Immune infiltration and a ferroptosis-associated gene signature for predicting the prognosis of patients with endometrial cancer

T-Box Transcription Factor 2 Mediates Chemoresistance of Endometrial Cancer via Regulating FSP1-involved Ferroptosis

Chemotherapy is increasingly being used in the first-line treatment of endometrial cancer (EC) patients. However, chemoresistance seriously affects its efficacy. Understanding the underlying molecular mechanisms is critical for EC treatment. We explored the regulatory role of T-Box transcription factor 2 (TBX2)-ferroptosis suppressor protein 1 (FSP1) axis in ferroptosis and chemoresistance of EC. Cisplatin-resistant cell line Ishikawa/DDP cells were utilized to generate TBX2 and FSP1 overexpression and knockdown stable cell lines by using lentivirus infection and puromycin selection. Cell viability and ferroptosis status were evaluated in EC cells with or without Cisplatin and/or FSP1 inhibitor (iFSP1) using CKK-8, lipid peroxidation, malondialdehyde, and lactate dehydrogenase release assays. Endometrial carcinoma xenograft mouse model was established to further explore the function of TBX2-FSP1 axis on ferroptosis and tumor progression in EC. TBX2 suppressed Cisplatin-induced ferroptosis through up-regulating FSP1 expression level in EC cells. On the contrary, knockdown of TBX2 reduced FSP1 expression and significantly promoted Cisplatin-induced ferroptosis. TBX2 or FSP1 overexpression and knockdown promote and inhibit EC tumor growth under Cisplatin treatment, respectively. Interestingly, silence FSP1 could reverse TBX2-mediated ferroptosis inhibition and tumor-promoting effect. TBX2-FSP1 axis inhibits ferroptosis and enhances the Cisplatin resistance, which will provide an important theoretical basis and potential solution for the clinical treatment of EC.

Integrated Identification and Immunotherapy Response Analysis of the Prognostic Signature Associated With m6A, Cuproptosis-Related, Ferroptosis-Related lncRNA in Endometrial Cancer

BACKGROUND

Endometrial cancer (EC) stands as the predominant gynecological malignancy impacting the female reproductive system on a global scale. N6-methyladenosine, cuproptosis- and ferroptosis-related biomarker is beneficial to the prognostic of tumor patients. Nevertheless, the correlation between m6A-modified lncRNAs and ferroptosis, copper-induced apoptosis in the initiation and progression of EC remains unexplored in existing literature.

AIMS

In this study, based on bioinformatics approach, we identified lncRNAs co-expressing with cuproptosis-, ferroptosis-, m6A- related lncRNAs from expression data of EC. By constructing the prognosis model in EC, we screened hub lncRNA signatures affecting prognosis of EC patients. Furthermore, the guiding value of m6A-modified ferroptosis-related lncRNA (mfrlncRNA) features was assessed in terms of prognosis, immune microenvironment, and drug sensitivity.

METHOD

Our research harnessed gene expression data coupled with clinical insights derived from The Cancer Genome Atlas (TCGA) collection. To forge prognostic models, we adopted five machine learning approaches, assessing their efficacy through C-index and time-independent ROC analysis. We pinpointed prognostic indicators using the LASSO Cox regression approach. Moreover, we delved into the biological and immunological implications of the discovered lncRNA prognostic signatures.

RESULTS

The survival rate for the low-risk group was markedly higher than that for the high-risk group, as evidenced by a significant log-rank test (p < 0.001). The LASSO Cox regression model yielded concordance indices of 0.76 for the training set and 0.77 for the validation set, indicating reliable prognostic accuracy. Enrichment analysis of gene functions linked the identified signature predominantly to endopeptidase inhibitor activity, highlighting the signature's potential implications. Additionally, immune function and drug density emphasized the importance of early diagnosis in EC.

CONCLUSION

Five hub lncRNAs in EC were identified through constructing the prognosis model. Those genes might be potential biomarkers to provide valuable reference for targeted therapy and prognostic assessment of EC.

Establishing and Validating an Innovative Focal Adhesion-Linked Gene Signature for Enhanced Prognostic Assessment in Endometrial Cancer

Studies have highlighted the significant role of focal adhesion signaling in cancer. Nevertheless, its specific involvement in the pathogenesis of endometrial cancer and its clinical significance remains uncertain. We analyzed TCGA-UCEC and GSE119041 datasets with corresponding clinical data to investigate focal adhesion-related gene expression and their clinical significance. A signature, "FA-riskScore," was developed using LASSO regression in the TCGA cohort and validated in the GSE dataset. The FA-riskScore was compared with four existing models in terms of their prediction performance. We employed univariate and multivariate Cox regression analyses towards FA-riskScore to assess its independent prognostic value. A prognostic evaluation nomogram based on our model and clinical indexes was established subsequently. Biological and immune differences between high- and low-risk groups were explored through functional enrichment, PPI network analysis, mutation mining, TME evaluation, and single-cell analysis. Sensitivity tests on commonly targeted drugs were performed on both groups, and Connectivity MAP identified potentially effective molecules for high-risk patients. qRT-PCR validated the expressions of FA-riskScore genes. FA-riskScore, based on FN1, RELN, PARVG, and PTEN, indicated a poorer prognosis for high-risk patients. Compared with published models, FA-riskScore achieved better and more stable performance. High-risk groups exhibited a more challenging TME and suppressive immune status. qRT-PCR showed differential expression in FN1, RELN, and PTEN. Connectivity MAP analysis suggested that BU-239, potassium-canrenoate, and tubocurarine are effective for high-risk patients. This study introduces a novel prognostic model for endometrial cancer and offers insights into focal adhesion's role in cancer pathogenesis.

Identification of a disulfidptosis-related prognostic signature for prediction of the effect of treatment in patients with endometrial carcinoma

Background

Disulfide, an essential compounds family, has diverse biological activity and can affect the dynamic balance between physiological and pathological states. A recently published study found that aberrant accumulation of disulfide had a lethal effect on cells. This mechanism of cell death, named disulfidptosis, differs from other known cell death mechanisms, including cuproptosis, apoptosis, necroptosis, and pyroptosis. The relationship between disulfidptosis and development of cancer, in particular endometrial carcinoma, remains unclear.

Methods

To address this knowledge gap, we performed a preliminary analysis of samples from The Cancer Genome Atlas database. The samples were divided equally into a training group and a test group. A total of 2308 differentially expressed genes were extracted, and 11 were used to construct a prognostic model.

Results

Based on the risk score calculated using the prognostic model, the samples were divided into a high-risk group and a low-risk group. Survival time, tumor mutation burden, and microsatellite instability scores differed significantly between the two groups. Furthermore, a between-group difference in treatment effect was predicted. Comparison with other models in the literature indicated that this prognostic model had better predictive anility.

Conclusion

The results of this study provide a general framework for understanding the relationship between disulfidptosis and endometrial cancer that could be used for clinical evaluation and selection of appropriate personalized treatment strategies.

