Necroptosis and Cancer

Insights into intricacies of the Latent Membrane Protein-1 (LMP-1) in EBV-associated cancers

Numerous lymphomas, carcinomas, and other disorders have been associated with Epstein-Barr Virus (EBV) infection. EBV's carcinogenic potential can be correlated to latent membrane protein 1 (LMP1), which is essential for fibroblast and primary lymphocyte transformation. LMP1, a transmembrane protein with constitutive activity, belongs to the tumour necrosis factor receptor (TNFR) superfamily. LMP1 performs number of role in the life cycle of EBV and the pathogenesis by interfering with, reprogramming, and influencing a vast range of host cellular activities and functions that are getting well-known but still poorly understood. LMP1, pleiotropically perturbs, reprograms and balances a wide range of various processes of cell such as extracellular vesicles, epigenetics, ubiquitin machinery, metabolism, cell proliferation and survival, and also promotes oncogenic transformation, angiogenesis, anchorage-independent cell growth, metastasis and invasion, tumour microenvironment. By the help of various experiments, it is proven that EBV-encoded LMP1 activates multiple cell signalling pathways which affect antigen presentation, cell-cell interactions, chemokine and cytokine production. Therefore, it is assumed that LMP1 may perform majorly in EBV associated malignancies. For the development of novel techniques toward targeted therapeutic applications, it is essential to have a complete understanding of the LMP1 signalling landscape in order to identify potential targets. The focus of this review is on LMP1-interacting proteins and related signalling processes. We further discuss tactics for using the LMP1 protein as a potential therapeutic for cancers caused by the EBV.

Promising Nanomedicines of Shikonin for Cancer Therapy

Malignant tumor, the leading cause of death worldwide, poses a serious threat to human health. For decades, natural product has been proven to be an essential source for novel anticancer drug discovery. Shikonin (SHK), a natural molecule separated from the root of Lithospermum erythrorhizon, shows great potential in anticancer therapy. However, its further clinical application is significantly restricted by poor bioavailability, adverse effects, and non-selective toxicity. With the development of nanotechnology, nano drug delivery systems have emerged as promising strategies to improve bioavailability and enhance the therapeutic efficacy of drugs. To overcome the shortcoming of SHK, various nano drug delivery systems such as liposomes, polymeric micelles, nanoparticles, nanogels, and nanoemulsions, were developed to achieve efficient delivery for enhanced antitumor effects. Herein, this review summarizes the anticancer pharmacological activities and pharmacokinetics of SHK. Additionally, the latest progress of SHK nanomedicines in cancer therapy is outlined, focusing on long circulation, tumor targeting ability, tumor microenvironment responsive drug release, and nanosystem-mediated combination therapy. Finally, the challenges and prospects of SHK nanomedicines in the future clinical application are spotlighted.

Tumor necroptosis-mediated shedding of cell surface proteins promotes metastasis of breast cancer by suppressing anti-tumor immunity

Necroptosis is a form of regulated necrosis and is executed by MLKL when MLKL is engaged in triggering the rupture of cell plasma membrane. MLKL activation also leads to the protease, ADAMs-mediated ectodomain shedding of cell surface proteins of necroptotic cells. Tumor necroptosis often happens in advanced solid tumors, and blocking necroptosis by MLKL deletion in breast cancer dramatically reduces tumor metastasis. It has been suggested that tumor necroptosis affects tumor progression through modulating the tumor microenvironment. However, the exact mechanism by which tumor necroptosis promotes tumor metastasis remains elusive. Here, we report that the ectodomain shedding of cell surface proteins of necroptotic cells is critical for the promoting effect of tumor necroptosis in tumor metastasis through inhibiting the anti-tumor activity of T cells. We found that blocking tumor necroptosis by MLKL deletion led to the dramatic reduction of tumor metastasis and significantly elevated anti-tumor activity of tumor-infiltrating and peripheral blood T cells. Importantly, the increased anti-tumor activity of T cells is a key cause for the reduced metastasis as the depletion of CD8+ T cells completely restored the level of metastasis in the Mlkl KO mice. Interestingly, the levels of some soluble cell surface proteins including sE-cadherin that are known to promote metastasis are also dramatically reduced in MLKL null tumors/mice. Administration of ADAMs pan inhibitor reduces the levels of soluble cell surface proteins in WT tumors/mice and leads to the dramatic decrease in metastasis. Finally, we showed the sE-cadherin/KLRG1 inhibitory receptor is the major pathway for necroptosis-mediated suppression of the anti-tumor activity of T cells and the promotion of metastasis. Hence, our study reveals a novel mechanism of tumor necroptosis-mediated promotion of metastasis and suggests that tumor necroptosis and necroptosis-activated ADAMs are potential targets for controlling metastasis.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

RIPK1 and RIPK3 are positive prognosticators for cervical cancer patients and C2 ceramide can inhibit tumor cell proliferation in vitro

Introduction

The enzymes Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) und 3 (RIPK3) as well as the protein Mixed lineage kinase domain like pseudokinase (pMLKL) play a role in the signaling cascade of necroptosis. This is a form of programmed cell death which is caspase-independent. High-risk human papilloma virus infection can inhibit necroptosis. Thereby, a persistent infection and consequently the development of cervical cancer can be triggered. Aim of this study was the analysis of the expression of RIPK1, RIPK3 and pMLKL in cervical cancer tissue and the evaluation of its prognostic value on overall survival, progression-free survival and additional clinical parameters.

Methods

The expression of RIPK1, RIPK3, and pMLKL in cervical cancer tissue microarrays of n = 250 patients was analyzed immunohistochemically. Further, the effect of C2 ceramide on several cervical cancer cell lines (CaSki, HeLa, SiHa) was examined. C2 ceramide is a biologically active short-chain ceramide that induces necroptosis in human luteal granulosa cells.

Results

Significantly longer overall survival and progression-free survival rates could be detected in cervical cancer patients expressing nuclear RIPK1 or RIPK3 alone or simultaneously (RIPK1 and RIPK3). Cell viability and proliferation was reduced through C2 ceramide stimulation of cervical cancer cells. Simultaneous stimulation of C2 ceramide and the pan-caspase inhibitor Z-VAD-fmk, or the RIPK1-inhibitor necrostatin-1, partly reversed the negative effect of C2 ceramide on cell viability. This observation could imply that caspase-dependent and -independent forms of cell death, including necroptosis, can occur. AnnexinV-FITC apoptosis staining induced a significant increase in apoptotic cells in CaSki and SiHa cells. The stimulation of CaSki cells with C2 ceramide led to a significant percentual increase in necrotic/intermediate (dying) cells after stimulation with C2 ceramide. In addition, after stimulation with C2 ceramide, CaSki and HeLa cells live cell imaging showed morphological changes which are common for necroptosis.

Discussion

In conclusion, RIPK1 and RIPK3 are independent positive predictors for overall survival and progression-free survival in cervical cancer patients. C2 ceramide can reduce cell viability and proliferation in cervical cancer cells by inducing most likely both apoptosis and necroptosis.

Surviving death: emerging concepts of RIPK3 and MLKL ubiquitination in the regulation of necroptosis

Lytic forms of programmed cell death, like necroptosis, are characterised by cell rupture and the release of cellular contents, often provoking inflammatory responses. In the recent years, necroptosis has been shown to play important roles in human diseases like cancer, infections and ischaemia/reperfusion injury. Coordinated interactions between RIPK1, RIPK3 and MLKL lead to the formation of a dedicated death complex called the necrosome that triggers MLKL-mediated membrane rupture and necroptotic cell death. Necroptotic cell death is tightly controlled by post-translational modifications, among which especially phosphorylation has been characterised in great detail. Although selective ubiquitination is relatively well-explored in the early initiation stages of necroptosis, the mechanisms and functional consequences of RIPK3 and MLKL ubiquitination for necrosome function and necroptosis are only starting to emerge. This review provides an overview on how site-specific ubiquitination of RIPK3 and MLKL regulates, fine-tunes and reverses the execution of necroptotic cell death.

