Ferroptosis-related gene signature predicts the clinical outcome in pediatric acute myeloid leukemia patients and refines the 2017 ELN classification system

Prognostic assessment value of immune escape-related genes in patients with acute myeloid leukemia

This study explores the prognostic value of immune escape-related genes in acute myeloid leukemia (AML) patients. Using TARGET_AML and GSE37642 datasets, we identified CEP55, DNAJC13, and EMC2 as significant prognostic indicators, with high transcript abundance correlating with poor outcomes. Consensus clustering divided patients into two groups, with Cluster 1 showing worse prognosis. A prognostic signature based on these genes stratified patients into high- and low-risk groups, with the high-risk group experiencing worse outcomes. The risk score was an independent prognostic factor. Functional analysis revealed that high-risk genes could promote cell cycle progression. The selected genes were strongly associated with immune cells, particularly mast cells and CD8+ T cells. This study enriches the prognostic evaluation system for AML and suggests a new therapeutic direction.

A review on trends in development and translation of omics signatures in cancer

The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift sequencing of individual tumor genome and transcriptome. The steady growth in genome, epigenome, and transcriptome datasets on a genome-wide scale has significantly increased our capability in capturing signatures that represent both the intrinsic and extrinsic biological features of tumors. These biological differences can help in precise molecular subtyping of cancer, predicting tumor progression, metastatic potential, and resistance to therapeutic agents. In this review, we summarized the current development of genomic, methylomic, transcriptomic, proteomic and metabolic signatures in the field of cancer research and highlighted their potentials in clinical applications to improve diagnosis, prognosis, and treatment decision in cancer patients.

Identification of pyroptosis subtypes and prognosis model of hepatocellular carcinoma based on pyroptosis-related genes

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis. Pyroptosis, a type of programmed cell death, regulates tumor cell development. However, the role of pyroptosis-related genes (PRGs) in HCC and their association with prognosis are unclear.

METHODS

We conducted bioinformatics analysis to identify PRGs in The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) patients. Consensus clustering classified patients into different subtypes. We used LASSO regression to established a pyroptosis subtype-related score (PSRS) related to prognosis. OncoPredict identified potential pharmaceuticals based on PSRS.

RESULTS

We found 20 HCC-related PRGs in 335 TCGA-LIHC patients. Consensus clustering classified patients into two subtypes. Subtype I had better overall survival and higher response to anti-PD1 treatment. The prognostic model involving 20 genes predicted poorer prognosis for high-PSRS group. The model was validated in two external cohorts. OncoPredict identified 65 potential pharmaceuticals based on PSRS.

CONCLUSION

Our investigation revealed a correlation between pyroptosis and HCC. We established PSRS as independent risk factors for predicting prognosis. The study paves the way for using PRGs as prognostic biomarkers and exploring personalized therapy for HCC.

Development and validation of a promising 5-gene prognostic model for pediatric acute myeloid leukemia

Risk classification in pediatric acute myeloid leukemia (P-AML) is crucial for personalizing treatments. Thus, we aimed to establish a risk-stratification tool for P-AML patients and eventually guide individual treatment. A total of 256 P-AML patients with accredited mRNA-seq data from the TARGET database were divided into training and internal validation datasets. A gene-expression-based prognostic score was constructed for overall survival (OS), by using univariate Cox analysis, LASSO regression analysis, Kaplan-Meier (K-M) survival, and multivariate Cox analysis. A P-AML-5G prognostic score bioinformatically derived from expression levels of 5 genes (ZNF775, RNFT1, CRNDE, COL23A1, and TTC38), clustered P-AML patients in training dataset into high-risk group (above optimal cut-off) with shorter OS, and low-risk group (below optimal cut-off) with longer OS (p < 0.0001). Meanwhile, similar results were obtained in internal validation dataset (p = 0.005), combination dataset (p < 0.001), two treatment sub-groups (p < 0.05), intermediate-risk group defined with the Children's Oncology Group (COG) (p < 0.05) and an external Japanese P-AML dataset (p = 0.005). The model was further validated in the COG study AAML1031(p = 0.001), and based on transcriptomic analysis of 943 pediatric patients and 70 normal bone marrow samples from this dataset, two genes in the model demonstrated significant differential expression between the groups [all log2(foldchange) > 3, p < 0.001]. Independent of other prognostic factors, the P-AML-5G groups presented the highest concordance-index values in training dataset, chemo-therapy only treatment subgroups of the training and internal validation datasets, and whole genome-sequencing subgroup of the combined dataset, outperforming two Children's Oncology Group (COG) risk stratification systems, 2022 European LeukemiaNet (ELN) risk classification tool and two leukemic stem cell expression-based models. The 5-gene prognostic model generated by a single assay can further refine the current COG risk stratification system that relies on numerous tests and may have the potential for the risk judgment and identification of the high-risk pediatric AML patients receiving chemo-therapy only treatment.

