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

Ligusticum chuanxiong Hort. Ameliorates Neuropathic Pain by Regulating Microglial M1 Polarization: A Study Based on Network Pharmacology

Background

In traditional Chinese medicine, Ligusticum chuanxiong Hort. (LCH) is used to treat neuropathic pain (NP). This study was performed to investigate the underlying pharmacological mechanisms.

Methods

The main components of the LCH were obtained from the TCMSP database. The targets of the active components were obtained using the Swiss Target Prediction database and HERB database. The NP-related genes were obtained from the CTD database and GeneCard database. Protein-protein interaction (PPI) network was constructed using the STRING platform and Cytoscape 3.9.0 software. GO and KEGG enrichment analyses were performed using the DAVID database. Interactions between the key components and hub target proteins were verified using molecular docking and molecular dynamics simulation. In addition, microglial cell line HMC3 was induced to polarize to the M1 phenotype using 100 ng/mL lipopolysaccharide (LPS). Quantitative real-time polymerase chain reaction (qRT-PCR), Western blot and enzyme-linked immunosorbent assays were used to detect the expression levels of M1 markers and inflammatory factors, respectively.

Results

Seven LCH active components of LCH were identified, corresponding to 387 target genes. 2019 NP-related genes were obtained, and a total of 174 NP-related genes were identified as target genes that could be modulated by LCH. Beta-sitosterol, senkyunone, wallichilide, myricanone, and mandenol were considered as the key components of LCH in the treatment of NP. SRC, BCL2, AKT1, HIF1A and HSP90AA1 were identified as the hub target proteins. GO analysis showed that 328 biological processes, 61 cell components, and 85 molecular functions were likely modulated by the components of LCH, and KEGG enrichment analysis showed that 132 signaling pathways were likely modulated by the components of LCH. Beta-sitosterol, senkyunone, wallichilide, myricanone, and mandenol showed good binding activity with hub target proteins including SRC, BCL2, AKT1, and HSP90AA1. In addition, beta-sitosterol inhibited LPS-induced M1 polarization in HMC3 in vitro.

Conclusion

This study provides a theoretical basis for the application of LCH in the treatment of NP through multicomponent, multitarget, and multiple pathways.

Disulfidptosis-related signature elucidates the prognostic, immunologic, and therapeutic characteristics in ovarian cancer

Introduction

Ovarian cancer (OC) is the deadliest malignancy in gynecology, but the mechanism of its initiation and progression is poorly elucidated. Disulfidptosis is a novel discovered type of regulatory cell death. This study aimed to develop a novel disulfidptosis-related prognostic signature (DRPS) for OC and explore the effects and potential treatment by disulfidptosis-related risk stratification.

Methods

The disulfidptosis-related genes were first analyzed in bulk RNA-Seq and a prognostic nomogram was developed and validated by LASSO algorithm and multivariate cox regression. Then we systematically assessed the clinicopathological and mutational characteristics, pathway enrichment analysis, immune cell infiltration, single-cell-level expression, and drug sensitivity according to DRPS.

Results

The DRPS was established with 6 genes (MYL6, PDLIM1, ACTN4, FLNB, SLC7A11, and CD2AP) and the corresponding prognostic nomogram was constructed based on the DRPS, FIGO stage, grade, and residual disease. Stratified by the risk score derived from DRPS, patients in high-risk group tended to have worse prognosis, lower level of disulfidptosis, activated oncogenic pathways, inhibitory tumor immune microenvironment, and higher sensitivity to specific drugs including epirubicin, stauroporine, navitoclax, and tamoxifen. Single-cell transcriptomic analysis revealed the expression level of genes in the DRPS significantly varied in different cell types between tumor and normal tissues. The protein-level expression of genes in the DRPS was validated by the immunohistochemical staining analysis.

Conclusion

In this study, the DRPS and corresponding prognostic nomogram for OC were developed, which was important for OC prognostic assessment, tumor microenvironment modification, drug sensitivity prediction, and exploration of potential mechanisms in tumor development.

ANGPTL4 regulates ovarian cancer progression by activating the ERK1/2 pathway

BACKGROUND

Ovarian cancer (OC) has the highest mortality rate among all gynecological malignancies. A hypoxic microenvironment is a common feature of solid tumors, including ovarian cancer, and an important driving factor of tumor cell survival and chemo- and radiotherapy resistance. Previous research identified the hypoxia-associated gene angiopoietin-like 4 (ANGPTL4) as both a pro-angiogenic and pro-metastatic factor in tumors. Hence, this work aimed to further elucidate the contribution of ANGPTL4 to OC progression.

