Genomic analysis uncovers prognostic and immunogenic characteristics of ferroptosis for clear cell renal cell carcinoma

PAQR6 as a prognostic biomarker and potential therapeutic target in kidney renal clear cell carcinoma

Background

Progestin And AdipoQ Receptor Family Member VI (PAQR6) plays a significant role in the non-genomic effects of rapid steroid responses and is abnormally expressed in various tumors. However, its biological function in kidney renal clear cell carcinoma (KIRC) and its potential as a therapeutic target remain underexplored.

Methods

In this study, PAQR6 was identified as a critical oncogene by WGCNA algorithm and differential gene expression analysis using TCGA - KIRC and GSE15641 data. The differences in PAQR6 expression and its association with KIRC survival outcomes were investigated, and transcriptomic data were used to further elucidate PAQR6's biological functions. Moreover, XCELL and single - cell analysis assessed the correlation between PAQR6 expression and immune infiltration. TIDE algorithm was used to assess how well various patient cohorts responded to immune checkpoint therapy. Finally, the role of PAQR6 in the development of KIRC was verified through EdU, scratch assays, and Transwell assays.

Results

Our findings suggest that elevated expression of PAQR6 is linked to a poor prognosis for KIRC patients. Functional enrichment analysis demonstrated that PAQR6 is primarily involved in angiogenesis and pluripotent stem cell differentiation, which are crucial in mediating the development of KIRC. Additionally, we established a ceRNA network that is directly related to overall prognosis, further supporting the role of PAQR6 as a prognostic biomarker for KIRC.

Conclusion

Using both computational and experimental methods, this study leads the charge in discovering and verifying PAQR6 as a prognostic biomarker and possible therapeutic target for KIRC. In the future, to determine its molecular mechanism in KIRC carcinogenesis, more in vivo research will be carried out.

ATF4/NUPR1 axis promotes cancer cell survival and mediates immunosuppression in clear cell renal cell carcinoma

Cancer cells encounter unavoidable stress during tumor growth. The stress-induced transcription factor, activating transcription factor 4 (ATF4), has been reported to upregulate various adaptive genes involved in salvage pathways to alleviate stress and promote tumor progression. However, this effect is unknown in clear cell renal cell carcinoma (ccRCC). In this study, we found that ATF4 expression was remarkably upregulated in tumor tissues and associated with poor ccRCC outcomes. ATF4 depletion significantly impaired ccRCC cell proliferation, migration, and invasion in vitro and in vivo by inhibiting the AKT/mTOR and epithelial-mesenchymal transition (EMT)-related signaling pathway. RNA sequencing and functional studies identified nuclear protein 1 (NUPR1) as a key downstream target of ATF4 for repressing ferroptosis and promoting ccRCC cell survival. In addition, targeting ATF4 or pharmacological inhibition using NUPR1 inhibitor ZZW115 promoted antitumor immunity in syngeneic graft mouse models, represented by increased infiltration of CD4+ and CD8+ T cells. Furthermore, ZZW115 could improve the response to the PD-1 immune checkpoint blockade. The results demonstrate that the ATF4/NUPR1 signaling axis promotes ccRCC survival and facilitates tumor-mediated immunosuppression, providing a set of potential targets and prognostic indicators for ccRCC patients.

Ferroptosis-associated genes and compounds in renal cell carcinoma

As the main type of renal cell carcinoma (RCC), clear cell RCC (ccRCC) is often associated with the deletion or mutation of the von Hippel Lindau (VHL) gene, enhancement of glucose and lipid metabolism, and heterogeneity of the tumor microenvironment. VHL alterations in RCC cells lead to the activation of hypoxia-inducible factors and their downstream target vascular endothelial growth factor, and to the reprogramming of multiple cell death pathways and metabolic weakness, including ferroptosis, which are associated with targeted therapy or immunotherapy. The changes in biological metabolites (e.g., iron and lipids) support ferroptosis as a potential therapeutic strategy for RCC, while iron metabolism and ferroptosis regulation have been examined as anti-RCC agents in numerous studies, and various ferroptosis-related molecules have been shown to be related to the metastasis and prognosis of ccRCC. For example, glutathione peroxidase 4 and glutaminase inhibitors can inhibit pyrimidine synthesis and increase reactive oxygen species levels in VHL-deficient RCC cells. In addition, the release of damage-associated molecular patterns by tumor cells undergoing ferroptosis also mediates antitumor immunity, and immune therapy can synergize with targeted therapy or radiotherapy through ferroptosis. However, Inducing ferroptosis not only suppresses cancer, but also promotes cancer development due to its potential negative effects on anti-cancer immunity. Therefore, ferroptosis and various tumor microenviroment-related molecules may co-occur during the development and treatment of RCC, and further understanding of the interactions, core targets, and related drugs of ferroptosis may provide new combination drug strategies for RCC treatment. Here we summarize the key genes and compounds on ferroptosis and RCC in order to envision future treatment strategies and to provide sufficient information for overcoming RCC resistance through ferroptosis.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Identification and validation of m6A-associated ferroptosis genes in renal clear cell carcinoma

Urinary cancer is synonymous with clear cell renal cell carcinoma (ccRCC). Unfortunately, existing treatments for this illness are ineffective and unpromising. Finding novel ccRCC biomarkers is crucial to creating successful treatments. The Cancer Genome Atlas provided clear cell renal cell carcinoma transcriptome data. Functional enrichment analysis was performed on ccRCC and control samples' differentially expressed N6-methyladenosine RNA methylation and ferroptosis-related genes (DEMFRGs). Machine learning was used to find and model ccRCC patients' predicted genes. A nomogram was created for clear cell renal cell carcinoma patients. Prognostic genes were enriched. We examined patients' immune profiles by risk score. Our prognostic genes predicted ccRCC treatment drugs. We found 37 DEMFRGs by comparing 1913 differentially expressed ccRCC genes to 202 m6A RNA methylation FRGs. Functional enrichment analysis showed that hypoxia-induced cell death and metabolism pathways were the most differentially expressed methylation functional regulating genes. Five prognostic genes were found by machine learning: TRIB3, CHAC1, NNMT, EGFR, and SLC1A4. An advanced renal cell carcinoma nomogram with age and risk score accurately predicted the outcome. These five prognostic genes were linked to various cancers. Immunological cell number and checkpoint expression differed between high- and low-risk groups. The risk model successfully predicted immunotherapy outcome, showing high-risk individuals had poor results. NIACIN, TAE-684, ROCILETINIB, and others treat ccRCC. We found ccRCC prognostic genes that work. This discovery may lead to new ccRCC treatments.

