Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis

Identification of molecular targets of Trigonelline for treating breast cancer through network pharmacology and bioinformatics-based prediction

Breast cancer, a highly prevalent and fatal cancer that affects the female population worldwide, stands as a significant health challenge. Despite the abundance of chemotherapy drugs, the adverse side effects associated with them have initiated an investigation into natural plant-based compounds. Trigonelline, an alkaloid found in Trigonella foenum-graecum, was previously reported for its anticancer properties by the researchers. In this present study, we have identified the molecular targets of Trigonelline in breast cancer and predicted its drug-like properties and toxicity. By analyzing breast cancer targets from databases including TTD, TCGA, Gene cards, and Trigonelline targets obtained from CTD, we identified 14 specific targets of Trigonelline in the context of breast cancer. The protein-protein interaction (PPI) network of the 14 Trigonelline targets provided insights into the complex relationships between different genes and targets. Heatmap analysis demonstrated the expression patterns of these 14 genes at the protein and RNA levels in breast cancer cells and breast tissues. Notably, four genes, namely EGF, BAX, EGFR, and MTOR, were enriched in the breast cancer pathway. At the same time, PARP1, DDIT3, BAX, and TNF were associated with the apoptosis pathway according to KEGG pathway enrichment analyses. Molecular docking studies between Trigonelline and target proteins from the Protein Data Bank (PDB) revealed favorable binding affinity. Furthermore, mutation analysis of target genes within a dataset of 1918 samples from cBioPortal revealed the absence of mutations. Remarkably, Trigonelline also exhibited binding affinity towards two mutant proteins, and based on these findings, we predicted that Trigonelline could be utilized to target breast cancer genes and their mutants through network pharmacology. Additionally, this was supported by molecular dynamic simulation studies. As our study is preliminary, further validation through in vitro and in vivo studies is essential to confirm the efficacy of Trigonelline in breast cancer treatment.

AQP4-AS1 Can Regulate the Expression of Ferroptosis-Related Regulator ALOX15 through Competitive Binding with miR-4476 in Lung Adenocarcinoma

Background  The AQP4-AS1/miR-4476-ALOX15 regulatory axis was discovered in previous studies. We aimed to investigate the regulatory mechanism of the ferroptosis-related regulator ALOX15 by AQP4-AS1 and miR-4476 in lung adenocarcinoma (LUAD) and find new targets for clinical treatment. Methods  After bioinformatics analysis, we contained one ferroptosis-related gene (FRG), namely ALOX15. MicroRNAs (miRNAs) and long noncoding RNAs were predicted by miRWalk. Furthermore, we constructed overexpressed LUAD cell lines. Real-time quantitative polymerase chain reaction and western blot were used to determine the expression of mRNA and protein, respectively. Cell Counting Kit-8 (CCK-8) and EdU assay were used to detect the cell proliferation. Double luciferase assay was used to detect the binding relationship between AQP4-AS1 and miR-4464. Results  ALOX15 was the most significantly downregulated FRG compared with normal tissues. Furthermore, protein-protein interaction network analysis indicated that the AQP4-AS1-miR-4476-ALOX15 regulatory axis might be involved in the occurrence and development of LUAD and there might be direct interaction between AQP4-AS1 and miR-4476, and miR-4476 and ALOX15. Furthermore, AQP4-AS1 and ALOX15 were significantly downregulated in the LUAD tissue and cell lines, whereas miR-4476 showed the opposite results ( p  < 0.001). AQP4-AS1 overexpression improved the ALOX15 expression in LUAD cell lines. CCK-8 and EdU assay revealed that overexpression of AQP4-AS1 and ALOX15 inhibited the LUAD cell proliferation. Double luciferase assay results indicated that there was a combination between AQP4-AS1 and miRNA-4476. In addition, we found that overexpressed AQP4-AS1 activates the ferroptosis in LUAD cell lines. Conclusions  AQP4-AS1 can regulate the expression of ALOX15 through competitive binding with miR-4476, further activate ferroptosis and inhibit the proliferation of LUAD cells.

TFAP2C/FLT3 axis reduces ferroptosis in breast cancer cells by inhibiting mitochondrial autophagy

BACKGROUND

FMS-like tyrosine kinase 3 (FLT3), a key target protein for treating acute myeloid leukemia, has recently been found to be closely related to ferroptosis in breast cancer (BC). However, the mechanism by which FLT3 regulates ferroptosis in BC remains unknown. Whether this regulatory relationship can be exploited for BC treatment needs further exploration.

METHODS

This study combined analysis from The Cancer Genome Atlas database with immunohistochemistry/quantitative reverse transcription-PCR/Western blot experiments to verify the expression of FLT3 in BC. FLT3 knockdown/overexpression plasmids were used in conjunction with mitochondrial autophagy inducers to treat BC cells, analyzing the effects of FLT3 on autophagy and ferroptosis. Key transcription factors for FLT3 were determined through predictions from the KnockTF database and dual luciferase/chromatin immunoprecipitation experiments, further analyzing the impact of this regulatory axis on autophagy and ferroptosis in BC cells.

RESULTS

FLT3 was significantly overexpressed in BC tissues and cells. Overexpression of FLT3 could inhibit autophagy and ferroptosis in BC cells, a regulation that was restored upon the addition of mitochondrial autophagy inducers. Additionally, transcription factor AP-2 gamma (TFAP2C) could mediate the transcriptional activation of FLT3, further inhibiting ferroptosis induced by mitochondrial autophagy.

CONCLUSION

The TFAP2C/FLT3 axis reduced ferroptosis in BC cells by inhibiting mitochondrial autophagy. These research findings elucidated the mechanism by which FLT3 regulated ferroptosis in BC and provided potential targets for BC treatment.

Enhanced prognostic signature for lung adenocarcinoma through integration of adjacent normal and tumor gene expressions

BACKGROUND

Cancer prognosis-related signatures have traditionally been constructed based on gene expression profiles derived from tumor or normal tissues. However, the potential benefits of incorporating gene expression profiles from both tumor and normal tissues to improve signature performance have not been explored.

METHODS

In this study, we developed three prognostic models for lung adenocarcinoma (LUAD) using gene expression profiles from tumor tissues, normal tissues, and a combination (COM) of both, sourced from The Cancer Genome Atlas (TCGA). To ensure comparability, the same workflow was followed for all three models.

RESULTS

When applied to the TCGA LUAD dataset, the tumor-derived model exhibited the best overall performance, except in calibration analysis, where the normal-derived model performed better. The COM-derived model demonstrated intermediate performance. Validation on three independent test datasets revealed that the COM-derived model showed the best performance, while the normal-derived model showed the worst. In overall survival (OS) analysis, the low-risk group defined by the COM-derived model consistently exhibited longer mean survival times. The tumor-derived model did not consistently show this trend, and the normal-derived model produced opposite results. In discrimination analysis, no significant differences were observed. The COM-derived model demonstrated good discrimination ability for short periods, while the tumor-derived model performed better for longer periods. In calibration analysis, both the COM and tumor-derived models had similar absolute prediction errors, which were better than those of the normal-derived model. However, the tumor-derived model tended to underestimate survival rates. The clinical feature analysis and validation in GSE229705 indicate that the risk score (RS) from the COM model is the most clinically significant. These results demonstrate that the COM model's RS aligns more closely with clinical data, maintaining stable performance and the strongest generalizability.

CONCLUSIONS

Overall, the COM-derived model demonstrated the best generalization ability. The superior performance of the tumor-derived model in the TCGA LUAD dataset might be due to overfitting. Our results suggest that appropriate combinations of gene expression data from tumor and normal tissues can enhance the predictive power of prognostic signatures.

Comprehensive analysis of multiple regulated cell death risk signatures in lung adenocarcinoma

Background

Regulated cell death (RCD) has considerable impact on tumor progress and sensitivity of treatment. Lung adenocarcinoma (LUAD) show a high resistance for conventional radiotherapies and chemotherapies. Currently, regulation of cancer cell death has been emerging as a new promising therapeutic avenue for LUAD patients. However, the crosstalk in each pattern RCD is unclear.

Methods

We integrated collected the hub-genes of 12 RCD subroutines and compressively analyzed these hub-genes synergistic effect in LUAD. The characters of RCD genes expression and prognosis were developed in The Cancer Genome Atlas (TCGA)-LUAD data. We developed and validated an RCD risk model based on TCGA and GSE70294 data set, respectively. Functional annotation and tumor immunotherapy based on the risk model were also investigated.

Results

28 RCD-related genes and two LUAD molecular cluster were identified. Survival analysis revealed that the prognosis in high-risk group was worser than those in low-risk group. Functional enrichment analysis indicated that the RCD risk model correlated with immune responses. Further analysis indicated that the high-risk group in RCD risk model exhibited an immunosuppressive microenvironment and a lowly immunotherapy responder ratio.

