Integrated Analysis of Ferroptosis-Related Biomarker Signatures to Improve the Diagnosis and Prognosis Prediction of Ovarian Cancer

From Defense to Disease: How the Immune System Fuels Epithelial-Mesenchymal Transition in Ovarian Cancer

Ovarian cancer is one of the most deadly gynecological cancers, with over 300 thousand new cases per year, most of which are diagnosed in advanced stages. The limited availability of effective biomarkers and lack of characteristic symptoms make early diagnosis difficult, resulting in a five-year survival rate of 30-40%. Mutations in the BRCA1 and BRCA2 genes and abnormalities of signaling pathways such as PI3K/AKT and TP53 play a key role in the progression of ovarian cancer. The immune system, which can act against tumors, often supports tumor development in the ovarian cancer microenvironment through immunoevasion, which is influenced by cytokines such as IL-6, IL-10, and TGF-β. Epithelial-to-mesenchymal transition (EMT) allows cancer cells to acquire mesenchymal characteristics, increasing their invasiveness and metastatic capacity. Immunological factors, including pro-inflammatory cytokines and signals from the tumor microenvironment regulate the EMT process. This review aims to present the role of EMT in ovarian cancer progression, its interactions with the immune system, and potential biomarkers and therapeutic targets. Modulation of the immune response and inhibition of EMT may constitute the basis for personalized therapies, which opens new possibilities for improving the prognosis and efficacy of treatment in patients with ovarian cancer.

SNRPB and CEP290, predicting the prognosis of diffuse large B cell lymphoma and associated with tumour immune microenvironment

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL), the most prevalent type of non-Hodgkin's lymphoma, exhibits significant correlations with efferocytosis-related molecules (ERMs) concerning invasion, metastasis, and clinical outcomes. This study aims to establish an efferocytosis-related gene signature specifically linked to DLBCL.

METHODS

Key module genes linked to DLBCL were identified via weighted gene co-expression network analysis (WGCNA) in GSE32018. Univariate Cox analysis of GSE31312 revealed ERMs associated with DLBCL survival. Differential expression analysis identified differentially expressed genes (DEGs) between DLBCL subtypes and normal samples. Venn diagram analysis identified common DEGs and key module genes. A DLBCL gene signature was built by using univariate Cox and least absolute shrinkage and selection operator (LASSO) analysis. Gene functional enrichment, immune microenvironment, and immunotherapy analyses compared two risk subgroups. Prognostic gene expression was validated at the single-cell level.

RESULTS

In the GSE32018 dataset, 1760 key module genes related to DLBCL were identified. Using GSE31312, 14 ERMs associated with DLBCL prognosis were determined.Then, an ERMs-related prognostic signature, including small nuclear ribonucleoprotein polypeptides B (SNRPB) and centrosomal protein 290 (CEP290), was established. Independent prognostic analysis showed that the RiskScore derived from this signature was a prognostic factor. Significant immune microenvironment differences were observed between two risk subgroups. Additionally, chemotherapeutic drug sensitivity results indicated the signature could predict therapeutic response. Eventually, expression of SNRPB and CEP290 was confirmed in B cells.

CONCLUSION

The prognostic signature comprised of SNRPB and CEP290 based on ERMs-DEGs was established, providing a theoretical basis and reference value for DLBCL research.

Ferroptosis: mechanism, immunotherapy and role in ovarian cancer

Ovarian cancer is currently the second most common malignant tumor among gynecological cancers worldwide, primarily due to challenges in early diagnosis, high recurrence rates, and resistance to existing treatments. Current therapeutic options are inadequate for addressing the needs of ovarian cancer patients. Ferroptosis, a novel form of regulated cell death with demonstrated tumor-suppressive properties, has gained increasing attention in ovarian malignancy research. A growing body of evidence suggests that ferroptosis plays a significant role in the onset, progression, and incidence of ovarian cancer. Additionally, it has been found that immunotherapy, an emerging frontier in tumor treatment, synergizes with ferroptosis in the context of ovarian cancer. Consequently, ferroptosis is likely to become a critical target in the treatment of ovarian cancer.