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.

Establishment of an immunogenic cell death-related model for prognostic prediction and identification of therapeutic targets in endometrial carcinoma

OBJECTIVE

Studies have firmly established the pivotal role of the immunogenic cell death (ICD) in the development of tumors. This study seeks to develop a risk model related to ICD to predict the prognosis of patients with endometrial carcinoma (EC).

MATERIALS AND METHODS

RNA-seq data of EC retrieved from TCGA database were analyzed using R software. We determined clusters based on ICD-related genes (ICDRGs) expression levels. Cox and LASSO analyses were further used to build the prediction model, and its accuracy was evaluated in the train and validation sets. Finally, in vitro and in vivo experiments were conducted to confirm the impact of the high-risk gene IFNA2 on EC.

RESULTS

Patients were sorted into two ICD clusters, with survival analysis revealing divergent prognoses between the clusters. The Cox regression analysis identified prognostic risk genes, and the LASSO analysis constructed a model based on 9 of these genes. Notably, this model displayed excellent predictive accuracy when validated. Finally, increased IFNA2 levels led to decreased vitality, proliferation, and invasiveness in vitro. IFNA2 also has significant tumor inhibiting effect in vivo.

CONCLUSIONS

The ICD-related model can accurately predict the prognosis of patients with EC, and IFNA2 may be a potential treatment target.

Novel LncRNA LINC02936 Suppresses Ferroptosis and Promotes Tumor Progression by Interacting with SIX1/CP Axis in Endometrial Cancer

Endometrial cancer (EC) is a prevalent gynecological malignancy, and metabolic disorders are among its most significant risk factors. Abnormal iron metabolism is associated with the progression of cancer malignancy. Nevertheless, the involvement of iron metabolism in the EC remains uncertain. Ceruloplasmin (CP) functions as a multicopper oxidase and ferroxidase, playing a crucial role in maintaining the metabolic balance between copper and iron. Prior research has demonstrated that the dysregulated expression of CP has important clinical implications in EC. However, ​the specific underlying molecular mechanisms remains uncertain. This research examined the impact of CP on the malignant advancement of EC by suppressing ferroptosis. Next, we explored the possibility that Long non-coding RNA (lncRNA) LINC02936/SIX1/CP axis may be a key pathway for inhibiting ferroptosis and promoting cancer progression in EC. Mechanistically, SIX1 modulates the expression of CP, whereas LINC02936 interacts with SIX1 and recruits SIX1 to the CP promoter, leading to upregulation of CP, inhibition of ferroptosis, and promotion of EC progression. Administration of a small peptide cloud block the LINC02936-SIX1 interaction, thereby inhibits EC progression by promoting ferroptosis. Altogether, this is the first report on the lncRNA regulation of ferroptosis in EC. Our research enhances the knowledge of the lncRNA-mediated regulation of ferroptosis in EC progression and indicates the potential therapeutic significance of the LINC02936/SIX1/CP axis in treating EC.

SIM2: Its Prognostic Significance and Oncogenic Role in Endometrial Carcinoma

Background

Endometrial carcinoma ranks as the second most widespread malignancy affecting the reproductive system in females. Effective prognostic biomarkers are required to further improve survival rates for patients. Single-minded homolog 2 (SIM2) is known to participate in neurogenesis as a transcription factor. However, the potential role of SIM2 in endometrial carcinoma remains elusive.

Methods

Multiple public databases, including TIMER2.0, GEIPA2, UALCAN, LinkedOmics, BioGRID, DAVID and cBioPortal, were used to investigate SIM2 mRNA expression, SIM2-associated genes, PPI network, functional enrichment analysis, SIM2 gene alterations and methylation. The association between SIM2 expression and immune cell infiltrates was explored using GSVA. The effects of gene alterations and methylation on patient survival and CD8+T infiltration were examined using GSCA. Moreover, the prognostic potential of SIM2 was evaluated using COX regression, ROC curves and a nomogram model. Finally, the differential expression and function of SIM2 in UCEC were explored using qPCR, WB, CCK8 and Transwell assays.

Results

Our findings revealed the heightened expression of SIM2 in endometrial carcinoma, and that its DNA methylation and CNV alterations were correlated with immune infiltration and patients' prognosis. Additionally, functional enrichment revealed the involvement of SIM2 in transcription regulation and signal transduction. Moreover, we performed cell-based experiments to corroborate the oncogenic function of SIM2 in facilitating cell proliferation, migration and invasion.

Conclusion

Collectively, these results suggest that SIM2 holds promise as both a potential prognostic indicator and a viable treatment target for endometrial carcinoma.

Comprehensive Analyses and Experiments Confirmed IGFBP5 as a Prognostic Predictor Based on an Aging-genomic Landscape Analysis of Ovarian Cancer

BACKGROUND

Ovarian cancer (OC) is one of the malignant diseases of the reproductive system in elderly women. Aging-related genes (ARGs) were involved in tumor malignancy and cellular senescence, but the specifics of these mechanisms in OC remain unknown.

METHODS

ARGs expression and survival data of OC patients were collected from TCGA and CPTAC databases. Subtype classification was used to identify the roles of hub ARGs in OC progression, including function enrichment, immune infiltration, and drug sensitivity. LASSO regression was utilized to confirm the prognosis significance for these hub ARGs. MTT, EdU, Transwell, and wounding healing analysis confirmed the effect of IGFBP5 on the proliferation and migration ability of OC cells.

RESULTS

ARGs were ectopically expressed in OC tissues compared to normal ovary tissues. Three molecular subtypes were divided by ARGs for OC patients. There were significant differences in ferroptosis, m6A methylation, prognosis, immune infiltration, angiogenesis, differentiation level, and drug sensitivity among the three groups. LASSO regression indicated that 4 signatures, FOXO4, IGFBP5, OGG1 and TYMS, had important prognosis significance. Moreover, IGFBP5 was significantly correlated with immune infiltration. The hub ARG, IGFBP5, expression was significantly decreased in OC patients compared to normal women. IGFBP5 could also reduce the migration and proliferation ability of OC cells compared to vector and NC groups.

CONCLUSION

IGFBP5 was correlated with OC prognosis and associated with OC migration and proliferation. This gene may serve as potential prognostic biomarkers and therapeutic targets for OC patients.

Identification of a prognostic signature based on five ferroptosis-related genes for diffuse large B-cell lymphoma

BACKGROUND

Therapies for diffuse large B-cell lymphoma (DLBCL) are limited due to the diverse gene expression profiles and complicated immune microenvironments, making it an aggressive lymphoma. Beyond this, researches have shown that ferroptosis contributes to tumorigenesis, progression, and metastasis. We thus are interested to dissect the connection between ferroptosis and disease status of DLBCL. We aim at generating a valuable prognosis gene signature for predicting the status of patients of DLBCL, with focus on ferroptosis-related genes (FRGs).

OBJECTIVE

To examine the connection between ferroptosis-related genes (FRGs) and clinical outcomes in DLBCL patients based on public datasets.