Conclusions

We present an RCD risk model which have a promising ability in predicting LUAD prognosis and immunotherapy response.

Predictive role and molecular biological function of proline-rich small repeat protein SPRR3 in the diagnosis of lung adenocarcinoma

The fascinating role of SPRR3 in various malignant tumors has prompted extensive research to unravel its expression patterns and prognostic significance. To comprehensively investigate SPRR3, we leveraged multiple datasets containing invaluable biomedical information, specifically focusing on the comparative analysis of SPRR3 gene expression levels across different cancer types. Meticulous examination of lung adenocarcinoma allowed us to delve deeper into the correlation between SPRR3 expression and its molecular biological functions. Our comprehensive analysis encompassed 33 malignant tumors, and the results unveiled significant differential expression of SPRR3 across a range of malignancies. Moreover, this aberrant expression of SPRR3 was observed to be closely associated with poorer prognosis in these malignant tumors. Notably, our investigation also unearthed a compelling link between SPRR3 and immune infiltrating cells in lung adenocarcinoma. The utilization of receiver operating characteristic (ROC) curves and survival curves in our study illustrated the immense potential of SPRR3 as a highly accurate predictor of cancer. These findings further emphasize the possibility of SPRR3 serving as a promising diagnostic and prognostic biomarker for a diverse array of cancers.

Identification of the ferroptosis-related gene signature and the associated regulation axis in lung cancer and rheumatoid arthritis

Patients with Rheumatoid arthritis (RA) have an elevated risk of lung cancer compared to the healthy population. However, there are few studies on the relationship between RA and lung adenocarcinoma (LUAD), especially the mechanisms at the genetic level. In this study, we investigated the link between RA and LUAD regarding Ferroptosis-Related Genes. The RNA-seq data of RA (GSE77298 and GSE 82107) and LUAD(GSE75037) in the Gene Expression Omnibus (GEO) database were obtained. 259 ferroptosis-related genes were obtained from the website ( http://www.zhounan.org/ferrdb/ ).The differential genes obtained from the RA and LUAD datasets were intersected with ferroptosis-related genes to obtain the ferroptosis-related differentially expressed genes (FRDEGs). Next, the mRNA-miRNA network was constructed, then Gene Set Enrichment Analysis (GSEA) for target genes were performed. The CIBERSORT algorithm was used to analyze the immune infiltration. Finally, the results were validated using external datasets (GSE89408 and GSE48780) and The Cancer Genome Atlas (TCGA) dataset. We obtained FRDEGs common to LUAD and RA: FANCD2, HELLS, RRM2, G6PD, VLDLR. These five genes play important roles in the progression of RA and LUAD. They also hold great diagnostic value for both diseases. Also, we found that LUAD and RA share common signaling pathways and similar immune mechanisms.

Targeting Nrf2/PHKG2 axis to enhance radiosensitivity in NSCLC

While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.

Ferroptosis in thyroid cancer: Potential mechanisms, effective therapeutic targets and predictive biomarker

Thyroid cancer is a prevalent endocrine malignancy whose global incidence has risen over the past several decades. Ferroptosis, a regulated form of cell death distinguished by the excessive buildup of iron-dependent lipid peroxidates, stands out from other programmed cell death pathways in terms of morphological and molecular characteristics. Increasing evidence suggests a close association between thyroid cancer and ferroptosis, that is, inducing ferroptosis effectively suppresses the proliferation of thyroid cancer cells and impede tumor advancement. Therefore, ferroptosis represents a promising therapeutic target for the clinical management of thyroid cancer in clinical settings. Alterations in ferroptosis-related genes hold potential for prognostic prediction in thyroid cancer. This review summarizes current studies on the role of ferroptosis in thyroid cancer, elucidating its mechanisms, therapeutic targets, and predictive biomarkers. The findings underscore the significance of ferroptosis in thyroid cancer and offer valuable insights into the development of innovative treatment strategies and accurate predictors for the thyroid cancer.

Cell-Cycle-related Protein Centromere Protein F Deficiency Inhibits Cervical Cancer Cell Growth by Inducing Ferroptosis Via Nrf2 Inactivation

Cervical cancer (CC) is one of the severe cancers that pose a threat to women's health and result in death. CENPF, the centromere protein F, plays a crucial role in mitosis by regulating numerous cellular processes, such as chromosome segregation during mitosis. According to bioinformatics research, CENPF serves as a master regulator that is upregulated and activated in cervical cancer. Nevertheless, the precise biological mechanism that CENPF operates in CC remains unclear. The aim of this study was to analyze the function of CENPF on cervical cancer and its mechanism. We conducted immunohistochemistry and western blot analysis to examine the expression levels of CENPF in both cervical cancer tissues and cells. To explore the hidden biological function of CENPF in cell lines derived from CC, we applied lentivirus transfection to reduce CENPF manifestation. CENPF's main role is to regulate ferroptosis which was assessed by analyzing Reactive Oxygen Species (ROS), malonaldehyde (MDA), etc. The vitro findings were further validated through a subcutaneous tumorigenic nude mouse model. Our research finding indicates that there is an apparent upregulation of CENPF in not merely tumor tissues but also cell lines in the carcinomas of the cervix. In vitro and vivo experimental investigations have demonstrated that the suppression of CENPF can impede cellular multiplication, migration, and invasion while inducing ferroptosis. The ferroptosis induced by CENPF inhibition in cervical cancer cell lines is likely mediated through the Nrf2/HO-1 pathway. The data herein come up with the opinion that CENPF may have a crucial role in influencing anti-cervical cancer effects by inducing ferroptosis via the triggering of the Nrf2/HO-1 signaling pathway.

A ferroptosis-related signature predicts the clinical diagnosis and prognosis, and associates with the immune microenvironment of lung cancer

Targeting ferroptosis-related pathway is a potential strategy for treatment of lung cancer (LC). Consequently, exploration of ferroptosis-related markers is important for treating LC. We collected LC clinical data and mRNA expression profiles from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained through FerrDB database. Expression analysis was performed to obtain differentially expressed FRGs. Diagnostic and prognostic models were constructed based on FRGs by LASSO regression, univariate, and multivariate Cox regression analysis, respectively. External verification cohorts GSE72094 and GSE157011 were used for validation. The interrelationship between prognostic risk scores based on FRGs and the tumor immune microenvironment was analyzed. Immunocytochemistry, Western blotting, and RT-qPCR detected the FRGs level. Eighteen FRGs were used for diagnostic models, 8 FRGs were used for prognostic models. The diagnostic model distinguished well between LC and normal samples in training and validation cohorts of TCGA. The prognostic models for TCGA, GSE72094, and GSE157011 cohorts significantly confirmed lower overall survival (OS) in high-risk group, which demonstrated excellent predictive properties of the survival model. Multivariate Cox regression analysis further confirmed risk score was an independent risk factor related with OS. Immunoassays revealed that in high-risk group, a significantly higher proportion of Macrophages_M0, Neutrophils, resting Natural killer cells and activated Mast cells and the level of B7H3, CD112, CD155, B7H5, and ICOSL were increased. In conclusion, diagnostic and prognostic models provided superior diagnostic and predictive power for LC and revealed a potential link between ferroptosis and TIME.

Cell Cycle-Related Centromere Protein F Deficiency Suppresses Ovarian Cancer Cell Growth by Inducing Ferroptosis

OBJECTIVES

This study aimed to investigate the involvement of the cell cycle-related protein centromere protein F (CENPF) in the development of ovarian cancer (OC) and explored its relationship with ferroptosis.

DESIGN

The databases were analysed to identify differential expression of cell cycle-related proteins between individuals with OC and normal individuals. Immunohistochemistry and statistical analysis were conducted on ovarian tissues obtained from 40 patients with epithelial OC and 20 normal individuals. In vitro experiments were performed using SKOV3 and HEY epithelial OC cell lines.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The mRNA microarray dataset, consisting of GSE14001, GSE54388, GSE40595, and GSE14407, was downloaded from the Gene Expression Omnibus (GEO) database to investigate the genes associated with cell cycle regulation in OC cells. CENPF was selected as the subject of study through differential analysis.Assessed the expression of CENPF in both OC patients and normal ovarian tissues using immunohistochemistry. Lentivirus infection was employed to downregulate CENPF expression, and subsequent experiments including Cell Counting Kit-8 assay, cell cycle analysis, transwell assay, and wound-healing assay were conducted to investigate the effects of CENPF on proliferation, invasion, migration, and cell cycle regulation in OC cells. The reactive oxygen species (ROS) and the malondialdehyde (MDA) assays were performed to assess the involvement of CENPF in cellular redox reactions. Western blot analysis was conducted to examine the expression levels of ferroptosis-related proteins (GPX4, SLC7A11, DMT1, and protein 53 [p53]).