Machine learning constructs a T cell-related signature for predicting prognosis and drug sensitivity in ovarian cancer

BACKGROUND

The leading cause of death related to gynecologic cancer is ovarian cancer, which typically has a poor prognosis. T cells are referred to as key mediators of immunosurveillance and tumor eradication, and unbalanced regulation or lack of T cells in tumors result in immunotherapy resistance.

METHODS

The identification of T cell related markers depended on single-cell RNA-seq analysis. Using data from multiple datasets, including TCGA, GSE14764, GSE26193, GSE26712, and GSE140082, we constructed a prognostic signature called TRS (T cell-related signature) using 10 different machine learning algorithms. The correlation between TRS and drug sensitivity were analyzed using the data from GSE91061 and IMvigor210 dataset.

RESULTS

PlsRcox method based TRS was as a risk factor for the clinical outcome of ovarian cancer patients. In comparison with stage, grade and many prognostic signatures, the performance of our TRS in evaluating the clinical outcome was better in ovarian cancer. TRS-based risk score showed distinct association with the level of ESTIMATE score, immune-related function score and immune cells. Moreover, TRS could be used to predict the immunotherapy response and chemotherapy response in ovarian cancer.

CONCLUSION

In conclusion, we constructed a powerful TRS in ovarian cancer, which could accurately predict the clinical outcome of patients and be used to predict the immunotherapy response and chemotherapy response.

Ferroptosis in epithelial ovarian cancer: a burgeoning target with extraordinary therapeutic potential

Epithelial ovarian cancer (EOC) is universally acknowledged as a terrifying women killer for its high mortality. Recent research advances support that ferroptosis, an emerging iron-dependent type of regulated cell death (RCD) triggered by the excessive accumulation of lipid peroxides probably possesses extraordinary therapeutic potential in EOC therapy. Herein, we firstly provide a very concise introduction of ferroptosis. Special emphasis will be put on the ferroptosis's vital role in EOC, primarily covering its role in tumorigenesis and progression of EOC, the capability of reversing chemotherapy resistance, and the research and development of related therapeutic strategies. Furthermore, the construction of ferroptosis-related prognostic prediction systems, and mechanisms of ferroptosis resistance in EOC are also discussed. Finally, we propose and highlight several important yet unanswered problems and some future research directions in this field.

The recent advancements of ferroptosis in the diagnosis, treatment and prognosis of ovarian cancer

Ovarian cancer affects the female reproductive system and is the primary cause of cancer related mortality globally. The imprecise and non-specific nature of ovarian cancer symptoms often results in patients being diagnosed at an advanced stage, with metastatic lesions extending beyond the ovary. This presents a significant clinical challenge and imposes a substantial economic burden on both patients and society. Despite advancements in surgery, chemotherapy, and immunotherapy, the prognosis for most patients with ovarian cancer remains unsatisfactory. Therefore, the development of novel treatment strategies is imperative. Ferroptosis, a distinct form of regulated cell death, characterized by iron-dependent lipid peroxidation, differs from autophagy, apoptosis, and necrosis, and may hold promise as a novel cell death. Numerous studies have demonstrated the involvement of ferroptosis in various conventional signaling pathways and biological processes. Recent investigations have revealed the significant contribution of ferroptosis in the initiation, progression, and metastasis of diverse malignant tumors, including ovarian cancer. Moreover, ferroptosis exhibits a synergistic effect with chemotherapy, radiotherapy, and immunotherapy in restraining the proliferation of ovarian cancer cells. The aforementioned implies that ferroptosis holds considerable importance in the management of ovarian cancer and has the potential to serve as a novel therapeutic target. The present review provides a comprehensive overview of the salient features of ferroptosis, encompassing its underlying mechanisms and functional role in ovarian cancer, along with the associated signaling pathways and genes. Furthermore, the review highlights the prospective utility of ferroptosis in the treatment of ovarian cancer.

Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer

BACKGROUND

Ovarian cancer is one of the deadliest malignancies among females, generally having a poor prognosis. The PI3K/Akt pathway plays a vital role in the oncogenesis and progression of many types of cancer. Limited studies have fully clarified the role of PI3K/Akt pathway in the prognosis of ovarian cancer and its correlation with drug sensitivity.

METHODS

A prognostic PI3K/Akt pathway related signature (PRS) was constructed with 10 machine learning algorithms using TCGA, GSE14764, GSE26193, GSE26712, GSE63885 and GSE140082 datasets. Gaussian mixture and logistic regression were performed to identify the optimal models for classifying lymphatic and venous invasion.

RESULTS

The optimal prognostic PRS developed by Lasso + survivalSVM algorithm acted as an independent risk factor for overall survival (OS) of ovarian cancer patients and had a good performance in evaluating OS rate of ovarian cancer patients. Significant correlation was obtained between PRS-based risk score and Immune score, ESTIMATE score, immune cells and cancer-related hallmarks. Low risk score indicated a lower immune escape score, TIDE score, and higher PD1&CTLA4 immunophenoscore in ovarian cancer. Moreover, PRS-based risk score acted as an indicator for drug sensitivity in the immunotherapy and chemotherapy of ovarian cancer patients.

CONCLUSIONS

All in all, our study developed a prognostic PRS showing powerful and good performance in predicting clinical outcome of ovarian cancer patients. PRS could serve as an indicator for drug sensitivity in the chemotherapy and immunotherapy.

Ferroptosis-related gene HIC1 in the prediction of the prognosis and immunotherapeutic efficacy with immunological activity

Background

Hypermethylated in Cancer 1 (HIC1) was originally confirmed as a tumor suppressor and has been found to be hypermethylated in human cancers. Although growing evidence has supported the critical roles of HIC1 in cancer initiation and development, its roles in tumor immune microenvironment and immunotherapy are still unclear, and no comprehensive pan-cancer analysis of HIC1 has been conducted.

Methods

HIC1 expression in pan-cancer, and differential HIC1 expression between tumor and normal samples were investigated. Immunohistochemistry (IHC) was employed to validate HIC1 expression in different cancers by our clinical cohorts, including lung cancer, sarcoma (SARC), breast cancer, and kidney renal clear cell carcinoma (KIRC). The prognostic value of HIC1 was illustrated by Kaplan-Meier curves and univariate Cox analysis, followed by the genetic alteration analysis of HIC1 in pan-cancer. Gene Set Enrichment Analysis (GSEA) was conducted to illustrate the signaling pathways and biological functions of HIC1. The correlations between HIC1 and tumor mutation burden (TMB), microsatellite instability (MSI), and the immunotherapy efficacy of PD-1/PD-L1 inhibitors were analyzed by Spearman correlation analysis. Drug sensitivity analysis of HIC1 was performed by extracting data from the CellMiner™ database.

Results

HIC1 expression was abnormally expressed in most cancers, and remarkable associations between HIC1 expression and prognostic outcomes of patients in pan-cancer were detected. HIC1 was significantly correlated with T cells, macrophages, and mast cell infiltration in different cancers. Moreover, GSEA revealed that HIC1 was significantly involved in immune-related biological functions and signaling pathways. There was a close relationship of HIC1 with TMB and MSI in different cancers. Furthermore, the most exciting finding was that HIC1 expression was significantly correlated with the response to PD-1/PD-L1 inhibitors in cancer treatment. We also found that HIC1 was significantly correlated with the sensitivity of several anti-cancer drugs, such as axitinib, batracylin, and nelarabine. Finally, our clinical cohorts further validated the expression pattern of HIC1 in cancers.

