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Identification of the seven-candidate radiosensitivity-and ferroptosis-associated genes in TCGA. (A) Intersection of the DEGs and the prognostic genes for radiosensitivity and ferroptosis is shown in the veen diagram. (B) Five genes were upregulated, while two genes were downregulated in glioma tissues. (C) Interactions among the seven candidate genes are shown in the PPI network. (D) The red and blue lines represent positive and negative correlations, respectively.
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Background: Gliomas are the most refractory intracranial disease characterized by high incidence and mortality rates. Therefore, radiotherapy plays a crucial role in the treatment of gliomas. However, recent evidence reveals that ferroptosis is highly associated with radiosensitivity in tumor cells. Therefore, this study aimed to investigate radios...
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Context 2
... of the radiosensitivity-and ferroptosis-associated DEGs with OS revealed 36 radiosensitivity-and 19 ferroptosis-associated DEGs with prognostic value (Supplementary Table 4 and Supplementary Table 5). Of these, seven were overlapping genes ( Figure 1A). Moreover, ZEB1, CA9, HSPB1, STAT3 and TNFAIP3 of the overlapping genes were upregulated in glioma tissues ( Figure 1B). ...
Context 3
... these, seven were overlapping genes ( Figure 1A). Moreover, ZEB1, CA9, HSPB1, STAT3 and TNFAIP3 of the overlapping genes were upregulated in glioma tissues ( Figure 1B). The protein-protein interaction (PPI) network revealed that STAT3 was the hub gene ( Figure 1C). ...
Context 4
... ZEB1, CA9, HSPB1, STAT3 and TNFAIP3 of the overlapping genes were upregulated in glioma tissues ( Figure 1B). The protein-protein interaction (PPI) network revealed that STAT3 was the hub gene ( Figure 1C). The correlation of the overlapping genes is presented in Figure 1D. ...
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Purpose
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Citations
... Though effective, the combination is not curative and the identification of radiosensitive-associated biomarkers is an urgent need for predicting prognosis and therapy outcome. In the study by Xie et al. (2022), expression profiles of genes involved in radiation response and ferroptosis-associated pathways of GBM patients and healthy subjects from The Cancer Genome Atlas (TCGA) database are analyzed. Among the differentially expressed genes (DEGs) intersecting the two pathways, seven genes (MAPK1, ZEB1, MAP1LC3A, HSPB1, CA9, STAT3, and TNFAIP3) overlap and the analysis of the protein-protein interaction network indicates STAT3 as the hub gene. ...
Ferroptosis is a regulated cell death mechanism controlled by iron, amino acid and reactive oxygen species metabolisms, which is very relevant for cancer therapy. Radiotherapy-induced ferroptosis is critical for tumor suppression and several preclinical studies have demonstrated that the combination of ionizing radiation with small molecules or nano-systems is effective in combating cancer growth and overcoming drug or ionizing radiation resistance. Here, we briefly overview the mechanisms of ferroptosis and the cross-talk existing between the cellular pathways activated by ferroptosis and those induced by radiotherapy. Lastly, we discuss the recently reported combinational studies involving radiotherapy, small molecules as well as nano-systems and report the recent findings achieved in this field for the treatment of tumors.
... 33 A novel risk signature containing ferroptosis-associated HSPB1 has been established and could be used to predict the survival time and radiosensitivity in glioma patients. 43 Here, we demonstrated the up-regulated HSPB1 expression in glioma tissues. The glioma patients with high ...
Background
As a new type of regulatory cell death, ferroptosis has been proven to be involved in cancer pathogenesis and therapeutic response. However, the detailed roles of ferroptosis or ferroptosis‐associated genes in glioma remain to be clarified.
Methods
Here, we performed the TMT/iTRAQ‐Based Quantitative Proteomic Approach to identify the differentially expressed proteins between glioma specimens and adjacent tissues. Kaplan–Meier survival was used to estimate the survival values. We also explored the regulatory roles of abnormally expressed formin homology 2 domain‐containing protein 1 (FHOD1) in glioma ferroptosis sensitivity.
Results
In our study, FHOD1 was identified to be the most significantly upregulated protein in glioma tissues. Multiple glioma datasets revealed that the glioma patients with low FHOD1 expression displayed favorable survival time. Functional analysis proved that the knockdown of FHOD1 inhibited cell growth and improved the cellular sensitivity to ferroptosis in glioma cells T98G and U251. Mechanically, we found the up‐regulation and hypomethylation of HSPB1, a negative regulator of ferroptosis, in glioma tissues. FHOD1 knockdown could enhance the ferroptosis sensitivity of glioma cells via up‐regulating the methylated heat‐shock protein B (HSPB1). Overexpression of HSPB1 significantly reversed FHOD1 knockdown‐mediated ferroptosis.