RESULTS

By querying and integrating cell cycle-related genes from the GEO database, in silico analyses using The Cancer Genome Atlas database combined with immunohistochemical studies, we discovered that CENPF is upregulated in OC tissues and is related to survival. Downregulation of CENPF inhibited biological function of OC cells, increased intracellular ROS and MDA levels, and downregulated the GPX4 protein and the SLC7A11/xCT protein, but upregulated the DMT1 protein and the tumour p53 expression to induce ferroptosis.

LIMITATIONS

This study did not investigate ferroptosis-related studies following CENPF overexpression, and the findings have not been validated in animal studies.

CONCLUSIONS

Our findings demonstrated that the deficiency of CENPF played a crucial anti-oncogenic role in the progression of OC through the mechanism of ferroptosis.

Lipoxygenases at the Intersection of Infection and Carcinogenesis

The persisting presence of opportunistic pathogens like Pseudomonas aeruginosa poses a significant threat to many immunocompromised cancer patients with pulmonary infections. This review highlights the complexity of interactions in the host's defensive eicosanoid signaling network and its hijacking by pathogenic bacteria to their own advantage. Human lipoxygenases (ALOXs) and their mouse counterparts are integral elements of the innate immune system, mostly operating in the pro-inflammatory mode. Taking into account the indispensable role of inflammation in carcinogenesis, lipoxygenases have counteracting roles in this process. In addition to describing the structure-function of lipoxygenases in this review, we discuss their roles in such critical processes as cancer cell signaling, metastases, death of cancer and immune cells through ferroptosis, as well as the roles of ALOXs in carcinogenesis promoted by pathogenic infections. Finally, we discuss perspectives of novel oncotherapeutic approaches to harness lipoxygenase signaling in tumors.

Recent progress in biomaterials-driven ferroptosis for cancer therapy

Ferroptosis, first suggested in 2012, is a type of non-apoptotic programmed cell death caused by the buildup of lipid peroxidation and marked by an overabundance of oxidized poly unsaturated fatty acids. During the last decade, researchers have uncovered the formation of ferroptosis and created multiple drugs aimed at it, but due to poor selectivity and pharmacokinetics, clinical application has been hindered. In recent years, biomedical discoveries and developments in nanotechnology have spurred the investigation of ferroptosis nanomaterials, providing new opportunities for the ferroptosis driven tumours treatment. Additionally, hydrogels have been widely studied in ferroptosis because of their unique 3D structure and excellent controllability. By using these biomaterials, it is possible to achieve controlled release and targeted delivery of drugs, thus increasing the potency of the drugs and minimizing adverse effects. Therefore, summarizing the biomedical nanomaterials, including hydrogels, used in ferroptosis for cancer therapy is a must. This article provides an overview of ferroptosis, detailing its properties and underlying mechanisms. It also categorizes and reviews the use of various nanomaterials in ferroptosis, along with relevant explanations and illustrations. In addition, we discuss the opportunities and challenges facing the application of nanomaterials in ferroptosis. Finally, the development prospects of this field are prospected. This review is intended to provide a foundation for the development and application of biomedical nanomaterials in ferroptosis.

The prognostic and antitumor roles of key genes of ferroptosis in liver hepatocellular cancer and stomach adenocarcinoma

BACKGROUND

Liver hepatocellular cancer (LIHC) and stomach adenocarcinoma (STAD) are common malignancies with high lethal ratios worldwide. Great progress has been achieved by using diverse therapeutic strategies; however, these diseases still have an unfavourable prognosis. Ferroptosis inducer drugs, unlike apoptosis-related drugs, can overcome the resistance to cancer therapy caused by traditional chemicals. However, the relationship between overall survival (OS) and ferroptosis-related genes, as well as the mechanisms involved, are largely unclear.

METHODS

The expression levels of AIFM2, GPX4, ACSL4, FTH1, NOS1, and PTGS2 in LIHC and STAD were obtained from UALCAN. The correlations of OS with these gene expression levels were obtained using the Kaplan-Meier Plotter database. The OS associated with genetic mutations of those genes compared to that of unchanged genes was analysed using the TIMER website. GO and KEGG enrichment analyses of ferroptosis-related genes and their coexpressed genes in LIHC and STAD were conducted using the STRING and DAVID databases. The relationship of PTGS2 and ACSL4 to immune cell infiltration was analysed using the TIMER website. The viability and GPX5 expression levels in LIHC cells treated with RSL3 and As2O3 were detected by MTT methods and western blotting, respectively.

RESULTS

Our results showed that GPX4, FTH1 and AIFM2 were overexpressed in LIHC and STAD. High levels of GPX4, FTH1 and AIFM2 were prominently correlated with better prognosis in LIHC. However, GPX and FTH1 in STAD did not show significant correlations with OS. AIFM2 in STAD had the opposite trend with OS compared with that in LIHC. Moreover, a high mutation rate of these genes (35.74%) was also observed in LIHC patients, and genetic mutation of these genes was correlated with shorter OS. In contrast, the genetic mutation of these genes did not change OS in STAD. Enrichment analysis showed that the respiratory electron transport chain, cell chemotaxis and T-cell migration were related to ferroptosis. ASCL4 and PTGS2 coexpressed with cytokines associated with immune cell infiltration. Compared to RSL3 or As2O3 alone, As2O3 plus RSL3 significantly inhibited the growth of Huh7 cells. GPX4 was downregulated to an undetectable level when in combination with RSL3.

CONCLUSIONS

Our results indicated that ferroptosis-related genes might play an important role in LIHC and STAD and might be risk factors for overall survival in LIHC and STAD.

Multi-omics analysis reveals that ferroptosis-related gene CISD2 is a prognostic biomarker of head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is a prevalent malignancy, with high mortality rate and unavailability of accurate therapies. However, its early prevention remains a challenge. In the purview of predictive, preventive, and personalized medicine (PPPM), it is paramount to identify novel and powerful biomarkers. CISD2 is a crucial regulator of iron homeostasis and reactive oxygen species (ROS). Recent studies showed that the NEET protein (NAF-1) encoded by CISD2 is involved in regulating the proliferation and metastasis of tumor cells. Nevertheless, the prognostic value and immunological correlations of CISD2 remain unclear.

METHODS

Bioinformatics analyses conducted utilizing data from comprehensive databases The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). All statistical evaluations were executed employing R software.

RESULTS

Our investigation of biological function, enrichment pathway, and immune correlation revealed a discernable linkage between CISD2 and the immune response. Moreover, we found that the suppression of CISD2 is associated with immune cell infiltration and various immune signatures.

CONCLUSIONS

The present study successfully revealed the potential prognostic and biological function of CISD2 in HNSCC. High expression of CISD2 are linked to gender, race, grade, etc., can notably enhance the early detection, prognosis, and prediction for individuals afflicted with HNSCC.

Emerging roles and therapeutic potentials of ferroptosis: from the perspective of 11 human body organ systems

Since ferroptosis was first described as an iron-dependent cell death pattern in 2012, there has been increasing interest in ferroptosis research. In view of the immense potential of ferroptosis in treatment efficacy and its rapid development in recent years, it is essential to track and summarize the latest research in this field. However, few writers have been able to draw on any systematic investigation into this field based on human body organ systems. Hence, in this review, we provide a comprehensive description of the latest progress in unveiling the roles and functions, as well as the therapeutic potential of ferroptosis, in treating diseases from the aspects of 11 human body organ systems (including the nervous system, respiratory system, digestive system, urinary system, reproductive system, integumentary system, skeletal system, immune system, cardiovascular system, muscular system, and endocrine system) in the hope of providing references for further understanding the pathogenesis of related diseases and bringing an innovative train of thought for reformative clinical treatment.

Identification of a novel endocytosis‑associated gene signature for prognostic prediction in lung adenocarcinoma

Lung cancer is one of the most common malignant solid tumors and the leading cause of cancer-associated mortality worldwide. Endocytosis is an essential physiological activity for cells to maintain membrane homeostasis, and has been reported to serve an important role in tumorigenesis and progression. In the present study, the aim was to construct a prognostic prediction model of endocytosis-associated genes for patients with lung adenocarcinoma (LUAD). The endocytosis-associated gene signature was established using Lasso Cox regression analysis using the training set of the LUAD cohort from The Cancer Genome Atlas (TCGA) database, and verified using two datasets from the Gene Expression Omnibus (GEO) database. Kaplan-Meier survival curves were used to evaluate the effectiveness of the prognostic evaluation of patients with LUAD. Differentially expressed genes were screened in the tumor tissue of patients compared with paired paracancerous tissues. A series of candidate genes associated to the prognosis of patients with LUAD was obtained using univariate Cox's regression analysis. Using the Lasso Cox regression analysis, an appropriate risk model with 18 endocytosis-associated genes was established. A high-risk score was positively correlated with a higher tumor stage and pathologic grade. Patients with LUAD and high-risk scores had shorter survival times, increased intratumor heterogeneities and immune cell infiltration into tumor tissues, compared with those patients with LUAD and low-risk scores. The endocytosis inhibitor chloroquine could repress proliferation and increase the apoptosis of lung cancer cells. In summary, a novel endocytosis-associated gene signature was constructed using TCGA and GEO datasets. Patients with LUAD and high-risk scores, as calculated by the signature, had a poor prognosis and short survival time.

