Immunological and prognostic significance of novel ferroptosis-related genes in soft tissue sarcoma

Zhao, Jiazheng; Zhao, Yi; Ma, Xiaowei; Feng, Helin; Cui, Rongmin

doi:10.1371/journal.pone.0262234

Cited by 3 publications

(5 citation statements)

References 48 publications

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“…It should be noted that the role of CENPA in ferroptosis has been rarely reported. However, STMN1 has been reported to as an important ferrGene in coronary artery disease, 45 soft tissue sarcoma, 46 adrenocortical carcinoma. 47 Similarly, the research of Wang et al 48 exhibited that STMN1 was a ferrGene that correlated to the poor survival of HCC.…”

Section: Discussionmentioning

confidence: 99%

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Liang¹,

Luo²,

Wang³

et al. 2023

J Clin Transl Hepatol

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Background and Aims The growing knowledge of ferroptosis has suggested the regulatory role of ferroptosis in hepatocellular carcinoma (HCC), but the pertinent molecular mechanisms remain unclear. Herein, this study investigated the mechanistic basis of ferroptosis-related genes (ferrGenes) in the growth of HCC. Methods Differentially expressed human ferrGenes and tumor-related transcription factors (TFs) were obtained from the The Cancer Genome Atlas (TCGA) dataset and the GTEx dataset. Spearman method-based correlation analysis were conducted to construct TF-ferrGene coexpression regulatory network. Key genes associated with prognosis were singled out with Lasso regression and multivariate Cox analysis to construct the prognostic risk model. Then the accuracy and independent prognostic ability of the model were evaluated. Expression of CENPA and STMN1 was determined in clinical HCC tissues and HCC cells, and their binding was analyzed with dual-luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, ectopic expression and knockdown assays were performed in HCC cells to assess the effect of CENPA and STMN1 on ferroptosis and malignant phenotypes. Results The prognostic risk model constructed based on the eight TF-ferrGene regulatory network-related genes accurately predicted the prognosis of HCC patients. It was strongly related to the clinical characteristics of HCC patients. Moreover, CENPA/STMN1 might be a key TF-ferrGene regulatory network in ferroptosis of HCC. CENPA and STMN1 were overexpressed in HCC tissues and cells. Additionally, CENPA facilitated STMN1 transcription by binding to STMN1 promoter, thus facilitating the malignant phenotypes and suppressing the ferroptosis of HCC cells. Conclusions Taken together, CENPA curbs the ferroptosis of HCC cells by upregulating STMN1 transcription, thereby promoting HCC growth.

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Section: Discussionmentioning

confidence: 99%

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Liang¹,

Luo²,

Wang³

et al. 2023

J Clin Transl Hepatol

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“…For example, ferroptosis, a novel iron-dependent lipid peroxidation induced RCD, was recently identified and found to be greatly involved in tumorigenesis (41). Evaluation of the prognostic value of ferroptosis-related genes has been widely performed in various tumors, such as pancreatic cancer, bladder cancer, colon cancer, hepatocellular carcinoma, glioblastoma, soft tissue sarcoma, thyroid papillary carcinoma, gastric cancer, ovarian cancer and so on (42)(43)(44)(45)(46)(47)(48)(49)(50). Associations between ferroptosis-related genes and TME have also been investigated in multiple cancers, including breast cancer, hepatocellular carcinoma, clear cell renal cell carcinoma, lung adenocarcinoma, head and neck squamous cell carcinoma, melanoma, papillary thyroid carcinoma and so on (51-57).…”