Construction of a Necroptosis-Related lncRNA Signature for Predicting Prognosis and Immune Response in Kidney Renal Clear Cell Carcinoma

Necroptosis is a new type of programmed cell death and involves the occurrence and development of various cancers. Moreover, the aberrantly expressed lncRNA can also affect tumorigenesis, migration, and invasion. However, there are few types of research on the necroptosis-related lncRNA (NRL), especially in kidney renal clear cell carcinoma (KIRC). In this study, we analyzed the sequencing data obtained from the TGCA-KIRC dataset, then applied the LASSO and COX analysis to identify 6 NRLs (AC124854.1, AL117336.1, DLGAP1-AS2, EPB41L4A-DT, HOXA-AS2, and LINC02100) to construct a risk model. Patients suffering from KIRC were divided into high- and low-risk groups according to the risk score, and the patients in the low-risk group had a longer OS. This signature can be used as an indicator to predict the prognosis of KIRC independent of other clinicopathological features. In addition, the gene set enrichment analysis showed that some tumor and immune-associated pathways were more enriched in a high-risk group. We also found significant differences between the high and low-risk groups in the infiltrating immune cells, immune functions, and expression of immune checkpoint molecules. Finally, we use the "pRRophetic" package to complete the drug sensitivity prediction, and the risk score could reflect patients' response to 8 small molecule compounds. In general, NRLs divided KIRC into two subtypes with different risk scores. Furthermore, this signature based on the 6 NRLs could provide a promising method to predict the prognosis and immune response of KIRC patients. To some extent, our findings helped give a reference for further research between NRLs and KIRC and find more effective therapeutic drugs for KIRC.

Construction of a machine learning-based artificial neural network for discriminating PANoptosis related subgroups to predict prognosis in low-grade gliomas

The poor prognosis of gliomas necessitates the search for biomarkers for predicting clinical outcomes. Recent studies have shown that PANoptosis play an important role in tumor progression. However, the role of PANoptosis in in gliomas has not been fully clarified.Low-grade gliomas (LGGs) from TCGA and CGGA database were classified into two PANoptosis patterns based on the expression of PANoptosis related genes (PRGs) using consensus clustering method, followed which the differentially expressed genes (DEGs) between two PANoptosis patterns were defined as PANoptosis related gene signature. Subsequently, LGGs were separated into two PANoptosis related gene clusters with distinct prognosis based on PANoptosis related gene signature. Univariate and multivariate cox regression analysis confirmed the prognostic values of PANoptosis related gene cluster, based on which a nomogram model was constructed to predict the prognosis in LGGs. ESTIMATE algorithm, MCP counter and CIBERSORT algorithm were utilized to explore the distinct characteristics of tumor microenvironment (TME) between two PANoptosis related gene clusters. Furthermore, an artificial neural network (ANN) model based on machine learning methods was developed to discriminate distinct PANoptosis related gene clusters. Two external datasets were used to verify the performance of the ANN model. The Human Protein Atlas website and western blotting were utilized to confirm the expression of the featured genes involved the ANN model. We developed a machine learning based ANN model for discriminating PANoptosis related subgroups with drawing implications in predicting prognosis in gliomas.

Identification of necroptosis-related subtypes, development of a novel signature, and characterization of immune infiltration in colorectal cancer

Introduction

Necroptosis, a type of programmed cell death, has recently been extensively studied as an important pathway regulating tumor development, metastasis, and immunity. However, the expression patterns of necroptosis-related genes (NRGs) in colorectal cancer (CRC) and their potential roles in the tumor microenvironment (TME) have not been elucidated.

Methods

We explored the expression patterns of NRGs in 1247 colorectal cancer samples from genetics and transcriptional perspective. Based on a consensus clustering algorithm, we identified NRG molecular subtypes and gene subtypes, respectively. Furthermore, we constructed a necroptosis-related signature for predicting overall survival time and verified the predictive ability of the model. Using the ESTIMATE, CIBERSORT, and ssGSEA algorithms, we assessed the association between the above subtypes, scores and immune infiltration.

Results

Most NRGs were differentially expressed between CRC tissues and normal tissues. We found that distinct subtypes exhibited different NRGs expression, patients' prognosis, immune checkpoint gene expression, and immune infiltration characteristics. The scores calculated from the necroptosis-related signature can be used to classify patients into high-risk and low-risk groups, with the high-risk group corresponding to reduced immune cell infiltration and immune function, and a greater risk of immune dysfunction and immune escape.

Discussion

Our comprehensive analysis of NRGs in CRC demonstrated their potential role in clinicopathological features, prognosis, and immune infiltration in the TME. These findings help us deepen our understanding of NRGs and the tumor microenvironment landscape, and lay a foundation for effectively assessing patient outcomes and promoting more effective immunotherapy.

PGAM5: A necroptosis gene associated with poor tumor prognosis that promotes cutaneous melanoma progression

Cutaneous melanoma is the deadliest type of skin cancer, and its highly aggressive and metastatic nature leads to an extremely poor prognosis. Necrotizing apoptosis, a specific form of programmed cell death, has been extensively studied in recent years. In this study, we analyzed the relationship between necroptosis-related functional genes and cutaneous melanoma in order to identify the biomarkers associated with the prognosis and progression of cutaneous melanoma. Cutaneous melanoma samples were classified into three subgroups on the basis of a necroptosis gene set. These subgroups were subjected to a prognostic survival analysis, and the greatest differences were observed between subgroups C1 and C3. Between these subgroups, 28 necrotizing apoptosis-related genes were significantly differently expressed. Among these, 16 necrotizing apoptosis-related genes were associated with cutaneous melanoma prognosis. Downscaling analysis and prognostic modeling using the least absolute shrinkage and selection operator analysis yielded nine pivotal genes and revealed phosphoglycerate translocase 5 (PGAM5) as the key gene. Then, qRT-PCR was used to verify the expression level of PGAM5. The results showed that PGAM5 was highly expressed in cutaneous melanoma tissues. In this study, a bioinformatics approach was used to identify PGAM5, a biomarker whose high expression is associated with the poor prognosis of cutaneous melanoma.

Integrative Analysis of Necroptosis-Related Signature for Predicting the Prognosis of Osteosarcoma.. [DOI: 10.21203/rs.3.rs-2241039/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background Osteosarcoma (OS) is the most common and malignant bone tumor among children and adolescents worldwide. Over decades, clinical treatment for osteosarcoma has proven to be intractable. Novel approaches, such as immunotherapy, face immune escape. Thus, exploring potential therapeutic targets for osteosarcoma is an urgent need. Method Gene expression data and clinical information were downloaded from Therapeutically Applicable Research to Generate Effective Treatments (TARGET), Gene Expression Omnibus (GEO), and Univariate Cox regression analysis was used to identify prognostic necroptosis-related genes (NRGs). A non-negative matrix factorization algorithm (NMF) was used to cluster patients into various molecular subgroups with NRGs. We dealt with multi-collinearity with the least absolute shrinkage and selection operator (LASSO). Multivariate Cox regression was used to construct the prediction model that divided OS patients into two risk groups. The model's validity was assessed by time-dependent receiver operating characteristic (ROC) analysis. Different expression genes (DEGs) between these two groups were conducted for functional analysis, including gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA). Eight algorithms were carried out to evaluate the tumor microenvironment. These marker genes on the single-cell transcriptome were further labeled to explore whether their expression was cell-specific. Results Based on the model constructed by 5 NRGs (TLR4, STAT5A, IFNGR1, PYGM, CHMP4C), the patients were divided into two risk groups. Patients in the high-risk group suffered a poorer prognosis than those in the low-risk group. The nomogram was constructed and integrated with clinical features and gene signatures, demonstrating better predictive ability in training and testing cohorts. Immune cell infiltrations were highly associated with the risk score generated by Multivariate Cox. All 5 NRGs can be successfully marked on the feature plot of single-cell RNA-Seq, and two NRGs were associated with cell-specific genes of osteosarcoma pluripotency with statistical significance. Conclusion This study can provide a reference for diagnosing molecular subtyping and treating patients with OS.

Dual Topoisomerase I/II Inhibition-Induced Apoptosis and Necro-Apoptosis in Cancer Cells by a Novel Ciprofloxacin Derivative via RIPK1/RIPK3/MLKL Activation

Fluoroquinolones (FQs) are synthetic broad-spectrum antimicrobial agents that have been recently repurposed to anticancer candidates. Designing new derivatives of FQs with different moieties to target DNA topoisomerases could improve their anticancer efficacy. The present study aimed to synthesize a novel ciprofloxacin derivative, examine its anticancer activity against HepG2 and A549 cancer cells, and investigate the possible molecular mechanism underlying this activity by examining its ability to inhibit the topo I/II activity and to induce the apoptotic and necro-apoptotic pathways. Molecular docking, cell viability, cell migration, colony formation, cell cycle, Annexin V, lactate dehydrogenase (LDH) release, ELISA, and western blotting assays were utilized. Molecular docking results showed that this novel ciprofloxacin derivative exerted dual topo I and topo II binding and inhibition. It significantly inhibited the proliferation of A549 and HepG2 cancer cells and decreased their cell migration and colony formation abilities. In addition, it significantly increased the % of apoptotic cells, caused cell cycle arrest at G2/M phase, and elevated the LDH release levels in both cancer cells. Furthermore, it increased the expression of cleaved caspase 3, RIPK1, RIPK3, and MLKL proteins. This novel ciprofloxacin derivative exerted substantial dual inhibition of topo I/II enzyme activities, showed antiproliferative activity, suppressed the cell migration and colony formation abilities for A549 and HepG2 cancer cells and activated the apoptotic pathway. In addition, it initiated another backup deadly pathway, necro-apoptosis, through the activation of the RIPK1/RIPK3/MLKL pathway.