Identification of endoplasmic reticulum stress-related signature characterizes the tumor microenvironment and predicts prognosis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains one of the most lethal malignancies worldwide, with a high mortality rate and unfavorable prognosis. Endoplasmic reticulum (ER) stress is a key regulator of tumour growth, metastasis, and the response to chemotherapy, targeted therapies and immune response. It acts via responding to misfolded proteins and triggering abnormal activation of ER stress sensors and downstream signalling pathways. Notably, the expression patterns of ER-stress-related-genes (ERSRGs) are indicative of survival outcomes, especially in the context of immune infiltration. Through consensus clustering of prognosis-associated ERSRGs, we delineated two distinct LUAD subtypes: Cluster 1 and Cluster 2. Comprehensive analyses revealed significant disparities between these subtypes in terms of prognosis, immune cell infiltration, and tumor progression. Leveraging the robustness of LASSO regression and Multivariate stepwise regression, we constructed and validated an ER Stress-associated risk signature for LUAD. This signature underwent assessments for its prognostic value, correlation with clinical attributes, and interaction within the tumour immune microenvironment. By integrating this signature with multivariate cox analysis of distinct pathological stages, we devised an enhanced nomogram, validated through various statistical metrics, with an area under the curve for overall survival at 1, 3, and 5 years post-diagnosis being 0.79, 0.80, and 0.81, respectively. In conclusion, our findings introduce a composite signature of 11 pivotal ERSRGs, holding promise as a potent prognostic tool for LUAD, and offering insights for immunotherapeutic and targeted intervention strategies.

A robust six-gene prognostic signature based on two prognostic subtypes constructed by chromatin regulators is correlated with immunological features and therapeutic response in lung adenocarcinoma

Accumulating evidence has demonstrated that chromatin regulators (CRs) regulate immune cell infiltration and are correlated with prognoses of patients in some cancers. However, the immunological and prognostic roles of CRs in lung adenocarcinoma (LUAD) are still unclear. Here, we systematically revealed the correlations of CRs with immunological features and the survival in LUAD patients based on a cohort of gene expression datasets from the public TCGA and GEO databases and real RNA-seq data by an integrative analysis using a comprehensive bioinformatics method. Totals of 160 differentially expressed CRs (DECRs) were identified between LUAD and normal lung tissues, and two molecular prognostic subtypes (MPSs) were constructed and evaluated based on 27 prognostic DECRs using five independent datasets (p =0.016, <0.0001, =0.008, =0.00038 and =0.00055, respectively). Six differentially expressed genes (DEGs) (CENPK, ANGPTL4, CCL20, CPS1, GJB3, TPSB2) between two MPSs had the most important prognostic feature and a six-gene prognostic model was established. LUAD patients in the low-risk subgroup showed a higher overall survival (OS) rate than those in the high-risk subgroup in nine independent datasets (p <0.0001, =0.021, =0.016, =0.0099, <0.0001, =0.0045, <0.0001, =0.0038 and =0.00013, respectively). Six-gene prognostic signature had the highest concordance index of 0.673 compared with 19 reported prognostic signatures. The risk score was significantly correlated with immunological features and activities of oncogenic signaling pathways. LUAD patients in the low-risk subgroup benefited more from immunotherapy and were less sensitive to conventional chemotherapy agents. This study provides novel insights into the prognostic and immunological roles of CRs in LUAD.

Comprehensive analysis identifies DNA damage repair-related gene HCLS1 associated with good prognosis in lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-associated mortality. Lung adenocarcinoma (LUAD) amounts to more than 40% of all lung malignancies. Therefore, developing clinically useful biomarkers for this disease is critical. DNA damage repair (DDR) is a complicated signal transduction process that ensures genomic stability. DDR should be comprehensively analyzed to elucidate their clinical significance and tumor immune microenvironment interactions.

Methods

In this study, DDR-related genes (DRGs) were selected to investigate their prognostic impact on LUAD. A regression-based prognostic model was established based on The Cancer Genome Atlas (TCGA)-LUAD cohort and three external Gene Expression Omnibus (GEO) validation cohorts (GSE31210, GSE68465, and GSE72094). The robust, established model could independently predict the clinical outcomes in patients. Then, the prognostic performance of risk profiles was assessed using a time-dependent receiver operating characteristic (ROC) curve, Cox regression, nomogram, and Kaplan-Meier analyses. Furthermore, the potential biological functions and infiltration status of DRGs in LUAD were investigated with ESTIMATE and CIBERSORT. Finally, the effects of HCLS1 on the clinical features, prognosis, biological function, immune infiltration, and treatment response in LUAD were systematically analyzed.

Results

Eleven DRGs were constructed to categorize patients into high- and low-risk groups. The risk score was an independent predictor of overall survival (OS). HCLS1 expression was downregulated in LUAD samples and linked with clinicopathological features. Multivariate Cox regression analysis using the Kaplan-Meier plotter revealed that low HCLS1 expression was independently associated with poor OS. Moreover, the HCLS1 high-expression group had higher immune-related gene expression and ESTIMATE scores. It was positively correlated with the infiltration of M1 macrophages, activated memory CD4 T cells, CD8 T cells, memory B cells, resting dendritic cells, and memory CD4 T cells, Tregs, and neutrophils.

Conclusions

A new classification system was developed for LUAD according to DDR characteristics. This stratification has important clinical values, reliable prognosis, and immunotherapy in patients with LUAD. Moreover, HCLS1 is a potential prognostic biomarker of LUAD that correlates with the extent of immune cell infiltration in the tumor microenvironment (TME).

CENPA-driven STMN1 Transcription Inhibits Ferroptosis in Hepatocellular Carcinoma

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.

Knockdown of BAP31 Downregulates Galectin-3 to Inhibit the Wnt/β-Catenin Signaling Pathway to Modulate 5-FU Chemosensitivity and Cancer Stemness in Colorectal Cancer

Increased stemness is causally linked to the development of chemoresistance in cancers. B-cell receptor-associated protein 31 (BAP31) has been identified to play an oncogenic role in many types of cancer. However, the role of BAP31 in 5-fluorouracil (5-FU) chemosensitivity and stemness of colorectal cancer (CRC) is still unknown. The aim of this study was to investigate the biological function and molecular mechanism of BAP31 in regulating 5-FU chemosensitivity and stemness. The correlation between BAP31 expression and 5-FU chemosensitivity was examined using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide and colony formation assays. Cancer stemness was analyzed using tumor sphere formation and Western blot assays. Western blot and immunofluorescence analyses of the knockdown cell lines were performed to explore the possible mechanisms. Finally, we investigated the function of BAP31 by constructing xenograft nude mouse models in vivo. In this study, we demonstrated that BAP31 was increased in CRC cells, and knockdown of BAP31 reduced the half maximal inhibitory concentration (IC50) of 5-FU, while this effect was reversed by overexpression of BAP31. In addition, knockdown of BAP31 substantially reduced the stemness of CRC cells in vitro. Consistently, knockdown of BAP31 significantly suppressed the tumorigenicity and stemness of CRC in vivo. The functional study further suggested that knockdown of BAP31 downregulated galectin-3 to inhibit the accumulation of β-catenin, which in turn repressed the transcription of downstream target genes (c-MYC, SOX2) of the Wnt/β-catenin signaling pathway. Knockdown of BAP31 reduced stemness by inhibiting the Wnt/β-catenin signaling pathway to increase 5-FU chemosensitivity. Importantly, intrabodies against BAP31 suppressed tumor growth and enhanced the antitumor effects of 5-FU in vivo. Therefore, using intrabodies against BAP31 may be a strategy for improving the antitumor effect of 5-FU in CRC.

