Identification and validation of a ferroptosis-related lncRNA signature to robustly predict the prognosis, immune microenvironment, and immunotherapy efficiency in patients with clear cell renal cell carcinoma

Molecular mechanism of ferroptosis and its application in the treatment of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary tract, the incidence of which is continuously increasing and affects human health worldwide. Despite advances in existing treatments, treatment outcomes still need to be improved due to higher rates of postoperative recurrence, chemotherapy resistance, etc.; thus, there is an urgent need for innovative therapeutic approaches. Ferroptosis is a recently found type of regulated cell death that is characterized primarily by the buildup of lipid peroxidation products and fatal reactive oxygen species created by iron metabolism, which plays a crucial role in tumor progression and therapy.With the molecular mechanisms associated with ferroptosis being increasingly studied and refined, triggering ferroptosis by regulators that target ferroptosis and ccRCC may be the key to developing potential therapeutic strategies for ccRCC. Therefore, ferroptosis is expected to be a new breakthrough in treating ccRCC. This paper examines the mechanism of ferroptosis, the regulatory mechanism of ferroptosis in ccRCC, and the potential application of ferroptosis in combination with other therapies for the treatment of ccRCC. The goal is to offer novel perspectives for the research and clinical application of ferroptosis in the treatment of ccRCC.

S100A12 is involved in the pathology of osteoarthritis by promoting M1 macrophage polarization via the NF-κB pathway

BACKGROUND

Osteoarthritis (OA) is a degenerative joint disease that affects millions worldwide. Synovitis and macrophage polarization are important factors in the development of OA. However, the specific components of synovial fluid (SF) responsible for promoting macrophage polarization remain unclear.

METHODS

Semi-quantitative antibody arrays were used to outline the proteome of SF. Differential expression analysis and GO/KEGG were performed on the obtained data. Immunohistochemistry and ELISA were used to investigate the relationship between SF S100A12 levels and synovitis levels in clinalclinical samples. In vitro cell experiments were conducted to investigate the effect of S100A12 on macrophage polarization. Public databases were utilized to predict and construct an S100A12-centered lncRNA-miRNA-mRNA competing endogenous RNA network, which was preliminarily validated using GEO datasets.

RESULTS

The study outlines the protein profile in OA and non-OA SF. The results showed that the S100A12 level was significantly increased in OA SF and inflammatory chondrocytes. The OA synovium had more severe synovitis and higher levels of S100A12 than non-OA synovium. Exogenous S100A12 upregulated the levels of M1 markers and phosphorylated p65 and promoted p65 nuclear translocation, while pretreatment with BAY 11-7082 reversed these changes. It was also discovered that LINC00894 was upregulated in OA and significantly correlated with S100A12, potentially regulating S100A12 expression by acting as a miRNA sponge.

CONCLUSIONS

This study demonstrated that S100A12 promotes M1 macrophage polarization through the NF-κB pathway, and found that LINC00894 has the potential to regulate the expression of S100A12 as a therapeutic approach.

Development and validation of a combined hypoxia- and metabolism-related prognostic signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Hypoxia and metabolism are closely correlated with the progression of cancer. We aimed to construct a combined hypoxia- and metabolism-related genes (HMRGs) prognostic signature to predict survival and immunotherapy responses in patients with clear cell renal cell carcinoma (ccRCC).

Methods

The RNA-seq profiles and clinical data of ccRCC were acquired from the TCGA and the ArrayExpress (E-MTAB-1980) databases. Least absolute shrinkage and selection operator (LASSO) and univariate and multivariate Cox regression analyses were applied to establish a prognostic signature. The E-MTAB-1980 cohort was selected for validation. The effectiveness and reliability of the signature were further evaluated by Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) curves. Further analyses, including functional enrichment, ssGSEA algorithm, CIBERSORT algorithm, and expression of immune checkpoints, were explored to investigate immune status and immunotherapy responses.