A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma

Background

Gastric cancer (GC) represents a major global clinical problem with very limited therapeutic options and poor prognosis. Necroptosis, a recently discovered inflammatory form of cell death, has been implicated in carcinogenesis and inducing necroptosis has also been considered as a therapeutic strategy.

Objective

We aim to evaluate the role of this pathway in gastric cancer development, prognosis and immune aspects of its tumor microenvironment.

Methods and results

In this study, we evaluated the gene expression of 55 necroptosis-related genes (NRGs) that were identified via carrying out a comprehensive review of the medical literature. Necroptosis pathway was deregulated in gastric cancer samples (n=375) as compared to adjacent normal tissues (n=32) obtained from the “The Cancer Genome Atlas (TCGA)”. Based on the expression of these NRGs, two molecular subtypes were obtained through consensus clustering that also showed significant prognostic difference. Differentially expressed genes between these two clusters were retrieved and subjected to prognostic evaluation via univariate cox regression analysis and LASSO cox regression analysis. A 13-gene risk signature, termed as necroptosis-related genes prognostic index (NRGPI), was constructed that comprehensively differentiated the gastric cancer patients into high- and low-risk subgroups. The prognostic significance of NRGPI was validated in the GEO cohort (GSE84437: n=408). The NRGPI-high subgroup was characterized by upregulation of 10 genes (CYTL1, PLCL1, CGB5, CNTN1, GRP, APOD, CST6, GPX3, FCN1, SERPINE1) and downregulation of 3 genes (EFNA3, E2F2, SOX14). Further dissection of these two risk groups by differential gene expression analysis indicated involvement of signaling pathways associated with cancer cell progression and immune suppression such as WNT and TGF-β signaling pathway. Para-inflammation and type-II interferon pathways were activated in NRGPI-high patients with an increased infiltration of Tregs and M2 macrophage indicating an exhausted immune phenotype of the tumor microenvironment. These molecular characteristics were mainly driven by the eight NRGPI oncogenes (CYTL1, PLCL1, CNTN1, GRP, APOD, GPX3, FCN1, SERPINE1) as validated in the gastric cancer cell lines and clinical samples. NRGPI-high patients showed sensitivity to a number of targeted agents, in particular, the tyrosine kinase inhibitors.

Conclusions

Necroptosis appears to play a critical role in the development of gastric cancer, prognosis and shaping of its tumor immune microenvironment. NRGPI can be used as a promising prognostic biomarker to identify gastric cancer patients with a cold tumor immune microenvironment and poor prognosis who may response to selected molecular targeted therapy.

Exosome-encapsulated ncRNAs: Emerging yin and yang of tumor hallmarks

Tumorigenesis is a multifaceted process, where multiple physiological traits serving as cancer’s distinctive characteristics are acquired. “Hallmarks of cancer” is a set of cognitive abilities acquired by human cells that are pivotal to their tumor-forming potential. With limited or no protein-coding ability, non-coding RNAs (ncRNAs) interact with their target molecules and yield significant regulatory effects on several cell cycle processes. They play a “yin” and “yang” role, thereby functioning both as oncogenic and tumor suppressor and considered important in the management of various types of cancer entities. ncRNAs serve as important post-transcriptional and translational regulators of not only unrestricted expansion and metastasis of tumor cells but also of various biological processes, such as genomic mutation, DNA damage, immune escape, and metabolic disorder. Dynamical attributes such as increased proliferative signaling, migration, invasion, and epithelial–mesenchymal transition are considered to be significant determinants of tumor malignancy, metastatic dissemination, and therapeutic resistance. Furthermore, these biological attributes engage tumor cells with immune cells within the tumor microenvironment to promote tumor formation. We elaborate the interaction of ncRNAs with various factors in order to regulate cancer intra/intercellular signaling in a specific tumor microenvironment, which facilitates the cancer cells in acquiring malignant hallmarks. Exosomes represent a means of intercellular communication and participate in the maintenance of the tumor hallmarks, adding depth to the intricate, multifactorial character of malignant neoplasia. To summarize, ncRNAs have a profound impact on tumors, affecting their microcirculation, invasiveness, altered metabolism, microenvironment, and the capacity to modify the host immunological environment. Though the significance of ncRNAs in crosstalk between the tumor and its microenvironment is being extensively explored, we intend to review the hallmarks in the light of exosome-derived non-coding RNAs and their impact on the tumor microenvironment.

Qualification of Necroptosis-Related lncRNA to Forecast the Treatment Outcome, Immune Response, and Therapeutic Effect of Kidney Renal Clear Cell Carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is considered as a highly immune infiltrative tumor. Necroptosis is an inflammatory programmed cell death associated with a wide range of diseases. Long noncoding RNAs (lncRNAs) play important roles in gene regulation and immune function. lncRNA associated with necroptosis could systematically explore the prognostic value, regulate tumor microenvironment (TME), etc.

Method

The patients' data was collected from TCGA datasets. We used the univariate Cox regression (UCR) to select prediction lncRNAs that are related to necroptosis. Meanwhile, risk models were constructed using LASSO Cox regression (LCR). Kaplan–Meier (KM) analysis, accompanied with receiver operating characteristic (ROC) curves, was performed to assess the independent risk factors of different clinical characteristics. The evaluated factors are age, gender, disease staging, grade, and their related risk score. Databases such as Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSEA) were used to search the probable biological characteristics that could influence the risk groups, containing signaling pathway and immue-related pathways. The single-sample gene set enrichment analysis (ssGSEA) was chosen to perform gene set variation analysis (GSVA), and the GSEABase package was selected to detect the immune and inflammatory infiltration profiles. The TIDE and IC₅₀ evaluation were used to estimate the effectiveness of clinical treatment on KIRC.

Results

Based on the above analysis, we have got a conclusion that patients who show high risk had higher immune infiltration, immune checkpoint expression, and poorer prognosis. We identified 19 novel prognostic necroptosis-related lncRNAs, which could offer opinions for a deeper study of KIRC.

Conclusion

The risk model we constructed makes it possible to predict the prognosis of KIRC patients and offers directions for further research on the prognostication and treatment strategies for KIRC.

A novel necroptosis-related lncRNAs signature for survival prediction in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common kind of kidney cancer with poor prognosis. Necroptosis is a newly observed type of programmed cell death in recent years. However, the effects of necroptosis-related lncRNAs (NRlncRNAs) on ccRCC have not been widely explored. The transcription profile and clinical information were obtained from The Cancer Genome Atlas. Necroptosis-related lncRNAs were identified by utilizing a co-expression network of necroptosis-related genes and lncRNAs. Univariate Cox regression, least absolute shrinkage, and selection operator regression and multivariate Cox regression were performed to screen out ideal prognostic necroptosis-related lncRNAss and develop a multi-lncRNA signature. Finally, 6 necroptosis-related lncRNA markers were established. Patients were separated into high- and low-risk groups based on the performance value of the median risk score. Kaplan-Meier analysis identified that high-risk patients had poorer prognosis than low-risk patients. Furthermore, the area under time-dependent receiver operating characteristic curve reached 0.743 at 1 year, 0.719 at 3 years, and 0.742 at 5 years, which indicating that they can be used to predict ccRCC prognosis. In addition, the proposed signature was related to immunocyte infiltration. A nomogram model was also established to provide a more beneficial prognostic indicator for the clinic. Altogether, in the present study, the 6-lncRNA prognostic risk signature are trustworthy and effective indicators for predicting the prognosis of ccRCC.

A necroptosis-related prognostic model for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma based on single-cell sequencing analysis and weighted co-expression network

Background: Hepatocellular carcinoma (HCC) is a highly lethal cancer and is the second leading cause of cancer-related deaths worldwide. Unlike apoptosis, necroptosis (NCPS) triggers an immune response by releasing damage-related molecular factors. However, the clinical prognostic features of necroptosis-associated genes in HCC are still not fully explored.

Methods: We analyzed the single-cell datasets GSE125449 and GSE151530 from the GEO database and performed weighted co-expression network analysis on the TCGA data to identify the necroptosis genes. A prognostic model was built using COX and Lasso regression. In addition, we performed an analysis of survival, immunity microenvironment, and mutation. Furthermore, the hub genes and pathways associated with HCC were localized within the single-cell atlas.

Results: Patients with HCC in the TCGA and ICGC cohorts were classified using a necroptosis-related model with significant differences in survival times between high- and low-NCPS groups (p < 0.05). High-NCPS patients expressed more immune checkpoint-related genes, suggesting immunotherapy and some chemotherapies might prove beneficial to them. In addition, a single-cell sequencing approach was conducted to investigate the expression of hub genes and associated signaling pathways in different cell types.