STARD12/14 are diagnostic and prognostic biomarkers of lung adenocarcinoma associated with epigenetic regulation, immune infiltration and ferroptosis

Background: Metabolic reprogramming plays an important role in tumor progression and antitumor immunity. START domain-containing proteins (STARDs) are responsible for lipid metabolism. However, the underlying functions of STARDs in lung adenocarcinoma (LUAD) have not been clarified yet. Methods: Oncomine, UALCAN, TCGA and CPTAC were used to explore the expression landscape and clinicopathological characteristics of STARDs in LUAD. Diagnostic and prognostic values were assessed by Kaplan-Meier Plotter, Cox regression analysis, and ROC curve. GeneMANIA, GO, KEGG and GSEA were applied for exploring the potential biological functions. Epigenetic process, including mutation and m6A modification were analyzed by cBioPortal and TCGA. TIMER, TISIDB and TCGA cohort provided an immune signature. The correlation between STARDs expression and ferroptosis was analyzed by TCGA. Finally, the STARDs expression were confirmed by RT-qPCR and western blot. Results: STARD5/10/14 were overexpressed in LUAD compared with normal, while STARD4/7/8/11/12/13 were relatively low. STARD5/12/14 levels were positively related to clinical and lymph node stage. Survival analysis showed high STARD12 expression was associated with favorable overall survival, disease special survival as well as disease free survival, while STARD14 showed the opposite. GSEA analysis found STARD12 and STARD14 were associated with glycolysis, oxidative phosphorylation and tumor related signaling pathways. STARD12 co-expressed genes participated in cell cycle and DNA replication, and STARD14 were enriched in ECM-receptor interaction. Both STARD12 and STARD14 were corelated with epigenetic regulation, especially TP53 mutation and m6A modification. STARD12 expression was positively correlated with TMB level. The level of STARD12 was significantly associated with the abundance of infiltrating immune cells, including B cells, CD8+T cells, macrophages, dendritic cells, and chemokine, receptor, MHC, immunostimulatory related genes. STARD14 was negatively associated with the infiltration of CD8+T cells, while positively with CCL28 and immune checkpoints, including CTLA4 as well as PD-L2. In addition, STARD12/14 could regulate the ferroptosis related genes. Conclusion: STARD12 and STARD14 were expected to be potential biomarkers for LUAD, which were associated with epigenetic regulation, immune infiltration and ferroptosis.

LPCAT3 Is Transcriptionally Regulated by YAP/ZEB/EP300 and Collaborates with ACSL4 and YAP to Determine Ferroptosis Sensitivity

Aims: Lipid peroxidation occurring in lung adenocarcinoma (LUAD) cells leads to ferroptosis. Lysophosphatidylcholine acyl-transferase 3 (LPCAT3) plays a key role in providing raw materials for lipid peroxidation by promoting esterification of polyunsaturated fatty acids to phospholipids. Whether LPCAT3 determines ferroptosis sensitivity and the mechanism by which its expression is regulated in LUAD has not been reported. Results: LPCAT3 and acyl-coenzyme A (CoA) synthetase long-chain family member (ACSL)4 levels were positively associated with ferroptosis sensitivity in LUAD cell lines. Overexpression of LPCAT3 and ACSL4 sensitized LUAD cells to ferroptosis, while LPCAT3 and ACSL4 knockout showed the opposite effect. Zinc-finger E-box-binding (ZEB) was shown to directly bind the LPCAT3 promoter to stimulate its transcription in a Yes-associated protein (YAP)-dependent manner. An interaction between YAP and ZEB was also observed. E1A-binding protein p300 (EP300) simultaneously bound with YAP and ZEB, and induced H3K27Ac for LPCAT3 transcription. This mechanism was verified in primary LUAD cell and xenograft models. The ACSL4, LPCAT3, and YAP combination can jointly determine LUAD ferroptosis sensitivity. Innovation: The binding site of ZEB exists in the -1600 to -1401 nt region of LPCAT3 promoter, which promotes LPCAT3 transcription after ZEB binding. ZEB and YAP bind, and the ZEB zinc-finger cluster domain and YAP WW domain are crucial for their binding. EP300 may bind with YAP via its Bromo domain and with ZEB via its CBP/p300-HAT domain. In addition, the combination of ACSL4, LPCAT3, and YAP to determine ferroptosis sensitivity of LUAD cells is better than prostaglandin-endoperoxide synthase 2 (PTGS2), transferrin receptor (TFRC), or NADPH oxidase 1 (NOX1). Conclusion: LPCAT3 transcription is regulated by YAP, ZEB, and EP300. LUAD ferroptosis sensitivity can be determined by the combination of ACSL4, LPCAT3, and YAP. Antioxid. Redox Signal. 39, 491-511.

Complement-mediated inflammation and mitochondrial energy metabolism in the proteomic profile of myopic human corneas

Myopia is one of the most common causes of visual impairment worldwide. To identify proteins related to myopiagenesis, data-independent acquisition proteomic analysis was performed using corneal lenticules of myopic patients who underwent small incision lenticule extraction surgery. A total of 19 lenticules from 19 age and sex-matched patients were analyzed, 10 in high refractive error (HR, spherical equivalent over -6.00 D) group and 9 in low refractive error (LR, spherical equivalent between -3.00 and - 1.00 D) group. Differentially expressed proteins (DEPs) were identified by comparing the corneal proteome between the two groups. Functional analyses were performed to explore the biological pathways and interactions of the DEPs. 107 DEPs (67 upregulated and 40 downregulated in HR group, compared to LR) were identified from 2138 quantified proteins. Functional analyses indicated that upregulated proteins were primarily involved in the complement pathways and extracellular matrix (ECM) remodeling, while downregulated proteins were involved in mitochondrial energy metabolism. Western blot analysis confirmed increased complement C3a and apolipoprotein E in HR samples, further supporting the proteomics data. In conclusion, this proteomic study reveals that proteins associated with the complement system, ECM remodeling, and mitochondrial energy metabolism might be key effectors in myopiagenesis. SIGNIFICANCE: Myopia has become one of the most prevalent causes of visual impairment, especially in Asia. The underlying mechanism of myopia development is still up for debate. This study compares the proteomic profiles of high and low myopic corneas, identifying differentially expressed proteins associated with the complement system, ECM remodeling, and mitochondrial energy metabolism. The findings of this study could provide novel insights into the pathogenesis of myopia. The complement system and mitochondrial energy metabolism may provide potential therapeutic targets in the treatment and prevention of myopia.

Comprehensive analysis of ferroptosis-related genes for clinical and biological significance in hepatocellular carcinoma

OBJECTIVE

This study aims to build a prognostic model of hepatocellular carcinoma (HCC) with ferroptosis-associated genes and explore their molecular function.

METHODS

Gene expression data and clinical information were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases and the International Cancer Genome Consortium (ICGC). A ferroptosis-associated gene set was obtained from the FerrDb database to identify differentially expressed genes. Then, we performed pathway enrichment analysis and immune infiltration analysis. A combined model based on ferroptosis-associated genes for predicting the overall survival of HCC was built by univariate and multivariate Cox regression analyses. Quantitative real-time polymerase chain reaction, Western blotting, colony formation, CCK-8, and EdU incorporation assays were performed to clarify the function of CAPG in the regulation of cell proliferation in human HCC. Ferroptosis was evaluated by glutathione (GSH), malondialdehyde (MDA), and total iron detection.

RESULTS

Forty-nine ferroptosis-related genes were significantly correlated with HCC, 19 of which had prognostic significance. CAPG, SLC7A11 and SQSTM1 were used to construct a novel risk model. The areas under the curves (AUCs) were 0.746 and 0.720 (1 year) in the training and validation groups, respectively. The survival analysis indicated that patients with high risk scores exhibited worse survival in the training and validation groups. The risk score was also identified as an independent prognostic factor of overall survival (OS), which established and validated the predictive abilities of the nomogram. The risk score was also significantly correlated with the expression of immune checkpoint genes. In vitro data showed that CAPG knockdown dramatically suppressed HCC cell proliferation, and the underlying molecular mechanisms might be that the silencing of CAPG reduced the expression of SLC7A11 and promoted ferroptosis.

CONCLUSION

The established risk model can be used to predict the prognosis of HCC. At the mechanistic level, CAPG may drive HCC progression by regulating SLC7A11, and ferroptosis activation in HCC patients with high CAPG expression may serve as a potential therapeutic strategy.

The combination therapy of isomucronulatol 7-O-beta-glucoside (IMG) and CEP-9722 targeting ferroptosis-related biomarkers in non-small cell lung cancer (NSCLC)

BACKGROUND

NSCLC is a malignant tumor with a high incidence. Ferroptosis presents an essential function in regulating carcinogenesis and tumor progression. However, the ferroptosis-associated prognostic model based on single-cell sequencing of NSCLC remains unexplored. Our study aims to establish a potential predictive model for NSCLC patients and provide available targeted drugs for clinical treatment.

METHODS

The data on NSCLC patients were collected from TCGA and GEO databases to analyze their gene expression profiles. ConsensusCluster was adopted to divide the patients into different groups based on ferroptosis-related genes. Then, the univariable Cox and LASSO analyses were applied to data analysis and model establishment. Single-cell analysis was used to explore the risk score genes in different cell populations and states. The protein levels of these genes were also investigated through the HPA database. Drug sensitivity was evaluated in CellMiner database. CCK8 and colony formation assays were performed to validate potential drugs' effects on lung cancer cell lines.

