Genomic, Immunological, and Clinical Characterization of Pyroptosis in Ovarian Cancer

A Novel pyroptosis-related signature for predicting prognosis and evaluating tumor immune microenvironment in ovarian cancer

Ovarian cancer (OV) is the most fatal gynecological malignant tumor worldwide, with high recurrence rates and great heterogeneity. Pyroptosis is a newly-acknowledged inflammatory form of cell death with an essential role in cancer progression, though studies focusing on prognostic patterns of pyroptosis in OV are still lacking. Our research filtered 106 potential pyroptosis-related genes (PRGs) among the 6406 differentially expressed genes (DEGs) between the 376 TCGA-OV samples and 180 normal controls. Through the LASSO-Cox analysis, the 6-gene prognostic signature, namely CITED2, EXOC6B, MIA2, NRAS, SETBP1, and TRPV46, was finally distinguished. Then, the K-M survival analysis and time-dependent ROC curves demonstrated the promising prognostic value of the 6-gene signature (p-value < 0.0001). Furthermore, based on the signature and corresponding clinical features, we constructed and validated a nomogram model for 1-year, 2-year, and 3-year OV survival, with reliable prognostic values in TCGA-OV (p-value < 0.001) and ICGC-OV cohort (p-value = 0.040). Pathway analysis enriched several critical pathways in cancer, refer to the pyroptosis-related signature, while the m6A analysis indicated greater m6A level in high-risk group. We assessed tumor immune microenvironment through the CIBERSORT algorithm, which demonstrated the upregulation of M1 Macrophages and activated DCs and high expression of key immune checkpoint molecules (CTLA4, PDCD1LG2, and HAVCR2) in high-risk group. Interestingly, the high-risk group exhibited poor sensitivity towards immunotherapy and better sensitivity towards chemotherapies, including Vinblastine, Docetaxel, and Sorafenib. Briefly, the pyroptosis-related signature was a promising tool to predict prognosis and evaluate immune responses, in order to assist decision-making for OV patients in the realm of precision medicine.

Identification of N6-methylandenosine related lncRNA signatures for predicting the prognosis and therapy response in colorectal cancer patients

Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play an important role in CRC progression. Nonetheless, few studies have focused on the impact of m6A-related lncRNAs on the prognosis, tumor microenvironment (TME) and treatment of CRC. In this study, 1707 m6A-related lncRNAs were identified through Pearson correlation analysis and Weighted co-expression network analysis (WGCNA) using The Cancer Genome Atlas (TCGA) cohort. Then, 28 m6A-related prognostic lncRNAs were screened by univariate Cox regression analysis, followed by identifying two clusters by consensus clustering analysis. A prognostic model consisted of 8 lncRNA signatures was constructed by the least absolute shrinkage and selection operator (LASSO). Kaplan–Meier curve analysis and a nomogram were performed to investigate the prognostic ability of this model. The risk score of prognostic model act as an independent risk factor for OS rate. Functional enrichment analysis indicated that lncRNA signatures related tumor immunity. The low-risk group characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of OS. Moreover, the lncRNA signatures were significantly associated with the cancer stem cell (CSC) index and drug sensitivity. In addition, 3 common immune genes shared by the lncRNA signatures were screened out. We found that these immune genes were widely distributed in 2 cell types of TME. Finally, a ceRNA network was constructed to identify ZEB1-AS1 regulatory axis in CRC. We found that ZEB1-AS1 was significantly overexpressed in tumor tissues, and was related to the metastasis of EMT and the chemoresistance of 5-Fu in CRC. Therefore, our study demonstrated the important role of m6A-related lncRNAs in TME remodeling. Moreover, these results illustrated the levels of ZEB1-AS1 might be valuable for predicting the progression and prognosis of CRC, and further provided a new target for the diagnosis and treatment of CRC patients.

Angiotensin II can trigger HSC-LX2 pyroptosis through both classical and non-classical pathways

BACKGROUND

Current evidence suggests that liver fibrosis is reversible even at late stages. Pyroptosis is reportedly regulated by classical and non-classical pathways and is also involved in the activation of the human hepatic stellate cell line LX2. This study sought to identify regulatory pathways that pyroptosis of HSC during AngII-ROS-induced HSC activation and provides novel insights for anti-fibrosis therapy by targeting HSC.