Conclusion: Through the analysis of single-cell and bulk multi-omics sequencing data, we constructed a prognostic model related to necroptosis and explored the relationship between high- and low-NCPS groups and immune cell infiltration in HCC. This provides a new reference for further understanding the role of necroptosis in HCC.

The Expression Pattern of Non-apoptotic Cell Death Pathway in Osteosarcoma: Necroptosis and Autophagy as Backup Mechanisms for Therapeutics Strategy

Background: Among the primary bone tumors, osteosarcoma accounts for a malignant tumor with a high rate of progression and poor prognosis. Despite the achievement of combined therapy regimens in improving patients’ overall survival, patients with osteosarcoma confront the chemoresistance obstacle. Objectives: This study aimed at determining the expression pattern of autophagy and necroptosis pathways mediators in osteosarcoma tumors. Methods: The expression level of autophagy main mediators such as autophagy-associated protein 5 (ATG5), Beclin 1 (BECN1), and microtubule-associated protein 1A/1B-light chain 3 (LC3), necroptosis biomarkers such as receptor-interacting protein kinases (RIPK1 and RIPK3), and mixed lineage kinase domain-like (MLKL) were evaluated in 80 bone tissues including 60 bone tumors (40 malignant tumors and 20 benign tumors) and 20 margin tissues, using real-time PCR. The correlations of gene expression levels with the patient’s clinical and pathological features were considered. Results: Based on our data, ATG5, BECN1 and LC3 expression were down-regulated in osteosarcoma tumors compared to margin tissues. Also, malignant osteosarcoma tumors showed a significant decrease in the expression level of RIPK1 and MLKL as necroptosis regulators, which revealed a correlation with tumor malignancy. In addition, the higher expression levels of BECN1, LC3, RIPK1, and MLKL were observed in tumor tissues of patients under the chemotherapy regimen, indicating the relevance of autophagy and necroptosis pathways with the patient’s response to therapy. Conclusions: Reduction in the expression level of autophagy and necroptosis mediators in high-grade osteosarcoma tumors indicates the possible impact of these pathways on the rate of proliferation and growth of osteosarcoma tumor cells and can emphasize the importance of cell death alternative pathways for treatment when apoptosis machinery is mutated and cause chemoresistance.

Identification and validation of the necroptosis-related gene signature related to prognosis and tumor immune in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the sixth most common cancer, which is characterized by complicated etiology, excessive heterogeneity, and poor prognosis. Necroptosis is a new kind of programmed cell death, which is intently associated with the occurrence and development of tumors. Although researchers have had a deep understanding of necroptosis in recent years, the expression level of necroptosis-related genes in HCC and its relationship with the survival time of HCC patients are not clear.

METHODS

According to the expression of necroptosis-related genes and the survival of HCC patients, HCC patients in the TCGA database were divided into 2 groups that were relatively independent of each other. The genes related to the survival time of HCC patients were screened from the 2 groups of differentially expressed genes. By using the Least Absolute Shrinkage and Selection Operator Cox regression analysis, the optimal λ value was obtained, and the 10-gene signature model was established.

RESULTS

According to the median risk score of the TCGA cohort, HCC patients were averagely divided into high- and low-risk groups. Compared with the low-risk group, the death toll of the high-risk group was relatively higher and the survival time was relatively shorter. Principal component analysis and t-distributed stochastic neighbor embedding analysis showed that there was a significant separation between high- and low-risk groups. Through Kaplan-Meier analysis, it was found that the survival time of HCC patients in the high-risk group was significantly shorter than that in the low-risk group. Through receiver operating characteristic analysis, it was found that the sensitivity and specificity of the model were good. We also make a comprehensive analysis of the international cancer genome consortium database as a verification queue and prove the reliability of the 10-gene signature model. Gene Ontolog, Kyoto Encyclopedia of Genes and Genomes, and single-sample gene set enrichment analysis showed that many biological processes and pathways related to immunity had been enriched, and the antitumor immune function was weakened in the high-risk population.

CONCLUSION

The risk score can be considered as an independent prognostic factor to predict the prognosis of patients with HCC, and necroptosis-related genes are also closely related to tumor immune function.

Alteration of intestinal microecology by oral antibiotics promotes oral squamous cell carcinoma development

Oral antibiotics can influence cancers and immunotherapy by interfering with the intestinal microbiota. However, the association between oral antibiotics and oral squamous cell carcinoma (OSCC) as well as the mechanisms underlying the effects of oral antibiotics on OSCC remain unclear. Here, we found that oral antibiotics cocktail (4Abx) promoted the tumor development and shifted the microbiota, decreasing the abundance of probiotic bacteria, and altered microbial metabolism in the gut of OSCC mice, increasing tyrosine and decreasing glutamate levels. In vitro experiments showed that tyrosine upregulated the PD-1 expression in T cells, SCC7 cell proliferation, and necroptosis expression. IL-10 expression level in CD11c+ cells was reduced by glutamate. Furthermore, the expression of the necroptosis-related proteins, including receptor-interacting protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like (MLKL), was higher in the OSCC mice treated with 4Abx. Supplementation with glutamate or healthy mouse feces by gavage alleviated the tumor-promoting effect of 4Abx with restored balance of microbial metabolism. Overall, we identified the detrimental role of oral antibiotics in promoting OSCC development through altered intestinal microbiota, microbial metabolism, and immune dysbiosis, implying the need for antibiotic stewardship in OSCC treatment.

Identification of Necroptosis-Related miRNA Signature as a Potential Predictive Biomarker for Prognosis and Immune Status in Colon Adenocarcinoma

Objective

Increasing studies suggest that necroptosis is correlated with tumor progression. And aberrant microRNA (miRNA) expression plays a vital role in various tumors. Thus, we are committed to exploring a necroptosis-associated miRNA signature to serve as a prognostic biomarker in colon adenocarcinoma (COAD). Data Sources and Methods. In the current study, The Cancer Genome Atlas (TCGA) database was used to download the miRNA and mRNA expression profiles and clinical information of samples. All patients were stochastically assigned to TCGA-train and TCGA-test clusters. Subsequently, we established a prognostic signature comprised of necroptosis-related miRNAs (NR-mis) via LASSO-Cox regression and then developed a nomogram signature composed of the prognostic signature and clinical factors. Corresponding prognostic values were evaluated. Functional analysis, tumor microenvironment (TME), and chemosensitivity of risk subgroups were also identified.

Results

The prognostic signature based on miR-141-3p, miR-148a-3p, miR-16-5p, and miR-200a-5p was closely associated with overall survival (OS) of samples and tumor metastasis in COAD. The Area Under Curve (AUC) was 0.605, 0.721, and 0.752 in TCGA-train cluster , 0.661, 0.613, and 0.695 in the TCGA-test cluster at 1, 3, and 5 years, respectively. The C-index for nomogram signature was 0.754. Functional analysis showed the remarkable enrichment of the signature-dependent miRNAs in tumor progression and immune response. And two risk subgroups were correlated with the distinct immune infiltration and immune checkpoints. In addition, the high-risk subgroup is more sensitive to cisplatin, doxorubicin, etoposide, and gemcitabine.

Conclusions

Necroptosis-related miRNAs play a crucial role in the prognosis, metastasis, immune status, and drug sensitivity in COAD.

Epimedokoreanin B inhibits the growth of lung cancer cells through endoplasmic reticulum stress-mediated paraptosis accompanied by autophagosome accumulation

Epimedokoreanin B (EKB) is a prenylated flavonoid isolated from Epimedium koreanum. In this article, we described the anti-cancerous effects of EKB and its underlying mechanism in human non-small cell lung cancer (NSCLC) A549 and NCI-H292 cells. EKB treatment inhibited cell proliferation and migration accompanied by cytoplasmic vacuolation in both cell lines. The cell death induced by EKB lacked the features of apoptosis like chromatin condensation, phosphatidyl serine exposure and caspase cleavage. The vacuoles stimulated by EKB predominantly derived from endoplasmic reticulum (ER) and mitochondria dilation, which are the characteristics of paraptosis. Down-regulation of Alix and up-regulation of ER stress-related proteins after EKB treatment further supported the occurrence of paraptosis. ER stress inhibitor 4-phenylbutyric acid (4-PBA) and protein synthesis inhibitor cycloheximide (CHX) treatment antagonized the vacuoles formation as well as cell death induced by EKB, indicating that ER stress was involved in EKB induced paraptosis. In addition, autophagosome accumulation accompanied with autophagy flux blocking was observed in EKB treated cells, this was consistent with the occurrence of ER stress. Collectively, EKB was demonstrated as a paraptosis-like cell death inducer in A549 and NCI-H292 cells. The inhibitory effect of EKB on lung cancer cell proliferation was further demonstrated in a zebrafish xenograft model. These findings raise the possibility that paraptosis inducers may be considered as alternative choices for lung cancer therapy.