Conclusions

Our investigation provided an integrative understanding of the clinicopathological significance and functional roles of HIC1 in pan-cancer. Our findings suggested that HIC1 can function as a potential biomarker for predicting the prognosis, immunotherapy efficacy, and drug sensitivity with immunological activity in cancers.

Identification of iron metabolism-related predictive markers of endometriosis and endometriosis-relevant ovarian cancer

Endometriosis is associated with ovarian cancers, mainly endometrioid and clear-cell carcinomas. Iron metabolism has been shown to play a role in endometriosis. Therefore, it is vital to explore the relationship between iron metabolism and ovarian cancer and to identify novel markers for diagnostics and therapeutics. The endometriosis dataset GSE51981 and the ovarian cancer dataset GSE26712 were obtained from the gene expression omnibus database, and differentially expressed genes were identified. Iron metabolism genes were obtained from molecular signatures database, and hub genes from the 3 datasets were obtained. Seven hub genes were identified by bioinformatic analysis, and 3 hub genes (NCOA4, ETFDH, and TYW1) were further selected by logistic regression, which were verified in an independent endometriosis dataset (GSE25628) and ovarian cancer dataset (GSE14407), showing good predictive diagnostic value (area under the receiver operating characteristic curve of 0.88 and 0.9, respectively). Gene Ontology, gene set enrichment analysis, and immune infiltration analysis further confirmed the related functions, pathways, and immune relationship between iron metabolism and ovarian cancer. This study highlights the potential of targeting iron metabolism in the prevention of potential ovarian cancer and in the further exploration of endometriosis and endometriosis-relevant ovarian cancer therapeutics.

ACSF2-mediated ferroptosis is involved in ulcerative colitis

AIMS

To investigate the role of ferroptosis-related genes in the induction into ulcerative colitis (UC) and provide new strategies for the prevention and treatment of UC.

MATERIALS AND METHODS

We screened the UC dataset from the GEO database and obtained ferroptosis-related genes from FerrDB and GeneCards. The R package "CancerSubtypes" was performed to identify the UC subtypes, followed by Short Time-series Expression Miner (STEM) analysis. The key genes were further screened by machine learning algorithms (LASSO and SVM-RFE). WB and IHC verified the changes in the expression content of ACSF2 in vivo and in vitro models. The changes in intracellular ROS and Fe2 + levels were detected.

KEY FINDINGS

Through bioinformatics analysis, we selected the ferroptosis-related gene ACSF2 (acyl CoA synthetase family member 2), which is significantly associated with immune-related pathways "Toll-like receptor signaling pathway", "NF-kappa B signaling pathway" and "NOD-like receptor signaling pathway". The expression of ACSF2 was significantly down-regulated in UC animals, Salmonella typhimurium colitis models and cell models, while the ferroptosis inhibitor Fer-1 reversed the expression of ACSF2 in LPS-induced cell models, indicating that the ferroptosis-related gene ACSF2 plays an important role in mediating ferroptosis and inflammation, and is expected to become a new target for further research.

SIGNIFICANCE

Ferroptosis is closely associated with the development of UC, and the ferroptosis-related gene ACSF2 can be used as a potential biomarker for the diagnosis and treatment of UC.

Construction and validation of a novel ferroptosis-related signature for evaluating prognosis and immune microenvironment in ovarian cancer