The crosstalk between ferroptosis and autophagy in cancer

BACKGROUND

In order to better understand the interplay between ferroptosis and autophagy, enhance the interpretation of the crosstalk between these two forms of regulated cell death, develop the effective pharmacological mechanisms for cancer treatment, discover novel biomarkers for better diagnostic, and envisage the future hotspots of the research on ferroptosis and autophagy, we harnessed bibliometric tools to study the articles published from 2012 to 2022 on the relationship between ferroptosis and autophagy.

METHODS

Web of Science Core Collection (WOSCC) database was used to conduct a comprehensive search and analysis of articles in this field from January 1, 2012, to September 1, 2022. The Citespace 6.1.R2 software and VOS viewer 6.1.8 software were utilized to analyze the overall structure of the network, network clusters, links between clusters, key nodes or pivot points, and pathways.

RESULTS

A total of 756 articles associated with the crosstalk between ferroptosis and autophagy were published in 512 journals by 4183 authors in 980 organizations from 55 countries or regions. The distribution of countries and organizations was demonstrated using CiteSpace and VOS viewer. The top three countries with the most articles were China (n = 511), United States (n = 166), and Germany (n = 37). The most productive institutions were Guangzhou Medical University and Central South University (n = 42), but their centralities were relatively low, which values were respective 0.04 and 0.03. Kang and Tang published the most articles related to ferroptosis and autophagy (n = 49), followed by Jiao Liu (n = 22), Guido Kroemer (n = 20), and Daniel Klionsky (n = 12). Published studies on ferroptosis and asthma have the most cited counts. The top three keywords with the highest frequencies were autophagy (n = 283), cell death (n = 243), and oxidative stress (n = 165).

CONCLUSION

Our results provide insights into the development of recognition related to the crosstalk between ferroptosis and autophagy, and the current molecular crosslinked mechanisms in the context of common signal transduction pathways or affecting cellular environment to induce the adaptive stress response and to activate the particular form of regulated cell death (RCD), and the development of cancer treatment based on novel targets and signaling regulatory networks provided by ferroptosis and autophagy.

A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis

Background

Cuproptosis, the most recently identified and regulated cell death, depends on copper ions in vivo. Copper regulates the pathogenesis of Idiopathic pulmonary fibrosis (IPF), but the mechanism of action underlying cuproptosis in IPF remains unclear.

Methods

We identified three cuproptosis patterns based on ten cuproptosis-related genes using unsupervised consensus clustering. We quantified these patterns using a PCA algorithm to construct a cuproptosis score. ssGSEA and the Cibersort algorithm assessed the immune profile of IPF patients. GSEA and GSVA were used to analyze the functional differences in different molecular patterns. Drug susceptibility prediction based on cuproptosis scores and meaningful gene markers was eventually screened in combination with external public data sets,in vitro experiments and our cases.

Results

Of the three types of cuproptosis-related clusters identified in the study, patients in the clusterA, geneclusterB, and score-high groups showed improved prognoses. Moreover, each cluster exhibited differential immune characteristics, with the subtype showing a poorer prognosis associated with an immune overreaction. Cuproptosis score can be an independent risk factor for predicting the prognosis of IPF patients. GSEA showed a significant functional correlation between the score and cuproptosis. The genes AKAP9, ANK3, C6orf106, LYRM7, and MBNL1, were identified as prognostic-related signatures in IPF patients. The functional role of immune regulation in IPF was further explored by correlating essential genes with immune factors. Also, the nomogram constructed by cumulative information from gene markers and cuproptosis score showed reliable clinical application.

Conclusions

Cuproptosis patterns differ significantly in the prognosis and immune characteristics of IPF patients. The cuproptosis score and five gene signatures can provide a reliable reference in the prognosis and diagnosis of IPF.

Elucidating the Role of Pyroptosis in Lower-Grade Glioma: Development of a Novel Scoring System to Enhance Personalized Therapeutic Approaches

Pyroptosis, an orchestrated cellular death pathway, has gained attention due to its role in the pathophysiology and evolution of numerous malignancies. Despite this, no robust quantitative measure of pyroptosis activity in lower-grade glioma (LGG) exists currently. We scrutinized the transcriptomic data of LGG specimens acquired from TCGA and CGGA repositories, juxtaposed with the expression patterns of healthy brain tissues from the GTEx database. A register of pyroptosis-associated genes was extracted from the GSEA database. Utilizing unsupervised clustering algorithms on the expression patterns of these genes, we stratified LGG samples into unique subgroups. We implemented the Boruta machine learning algorithm to discern representative variables for each pyroptosis subtype and applied principal component analysis (PCA) to condense the dimensionality of the feature gene expression data, which led to the formulation of a pyroptosis scoring system (P score) to estimate pyroptosis activity in LGG. Furthermore, we affirmed the capacity of the P score to discriminate diverse cell subpopulations within a single-cell database and explored the correlations between the P score and clinical attributes, prognostic implications, and the tumor immune microenvironment in LGG. We identified three distinctive pyroptosis patterns with significant correlations to patient survival, clinicopathological properties, and characteristics of the tumor immune microenvironment (TIME). Two gene clusters, associated with unique prognostic and TIME attributes, emerged from differentially expressed genes (DEGs) across the pyroptosis patterns. The P score was formulated and authenticated as an autonomous prognostic determinant for overall survival in the TCGA and CGGA cohorts. Additionally, the P score demonstrated its competency to quantitatively represent pyroptosis activity across different cellular subpopulations in single-cell data. Notably, the P score in LGG was found to be indicative of tumor stemness and could serve as a predictive biomarker for the efficacy of temozolomide treatment and immunotherapy, underscoring its potential clinical utility. Our investigation pioneers a novel pyroptosis-centric scoring system with significant prognostic implications. The P score holds promise as a potential predictive biomarker for the response to chemotherapy and immunotherapy, facilitating the development of personalized therapeutic approaches in LGG patients.