METHODS

An expression profile dataset for DLBCL was downloaded from GSE32918 (https://www.ncbi.nlm.nih.gov/geo/ query/acc.cgi?acc=gse32918), and a ferroptosis-related gene cluster was obtained from the FerrDb database (http://www. zhounan.org/ferrdb/). A prognostic signature was developed from this gene cluster by applying a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to GSE32918, followed by external validation. Its effectiveness as a biomarker and the prognostic value was determined by a receiver operator characteristic curve mono factor analysis. Finally, functional enrichment was evaluated by the package Cluster Profiler of R.

RESULTS

Five ferroptosis-related genes (FRGs) (GOP1, GPX2, SLC7A5, ATF4, and CXCL2) associated with DLBCL were obtained by a multivariate analysis. The prognostic power of these five FRGs was verified by TCGA (https://xenabrowser.net/datapages/?dataset=TCGA.DLBC.sampleMap%2FHiSeqV2_PANCAN&host=https%3A%2F%2Ftcga.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A44) and GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=gse 32918) datasets, with ROC analyses. KEGG and GO analyses revealed that upregulated genes in the high-risk group based on the gene signature were enriched in receptor interactions and other cancer-related pathways, including pathways related to abnormal metabolism and cell differentiation.

CONCLUSION

The newly developed signature involving GOP1, GPX2, SLC7A5, ATF4, and CXCL2 has the potential to serve as a prognostic biomarker. Furthermore, our results provide additional support for the contribution of ferroptosis to DLBCL.

Integrating ferroptosis-related genes (FRGs) and prognostic models to enhance UCEC outcome prediction and therapeutic insights

Ferroptosis is closely associated with uterine corpus endometrial carcinoma (UCEC) development. This project aimed to identify new potential biomarkers to predict the prognosis of UCEC. In this work, UCEC transcriptome data along with clinical information was retrieved from the TCGA database including a total of 382 FRGs. We performed univariate Cox regression analysis to evaluate ferroptosis-related genes (FRGs) for prognostic significance. The genes with prognostic significance were then analyzed using LASSO-Cox to construct a prognosis model. The model genes were further characterized through various proteomic analyses and expression detection in clinical samples. A multivariate Cox regression model was constructed containing four FRGs (CDKN1A, CDKN2A, CEBPG, NOS2). Among four FRGs, higher expressions of CDKN2A, CEBPG, and NOS2 were associated with poorer overall survival probability, while higher expression of CDKN1A was associated with better overall survival probability. The area under the receiver operating characteristic curve of the risk model was 0.617, 0.688, and 0.693 for 1 year, 3 years, and 5 years, respectively. Moreover, proteomic analysis showed that the protein expression of CDKN1A, CDKN2A, and CEBPG was higher in tumor tissues than that in normal tissues. Higher protein expression of CDKN1A and CDKN2A predicted poorer survival probability. Besides, CDKN1A protein had an interaction relationship with CDKN2A protein or NOS2 protein. In clinical samples, all four FRGs were upregulated in UCEC tissues, regardless of gene expression or protein expression. Our four FRGs risk model provides new insights for predicting the prognosis of UCEC patients.

Exploration of Simiao-Yongan Decoction on knee osteoarthritis based on network pharmacology and molecular docking

Use network pharmacology combined with molecular docking to study the effects of Simiao-Yongan Decoction (SMYAD) intervenes in Knee Osteoarthritis (KOA) related targets and signaling pathways, and explores the molecular mechanism of SMYAD in treating KOA. The active ingredients and targets of SMYAD, which concluded 4 traditional Chinese medicines, were screened in TCMSP, and the related gene targets of KOA were screened in the disease databases GeneCards, MalaCards, DisGeNET, and Comparative Toxicogenomics Database, and their intersection data were obtained after integration. And used Cytoscape 3.9.1, the software topologies the network diagram of "compound-drug-active ingredient-target protein-disease." Obtains the protein-protein interaction network diagram through STRING, and enriches and analyzes the obtained core targets. Carry out molecular docking matching verification on the main active ingredients and key targets of the drug. 106 active ingredients and 175 targets were screened from SMYAD to intervene in KOA, 36 core targets were obtained through protein-protein interaction screening, and 10 key targets played an important role. The enrichment results showed that the biological process of gene ontology mainly involved positive regulation of gene expression, negative regulation of apoptosis process, and positive regulation of apoptosis process. KEGG signaling pathway mainly involves AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, hypoxia-inducible factor-1 signaling pathway, IL-17 signaling pathway. The pathway of Reactome mainly involves interleukin-4 and interleukin-13 signaling, cytokine signaling in immune system, immune system, apoptosis. Molecular docking showed that the mainly effective components of SMYAD can fully combine with TNF, IL1B, IL6, and CASP3. The results show that the main active ingredients and potential mechanism of action of SMYAD in the treatment of KOA have the characteristics of multiple targets and multiple pathways, which provides ideas and basis for further in-depth exploration of its specific mechanism.

Genome-wide CRISPR screening reveals ADCK3 as a key regulator in sensitizing endometrial carcinoma cells to MPA therapy

BACKGROUND

The effectiveness of conservative treatment of endometrial carcinoma (EC) with oral progesterone therapy, such as medroxyprogesterone acetate (MPA), can be blunted due to primary or acquired resistance, but the underlying mechanisms remain incompletely defined.

METHODS

Genome-wide CRISPR screening was performed to identify potential regulators in response to MPA in Ishikawa cells. Crystal violet staining, RT-qPCR, western blotting, ChIP-qPCR and luciferase assays were employed to elucidate the p53-AarF domain-containing kinase 3 (ADCK3) regulatory axis and its roles in sensitizing EC cells to MPA treatment.

RESULTS

ADCK3 is identified as a previously unrecognized regulator in response to MPA in EC cells. Loss of ADCK3 in EC cells markedly alleviated MPA-induced cell death. Mechanistically, loss of ADCK3 primarily suppresses MPA-mediated ferroptosis by abrogating arachidonate 15-lipoxygenase (ALOX15) transcriptional activation. Moreover, we validated ADCK3 as a direct downstream target of the tumor suppressor p53 in EC cells. By stimulating the p53-ADCK3 axis, the small-molecule compound Nutlin3A synergized with MPA to efficiently inhibit EC cell growth.

CONCLUSIONS

Our findings reveal ADCK3 as a key regulator of EC cells in response to MPA and shed light on a potential strategy for conservative EC treatment by activating the p53-ADCK3 axis to sensitize MPA-mediated cell death.