Potential applications of ferroptosis inducers and regulatory molecules in hematological malignancy therapy

Ferroptosis, a novel form of iron-dependent cell death, has emerged as a potential avenue for promoting tumor cell death by causing cell membrane rupture and the accumulation of lipid peroxides (LPO) in the cell. Since its discovery in 2012, extensive research has been conducted to explore the mechanism of ferroptosis inducers, including erastin, sulfasalazine, and sorafenib. These compounds inhibit system XC-, while Ras-selective lethal small molecule 3 (RSL3) and FION2 specifically target GPX4 to promote ferroptosis. Therefore, targeting ferroptosis presents a promising therapeutic approach for malignant tumors. While the study of ferroptosis in solid tumors has made significant progress, there is limited information available on its role in hematological tumors. This review aims to summarize the molecular mechanisms of ferroptosis inducers and discuss their clinical applications in hematological malignancies. Furthermore, the identification of non-coding RNAs (ncRNAs) and genes that regulate key molecules in the ferroptosis pathway could provide new targets and establish a molecular theoretical foundation for exploring novel ferroptosis inducers in hematological malignancies.

A prognostic model based on prognosis-related ferroptosis genes for patients with acute myeloid leukemia

Background: Acute myeloid leukemia (AML) is a heterogeneous disorder with an unpredictable prognosis. Ferroptosis, the iron-dependent cell death program, could serve as an alternative for overcoming drug resistance. However, its effect on AML remains largely unclear. Methods: We collected RNA sequencing data and relevant clinical information of AML patients from The Cancer Genome Atlas to construct a prognosis prediction model. Risk score was calculated with eight prognosis-related ferroptosis genes (PRFGs) discovered through univariate analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. A nomogram was constructed by incorporating LASSO risk score, age, and cytogenetic risk based on univariate/multivariate Cox regression. Results: Of the 33 AML PRFGs identified from the TCGA-derived dataset, 8 genes were used to construct a gene signature to predict AML prognosis. Principal component analysis and heatmap showed significant differences between the low and high risk score groups. Next, LASSO risk score, age, and cytogenetic risk were incorporated into the nomogram to predict the overall survival (OS) of AML patients. According to survival analysis, patients with a low risk score had markedly increased OS as compared to those with a high risk score. Based on the results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, the differences between the two risk groups showed a close relationship with immune-related pathways and membrane transportation. The analysis of tumor-infiltrating immune cells and immune checkpoints revealed that the immunosuppressive tumor microenvironment possibly facilitated different prognostic outcomes between the two groups. Gene expression analyses showed that the mRNA expression levels of PARP1 and PARP3 (PARPs) were closely related to the different clinical subgroups and the analyzed OS in AML patients. Finally, the PARP inhibitor talazoparib and the ferroptosis inducer erastin exerted a synergistic anti-proliferative effect on AML cells. Conclusion: We constructed a nomogram by incorporating PRFGs, and the constructed nomogram showed a good performance in AML patient stratification and prognosis prediction. The combination of PARP inhibitors with ferroptosis inducers could be a novel treatment strategy for treating AML patients.