Life span-associated ferroptosis-related genes identification and validation for hepatocellular carcinoma patients as hepatitis B virus carriers

BACKGROUND

Hepatitis B virus (HBV)-infected population accounts for approximately 50% of all hepatocellular carcinoma (HCC) cases and has a relatively poor prognosis. Although the significant role of ferroptosis in the development and therapeutic response of various cancers has been validated, the key ferroptosis-related genes (FRGs) on the stratification of HBV-associated HCC are still unclear.

METHODS

Through the random forest, GSVA and Cox regression analyses, we established a comprehensive prognostic system covering multiple FRGs to elevate the predictive accuracy for the survival rate of HBV-related HCC using information obtained from public databases. The association between key FRGs and the immune microenvironment was evaluated, and the molecular mechanism was identified by GSEA and SNV analyses. Finally, the differential expression of key FRGs was validated by immunohistochemistry staining of patient tissue microarrays.

RESULTS

Within the top 10 key FRGs, EPAS1 and GABARAPL1 were taken as protective factors, and SQLE, RAD51AP1, RPL8, CAPG, RRM2, SLC1A5, SLC38A1, and SRC were the other eight dangerous markers. Cox regression analysis combined with clinicopathological features indicated the independent prognostic efficacy of GSVA complex score based on these FRGs. In addition, key FRGs were related to immune and metabolic-related functions. Especially, the immunohistochemical analysis of SQLE in 50 clinical samples showed significantly higher expression in HBV+ HCC tissues.

CONCLUSIONS

These results indicate that 10 FRGs may be potential biomarkers and therapeutic targets for long-term survival in HBV-related HCC.

Deciphering the immune heterogeneity dominated by natural killer cells with prognostic and therapeutic implications in hepatocellular carcinoma

Belonging to type 1 innate lymphoid cells (ILC1), natural killer (NK) cells play an important role not only in fighting microbial infections but also in anti-tumor response. Hepatocellular carcinoma (HCC) represents an inflammation-related malignancy and NK cells are enriched in the liver, making them an essential component of the HCC immune microenvironment. In this study, we performed single-cell RNA-sequencing (scRNA-seq) analysis to identify the NK cell marker genes (NKGs) and uncovered 80 prognosis-related ones by the TCGA-LIHC dataset. Based on prognostic NKGs, HCC patients were categorized into two subtypes with distinct clinical outcomes. Subsequently, we conducted LASSO-COX and stepwise regression analysis on prognostic NKGs to establish a five-gene (UBB, CIRBP, GZMH, NUDC, and NCL) prognostic signature-NKscore. Different mutation statuses of the two risk groups stratified by NKscore were comprehensively characterized. Besides, the established NKscore-integrated nomogram presented enhanced predictive performance. Single sample gene set enrichment analysis (ssGSEA) analysis was used to uncover the landscape of the tumor immune microenvironment (TIME) and the high-NKscore risk group was characterized with an immune-exhausted phenotype while the low-NKscore risk group held relatively strong anti-cancer immunity. T cell receptor (TCR) repertoire, tumor inflammation signature (TIS), and Immunophenoscore (IPS) analyses revealed differences in immunotherapy sensitivity between the two NKscore risk groups. Taken together, we developed a novel NK cell-related signature to predict the prognosis and immunotherapy efficacy for HCC patients.

Genomic analysis of matrix metalloproteinases affecting the prognosis and immunogenic profile of gastric cancer

This study systematically and comprehensively analyzed the characteristics of matrix metalloproteinases (MMPs) in gastric cancer (GC) and revealed the relationship between MMPs and prognoses, clinicopathological features, tumor microenvironment, gene mutations, and drug therapy response in patients with GC. Based on the mRNA expression profiles of 45 MMP-related genes in GC, we established a model that classified GC patients into three groups based on cluster analysis of the mRNA expression profiles. The 3 groups of GC patients showed significantly different prognoses as well as tumor microenvironmental characteristics. Next, we used Boruta's algorithm and PCA method to establish an MMP scoring system and found that lower MMP scores were associated with better prognoses, lower clinical stages, better immune cell infiltration, lower degrees of immune dysfunction and rejection, and more genetic mutations. Whereas a high MMP score was the opposite. These observations were further validated with data from other datasets, showing the robustness of our MMP scoring system. Overall, MMP could be involved in the tumor microenvironment (TME), clinical features, and prognosis of GC. An in-depth study of MMP patterns can better understand the indispensable role of MMP in the development of GC and reasonably assess the survival prognosis, clinicopathological features, and drug efficacy of different patients, thus providing clinicians with a broader vision of GC progression and treatment.

A new thinking: deciphering the aberrance and clinical implication of copper-death signatures in clear cell renal cell carcinoma

RATIONALE

Recent research has indicated that cuprotosis, or copper induced cell death, is a novel type of cell death that could be utilized as a new weapon for cancer management. However, the characteristics and implications of such signatures in cancers, especially in clear cell renal cell cancer (ccRCC), remain elusive.