Conclusions
In summary, this study demonstrated that the FHOD1‐HSPB1 axis exerts marked regulatory effects on ferroptosis, and might affect the prognosis and therapeutic response in glioma.
... A large number of regularization regression models (e.g. LASSO regression) have been demonstrated to be effective [9][10][11][12][13][14]. Other genebased machine-learning algorithms such as random forest, partial least squares, and SVM could also successfully predict radiosensitivity and radiocurability [15,16]. ...
Background
Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a lack of emerging powerful models, artificial neural networks (ANN), in the practice of gene-based radiosensitivity prediction. In addition, ANN may overfit and learn biologically irrelevant features.
Methods
We developed a novel ANN with Selective Connection based on Gene Patterns (namely ANN-SCGP) to predict radiosensitivity and radiocurability. We creatively used gene patterns (gene similarity or gene interaction information) to control the "on–off" of the first layer of weights, enabling the low-dimensional features to learn the gene pattern information. ANN-SCGP was trained and tested in 82 cell lines and 1,101 patients from the 11 pan-cancer cohorts.
Results
For survival fraction at 2 Gy, the root mean squared errors (RMSE) of prediction in ANN-SCGP was the smallest among all algorithms (mean RMSE: 0.1587–0.1654). For radiocurability, ANN-SCGP achieved the first and second largest C-index in the 12/20 and 4/20 tests, respectively. The low dimensional output of ANN-SCGP reproduced the patterns of gene similarity. Moreover, the pan-cancer analysis indicated that immune signals and DNA damage responses were associated with radiocurability.
Conclusions
As a model including gene pattern information, ANN-SCGP had superior prediction abilities than traditional models. Our work provided novel insights into radiosensitivity and radiocurability.
... Although the sensitivity of different types of tumor cells towards ferroptosis are diverse, a combination of erastin (an inducer of ferroptosis) and chemotherapeutics could improve curative effects in various types of cancer, such as ovarian cancer (15), lung cancer (16) and breast cancer (17). Moreover, ferroptosis has been reported to be associated with the prognosis of various types of cancer, and ferroptosis-related prognostic models have been constructed in glioma (18), melanoma (19) and renal cell carcinoma (20), further indicating the potential value of FRGs as prognostic markers and therapeutic targets in human cancer. Several reports have shown that ferroptosis is strongly associated with breast cancer (21,22), indicating that ferroptosis may be considered an important biomarker in breast cancer. ...
Breast cancer is the most prevalent type of cancer among women worldwide. The heterogeneous nature of breast cancer poses a serious challenge for prognostic prediction and individualized therapies. Recently, ferroptosis, an iron‑dependent form of programmed cell death, has been reported to serve a significant role in the regulation of the biological behavior of tumors. Several studies have revealed the prognostic significance of the ferroptosis‑related gene (FRG) model; however, additional efforts are required to elucidate the details. Moreover, genes that modulate ferroptosis may be promising candidate bioindicators in cancer therapy. The present study systematically assessed the expression profiles of FRGs to reveal the relationship between FRGs and the prognostic features of patients with breast cancer based on data obtained from the Gene Expression Omnibus and Molecular Taxonomy of Breast Cancer International Consortium. Using a non‑negative matrix factorization clustering method, patients with breast cancer were classified into two sub‑groups (cluster 1 and cluster 2) based on the expression of FRGs. Furthermore, Cox regression, and least absolute shrinkage and selection operator methods were used to construct a risk score formula comprised of nine genes, which stratified patients with breast cancer into two risk groups. Patients belonging to the high‑risk group exhibited significantly shorter overall survival (OS) time compared with patients in the low‑risk group. The prognostic value of this signature was further verified in the training and validation cohorts. The results for univariate and multivariate Cox regression analyses indicated that risk score acted as an independent predictor for OS. Subsequently, a nomogram was constructed. Receiver operating characteristic analysis further confirmed that the resulting nomogram exhibited powerful discriminatory ability. Functional analysis revealed that the immune environment differed notably between the two groups and indicated an association between ferroptosis and breast cancer proliferation, migration and drug resistance. Taken together, the present study demonstrated that FRGs were significantly associated with breast cancer progression, and thus could be used as novel biomarkers for prognostic prediction and individualized treatment of patients with breast cancer.