Crosstalk of three novel types of programmed cell death defines distinct microenvironment characterization and pharmacogenomic landscape in breast cancer

Background

Prior studies have highlighted that novel programmed cell death (PCD) modalities, including ferroptosis, pyroptosis, and necroptosis, are correlated with tumor progression and antitumor immunity. Nonetheless, comprehensive analysis of tumor microenvironment (TME) profiles mediated by the crosstalk of distinct PCD forms has not been conducted in breast cancer (BC).

Methods

Here, we curated 34 identified PCD-associated genes (PCDAGs) and applied the consensus clustering algorithm to establish PCD-mediated tumor patterns in BC. Subsequently, based on prognostic differentially expressed genes extracted from distinct PCD-mediated patterns, we applied the LASSO algorithm to construct CD_Score. Furthermore, the correlation analysis between CD_Score and TME features, molecular subtypes, clinicopathological characteristics, drug response, and immunotherapeutic efficacy was performed.

Results

Three distinct PCD-clusters were determined among 2,038 BC samples, which did not only display different clinical outcomes but highly correlated to the established immunological tumor phenotypes: “desert,” “excluded,” and “inflamed” immune profiles. Based on the CD_Score derived from the PCD-related gene signature, BC patients could be stratified into CD_Score-low and -high group, of which the former displayed satisfactory survival outcome and enhanced immune infiltration. Further exploration identified that the CD_Score-high group significantly correlated with elevated neoantigen load and higher mutation frequency in SMGs (e.g., TP53 and MAP3K1) and reduced expression of immune checkpoint proteins.

Conclusions

This research is the first to emphasize the close relationship between distinct cell death modalities and the diversity and complexity of immune infiltration in TME. We established the CD_Score, which could help enhance our cognition of TME features and facilitate the clinical application of immunotherapy.

A novel signature based on necroptosis-related long non-coding RNAs for predicting prognosis of patients with glioma

Necroptosis is closely related to the occurrence and development of tumors, including glioma. A growing number of studies indicate that targeting necroptosis could be an effective treatment strategy against cancer. Long non-coding RNA (lncRNA) is also believed to play a pivotal role in tumor epigenetics. Therefore, it is necessary to identify the functions of necroptosis-related lncRNAs in glioma. In this study, the transcriptome and clinical characteristic data of glioma patients from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were collected, and the differentially expressed necroptosis-related lncRNAs in TCGA that have an impact on overall survival (OS) were screened out to construct risk score (RS) formula, which was verified in CGGA. A nomogram was constructed to predict the prognosis of glioma patients based on clinical characteristics and RS. In addition, Gene Set Enrichment Analysis (GSEA) was used to analyze the main enrichment functions of these necroptosis-related lncRNAs and the immune microenvironment. A total of nine necroptosis-related lncRNAs have been identified to construct the RS formula, and the Kaplan–Meier (K-M) survival analysis showed significantly poorer outcomes in the high RS group in both TCGA and CGGA databases. Moreover, the receiver operating characteristic (ROC) curve shows that our prediction RS model has good predictability. Regarding the analysis of the immune microenvironment, significant differences were observed in immune function and immune checkpoint between the high RS group and the low RS group. In conclusion, we constructed a necroptosis-related lncRNA RS model that can effectively predict the prognosis of glioma patients and provided the theoretical basis and the potential therapeutic targets for immunotherapy against gliomas.

Development of a prognostic model for children with neuroblastoma based on necroptosis-related genes

Background: Neuroblastoma (NBL) is a rare malignant tumor of the peripheral sympathetic nervous system in children with a low overall survival rate. Recent studies have revealed the important role of necroptosis in the occurrence and development of many kinds of tumors. In this study, a prognostic model based on necroptosis-related genes was constructed for NBL.

Methods: Expression profiles and clinical information for patients with NBL were downloaded from TARGET. Data for necroptosis-related genes were extracted for Cox regression and lasso regression analyses to evaluate factors associated with prognosis and to construct a prognostic model. Data from the GEO datasets GSE62564 and GSE85047 were used for external verification. Associations between risk scores were calculated, and immune infiltration, drug sensitivity, and mutation analyses were conducted. Functional enrichment analyses of genes in the prognostic model were performed.

Results: Six necroptosis-related genes (i.e., CYLD, JAK1, APC, ERH, CNBP, and BAX) were selected to construct a prognostic risk model. The risk score was highly correlated with levels of infiltration of multiple immune cells and sensitivity to common antineoplastic drugs. In addition, the risk score was identified as an independent prognostic factor for patients with NBL.

Conclusion: We constructed and validated a prognostic model based on necroptosis-related genes, providing insights into the development and progression of NBL and a basis for improved management. In addition to providing a tool for clinical decision-making, these findings support the importance of necroptosis in NBL and may guide the development of therapeutic strategies targeting this process.

A panel of necroptosis-related genes predicts the prognosis of pancreatic adenocarcinoma

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The 5-NRGs signature can predict the prognosis of pancreatic adenocarcinoma.

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The 5-NRGs signature reflects the immune landscape of pancreatic adenocarcinoma.

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The 5-NRGs can be detected in exosomes of serum using RT-qPCR method.

Pancreatic adenocarcinoma (PAAD) has become one of the deadliest malignancies in the world. Since necroptosis plays a crucial role in regulating the immune system, it is necessary to develop novel prognostic biomarkers associated with necroptosis and explore its potential role in PAAD. The transcriptome RNA-seq data of PAAD were downloaded from the TCGA and GTEx databases. A prognostic signature was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression, and its prognostic value was evaluated by nomogram and validated in an independent GEO cohort. We identified a total of 24 differentially expressed NRGs in PAAD, and constructed a prognostic signature with 5 NRGs, which showed good performance in predicting the prognosis of PAAD patients. The ROC curves for 1-, 3-, and 5-year survival rate were 0.652, 0.778, and 0.817, respectively. This prognostic signature showed consistent prognosis prediction in an independent patient cohort. Furthermore, the correlations between 5-NRGs signature and TMB, MSI, histopathological classification, immune infiltration, immune types, and immunomodulators were all significant. Notably, the expression profiles of the five NRGs in exosomes of serum were consistent with their expression in tumor tissues. These data suggested that the 5-NRGs signature is a promising biomarker for predicting the prognosis of PAAD.

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.

Establishment of a Necroptosis-Related Prognostic Signature to Reveal Immune Infiltration and Predict Drug Sensitivity in Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a common type of primary liver cancer and has a poor prognosis. In recent times, necroptosis has been reported to be involved in the progression of multiple cancers. However, the role of necroptosis in HCC prognosis remains elusive.

Methods: The RNA-seq data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes (DEGs) and prognosis-related genes were explored, and the nonnegative matrix factorization (NMF) clustering algorithm was applied to divide HCC patients into different subtypes. Based on the prognosis-related DEGs, univariate Cox and LASSO Cox regression analyses were used to construct a necroptosis-related prognostic model. The relationship between the prognostic model and immune cell infiltration, tumor mutational burden (TMB), and drug response were explored.

Results: In this study, 13 prognosis-related DEGs were confirmed from 18 DEGs and 24 prognostic-related genes. Based on the prognosis-related DEGs, patients in the TCGA cohort were clustered into three subtypes by the NMF algorithm, and patients in C3 had better survival. A necroptosis-related prognostic model was established according to LASSO analysis, and HCC patients in TCGA and ICGC were divided into high- and low-risk groups. Kaplan–Meier (K–M) survival analysis revealed that patients in the high-risk group had a shorter survival time compared to those in the low-risk group. Using univariate and multivariate Cox analyses, the prognostic model was identified as an independent prognostic factor and had better survival predictive ability in HCC patients compared with other clinical biomarkers. Furthermore, the results revealed that the high-risk patients had higher stromal, immune, and ESTIMATE scores; higher TP53 mutation rate; higher TMB; and lower tumor purities compared to those in the low-risk group. In addition, there were significant differences in predicting the drug response between the high- and low-risk groups. The protein and mRNA levels of these prognostic genes were upregulated in HCC tissues compared to normal liver tissues.

Conclusion: We established a necroptosis-related prognostic signature that may provide guidance for individualized drug therapy in HCC patients; however, further experimentation is needed to validate our results.