MATERIALS AND METHODS

All experiments were conducted in HSC-LX2. The expressions of α-SMA, NLRP3, Caspases-1, -4, -5, ASC and GSDMD-N were detected in HSC-LX2 cells induced with AngII by Western blot and qRT-PCR. CCK8 was used to detect cell proliferation and activity. 2'-7'dichlorofluorescin diacetate (DCFH-DA) was used to measure ROS generation. An LDH assay kit was used to detect LDH released from damaged cells, and ELISA was used to quantify IL-18 and IL-1β levels.

RESULTS

After AngII stimulation, HSC-LX2 cell viability, ROS, LDH, IL-18, and IL-1β were increased compared with Control group. At the same time, the protein and mRNA levels of α-SMA, NLRP3, Caspases-1, -4, -5, ASC and GSDMD-N were increased. In addition, after NAC and NSA treatment, LDH, IL-18 and IL-1β levels and the protein and mRNA expression of α-SMA, Caspases-4 and -5, and GSDMD-N were decreased.

CONCLUSION

HSC-LX2 pyroptosis induced by AngII-ROS is mediated by the classical pathway involving NLRP3/Caspase-1 and the non-classical pathway involving Caspases-4 and -5. Our results provide compelling evidence that AngII could activate Caspases-4 and -5 by producing ROS.

Identification of molecular subtypes, risk signature, and immune landscape mediated by necroptosis-related genes in non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is a highly heterogeneous malignancy with an extremely high mortality rate. Necroptosis is a programmed cell death mode mediated by three major mediators, RIPK1, RIPK3, and MLKL, and has been shown to play a role in various cancers. To date, the effect of necroptosis on NSCLC remains unclear.

Methods

In The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we downloaded transcriptomes of lung adenocarcinoma (LUAD) patients and their corresponding clinicopathological parameters. We performed multi-omics analysis using consensus clustering based on the expression levels of 40 necroptosis-related genes. We constructed prognostic risk models and used the receiver operating characteristic (ROC) curves, nomograms, and survival analysis to evaluate prognostic models.

Results

With the use of consensus clustering analysis, two distinct subtypes of necroptosis were identified based on different mRNA expression levels, and cluster B was found to have a better survival advantage. Correlation results showed that necroptosis was significantly linked with clinical features, overall survival (OS) rate, and immune infiltration. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis confirmed that these differential genes were valuable in various cellular and biological functions and were significantly enriched in various pathways such as the P53 signaling pathway and cell cycle. We further identified three genomic subtypes and found that gene cluster B patients had better prognostic value. Multivariate Cox analysis identified the 14 best prognostic genes for constructing prognostic risk models. The high-risk group was found to have a poor prognosis. The construction of nomograms and ROC curves showed stable validity in prognostic prediction. There were also significant differences in tumor immune microenvironment, tumor mutational burden (TMB), and drug sensitivity between the two risk groups. The results demonstrate that the 14 genes constructed in this prognostic risk model were used as tumor prognostic biomarkers to guide immunotherapy and chemotherapy. Finally, we used qRT-PCR to validate the genes involved in the signature.

Conclusion

This study promotes our new understanding of necroptosis in the tumor microenvironment of NSCLC, mines prognostic biomarkers, and provides a potential value for guiding immunotherapy and chemotherapy.

Genomic and Immunological Characterization of Pyroptosis in Lung Adenocarcinoma

Pyroptosis is a programmed cell death that may either promote or hinder cancer growth under different circumstances. Pyroptosis-related genes (PRGs) could be a useful target for cancer therapy, and are uncommon in lung adenocarcinoma (LUAD). The expression profiles, mutation data and clinical information of LUAD patients were included in this study. A pyroptosis-related prognostic risk score (PPRS) model was constructed by performing Cox regression, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis to score LUAD patients. Somatic mutation and copy number variation (CNV), tumor immunity, and sensitivity to immunotherapy/chemotherapy were compared between different PPRS groups. Clinical parameters of LUAD were combined with PPRS to construct a decision tree and nomogram. Red module was highly positively correlated with pyroptosis. Seven genes (FCRLB, COTL1, GNG10, CASP4, DOK1, CCR2, and AQP8) were screened from the red module to construct a PPRS model. Significantly lower overall survival (OS), higher incidence of somatic mutation and CNV, elevated infiltration level of the immune cell together with increased probability of immune escape were observed in LUAD patients with higher PPRS, and were more sensitive to Cisplatin, Docetaxel, and Vinorelbine. We constructed a new PPRS model for patients with LUAD. The model might have clinical significance in the prediction of the prognosis of patients with LUAD and in the efficacy of chemotherapy and immunotherapy.

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.