Section: Discussionmentioning

confidence: 99%

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

et al. 2022

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IntroductionCuproptosis is a novel identified regulated cell death (RCD), which is correlated with the development, treatment response and prognosis of cancer. However, the potential role of cuproptosis-related genes (CRGs) in the tumor microenvironment (TME) of gastric cancer (GC) remains unknown.MethodsTranscriptome profiling, somatic mutation, somatic copy number alteration and clinical data of GC samples were downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database to describe the alterations of CRGs from genetic and transcriptional fields. Differential, survival and univariate cox regression analyses of CRGs were carried out to investigate the role of CRGs in GC. Cuproptosis molecular subtypes were identified by using consensus unsupervised clustering analysis based on the expression profiles of CRGs, and further analyzed by GO and KEGG gene set variation analyses (GSVA). Genes in distinct molecular subtypes were also analyzed by GO and KEGG gene enrichment analyses (GSEA). Differentially expressed genes (DEGs) were screened out from distinct molecular subtypes and further analyzed by GO enrichment analysis and univariate cox regression analysis. Consensus clustering analysis of prognostic DEGs was performed to identify genomic subtypes. Next, patients were randomly categorized into the training and testing group at a ratio of 1:1. CRG Risk scoring system was constructed through logistic least absolute shrinkage and selection operator (LASSO) cox regression analysis, univariate and multivariate cox analyses in the training group and validated in the testing and combined groups. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to evaluate the expression of key Risk scoring genes. Sensitivity and specificity of Risk scoring system were examined by using receiver operating characteristic (ROC) curves. pRRophetic package in R was used to investigate the therapeutic effects of drugs in high- and low- risk score group. Finally, the nomogram scoring system was developed to predict patients’ survival through incorporating the clinicopathological features and CRG Risk score.ResultsMost CRGs were up-regulated in tumor tissues and showed a relatively high mutation frequency. Survival and univariate cox regression analysis revealed that LIAS and FDX1 were significantly associated with GC patients’ survival. After consensus unsupervised clustering analysis, GC patients were classified into two cuproptosis molecular subtypes, which were significantly associated with clinical features (gender, age, grade and TNM stage), prognosis, metabolic related pathways and immune cell infiltration in TME of GC. GO enrichment analyses of 84 DEGs, obtained from distinct molecular subtypes, revealed that DEGs primarily enriched in the regulation of metabolism and intracellular/extracellular structure in GC. Univariate cox regression analysis of 84 DEGs further screened out 32 prognostic DEGs. According to the expression profiles of 32 prognostic DEGs, patients were re-classified into two gene subtypes, which were significantly associated with patients’ age, grade, T and N stage, and survival of patients. Nest, the Risk score system was constructed with moderate sensitivity and specificity. A high CRG Risk score, characterized by decreased microsatellite instability-high (MSI-H), tumor mutation burden (TMB) and cancer stem cell (CSC) index, and high stromal and immune score in TME, indicated poor survival. Four of five key Risk scoring genes expression were dysregulated in tumor compared with normal samples. Moreover, CRG Risk score was greatly related with sensitivity of multiple drugs. Finally, we established a highly accurate nomogram for promoting the clinical applicability of the CRG Risk scoring system.DiscussionOur comprehensive analysis of CRGs in GC demonstrated their potential roles in TME, clinicopathological features, and prognosis. These findings may improve our understanding of CRGs in GC and provide new perceptions for doctors to predict prognosis and develop more effective and personalized therapy strategies.

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“…GO and KEGG enrichment analyses have uncovered that FRGs are significantly enriched in pathways related to cancer and the immune system. Correlation analyses of key FRGs with immune checkpoint genes (ICGs) have revealed positive associations between the expression levels of CXCL2 and IL6, which are proteins encoded by FRGs, and the expression of immune factors [ 235 ]. RIPK1, a key FRG, has also been shown to be part of the same protein interaction network as immune checkpoints like PD-1 [ 239 ].…”

Section: Progress Of Research On Ferroptosis In Sarcoma Treatmentmentioning

confidence: 99%

“…RIPK1, a key FRG, has also been shown to be part of the same protein interaction network as immune checkpoints like PD-1 [ 239 ]. Furthermore, prognostic analyses based on FRGs have demonstrated that different risk groups exhibit varying patterns of immune cell infiltration, and individuals with more active immune cell involvement tend to have a better prognosis [ 9 , 235 , 237 ]. These findings suggest that FRG-encoded proteins can influence tumor prognosis by modulating the immune system, and further support the relationship between ferroptosis and tumor immune system.…”

Section: Progress Of Research On Ferroptosis In Sarcoma Treatmentmentioning

confidence: 99%

“…Lastly, it’s worth noting that FRGs hold promise in predicting sarcoma prognosis and refining clinical staging, providing a direction for the future research of molecular targeted therapy of sarcoma [ 9 , 235 ]. However, the lack of research on FRGs, the data set from retrospective study and the limited clinical variable data have affected the accuracy and practicability of this technology.…”

Section: Challenges and Prospectsmentioning

confidence: 99%

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Harnessing ferroptosis for enhanced sarcoma treatment: mechanisms, progress and prospects

Zeng,

Zhang,

Lin

et al. 2024

Exp Hematol Oncol

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Sarcoma is a malignant tumor that originates from mesenchymal tissue. The common treatment for sarcoma is surgery supplemented with radiotherapy and chemotherapy. However, patients have a 5-year survival rate of only approximately 60%, and sarcoma cells are highly resistant to chemotherapy. Ferroptosis is an iron-dependent nonapoptotic type of regulated programmed cell death that is closely related to the pathophysiological processes underlying tumorigenesis, neurological diseases and other conditions. Moreover, ferroptosis is mediated via multiple regulatory pathways that may be targets for disease therapy. Recent studies have shown that the induction of ferroptosis is an effective way to kill sarcoma cells and reduce their resistance to chemotherapeutic drugs. Moreover, ferroptosis-related genes are related to the immune system, and their expression can be used to predict sarcoma prognosis. In this review, we describe the molecular mechanism underlying ferroptosis in detail, systematically summarize recent research progress with respect to ferroptosis application as a sarcoma treatment in various contexts, and point out gaps in the theoretical research on ferroptosis, challenges to its clinical application, potential resolutions of these challenges to promote ferroptosis as an efficient, reliable and novel method of clinical sarcoma treatment.

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Immunological and prognostic significance of novel ferroptosis-related genes in soft tissue sarcoma

Cited by 3 publications

References 48 publications

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

Identification of cuproptosis-related subtypes, construction of a prognosis model, and tumor microenvironment landscape in gastric cancer

Harnessing ferroptosis for enhanced sarcoma treatment: mechanisms, progress and prospects

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