Immunotherapy landscape analyses of necroptosis characteristics for breast cancer patients

Necroptosis plays a major role in breast cancer (BC) progression and metastasis. Besides, necroptosis also regulates inflammatory response and tumor microenvironment. Here, we aim to explore the predictive signature based on necroptosis-related genes (NRGs) for predicting the prognosis and response to therapies. Using Lasso multivariate cox analysis, we firstly established the NRG signature based on TCGA database. A total of 6 NRGs (FASLG, IPMK, FLT3, SLC39A7, HSP90AA1, and LEF1), which were associated with the prognosis of BC patients, were selected to establish our signature. Next, CIBERSORT algorithm was utilized to evaluate immune cell infiltration levels. We compare the response to immunotherapy using IMvigor 210 database, and also compared immune indicators in two risk groups via multiple methods. The biological function of IPMK was explored via in vitro verification. Finally, our results indicated that the signature was an independent prognostic indicator for BC patients with better efficiency than other reported signatures. The immune cell infiltration levels were higher, and the response to immunotherapy and chemotherapy was better in the low-risk groups. Besides, other immunotherapy-related factors, including TMB, TIDE, and expression of immune checkpoints were also increased in the low-risk group. Clinical sample validation showed that CD206 and IPMK in clinical samples were both up-regulated in the high-risk group. In vitro assay showed that IPMK promoted BC cell proliferation and migration, and also enhanced macrophage infiltration and M2 polarization. In summary, we successfully established the NRG signature, which could be used to evaluate BC prognosis and identify patients who will benefit from immunotherapy.

Identification of a Necroptosis-Related Prognostic Signature and Associated Regulatory Axis in Liver Hepatocellular Carcinoma

Background

Liver hepatocellular carcinoma (LIHC) ranks the sixth in global cancer incidence with poor prognosis. Necroptosis is a kind of regulated cell death and has been proved to be of significance in cancer occurrence and progression. However, few studies comprehensively discuss the potential applications of necroptosis-related genes (NRGs) in the prognostic evaluation and immunotherapy of LIHC.

Methods

The prognostic signature in the present study was built up using LASSO Cox regression analysis. Integrated bioinformatics tools were utilized to explore the potential mRNA-miRNA-lncRNA regulatory axis in LIHC. Furthermore, qRT-PCR method was used to verify the EZH2 expression in LIHC tissues. Furthermore, prognostic performance of EZH2 in LIHC was assessed by Kaplan-Meier method.

Results

A total of 14 NRGs were differentially expressed in LIHC tissues. The overall genetic mutation status of these NRGs in LIHC was also shown. NRGs were significantly correlated with programmed necrotic cell death, as well as Toll-like receptor signaling pathway in GO and KEGG pathway analysis. Kaplan-Meier analysis revealed that ALDH2, EZH2, NDRG2, PGAM5, RIPK1, and TRAF2 were related to the prognosis. A prognostic signature was constructed by these six genes and showed medium to high accuracy in the prediction of LIHC patients' prognosis. Further analysis revealed that NRGs were correlated with pathological stage, immune infiltration, and drug resistance in LIHC. Moreover, we identified a potential lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis in LIHC, which might affect the progression of LIHC. qRT-PCR suggested a higher mRNA level of EZH2 in LIHC tissues. And a poor overall survival rate was detected in LIHC patients with high EZH2 expression. Moreover, EZH2 expression and cancer stage were identified as the independent risk factors affecting LIHC patients' prognosis.

Conclusion

In the present study, we conducted comprehensive bioinformatic analyses and built up a necroptosis-related prognostic signature containing four genes (ALDH2, EZH2, NDRG2, and PGAM5) for patients with LIHC, and this prognostic signature showed a medium to high predictive accuracy. And our study also identified a lncRNA TUG1/miR-26b-5p/EZH2 regulatory axis, which might be of great significance in LIHC progression. In addition, based on the data from our center, the result of qRT-PCR and survival analysis showed a higher mRNA level of EZH2 in LIHC tissues and an unfavorable prognosis in high EZH2 expression group, respectively.

Computational Characterizing Necroptosis Reveals Implications for Immune Infiltration and Immunotherapy of Hepatocellular Carcinoma

Necroptosis is a programmed form of necrotic cell death in regulating cancer ontogenesis, progression, and tumor microenvironment (TME) and could drive tumor-infiltrating cells to release pro-inflammatory cytokines, incurring strong immune responses. Nowadays, there are few identified biomarkers applied in clinical immunotherapy, and it is increasingly recognized that high levels of tumor necroptosis could enhance the response to immunotherapy. However, comprehensive characterization of necroptosis associated with TME and immunotherapy in Hepatocellular carcinoma (HCC) remains unexplored. Here, we computationally characterized necroptosis landscape in HCC samples from TCGA and ICGA cohorts and stratified them into two necroptosis clusters (A or B) with significantly different characteristics in clinical prognosis, immune cell function, and TME-landscapes. Additionally, to further evaluate the necroptosis levels of each sample, we established a novel necroptosis-related gene score (NRGscore). We further investigated the TME, tumor mutational burden (TMB), clinical response to immunotherapy, and chemotherapeutic drug sensitivity of HCC subgroups stratified by the necroptosis landscapes. The NRGscore is robust and highly predictive of HCC clinical outcomes. Further analysis indicated that the high NRGscore group resembles the immune-inflamed phenotype while the low score group is analogous to the immune-exclusion or metabolism phenotype. Additionally, the high NRGscore group is more sensitive to immune checkpoint blockade-based immunotherapy, which was further validated using an external HCC cohort, metastatic melanoma cohort, and advanced urothelial cancer cohort. Besides, the NRGscore was demonstrated as a potential biomarker for chemotherapy, wherein the high NRGscore patients with more tumor stem cell composition could be more sensitive to Cisplatin, Doxorubicin, Paclitaxel-based chemotherapy, and Sorafenib therapy. Collectively, a comprehensive characterization of the necroptosis in HCC suggested its implications for predicting immune infiltration and response to immunotherapy of HCC, providing promising strategies for treatment.

Non-Canonical Programmed Cell Death in Colon Cancer

Simple Summary

Non-canonical PCD is an important player in colon cancer cell suicide. It influences colon cancer in many ways, such as through tumorigenesis, treatment, and prognosis. In this review, we present the mechanism, application, and prospect of different types of non-canonical PCD in colon cancer.

Abstract

Programmed cell death (PCD) is an evolutionarily conserved process of cell suicide that is regulated by various genes and the interaction of multiple signal pathways. Non-canonical programmed cell death (PCD) represents different signaling excluding apoptosis. Colon cancer is the third most incident and the fourth most mortal worldwide. Multiple factors such as alcohol, obesity, and genetic and epigenetic alternations contribute to the carcinogenesis of colon cancer. In recent years, emerging evidence has suggested that diverse types of non-canonical programmed cell death are involved in the initiation and development of colon cancer, including mitotic catastrophe, ferroptosis, pyroptosis, necroptosis, parthanatos, oxeiptosis, NETosis, PANoptosis, and entosis. In this review, we summarized the association of different types of non-canonical PCD with tumorigenesis, progression, prevention, treatments, and prognosis of colon cancer. In addition, the prospect of drug-resistant colon cancer therapy related to non-canonical PCD, and the interaction between different types of non-canonical PCD, was systemically reviewed.

A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma

Objective

Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration.

Methods

Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression.

Results

We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate.

Conclusion

We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses.

Identification and Verification of Necroptosis-Related Gene Signature With Prognosis and Tumor Immune Microenvironment in Ovarian Cancer

Ovarian cancer is the most lethal heterogeneous disease among gynecological tumors with a poor prognosis. Necroptosis, the most studied way of death in recent years, is different from apoptosis and pyroptosis. It is a kind of regulated programmed cell death and has been shown to be closely related to a variety of tumors. However, the expression and prognosis of necroptosis-related genes in ovarian cancer are still unclear. Our study therefore firstly identified the expression profiles of necroptosis-related genes in normal and ovarian cancer tissues. Next, based on differentially expressed necroptosis-related genes, we clustered ovarian cancer patients into two subtypes and performed survival analysis. Subsequently, we constructed a risk model consisting of 5 genes by LASSO regression analysis based on the differentially expressed genes in the two subtypes, and confirmed the strong prognostic ability of the model and its potential as an independent risk factor via survival analysis and independent risk factor analysis. Based on this risk model, patients were divided into high and low risk groups. By exploring differentially expressed genes, enrichment functions and tumor immune microenvironment in patients in high and low risk groups, the results showed that patients in the low risk group were significantly enriched in immune signaling pathways. Besides, immune cells content, immune function activity was significantly better than the high-risk group. Eventually, we also investigated the sensitivity of patients with different risk groups to ICB immunotherapy and chemotherapy drugs. In conclusion, the risk model could effectively predict the survival and prognosis of patients, and explore the tumor microenvironment status of ovarian cancer patients to a certain extent, and provide promising and novel molecular markers for clinical diagnosis, individualized treatment and immunotherapy of patients.