METHODS

The expression of hypoxia-associated ANGPTL4 in human ovarian cancer was examined by bioinformatics analysis of TCGA and GEO datasets. The CIBERSORT tool was used to analyze the distribution of tumor-infiltrating immune cells in ovarian cancer cases in TCGA. The effect of ANGPTL4 silencing and overexpression on the proliferation and migration of OVCAR3 and A2780 OC cells was studied in vitro, using CCK-8, colony formation, and Transwell assays, and in vivo, through subcutaneous tumorigenesis assays in nude mice. GO enrichment analysis and WGCNA were performed to explore biological processes and genetic networks associated with ANGPTL4. The results obtained were corroborated in OC cells in vitro by western blotting.

RESULTS

Screening of hypoxia-associated genes in OC-related TCGA and GEO datasets revealed a significant negative association between ANGPTL4 expression and patient survival. Based on CIBERSORT analysis, differential representation of 14 distinct tumor-infiltrating immune cell types was detected between low- and high-risk patient groups. Silencing of ANGPTL4 inhibited OVCAR3 and A2780 cell proliferation and migration in vitro and reduced the growth rate of xenografted OVCAR3 cells in vivo. Based on results from WGCNA and previous studies, western blot assays in cultured OC cells demonstrated that ANGPTL4 activates the Extracellular signal-related kinases 1 and 2 (ERK1/2) pathway and this results in upregulation of c-Myc, Cyclin D1, and MMP2 expression. Suggesting that the above mechanism mediates the pro-oncogenic actions of ANGPTL4T in OC, the pro-survival effects of ANGPTL4 were largely abolished upon inhibition of ERK1/2 signaling with PD98059.

CONCLUSIONS

Our work suggests that the hypoxia-associated gene ANGPTL4 stimulates OC progression through activation of the ERK1/2 pathway. These findings may offer a new prospect for targeted therapies for the treatment of OC.

Role of SLC7A11/xCT in Ovarian Cancer

Ovarian cancer is one of the most dangerous gynecologic cancers worldwide and has a high fatality rate due to diagnosis at an advanced stage of the disease as well as a high recurrence rate due to the occurrence of chemotherapy resistance. In fact, chemoresistance weakens the therapeutic effects, worsening the outcome of this pathology. Solute Carrier Family 7 Member 11 (SLC7A11, also known as xCT) is the functional subunit of the Xc- system, an anionic L-cystine/L-glutamate antiporter expressed on the cell surface. SLC7A11 expression is significantly upregulated in several types of cancers in which it can inhibit ferroptosis and favor cancer cell proliferation, invasion and chemoresistance. SLC7A11 expression is also increased in ovarian cancer tissues, suggesting a possible role of this protein as a therapeutic target. In this review, we provide an overview of the current literature regarding the role of SLC7A11 in ovarian cancer to provide new insights on SLC7A11 modulation and evaluate the potential role of SLC7A11 as a therapeutic target.

Pancancer analysis reveals the role of disulfidptosis in predicting prognosis, immune infiltration and immunotherapy response in tumors

Disulfidptosis has been reported as a novel cell death process, suggesting a therapeutic strategy for cancer treatment. Herein, we constructed a multiomics data analysis to reveal the effects of disulfidptosis in tumors. Data for 33 kinds of tumors were downloaded from UCSC Xene, and disulfidptosis-related genes (DRGs) were selected from a previous study. After finishing processing data by the R packages, the expression and coexpression of DRGs in different tumors were assessed as well as copy number variations. The interaction network was drawn by STRING, and the activity of disulfidptosis was compared to the single-sample gene set enrichment analysis algorithm. Subsequently, the differences in DRGs for prognosis and clinicopathological features were evaluated, and the tumor immune microenvironment was assessed by the TIMER and TISCH databases. Tumor mutation burden, stem cell features and microsatellite instability were applied to predict drug resistance, and the expression of checkpoints was identified for the prediction of immunotherapy. Moreover, the TCIA, CellMiner and Enrichr databases were also utilized for selecting potential agents. Ten DRGs were differentially expressed in tumors, and the plots of coexpression and interaction revealed their correlation. Survival analysis suggested SLC7A11 as the most prognosis-related DRG with the most significant results. Additionally, the comparison also reflected the differences in DRGs in the status of pathologic lymph node metastasis for 5 types of tumors. The tumor immune microenvironment showed commonality among tumors based on immune infiltration and single-cell sequencing, and the analysis of tumor mutation burden, stemness and microsatellite instability showed a mostly positive correlation with DRGs. Moreover, referring to the prediction about clinical treatment, most DRGs can enhance sensitivity to chemotherapeutic agents but decrease the response to immune inhibitors with increasing expression. In this study, a primarily synthetic landscape of disulfidptosis in tumors was established and provided guidance for further exploration and investigation.