Identification and verification of novel immune-related ferroptosis signature with excellent prognostic predictive and clinical guidance value in hepatocellular carcinoma

Background: Immunity and ferroptosis often play a synergistic role in the progression and treatment of hepatocellular carcinoma (HCC). However, few studies have focused on identifying immune-related ferroptosis gene biomarkers. Methods: We performed weighted gene co-expression network analysis (WGCNA) and random forest to identify prognostic differentially expressed immune-related genes (PR-DE-IRGs) highly related to HCC and characteristic prognostic differentially expressed ferroptosis-related genes (PR-DE-FRGs) respectively to run co-expression analysis for prognostic differentially expressed immune-related ferroptosis characteristic genes (PR-DE-IRFeCGs). Lasso regression finally identified 3 PR-DE-IRFeCGs for us to construct a prognostic predictive model. Differential expression and prognostic analysis based on shared data from multiple sources and experimental means were performed to further verify the 3 modeled genes' biological value in HCC. We ran various performance testing methods to test the model's performance and compare it with other similar signatures. Finally, we integrated composite factors to construct a comprehensive quantitative nomogram for accurate prognostic prediction and evaluated its performance. Results: 17 PR-DE-IRFeCGs were identified based on co-expression analysis between the screened 17 PR-DE-FRGs and 34 PR-DE-IRGs. Multi-source sequencing data, QRT-PCR, immunohistochemical staining and testing methods fully confirmed the upregulation and significant prognostic influence of the three PR-DE-IRFeCGs in HCC. The model performed well in the performance tests of multiple methods based on the 5 cohorts. Furthermore, our model outperformed other related models in various performance tests. The immunotherapy and chemotherapy guiding value of our signature and the comprehensive nomogram's excellent performance have also stood the test. Conclusion: We identified a novel PR-DE-IRFeCGs signature with excellent prognostic prediction and clinical guidance value in HCC.

A novel machine learning-based programmed cell death-related clinical diagnostic and prognostic model associated with immune infiltration in endometrial cancer

Background

To explore the underlying mechanism of programmed cell death (PCD)-related genes in patients with endometrial cancer (EC) and establish a prognostic model.

Methods

The RNA sequencing data (RNAseq), single nucleotide variation (SNV) data, and corresponding clinical data were downloaded from TCGA. The prognostic PCD-related genes were screened and subjected to consensus clustering analysis. The two clusters were compared by weighted correlation network analysis (WGCNA), immune infiltration analysis, and other analyses. The least absolute shrinkage and selection operator (LASSO) algorithm was used to construct the PCD-related prognostic model. The biological significance of the PCD-related gene signature was evaluated through various bioinformatics methods.

Results

We identified 43 PCD-related genes that were significantly related to prognoses of EC patients, and classified them into two clusters via consistent clustering analysis. Patients in cluster B had higher tumor purity, higher T stage, and worse prognoses compared to those in cluster A. The latter generally showed higher immune infiltration. A prognostic model was constructed using 11 genes (GZMA, ASNS, GLS, PRKAA2, VLDLR, PRDX6, PSAT1, CDKN2A, SIRT3, TNFRSF1A, LRPPRC), and exhibited good diagnostic performance. Patients with high-risk scores were older, and had higher stage and grade tumors, along with worse prognoses. The frequency of mutations in PCD-related genes was correlated with the risk score. LRPPRC, an adverse prognostic gene in EC, was strongly correlated with proliferation-related genes and multiple PCD-related genes. LRPPRC expression was higher in patients with higher clinical staging and in the deceased patients. In addition, a positive correlation was observed between LRPPRC and infiltration of multiple immune cell types.

Conclusion

We identified a PCD-related gene signature that can predict the prognosis of EC patients and offer potential targets for therapeutic interventions.

Ferroptosis, a new form of cell death: mechanisms, biology and role in gynecological malignant tumor

Ferroptosis, a term coined by Dixon et al. in 2012, refers to an iron-dependent form of regulated cell death driven by an overload of lipid peroxides on cellular membranes. It is morphologically and mechanistically distinct from apoptosis and other types of regulated cell death. Many studies have confirmed that ferroptosis is involved in the occurrence and development of many diseases, such as neurodegenerative diseases, chronic cardiovascular diseases, respiratory diseases and even tumors. While in the systemic diseases of obstetrics and gynecology, the related researches are still limited. In this article, we retrieved PubMed and WEB OF SCI databases for articles and reviews published before May 6, 2022, using "ferroptosis, ferroptosis regulator, gynecological tumors" as keywords, and comprehensively reviewed on their basis. Here, we systematically summarize the studies on the mechanism and characteristics of ferroptosis, investigate the role of ferroptosis in clinical systemic diseases of obstetrics and gynecology, evaluate the research status, unsolved problems and further research directions of ferroptosis, so as to let people learn more about ferroptosis and establish a research foundation for the exploration of the treatment strategies for ferroptosis-mediated diseases.

Crosstalk between ferroptosis and steroid hormone signaling in gynecologic cancers

Ferroptosis is a novel types of regulated cell death and is widely studied in cancers and many other diseases in recent years. It is characterized by iron accumulation and intense lipid peroxidation that ultimately inducing oxidative damage. So far, signaling pathways related to ferroptosis are involved in all aspects of determining cell fate, including oxidative phosphorylation, metal-ion transport, energy metabolism and cholesterol synthesis progress, et al. Recently, accumulated studies have demonstrated that ferroptosis is associated with gynecological oncology related to steroid hormone signaling. This review trends to summarize the mechanisms and applications of ferroptosis in cancers related to estrogen and progesterone, which is expected to provide a theoretical basis for the prevention and treatment of gynecologic cancers.

Ferroptosis and the bidirectional regulatory factor p53

Ferroptosis is a type of regulated cell death characterized by iron-mediated lipid peroxidation, in contrast with apoptosis, autophagy, and necrosis. It can be triggered by many pathological processes, including cellular metabolism, tumors, neurodegenerative diseases, cardiovascular diseases, and ischemia-reperfusion injuries. In recent years, ferroptosis has been discovered to be associated with p53. P53 is a tumor suppressor protein with multiple and powerful functions in cell cycle arrest, senescence, cell death, repair of DNA damage, and mitophagy. Emerging evidence shows that ferroptosis plays a crucial role in tumor suppression by p53. P53 functions as a key bidirectional regulator of ferroptosis by adjusting metabolism of iron, lipids, glutathione peroxidase 4, reactive oxygen species, and amino acids via a canonical pathway. In addition, a noncanonical pathway of p53 that regulates ferroptosis has been discovered in recent years. The specific details require to be further clarified. These mechanisms provide new ideas for clinical applications, and translational studies of ferroptosis have been performed to treat various diseases.

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.