Results

We constructed a prognostic eight-gene signature with IRF6, TEK, PLCB2, ABCB1, TGFA, COL4A5, PLOD2, and TUBB6. Patients were divided into high-risk and low-risk groups based on the medium-risk score. The K-M analysis revealed that patients in the high-risk group had an apparently poor prognosis compared to those in the low-risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p < 0.005). The area under ROC curve (AUC) of the prognostic signature was 0.8 at 1 year, 0.77 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.82 at 1 year, 0.74 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis confirmed the risk score as a separate prognostic factor in ccRCC patients (p < 0.001). The results of ssGSEA showed not only a high degree of immune cell infiltration but also high scores of immune-related functions in the high-risk group. The CIBERSORT analysis further confirmed that the abundance of immune cells was apparently different between the two risk groups. The risk score was significantly correlated with the expression of cytotoxic T lymphocyte-associated antigen-4 (CTLA4), lymphocyte-activation gene 3 (LAG3), and programmed cell death protein 1 (PD-1).

Conclusion

The HMRGs signature could be used to predict clinical prognosis, evaluate the efficacy of immunotherapy, and guide personalized immunotherapy in ccRCC patients.

Analysis of lncRNAs profiles associated with ferroptosis can predict prognosis and immune landscape and drug sensitivity in patients with clear cell renal cell carcinoma

Ferroptosis is a novel kind of iron- and reactive oxygen-induced cell death, investigation into ferroptosis-associated long noncoding RNAs (FALs) in clear cell renal cell carcinoma (ccRCC) is scarce. The goal of the research was to look at FALs' possible predictive significance, as well as their interaction with the immune microenvironment and therapeutic responsiveness of ccRCC. The Cancer Genome Atlas database was employed to retrieve RNA sequencing data from 530 individuals with ccRCC. Patients with ccRCC were randomly assigned to one of two groups: training or testing. Pearson's correlation analysis through the identified ferroptosis-related genes was implemented to screen for FALs. Finally, a FALs signature composed of eight lncRNAs was discovered for predicting survival outcomes in ccRCC patients. ccRCC patients in the training, testing, and overall cohorts were separated into low-risk and high-risk groups based on their risk score. The FALs signature was identified to be an independent factor for overall survival in the multivariate Cox analysis (hazard ratio = 1.013, 95% confidence interval = 1.008-1.018, p < 0.001). A clinically prognostic nomogram was created depending on the FALs signature and clinical characteristics. The nomogram provides greater clinical practicability and may reliably estimate patients' overall survival. The FALs signature may additionally precisely represent ccRCC's immunological environment, immunotherapy reaction, and drug sensitivity. The eight FALs and their signature provide precise and reliable methods for evaluating the clinical effects of in ccRCC patients, and they could be biological markers and targets for therapy.

Noncoding RNAs as an emerging resistance mechanism to immunotherapies in cancer: basic evidence and therapeutic implications

The increasing knowledge in the field of oncoimmunology has led to extensive research into tumor immune landscape and a plethora of clinical immunotherapy trials in cancer patients. Immunotherapy has become a clinically beneficial alternative to traditional treatments by enhancing the power of the host immune system against cancer. However, it only works for a minority of cancers. Drug resistance continues to be a major obstacle to the success of immunotherapy in cancer. A fundamental understanding of the detailed mechanisms underlying immunotherapy resistance in cancer patients will provide new potential directions for further investigations of cancer treatment. Noncoding RNAs (ncRNAs) are tightly linked with cancer initiation and development due to their critical roles in gene expression and epigenetic modulation. The clear appreciation of the role of ncRNAs in tumor immunity has opened new frontiers in cancer research and therapy. Furthermore, ncRNAs are increasingly acknowledged as a key factor influencing immunotherapeutic treatment outcomes. Here, we review the available evidence on the roles of ncRNAs in immunotherapy resistance, with an emphasis on the associated mechanisms behind ncRNA-mediated immune resistance. The clinical implications of immune-related ncRNAs are also discussed, shedding light on the potential ncRNA-based therapies to overcome the resistance to immunotherapy.