Ferroptosis at the crossroads of tumor-host interactions, metastasis, and therapy response

Ferroptosis is a form of regulated cell death characterized by the accumulation of lipid peroxides in an iron-dependent manner. Ferroptotic cell death is modulated by many metabolic pathways, such as pathways governing the metabolism of sugars, lipids, amino acids, and iron, as well as mitochondrial activity and redox homeostasis. Tumor metastasis and therapy resistance are the main obstacles to curing cancers. Because tumor cells usually exhibit higher iron dependence than normal cells, they may be more susceptible to ferroptosis despite being resistant to other forms of cell death. Moreover, recent evidence has suggested that ferroptosis is involved in tumor-host interactions, modulates the tumor microenvironment, and serves as an anti-metastatic mechanism. Thus, inducing ferroptosis in tumor cells has the potential to improve cancer treatment. Here, we review ferroptosis-regulating mechanisms and the roles of ferroptosis in malignant progression, including the tumor-host interactions, metastasis, and cancer therapy response.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC).

Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy.

Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them.

Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

A K+-sensitive AND-gate dual-mode probe for simultaneous tumor imaging and malignancy identification

Although molecular imaging probes have the potential to non-invasively diagnose a tumor, imaging probes that can detect a tumor and simultaneously identify tumor malignancy remain elusive. Here, we demonstrate a potassium ion (K⁺) sensitive dual-mode nanoprobe (KDMN) for non-invasive tumor imaging and malignancy identification, which operates via a cascaded ‘AND’ logic gate controlled by inputs of magnetic resonance imaging (MRI) and fluorescence imaging (FI) signals. We encapsulate commercial K⁺ indicators into the hollow cavities of magnetic mesoporous silica nanoparticles, which are subsequently coated with a K⁺-selective membrane that exclusively permits the passage of K⁺ while excluding other cations. The KDMN can readily accumulate in tumors and enhance the MRI contrast after systemic administration. Spatial information of the tumor lesion is thus accessible via MRI and forms the first layer of the ‘AND’ gate. Meanwhile, the KDMN selectively captures K⁺ and prevents interference from other cations, triggering a K⁺-activated FI signal as the second layer of the ‘AND’ gate in the case of a malignant tumor with a high extracellular K⁺ level. This dual-mode imaging approach effectively eliminates false positive or negative diagnostic results and allows for non-invasive imaging of tumor malignancy with high sensitivity and accuracy.

Identification of Bladder Cancer Subtypes Based on Necroptosis-Related Genes, Construction of a Prognostic Model

Background

Necroptosis is associated with the development of many tumors but in bladder cancer the tumor microenvironment (TME) and prognosis associated with necroptosis is unclear.

Methods

We classified patients into different necroptosis subtypes by the expression level of NRGS (necroptosis-related genes) and analyzed the relationship between necroptosis subtypes of bladder cancer and TME, then extracted differentially expressed genes (DEGS) of necroptosis subtypes, classified patients into different gene subtypes according to DEGS, and performed univariate COX analysis on DEGS to obtain prognosis-related DEGS. All patients included in the analysis were randomized into the Train and Test groups in a 1:1 ratio, and the prognostic model was obtained using the LASSO algorithm and multivariate COX analysis with the Train group as the sample, and external validation of the model was conducted using the GSE32894.

Results

Two necroptosis subtypes and three gene subtypes were obtained by clustering analysis and the prognosis-related DEGS was subjected to the LASSO algorithm and multivariate COX analysis to determine six predictors to construct the prognostic model using the formula: riskScore = CERCAM × 0.0035 + POLR1H × −0.0294 + KCNJ15 × −0.0172 + GSDMB × −0.0109 + EHBP1 × 0.0295 + TRIM38 × −0.0300. The results of the survival curve, roc curve, and risk curve proved the reliability of the prognostic model by validating the model with the test group and the results of the calibration chart of the Nomogram applicable to the clinic also showed its good accuracy. Necroptosis subtype A with high immune infiltration had a higher risk score than necroptosis subtype B, gene subtype B with low immune infiltration had a lower risk score than gene subtypes A and C, CSC index was negatively correlated with the risk score and drug sensitivity prediction showed that commonly used chemotherapeutic agents were highly sensitive to the high-risk group.

Conclusion

Our analysis of NRGS in bladder cancer reveals their potential role in TME, immunity, and prognosis. These findings may improve our understanding of necroptosis in bladder cancer and provide some reference for predicting prognosis and developing immunotherapies.

Non-apoptotic cell death-based cancer therapy: Molecular mechanism, pharmacological modulators, and nanomedicine

As an emerging cancer therapeutic target, non-apoptotic cell death such as ferroptosis, necroptosis and pyroptosis, etc., has revealed significant potential in cancer treatment for bypassing apoptosis to enhance the undermined therapeutic efficacy triggered by apoptosis resistance. A variety of anticancer drugs, synthesized compounds and natural products have been proven recently to induce non-apoptotic cell death and exhibit excellent anti-tumor effects. Moreover, the convergence of nanotechnology with functional materials and biomedicine science has provided tremendous opportunities to construct non-apoptotic cell death-based nanomedicine for innovative cancer therapy. Nanocarriers are not only employed in targeted delivery of non-apoptotic inducers, but also used as therapeutic components to induce non-apoptotic cell death to achieve efficient tumor treatment. This review first introduces the main characteristics, the mechanism and various pharmacological modulators of different non-apoptotic cell death forms, including ferroptosis, necroptosis, pyroptosis, autophagy, paraptosis, lysosomal-dependent cell death, and oncosis. Second, we comprehensively review the latest progresses of nanomedicine that induces various forms of non-apoptotic cell death and focus on the nanomedicine targeting different pathways and components. Furthermore, the combination therapies of non-apoptotic cell death with photothermal therapy, photodynamic therapy, immunotherapy and other modalities are summarized. Finally, the challenges and future perspectives in this regard are also discussed.

Identification and Verification of Necroptosis-Related Gene Signature and Associated Regulatory Axis in Breast Cancer

Background: Breast invasive carcinoma (BRCA) is the second leading cause of malignancy death among women. Necroptosis is a newly discovered mechanism of cell death involved in the progression and prognosis of cancer. The role of necroptosis-related genes (NRGs) in BRCA is still a mystery.

Methods: LASSO Cox regression analysis was performed to construct a prognostic necroptosis-related signature. A ceRNA was constructed to explore the potential lncRNA-miRNA-mRNA regulatory axis in BRCA.

Results: A total of 63 necroptosis-related genes were differentially expressed in BRCA. We also summarized the genetic mutation landscape of NRGs in BRCA. BRCA patients with low expression of BCL2 and LEF1, as well as high expression of PLK1 and BNIP3, had a poor OS, DSS, and DFS. A necroptosis-related prognostic signature with four genes (BCL2, LEF1, PLK1, and BNIP3) was constructed, and it could serve as a prognosis biomarker in BRCA, predicting the OS rate with medium to high accuracy. Moreover, the risk score was correlated with immune infiltration in BRCA. Further comprehensive analysis revealed that the expression of BCL2, LEF1, PLK1, and BNIP3 was correlated with tumor mutation burden, microsatellite instability, drug sensitivity, and pathology stage. Previous studies have been extensively studied. The roles of LEF1, PLK1, and BNIP3 in BRCA and BCL2 were selected for further analysis. We then constructed a ceRNA network, which identified an lncRNA LINC00665/miR-181c-5p/BCL2 regulatory axis for BRCA.

Conclusion: The bioinformatics method was performed to develop a prognostic necroptosis-related prognostic signature containing four genes (BCL2, LEF1, PLK1, and BNIP3) in BRCA. We also constructed a ceRNA network and identified an lncRNA LINC00665/miR-181c-5p/BCL2 regulatory axis for BRCA. Further in vivo and in vitro studies should be conducted to verify these results.

Autophagy and cancer treatment: four functional forms of autophagy and their therapeutic applications

Cancer is the leading cause of death worldwide. Drugs play a pivotal role in cancer treatment, but the complex biological processes of cancer cells seriously limit the efficacy of various anticancer drugs. Autophagy, a self-degradative system that maintains cellular homeostasis, universally operates under normal and stress conditions in cancer cells. The roles of autophagy in cancer treatment are still controversial because both stimulation and inhibition of autophagy have been reported to enhance the effects of anticancer drugs. Thus, the important question arises as to whether we should try to strengthen or suppress autophagy during cancer therapy. Currently, autophagy can be divided into four main forms according to its different functions during cancer treatment: cytoprotective (cell survival), cytotoxic (cell death), cytostatic (growth arrest), and nonprotective (no contribution to cell death or survival). In addition, various cell death modes, such as apoptosis, necrosis, ferroptosis, senescence, and mitotic catastrophe, all contribute to the anticancer effects of drugs. The interaction between autophagy and these cell death modes is complex and can lead to anticancer drugs having different or even completely opposite effects on treatment. Therefore, it is important to understand the underlying contexts in which autophagy inhibition or activation will be beneficial or detrimental. That is, appropriate therapeutic strategies should be adopted in light of the different functions of autophagy. This review provides an overview of recent insights into the evolving relationship between autophagy and cancer treatment.