Ovarian cancer (OV) is the most lethal form of gynecological malignancy worldwide, with limited therapeutic options and high recurrence rates. However, research focusing on prognostic patterns of ferroptosis-related genes (FRGs) in ovarian cancer is still lacking. From the 6,406 differentially expressed genes (DEGs) between TCGA-OV (n = 376) and GTEx cohort (n = 180), we identified 63 potential ferroptosis-related genes. Through the LASSO-penalized Cox analysis, 3 prognostic genes, SLC7A11, ZFP36, and TTBK2, were finally distinguished. The time-dependent ROC curves and K-M survival analysis performed powerful prognostic ability of the 3-gene signature. Stepwise, we constructed and validated the nomogram based on the 3-gene signature and clinical features, with promising prognostic value in both TCGA (p-value < .0001) and ICGC cohort (p-value = .0064). Gene Set Enrichment Analysis elucidated several potential pathways between the groups stratified by 3-gene signature, while the m6A gene analysis implied higher m6A level in the high-risk group. We applied the CIBERSORT algorithm to distinct tumor immune microenvironment between two groups, with less activated dendritic cells (DCs) and plasma cells, more M0 macrophages infiltration, and higher expression of key immune checkpoint molecules (CD274, CTLA4, HAVCR2, and PDCD1LG2) in the high-risk group. In addition, the low-risk group exhibited more favorable immunotherapy and chemotherapy responses. Collectively, our findings provided new prospects in the role of ferroptosis-related genes, as a promising prediction tool for prognosis and immune responses, in order to assist personalized treatment decision-making among ovarian cancer 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.

Seven Fatty Acid Metabolism-Related Genes as Potential Biomarkers for Predicting the Prognosis and Immunotherapy Responses in Patients with Esophageal Cancer

Background: Esophageal cancer (ESCA) is a major cause of cancer-related mortality worldwide. Altered fatty acid metabolism is a hallmark of cancer. However, studies on the roles of fatty acid metabolism-related genes (FRGs) in ESCA remain limited. Method: We identified differentially expressed FRGs (DE-FRGs). Then, the DE-FRGs prognostic model was constructed and validated using a comprehensive analysis. Moreover, the correlation between the risk model and clinical characteristics was investigated. A nomogram for predicting survival was established and evaluated. Subsequently, the difference in tumor microenvironment (TME) was compared between two risk groups. The sensitivity of key DE-FRGs to chemotherapeutic interventions and their correlation with immune cells were investigated. Finally, DEGs between two risk groups were measured and the prognostic value of key DE-FRGs in ESCA was confirmed in other databases. Results: A prognostic model was constructed based on seven selected DEG-FRGs. TNM staging and CD8+ T cells were significantly correlated with high-risk groups. Low-risk groups exhibited more infiltrated M0 macrophages, an activation of type II interferon (IFN-γ) responses, and were found to be more suitable for immunotherapy. Seven key DE-FRGs with prognostic value were found to be considerably influenced by different chemotherapy drugs. Conclusion: A prognostic model based on seven DE-FRGs may efficiently predict patient prognosis and immunotherapy response, helping to develop individualized treatment strategies in ESCA.

LPCAT3 is a potential prognostic biomarker and may be correlated with immune infiltration and ferroptosis in acute myeloid leukemia: a pan-cancer analysis

BACKGROUND

Recent studies have highlighted the critical role of lysophosphatidylcholine acyltransferase 3 (LPCAT3) during cancer development. However, the abnormal expression and prognostic significance of pan-cancer have not been determined.

METHODS

We explored the expression level and prognostic value of LPCAT3 in 33 cancers by bioinformatics techniques, and comprehensively studied the biological function and immune infiltration based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases as well as many online websites.

RESULTS

LPCAT3 is significantly upregulated in many cancers, and it is associated with prognosis. Pan-cancer Cox regression analysis indicated that the high expression of LPCAT3 was associated with poor prognosis in acute myeloid leukemia (AML), lower-grade glioma (LGG), ovarian cancer (OV), and uveal melanoma (UVM), while better prognosis in kidney renal clear cell carcinoma (KIRC) (all P<0.05). Further analysis indicated that higher LPCAT3 expression in most cancers markedly decreased the infiltration of immune cells, except diffuse large B-cell lymphoma (DLBC), AML, LGG, stomach adenocarcinoma (STAD), and UVM. In contrast, the expression level of LPCAT3 was positively correlated with most immune checkpoints in colon adenocarcinoma (COAD), DLBC, LGG, liver hepatocellular carcinoma (LIHC), and UVM. Additionally, LPCAT3 expression was associated with tumor mutational burden (TMB) in 4 cancer types, while microsatellite instability (MSI) was in 3 cancer types. Functional enrichment analysis showed LPCAT3 upregulation was highly associated with lipid metabolism and ferroptosis processes. In addition, the result of prediction drug response suggested that B-cell lymphoma 2 (BCL2) inhibitors and Midostaurin may be a potential treatment option for AML with low-LPCAT3 expression.