METHODS

Expression, methylation, mutation, clinical information, copy number variation, functional implication, and drug sensitivity data at the pan-cancer level were collected from The Cancer Genome Atlas. An unsupervised clustering algorithm was applied to decipher ccRCC heterogeneity. Immune microenvironment construction, immune therapy response, metabolic pattern, and cancer progression signature between subgroups were also investigated.

RESULTS

Cuprotosis related genes were specifically downregulated in various cancer tissues compared with normal tissues and were correlated with hypermethylation and copy number variation. Cuprotosis scores were also dysregulated in tumor tissues, and we found that such a signature could positively regulate oxidative phosphorylation and Myc and negatively regulate epithelial mesenchymal translation and myogenesis pathways. CPCS1 (cuprotosis scores high) and CPCS2 (cuprotosis scores low) in ccRCC displayed distinctive clinical profiles and biological characteristics; the CPCS2 subtype had a higher clinical stage and a worse prognosis and might positively regulate cornification and epidermal cell differentiation to fuel cancer progression. CPCS2 also displayed a higher tumor mutation burden and low tumor stemness index, while it led to a low ICI therapy response and dysfunctional tumor immunity state. The genome-copy numbers of CPCS2, including arm- gain and arm- loss, were higher than those of CPCS1. The prognostic model constructed based on subgroup biomarkers exerted satisfactory performance in both the training and validation cohorts. In addition, overexpression of the copper death activator DLAT suppressed the malignant ability, including cell migration and proliferation, of renal cell lines in vitro and in vivo. Finally, activation of cuprotosis in tumors could enhance antitumor immunity through dsDNA-cGAS-STING signaling in ccRCC.

CONCLUSION

The activation of cuprotosis might function as a promising approach among multiple cancers. The cuprotosis related signatures could reshape tumor immunity in the ccRCC microenvironment via cGAS-STING signal, thus activating tumor antigen-presenting process. Upregulation of DLAT expression in ccRCC cell lines could reactivate the copper death pattern and be treated as a suitable target for ccRCC.

A Cuproptosis-Related lncRNAs Signature Could Accurately Predict Prognosis in Patients with Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancers. As cuproptosis, a new cell death mechanism proposed recently, differs from all other known mechanisms regulating cell death, we aimed to create prognostic markers using cuproptosis-related long non-coding ribonucleic acids (RNAs; lncRNAs) and elucidate the molecular mechanism.

Methods

Data from transcriptome RNA sequencing of ccRCC samples and the relevant clinical data were downloaded from The Cancer Genome Atlas, and Pearson's correlation analysis was implemented to obtain the cuproptosis-related lncRNAs. Then, univariate Cox, multivariate Cox, and Least Absolute Shrinkage and Selection Operator Cox analyses were performed to construct the risk signatures. The cuproptosis-related lncRNAs predictive signature was evaluated with receiver operating characteristic curves and subgroup analysis. Finally, Gene Set Enrichment Analysis (GSEA), single-sample GSEA (ssGSEA), tumor immune microenvironment (TIME), and immune checkpoints were performed to explore the relationship between immunity and patient prognosis.

Results

Five cuproptosis-related lncRNAs, including FOXD2-AS1, LINC00460, AC091212.1, AC007365.1, and AC026401.3, were used to construct the signature. In the training and test sets, low-risk groups (as identified by a risk score lower than the median) demonstrated a better prognosis with an area under the curve for 1-, 3-, and 5-year survival being 0.793, 0.716, and 0.719, respectively. GSEA analysis suggested significant enrichment of the tricarboxylic acid cycle and metabolism-related pathways in the low-risk group. Besides, both ssGSEA and TIME suggested that the high-risk group exhibited more active immune infiltration.

Conclusion

We proposed a cuproptosis-related lncRNAs signature, which had the potential for prognoses and prediction. Our findings might contribute to elucidating potential genomic biomarkers and targets for future therapies in the cuproptosis-related signaling pathways.

Ferroptosis: a double-edged sword mediating immune tolerance of cancer

The term ferroptosis was put forward in 2012 and has been researched exponentially over the past few years. Ferroptosis is an unconventional pattern of iron-dependent programmed cell death, which belongs to a type of necrosis and is distinguished from apoptosis and autophagy. Actuated by iron-dependent phospholipid peroxidation, ferroptosis is modulated by various cellular metabolic and signaling pathways, including amino acid, lipid, iron, and mitochondrial metabolism. Notably, ferroptosis is associated with numerous diseases and plays a double-edged sword role. Particularly, metastasis-prone or highly-mutated tumor cells are sensitive to ferroptosis. Hence, inducing or prohibiting ferroptosis in tumor cells has vastly promising potential in treating drug-resistant cancers. Immunotolerant cancer cells are not sensitive to the traditional cell death pathway such as apoptosis and necroptosis, while ferroptosis plays a crucial role in mediating tumor and immune cells to antagonize immune tolerance, which has broad prospects in the clinical setting. Herein, we summarized the mechanisms and delineated the regulatory network of ferroptosis, emphasized its dual role in mediating immune tolerance, proposed its significant clinical benefits in the tumor immune microenvironment, and ultimately presented some provocative doubts. This review aims to provide practical guidelines and research directions for the clinical practice of ferroptosis in treating immune-resistant tumors.