Potential applications of N6 -methyladenosine modification in the prognosis and treatment of cancers via modulating apoptosis, autophagy, and ferroptosis

N⁶ -methyladenosine (m⁶ A) is one of the most abundant modifications determining the fate of RNA. Currently, m⁶ A modification is tightly connected with tumorigenesis and presents novel promise in clinical applications. Regulated cell death (RCD) is a programmed mechanism that plays a complicated role in malignant transition. Regarding the main forms of RCD, aberrant levels of m⁶ A modification have been detected during the progression of apoptosis, autophagy, ferroptosis, necroptosis, and pyroptosis in several diseases. However, few reviews have elucidated the correlation between m⁶ A-modified RCD and carcinogenesis. In this review, we summarize the regulators of m⁶ A methylation and their functions in carcinogenesis through an overview of m⁶ A-modified RCD. Additionally, we assume the potential role of m⁶ A modification regulators as novel biomarkers for chemotherapies and precision medicine. Furthermore, we review the controversies and conflicts in m⁶ A explorations and predict future orientations of m⁶ A-modified RCD for clinical applications. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

The emerging role of irisin in experimentally induced arthritis: a recent update involving HMGB1/MCP1/Chitotriosidase I–mediated necroptosis

Objectives

Methods

Results

Conclusions

Abbreviations

Organoantimony (III) Derivative induces necroptosis in human breast cancer MDA-MB-231 cells

PURPOSE

This study aimed to investigate the anticancer effect and the underlying mechanisms of organoantimony (III) fluoride on MDA-MB-231 human breast cancer cells.

METHODS

Five cancer and one normal cell line were treated with an organoantimony (III) compound 6-cyclohexyl-12-fluoro-5,6,7,12-tetrahydrodibenzo[c,f][1,5]azastibocine (denoted as C4). The cell viability was detected by MTT assay. Induction of cell death was determined by Hoechst 33342/PI staining and Annexin-V/PI staining. The effect of C4 on the necroptotic relative protein was determined by Western blot analysis.

RESULTS

Among the five cancer cell lines, C4 decreased the viability of MDA-MB-231, MCF-7 and A2780/cisR, and showed less toxicity to normal human embryonic kidney cells. In breast cancer cell line MDA-MB-231, the C4 treatment induced the percentage of necrotic cell death as well as LDH releasing in a time- and dose-dependent manner. Moreover, C4 could increase the expression of phosphorylated RIPK3 and MLKL proteins. Overall, the C4 treatment resulted in reduction of mitochondrial transmembrane potential and accumulation ROS in MDA-MB-231 cells.

CONCLUSION

C4-induced necroptosis could be ascribed to glutathione depletion and ROS elevation in MDA-MB-231 cells. Our findings illustrate that C4 is a potential necroptosis inducer for breast cancer treatment.

Emerging Mechanisms and Disease Implications of Ferroptosis: Potential Applications of Natural Products

Ferroptosis, a newly discovered form of regulatory cell death (RCD), has been demonstrated to be distinct from other types of RCD, such as apoptosis, necroptosis, and autophagy. Ferroptosis is characterized by iron-dependent lipid peroxidation and oxidative perturbation, and is inhibited by iron chelators and lipophilic antioxidants. This process is regulated by specific pathways and is implicated in diverse biological contexts, mainly including iron homeostasis, lipid metabolism, and glutathione metabolism. A large body of evidence suggests that ferroptosis is interrelated with various physiological and pathological processes, including tumor progression (neuro)degenerative diseases, and hepatic and renal failure. There is an urgent need for the discovery of novel effective ferroptosis-modulating compounds, even though some experimental reagents and approved clinical drugs have been well documented to have anti- or pro-ferroptotic properties. This review outlines recent advances in molecular mechanisms of the ferroptotic death process and discusses its multiple roles in diverse pathophysiological contexts. Furthermore, we summarize chemical compounds and natural products, that act as inducers or inhibitors of ferroptosis in the prevention and treatment of various diseases. Herein, it is particularly highlighted that natural products show promising prospects in ferroptosis-associated (adjuvant) therapy with unique advantages of having multiple components, multiple biotargets and slight side effects.

Necroptosis and tumor progression

Necroptosis, a form of programmed necrotic cell death, is a gatekeeper of host defense against certain pathogen invasions. The deregulation of necroptosis is also a key factor of many inflammatory diseases. Recent studies have revealed an important role of necroptosis in tumorigenesis and metastasis and imply the potential of targeting necroptosis as a novel cancer therapy. While its molecular mechanism has been well studied, details of the regulation and function of necroptosis of tumor cells in tumorigenesis and metastasis only began to emerge recently, and we discuss these herein.

Promyelocytic leukemia protein targets MK2 to promote cytotoxicity

Promyelocytic leukemia protein (PML) is a tumor suppressor possessing multiple modes of action, including induction of apoptosis. We unexpectedly find that PML promotes necroptosis in addition to apoptosis, with Pml^-/- macrophages being more resistant to TNF-mediated necroptosis than wild-type counterparts and PML-deficient mice displaying resistance to TNF-induced systemic inflammatory response syndrome. Reduced necroptosis in PML-deficient cells is associated with attenuated receptor-interacting protein kinase 1 (RIPK1) activation, as revealed by reduced RIPK1[S166] phosphorylation, and attenuated RIPK1-RIPK3-MLKL necrosome complex formation. We show that PML deficiency leads to enhanced TNF-induced MAPK-activated kinase 2 (MK2) activation and elevated RIPK1[S321] phosphorylation, which suppresses necrosome formation. MK2 inhibitor treatment or MK2 knockout abrogates resistance to cell death induction in PML-null cells and mice. PML binds MK2 and p38 MAPK, thereby inhibiting p38-MK2 interaction and MK2 activation. Moreover, PML participates in autocrine production of TNF induced by cellular inhibitors of apoptosis 1 (cIAP1)/cIAP2 degradation, since PML-knockout attenuates autocrine TNF. Thus, by targeting MK2 activation and autocrine TNF, PML promotes necroptosis and apoptosis, representing a novel tumor-suppressive activity for PML.

The role of necroptosis in disease and treatment

Necroptosis, a distinctive type of programmed cell death different from apoptosis or necrosis, triggered by a series of death receptors such as tumor necrosis factor receptor 1 (TNFR1), TNFR2, and Fas. In case that apoptosis process is blocked, necroptosis pathway is initiated with the activation of three key downstream mediators which are receptor-interacting serine/threonine protein kinase 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like protein (MLKL). The whole process eventually leads to destruction of the cell membrane integrity, swelling of organelles, and severe inflammation. Over the past decade, necroptosis has been found widely involved in life process of human beings and animals. In this review, we attempt to explore the therapeutic prospects of necroptosis regulators by describing its molecular mechanism and the role it played in pathological condition and tissue homeostasis, and to summarize the research and clinical applications of corresponding regulators including small molecule inhibitors, chemicals, Chinese herbal extracts, and biological agents in the treatment of various diseases.

RIPK3 signaling and its role in the pathogenesis of cancers

RIPK3 (receptor-interacting protein kinase 3) is a serine/threonine-protein kinase. As a key component of necrosomes, RIPK3 is an essential mediator of inflammatory factors (such as TNFα-tumor necrosis factor α) and infection-induced necroptosis, a programmed necrosis. In addition, RIPK3 signaling is also involved in the regulation of apoptosis, cytokine/chemokine production, mitochondrial metabolism, autophagy, and cell proliferation by interacting with and/or phosphorylating the critical regulators of the corresponding signaling pathways. Similar to apoptosis, RIPK3-signaling-mediated necroptosis is inactivated in most types of cancers, suggesting RIPK3 might play a critical suppressive role in the pathogenesis of cancers. However, in some inflammatory types of cancers, such as pancreatic cancers and colorectal cancers, RIPK3 signaling might promote cancer development by stimulating proliferation signaling in tumor cells and inducing an immunosuppressive response in the tumor environment. In this review, we summarize recent research progress in the regulators of RIPK3 signaling, and discuss the function of this pathway in the regulation of mixed lineage kinase domain-like (MLKL)-mediated necroptosis and MLKL-independent cellular behaviors. In addition, we deliberate the potential roles of RIPK3 signaling in the pathogenesis of different types of cancers and discuss the potential strategies for targeting this pathway in cancer therapy.