Downregulation of PSAT1 inhibits cell proliferation and migration in uterine corpus endometrial carcinoma

Phosphoserine aminotransferase 1 (PSAT1) has been associated with the occurrence and development of various carcinomas; however, its function in uterine corpus endometrial carcinoma (UCEC) is unknown. We aimed to explore the relationship between PSAT1 and UCEC using The Cancer Genome Atlas database and functional experiments. PSAT1 expression levels in UCEC were employed using the paired sample t-test, Wilcoxon rank-sum test, the Clinical Proteomic Tumor Analysis Consortium database, and the Human Protein Atlas database, while survival curves were constructed using the Kaplan-Meier plotter. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore the possible functions and related pathways of PSAT1. Furthermore, single-sample gene set enrichment analysis was performed to detect the relationship between PSAT1 and tumor immune infiltration. StarBase and quantitative PCR were used to predict and verify the interactions between miRNAs and PSAT1. The Cell Counting Kit-8, EdU assay, clone formation assay, western blotting and flow cytometry were used to evaluate cell proliferation. Finally, Transwell and Wound healing assays were used to assess cell invasion and migration. Our study found that PSAT1 was significantly overexpressed in UCEC, and this high expression was associated with a worse prognosis. A high level of PSAT1 expression was associated with a late clinical stage and, histological type. In addition, the results of GO and KEGG enrichment analysis showed that PSAT1 was mainly involved in the regulation of cell growth, immune system and cell cycle in UCEC. In addition, PSAT1 expression was positively correlated with Th2 cells and negatively correlated with Th17 cells. Furthermore, we also found that miR-195-5P negatively regulated the expression of PSAT1 in UCEC. Finally, the knockdown of PSAT1 resulted in the inhibition of cell proliferation, migration, and invasion in vitro. Overall, PSAT1 was identified as a potential target for the diagnosis and immunotherapy of UCEC.

Comprehensive Analysis of Prognosis and Immune Landscapes Based on Lipid-Metabolism- and Ferroptosis-Associated Signature in Uterine Corpus Endometrial Carcinoma

(1) Background: The effect of tumor immunotherapy is influenced by the immune microenvironment, and it is unclear how lipid metabolism and ferroptosis regulate the immune microenvironment of uterine corpus endometrial carcinoma (UCEC). (2) Methods: Genes associated with lipid metabolism and ferroptosis (LMRGs-FARs) were extracted from the MSigDB and FerrDb databases, respectively. Five hundred and forty-four UCEC samples were obtained from the TCGA database. The risk prognostic signature was constructed by consensus clustering, univariate cox, and LASSO analyses. The accuracy of the risk modes was assessed through receiver operating characteristic (ROC) curve, nomogram, calibration,, and C-index analyses. The relationship between the risk signature and immune microenvironment was detected by the ESTIMATE, EPIC, TIMER, xCELL, quan-TIseq, and TCIA databases. The function of a potential gene, PSAT1, was measured by in vitro experiments. (3) Results: A six-gene (CDKN1A, ESR1, PGR, CDKN2A, PSAT1, and RSAD2) risk signature based on MRGs-FARs was constructed and evaluated with high accuracy in UCEC. The signature was identified as an independent prognostic parameter and it divided the samples into high- and low-risk groups. The low-risk group was positively associated with good prognosis, high mutational status, upregulated immune infiltration status, high expression of CTLA4, GZMA and PDCD1, anti-PD-1 treatment sensitivity, and chemoresistance. (4) Conclusions: We constructed a risk prognostic model based on both lipid metabolism and ferroptosis and evaluated the relationship between the risk score and tumor immune microenvironment in UCEC. Our study has provided new ideas and potential targets for UCEC individualized diagnosis and immunotherapy.

A mitochondria-localized iridium(iii) photosensitizer for two-photon photodynamic immunotherapy against melanoma

Conventional photodynamic therapy mainly causes a therapeutic effect on the primary tumor through the localized generation of reactive oxygen species, while metastatic tumors remain poorly affected. Complementary immunotherapy is effective in eliminating small, non-localized tumors distributed across multiple organs. Here, we report the Ir(iii) complex Ir-pbt-Bpa as a highly potent immunogenic cell death inducing photosensitizer for two-photon photodynamic immunotherapy against melanoma. Ir-pbt-Bpa can produce singlet oxygen and superoxide anion radicals upon light irradiation, causing cell death by a combination of ferroptosis and immunogenic cell death. In a mouse model with two physically separated melanoma tumors, although only one of the primary tumors was irradiated, a strong tumor reduction of both tumors was observed. Upon irradiation, Ir-pbt-Bpa not only induced the immune response of CD8+ T cells and the depletion of regulatory T cells, but also caused an increase in the number of the effector memory T cells to achieve long-term anti-tumor immunity.

SLC11A2: a promising biomarker and therapeutic target in ovarian cancer

Ovarian cancer has the highest mortality rate among gynecologic tumors, with a 5-year survival rate of less than 25%. There is an urgent need for early diagnosis and new drugs to reduce the disease burden of ovarian cancer. The aim of this study was to investigate the effectiveness of SLC11A2 as a therapeutic target and marker for ovarian cancer. Expression data of SLC11A2 were obtained from public databases. Then, the biological functions of SLC11A2 were validated in four ovarian cancer cell lines. Finally, we collected ovarian cancer clinical tissues, serum, and plasma exosomes and used immunohistochemistry, Elisa, and liquid chromatography-mass spectrometry (LC-MS) to validate the test efficacy of SLC11A2. The results showed that ovarian cancers with high SLC11A2 mRNA expression had shorter 5-year PFS and MST. Knockdown of SLC11A2 reduced ovarian cancer migration and increased cisplatin-induced apoptosis. Serum SLC11A2 may help improve the detection rate of ovarian cancer.

Association Analysis of PRKAA2 and MSMB Polymorphisms and Growth Traits of Xiangsu Hybrid Pigs

In this study, Xiangsu hybrid pig growth traits were evaluated via PRKAA2 and MSMB as candidate genes. Sanger sequencing revealed three mutation sites in PRKAA2, namely, g.42101G>T, g.60146A>T, and g.61455G>A, and all these sites were intronic mutations. Moreover, six mutation sites were identified in MSMB: intronic g.4374G>T, exonic g.4564T>C, exonic g.6378G>A, exonic g.6386C>T, intronic g.8643G>A, and intronic g.8857A>G. Association analysis revealed that g.42101G>T, g.60146A>T, g.61455G>A, g.4374G>T, g.4564T>C, g.6378G>A, g.6386C>T, g.8643G>A, and g.8857A>G showed different relationship patterns among body weight, body length, body height, chest circumference, abdominal circumference, tube circumference, and chest depth. Real-time polymerase chain reaction results revealed that the expression of PRKAA2 was highest in the longissimus dorsi muscle, followed by that in the heart, kidney, liver, lung, and spleen. The expression of MSMB was highest in the spleen, followed by that in the liver, kidney, lung, heart, and longissimus dorsi muscle. These results suggest that PRKAA2 and MSMB can be used in marker-assisted selection to improve growth related traits in Xiangsu hybrid pigs, providing new candidate genes for Pig molecular breeding.