A mitophagy-related gene signature associated with prognosis and immune microenvironment in colorectal cancer

Colorectal cancer (CRC) is a heterogeneous disease and one of the most prevalent malignancies worldwide. Previous research has demonstrated that mitophagy is crucial to developing colorectal cancer. This study aims to examine the association between mitophagy-related genes and the prognosis of CRC patients. Gene expression profiles and clinical information of CRC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis were applied to establish a prognostic signature using mitophagy related genes. Kaplan-Meier and receiver operating characteristic (ROC) curves were used to analyze patient survival and predictive accuracy. Meanwhile, we also used the Genomics of Drug Sensitivity in Cancer (GDSC) database and Tumor Immune Dysfunction and Exclusion (TIDE) algorithm to estimate the sensitivity of chemotherapy, targeted therapy and immunotherapy. ATG14 overexpression plasmid was used to regulate the ATG14 expression level in HCT116 and SW480 cell lines, and cell counting kit-8, colony formation and transwell migration assay were performed to validate the function of ATG14 in CRC cells. A total of 22 mitophagy-driven genes connected with CRC survival were identified, and then a novel prognostic signature was established based on 10 of them (AMBRA1, ATG14, MAP1LC3A, MAP1LC3B, OPTN, VDAC1, ATG5, CSNK2A2, MFN1, TOMM22). Patients were divided into high-risk and low-risk groups based on the median risk score, and the survival of patients in the high-risk group was significantly shorter in both the training cohort and two independent cohorts. ROC curve showed that the area under the curves (AUC) of 1-, 3- and 5-year survival were 0.66, 0.66 and 0.64, respectively. Multivariate Cox regression analysis confirmed the independent prognostic value of the signature. Then we constructed a Nomogram combining the risk score, age and M stage, which had a concordance index of survival prediction of 0.77 (95% CI 0.71-0.83) and more robust predictive accuracy. Results showed that CD8+ T cells, regulatory T cells and activated NK cells were significantly more enriched in the high-risk group. Furthermore, patients in the high-risk group are more sensitive to targeted therapy or chemotherapy, including bosutinib, elesclomol, lenalidomide, midostaurin, pazopanib and sunitinib, while the low-risk group is more likely to benefit from immunotherapy. Finally, in vitro study confirmed the oncogenic significance of ATG14 in both HCT116 and SW480 cells, whose overexpression increased CRC cell proliferation, colony formation, and migration. In conclusion, we developed a novel mitophagy-related gene signature that can be utilized not only as an independent predictive biomarker but also as a tool for tailoring personalizing treatment for CRC patients, and we confirmed ATG14 as a novel oncogene in CRC.

Comprehensive investigation into cuproptosis in the characterization of clinical features, molecular characteristics, and immune situations of clear cell renal cell carcinoma

Background

Copper-induced cell death has been widely investigated in human diseases as a form of programmed cell death (PCD). The newly recognized mechanism underlying copper-induced cell death provided us creative insights into the copper-related toxicity in cells, and this form of PCD was termed cuproptosis.

Methods

Through consensus clustering analysis, ccRCC patients from TCGA database were classified into different subgroups with distinct cuproptosis-based molecular patterns. Analyses of clinical significance, long-term survival, and immune features were performed on subgroups accordingly. The cuproptosis-based risk signature and nomogram were constructed and validated relying on the ccRCC cohort as well. The cuproptosis scoring system was generated to better characterize ccRCC patients. Finally, in vitro validation was conducted using ccRCC clinical samples and cell lines.

Result

Patients from different subgroups displayed diverse clinicopathological features, survival outcomes, tumor microenvironment (TME) characteristics, immune-related score, and therapeutic responses. The prognostic model and cuproptosis score were well validated and proved to efficiently distinguish the high risk/score and low risk/score patients, which revealed the great predictive value. The cuproptosis score also tended out to be intimately associated with the prognosis and immune features of ccRCC patients. Additionally, the hub cuproptosis-associated gene (CAG) FDX1 presented a dysregulated expression pattern in human ccRCC samples, and it was confirmed to effectively promote the killing effects of copper ionophore elesclomol as a direct target. In vitro functional assays revealed the prominent anti-cancer role of FDX1 in ccRCC.

Conclusion

Cuproptosis played an indispensable role in the regulation of TME features, tumor progression, and long-term prognosis of ccRCC.

A Novel Prognosis Signature Based on Ferroptosis-Related Gene DNA Methylation Data for Lung Squamous Cell Carcinoma

Ferroptosis-related genes regulating an iron- and lipid reactive oxygen species (ROS)-dependent form of programmed cell death suggest critical roles for ferroptosis in cancers. However, the prognostic value of ferroptosis-related epigenetic features such as DNA methylation in lung squamous cell carcinoma (LUSC) needs to be studied. Ferroptosis-related genes are collected from the FerrDb database, and the methylation data of these related genes in LUSC methylation data downloaded from the TCGA are retrieved. The DNA methylation data (362 LUSC samples) were analyzed to screen prognostic ferroptosis-related methylation sites. After patients with complete overall survival (OS) information were randomly separated into training cohort (n = 200) and validation cohort (n = 162), the least absolute shrinkage and selection operator (LASSO) and the Cox regression were used to establish and validate the prognostic signature. The time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses, Harrell's concordance index (C-index), calibration analysis, and decision curve analysis (DCA) were performed to evaluate the risk signature and related nomogram. A series of other bioinformatics approaches such as mexpress, cbioportal, maftools, string, metascape, TIMER, and Kaplan–Meier survival curve analysis were also used to determine the methylation, mutation status, protein interaction network or functional enrichment, effects on immune cell infiltration, or expression level prognosis of those signature-related genes. A total of 137 DNA methylation sites were identified as prognostic predictors corresponding to 109 ferroptosis-related genes (FRGs). The methylation signature containing 31 methylation sites proved to be superior predictive efficiency in predicting the 1-, 3-, 5-, and 10-year OS. 8 out of 28 signature-related genes were significantly related to OS time or OS state in patients with LUSC. In addition, DUSP1, ZFN36, and ALOX5 methylation status also correlated with pathological M and ALOX5 methylation correlated with pathological N. The prognostic prediction efficiency of T, N, M, and the stage was inferior to that of the DNA methylation signature. LUSC patients in the high-risk group own a significantly larger number of variants of FRGs than those in the low-risk group. In addition, negative or positive correlation patterns were presented among the different infiltrating immune cells with risk scores or signature-related genes in patients with LUSC. The expression level of 15 signature-related genes showed a significant relationship with OS of LUSC patients. A novel prognostic nomogram survival model containing 4 factors including age, pathologic T, stage, and risk group was constructed and validated, AndC-index, decision curve analysis (DCA), and calibration analysis demonstrated its excellent predictive performance. The FRG DNA methylation data-based prognostic model acts as a powerful prognostic prediction indicator in LUSC patients and is advantageous over the traditional model based on T, N, M, and stage.