Targeting ferroptosis in renal cell carcinoma: Potential mechanisms and novel therapeutics

Renal cell carcinoma (RCC) is an increasingly prevalent urologic malignancy that impacts human health worldwide. Surgery is an effective strategy for early RCC treatment, but advanced RCC is resistant to chemotherapy, thus development of other potential therapeutic strategies is urgent. Ferroptosis is a newly defined form of programmed cell death characterized by accumulation of iron-dependent lipid peroxides and plays a crucial role in the tumor progression and drug resistance. Recent studies have shown that ferroptosis participates in RCC progression and chemoresistance. Therefore, identifying the potential role of ferroptosis in RCC could develop novel therapeutic targets and clinical markers for this disease. This review concisely summarizes the regulatory role of iron, amino acid, and lipid metabolism in ferroptosis, as well as discusses the relationship between ferroptosis and RCC, and details the role of ferroptosis in tumor progression, which indicates that various ferroptosis regulators are dysregulated in RCC and exert paradoxical effects, either tumor-suppressive or oncogenic. These ferroptosis-related regulators are expected to be used as clinical markers for RCC prognosis. Thus, targeting these regulators to trigger ferroptosis may be the key to the development of potential therapeutic strategies for this disease.

Discovery and Potential Functional Characterization of Long Noncoding RNAs Associated with Familial Acne Inversa with NCSTN Mutation

BACKGROUND

Long noncoding RNAs (lncRNAs) are associated with many dermatologic diseases. However, little is known about the regulatory function of lncRNAs in familial acne inversa (AI) patients with nicastrin (NCSTN) mutation.

OBJECTIVES

The aim of this study was to explore the regulatory function of lncRNAs in familial AI patients with NCSTN mutation.

METHODS

The expression profiles of lncRNAs and mRNAs in skin tissues from familial AI patients with NCSTN mutation and healthy individuals were analysed in this study via RNA sequencing (RNA-seq).

RESULTS

In total, 359 lncRNAs and 1,863 mRNAs were differentially expressed between the two groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the dysregulated mRNAs targeted by lncRNAs were mainly associated with the immune regulation, Staphylococcus aureus infection and B cell receptor signalling pathways. The lncRNA-miRNA-mRNA coexpression network contained 265 network pairs comprising 55 dysregulated lncRNAs, 11 miRNAs, and 74 mRNAs. Conservation analysis of the differentially expressed lncRNAs between familial AI patients with NCSTN mutation and Ncstn keratinocyte-specific knockout (NcstnΔKC) mice identified 6 lncRNAs with sequence conservation; these lncRNAs may participate in apoptosis, proliferation, and skin barrier function.

CONCLUSIONS

These findings provide a direction for exploring the regulatory mechanisms underlying the progression of familial AI patients with NCSTN mutation.

Construction and Assessment of a Prognostic Risk Model for Cervical Cancer Based on Lactate Metabolism-Related lncRNAs

Purpose

Cervical cancer (CC) has the fourth highest incidence and mortality rate among female cancers. Lactate is a key regulator promoting tumor progression. Long non-coding RNAs (lncRNAs) are closely associated with cervical cancer (CC). The study was aimed to develop a prognostic risk model for cervical cancer based on lactate metabolism-associated lncRNAs and to determine their clinical prognostic value.

Patients and Methods

In this study, CESC transcriptome data were obtained from the TCGA database. 262 lactate metabolism-associated genes were extracted from MsigDB (Molecular Characterization Database). Then, correlation analysis was used to identify LRLs. Univariate Cox regression analysis was performed afterwards, followed by least absolute shrinkage and selection operator (LASSO) regression analysis and multiple Cox regression analysis. 10 lncRNAs were finally identified to construct a risk score model. They were divided into two groups of high risk and low risk according to the median of risk scores. The predictive performance of the models was assessed by Kaplan-Meier (K-M) analysis, subject work characteristics (ROC) analysis, and univariate and multivariate Cox analyses. To assess the clinical utility of the prognostic model, we performed functional enrichment analysis, immune microenvironment analysis, mutation analysis, and column line graph generation.

Results

We constructed a prognostic model consisting of 10 LRLs at CC. We observed that high-risk populations were strongly associated with poor survival outcomes. Risk score was an independent risk factor for CC prognosis and was strongly associated with immune microenvironment analysis and tumor mutational load.

Conclusion

We developed a risk model of lncRNAs associated with lactate metabolism and used it to predict prognosis of CC, which could guide and facilitate the progress of new treatment strategies and disease monitoring in CC patients.