RESULTS

A ferroptosis-related prognostic model involving 14 genes in NSCLC patients was established. The risk score model was developed in training set GSE31210 and validated in the test set TCGA. The low-risk score group showed a better prognosis than the high-risk score group. The single-cell analysis revealed that the risk score genes were mainly derived from lung tumor cells. Most risk score genes were more highly expressed in tumor tissue than in normal tissue, according to the HPA database. Besides, these genes were associated with 106 drugs in CellMiner database. Finally, the drug effects on NSCLC cell growth were evaluated by cck8 and colony formation.

CONCLUSIONS

We identified an effective ferroptosis-related prognostic model based on single-cell sequencing. The potential prediction model is devoted to exploring clinical therapeutic targets for NSCLC.

PHKG2 regulates RSL3-induced ferroptosis in Helicobacter pylori related gastric cancer

Ferroptosis is a newly discovered form of regulatory cell death induced by iron-dependent lipid peroxidation. Infection with Helicobacter pylori (H. pylori) is regarded as a high-risk factor for the development of gastric cancer (GC) and is associated with an increase in the levels of reactive oxygen species with activation of oncogenic signaling pathways. However, whether GC arising in the context of infection with H. pylori is correlated with ferroptosis is still unknown. In this study, we demonstrate that H. pylori infection increased the sensitivity of GC cells to RSL3 (RAS-selective lethal3)-induced ferroptosis. The molecular subtypes mediated by ferroptosis-related genes are associated with tumor microenvironment (TME) cell infiltration and patient survival. Importantly, we identified that the expression of phosphorylase kinase G2 (PHKG2) was remarkably correlated with H. pylori infection, metabolic biological processes, patient survival and therapy response. We further found the mechanism of H. pylori-induced cell sensitivity to ferroptosis, which involves PHKG2 regulation of the lipoxygenase enzyme Arachidonate 5-Lipoxygenase (ALOX5). In conclusion, PHKG2 facilitates RSL3-induced ferroptosis in H. pylori-positive GC cells by promoting ALOX5 expression. These findings may contribute to a better understanding of the unique pathogenesis of H. pylori-induced GC and allow for maximum efficacy of genetic, cellular, and immune therapies for controlling ferroptosis in diverse contexts.

Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer

Background

This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.

Methods

The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, survival analysis was performed to investigate the risk score values in the TCGA cohort. And the enrichment analysis, immune cell infiltration levels analysis, and protein-protein internet (PPI) analysis were performed. Simultaneously, the GEO cohort was used to validate the model. Lastly, we constructed a nomogram to explore the influence of polygenic risk score and other clinical factors on the survival probability of patients with BRCA.

Results

A total of 1000 DEGs including 396 upregulated genes and 604 downregulated genes were identified from the TCGA-BRCA dataset. We obtained 5 prognosis-related genes, as the key biomarkers by Lasso-cox analysis (FBXL19, HAGHL, PHKG2, PKMYT1, and TXNDC17), all of which were significantly upregulated in breast tumors. The prognostic prediction of the 5 genes model was great in training and validation cohorts. Moreover, the high-risk group had a poorer prognosis. The Cox regression analysis showed that the comprehensive risk score for 5 genes was an independent prognosis factor.

Conclusion

The 5 genes risk model constructed in this study had an independent predictive ability to distinguish patients with a high risk of death from those with a low-risk score, and it can be used as a practical and reliable prognostic tool for BRCA.

Identification of CISD1 as a Prognostic Biomarker for Breast Cancer

Background

Although CISD1 (CDGSH iron sulfur domain 1) is upregulated in many cancer types, the potential role of CISD1 in breast cancer is still unclear. The purpose of this study was to investigate its clinical significance in breast cancer.

Methods

We obtained 1109 breast cancer samples and 113 normal samples from The Cancer Genome Atlas (TCGA) and GTEx databases to demonstrate the relationship between CISD1 expression and pancancer characteristics. We analysed the relationship between CISD1 and breast cancer using the t-test and the chi-square test to evaluate the expression level of CISD1 and its clinical significance in breast cancer. The prognostic value of CISD1 in breast cancer was determined by Kaplan‒Meier and Cox regression analyses. The biological pathways were screened by gene set analysis and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and single-sample gene set enrichment analysis (ssGSEA), of which the correlation between the level of immune infiltration and the expression of CISD1 in breast cancer was then analysed. Finally, we verified the conclusion by qPCR, immunohistochemistry, and CCK8.

Results

CISD1 is highly expressed in breast cancer patients. In addition, we verified a higher expression of CISD1 expressed in the BRCA (breast cancer) cell line, whereas CISD1 has a high diagnostic value, with an AUC of 0.718. Kaplan‒Meier survival and Cox regression analyses showed that high expression of CISD1 was independently associated with adverse clinical outcomes. In turn, GO and KEGG analyses showed that most genes were related to rRNA metabolic process, rRNA processing. Moreover, PCR and immunohistochemistry showed that CISD1 in breast cancer tissues was upregulated significantly, with CCK8 results showing that the proliferation of breast cancer cells decreased after CISD1 knockout.

Conclusion

A high level of CISD1 is associated with poor prognosis and immune infiltration in breast cancer.

LATPS, a novel prognostic signature based on tumor microenvironment of lung adenocarcinoma to better predict survival and immunotherapy response

Background

Clinically, only a minority of patients benefit from immunotherapy and few efficient biomarkers have been identified to distinguish patients who would respond to immunotherapy. The tumor microenvironment (TME) is reported to contribute to immunotherapy response, but details remain unknown. We aimed to construct a prognostic model based on the TME of lung adenocarcinoma (LUAD) to predict the prognosis and immunotherapy efficacy.

Methods

We integrated computational algorithms to describe the immune infiltrative landscape of LUAD patients. With the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses, we developed a LUAD tumor microenvironment prognostic signature (LATPS). Subsequently, the immune characteristics and the benefit of immunotherapy in LATPS-defined subgroups were analyzed. RNA sequencing of tumor samples from 28 lung cancer patients treated with anti-PD-1 therapy was conducted to verify the predictive value of the LATPS.

Results

We constructed the LATPS grounded on four genes, including UBE2T, KRT6A, IRX2, and CD3D. The LATPS-low subgroup had a better overall survival (OS) and tended to have a hot immune phenotype, which was characterized by an elevated abundance of immune cell infiltration and increased activity of immune-related pathways. Additionally, tumor immune dysfunction and exclusion (TIDE) score was markedly decreased in the LATPS-low subgroup, indicating an enhanced opportunity to benefit from immunotherapy. Survival analysis in 28 advanced lung cancer patients treated with an anti-PD-1 regimen at Nanfang hospital revealed that the LATPS-low subgroup had better immunotherapy benefit.

Conclusion

LATPS is an effective predictor to distinguish survival, immune characteristics, and immunotherapy benefit in LUAD patients.

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

Introduction

Cuproptosis 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.

Methods

Transcriptome 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.

Results

Most 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.

Discussion

Our 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.

Identification of a novel ferroptosis-related gene signature associated with prognosis, the immune landscape, and biomarkers for immunotherapy in ovarian cancer

Ferroptosis has been implicated in tumor progression and immunoregulation. Identification of ferroptosis-related prognostic gene is important for immunotherapy and prognosis in ovarian cancer (OV). We assessed the potential predictive power of a novel ferroptosis-related gene (FRG) signature for prognosis and immunotherapy in Asian and Caucasian OV populations. We collected gene expression profiles and clinicopathological data from public databases. The least absolute shrinkage and selection operator Cox regression algorithm was used to construct the FRG signature. Receiver operating characteristic (ROC) curve, Kaplan-Meier method, Cox regression model were used to evaluate the clinical benefits of FRG signature. Gene functional and gene set enrichment analyses were used for functional annotation and immune landscape analysis. A 15-FRG signature was constructed and used to stratify patients into two risk groups. Patients in the high-risk group had significantly worse survival. The risk score was a significant independent risk factor for OS. The area under the ROC curve indicated the good prediction performance of the FRG signature. Notably, the low-risk group showed a significant enrichment in immune-related pathways and a “hot” immune status. The risk score was found to be an efficient and robust predictor of response to immunotherapy. In conclusion, our study identified a novel 15-FRG prognostic signature that can be used for prognostic prediction and precision immunotherapy in Asian and Caucasian OV populations.

Identification of ATG7 as a Regulator of Proferroptosis and Oxidative Stress in Osteosarcoma

Background

Ferroptosis has gained significant attention from oncologists as a vital outcome of oxidative stress. The aim of this study was to develop a prognostic signature that was based on the ferroptosis-related genes (FRGs) for osteosarcoma patients and explore their specific role in osteosarcoma.