Glycosylation modification patterns reveal distinct tumor metabolism and immune microenvironment landscape in lower-grade gliomas

Glycosylation alterations, a key driver throughout tumorigenesis and tumor progression, could regulate the microenvironment and immune response as well as lead to harmful metabolism and cell signaling. In this study, we first comprehensively evaluated the glycosylation modification patterns of LGGs based on glycosyltransferase family genes and systematically integrated these modification patterns with tumor metabolism and immune microenvironment characteristics. Glycosylation score was also developed to quantify glycosylation modification patterns of individuals. As a result, two glycosylation modification patterns were identified, with distinct prognosis, metabolism, and immune microenvironment features. The glycosylation subtype A and cluster A were characterized by higher carbohydrates and amino acid metabolism activity, higher levels of infiltrating cells, and poor prognosis, whereas an opposite modification pattern was observed in glycosylation subtype B and cluster B. In addition, a high glycosylation score is closer to a microenvironment characterized by chronic inflammation, immunosuppression, and tumor promotion. Following analysis and validation, the glycosylation score was a reliable and independent prognostic index. More importantly, the glycosylation score influenced the response to immunotherapy, chemotherapy, or targeted therapy, which provided a novel insight into promoting personalized therapy in the future and may contribute to developing novel therapeutic drugs or exploring promising drug combination therapy strategies.

Cuproptosis scoring system to predict the clinical outcome and immune response in bladder cancer

Cuproptosis is a novel copper ion-dependent cell death type being regulated in cells, and this is quite different from the common cell death patterns such as apoptosis, pyroptosis, necroptosis, and ferroptosis. Interestingly, like with death patterns, cuproptosis-related genes have recently been reported to regulate the occurrence and progression of various tumors. However, in bladder cancer, the link between cuproptosis and clinical outcome, tumor microenvironment (TME) modification, and immunotherapy is unknown. To determine the role of cuprotosis in the tumor microenvironment, we systematically examined the characteristic patterns of 10 cuproptosis-related genes in bladder cancer (BLCA). By analyzing principal component data, we established a cuproptosis score to determine the degree of cuproptosis among patients. Finally, we evaluated the potential of these values in predicting BLCA prognosis and treatment responses. A comprehensive study of the mutations of cuproptosis-related genes in BLCA specimens was conducted at the genetic level, and their expression and survival patterns were evaluated using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Two cuproptosis patterns were constructed based on the transcription level of 10 cuproptosis-related genes, featuring differences in the prognosis and the infiltrating landscape of immune cells (especially T and dendritic cells) with interactions between cuproptosis and the TME. Our study further demonstrated that cuproptosis score may predict prognosis, immunophenotype sensitivity to chemotherapy, and immunotherapy response among bladder cancer patients. The development and progression of bladder cancer are likely to be influenced by cuproptosis, which may involve a diverse and complex TME. The cuproptosis pattern evaluated in our study may enhance understanding of immune infiltrations and guide more potent immunotherapy interventions.

Establishment and Validation of a Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Lower-Grade Glioma

Background

The prognosis of lower-grade glioma (LGG) is highly variable, and more accurate predictors are still needed. The aim of our study was to explore the prognostic value of ferroptosis-related long non-coding RNAs (lncRNAs) in LGG and to develop a novel risk signature for predicting survival with LGG.

Methods

We first integrated multiple datasets to screen for prognostic ferroptosis-related lncRNAs in LGG. A least absolute shrinkage and selection operator (LASSO) analysis was then utilized to develop a risk signature for prognostic prediction. Based on the results of multivariate Cox analysis, a prognostic nomogram model for LGG was constructed. Finally, functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA), immunity, and m6A correlation analyses were conducted to explore the possible mechanisms by which these ferroptosis-related lncRNAs affect survival with LGG.

Results

A total of 11 ferroptosis-related lncRNAs related to the prognosis of LGG were identified. Based on prognostic lncRNAs, a risk signature consisting of 8 lncRNAs was constructed and demonstrated good predictive performance in both the training and validation cohorts. Correlation analysis suggested that the risk signature was closely linked to clinical features. The nomogram model we constructed by combining the risk signature and clinical parameters proved to be more accurate in predicting the prognosis of LGG. In addition, there were differences in the levels of immune cell infiltration, immune-related functions, immune checkpoints, and m6A-related gene expression between the high- and low-risk groups.

Conclusion

In summary, our ferroptosis-related lncRNA signature exhibits good performance in predicting the prognosis of LGG. This study may provide useful insight into the treatment of LGG.

Identifies microtubule-binding protein CSPP1 as a novel cancer biomarker associated with ferroptosis and tumor microenvironment

Centrosome and spindle pole-associated protein (CSPP1) is a centrosome and microtubule-binding protein that plays a role in cell cycle-dependent cytoskeleton organization and cilia formation. Previous studies have suggested that CSPP1 plays a role in tumorigenesis; however, no pan-cancer analysis has been performed. This study systematically investigates the expression of CSPP1 and its potential clinical outcomes associated with diagnosis, prognosis, and therapy. CSPP1 is widely present in tissues and cells and its aberrant expression serves as a diagnostic biomarker for cancer. CSPP1 dysregulation is driven by multi-dimensional mechanisms involving genetic alterations, DNA methylation, and miRNAs. Phosphorylation of CSPP1 at specific sites may play a role in tumorigenesis. In addition, CSPP1 correlates with clinical features and outcomes in multiple cancers. Take brain low-grade gliomas (LGG) with a poor prognosis as an example, functional enrichment analysis implies that CSPP1 may play a role in ferroptosis and tumor microenvironment (TME), including regulating epithelial-mesenchymal transition, stromal response, and immune response. Further analysis confirms that CSPP1 dysregulates ferroptosis in LGG and other cancers, making it possible for ferroptosis-based drugs to be used in the treatment of these cancers. Importantly, CSPP1-associated tumors are infiltrated in different TMEs, rendering immune checkpoint blockade therapy beneficial for these cancer patients. Our study is the first to demonstrate that CSPP1 is a potential diagnostic and prognostic biomarker associated with ferroptosis and TME, providing a new target for drug therapy and immunotherapy in specific cancers.