Identification of cuproptosis-related subtypes, establishment of a prognostic model and tumor immune landscape in endometrial carcinoma

Cuproptosis, the mechanism of copper-dependent cell death, is distinct from all other known forms of regulated cell death and dependents on mitochondrial respiration. Cuproptosis promises to be a novel treatment, especially for tumors resistant to conventional therapies. We investigated the changes in cuproptosis-related genes (CRGs) in endometrial cancer (EC) cohorts from the merged Gene Expression Omnibus and the Cancer Genome Atlas databases, which could be divided into three distinct CRGclusters. Patients in CRGcluster C would have higher survival probability (P = 0.007), and higher levels of tumor microenvironment (TME) cell infiltration than other CRGclusters. CRG score was calculated via the results of univariate, multivariate cox analysis and least absolute shrinkage and selection operator regression analysis. Patients were divided into two risk subgroups according to the median risk score. Low-risk patients exhibited a more favorable prognosis, higher immunogenicity, and greater immunotherapy efficacy. Besides, CRG scores were strongly correlated to copy number variation, immunophenoscore, tumor mutation load, cancer stem cell index, microsatellite instability, and chemosensitivity. The c-index of our model is 0.702, which is higher than other four published model. The results proved that our model can distinguish EC patients with high-risk and low-risk and accurately predict the prognosis of EC patients. It will provide new ideas for clinical prognosis and precise treatments.

Characterization of peripheral white blood cells transcriptome to unravel the regulatory signatures of bovine subclinical mastitis resistance

Subclinical bovine mastitis is a pathogenic infection of the breast characterized by a marked decrease in milk production and quality. As it has no obvious clinical symptoms, diagnosis and treatment are challenging. Therefore, searching for biomarkers in cows’ peripheral white blood cells is valuable for preventing and treating subclinical mastitis. Thus, in this study, the transcriptome of peripheral blood from healthy and subclinical mastitis cows was characterized to find the regulatory signatures of bovine subclinical mastitis using RNA-seq. A total of 287 differentially expressed genes (DEGs) and 70 differentially expressed lncRNAs (DELs) were detected, and 37 DELs were documented near known Quantitative Trait Loci (QTL) associated with the mastitis of cows. Bioinformatic analysis indicated that lncRNAs MSTRG25101.2, MSTRG.56327.1, and MSTRG.18968.1, which are adjacent to the SCS QTL and SCC QTL, may be candidate lncRNAs that influence the pathogenesis of mastitis in cows by up-regulating the expression of genes TLR4, NOD2, CXCL8, and OAS2. Moreover, the alternative splicing (AS) pattern of transcriptional sequence differences between healthy cows and subclinical mastitis cows suggested a molecular mechanism of mastitis resistance and susceptibility. A total of 2,212 differential alternative splicing (DAS) events, corresponding to 1,621 unique DAS genes, were identified in both groups and significantly enriched in immune and inflammatory pathways. Of these, 29 DAS genes were subject to regulation by 32 alternative splicing SNPs, showing diverse and specific splicing patterns and events. It is hypothesized that the PIK3C2B and PPRPF8 splice variants associated with AS SNPs (rs42705933 and rs133847062) may be risk factors for susceptibility to bovine subclinical mastitis. Altogether, these key blood markers associated with resistance to subclinical mastitis and SNPs associated with alternative splicing of genes provide the basis for genetic breeding for resistance to subclinical mastitis in cows.

Comprehensive analysis reveals the potential value of inflammatory response genes in the prognosis, immunity, and drug sensitivity of lung adenocarcinoma

Background

Although the relationship between inflammatory response and tumor has been gradually recognized, the potential implications of of inflammatory response genes in lung adenocarcinoma (LUAD) remains poorly investigated.

Methods

RNA sequencing and clinical data were obtained from multiple independent datasets (GSE29013, GSE30219, GSE31210, GSE37745, GSE42127, GSE50081, GSE68465, GSE72094, TCGA and GTEx). Unsupervised clustering analysis was used to identify different tumor subtypes, and LASSO and Cox regression analysis were applied to construct a novel scoring tool. We employed multiple algorithms (ssGSEA, CIBERSORT, MCP counter, and ESTIMATE) to better characterize the LUAD tumor microenvironment (TME) and immune landscapes. GSVA and Metascape analysis were performed to investigate the biological processes and pathway activity. Furthermore, ‘pRRophetic’ R package was used to evaluate the half inhibitory concentration (IC50) of each sample to infer drug sensitivity.

Results

We identified three distinct tumor subtypes, which were related to different clinical outcomes, biological pathways, and immune characteristics. A scoring tool called inflammatory response gene score (IRGS) was established and well validated in multiple independent cohorts, which could well divide patients into two subgroups with significantly different prognosis. High IRGS patients, characterized by increased genomic variants and mutation burden, presented a worse prognosis, and might show a more favorable response to immunotherapy and chemotherapy. Additionally, based on the cross-talk between TNM stage, IRGS and patients clinical outcomes, we redefined the LUAD stage, which was called ‘IRGS-Stage’. The novel staging system could distinguish patients with different prognosis, with better predictive ability than the conventional TNM staging.

Conclusions

Inflammatory response genes present important potential value in the prognosis, immunity and drug sensitivity of LUAD. The proposed IRGS and IRGS-Stage may be promising biomarkers for estimating clinical outcomes in LUAD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01340-7.

ACO1 and IREB2 downregulation confer poor prognosis and correlate with autophagy-related ferroptosis and immune infiltration in KIRC

Background

ACO1 and IREB2 are two homologous cytosolic regulatory proteins, which sense iron levels and change iron metabolism–linked molecules. These two genes were noticeably decreased in kidney renal clear cell carcinoma (KIRC), which confer poor survival. Meanwhile, there is a paucity of information about the mechanisms and clinical significance of ACO1 and IREB2 downregulation in renal cancers.

Methods

The expression profiles of ACO1 and IREB2 were assessed using multiple public data sets via several bioinformatics platforms. Clinical and pathological information was utilized to stratify cohorts for comparison. Patient survival outcomes were evaluated using the Kaplan–Meier plotter, a meta-analysis tool. The correlations of ACO1 and IREB2 with ferroptosis were further evaluated in The Cancer Genome Atlas (TCGA)–KIRC database. Tumor immune infiltration was analyzed using the CIBERSORT, TIMER, and GEPIA data resources. ACO1 antagonist sodium oxalomalate (OMA) and IREB2 inhibitor sodium nitroprusside (SNP) was used to treat renal cancer ACHN cells together with sorafenib.

Results

KIRC patients with low ACO1 or IREB2 contents exhibited a remarkably worse survival rate in contrast with those with high expression in Kaplan–Meier survival analyses. Meanwhile, ACO1 and IREB2 regulate autophagy-linked ferroptosis along with immune cell invasion in the tumor microenvironment in KIRC patients. Blocking the activation of these two genes by their inhibitors OMA and SNP ameliorated sorafenib-triggered cell death, supporting that ACO1 and IREB2 could be participated in its cytotoxic influence on renal cancer cells.

Conclusion

ACO1 and IREB2 downregulation in renal cancers were correlated with cancer aggressiveness, cellular iron homeostasis, cytotoxic immune cell infiltration, and patient survival outcomes. Our research is integral to verify the possible significance of ACO1 and IREB2 contents as a powerful signature for targeted treatment or novel immunotherapy in clinical settings.