... Furthermore, low-dose sorafenib can induce ferroptosis, but high-dose sorafenib can induce not only ferroptosis, but also other forms of programmed cell death (Peng et al., 2023). Xie et al. (2022), investigating the transcriptome data of TCGA and Chinese Glioma Genome Atlas (CGGA) database, and thus identifying 36 radiosensitivity-and 19 ferroptosis associated differentially expressed genes with a prognostic value. In results, they also revealed that the radiosensitivity-and ferroptosis-associated biomarkers, includes HSPB1, STAT3, CA9, MAP1LC3A, MAPK1, ZEB1, and TNFAIP3, with a prognostic value for gliomas patients. ...
The mechanism underlying the association between the development of head and neck squamous cell carcinoma (HNSCC) and ferroptosis is unclear. We analyzed the transcriptomes of 5902 single cells from a single-cell RNA-sequencing (scRNA-seq) dataset. They then aggregate into B cells, epithelial cells, fibroblasts, germ cells, mesenchymal cells, cancer stem cells, stem cells, T cells and endometrial cells, respectively. Our study shows that multiple pathways are significantly enriched in HNSCC development including extracellular matrix structural components, humoral immune responses, and muscle contraction. Differentially expressed genes analysis in Pseudotime analysis, pathway and biological function indicated that there was a significant correlation in the ferroptosis pathway. Furthermore, higher ferroptosis potential index (FPI) scores were significantly associated with worse overall survival prognosis in HNSCC patients. Pseudo-temporal, survival analyses and immunohistochemistry identified multiple central genes in HNSCC development, including ACSL1, SLC39A14, TFRC, and PRNP genes, and indicated associated ferroptosis. Overall, our study detected ferroptosis-related features is closely correlated with HNSCC prognosis and development, and deserved candidates suitable for immunotherapy treatment strategies determination for HNSCC patients.
... 9,[39][40][41][42] Although several molecular signatures have been used to predict glioma, they are yet to be adopted clinically for the prognostic evaluation of glioma patients. 43 Diverse and precise molecular profiling resources will be needed to provide diagnosis and prognosis predictions of glioma. GPCRs are critically involved in cell proliferation and survival and are abnormally expressed in tumour cells. ...
Objective
To undertake a comprehensive analysis of the differential expression of the G protein-coupled receptor ( GPCR) genes in order to construct a GPCR gene signature for human glioma prognosis.
Methods
This current study investigated several glioma transcriptomic datasets and identified the GPCR genes potentially associated with glioma severity.
Results
A gene signature comprising 13 GPCR genes (nine upregulated and four downregulated genes in high-grade glioma) was developed. The predictive power of the 13-gene signature was tested in two validation cohorts and a strong positive correlation (Spearman’s rank correlation test: ρ = 0.649 for the Validation1 cohort; ρ = 0.693 for the Validation2 cohort) was observed between the glioma grade and 13-gene based severity score in both cohorts. The 13-gene signature was also predictive of glioma prognosis based on Kaplan–Meier survival curve analyses and Cox proportional hazard regression analysis in four cohorts of patients with glioma.
Conclusions
Knowledge of GPCR gene expression in glioma may help researchers gain a better understanding of the pathogenesis of high-grade glioma. Further studies are needed to validate the association between these GPCR genes and glioma pathogenesis.
Tumor cell death and antitumor immune activation induced by radiotherapy are extensively well-studied. While radiotherapy is believed to mainly induce tumor cell necrosis and apoptosis, recent studies have shown that it can also induce ferroptosis, necroptosis, and pyroptosis in tumor cells. However, studies on the role of ferroptosis, necroptosis, and pyroptosis in radiotherapy and post-radiotherapy immune activation are limited. In this review, we summarize the comprehensive literature on the molecular mechanisms and more recent research progress related to radiotherapy-induced ferroptosis, necroptosis, and pyroptosis in tumor cells. Further, we discuss the role of tumor cells undergoing these types of cell death in immune activation after radiotherapy. In addition, we highlight some unresolved questions on the association of radiotherapy with ferroptosis, necroptosis, and pyroptosis. This review can improve our current understanding of the relationship between radiotherapy and different cell death pathways and provide a theoretical framework to improve the therapeutic effect of tumor radiotherapy in the future.