Methods

The training cohort dataset was extracted from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Different techniques like the univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression analyses, and the Kaplan-Meier (KM) survival analyses were utilized to develop a prognostic signature. Then, the intrinsic relationship between the developed gene signature and the infiltration levels of the immune cells was further investigated. An external validation dataset from the Gene Expression Omnibus (GEO) database was employed to assess the predictive ability of the developed gene signature. Subsequently, the specific function of potential FRG in affecting the oxidative stress reaction and ferroptosis of osteosarcoma cells was identified.

Results

A prognostic signature based on 5 FRGs (CBS, MUC1, ATG7, SOCS1, and PEBP1) was developed, and the patients were classified into the low- and high-risk groups (categories). High-risk patients displayed poor overall survival outcomes. The risk level was seen to be an independent risk factor for determining the prognosis of osteosarcoma patients (p < 0.001, hazard ratio: 7.457, 95% CI: 3.302-16.837). Additionally, the risk level was associated with immune function, which might affect the survival status of osteosarcoma patients. Moreover, the findings of the study indicated that the expression of ATG7 was related to the regulation of oxidative stress in osteosarcoma. Silencing the ATG7 gene promoted the proliferation and migration in osteosarcoma cells, suppressing the oxidative stress and ferroptosis process.

Conclusions

A novel FRG signature was developed in this study to predict the prognosis of osteosarcoma patients. The results indicated that ATG7 might regulate the process of oxidative stress and ferroptosis in osteosarcoma cells and could be used as a potential target to develop therapeutic strategies for treating osteosarcoma.

Application of genomic selection and experimental techniques to predict cell death and immunotherapeutic efficacy of ferroptosis-related CXCL2 in hepatocellular carcinoma

Since most hepatocellular carcinoma (HCC) patients are diagnosed at advanced stages, there is no effective treatment to improve patient survival. Ferroptosis, a regulated cell death driven by iron accumulation and lipid peroxidation, has been reported to play an important role in tumorigenesis. However, the detailed mechanism and biological function of ferroptosis are still incompletely understood in HCC patients. In this study, we analyzed genomic profiles of three HCC datasets, GSE6764, GSE14520, and GSE14323. Venn diagrams were implemented to visualize the overlapping genes between differentially expressed genes and ferroptosis-related gene set. Then, one up-regulated gene, ACSL4, and five down-regulated genes, STEAP3, MT1G, GCH1, HAMP, and CXCL2, were screened. Based on the survival analysis performed by Kaplan-Meier plotter database, ferroptosis-related gene CXCL2 was demonstrated positively-correlated with the patients' prognosis. Moreover, CXCL2 overexpression significantly inhibited cell growth and improved cellular ROS, Fe2+ and MDA levels in HCC cells Huh7 and MHCC97H, suggesting the roles of CXCL2 in inducing ferroptotic cell death. In addition, aberrantly expressed CXCL2 was negatively associated with malignancy clinical features, such as nodal metastasis and higher grades. The ssGSEA enrichment analysis revealed that CXCL2 co-expressed molecules were mainly involved in inflammation and immune-related pathways, such as acute inflammatory response, humoral immune response, adaptive immune response. TISIDB algorithm indicated the positive correlation between CXCL2 expression and tumor-infiltrating immune cells, including neutrophils and macrophages. Additionally, we also found that CXCL2 was positively correlated with immune infiltration score, and HCC patients with higher score harbored better prognosis. Together, these findings suggested that CXCL2 may enhance ferroptosis sensitivity and regulate immune microenvironment in HCC, and serve as a promising prognosis biomarker for HCC patients.

Cooperation effects of radiation and ferroptosis on tumor suppression and radiation injury

Ferroptosis is a kind of oxidative stress-dependent cell death characterized by iron accumulation and lipid peroxidation. It can work in conjunction with radiation to increase reactive oxygen species (ROS) generation and disrupt the antioxidant system, suppressing tumor progression. Radiation can induce ferroptosis by creating ROS, depleting glutathione, activating genes linked to DNA damage and increasing the expression of acyl-CoA synthetase long-chain family member 4 (ACSL4) in tumor cells. Furthermore, ferroptosis can enhance radiosensitivity by causing an iron overload, destruction of the antioxidant system, and lipid peroxidation. Radiation can also cause ferroptosis in normal cells, resulting in radiation injury. The role of ferroptosis in radiation-induced lung, intestinal, skin, and hematological injuries have been studied. In this review, we summarize the potential mechanisms linking ferroptosis, oxidative stress and radiation; analyze the function of ferroptosis in tumor suppression and radiation injury; and discuss the potential of ferroptosis regulation to improve radiotherapy efficacy and reduce adverse effects.

Necroptosis-related lncRNA in lung adenocarcinoma: A comprehensive analysis based on a prognosis model and a competing endogenous RNA network

Background: Necroptosis, an innovative type of programmed cell death, involves the formation of necrosomes and eventually mediates necrosis. Multiple lines of evidence suggest that necroptosis plays a major role in the development of human cancer. However, the role of necroptosis in lung adenocarcinoma (LUAD) remains unclear. In this study, we aimed to construct an NRL-related prognostic model and comprehensively analyze the role of NRL in LUAD.

Methods: A necroptosis-related lncRNA (NRL) signature was constructed in the training cohort and verified in the validation and all cohorts based on The Cancer Genome Atlas database. In addition, a nomogram was developed. The tumor microenvironment (TME), checkpoint, human leukocyte antigen, and m6A methylation levels were compared between low-risk and high-risk groups. Then, we identified five truly prognostic lncRNAs (AC107021.2, AC027117.1, FAM30A, FAM83A-AS1, and MED4-AS1) and constructed a ceRNA network, and four hub genes of downstream genes were identified and analyzed using immune, pan-cancer, and survival analyses.

Results: The NRL signature could accurately predict the prognosis of patients with LUAD, and patients with low risk scores were identified with an obvious “hot” immune infiltration level, which was strongly associated with better prognosis. Based on the ceRNA network, we postulated that NRLs regulated the TME of patients with LUAD via cyclin-dependent kinase (CDK) family proteins.

Conclusion: We constructed an NRL signature and a ceRNA network in LUAD and found that NRLs may modulate the immune microenvironment of LUAD via CDK family proteins.

Construction of a ferroptosis-associated circRNA-miRNA-mRNA network in age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of severe vision impairment in the aging population. However, the underlying molecular mechanism remains unclear. Ferroptosis is a novel non-apoptotic programmed cell death pathway, that contributes to AMD. In addition, non-coding RNA-led epigenetic profile was identified in the regulation of AMD progression. Considering that non-coding RNAs are vital regulators of ferroptosis-related genes in various pathological events, we explored and constructed a ferroptosis-associated circRNA-miRNA-mRNA network in AMD. Differential expression of fourteen ferroptosis-associated genes were identified based on our microarray analysis and the FerrDb tool at the threshold of P < 0.05 and log₂|fold change| ≥ 1, which were subsequently validated by the public datasets. We further screened eight miRNAs via public datasets and the miRNet database. Based on these eight miRNAs, 23 circRNAs were mined using the Starbase tool. Taking all these together, we obtained a ferroptosis-related network with 414 pairs of circRNA-miRNA-mRNA, which are potential targets in future AMD treatments.

Prediction of Prognosis in Patients With Endometrial Carcinoma and Immune Microenvironment Estimation Based on Ferroptosis-Related Genes

Background: Ferroptosis, a form of non-apoptotic cell death, has aroused worldwide interest in cancer researchers. However, the current study about the correlation between ferroptosis-related genes (FRGs) and endometrial cancer (EC) remains limited.

Methods: First, the transcriptome profiling and clinical data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) program as the training group and testing group, respectively. FRGs were acquired through literature mining. Then, we used R 4.1.1 software to screen the differently expressed FRGs from TCGA, which was also connected with the prognosis of EC patients. Subsequently, the risk score of each tumor sample was identified by LASSO regression analysis, and we classified these samples into the high- and low-risk groups in the light of the median risk score. Receiver operating characteristic (ROC) curve analysis and Kaplan-Meier analysis were performed to assess the accuracy of this signature. Significantly, the data from CPTAC was used to validate the prediction model externally. Furthermore, we evaluated the immune microenvironment in this model via single-sample gene set enrichment analysis (ssGSEA).

Results: Among the 150 FRGs, 6 differentially expressed genes (DEGs) based on TCGA had a relationship with the prognosis of EC patients, namely, TP53, AIFM2, ATG7, TLR4, PANX1 and MDM2. The survival curve indicated a higher survival probability in the low-risk group. Moreover, the FRGs-based signature acted well in the prediction of overall survival (OS). The results of external verification confirmed the prediction model we established. Finally, ssGSEA revealed significant differences in the abundance of 16 immune cells infiltration and the activity of 13 immune functions between different risk groups.