Identification and Validation of Cuproptosis-Related Prognostic Signature and Associated Regulatory Axis in Uterine Corpus Endometrial Carcinoma

Background: Uterine corpus endometrial carcinoma (UCEC) is a common gynecological malignancy globally with high recurrence and mortality rates. Cuproptosis is a new type of programmed cell death involved in tumor cell proliferation and growth, angiogenesis, and metastasis.

Methods: The difference in cuproptosis-related genes (CRGs) between UCEC tissues and normal tissues deposited in The Cancer Genome Atlas database was calculated using the “limma” R package. LASSO Cox regression analysis was conducted to construct a prognostic cuproptosis–related signature. Kaplan–Meier analysis was conducted to compare the survival of UCEC patients. A ceRNA network was constructed to identify the lncRNA–miRNA–mRNA regulatory axis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to verify CRG expression in UCEC.

Results: The expression of FDX1, LIAS, DLAT, and CDKN2A were upregulated, whereas the expression of LIPT1, DLD, PDHB, MTF1, and GLS were downregulated in UCEC versus normal tissues. The genetic mutation landscape of CRGs in UCEC was also summarized. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that these CRGs were enriched in the tricarboxylic acid (TCA) cycle, glycolysis, and HIF-1 signaling pathway. LASSO Cox regression analysis was performed and identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1). UCEC patients with high risk scores had a poor prognosis with an area under the curve of 0.782 and 0.764 on 3- and 5-year receiver operating characteristic curves. Further analysis demonstrated a significant correlation between CDKN2A and pTNM stage, tumor grade, immune cell infiltration, drug sensitivity, tumor mutational burden (TMB) score, and microsatellite instable (MSI) score. The data validation of qRT-PCR further demonstrated the upregulation of CDKN2A and the downregulation of LIPT1 and GLS in UCEC versus normal tissues. The ceRNA network also identified lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis for UCEC.

Conclusion: The current study identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1) for UCEC. The ceRNA network also identified that lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis may be involved in the progression of UCEC. Further in vivo and in vitro studies should be conducted to verify these results.

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.

Crosstalk of Redox-Related Subtypes, Establishment of a Prognostic Model and Immune Responses in Endometrial Carcinoma

Simple Summary

In order to explore the role of redox as a prognostic indicator in endometrial carcinoma (EC), we detected the expression patterns of 55 redox-related genes (RRGs) in EC cohorts from public databases. Performing consensus cluster algorithm, we determined four molecular subclusters based on RRGs which had significant differences in overall survival (OS) and immune activities of EC patients. Furthermore, we developed a prognostic risk model on the basis of the redox-related subtype by stepwise Cox regression analyses. All EC patients were divided into high-risk and low-risk groups according to the median value of risk score. Our proposed model could accurately assess the clinical outcome and had favorable independent ability in EC cases. Moreover, our signature can serve as a predictor for immune status and chemotherapy sensitivity.

Abstract

Redox plays a central part in the pathogeneses and development of tumors. We comprehensively determined the expression patterns of redox-related genes (RRGs) in endometrial carcinoma (EC) cohorts from public databases and identified four different RRG-related clusters. The prognosis and the characteristics of TME cell infiltration of RRGcluster C patients were worse than those of other RRG clusters. When it comes to the gene cluster, there were great differences in clinicopathology traits and immunocyte infiltration. The RRG score was calculated by Cox analyses, and an RRG-based signature was developed. The risk score performed well in the EC cohort. Samples were separated into two risk subgroups with the standard of the value of the median risk score. Low-risk patients had a better prognosis and higher immunogenicity. In addition, RRG score was closely associated with immunophenoscore, microsatellite instability, tumor mutation burden, tumor stem cell index, copy number variation and chemotherapy sensitivity. The nomogram accurately predicted the prognosis of patients, and our model showed better performance than other published models. In conclusion, we built a prognostic model of RRGs which can help to evaluate clinical outcomes and guide more effective treatment.

Ferroptosis: Opportunities and Challenges in Treating Endometrial Cancer

Ferroptosis, a new way of cell death, is involved in many cancers. A growing number of studies have focused on the unique role of ferroptosis on endometrial cancer. In this study, we made a comprehensive review of the relevant articles published to get deep insights in the association of ferroptosis with endometrial cancer and to present a summary of the roles of different ferroptosis-associated genes. Accordingly, we made an evaluation of the relationships between the ferroptosis-associated genes and TNM stage, tumor grade, histological type, primary therapy outcome, invasion and recurrence of tumor, and accessing the different prognosis molecular typing based on ferroptosis-associated genes. In addition, we presented an introduction of the common drugs, which targeted ferroptosis in endometrial cancer. In so doing, we clarified the opportunities and challenges of ferroptosis activator application in treating endometrial cancer, with a view to provide a novel approach to the disease.

Identification of immunity- and ferroptosis-related genes for predicting the prognosis of serous ovarian cancer

BACKGROUND

Serous ovarian cancer (SOC) is the most common type of ovarian cancer (OC), with bad outcomes. To improve the prognosis of SOC patients, a novel risk signature was developed by combining immunity- and ferroptosis-related genes.

METHODS

By means of comparing SOC tissues with normal tissues, we screened the differential expression of immunity-related genes (DE-IRGs) and ferroptosis-related genes(DE-FRGs) with the standards of |log₂fold change| > 1 and false discovery rate (FDR) < 0.05. After obtaining the meaningful differentially expressed genes from immune and ferroptosis (DEGs), we established a prognostic risk signature by utilizing Cox regression analyses in TCGA training set, which was validated in TCGA testing set and GSE26712 dataset. Besides, the differential expression of immune-related markers, immunophenoscore (IPS), TIDE score,T cell dysfunction score and T cell exclusion score were also analyzed. We further verified the expression of target genes in ovarian tumor cells lines by QRT-PCR.

RESULTS

A risk signature constructed by totally four immunity- and ferroptosis-related DEGs (CXCL11, CX3CR1, FH, and DNAJB6) was developed, which distinguished the SOC patients as high-risk and low-risk groups. Patients in the high-risk group showed a lower overall survival (OS) than those in the low-risk group. Furthermore, the risk score was independent when analyzed with clinical augments, which was significantly associated with 13 KEGG signaling pathways. The gene signature showed favorable predictive performance according to Receiver operating characteristic (ROC) curves. Notably, the expression of immune-related markers or IPS indicated a negative connection with the risk score. SOC patients had a lower score of TIDE and T cell dysfunction than Whom had a higher score. Nonetheless, there were no significant differences in T cell exclusion scores between the two groups.Compared with normal ovarian cell line IOSE-80,QRT-PCR experiments exhibited that CXCL11, CX3CR1and FH were up-regulated in ovarian tumor cells lines(SK-OV-3,COC1,A2780),while DNAJB6 was down-regulated.