Low expression of moonlight gene ALAD is correlated with poor prognosis in hepatocellular carcinoma

BACKGROUND

Moonlighting genes may involve in the progression of hepatocellular carcinoma (HCC), and the establishment of a prognostic signature based on moonlighting genes may help predict the prognosis of HCC patients.

METHODS

This study aimed to construct a prognostic signature based on moonlighting genes in HCC and determine whether there is a correlation with tumor microenvironment or immune responses. Then we used HCC cell lines and an HCC cDNA microarray to illuminate the role of moonlighting gene in prognosis of HCC.

RESULTS

We constructed an original prognostic signature based on eight moonlighting genes (ABCB1, S100A9, NCL, PRDX6, ALAD, YBX1, POU2F1, RPL5) with strong prognosis prediction capability. The prognostic signature may demonstrate the immune status of patients with HCC, because high-risk subgroups had significantly higher scores for regulatory T cells, dendritic cells, T follicular helper cells, macrophages, and major histocompatibility complex-I, and different expression levels of immune checkpoint molecules. Importantly, patients in the high-risk subgroup exhibited higher tumor immune dysfunction and exclusion scores, suggesting that they might be less sensitive to immunotherapy. The roles of ABCB1, S100A9, NCL, PRDX6, YBX1, and POU2F1 in HCC have been reported. However, there have been no reports on the association between ALAD and HCC. Then we used bioinformatics to confirm that ALAD expression was lower in HCC and low expression of ALAD was an indicator of poor prognosis. Moreover, we found that ALAD expression was lower in HCC cells than that in normal human hepatocytes or tumor-adjacent tissues, it was negatively correlated with the pathological grade, and low expression of ALAD was related to poor prognosis in patients with HCC.

CONCLUSION

We have successfully established a novel prognostic signature based on moonlighting genes, with a strong predictive capability for prognosis, immune status, and possible response to immunotherapy. Additionally, we have identified ALAD as a prognostic biomarker for HCC.

LncRNA PELATON, a Ferroptosis Suppressor and Prognositic Signature for GBM

PELATON is a long noncoding RNA also known as long intergenic nonprotein coding RNA 1272 (LINC01272). The known reports showed that PELATON functions as an onco-lncRNA or a suppressor lncRNA by suppressing miRNA in colorectal cancer, gastric cancer and lung cancer. In this study, we first found that PELATON, as an onco-lncRNA, alleviates the ferroptosis driven by mutant p53 and promotes mutant p53-mediated GBM proliferation. We also first confirmed that PELATON is a new ferroptosis suppressor lncRNA that functions as a ferroptosis inhibitor mainly by mutant P53 mediating the ROS ferroptosis pathway, which inhibits the production of ROS, reduces the levels of divalent iron ions, promotes the expression of SLC7A11, and inhibits the expression of ACSL4 and COX2.PELATON can inhibit the expression of p53 in p53 wild-type GBM cells and regulate the expression of BACH1 and CD44, but it has no effect on p53, BACH1 and CD44 in p53 mutant GBM cells. PELATON and p53 can form a complex through the RNA binding protein EIF4A3. Knockdown of PELATON resulted in smaller mitochondria, increased mitochondrial membrane density, and enhanced sensitivity to ferroptosis inducers to inhibit GBM cell proliferation and invasion. In addition, we established a favourite prognostic model with NCOA4 and PELATON. PELATON is a promising target for the prognosis and treatment of GBM.

Identification of co-expression hub genes for ferroptosis in kidney renal clear cell carcinoma based on weighted gene co-expression network analysis and The Cancer Genome Atlas clinical data

Renal clear cell carcinoma (KIRC) is one of the most common tumors worldwide and has a high mortality rate. Ferroptosis is a major mechanism of tumor occurrence and development, as well as important for prognosis and treatment of KIRC. Here, we conducted bioinformatics analysis to identify KIRC hub genes that target ferroptosis. By Weighted gene co-expression network analysis (WGCNA), 11 co-expression-related genes were screened out. According to Kaplan Meier's survival analysis of the data from the gene expression profile interactive analysis database, it was identified that the expression levels of two genes, PROM2 and PLIN2, are respectively related to prognosis. In conclusion, our findings indicate that PROM2 and PLIN2 may be effective new targets for the treatment and prognosis of KIRC.

Identification and Validation of a Ferroptosis-Related Signature for Predicting Prognosis and Immune Microenvironment in Papillary Renal Cell Carcinoma

Objective

We aimed to explore the prognostic patterns of ferroptosis-related genes in papillary renal cell carcinoma (PRCC) and investigate the relationship between ferroptosis-related genes and PRCC tumor immune microenvironment.

Methods

We obtained the mRNA expression and corresponding clinical data of PRCC from the public tumor cancer genome atlas database (TCGA). The PRCC patients were randomly divided into two cohort, training cohort and verification cohort, respectively. Univariate Cox regression, LASSO Cox regression, multivariate Cox regression analysis were utilized to construct ferroptosis signature for PRCC patients. And then, risk prognostic model was established and verified. The correlation of ferroptosis-related signature with survival and immune microenvironment was systematically analyzed.