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.

A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning

BACKGROUND

Ovarian cancer ranks the leading cause of gynecologic cancer-related death in the United States and the fifth most common cause of cancer-related mortality among American women. Increasing evidences have highlighted the vital role of macrophages M2/M1 proportion in tumor progression, prognosis and immunotherapy.

METHODS

Weighted gene co-expression network analysis (WGCNA) was performed to identify macrophages related markers. Integrative procedure including 10 machine learning algorithms were performed to develop a prognostic macrophage related signature (MRS) with TCGA, GSE14764, GSE140082 datasets. The role of MRS in tumor microenvironment (TME) and therapy response was evaluated with the data of CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER and EPIC, GSE91061 and IMvigor210 dataset.

RESULTS

The optimal MRS developed by the combination of CoxBoost and StepCox[forward] algorithm served as an independent risk factor in ovarian cancer. Compared with stage, grade and other established prognostic signatures, the current MRS had a better performance in predicting the overall survival rate of ovarian cancer patients. Low risk score indicated a higher TME score, higher level of immune cells, higher immunophenoscore, higher tumor mutational burden, lower TIDE score and lower IC50 value in ovarian cancer. The survival prediction nomogram had a good potential for clinical application in predicting the 1-, 3-, and 5-year overall survival rate of ovarian cancer patients.

CONCLUSION

All in all, the current study constructed a powerful prognostic MRS for ovarian cancer patients using 10 machine learning algorithms. This MRS could predict the prognosis and drug sensitivity in ovarian cancer.

A comprehensive overview of recent developments on the mechanisms and pathways of ferroptosis in cancer: the potential implications for therapeutic strategies in ovarian cancer

Cancer cells adapt to environmental changes and alter their metabolic pathways to promote survival and proliferation. Metabolic reprogramming not only allows tumor cells to maintain a reduction-oxidation balance by rewiring resources for survival, but also causes nutrient addiction or metabolic vulnerability. Ferroptosis is a form of regulated cell death characterized by the iron-dependent accumulation of lipid peroxides. Excess iron in ovarian cancer amplifies free oxidative radicals and drives the Fenton reaction, thereby inducing ferroptosis. However, ovarian cancer is characterized by ferroptosis resistance. Therefore, the induction of ferroptosis is an exciting new targeted therapy for ovarian cancer. In this review, potential metabolic pathways targeting ferroptosis were summarized to promote anticancer effects, and current knowledge and future perspectives on ferroptosis for ovarian cancer therapy were discussed. Two therapeutic strategies were highlighted in this review: directly inducing the ferroptosis pathway and targeting metabolic vulnerabilities that affect ferroptosis. The overexpression of SLC7A11, a cystine/glutamate antiporter SLC7A11 (also known as xCT), is involved in the suppression of ferroptosis. xCT inhibition by ferroptosis inducers (e.g., erastin) can promote cell death when carbon as an energy source of glucose, glutamine, or fatty acids is abundant. On the contrary, xCT regulation has been reported to be highly dependent on the metabolic vulnerability. Drugs that target intrinsic metabolic vulnerabilities (e.g., GLUT1 inhibitors, PDK4 inhibitors, or glutaminase inhibitors) predispose cancer cells to death, which is triggered by decreased nicotinamide adenine dinucleotide phosphate generation or increased reactive oxygen species accumulation. Therefore, therapeutic approaches that either directly inhibit the xCT pathway or target metabolic vulnerabilities may be effective in overcoming ferroptosis resistance. Real-time monitoring of changes in metabolic pathways may aid in selecting personalized treatment modalities. Despite the rapid development of ferroptosis-inducing agents, therapeutic strategies targeting metabolic vulnerability remain in their infancy. Thus, further studies must be conducted to comprehensively understand the precise mechanism linking metabolic rewiring with ferroptosis.