CONCLUSION

Four-biomarker signature formed by immunity- and ferroptosis-related genes may be clinically used as risk stratifcation tool in serous ovarian cancer,which can help further clinical decision-making regarding prognostic prediction,individualized treatment and follow-up scheduling.

Necroptosis-Related miRNA Biomarkers for Predicting Overall Survival Outcomes for Endometrial Cancer

Endometrial cancer (EC) is the gynecological tumor with the highest incidence. In recent years, it has been proved that necroptosis is a method of cell death related to EC. However, the expression of necroptosis-related miRNA in EC and its correlation with prognosis still ill-defined. Use the Cancer Genome Atlas (TCGA) cohort to obtain prognostic data and related clinical data for ECs and normal endometrium tissues. In this study, we identified three necroptotic regulatory miRNAs that are necroptosis-related and survival-related miRNAs (DENSMs) between normal endometrium tissues and EC from 13 necroptosis-related miRNAs. The three DENSMs signature was built to develop prognostic model and classified all EC patients into a high or low risk group. EC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (p = 0.0242), and the risk score was found to be an independent prognosis factor for predicting the OS of EC patients (p = 0.0254) in multivariate Cox regression. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed dephosphorylation, microtubule, protein serine/threonine kinase activity, PI3K-Akt signaling pathway and MAPK signaling pathway are closely related to it. In conclusion, the risk prediction model based on necroptosis-related miRNAs can effectively predict the prognosis of EC patients.

Identification of ferroptosis-related molecular markers in glomeruli and tubulointerstitium of lupus nephritis

PURPOSE

Ferroptosis, characterized by iron accumulation and lipid peroxidation, is a newly demonstrated form of programed cell death. Present studies reveal that ferroptosis is involved in tumor and neurodegenerative disease. Regarding its roles in the development of LN, it is least interrogated. In this study, we explored whether ferroptosis is activated and how does it change at transcriptomic level in LN.

METHODS

4-Hydroxynonenal (4-HNE) was stained to explore whether ferroptosis is activated. Subsequently, by using bioinformatic methods, public GSE32591 dataset was analyzed. Ferroptosis-related differentially expressed genes (FR-DEGs) were identified in both glomeruli and tubulointerstitium. Immune cell infiltration was evaluated. Correlation between FR-DEGs and infiltrated immune cells was also calculated. Finally, dataset of GSE113342, qPCR, and immunofluorescence staining were also used or performed to validate the results.

RESULTS

Expression of 4-HNE was significantly increased in both glomeruli and tubulointerstitium. At transcriptomic level, 19 FR-DEGs in glomeruli and 15 FR-DEGs in tubulointerstitium including genes of iron metabolism, antioxidant system inhibitors, and ferroptosis suppressors were significantly altered in LN. Of which, LTF, CYBB, and CCL5 were upregulated and G0S2 and AKR1C1 were downregulated in both glomeruli and tubulointerstitium of LN. qPCR further validated the alteration of LTF, CYBB, CCL5, G0S2, and AKR1C1 in the whole kidney. Correlation analysis showed that CYBB positively correlated with monocyte infiltration in glomeruli and positively correlated with response to therapy.

CONCLUSION

Lipid peroxidation was aberrantly activated in LN, suggesting the activation of ferroptosis. LTF, CYBB, CCL5, G0S2, and AKR1C1, especially CYBB, might be good biomarkers of ferroptosis in LN.

Identification and Validation of a GPX4-Related Immune Prognostic Signature for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a commonly occurring histological subtype of lung cancer. Glutathione peroxidase 4 (GPX4) is an important regulatory factor of ferroptosis and is involved in the development of many cancers, but its prognostic significance has not been systematically described in LUAD. In this study, we focused on developing a robust GPX4-related prognostic signature (GPS) for LUAD. Data for the training cohort was extracted from The Cancer Genome Atlas, and that for the validation cohort was sourced from the GSE72094 dataset including 863 LUAD patients. GPX4-related genes were screened out by weighted gene coexpression network analysis and Spearman’s correlation analysis. Then, Cox regression and least absolute shrinkage and selection operator regression analyses were employed to construct a GPS. The ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and GSEA were utilized to evaluate the relationship between GPS and the tumor microenvironment (TME). We constructed and validated a GPS premised on four GPX4-related genes (KIF14, LATS2, PRKCE, and TM6SF1), which could classify LUAD patients into low- and high-score cohorts. The high-risk cohort presented noticeably poorer overall survival (OS) as opposed to the low-risk cohort, meaning that the GPS may be utilized as an independent predictor of the OS of LUAD. The GPS was also adversely correlated with multiple tumor-infiltrating immune cells and immune-related processes and pathways in TME. Furthermore, greater sensitivity to erlotinib and lapatinib were identified in the low-risk cohort based on the GDSC database. Our findings suggest that the GPS can effectively forecast the prognosis of LUAD patients and may possibly regulate the TME of LUAD.

A Comprehensive Prognostic and Immune Analysis of Ferroptosis-Related Genes Identifies SLC7A11 as a Novel Prognostic Biomarker in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is still one of the illnesses with the greatest mortality and morbidity. As a recently identified mode of cellular death, the activation of ferroptosis may promote the effectiveness of antitumor therapies in several types of tumors. However, the expression and clinical significance of Ferroptosis-associated genes in LUAD are still elusive. The RNA sequencing data of LUAD and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) datasets. Subsequently, potential prognostic biomarkers were determined by the use of biological information technology. The R software package “ggalluvial” was applied to structure Sanguini diagram. Herein, our team screened 14 dysregulated ferroptosis-associated genes in LUAD. Among them, only four genes were associated with clinical outcome of LUAD patients, including ATP5MC3, FANCD2, GLS2, and SLC7A11. In addition, we found that high SLC7A11 expression predicted an advanced clinical progression in LUAD patients. Additionally, 8 immune checkpoint genes and 7 immune cells for LUAD were recognized to be related to the expression of SLC7A11. KEGG assays indicated that high expression of SLC7A11 might participate in the modulation of intestinal immune network for IgA generation and Staphylococcus aureus infection. Overall, our findings revealed that SLC7A11 might become a potentially diagnostic biomarker and SLC7A11 might serve as an independent prognosis indicator for LUAD.

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer

Aims: This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Methods: Based on the survival-related representation features yielded by BiDNNs through integrating transcriptomics and epigenomics data, K-means clustering analysis was performed to cluster tumor samples into different survival subgroups. The BiDNNs-based model was validated using tenfold cross-validation and in two independent confirmation cohorts. Results: Using the BiDNNs-based survival stratification model, patients were grouped into two survival subgroups with log-rank p-value = 9.05E-05. The subgroups classification was robustly validated in tenfold cross-validation (C-index = 0.65 ± 0.02) and in two confirmation cohorts (E-GEOD-26253, C-index = 0.609; E-GEOD-62254, C-index = 0.706). Conclusion: We propose and validate a robust and stable BiDNN-based survival stratification model in gastric cancer.