CONCLUSIONS

LPCAT3 expression is increased in multiple cancers. Overexpression of LPCAT3 is associated with poor prognosis and tumor immune microenvironment in many cancers, especially in AML. Our results showed that the oncogene of LPCAT3 may serve as a potential prognostic biomarker and/or therapeutic target in AML patients.

Immunotherapeutic Value of Transcription Factor 19 (TCF19) Associated with Renal Clear Cell Carcinoma: A Comprehensive Analysis of 33 Human Cancer Cases

Background

We aimed to study the relationship between transcription factor 19 (TCF19) and cancer immunotherapy in the 33 types of human cancers.

Methods

The Cancer Genome Atlas database was analyzed to obtain the gene expression data and clinical characteristics for the cases of 33 types of cancers. GSE67501, GSE78220, and IMvigor 210 were included in the immunotherapy cohorts. Relevant data were obtained by analyzing the gene expression database. The prognostic value of TCF19 was determined by analyzing various clinical parameters, such as survival duration, age, the stage of the tumor, and sex of the patients. The single-sample gene set enrichment analysis method was used to determine the activity of TCF19 and the method was also used to assess the differences between the TCF19 transcriptome and protein levels. The correlation between TCF19 and various immune processes and elements such as immunosuppressants, stimulants, and major histocompatibility complexes were analyzed to gain insights into the role of TCF19. The coherent paths associated with the process of TCF19 signal transduction and the influence of TCF19 on immunotherapy biomarkers have also been discussed herein. Finally, three independent immunotherapy methods were used to understand the relationship between TCF19 and immunotherapy response.

Results

It was observed that TCF19 was not significantly influenced by the age (5/33), sex (3/33), or tumor stage (3/21) of cancer patients. But the results revealed that TCF19 exhibited a potential prognostic value and could predict the survival rate of the patients. In some cases of this study, the activity and expression of TCF19 were taken at the same level (7/33).

Conclusion

TCF19 is strongly related to immune cell infiltration, immunomodulators, and immunotherapy markers. Our study demonstrated that high expression levels of TCF19 are strongly linked with the immune-related pathways. Nevertheless, it is noteworthy that TCF19 is not significantly associated with immunotherapy response.

Current progress of ferroptosis study in ovarian cancer

Tumors are the leading cause of death all over the world, among which ovarian cancer ranks the third in gynecological malignancies. The current treatment for ovarian cancer is liable to develop chemotherapy resistance and high recurrence rate, in which a new strategy is demanded. Ferroptosis, a newly discovered manner of regulatory cell death, is shown to be induced by massive iron-dependent accumulation of lipid reactive oxygen species. With the in-depth study of ferroptosis, its associated mechanism with various tumors is gradually elucidated, including ovarian tumor, which probably promotes the application of ferroptosis in treating ovarian cancer. To this end, this review will focus on the history and current research progress of ferroptosis, especially its regulation mechanism, and its potential application as a novel treatment strategy for ovarian cancer.