A novel immune-related prognostic model with surgical status to predict tumor immune cell infiltration and drug sensitivity in head and neck squamous cell carcinoma

Tumor-infiltrating immune cells (TICs) affect tumorigenesis and tumor development in head and neck squamous cell carcinoma (HNSCC). We constructed a novel predictive model for HNSCC based on immune-related genes (IRGs) from The Cancer Genome Atlas and the Immunology Database and Analysis Portal. After identifying the IRGs, a predictive model involving 13 IRGs with high stratification value of overall survival (OS) was constructed by multiple support vector machine recursive feature elimination and least absolute shrinkage and selection operator regression. We explored the relationship between the risk score (RS) and clinical characteristics. The nomogram showed high concordance and good agreement in OS. Four TICs affected the OS and were in agreement with the abundance analysis of the RS levels. Furthermore, the low-risk HNSCC group showed higher expression of PD-1, CTLA4, and TIGIT, while the high-risk group showed higher expression of EGFR. The high-risk HNSCC showed high sensitivity to eight drugs.

Noncoding RNAs in cancer ferroptosis: From biology to clinical opportunity

Ferroptosis is a recently discovered pattern of programmed cell death that is nonapoptotic and irondependent. It is involved in lipid peroxidation dependent on reactive oxygen species. Ferroptosis has been verified to play a crucial regulatory role in a variety of pathological courses of disease, in particularly cancer. Emerging research has highlighted the potential of ferroptosis in tumorigenesis, cancer development and resistance to chemotherapy. However, the regulatory mechanism of ferroptosis remains unclear, which limits the application of ferroptosis in cancer treatment. Noncoding RNAs (ncRNAs) are noncoding transcripts that regulate gene expression in various ways to affect the malignant phenotypes of cancer cells. At present, the biological function and underlying regulatory mechanism of ncRNAs in cancer ferroptosis have been partially elucidated. Herein, we summarize the current knowledge of the central regulatory network of ferroptosis, with a focus on the regulatory functions of ncRNAs in cancer ferroptosis. The clinical application and prospects of ferroptosis-related ncRNAs in cancer diagnosis, prognosis and anticancer therapies are also discussed. Elucidating the function and mechanism of ncRNAs in ferroptosis, along with assessing the clinical significance of ferroptosis-related ncRNAs, provides new perspectives for understanding cancer biology and treatment approaches, which may benefit numerous cancer patients in the future.

Basic mechanisms and novel potential therapeutic targets for ferroptosis in acute myeloid leukemia

Ferroptosis is a form of cell death that is regulated by iron and characterized by the buildup of lipid peroxides (LPO) and subsequent rupture of the cell membrane. The molecular mechanisms of ferroptosis involve metabolic pathways related to iron, lipids, and amino acids, which contribute to the production of lipid reactive oxygen species (ROS). In recent years, there has been increasing attention on the occurrence of ferroptosis in various diseases. Ferroptosis has been found to play a crucial role in cardiovascular diseases, digestive diseases, respiratory and immunological diseases, and particularly in malignancies. However, there is still a lack of studies on ferroptosis in acute myeloid leukemia (AML). This paper provides a comprehensive review of the mechanism of ferroptosis and its regulatory molecules and therapeutic agents in AML. It also evaluates the relationship between ferroptosis-related genes (FRGs), non-coding RNAs (ncRNAs), and prognosis to develop prognostic molecular models in AML. The study also explores the association between ferroptosis and immune infiltration in AML, to identify novel potential target regimens for AML.

Molecular Mechanisms of Ferroptosis and Updates of Ferroptosis Studies in Cancers and Leukemia

Ferroptosis is a mode of cell death regulated by iron-dependent lipid peroxidation. Growing evidence suggests ferroptosis induction as a novel anti-cancer modality that could potentially overcome therapy resistance in cancers. The molecular mechanisms involved in the regulation of ferroptosis are complex and highly dependent on context. Therefore, a comprehensive understanding of its execution and protection machinery in each tumor type is necessary for the implementation of this unique cell death mode to target individual cancers. Since most of the current evidence for ferroptosis regulation mechanisms is based on solid cancer studies, the knowledge of ferroptosis with regard to leukemia is largely lacking. In this review, we summarize the current understanding of ferroptosis-regulating mechanisms with respect to the metabolism of phospholipids and iron as well as major anti-oxidative pathways that protect cells from ferroptosis. We also highlight the diverse impact of p53, a master regulator of cell death and cellular metabolic processes, on the regulation of ferroptosis. Lastly, we discuss recent ferroptosis studies in leukemia and provide a future perspective for the development of promising anti-leukemia therapies implementing ferroptosis induction.