and invasion of renal clear cell carcinoma cells and promoted their apoptosis, whereas LTB4R overexpression promoted the proliferation, migration, and invasion of renal clear cell carcinoma cells and inhibited their apoptosis. In addition, we found that LTB4R regulated the proliferation and apoptosis of renal clear cell carcinoma cells by regulating the AKT/mTOR signaling pathway's phosphorylation process. Furthermore, we verified some of these results using bioinformatic analysis. LTB4R plays an oncogenic role in renal clear cell carcinoma; it is expected to be a molecular target for renal clear cell carcinoma treatment and a predictive biomarker for prognosis.

Effects and Prognostic Values of Circadian Genes CSNK1E/GNA11/KLF9/THRAP3 in Kidney Renal Clear Cell Carcinoma via a Comprehensive Analysis

Kidney renal clear cell carcinoma (KIRC) is one of the most prevalent and deadly types of renal cancer in adults. Recent research has identified circadian genes as being involved in the development and progression of KIRC by altering their expression. This study aimed to identify circadian genes that are differentially expressed in KIRC and assess their role in KIRC progression. In KIRC, there were 553 differentially expressed rhythm genes (DERGs), with 300 up-regulated and 253 down-regulated DERGs. Functional enrichment analyses showed that DERGs were greatly enriched in the circadian rhythm and immune response pathways. Survival analyses indicated that higher expression levels of CSNK1E were related to shorter overall survival of KIRC patients, whereas lower expression levels of GNA11, KLF9, and THRAP3 were associated with shorter overall survival of KIRC patients. Through cell assay verification, the mRNA level of CSNK1E was significantly up-regulated, whereas the mRNA levels of GNA11, KLF9, and THRAP3 were dramatically down-regulated in KIRC cells, which were consistent with the bioinformatics analysis of KIRC patient samples. Age, grade, stage, TM classification, and CSNK1E expression were all shown to be high-risk variables, whereas GNA11, KLF9, and THRAP3 expression were found to be low-risk factors in univariate Cox analyses. Multivariate Cox analyses showed that CSNK1E and KLF9 were also independently related to overall survival. Immune infiltration analysis indicated that the proportion of immune cells varied greatly between KIRC tissues and normal tissue, whereas CSNK1E, GNA11, KLF9, and THRAP3 expression levels were substantially linked with the infiltration abundance of immune cells and immunological biomarkers. Moreover, interaction networks between CSNK1E/GNA11/KLF9/THRAP3 and immune genes were constructed to explore the stream connections. The findings could help us better understand the molecular mechanisms of KIRC progression, and CSNK1E/GNA11/KLF9/THRAP3 might be used as molecular targets for chronotherapy in KIRC patients in the near future.

m7G Methylation-Related Genes as Biomarkers for Predicting Overall Survival Outcomes for Hepatocellular Carcinoma

Aim: The search for prognostic biomarkers and the construction of a prognostic risk model for hepatocellular carcinoma (HCC) based on N7-methyladenosine (m7G) methylation regulators. Methods: HCC transcriptomic data and clinical data were obtained from The Cancer Genome Atlas database and Shanghai Ninth People's Hospital, respectively. m7G methylation regulators were extracted, differential expression analysis was performed using the R software "limma" package, and one-way Cox regression analysis was used to screen for prognostic associations of m7G regulators. Using multi-factor Cox regression analysis, a prognostic risk model for HCC was constructed. Each patient's risk score was calculated using the model, and patients were divided into high- and low-risk groups according to the median risk score. Cox regression analysis was used to verify the validity of the model in the prognostic assessment of HCC in conjunction with clinicopathological characteristics. Results: The prognostic model was built using the seven genes, namely, CYFIP1, EIF4E2, EIF4G3, GEMIN5, NCBP2, NUDT10, and WDR4. The Kaplan-Meier survival analysis showed poorer 5-years overall survival in the high-risk group compared with the low-risk group, and the receiver-operating characteristic (ROC) curve suggested good model prediction (area under the curve AUC = 0.775, 0.820, and 0.839 at 1, 3, and 5 years). The Cox regression analysis included model risk scores and clinicopathological characteristics, and the results showed that a high-risk score was the only independent risk factor for the prognosis of patients with HCC. Conclusions: The developed bioinformatics-based prognostic risk model for HCC was found to have good predictive power.

An Aging and Senescence-Related Gene Signature for Prognosis Prediction in Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion in the kidney. This study aims to establish an aging and senescence-related mRNA model for risk assessment and prognosis prediction in ccRCC patients.

Methods: ccRCC data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. By applying univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, a new prognostic model based on aging and senescence-related genes (ASRGs) was established. Depending on the prognostic model, high- and low-risk groups were identified for further study. The reliability of the prediction was evaluated in the validation cohort. Pan-cancer analysis was conducted to explore the role of GNRH1 in tumors.

Results: A novel prognostic model was established based on eight ASRGs. This model was an independent risk factor and significantly correlated with the prognosis and clinicopathological features of ccRCC patients. The high- and low-risk groups exhibited distinct modes in the principal component analysis and different patterns in immune infiltration. Moreover, the nomogram combining risk score and other clinical factors showed excellent predictive ability, with AUC values for predicting 1-, 3-, and 5-year overall survival in the TCGA cohort equal to 0.88, 0.82, and 0.81, respectively.

Conclusion: The model and nomogram based on the eight ASRGs had a significant value for survival prediction and risk assessment for ccRCC patients, providing new insights into the roles of aging and senescence in ccRCC.

Prognostic and immunological value of LTB4R in pan-cancer

BACKGROUND

LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.

METHODS

We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies.

RESULTS

In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns.

CONCLUSION

The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.