MicroRNA-147a Targets SLC40A1 to Induce Ferroptosis in Human Glioblastoma

Objective. Glioblastoma is one of the most common malignant tumors in the brain, and these glioblastoma patients have very poor prognosis. Ferroptosis is involved in the progression of various tumors, including the glioblastoma. This study aims to determine the involvement of microRNA (miR)-147a in regulating ferroptosis of glioblastoma in vitro. Methods. Human glioblastoma cell lines were transfected with the inhibitor, mimic and matched negative controls of miR-147a in the presence or absence of ferroptotic inducers. To knock down the endogenous solute carrier family 40 member 1 (SLC40A1), cells were transfected with the small interfering RNA against SLC40A1. In addition, cells with or without the miR-147a mimic treatment were also incubated with temozolomide (TMZ) to investigate whether miR-147a overexpression could sensitize human glioblastoma cells to TMZ chemotherapy in vitro. Results. We found that miR-147a level was decreased in human glioblastoma tissues and cell lines and that the miR-147a mimic significantly suppressed the growth of glioblastoma cells in vitro. In addition, miR-147a expression was elevated in human glioblastoma cells upon erastin or RSL3 stimulation. Treatment with the miR-147a mimic significantly induced ferroptosis of glioblastoma cells, and the ferroptotic inhibitors could block the miR-147a mimic-mediated tumor suppression in vitro. Conversely, the miR-147a inhibitor prevented erastin- or RSL3-induced ferroptosis and increased the viability of glioblastoma cells in vitro. Mechanistically, we determined that miR-147a directly bound to the 3 $\prime$ -untranslated region of SLC40A1 and inhibited SLC40A1-mediated iron export, thereby facilitating iron overload, lipid peroxidation, and ferroptosis. Furthermore, miR-147a mimic-treated human glioblastoma cells exhibited higher sensitivity to TMZ chemotherapy than those treated with the mimic control in vitro. Conclusion. We for the first time determine that miR-147a targets SLC40A1 to induce ferroptosis in human glioblastoma in vitro.

Ferroptosis, necroptosis, and pyroptosis in the occurrence and development of ovarian cancer

Ovarian cancer (OC) is one of the most common malignancies that causes death in women and is a heterogeneous disease with complex molecular and genetic changes. Because of the relatively high recurrence rate of OC, it is crucial to understand the associated mechanisms of drug resistance and to discover potential target for rational targeted therapy. Cell death is a genetically determined process. Active and orderly cell death is prevalent during the development of living organisms and plays a critical role in regulating life homeostasis. Ferroptosis, a novel type of cell death discovered in recent years, is distinct from apoptosis and necrosis and is mainly caused by the imbalance between the production and degradation of intracellular lipid reactive oxygen species triggered by increased iron content. Necroptosis is a regulated non-cysteine protease–dependent programmed cell necrosis, morphologically exhibiting the same features as necrosis and occurring via a unique mechanism of programmed cell death different from the apoptotic signaling pathway. Pyroptosis is a form of programmed cell death that is characterized by the formation of membrane pores and subsequent cell lysis as well as release of pro-inflammatory cell contents mediated by the abscisin family. Studies have shown that ferroptosis, necroptosis, and pyroptosis are involved in the development and progression of a variety of diseases, including tumors. In this review, we summarized the recent advances in ferroptosis, necroptosis, and pyroptosis in the occurrence, development, and therapeutic potential of OC.

Research progress in the role and mechanism of LPCAT3 in metabolic related diseases and cancer

Lysophosphatidylcholine acyltransferases (LPCATs) are among the lysophopholipid acyltransferases (LPLATs) that specifically regulate the abundance of different phosphatidylcholine (PC) species in a variety of cell and tissue types, thereby playing an important role in lipid metabolism and homeostasis. Lysophosphatidylcholine acyltransferase 3 (LPCAT3, MBOAT5) is a member of the LPCAT family that primarily regulates the levels of arachidonic PC species. LPCAT3 is regulated by the liver X receptor, which plays an important role in lipoprotein production in the liver and small intestine. Increasing lines of research have demonstrated that LPCAT3 plays important roles in the occurrence and development of many diseases, such as atherosclerosis, intestinal tumors, and nonalcoholic steatohepatitis (NASH). The development of many diseases has been linked to the proinflammatory effects of LPCAT3. This review focuses on the current knowledge of LPCAT3, including its function and mechanism in different diseases. We aim to provide a comprehensive and in-depth understanding of LPCAT3 and to provide new ideas for the treatment of some diseases.