Conclusion: We identified a novel ferroptosis-related gene signature which could concisely predict the prognosis and immunotherapy in EC patients.

Identification of Ferroptosis-Related Hub Genes and Their Association with Immune Infiltration in Chronic Obstructive Pulmonary Disease by Bioinformatics Analysis

Purpose

Ferroptosis and immune infiltration are involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). We aim to identify ferroptosis-related hub genes and analyze their association with immune infiltration in COPD through bioinformatics methods.

Materials and Methods

The mRNA microarray data of GSE38974 were downloaded from Gene Expression Omnibus to obtain differentially expressed genes (DEGs). The DEGs were intersected with ferroptosis-related genes (FRGs) from FerrDb to obtain differentially expressed FRGs. GO and KEGG enrichment and protein–protein interaction (PPI) analyses of differentially expressed FRGs were conducted in R software and STRING database. The key module and hub genes were screened by Cytoscape software. MiRNAs, transcription factors and signal molecules were predicted in miRNet and NetworkAnalyst. The disease correlation in the Comparative Toxicomics Database (CTD) and the receiver operating characteristic (ROC) curves of hub genes were analyzed. Immune infiltration was evaluated by CIBERSORT algorithm. Spearman correlation analyses were conducted between hub genes and differentially infiltrated immune cells.

Results

Fifteen differentially expressed FRGs were identified, which were enriched in some terms involving airway inflammatory responses and structural remodeling. Five hub genes were selected including HIF1A, IL6, PTGS2, CDKN1A and ATM. Inference scores in CTD indicated their association with COPD. Two miRNAs, five transcription factors and one signal molecule were predicted. The combination of hub genes could be a fine diagnostic indicator of COPD (AUC: 0.981, CI: 0.940-1.000). Immune infiltration evaluation showed that monocytes and M0 macrophages were upregulated in COPD lung tissues, while CD8 T cells, activated NK cells, M2 macrophages, resting dendritic cells and resting mast cells were downregulated. The hub genes were significantly associated with differentially infiltrated immune cells.

Conclusion

We identified five ferroptosis-related hub genes (HIF1A, IL6, PTGS2, CDKN1A and ATM) in COPD, and found that they may influence the pathogenesis of COPD by regulating ferroptosis and thus affecting infiltrating immune cells.

Eucommia ulmoides Oliver-Tribulus terrestris L. Drug Pair Regulates Ferroptosis by Mediating the Neurovascular-Related Ligand-Receptor Interaction Pathway- A Potential Drug Pair for Treatment Hypertension and Prevention Ischemic Stroke

Background

In this study, we used the network pharmacology approach to explore the potential disease targets of the Eucommia ulmoides Oliver (EUO)-Tribulus terrestris L. (TT) drug pair in the treatment of hypertension-associated neurovascular lesions and IS via the ferroptosis pathway.

Methods

We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform to search for the key active compounds and targets of the drug pair. Based on the GeneCards database, the relevant targets for the drug pair were obtained. Then, we performed the molecular docking of the screened core active ingredients and proteins using the DAVID database and the R AutoDock Vina software. Based on the GSE22255 dataset, these screened target proteins were used to build random forest (RF) and support vector machine (SVM) models. Finally, a new IS nomogram prediction model was constructed and evaluated.

Results

There were 36 active compounds in the EUO-TT drug pair. CHRM1, NR3C1, ADRB2, and OPRD1 proteins of the neuroactive ligand-receptor interaction pathway interacted with the proteins related to the ferroptosis pathway. Molecular docking experiments identified 12 active ingredients of the drug pair that may tightly bind to those target proteins. We constructed a visual IS nomogram prediction model using four genes (CHRM1, NR3C1, ADRB2, and OPRD1). The calibration curve, DCA, and clinical impact curves all indicated that the nomogram model is clinically applicable and diagnostically capable. CHRM1, NR3C1, ADRB2, and OPRD1, the target genes of the four effective components of the EUO-TT drug pair, were considered as risk markers for IS.

Conclusions

The active ingredients of EUO-TT drug pair may act on proteins associated with the neuroactive ligand-receptor interaction pathway to regulate ferroptosis in vascular neurons cells, ultimately affecting the onset and progression of hypertension.

LPIN1 Is a Regulatory Factor Associated With Immune Response and Inflammation in Sepsis

Objectives

Sepsis is a clinical disease that is typically treated in the intensive care unit, and the complex pathophysiology under this disease has not been thoroughly understood. While ferroptosis is involved in inflammation and infection, its effect in sepsis is still unknown. The study aimed to identify ferroptosis-related genes in sepsis, providing translational potential therapeutic targets.

Methods

The dataset GSE65682 was used to download the sample source from the Gene Expression Omnibus (GEO) database. Consensus weighted gene co-expression network analysis (WGCNA) was performed to find suspected modules of sepsis. The differentially expressed genes (DEGs) most significantly associated with mortality were intersected with those altered by lipopolysaccharide (LPS) treatment and were further analyzed for the identification of main pathways of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The related pathway markers were further verified by qPCR.

Results

A total of 802 blood samples with sepsis were included for WGCNA, which identified 21 modules. Intersected with ferroptosis databases and LPS treatment groups, we identified two ferroptosis-related genes: PEBP1 and LPIN1. Only LPIN1 contributes to a poor outcome. Then, 205 DEGs were further identified according to the high or low LPIN1 expression. Among them, we constructed a gene regulatory network with several transcriptional factors using the NetworkAnalyst online tool and identified that these genes mostly correlate with inflammation and immune response. The immune infiltration analysis showed that lower expression of LPIN1 was related to macrophage infiltration and could be an independent predictor factor of the survival status in sepsis patients. Meanwhile, the multivariate Cox analysis showed that LPIN1 had a significant correlation with survival that was further verified by in vitro and in vivo experiments.

Conclusion

In conclusion, LPIN1 could become a reliable biomarker for patient survival in sepsis, which is associated with immune and inflammation status.

A Novel Predictive Model Incorporating Ferroptosis-Related Gene Signatures for Overall Survival in Patients with Lung Adenocarcinoma

BACKGROUND Lung adenocarcinoma (LUAD) is the predominant histological type of lung cancer with high morbidity and mortality. Ferroptosis is regarded as a new pattern of programmed cell death concerned with the progression of lung cancer characterized by lipid peroxidation. Nevertheless, the prognostic role of ferroptosis-related genes for LUAD warrant to be explored. MATERIAL AND METHODS RNA sequencing and relevant clinical patient data were obtained from public-access databanks. A prognostic model was constructed through the LASSO Cox regression in the cancer genome atlas cohort. The diagnostic value of the prognostic model was further evaluated in the gene expression omnibus cohort. RESULTS Most of the ferroptosis-related genes (69.9%) were differentially expressed between tumor and adjacent non-cancerous tissues. 43 differentially expressed genes showed a close association with the prognosis of LUAD patients (adjusted p-value <0.05). An 18-gene signature was built and applied to assign patients into high vs low-risk groups. Compared with the high-risk group, patients defined as the low-risk group suffered significantly prolonged OS. Both uni- and multivariate analyses demonstrated that the signature-based score served as a crucial role in influencing the OS of LUAD patients (hazard ratio >1, p<0.001). The immunity-related signaling pathway was enriched in the functional analysis and the infiltration of the immune cells showed a great difference between groups. CONCLUSIONS The predictive model could be applied for prognostic prediction for LUAD. Targeting ferroptosis could be a possible curative strategy against LUAD, and immunomodulation may be one of the potential mechanisms.

Ferroptosis in Lung Cancer: From Molecular Mechanisms to Prognostic and Therapeutic Opportunities

Lung cancer is the second commonly diagnosed malignancy worldwide and has the highest mortality rate among all cancers. Tremendous efforts have been made to develop novel strategies against lung cancer; however, the overall survival of patients still is low. Uncovering underlying molecular mechanisms of this disease can open up new horizons for its treatment. Ferroptosis is a newly discovered type of programmed cell death that, in an iron-dependent manner, peroxidizes unsaturated phospholipids and results in the accumulation of radical oxygen species. Subsequent oxidative damage caused by ferroptosis contributes to cell death in tumor cells. Therefore, understanding its molecular mechanisms in lung cancer appears as a promising strategy to induce ferroptosis selectively. According to evidence published up to now, significant numbers of research have been done to identify ferroptosis regulators in lung cancer. Therefore, this review aims to provide a comprehensive standpoint of molecular mechanisms of ferroptosis in lung cancer and address these molecules’ prognostic and therapeutic values, hoping that the road for future studies in this field will be paved more efficiently.