Results

A 4-genes ferroptosis signature (CDKN1A, MIOX, PSAT1, and RRM2) was constructed. Multivariate Cox regression assay indicates that the risk score of ferroptosis signature was an independent prognostic indicator (HR=1.391, p<0.001). The survival curve shows that the high-risk group has a poorer prognosis than the low-risk group (p<0.001). The risk prognostic model was established based on prognostic factors of clinical-stage, hemoglobin, and risk score. The time-dependent receiver operating characteristic curve (ROC) analysis proves the predictive capacity of the ferroptosis signature, the 3 years area under the curve (AUC) is 0.890, and the 5 years AUC is 0.733. Further analysis suggested that cell cycle, pentose phosphate pathway, P53 signaling pathway were significantly enriched in the high-risk group. The significantly different fractions of dendritic cells resting, macrophage cells, and T cells follicular helper were observed in risk groups.

Conclusion

This study implicates a ferroptosis signature which has a good predict capacity of the prognosis in PRCC patients. Ferroptosis-related genes may have a key role in the process of anti-tumor and serve as therapeutic targets for PRCC.

Identification of Subtypes and a Delayed Graft Function Predictive Signature Based on Ferroptosis in Renal Ischemia-Reperfusion Injury

Renal ischemia-reperfusion injury (IRI) is an inevitable process in kidney transplantation, leading to acute kidney injury, delayed graft function (DGF), and even graft loss. Ferroptosis is an iron-dependent regulated cell death in various diseases including IRI. We aimed to identify subtypes of renal IRI and construct a robust DGF predictive signature based on ferroptosis-related genes (FRGs). A consensus clustering analysis was applied to identify ferroptosis-associated subtypes of 203 renal IRI samples in the GSE43974 dataset. The FRG-associated DGF predictive signature was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO), and its robustness was further verified in the validation set GSE37838. The present study revealed two ferroptosis-related patient clusters (pBECN1 and pNF2 cluster) in renal IRI samples based on distinct expression patterns of BECN1 and NF2 gene clusters. Cluster pBECN1 was metabolically active and closely correlated with less DGF, while pNF2 was regarded as the metabolic exhausted subtype with higher incidence of DGF. Additionally, a six-gene (ATF3, SLC2A3, CXCL2, DDIT3, and ZFP36) ferroptosis-associated signature was constructed to predict occurrence of DGF in renal IRI patients and exhibited robust efficacy in both the training and validation sets. High-risk patients tended to have more infiltration of dendritic cells, macrophages, and T cells, and they had significantly enriched chemokine-related pathway, WNT/β-catenin signaling pathway, and allograft rejection. Patients with low risks of DGF were associated with ferroptosis-related pathways such as glutathione and fatty acid metabolism pathways. In conclusion, patient stratification with distinct metabolic activities based on ferroptosis may help distinguish patients who may respond to metabolic therapeutics. Moreover, the DGF predictive signature based on FRGs may guide advanced strategies toward prevention of DGF in the early stage.

Identification and Validation of a Novel Pyroptosis-Related Gene Signature for Prognosis Prediction in Soft Tissue Sarcoma

Soft tissue sarcoma (STS) represents an uncommon and heterogenous group of malignancies, and poses substantial therapeutic challenges. Pyroptosis has been demonstrated to be related with tumor progression and prognosis. Nevertheless, no studies exist that delineated the role of pyroptosis-related genes (PRGs) in STS. In the present study, we comprehensively and systematically analyzed the gene expression profiles of PRGs in STS. The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were utilized to identify differentially expressed PRGs. In total, 34 PRGs were aberrantly expressed between STS and normal tissues. Several PRGs were validated with RT-qPCR. Consensus clustering analysis based on PRGs was conducted to divide STS patients into two clusters, and significant survival difference was observed between two distinct clusters (p = 0.019). Differentially expressed genes (DEGs) were identified between pyroptosis-related clusters. Based on the least absolute shrinkage and selection operator (LASSO) COX regression analysis, the pyroptosis-related gene signature with five key DEGs was constructed. The high pyroptosis-related risk score group of TCGA cohort was characterized by poorer prognosis (p < 0.001), with immune infiltration and function significantly decreased. For external validation, STS patients from Gene Expression Omnibus (GEO) were grouped according to the same cut-off point. The survival difference between two risk groups of GEO cohort was also significant (p < 0.001). With the combination of clinical characteristics, pyroptosis-related risk score was identified to serve as an independent prognostic factor for STS patients. In conclusion, this study provided a comprehensive overview of PRGs in STS and the potential role in prognosis, which could be an important direction for future studies.

Regulated Cell Death in Urinary Malignancies

Urinary malignancies refer to a series of malignant tumors that occur in the urinary system and mainly include kidney, bladder, and prostate cancers. Although local or systemic radiotherapy and chemotherapy, immunotherapy, castration therapy and other methods have been applied to treat these diseases, their high recurrence and metastasis rate remain problems for patients. With in-depth research on the pathogenesis of urinary malignant tumors, this work suggests that regulatory cell death (RCD) plays an important role in their occurrence and development. These RCD pathways are stimulated by various internal and external environmental factors and can induce cell death or permit cell survival under the control of various signal molecules, thereby affecting tumor progression or therapeutic efficacy. Among the previously reported RCD methods, necroptosis, pyroptosis, ferroptosis, and neutrophil extracellular traps (NETs) have attracted research attention. These modes transmit death signals through signal molecules, such as cysteine-aspartic proteases (caspase) family and tumor necrosis factor-α (TNF-α) that have a wide and profound influence on tumor proliferation or death and even change the sensitivity of tumor cells to therapy. This review discussed the effects of necroptosis, pyroptosis, ferroptosis, and NETs on kidney, bladder and prostate cancer and summarized the latest research and achievements in these fields. Future directions and possibility of improving the denouement of urinary system tumors treatment by targeting RCD therapy were also explored.